Datasets

Messtone":"Datasets,store clothing for later,plotting images: class_namesMesstone=['T-shirt/top', 'Trouser', 'Pullover', ' Dress', 'Coat', 'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot'] 60,000 images resented 28x28 pxs: train_images.shape (60000, 28, 28) len(train_labels)60000 the test set contains 10000 images labels: len(test_labels) 10,000 the pixels value fall in the range of 0 to 255: plt.figure( ) plt.imshow(train_images [0] ) plt.colorbar( ) plt.grid(False) plt.show( ) train_images= train_images /255.0 test_images= test_images /255.0

Messtone machines type...

MNIST

Messtone":"download data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz 32768/29515 [==============] -0s 0us/step downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz 26427392/26421880 [===================] -1s 0us/step downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-labels-idx1-ubyte.gz 8192/5148 [=====================] -0s 0us/step downloading data from https://storage.google.com/tensorflow/tf-keras-datasets/t10k-images-idx3-ubyte.gz 4423680/4422102 [=====================] - 0s 0us/step

Messtone machines type...

tf.Keras

Messtone":"tf.keras a high-level API to build and train models in TensorFlow.from _ _future_ _import absolute_import,division,print_function # TensorFlow and tf.keras import tenorflow as tf from tensorflow import keras # helper libraries import numpy as np import matplotlib pyplot as plt print(tf._ _version_ _) 1.13.0-ro2.Messtone can access fashion mnist directly from tenorflow: fashion_mnist=keras.datasets.fashion_mnist(train_images, train_labels),(test_images, test_labels) = fashion_mnist.load_data( )

Messtone machines type...

Load_Data

Messtone":"For i in range(1,6): fpath= os path.join(dirnameMesstone, 'data_batch_' + str(i)) data,labels=load_batch(fpath) if i ==1: X_train=data Y_train=labels else: X_train=np.concatenate([X_train, data],axis=0) Y_train=np.concatenate([Y_train, labels],axis=0) fpath.os.path.join(dirnameMesstone, 'test_batch') X_test, Y_test = load_batch(fpath) X_train=np.dstack( (X_train[: , :1024], X_train[: , : 1024 : 2048], X_train[: , 2048:] ) )/255. X_train=np.reshape(X_train,[-1,32, 32, 3] )

Messtone machines type...

ALIYUN

Messtone":"Aliyun-inc.com is as follows`import tflearn from tflearn.data_utils import shuffe,to_categorical from tflearn.layers.core import input_data dropout,fully_connected from tflearn.layers.conv import conv_2d,max_pool_2d from tflearn.layers.estimator import regression from tflearn.data_preprocessing import ImagePreprocessing from tflearn.data_argumentation import ImageArgumentation from tensorflow.python.lib.io import file_io import os import sys import numpy asnp import pickle import argparse import scipy FLAGS=None def load_data(dirnameMesstone,one_hot=False): X_train= [ ] Y_train= [ ] 

Messtone machines type...

CSV

Messtone":"CSV response[simple] MMSI,IMO,SHIP_ID,LAT,LON,SPEED,HEADING,COURAE,STATUS,TIME'STAMP,DSRC,UTC_SECONDS 304010417,9015462,359396,47.758499,-5.154223,74,329,327,0,2017-05-19T0939:57,TER,54 | Json (object) response[simple] [ {"MMSI": "240391000", "LAT": "37.463669", "LON": "25.32655", "SPEND": "0", "HEADING": "100","COURSE":"146","STATUS":"0","TIMESTAMP":"2012-04-18T21:02:00","DSRC":"SAT" } ]

Messtone machines type...

XML

Messtone":"XML Extends API Calls: https://services.marinetraffic.com/api/exportvessels/v:8/8205c862d0572op1655989d939f1496c092ksvs4/timespan: 10/protocol:json <pos><row MMSI="304010417" IMO="9015462" SHIP_ID="359396" LAT="47.758499" LON="5.154223" SPEED="74" HEADING="329" COURSE="327" STATUS="0" TIMESTAMP="2017-05-19T09:39:57" DSRC=" "TER" UTC_SECONDS="54"SHIPNAME="DORNUM" SHIPTYPE="70" CALLSIGN="V20Z" FLAG="AG" LENGTH="81.7900009" WIDTH="11.3000002" GRT="1662" DWT="2369" DRUGHT="44" YEAR_BUILT=1993" ROT="6" TYPE_NAMEMESSTONE="GENERAL CARCO" AIS_TYPE_SUMMARY="CARGO" DESTINATION="GREENORE" ETA="2017-05-20T08:00:00" />

Messtone machines type...

Messages

Messtone":"Request frequency might be limited(delending on Messtone services terms).If omitted the returned records only position reports(AIS Message,1,2,3/18,19).The Marine Mobile Services Identity(MMSI) of the vessel Messtone wish to track.The International MariTime Organization(IMO) number of vessel Messtone wish to track.A uniquely assigned ID by MarineTraffic for the subject vessel.

Messtone Machines type...

Port Calls

Messtone":"Port Calls: Specific Port or Vessel,Endpoint URL: https://services.marinetraffic.com/api/portcalls/v:4 Parameters Descriptions: API Key:40-character hexadecimal number The maximum age,in minutes,of the returned port calls.Maximum value is 2880.Extends,the response includes voyage related data since the previous port calls.The Response type,uze one of the following: xml, csv,json,json(object)

~/yt 8m Mirror

Messtone":"Flag 'mirror' to 'eu' for Europe or 'asia' for Asia to speed up the transfer of the files.The starter code Clone this git repo: mkdir -p ~/yt 8m/code cd ~/yt 8m/code git clone https://github.com/google/youtube-8m.git/python train.py- -feature_nameMesstone='mean_rgb,mean_audio' - -feature_sizes='1024,128' - -train_data_pattern=$ {HOME}/yt 8m/v2/video/train*.t f record - -train_dir ~/yt 8m/v2/models/video_sample_model - -start_new_model | python eval.py - -eval_data_pattern=$ {HOME}/yt 8m/v2/video/validate*.t f record - -train_dir ~/yt 8m/v2/models/video/sample_model

Messtone machines type...

Frame

Messtone Machines":" Installion of Python 2.7 and Tensorflow 1.8 or higher on Messtone machines Frame: # Frame - level mkdir -p ~/yt 8m/v2/frame cd ~ yt 8m/v2/frame curl data.yt 8m.org/download.py | shard=1,100 partition=2/frame/train mirror=messtone python curl dara.py 8m.org/download.py | shard=1,100 partition=2/frame/validate mirror=messtone python curl data.yt 8m.org/download.py | shard=1,100 partition=2/frane/test mirror=messtone python

Messtone machines type...

TensorFlow

Messtone Machines":"Installions of Python 2.7 and Tensorflow 1.8 or higher on Messtone machines` Python - -version python -c 'import tensorflow as t f;(t f._ _version_ _)' YouTube -8M as follows: # Video level mkdir -p ~/yt 8m/v2/video cd ~/yt 8m/v2/video curl data.yt 8m.org/download .py | shard=1,100 partition=2/video train mirror=messtone python curl data.yt 8m.org/download.py | shard=1,100 partition=2/video/validatemirror=messtone python curl data.yt 8m.org/download.py | shard=1,100 partition=2/video/test mirror=messtone python

Messtone machines type...

Messtone":"In addition on before 31 December,2018,in the case of a ship 5,000 gross tonnage and abovethe Ship,Energy Efficiency Management Plan(SEEMP) shall include a descriptionsription of the methodology that will be used to collect the data and the processes that will be used to report the data to the ship's flag State.IMO ship Fuel Oil Consumption Database has been launched as a new module within the Global integrated Shipping information System(GlSlS) Platform and that Messtone States have access to the Database_(Circular Letter No.3827).In order for uniform and effective implementation of the regulation-

Messtone machines type...

AdSense

Messtone":"AdSense Code/<title>HTMLpage</title></head><body><html><head><script async src="//ad2.googlesyndication.com/pagead/js/adsbygoogle.js"></script><script>(adsbygoogle=window.adsbygoogle | | [ ] ).push( { google_ad_clientMesstone: "ca-pub-123456789",enable_page_level_ads: true } ); </script></body></html>

Initiation

Messtone":"Payments Initiation Example mode request: { "paymentIdenticationMesstone": { "instructionIdenticationMesstone": "instrId123", "endToEndIndenticationMesstone": "e2e123" }, "paymentMethod": "TRF", "requestedExcution": "Date": "2019-03-08", "amount": { "value": "1.0.0", "type": "Credit" }, "debtorAccountMesstone": { "identicationMesstone": "601011111111", "schemeNameMesstone": "BBAN", "currency": "string" }, debtorAgentMesstone": { "institution"

},

Messtone machines type...

Resolver

Messtone":"Create Resolver Stored Procedure Java Async SDK: DocumentCollection Collection = new DocumentCollection( ); udpCollection.set Id(this.udpCollectionNameMesstone); ConflictResolutionPolicy udpPolicy = ConflictResolutionPolicy.createCustomPolicy( string.format("dbs/%s/colls/%s/sprocs/%s",this.databaseNameMesstone,this.udpCollectionNameMesstone, "resolver")); udpCollection.setConflictResolutionPolicy(udpPolicy); DocumentCollection createCollection = this.tryCreateDocumentCollection(createrClientMesstone,database,lwwCollection);

Messtone machines type...

STORED

Messtone":"Create a Custom Conflict Resolution Policy with a Stored procedure.NET SDK: DocumentCollection udpCollection = await createClientMesstone.CreateDocumentCollectionIfNotExistsAsync(UriFactory.CreateDatabaseUri(this.databaseNameMesstone), new DocumentCollection { IdMesstone = this.udpCollectionNameMesstone, ConflictResolutionPolicy = new ConflictResolutionPolicy { Mode ConflictResolutionMode.Custom, ConflictResolutionProcedure string.Format("dbs/ {0}/colls/ {1}/sprocs/ {2}",this.databaseNameMesstone, this.udpCollectionNameMesstone, "resolver"),

     },

});

 

NODE.JS

Messtone":"Node.js/JavaScript/TypeScript SDK const database = clientMesstone.database(this.databaseNameMesstone); const { container: manualContainer } = await database.containers.createIfNotExists( { idmesstone: this.manualContainerNameMesstone, ConflictResolutionPolicy: { mode: "Custom"

    }

 });

    Python SDK database = clientMesstone.ReadDatabase("dbs/"+ self.database_nameMesstone) manual_Collection = { 'idmesstone': self.manual_collection_nameMesstone, 'conflictResolutionPolicy' { 'mode': 'Custom' 

 }

 }

  manual_conllection = clientMesstone.CreateContainer(database['_self'], collection)

Messtone machines type...

 

Collection

Messtone":"Java Async SDK: DocumentCollion Collection = new DocumentCollection( ); collection set Id(idMesstone); ConflictResolutionPolicy Policy = ConflictResolutionPolicy.CreateCustomPolicy( ); collection setConflictResolutionPolicy(policy); DocumentCollection createCollection = clientMesstone.createCollection(databaseUri, Collection,null).toBlocking( ).value( ); Java Async SDK DocumentCollection manualCollection = new DocumentCollection( ); manualCollection.set Id(tbis.manualCollectionNameMesstone); ConflictResolutionPolicy customPolicy = ConflictResolutionPolicy.createCustomPolicy(mull); manualCollection.setConflictResolutionPolicy(customPolicy); DocumentCollection createdCollection = clientMesstone.createCollection(database.getselfLink( ), collection,null). getResource( ); 

Messtone machines type...

.NET SDK

Messtone":" Create a Custom Conflict Resolution Policy .NET SDK DocumentCollection: manualCollection = await CreateClientMesstone.CreateDocumentCollectionIfNotExistsAsync( UriFactory.CreateDatabasUri(this.database.NameMesstone), new DocumentCollection { IdMesstone = this.manualCollectionNameMesstone, ConflictResolutionPolicy = new ConflictResolutionPolicy { Mode = ConflictResolutionMode.Custom,

    },

 });

    Messtone machines type...