Fast Neural Machine Translation in C++
Version: v1.7.0 67124f8 2018-11-28 13:04:30 +0000
Marian toolkit provides the following tools:
Click on the tool name above for a list of command line options.
s2s
: An RNN-based encoder-decoder model with attention mechanism. The
architecture is equivalent to the
DL4MT or
Nematus models (Senrich et al.,
2017).transformer
: A model originally proposed by Google (Vaswani et al.,
2017) based solely on attention mechanisms.multi-s2s
: As s2s
, but uses two or more encoders allowing multi-source
neural machine translation.multi-transformer
: As transformer
, but uses multiple encoders.amun
: A model equivalent to Nematus models unless layer normalization is
used. Can be decoded with Amun as nematus model type.nematus
: A model type developed for decoding deep RNN-based encoder-decoder
models created by the Edinburgh MT group for WMT 2017 using Nematus toolkit.
Can be decoded with Amun as nematus2 model type.lm
: An RNN language model.lm-transformer
: An transformer-based language model.Clone a fresh copy from github:
git clone https://github.com/marian-nmt/marian
The project is a standard CMake out-of-source build:
cd marian
mkdir build
cd build
cmake ..
make -j4
The complete list of compilation options in the form of CMake flags can be
obtained by running cmake -LH -N
or cmake -LAH -N
from the build
directory after running cmake ..
first.
Assuming a fresh Ubuntu LTS installation with CUDA, the following packages need to be installed to compile with all features, including the web server, built-in SentencePiece and TCMalloc support:git cmake3 build-essential libboost-all-dev
Ubuntu 18.04 + CUDA 9.2 (defaults are gcc 7.3.0, Boost 1.65):
sudo apt-get install git cmake build-essential libboost-all-dev libprotobuf10 protobuf-compiler libprotobuf-dev openssl libssl-dev libgoogle-perftools-dev
Ubuntu 16.04 + CUDA 9.2 (gcc 5.4.0, Boost 1.58):
sudo apt-get install git cmake build-essential libboost-all-dev zlib1g-dev libprotobuf9v5 protobuf-compiler libprotobuf-dev openssl libssl-dev libgoogle-perftools-dev
Ubuntu 14.04 + CUDA 8.0 (gcc 4.8.4, Boost 1.54)
sudo apt-get install git cmake3 build-essential libboost-all-dev libprotobuf8 protobuf-compiler libprotobuf-dev openssl libssl-dev libgoogle-perftools-dev
Please see the GCC/CUDA compatibility table if you experience compilation issues with different versions of GCC and CUDA.
Marian will be compiled statically if the flag USE_STATIC_LIBS
is set:
cd build
cmake .. -DUSE_STATIC_LIBS=on
make -j4
Download, compile and install Boost:
wget https://dl.bintray.com/boostorg/release/1.67.0/source/boost_1_67_0.tar.gz
tar zxvf boost_1_67_0.tar.gz
cd boost_1_67_0
./bootstrap.sh
./b2 -j16 --prefix=$(pwd) --libdir=$(pwd)/lib64 --layout=system link=static install
If Boost can not be compiled on your machine because an error like this occurs:
boost error “none” is not a known value of feature <optimization>, you may
try adding --ignore-site-config
to the ./b2
command.
To compile Marian training framework with your custom Boost installation:
cd /path/to/marian-dev
mkdir build
cd build
cmake .. -DBOOST_ROOT=/path/to/boost_1_67_0
make -j4
Tested on Ubuntu 16.04.3 LTS.
Specify the path to your CUDA root directory via CMake:
cd /path/to/marian-dev
mkdir build
cd build
cmake .. -DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda-9.1
make -j4
Marian CPU version requires Intel MKL or OpenBLAS. Both are free, but MKL is not open-sourced. Intel MKL is strongly recommended as it is faster. On Ubuntu 16.04 it can be installed using the following steps:
wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS-2019.PUB
sudo sh -c 'echo deb https://apt.repos.intel.com/mkl all main > /etc/apt/sources.list.d/intel-mkl.list'
sudo apt-get update
sudo apt-get install intel-mkl-64bit-2019.4-XYZ
Where XYZ is the revision number.
A CPU build can be enabled by adding -DCOMPILE_CPU=on
to the CMake command.
Compilation with SentencePiece that is built-it in Marian v1.6.2+ can be
enabled by adding -DUSE_SENTENCEPIECE=on
to the CMake command and requires
the Protobuf library. On Ubuntu, you would need to install a couple of
packages:
# Ubuntu 14.04 LTS (Trusty Tahr):
sudo apt-get install libprotobuf8 protobuf-compiler libprotobuf-dev
# Ubuntu 16.04 LTS (Xenial Xerus):
sudo apt-get install libprotobuf9v5 protobuf-compiler libprotobuf-dev
# Ubuntu 17.10 (Artful Aardvark) and Later:
sudo apt-get install libprotobuf10 protobuf-compiler libprotobuf-dev
You may also compile Protobuf from source. For Ubuntu 16.04 LTS, version 2.6.1 (or possibly newer) works:
wget https://github.com/protocolbuffers/protobuf/releases/download/v2.6.1/protobuf-cpp-2.6.1.zip
unzip protobuf-cpp-2.6.1.zip
cd protobuf-2.6.1
./autogen.sh
./configure --prefix $(pwd)
make -j4
make install
and set the following CMake flags in Marian compilation:
mkdir build
cd build
cmake .. -DUSE_SENTENCEPIECE=on \
-DPROTOBUF_LIBRARY=/path/to/protobuf-2.6.1/lib/libprotobuf.so \
-DPROTOBUF_INCLUDE_DIR=/path/to/protobuf-2.6.1/include \
-DPROTOBUF_PROTOC_EXECUTABLE=/path/to/protobuf-2.6.1/bin/protoc
For more details see the documentation in the SentencePiece repo: https://github.com/marian-nmt/sentencepiece#c-from-source
For training NMT models, you want to use marian
command. Assuming corpus.en
and corpus.ro
are corresponding and preprocessed files of a English-Romanian
parallel corpus, the following command will create a Nematus-compatible neural
machine translation model:
./build/marian \
--train-sets corpus.en corpus.ro \
--vocabs vocab.en vocab.ro \
--model model.npz
Command options can be also specified in a configuration file in YAML format:
# config.yml
train-sets:
- corpus.en
- corpus.ro
vocabs:
- vocab.en
- vocab.ro
model: model.npz
which simplifies the command to:
./build/marian -c config.yml
Command-line options overwrite options stored in the configuration file.
For multi-GPU training you only need to specify the device ids of the GPUs you
want to use for training (this also works with most other binaries) as
--devices 0 1 2 3
for training on four GPUs. There is no automatic detection
of GPUs for now.
By default, this will use asynchronous SGD (or rather ADAM). For the deeper
models and the transformer model, we found async SGD to be unreliable and you
may want to use a synchronous SGD variant by setting --sync-sgd
.
For asynchronous SGD, the mini-batch size is used locally, i.e. --mini-batch
64
means 64 sentences per GPU worker.
For synchronous SGD, the mini-batch size is used globally and will be divided
across the number of workers. This means that for synchronous SGD the effective
mini-batch can be set N times larger for N GPUs. A mini-batch size of
--mini-batch 256
will mean a mini-batch of 64 per worker if four GPUs are
used. This choice makes sense when you realize that synchronous SGD is
essentially working like a single GPU training process with N times more memory.
Larger mini-batches in a synchronous setting result in quite stable training.
The choice of workspace memory, mini-batch size and max-length is quite involved and depends on the type of model, the available GPU memory, the number of GPUs, a number of other parameters like the chosen optimization algorithm, and the average or maximum sentence length in your training corpus (which you should know!).
The option --workspace
sets the size of the memory available for the forward
and backward step of the training procedure. This does not include model size
and optimizer parameters that are allocated outsize workspace. Hence you cannot
allocate all GPU memory to workspace. If you are not happy with default values
this is a trial and error process.
Setting --mini-batch 64 --max-length 100
will generate batches that contain
always 64 sentences (or less if the corpus is smaller) of up to a length of 100
tokens. Sentences longer than that are filtered out. Marian will grow workspace
memory if required and potentially exceed available memory, resulting in a
crash. Workspace memory is always rounded to multiples of 512 MB.
--mini-batch-fit
overrides the specified mini-batch size and automatically
chooses the largest mini-batch for a given sentence length that fits the
specified memory. When --mini-batch-fit
is set, memory requirements are
guaranteed to fit into the specified workspace. Choosing a too small workspace
will result in small mini-batches which can prohibit learning.
For shallow models I usually set the working memory to values between 3500 and
6000 (MB), e.g. --workspace 5500
and then use --mini-batch-fit
which
automatically tries to make the best use of the specified memory size,
mini-batch size and sentence length.
For very deep models, I first set all other parameters like --max-length 100
,
model type, depth etc. Next I use --mini-batch-fit
and try to max out
--workspace
until I get a crash due to insufficient memory. I then revert to
the last workspace size that did not crash. Since setting --mini-batch-fit
guarantees that memory will not grow during training due to batch-size this
should result in a stable training run and maximal batch size.
It is useful to monitor the performance of your model during training on
held-out data. Just provide --valid valid.src valid.trg
for that. By default
this provide sentence-wise normalized cross-entropy scores for the validation
set every 10,000 iterations. You can change the validation frequency to, say
5000, with --valid-freq 5000
and the display frequency to 500 with
--disp-freq 500
.
Attention: the validation set needs to have been preprocessed in exactly the same manner as your training data.
A minimum example of how to validate the model using cross-entropy and BLEU score:
./build/marian \
--train-sets corpus.en corpus.ro \
--vocabs vocab.en vocab.ro \
--model model.npz \
--valid-set dev.en dev.ro \
--valid-metrics cross-entropy translation \
--valid-script-path validate.sh
where validate.sh
is a bash script, which takes the file with output
translation of dev.en
as the first argument (i.e. $1
) and returns the BLEU
score, for example:
# validate.sh
./postprocess.sh < $1 > file.out 2>/dev/null
./moses-scripts/scripts/generic/multi-bleu-detok.perl file.ref < file.out 2>/dev/null \
| sed -r 's/BLEU = ([0-9.]+),.*/\1/'
cross-entropy
- computes the sentence-wise normalized cross-entropy score.ce-mean-words
- computes the mean word cross-entropy score.valid-script
- executes the script specified with --valid-script-path
.
The script is expected to return a score as a floating-point number.translation
- executes the script specified with --valid-script-path
passing the name of the file with translation of the source validation set as
the first argument (e.g. $1
in Bash script, sys.argv[1]
in Python, etc.).
The script is expected to return a score as a floating-point number.bleu
- computes BLEU score on raw validation sets. Those are usually
tokenized and BPE-segmented, so the score is overestimated, and should never
be used to report your BLEU scores in a research paper.bleu-detok
- computes BLEU score on postprocessed validation sets. Requires
SentencePiece and Marian v1.6.2+.Early stopping is a common technique for deciding when to stop training the model based on a heuristic involving a validation set.
By default we use early stopping with patience of 10, i.e. --early-stopping
10
. This means that training will finish if the first specified metric in
--valid-metrics
did not improve (stalled) for 10 consecutive validation
steps. Usually this will signal convergence or — if the scores get worse with
later validation steps — potential overfitting.
Marian has several regularization techniques implemented that help to prevent model overfitting, such as dropouts (Gal and Ghahramani, 2016), label smoothing (Vaswani et al. 2017), and exponential smoothing for network parameters.
Depending on the model type, Marian support multiple types of dropout. For
RNN-based models it supports the --dropout-rnn 0.2
(the numeric value of 0.2
is only provided as an example) option which uses variational dropout on all
RNN inputs and recursive states.
Options --dropout-src
and --dropout-trg
set the probability to drop out
entire source or target word positions, respectively. These dropouts are useful
for monolingual tasks.
For the transformer model the equivalent of --dropout-rnn 0.2
is
--transformer-dropout 0.2
. There are also two other dropouts for transformer
attention and transformer filter.
Manipulation of learning rate during the training may result in better convergence and higher-quality translations.
Marian supports various strategies for decaying learning rate
(--lr-decay-strategy
option). Decay factor can be specified with
--lr-decay
.
epoch
: learning rate will be decayed after each epoch starting from epoch
specified with --lr-decay-start
batches
: learning rate will be decayed every --lr-decay-freq
batches
starting after the batch specified with --lr-decay-start
stalled
: learning rate will be decayed every time when the first validation
metric does not improve for --lr-decay-start
consecutive validation stepsepoch+stalled
: learning rate will be decayed after the specified number of
epochs or stalled validation steps, whichever comes first. The option
--lr-decay-start
takes two numbers: for epochs and stalled validation
steps, respectivelybatches+stalled
: as epoch+stalled
, but the total number of batches is
taken into account instead of epochsOther learning rate schedules supported by Marian:
--lr-warmup
: learning rate will be increased linearly for the specific
number of first updates. The start value for learning rate warmup can be
specified with --lr-warmup-start-rate
.--lr-decay-inv-sqrt
: learning rate will be decreased at n / sqrt(no.
updates)
starting at n
-th updateData weighting is commonly used as a domain adaptation technique, which weights each data item according to its proximity to the in-domain data. Marian supports sentence and word-level data weighting strategies.
Data weighting requires providing a file with weights. In sentence weighting strategy, each line of that file contains a real-value weight:
./build/marian \
-t corpus.{en,de} -v vocab.{en,de} -m model.npz \
--data-weighting-type sentence --data-weighting weights.txt
To use word weighting you should choose --data-weighting-type word
, and each
line of the weight file should contain as many real-value weights as there are
words in the corresponding target training sentence.
Marian can handle custom embedding vectors trained with word2vec or another tool:
./build/marian \
-t corpus.{en,de} -v vocab.{en,de} -m model.npz \
--embedding-vectors vectors.{en,de} --dim-emb 400
Embedding vectors should be provided in a file in a format similar to the word2vec format, with word tokens replaced with words IDs from the relevant vocabulary.
Pre-trained vectors need to share the same vocabulary as your training data,
and ideally should contain vectors for <unk>
and </s>
tokens. The easiest
way to achieve this is to prepare the training data for word2vec w.r.t your
vocabularies using marian-dev/scripts/embeddings/prepare_corpus.py
. Vectors can be prepared or
trained w.r.t to vocabulary using marian-dev/scripts/embeddings/process_word2vec.py
.
Other options for managing embedding vectors:
--embedding-fix-src
fixes source embeddings in all encoders--embedding-fix-trg
fixes target embeddings in all decoders--embedding-normalization
normalizes vector values into [-1,1] rangeTraining with guided alignment may improve alignments produced by RNN models
(--type amun
or s2s
) and is mandatory to obtain useful word alignments from
Transformers (--type transformer
). Guided alignment training requires
providing a file with pre-calculated word alignments for the entire training
corpus, for example:
./build/marian \
-t corpus.{en,de} -v vocab.{en,de} -m model.npz \
--guided-alignment corpus.align
The file corpus.align from the example can be generated using the fast_align word aligner (please refer to their repository for installation instructions):
paste corpus.en corpus.de | sed 's/\t/ ||| /g' > corpus.en-de
fast_align/build/fast_align -vdo -i corpus.en-de > forward.align
fast_align/build/fast_align -vdor -i corpus.en-de > reverse.align
fast_align/build/atools -c grow-diag-final -i forward.align -j reverse.align > corpus.align
or a RNN model and marian-scorer
, for example:
./build/marian-scorer -m model.npz -v vocab.{en,de} -t corpus.en corpus.de > corpus.align
Marian has a few more options related to guided alignment training:
--guided-alignment-cost
- cost type for guided alignment--guided-alignment-weight
- weight for guided alignment cost--transformer-guided-alignment-layer
- number of layer to use for guided
alignment training; only for training transformer modelsMulti-node training requires an MPI installation with MPI_THREAD_MULTIPLE
set to
true
. A newer version (e.g. OpenMPI 2.X) is highly recommended due to intense
use of multi-threading.
Command-line options specific to multi-node training:
--multi-node
- enable multi-node.--devices
- set nodes and devices, e.g. 0: 0 1 1: 0
means that node 0 has
2 GPUs, with IDs 0 and 1, and node 1 has 1 GPU, with ID 0.--multi-node-overlap
- overlap communication with computations, default:
enabled.To start multi-node training, except compiling Marian with MPI, you need to create a host file and ensure that the nodes can ssh to each other without a password. Then you may use the command similar to:
mpirun -n 2 --hostfile hosts_mpi -tag-output \
./build/marian --devices 0:0 1 1:0 \
-m model.npz -t corpus.src corpus.trg -v vocab.src.yml vocab.trg.yml \
--multi-node --multi-node-overlap 0
where the host file hosts_mpi
contains on each line a host on which you want
to run Marian.
Note that multi-node currently only converges properly with gradient dropping, which requires layer normalization. Ideally, add the following line to your run script:
--layer-normalization --dropout-rnn 0.2 --dropout-src 0.1 --dropout-trg 0.1
Warning: The API described above refers to the experimental feature introduced in version 1.4.0. It is depreciated at least since version 1.7.0. The newest multi-node API is not documented yet.
All models trained with marian
can be decoded with marian-decoder
and
marian-server
command. Only models of type amun
and specific deep models of type
nematus
can be used with the amun
tool.
Currently, marian-decoder
supports only translation on GPUs. A CPU version
of Marian is planned.
Basic usage:
./build/marian-decoder -m model.npz -v vocab.en vocab.ro < input.txt
To generate n-best list with, say 10, best translations for each input
sentence, add --n-best
and --beam-size
10` to the list of command-line
arguments:
./build/marian-decoder -m model.npz -v vocab.en vocab.ro --beam-size 10 --n-best < input.txt
Models of different types and architectures can be ensembled as long as they use common vocabularies:
./build/marian-decoder \
--models model1.npz model2.npz model3.npz \
--weights 0.6 0.2 0.2 \
--vocabs vocab.en vocab.ro < input.txt
Weights are optional and set to 1.0 by default if omitted.
Batched translation generates translation for whole mini-batches and significantly increases translation speed (roughly by a factor of 10 or more). We recommend to use the following options to enable batched translation:
./marian-decoder -m model.npz -v vocab.src.yml vocab.trg.yml -b 6 --normalize 0.6 \
--mini-batch 64 --maxi-batch-sort src --maxi-batch 100 -w 2500
This does a number of things:
To give you an idea, how much faster batched translation is compared to sentence-by-sentence translation we have collected a few numbers. Below we have compiled the time it takes to translate the English-German WMT2013 test set with 3000 sentences using 4 Volta GPUs on AWS.
| System | Single | Batched |
|---|---|---|
| Nematus-style Shallow RNN | 82.7s | 4.3s |
| Nematus-style Deep RNN | 148.5s | 5.9s |
| Google Transformer | 201.9s | 19.2s |
marian-decoder
and marian-scorer
can produce attention output or word
alignments when the --alignment
option is used with one of the following
values:
soft
: Alignment weights for all words including EOS tokens. Sets of source
token weights for target tokens are separated by a whitespace, source token
weights are separated by a comma.
echo "now everyone knows" | ./marian-decoder -c config.yml --alignment soft
jetzt weiß jeder ||| 0.917065,0.0218936,0.0405725,0.0204688 0.00803049,0.0954254,0.853882,0.0426626 \
0.0294334,0.794184,0.00511072,0.171272 0.00743875,0.0147502,0.201069,0.776743
hard
or empty: Word alignments for each target token in the form of Moses
alignments, i.e. pairs of source and target tokens.
echo "now everyone knows" | ./marian-decoder -c config.yml --alignment
jetzt weiß jeder ||| 0-0 1-2 2-1 3-3
echo "now everyone knows" | ./marian-decoder -c config.yml --alignment 0.1
jetzt weiß jeder ||| 0-0 1-2 2-1 2-3 3-2 3-3
The transformer has basically 6x8 different alignment matrices, and in theory
none of these has to be very useful for word alignment purposes. We recommend
training model with guided alignments first (--guided-alignment
) so that the
model can learn word alignments in one of its heads.
With a lexical shortlist the output vocabulary is restricted to a small subset
of translation candidates, which can improve CPU-bound efficiency. A shortlist
file, say lex.s2t, can be passed to the decoder using the --shortlist
option, for example:
./build/marian-decoder -m model.npz -v vocab.en vocab.de \
--shortlist lex.s2t 100 75 < input.txt
The second and third arguments are optional, and mean that the output vocabulary will be restricted to the 100 most frequent target words and the 75 most probable translations for every source word in a batch.
Lexical shortlist files can be generated with marian-dev/scripts/shortlist/generate_shortlists.pl
, for example:
perl generate_shortlists.pl --bindir /path/to/bin -s corpus.en -t corpus.de
where corpus.en and corpus.de are preprocessed training data, and the bin
directory contains fast_align
and atools
from
fast_align and extract_lex
from
extract-lex.
The marian-server
command starts a web-socket server providing CPU and GPU
translation service that can be requested by a client program written in Python
or any other programming language. The server uses the same command-line
options as marian-decoder
. The only addition is --port
option, which
specifies the port number:
./build/marian-server --port 8080 -m model.npz -v vocab.en vocab.ro
An example client written in Python is marian-dev/scripts/server/client_example.py
:
./scripts/server/client_example.py -p 8080 < input.txt
Only specific types of models trained with Nematus, for example the Edinburgh WMT17
deep models can be decoded with
marian-decoder
. As such models do not include Marian-specific parameters,
all parameters related to the model architecture have to be set with
command-line options.
For example, for the de-en model this would be:
./build/marian-decoder \
--type nematus \
--models model/en-de/model.npz \
--vocabs model/en-de/vocab.en.json model/en-de/vocab.de.json \
--dim-vocabs 51100 74383 \
--enc-depth 1 \
--enc-cell-depth 4 \
--enc-type bidirectional \
--dec-depth 1 \
--dec-cell-base-depth 8 \
--dec-cell-high-depth 1 \
--dec-cell gru-nematus --enc-cell gru-nematus \
--tied-embeddings true \
--layer-normalization true
Alternatively, the parameters can be added into the model .npz file based on
the Nematus .json file using the script: marian-dev/scripts/contrib/inject_model_params.py
, e.g.:
python inject_model_params.py -m model.npz -j model.npz.json
Some models released by Edinburgh might require setting other parameters as
well, for instance --dim-emb 500
.
We do not recommend training models of type nematus
with Marian. It is much
more efficient to train s2s
models, which provide the same model architecture
(except layer normalization), more features, and faster training.
Amun is a translation tool for amun
and nematus
model types only and is now
available from the separate repository: amun/
. Translation
with Amun can be performed on GPU or CPU or both.
Basic usage:
./marian/build/amun -m model.npz -s vocab.en -t vocab.ro <<< "This is a test ."
The marian-scorer
tool is used for scoring (or re-scoring) parallel sentences
provided as plain texts in two corresponding files:
./build/marian-scorer -m model.npz -v vocab.{en,de} -t file.en file.de
A cross-entropy score for each sentence pair is returned by default.
N-best lists can be scored using the following command:
./build/marian-scorer -m model.npz -v vocab.{en,de} \
-t file.en.txt file.de.nbest --n-best --n-best-feature F0
which add a new score into the n-best list under the feature named F0.
The scorer can be used as a word aligner that generates word alignments for a pair of sentences:
./build/marian-scorer -m model.npz -v vocab.{en,de} \
-t file.en.txt file.de.txt --alignment
The feature works out-of-the-box for RNN models, while Transformer models need to be trained with guided alignments.
The scorer can report summarized score (cross-entropy or perplexity) for an
entire test set with option --summary
.
The code documentation for Marian toolkit is generated using Doxygen. The newest version can be generated locally with CMake:
mkdir -p build && cd build && cmake .. && make doc


| LIN | NSN | Item Name | PBIC | Type | DND | Qnty |
|---|---|---|---|---|---|---|
| WARLOCK SSVJ, ECM: SSVJ TMC DESI | V | TPE | N | 1 | ||
| POWER SUPPLY ASSEMBLY, TYX: BACK | 9 | INS | N | 1 | ||
| CAMERA, DIGITAL: POWERESHOT A520 | 9 | INS | N | 1 | ||
| DRILLING MACHINE: UPRIGHT FLOOR | 9 | INS | N | 1 | ||
| ARMT SS REMOTE OP | N | TPE | N | 1 | ||
| COM SE AN/UYK-128(V)1 | N | TPE | N | 7 | ||
| COM SE AN/UYK-128(V)3 | N | TPE | N | 1 | ||
| CAM NET SY AN/USQ-159 | 9 | INS | N | 3 | ||
| DISCHARGER GRSCL XM7 | N | TPE | N | 5 | ||
| DELTOID AND AXILLAR | N | TPE | N | 45 | ||
| DLTD AND AXLR UNV CAM | N | TPE | N | 100 | ||
| BODY VENTILATION SYSTEM III: GLO | N | TPE | N | 1 | ||
| BODY VENTILATION SYSTEM III: GLO | N | TPE | N | 2 | ||
| BODY VENTILATION SYSTEM III: GLO | N | TPE | N | 1 | ||
| INSERT,SMALL ARMS P | N | TPE | N | 248 | ||
| CARRIER ASSEMBLY,UN | N | TPE | N | 124 | ||
| RADIO COMMUNICATIONS SYSTEMS: IC | N | TPE | N | 31 | ||
| RADIO SET, AN/PRC 152 C: HARRIS | T | TPE | N | 2 | ||
| TELEVISION SET-(MDL# PT-52LCX65) | 9 | INS | N | 1 | ||
| DVD: PLAYER | 9 | INS | N | 1 | ||
| DETECTION SYSTEM: BOOMERANG | H | LTT | N | 2 | ||
| COUNTERMEASURES SET-(WARLOCK DUK | V | TPE | N | 12 | ||
| MIDES: NUZZER, MEDISM,GUARDIA AR | N | TPE | N | 1 | ||
| MINELAB MINE DETECTOR: F1A4 | N | TPE | N | 1 | ||
| TOUGHBOOK:CF-74 PANASONIC | 9 | INS | N | 1 | ||
| CROSSMATCH VERIFIER : 300 LC | 9 | INS | N | 1 | ||
| IRIS READER: 2.3 | 9 | INS | N | 1 | ||
| MULTI-MODAL BIOMETRIC COLLECTION | N | TPE | N | 2 | ||
| DISK DRIVE EXTERNAL: FD 353 | 9 | INS | N | 1 | ||
| HLMT CVC LRG LRG/LINR | H | LTT | N | 2 | ||
| HLMT CVC LRG LRG/LINR | N | TPE | N | 2 | ||
| MG 50 M2 HB FL GD/VEH | H | LTT | N | 7 | ||
| MACH GUN 5.56MM M249 | H | LTT | N | 14 | ||
| MT MACH GUN M197 | H | LTT | N | 2 | ||
| MT MACH GUN M197 | T | TPE | N | 2 | ||
| MT MAC GUN 40MM MK93 | H | LTT | N | 8 | ||
| MT MAC GUN MK64 MOD1 | T | TPE | N | 2 | ||
| MG GRENAD MK19 MODIII | H | LTT | N | 6 | ||
| MACH GUN 40MM: MK19 | T | TPE | N | 1 | ||
| MACH GUN 7.62MM M240B | H | LTT | N | 7 | ||
| MACH GUN 7.62MM M240B | T | TPE | N | 1 | ||
| PRESSURE WASHER: HONDA 240 | 9 | INS | N | 1 | ||
| JIG SAW: 255 | 9 | INS | N | 1 | ||
| DRILL KIT CORDLESS: DRILL KIT CO | 9 | INS | N | 1 | ||
| NAVIGATION SET,SATE | N | TPE | N | 11 | ||
| NAVIGATION SET: SAT | N | TPE | N | 5 | ||
| NAV SET SAT AN/PSN-13 | N | TPE | N | 2 | ||
| WARRIOR AID LITTER KIT WALK-(WAL | N | TPE | N | 7 | ||
| REC TR RT-1523A(C)/U | H | LTT | N | 19 | ||
| REC RT-1523B(C)/U | H | LTT | N | 19 | ||
| REC RT-1523B(C)/U | N | TPE | N | 1 | ||
| RADIO ST AN/VRC-89A | H | LTT | N | 15 | ||
| RADIO SET: AN/VRC-92A | H | LTT | N | 2 | ||
| RADIO SET AN/VRC-91D | N | TPE | N | 1 | ||
| REFRIGERATOR: IRAQI/WHITE | 9 | INS | N | 1 | ||
| AIR CONDITIONER-(CH620-2) | 9 | INS | N | 6 | ||
| TRK CARGO W/W M1078P1 | N | TPE | N | 1 | ||
| TRK UTIL HMMWV M1114 | N | TPE | N | 3 | ||
| TRK UTIL HMMWV M1114 | T | TPE | N | 13 | ||
| TRK UTIL HMMWV M1114 | T | TPE | N | 3 | ||
| TOWBAR MOTOR VEHICLE | H | LTT | N | 4 | ||
| TOWBAR MOTOR VEHICLE | N | TPE | N | 3 | ||
| TLR CGO 3/4 T M101A2 | T | TPE | N | 1 | ||
| MANNEQUIN: MALE EPITOME P/N EP1M | N | TPE | N | 2 | ||
| HMMWV M1114: W/ OFK5 | N | TPE | N | 1 | ||
| HMMWV M1114: W/ OFK5 | T | TPE | N | 2 | ||
| HMMWV M1114: OFK5 & OGPK | T | TPE | N | 1 | ||
| CARRIER, PERSONNEL: M113A3P1 | N | TPE | N | 1 | ||
| MINE ROLLER SYSTEM: LIGHTWEIGHT | N | TPE | N | 1 | ||
| MINE ROLLER SYSTEM: LIGHTWEIGHT | N | TPE | N | 2 | ||
| RAVEN, UNMANNED AERIAL VEH (UAV) | N | TPE | N | 1 | ||
| MULTIBAND INTER/INTRA TEAM RADIO | T | TPE | N | 1 | ||
| MOUNTZTRIPODZMACHIN | N | TPE | N | 2 |


discard this 1
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Shouldn't output this


Package br.com.armange.commons.thread
Class ThreadBuilder
- java.lang.Object
-
- br.com.armange.commons.thread.ThreadBuilder
-
@Deprecated(since="2.0.0", forRemoval=true) public class ThreadBuilder extends java.lang.Object
Deprecated, for removal: This API element is subject to removal in a future version.Consider to useThreadBuilder
Useful structure for thread creation in the following scenarios:- Timeout
The thread will be active only until the timeout be fired.
- Delay
The thread will be active only after the time delay be completed.
- Interval
The thread will be repeated after the time interval be completed.
- Exception handling
Handles of uncaught exceptions can be thrown and handled within threads.
The thread will wait a minimum delay (MINIMAL_REQUIRED_DELAY
) if and only if a (setAfterExecuteConsumer(BiConsumer)
) or a (setUncaughtExceptionConsumer(Consumer)
) is present.Example: final ExecutorService thread = ThreadBuilder .newBuilder() //New object to build a new thread. .setDelay(1000) //The thread will wait one second before start. .setTimeout(4000) //The thread will be canceled after four seconds. .setInterval(1000) //The thread will be repeated every second. .setAfterExecuteConsumer(afterExecuteConsumer) //A consumer will be called after thread execution. .setUncaughtExceptionConsumer(throwableConsumer) //A consumer will be called after any exception thrown. .setMayInterruptIfRunning(true) //The thread interruption/cancellation will not wait execution. .setSilentInterruption(true) //Interruption and Cancellation exceptions will not be thrown. .setExecution(anyRunnable) //The thread execution. .setThreadNameSupplier(() -> "Thread name") .setThreadPrioritySupplier(() -> 4) .start();
- Since:
- 2019-11-26 V1.0.0 (JDK 1.8)
- See Also:
ScheduledCaughtExecutorService
- Timeout
-
-
Field Summary
Fields Modifier and Type Field Description static long
MINIMAL_REQUIRED_DELAY
Deprecated, for removal: This API element is subject to removal in a future version.1000 milliseconds as a minimal delay.
-
Method Summary
All Methods Static Methods Instance Methods Concrete Methods Deprecated Methods Modifier and Type Method Description static ThreadBuilder
newBuilder()
Deprecated, for removal: This API element is subject to removal in a future version.static ThreadBuilder
newBuilder(int corePoolSize)
Deprecated, for removal: This API element is subject to removal in a future version.ThreadBuilder
setAfterExecuteConsumer(java.util.function.BiConsumer<java.lang.Runnable,java.lang.Throwable> afterExecuteConsumer)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the consumer to be called after thread execution.ThreadBuilder
setDelay(long milliseconds)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the delay value.ThreadBuilder
setExecution(java.lang.Runnable execution)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread execution.ThreadBuilder
setInterval(long milliseconds)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the repeating interval value.ThreadBuilder
setMayInterruptIfRunning(boolean flag)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread-interrupting-flag.ThreadBuilder
setSilentInterruption(boolean flag)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread-silent-interrupting-flag.ThreadBuilder
setThreadNameSupplier(java.util.function.Supplier<java.lang.String> threadNameSupplier)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread name supplier.The thread factory will consume this supplier to generate a thread name before return a new thread.ThreadBuilder
setThreadPrioritySupplier(java.util.function.IntSupplier threadPrioritySupplier)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread priority supplier.The thread factory will consume this supplier to generate a thread priority before return a new thread.ThreadBuilder
setTimeout(long milliseconds)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the timeout value.ThreadBuilder
setUncaughtExceptionConsumer(java.util.function.Consumer<java.lang.Throwable> uncaughtExceptionConsumer)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the consumer to be called after exception throwing.ExecutorResult
start()
Deprecated, for removal: This API element is subject to removal in a future version.Starts the thread.ThreadBuilder
startAndBuildOther()
Deprecated, for removal: This API element is subject to removal in a future version.Starts the thread.
-
-
-
Field Detail
-
MINIMAL_REQUIRED_DELAY
public static final long MINIMAL_REQUIRED_DELAY
Deprecated, for removal: This API element is subject to removal in a future version.1000 milliseconds as a minimal delay.- See Also:
- Constant Field Values
-
-
Method Detail
-
newBuilder
public static ThreadBuilder newBuilder()
Deprecated, for removal: This API element is subject to removal in a future version.- Returns:
- a new object to perform a thread creation.
-
newBuilder
public static ThreadBuilder newBuilder(int corePoolSize)
Deprecated, for removal: This API element is subject to removal in a future version.- Parameters:
corePoolSize
- theScheduledCaughtExecutorService
pool size.- Returns:
- a new object to perform a thread creation.
- See Also:
ScheduledCaughtExecutorService(int)
-
setTimeout
public ThreadBuilder setTimeout(long milliseconds)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the timeout value.- Parameters:
milliseconds
- the timeout value in milliseconds.- Returns:
- the current thread builder.
-
setDelay
public ThreadBuilder setDelay(long milliseconds)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the delay value.- Parameters:
milliseconds
- the delay value in milliseconds.- Returns:
- the current thread builder.
-
setInterval
public ThreadBuilder setInterval(long milliseconds)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the repeating interval value.- Parameters:
milliseconds
- the repeating interval value in milliseconds.- Returns:
- the current thread builder.
-
setAfterExecuteConsumer
public ThreadBuilder setAfterExecuteConsumer(java.util.function.BiConsumer<java.lang.Runnable,java.lang.Throwable> afterExecuteConsumer)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the consumer to be called after thread execution.- Parameters:
afterExecuteConsumer
- the consumer to be called after thread execution.- Returns:
- the current thread builder.
- See Also:
ScheduledCaughtExecutorService.afterExecute(Runnable, Throwable)
-
setUncaughtExceptionConsumer
public ThreadBuilder setUncaughtExceptionConsumer(java.util.function.Consumer<java.lang.Throwable> uncaughtExceptionConsumer)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the consumer to be called after exception throwing. This consumer will be called as a first after-executes consumer.- Parameters:
uncaughtExceptionConsumer
- the consumer to be called after exception throwing.- Returns:
- the current thread builder.
-
setThreadNameSupplier
public ThreadBuilder setThreadNameSupplier(java.util.function.Supplier<java.lang.String> threadNameSupplier)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread name supplier.The thread factory will consume this supplier to generate a thread name before return a new thread.- Parameters:
threadNameSupplier
- the thread name supplier.- Returns:
- the current thread builder.
-
setThreadPrioritySupplier
public ThreadBuilder setThreadPrioritySupplier(java.util.function.IntSupplier threadPrioritySupplier)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread priority supplier.The thread factory will consume this supplier to generate a thread priority before return a new thread.- Parameters:
threadPrioritySupplier
- the thread priority supplier.- Returns:
- the current thread builder.
-
setExecution
public ThreadBuilder setExecution(java.lang.Runnable execution)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread execution.- Parameters:
execution
- the thread execution(Runnable
)- Returns:
- the current thread builder.
-
setMayInterruptIfRunning
public ThreadBuilder setMayInterruptIfRunning(boolean flag)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread-interrupting-flag.- Parameters:
flag
- true if the thread executing this task should be interrupted; otherwise, in-progress tasks are allowed to complete.- Returns:
- the current thread builder.
- See Also:
Future.cancel(boolean)
-
setSilentInterruption
public ThreadBuilder setSilentInterruption(boolean flag)
Deprecated, for removal: This API element is subject to removal in a future version.Sets the thread-silent-interrupting-flag.- Parameters:
flag
- true if the Interruption/Cancellation exceptions should be ignored.- Returns:
- the current thread builder.
- See Also:
Future.cancel(boolean)
,CancellationException
,InterruptedException
-
start
public ExecutorResult start()
Deprecated, for removal: This API element is subject to removal in a future version.Starts the thread.- Returns:
- the executor's result after starting thread.
- See Also:
ExecutorResult
-
startAndBuildOther
public ThreadBuilder startAndBuildOther()
Deprecated, for removal: This API element is subject to removal in a future version.Starts the thread.- Returns:
- the current thread builder to prepare another thread.
-
-


PRICE : IN SINGAPORE DOLLARS & SUBJECT TO {% if not taxes: %} 0 {%else%} {{taxes[0].rate}}{%endif%}% GST
DELIVERY TERM : 2 WEEKVALIDITY OF QUOTE : 4 WEEKS FROM DATE OF QUOTATION
PAYMENT TERM : 30 DAYS
We look forward to receiving your purchase order soon.


BOth the SAT and the ACT value conciseness. You must seek out and delete anything that could be considered unnexessary, irrelevant, or redundant. Because we commonly speak redundantly, you cannot expect unnecessary, irrelevant, or redundant language to sound incorrect. Therefore, you should rely on the structure of the question to tip you off to look for such language.
Redundant: It was chilly and cold outside.
Correct: It was cold outside.
Although chilly and cold are not perfect synonyms, they are close enough in meaning that they are redundant when used together. Choose the more accurate of the two. Usually you will only be given the choice of one or the other so you will not have to decide which one is more accurate.
Redundant: The police cop arrested the burglar.
Correct: The cop arrested the burglar.

 Never use an adjective to modify a noun that already by definition presupposes that adjective.
Redundant: Large in size
Correct: Large
Large by definition refers to size.
Redundant: There was a blizzard outside, so he stayed in the house because of the snow.
Correct: There was a blizzard outside, so he stayed in the house.
Correct: He stayed in the house because of the snow.
There is no need to state why he stayed in the houre more that once.
Sometimes language isn't redundant, but it just isn't needed. Words that add no meaning should always be eliminated.
Unnecessary: He was tired for the particular reason that he had been working all day.
Correct: He was tired because he had been working all day.
"For the particular reason that" contains no more meaning that the single word "because."
Unnecessary: There must have been some sort of mistake
Correct: There must have been a mistake.
"Some sort of" adds no meaning to the sentence.
Irrelevant information is not directly on topic. All information must help to advance the logical flow of the paragraph, provide a relevant example, or clarify something that might otherwise be unclear. It must be more than "kind of related" to the focus of the paragraph. Many times, information that is only "kind of related," is really going off on a tangent, digressing from the focus of the paragraph. Any such information must be deleted.
Irrelevant: Grizzly bears are dangerous animals, so people who hike in grizzly bear territory should take certain precautions. Other dangerous animals include lions and poisonous snakes. In grizzly bear territory, people should hike with bear spray and make plenty of noise to prevent startling a bear.
Correct: Grizzly bears are dangerous animals, so people who hike in grizzly bear territory should take certain precautions. In grizzly bear territory, people should hike with bears spray or a large gun and make plenty of noise to prevent startling a bear.
Although the sentence about other dangerous animals is kind of related to the first sentence, it is irrelevant to the focus of the paragraph as a whole, since it merely goes off a tangent.
On the ACT, there are two structures you should look out for. If you are given the option to "OMIT the underlined portion" or "DELETE the underlined portion," you must consider whether there is any chance the underlined portion could be considered unnecessary, irrelevant, or redundant. If so, choose to omit or delete. Remember that the omitor delete option is correct about half the time it is offered. Of course, that also means it is incorrect about half the time, so be carefully not to overplay this tendency. The second structure you should look out for is when one answer choice is shorter than the others. Consider what is not included in that answer choice that is included in the others. If this information could be considered unnecessary, irrelevant, or redundant, choose the shorter option.


Speeding. Nervousness. Loss of desire, partly ability, to speak. Sensitivity to sound. Confusion, increasing fear. It all happens very suddenly. Great fear, shaking, things look & seem the same yet totally different. Senses heightened & perspective badly altered. Sense of rushing out badly. Terror, sudden heat & sweating. Inability to move or speak. Unwillingness to look around - world too strange - very frightening. Sudden vomiting - easy, not unpleasant, but not supressable. Feel better, but world different, not like acid where hallucinations seperable from reality, things more part of your own thoughts. Few more minutes of fear, decreasing. Then - +/- 6hrs of starnge, gentle joy & affection. Hug trees! Even pain decreases gradually. Feel slightly strange (quite lethargic) for +/- 24hrs. 1st time Ecstacy user.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Singular select with custom content:
One
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Nine
Ten
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Twelve
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Fourteen
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Sixteen
Seventeen
Eighteen
Nineteen
Twenty
Twenty-one
Twenty-two
Twenty-three
Twenty-four
Twenty-five
Twenty-six
Twenty-seven
Twenty-eight
Twenty-nine
Thirty
Singular select with dimmer:
One
Two
Singular select without search:
One
Two
Multi select with custom content:
One
Two
Three
Four
Five
Six
Seven
Eight
Nine
Ten
Eleven
Twelve
Thirteen
Fourteen
Multi select with custom content and without search:
One
Two
Three
Four
Five
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Eight
Nine
Ten
Eleven
Twelve
Thirteen
Fourteen
Multi select with custom content and keep open:
One
Two
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Nine
Ten
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Thirteen
Fourteen


Source code for schedulers.schedulerAuto
# Copyright 2014 Modelling, Simulation and Design Lab (MSDL) at
# McGill University and the University of Antwerp (http://msdl.cs.mcgill.ca/)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Automaticly polymorphic scheduler. It will automatically adapt to your scheduling requests, though at a slight overhead due to the indirection and statistics gathering. If you know what is your optimal scheduler, please choose this one. If the access pattern varies throughout the simulation, this scheduler is perfect for you. It will choose between the HeapSet and Minimal List scheduler.
.. warning:: Barely tested, certainly not with distribution and relocation!!! **Use with caution!!!***
"""
from pypdevs.schedulers.schedulerHS import SchedulerHS
from pypdevs.schedulers.schedulerML import SchedulerML
[docs]class SchedulerAuto(object):
"""
The polymorphic scheduler class
"""
[docs] def __init__(self, models, epsilon, total_models):
"""
Constructor
:param models: the models to schedule
:param epsilon: the allowed deviation
"""
self.epsilon = epsilon
self.models = list(models)
self.total_models = total_models
self.scheduler_type = SchedulerHS
self.subscheduler = SchedulerHS(self.models, self.epsilon, total_models)
# Statistics
self.total_schedules = 0
self.colliding_schedules = 0
[docs] def swapSchedulerTo(self, scheduler):
"""
Swap the current subscheduler to the provided one. If the scheduler is already in use, no change happens.
:param scheduler: the *class* to switch to
"""
if scheduler == self.scheduler_type:
return
self.scheduler_type = scheduler
self.subscheduler = scheduler(self.models, self.epsilon, self.total_models)
[docs] def schedule(self, model):
"""
Schedule a model
:param model: the model to schedule
"""
self.models.append(model)
return self.subscheduler.schedule(model)
[docs] def unschedule(self, model):
"""
Unschedule a model
:param model: the mode to unschedule
"""
self.models.remove(model)
return self.subscheduler.unschedule(model)
[docs] def massReschedule(self, reschedule_set):
"""
Reschedule all models
:param reschedule_set: the set of models to reschedule
"""
self.colliding_schedules += len(reschedule_set)
self.total_schedules += 1
if self.total_schedules > 100:
if self.colliding_schedules > 15.0 * len(self.models):
# This means that 5/100 of the models is scheduled in every iteration
self.swapSchedulerTo(SchedulerML)
elif self.colliding_schedules < 500:
self.swapSchedulerTo(SchedulerHS)
self.colliding_schedules = 0
self.total_schedules = 0
return self.subscheduler.massReschedule(reschedule_set)
[docs] def readFirst(self):
"""
Fetch the time of the first model
:returns: (time, age) -- time of the first scheduled model
"""
return self.subscheduler.readFirst()
[docs] def getImminent(self, time):
"""
Returns the imminent models for the provided time
:param time: time to check for
"""
return self.subscheduler.getImminent(time)


Make this wrap at the end of the line12345678: white-space
This is long enough a wrap at the next line text ...


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--- layout: default title: About description: ---
My Reps is a tool for looking up who your elected representatives are across the United States. Based on your address, we can find all the federal, state, county and local officials who represent you in government.
Knowing who these representatives are and contacting their offices directly is the most effective way to change how our government works.
Have an issue you care about? Find your rep and tell them!
For more, read our launch blog post: We find your reps so you don't have to.
We built this tool to be open source and easy to repurpose. Feel free to copy and reuse the My Reps codebase and customize the messaging and content for your issue.
Instructions on how to get started are in the GitHub repository. For an example, see My Reps by the Participatory Budgeting Project and the open source code for it.
Information on elected officials comes from the Google Civic Information API, which aggregates data across the United States on elected officials in federal, state, county and local government offices.
Sometimes data is outdated or missing. If you notice an issue with the data, please report it to Google.
DataMade built this representative lookup tool for the Participatory Budgeting Project to help them advocate for more participatory budgeting in local government. Participatory budgeting is a process of democratic deliberation and decision-making, and a type of participatory democracy, in which ordinary people decide how to allocate part of a municipal or public budget.
To get an elected official to take up a particular government policy like this, one of the most effective strategies is to empower their constituents to directly advocate for it.
We built an initial version of this tool for the Participatory Budgeting Project, called My Reps, and used it as a basis to make this more general version of it.
The team is:
All the code for this site is open source. It was built with Jekyll, Bootstrap and Javascript.
Technologies used:
All the code for this project is up on GitHub and under the open source MIT license.
Found a bug? Report it on our issue tracker!
Have a suggestion? Want to set customize this tool for your organization? Contact DataMade at info@datamade.us


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3 references to IsAllScope
System.Management.Automation (3)
engine\SessionStateScope.cs (1)
1757
if (variable.
IsAllScope
)
engine\ShellVariable.cs (2)
185
if (
IsAllScope
)
361
if (
IsAllScope
&& ((newOptions & ScopedItemOptions.AllScope) == 0))


| < Day Day Up > |
|
[SYMBOL]
[A]
[B]
[C]
[D]
[E]
[F]
[G]
[H]
[I]
[J]
[K]
[L]
[M]
[N]
[O]
[P]
[Q]
[R]
[S]
[T]
[U]
[V]
[W]
[X]
[Y]
[Z]
tar command, unpacking source TCP (Transmission Control Protocol), port numbers tcp_outgoing_address directive 2nd tcp_outgoing_tos directive 2nd tcp_recv_bufsize directive technical support terminal window cache.log messages testing and test_reachability directive netdb and testing access controls terminal window and time ACL type timestamp field access.log referer.log 2nd store.log timestamps traffic shaping [See Delay Pools] transfer size field, access.log transparent caching [See HTTP interception] transport layer, application layer and |
| < Day Day Up > |


PRINTED
Monday, October 01, 2007
††††††††††††††† We slept in and sure enjoyed being just the two of us.† It was 12 noon when we got away.† Our camp host was upset with us that we hadnít got out by 11 AM.† As we were going through Springdale Mae saw some flowers that she wanted to have a picture of.† I stopped and let her out to take the picture but she was out of power.† I went over to the Service station and bought her some new batteries.† While I was gone Mae went over to the church house and set on the lawn.† When I came out she called for me to come over by her.† There was a large Tarantula that she had almost set on.† It left the church lawn and crossed the sidewalk and then started across the road.† We were afraid that it would get ran over so I got a stick and chased it across the road.† I had to stop a couple of cars until it moved out of the road.† One driver thanked me for protecting the Tarantula.† We did take some pictures of it.† We also got the pictures of the flower that Mae wanted.† We traveled on down the road and stopped at a Cafť where we ate a late breakfast.† We traveled on home, stopping for gas and dinner.† I have been in quite a lot of pain through out the day.† I am not sure what I have eaten that has set it off.† It is always a worry to me when I have this affect me this way, for I wonder if it will yet come back on me and Doctor Wardenís predictions may yet happen.† It was 9 PM when we got home.† We stopped for gas and had a detour through Kanosh as the freeway was closed because of a dust storm and a wreck.† We also had three stops for natural gas and we stopped for dinner.† It started raining just after we got home.† We got most things brought in and put away.† Mae put things away and unpacked the suit cases.† I caught my journal up to date before we went to bed.† It has bee a long day and I am very tired.
Tuesday, October 02, 2007
††††††††††††††† I got up about 4:30 AM for the bathroom and then went back to bed.† We got up a little later and took showers.† Mae did some washing, unpacking and repacking to go down to Mike and Beckyís tomorrow.† I put the tent trailer away and brought the boat up closer to the house so we could use the vacuum to clean it our.† It was really a mess and took a lot of work to get it clean.† I went over to Grant and Stacyís and checked out some problems they are having with their house.† I had called Sandi about the work she wants done but she was not able to get the information back to me until this evening.† after I left Grantís I was going to Scottís to paint their patio cover but Mishelle called and they are not sure yet if they will paint or stain.† Mae cooked a very nice dinner of fish, baked potatoes and squash.† When I couldnít do Scott and Mishelleís I came back and with Markís help finished cleaning and waxing the boat.† Bob made a delicious apple pie and bought me some yogurt to go on top of it.† It was very good.† I filled out this entry before we went to bed.
Wednesday, October 03, 2007
††††††††††††††† I didnít sleep very well last night so was slow getting started.† Mae was up early and finished packing.† She wanted to leave early as she is concerned about the morning traffic.†  Bob prepared breakfast for me.† I worked most of the morning on Sandiís project.† I put the boat away and talked with Grant about his needs.† He wants me to do the needed repairs.† I went to Home Depot and priced out Sandiís material list.† I worked on Randyís estimate for a hydronic heat system for his new home.† After getting some super I watch a show and quite for the day.† I called Mae and told her I wouldnít be down this evening.
Thursday, October 04, 2007
††††††††††††††† I got ready, took my trailer and went out to Tooele.† I left my trailer in Sandiís garage and went to Home Depot where I purchased the items for Sandi and Nickís project.† I took the purchase up to their new home, put a new electrical cord on Sandiís clothes dryer and then drove to American Fork.† Mae and I went to the football game between American Fork High and Lehi High 9th grade.† David played on American Forks team and really did well.† It was special to watch him play.† American Fork won 26 to 6.† Mae had dinner ready when we got home.† David and I went to Orem where I filled my pickup with Natural gas.† We also stopped at the store and purchased a few items for Mae.† I spent a little time on my computer to fill my journal with todayís data.
Friday, October 05, 2007
††††††††††††††† I drove out to Tooele and worked about 6 hours getting the shelves and storage room painted.† It took over four gallons of paint of paint to paint the one room.† That is how much it took to paint all the walls in our apartment.† I guess there is a lot of surface area with all the shelving.† I got home fairly early and we relaxed and watched a show on TV.†
Saturday, October 06, 2007
††††††††††††††† I got up about 7 AM and Mae got up about 8 AM.† Mae went to work preparing to go out to Sandiís.† I went to the store and while I was there I saw some flowers so bought them for Mae.† That made her happy.† We went out about 4 PM.† We had watched the two session of General Conference and I thought that Brad, Nick, and Logan would be going to General Priesthood meeting with me.† However just Logan went with me and he was late getting ready.† When we got back to the house Sandi and Mon were busy putting things away from the move and wanted every thing ready for tomorrow.† It was after mid-night before they quite so we didnít have time to play any games.
Sunday, October 07, 2007
††††††††††††††† I got up at 7 AM but Mae and the rest didnít get up until after 8 AM so we had to hurry to have breakfast in time to watch General Conference.† All of our family, except for Shellieís family, came out after the morning session.† We had a nice lunch and part of us watched the afternoon session of conference. †I donít know if Conference is a good time to get together as some wants to watch Conference and others wants to just visit.† I donít have the answer for it.† It was a good day and we got home about 7:30 PM.† I worked on my journal trying to get it up to date.† After listening to President Iringís talk about his journal, I really wonder if my journal is worth much.† It was after 9:30 PM when we went to bed.
Monday, October 08, 2007
††††††††††††††† I got up at 5:30 AM to go to Sandi and Nickís.† It was a little after 8 AM when I arrived.† I worked most of the morning getting electrical wiring pulled.† At noon I stopped for lunch and then started sheet rocking but only got two sheets hung as I had to do some framing around a drain pipe.† Sandi called and said that the company wants to move the hot tub on the 11th.†† I went to Grantsville and checked out the hot tub.† It is too heavy for me to move so I got the electrical disconnected.† I helped move a couple of items before starting home.† It was after 8 PM when I got home.† Bob had done some work on his plumbing last week while we were gone.†  Mae went in the bedroom and stepped into water.† Bob tried to vacuum it up but his vacuum isnít strong enough.† Mae called me and I brought my shop vacuum home.† I drew out another gallon and a half and then inserted the hose under the carpet and turned it to blow.† I will let it blow all night and see if it is dry tomorrow.† I worked on statements for a while and then filled in my journal.† I will now take a shower and go to bed.† It is almost 11 PM.† I am tired.
Tuesday, October 09, 2007
††††††††††††††† We slept in as I am not going to Sandi and Nickís today.† After eating breakfast I went over to Irven and Sandyís where I assembled a shower stool and a handicap toilet seat.† I was going to put up a railing but Sandy couldnít decide where or how she wanted it.† We will wait until Irven gets home.† Bryce came over just as I was going to leave so we visited for a while.† I went over to the Layton Shoe store to get my boots that I had taken in to have repaired.† They werenít ready so I will come back again.† I went over to Durkís and bought some parts for Sandi and Nickís job.† This afternoon Mae and I went over to the shoe store again and looked at new work boots.† The fellow that is working there wasnít much help so we came home.† They have opened the round-a-bout on the corner for use now.† I watched a show on TV and Mae worked on her book club preparations.
Wednesday, October 10, 2007
††††††††††††††† I got up at 4:30 AM and left before 7 AM for Sandiís.† I went to Grantsville and finished removing the electrical from the hot tub.† I worked the rest of the day getting a new power line ran for the hot tub.† It required running 80 feet of new line from the main power box to a box close to the hot tub.† I had to work with live power as you are to be a licensed electrician in order to hook up to a main panel.† I also ran some more lines inside and mounted some outlet boxes.† I left for home about 4 PM.† Mae had dinner ready when I got home so I ate, showered and went Home Teaching with Bob.† Mae also went Visiting Teaching this evening.† I tried to work on my books and my journal this evening.† It was 11:30 PM when we got to bed.
Thursday, October 11, 2007
††††††††††††††† We didnít get up very early as it was late when we went to bed last night.† Mae and I talked it over and we decided that I would stay at Sandi and Nickís tonight as Mae will have her Book Club tonight.† It was 9:15 AM when I got out to Sandiís.† I worked until after 5 PM when I quite.† I showered and changed and went to the Grantsville girlís volleyball game with Nick.† Sandi was already there as she is keeping score for the game.† When we got home I called and visited with Mae.† Sandi then help me with my book keeping form changing it to an Excel form.† We got most of the form working now.† I filled in my journal and we went to bed.
Friday, October 12, 2007
††††††††††††††† I got up at 6 AM and studied for a while before going in to get something for breakfast.† I couldnít find anything so I went to Mc Donaldís and go something.† I went on down to Home Depot and got some sheetrock corners.† I finished sheet rocking the room which took some adjusting the window seals as they were not even.† I but on the corners and then after eating some lunch I put the first coat of mud on.† It was 4:30 PM by the time I finished and got ready to go home.† Due to heavy traffic it was 6:15 PM when I got home.† I showered and then Mae got me some dinner.† Carroll had problems last night with her heart so Bob called the Doctor who had him take her into the E. R. area of the hospital.† I guess she will be there for a couple of days.† David and Shauna brought the children for us to tend while they went out to eat with some of their friends.† It was about 10 PM when they came back.† We went to bed about 11 PM.
Saturday, October 13, 2007
††††††††††††††† We slept in this morning and got up after 8 AM.† I slept most of the night in the recliner but didnít sleep very well.† After getting something for breakfast I helped Mark for a couple of hours.† I then went over to Scott and Mishelleís and left the blinds that we were going to use† in front of our windows.† They also had the money they owed for there patio cover.† I stopped at the Layton Shoe Store and got my cowboy boots that they repaired for me.† I then went to Irven and Sandyís to install some handicap bars but they didnít want then installed.† I check there water distiller and found that it was full of water and did not turn on until it called for more water.† As soon as I removed some of the water it worked just fine.† We went to Maddockís in Brigham City this evening and took Irven and Sandy with us. †When we came back to their place and played games for a while.† We stopped at the grocery store for a few minutes and got a couple of items we need.† I filled out my journal before we went to bed.
Sunday, October 14, 2007
††††††††††††††† Mae and I slept in and then we lay in bed and watched the Tabernacle Choir performance and also a replay of General Conference.† I especially enjoyed President Hinckleyís testimony and I felt that if for no other reason than President Hinckley has lived such a perfect life that if he can say that he knows the Church is true and that he can bear solemn testimony that Jesus is the Christ and Savior of the world, then I can also know if for no other reason that these things are true.† I do however have my own personal testimony that I have had bourn by the Holy Ghost.† We attended the block program and was very tired when we finished with nursery.† We had 18 children there today and it was something else.† Even though I was tired I enjoyed the testimonyís that were given today.† I sure love the Gospel and what understanding of life and the purpose of it that the Gospel gives me.† I just hope that some how David and Jeff can have their understanding opened and the Spirit return to them.† After meetings we got some dinner and then Mae went with me to take a cake over to the Caseís as tomorrow will be their Wedding Anniversary.† We then went to the McKay Dee hospital where we visited with Jeanenne and Carroll.† Both are doing some better although the Doctors donít know what is causing Carrollís problems.† After returning home I took the garbage out to the street.† I called Grant and we decided that I will go out to Sandiís tomorrow and when I return I will bring my tools back and repair Grantís roof.† I will then go back to finish Sandiís project.† It was late when we got to bed.
Monday, October 15, 2007
††††††††††††††† Almost everyday I seem to relate my scripture study with my two boys.† Alma was concerned for his son Alma and because of his faith and prayers the Lord sent an Angle to awaken Alma the younger to his wrong doings.† I pray continually that the Lord will soften the hearts of Jeff and David.† I worked at Sandiís today getting the second coat of mud applied, installed a expansion tank on the water line and got the electrical done in the north basement bedrooms.† I also worked on the hot tub getting it so we can change the position of the tub.† It was almost 7 PM when I got home but I also stopped and filled up with gas.† Mae had dinner ready and after eating I filled in this entry.† David called me today and said that he had talked to the Doctors that are treating Carroll.† He said the two Doctors are very complaint in their profession.† They told David that they do not think that it is Carrollís heart that is the problem.† She is loosing blood and she has some kind of infection in the blood.† They are doing test to try to find the problem.† Right now they are just guessing from the symptoms, but it may be cancer.† We read from the Priesthood / Relief Society manual some of the lessons we have missed as we are in the nursery and miss Priesthood and Relief Society.† The on lesson and a comment Mae made left me with some concerns.
Tuesday, October 16, 2007
††††††††††††††† I didnít sleep very well and woke quite depressed.† That feeling stayed with me all day.† We went up to Jennieís which took a couple of hours and $250 less in out account.† I tried to get with Grant to check out the needs for his project but Stacy wasnít home.† He said that she would be there in about an hour so I went over.† She never did come so most of my time was wasted.† I am a little concerned about doing this job but I donít know how to get out of it.† I rented a carpet cleaner from Universal rental and cleaned the carpet in the spare bedroom.† Mae cooked some very good stew for dinner.† We invited Mark to eat with us.† Brother and Sister Thompson came for a home teaching visit.† As mark was Mark was downstairs we had him stay.† Bob came home from the hospital so we invited him down also.† I worked on the computer for a while getting my mileage charts up to date and set up a statement for Grant and Stacy.† I moved some of the things that were in the hallway so we could get in our †bedroom and then entered this journal entry.† I also wrote of an experience I remembered from my youth and put it in with the some of my other memories.† We were late getting to bed.
Wednesday, October 17, 2007
††††††††††††††† I got up just after 6 AM but Mae hadnít slept very well so I let her sleep until 7 am. †She got up and got my breakfast and a lunch for me to take.† It is raining this morning so I went back out to Sandiís.† it was 10 AM when I got there but I worked until 5:30 PM.† I left my trailer there as it looks like we will have rain again tomorrow.† It was almost 8 PM when I got home.† Mae had the freezer cleaned out but hadnít got the food put back into it when I got home.† She had gone over to have her Temple
Recommend updated by the Stake Presidency.† She had dinner ready and after eating we put the guest bedroom back together.†
Thursday, October 18, 2007
††††††††††††††† Mae went out to Sandiís with me.† We took our clothes so we could stay over.† This way I wonít have to drive back tonight. As Mae and I were looking out the back window we saw two fauns running in the back area.† They were just having a great time running and jumping.† Then the doe came running straight to them and suddenly both fauns stopped.† They came back to where the mother was and followed her back into the cover.† It was such a fun experience, watching the doe train her fauns.† I worked until about 6 PM when we ate dinner that Mae had prepared.† We then went to Sandi and Nickís old home in Grantsville and helped them move more of their things.† They have moved the hard way by trying to take a load at a time.† After returning we went down to the Maverick where we bought some frozen yogurts.† We played a game of marbles with Sandi and Nick before going to bed.† Sandi and Mae won.
Friday, October 19, 2007
††††††††††††††† I got up about 6 AM but then went back to bed for a little while with Mae.† I started working and then Mae fixed some breakfast.† I finished the sheet rocking and then worked on hanging doors and trimming.† We left to come home shortly after 3 PM.† it was just about 5 AM before we got to Jeff and Gailís.† They had invited us to spend the evening with them.† After eating a nice dinner we played some games for a little while.† We were very tired when we came home so soon came to bed.
Saturday, October 20, 2007
††††††††††††††† We slept in and then when we got up I cut Maeís hair and she cut my hair.† It was cold and raining outside so we mainly relaxed.† This afternoon we picked up Brice and Deanna and went up to Morgan.† Georgia and Rick met us at Kim and Jeanenneís where we enjoyed the evening eating, playing games and visiting.† It was almost 11 PM when we got home.† Mae and I stayed up and watched a John Wayne movie, the Island in the Sky.† It was very late when we went to bed.
Sunday, October 21, 2007
††††††††††††††† We slept in until 8 AM.† We mainly relaxed this morning.† We watched the Tabernacle Choir Broadcast and then watched a BYU Idaho devotional in which Elder Oaks and his wife spoke.† After that we watched a short movie of a young man that gets laid of his job.† Discouraged as he drives home he sees an older lady with a flat tire.† He stops and helps her but wonít except any money for his services.† The lady thanks him and drives on.† The next scene shows the Lady go into a restraint to get something to eat.† The waitress that helps her is very pregnant and tired but service with pleasantness.† As the lady finishes a bowl of soup and the waitress asks if she can get anything else the lady just asks for the bill.† The lady hands her a $100 dollar bill and while the waitress goes to get change the lady writes a note that says the change if for the baby and have a good night.† The waitress returns to find the note and the lady gone.† The next scene shows the waitress returning home late and her husband is asleep on the couch.† When he turns over it is the young man that got laid off.† It was just a neat show.† We next watched a rerun of a talk that President Hinckley gave while President Benson was still alive.† We attended our block program and served in the nursery for our last time as we were told that we will be released from the nursery today.† At one point I looked over and saw Mae with three children in her arms as she set on the floor playing with several children.† We had 19 children between 18 months and three years old in the nursery today.† This has been a good experience but a hard and tiring one.† We had a simple lunch this afternoon but a very good one.† Mae is a wonderful wife, home maker and sweetheart.† Julie Ann and Phillip came by to visit for a few minutes.† They are up here on an anniversary / business trip and took the opertunity for Phil to meet some of Julie Annís family.† We also listened to part of the Republican Presidential debate.†
Monday, October 22, 2007
††††††††††††††† I went out to Sandiís again today.† The traffic on the freeway came to almost a stop right after I got on the road.† It took me almost an hour to get to Kaysville.† I still made it to Sandi & Nickís by 8 AM.† it took me most of the day to get the three rooms prepped for painting.† I decided to stay over and work late tonight so I could get the primer coat on before I quite tonight.† It was after 7:30 PM when I quite.† I took a shower in order to get the paint off my face and hair.† Sandi and Nick had bought large chef salads for dinner tonight.† Eating so late I know that I could not lay down to sleep so I slept in the recliner tonight.
Tuesday, October 23, 2007
††††††††††††††† I got started at 7 AM and painted the craft room.† I had enough paint to do the small play room so I called Sandi and ask if she wanted it done.† She did so I painted that and then started on the desk.† I got the main framing done and the top almost cut out.† I was able to make some adjustments to my door jig and am able to rout out the holes for the electrical boxes.† I cleaned my paint pump and filled it with a protector.† I was able to mount the desk frame to the walls.† I wanted to put the desk top in the frame but at 5:30 PM I quite and came home. Mae was talking to Jeff on the phone when I got home.† He is sure having a struggle with life and I donít know how to help him.† I am sure that getting back to building his testimony about the church and a purpose for life would shore help him.† I think he needs professional help also.† Mae has been very busy while I have been gone.† She has put up grape juice, done the washing, cleaned out the storage room and just worked to hard.† Bob had made some noodles with chicken so that is what we ate for dinner tonight.† We watch a show on TV.† I caught my computer files and journal up to date.† Mae is going to go out Sandiís with me and we will plan on staying tomorrow evening.† I hope I can complete it by then.† I am sure tired tonight.† I will take a shower, shave and go to bed.
Wednesday, October 24, 2007
††††††††††††††† I got up at 4:30 AM and started getting ready to go out to Sandiís.† Mae got up an prepared breakfast.† By the time I ate I was so tired that I changed my mind and just went back to bed.† We woke about 9:30 AM and relaxed in bed a while longer.† We decided to attend the Temple and so went into town.† I took the boat into Petersonís and left it there to winterize for me.† we then stopped at Best Buy and bought some ink cartridges for our printer.† We then went to the Red Wing store and I bought a pair of work boots.† It was after 3 PM when we got to the Temple.† I havenít felt the best today but we enjoyed the Temple session.† We went out to eat at the Sizzler and then got gas in the truck before coming on home.† We visited with Bob as we donít know just what the situation is with Carroll.† Bob had me help give Carroll a blessing before we left today. †She is really having difficulty moving at all.† Carroll is to large for Bob to carry her so we are not sure just what or how to help.† Mae went up this evening and mopped the bathroom floor and cleaned the bathroom.† I called Sandi and told her I would be out in the morning but I am not sure if Mae will go with me or not.†
Thursday, October 25, 2007
††††††††††††††† Mae came with me to Sandi and Nickís.† We left at 6:45 AM but had heavy traffic and so it was 8:30 AM when we got here.† I went right to work.† Mae worked on her scrap books most of the day.† I took a nap after eating lunch so it was a hour lunch break.† JaNae came over this afternoon with her children.† Mae had dinner ready when Sandi and Nick came home.† It was 6 PM when I quite this evening.† I didnít get as much done as I wanted to.† Brad and JaNae left the children here while they went out for dinner.† When Brad and JaNae came back they stayed and visited until after 10 PM.†
Friday, October 26, 2007
††††††††††††††† I woke early thinking about the work I have to complete.† I worked on the table most of the morning and then worked on the suspended ceiling.† My stud finder quite working so I had Mae go to Home Depot and buy me a new one.† It took me a while to figure out the square of the room.†† I got the grid all hung but still have the rivets to add and some more suspension wires to add.† I was installing some support bracing and nailed a water line with my nail gun.† I was in luck and had parts in my trailer to repair the water line.† Sandi and Nick were going out to eat dinner so we decided to stay home and just have something light.† Mae helped Sandi and Nick with some pictures and time soon went.† It was late when we went to eat at Apple Beeís.† It was very good but I will have to sleep in the recliner after eating that late.†
Saturday, October 27, 2007
††††††††††††††† I slept most of the night in the recliner.† We slept in but I started work at 8 AM.† Mae called me when she had breakfast ready.† I worked all day getting the room finished.† Mae came down and helped me several times.† After we finished with the work we then had to clean up and load all my tools.† That took us over an hour.† Sandi cooked some home pizza for dinner and they were really good.† It was 10 PM when we got home.† We took showers before going to bed and then watched a movie on DVD.
Sunday, October 28, 2007
††††††††††††††† I got up early for a few minutes and then went back to bed.† I slept until after 8 AM.† I received a call from Brother Francom our ward executive secretary asking me to meet with the Bishop at 12:30 PM.† I got breakfast ready this morning while Mae started dinner.† Mae went with me to visit with Bishop Smith.† I was called to be a Ward Family History Specialist.† That will be a new calling for me that I have need of training in.† It was nice to attend Priesthood Meeting and Sunday School.† When we got home from meetings I help Mae get ready for dinner.† Scott, Mishelle, Kylan and Ashley came over for dinner.† After dinner Kylan and I throw the foot ball for a few minutes.† Scott, Kylan, Mae and I played a game of marbles.† It was nice to visit with Scott and Mishelle and the children for a while this afternoon.† I am sure tired this evening.
Monday, October 29, 2007
††††††††††††††† I got up about 7 AM.† Bob and Carroll wanted to leave about 8:30 AM so that they could be the first at the clinic and not have to wait so long as they did before.† I helped get Carroll to the car and that was a job.†  I ate breakfast and then started to build a temporary ramp when Bob called and said they were on their way home.† I had to have Carroll wait while I finished building the ramp but it worked and there would have been on way to have got her into the house with out the ramp.† Mae went up and mopped the kitchen floor and did some cleaning while they were gone.† I explained to Bob and Carroll that Carrollís leg may get some better but they couldnít expect it to be better than it was before this last problem occurred.† Even then it was hard for Carroll to clime up the stairs.† Therefore I suggested that we build a permanent ramp in the garage.† It will mean that we have to clean out some of the things in the garage and move others but it can be done.† I guess we will do that after I get Grantís and Scottís jobs done.† I went over to Scottís and replaced the GFI outlet in the bathroom as it had burned out.† It was 1 PM when I got to Home Depot to get some materials for Grantís.† I worked until 5 PM finding the areas that leaked in the roof.† It looks like the problem all comes from the valley not being shingled right.† After I got home and cleaned up we went over to Jeff and Gailís and had FHE with they and Scottís family.† We had dinner when we first got there.† After eating, the full time Elders came and presented the lesson. †It was an enjoyable evening.† After returning home I worked on my books and filled in this entry.† It was 11 PM before we got to bed.
Tuesday, October 30, 2007
††††††††††††††† I got up but about 7 I went back to bed for a while.† It was 9 AM when I left for work.† Aunt Beth called me as I was driving out the driveway.† She has a water problem.† The neighbor on the 3rd floor left the water running in the bath tub and it flooded the 2nd and 1st floors.† I got fans and put under Bethís carpet but the neighbor on the 2nd floor was at work.† It was 10:30 when I got to Grantís.† I installed more metal flashing under the shingles in the valley and stopped the leakage in that area.† I removed the swamp cooler vent pipe and filled in the hole.† I removed shingles in that area and installed ice and snow sheeting over that complete area.† I will now re-shingle that area of the roof.† I quite and came home at 4 PM.† I showered and changed then Bib and I went Home Teaching to the Fallisís.† When we returned home Mae and I ate dinner.† I worked on my computer for a while.† Mae went with me as I went to check on Aunt Beth.† I had to set the fans in another area that just got wet today.† I checked with the owner on the 2nd level and she has quite a bit of sheetrock damage.† Aunt Bethís is not that bad.† I recommended that they contact a restoration company for bids on both units.† Also they could make contact with an attorney as to legal responsibility.† It was after 9 PM when we got back home.† We soon went to bed.
Wednesday, October 31, 2007
††††††††††††††† I got up at 6 AM but Mae was not in bed.† That means the she didnít sleep very good.† She came in from the front room where she had slept in the recliner.† I had her go back to bed and sleep longer.† She had already prepared my lunch and had breakfast set out for me.† She is sure special.† I disconnected my trailer and left it in the street in front of the house.† Bob parked his car in front of the trailer so no one could hook on to the trailer while I am gone.† I went over to Aunt Bethís and got the fans and returned them to the rental company.† Aunt Beth gave me a check for the rental amount.† I didnít charge her for my time.† I went to Rooferís Supply in Ogden where I purchased the shingles for Grantís job.† I then went to Riverdale and picked up my boat from Petersonís Marineís.† I had them winterize it and change the oil.† I next stopped at The Home Depot and purchased a 10 foot step ladder so I could get to the ceiling in Grantís home.† It cost me $200.00 but if I were to fall that would be cheap.† I worked at Grantís and got the two areas of ceiling repaired.† When I was repairing the ceiling in the small bedroom I bumped the ceiling fan and it fell.† Grant had installed that fan and hadnít put proper bracing to carry the load.† I added bracing to the ceiling so that it will hold the fan this time.† After putting the first coat of mud on the patches I carried the three bundles of shingles up to the roof so I can start shingling tomorrow.† It was 5 PM when I left the job.† I was very tired when I got home.† Mae prepared dinner while I showered and shaved.† After eating we watched two shows on cable TV.† We didnít have anyone come Trick-or-Treating this evening but that is normal for where we live.† I filled out some invoices and my journal before we went to bed.† Mae was updating her Birthday Calendar and commented that the month has sure gone by fast.†


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