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Behaviour of Malaysia and Australia exchange rate in response to the prices of commodities 19

Behaviour of Malaysia and Australia exchange rate in respons...

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2nd international conference on Mathematics and Statistics, ICoMS 2019

作者： Soon, Wearn Qian Hong, Leng Poh Selvachandran, Ganeshsree Faculty of Business and Information Science UCSI University Jalan Menara Gading Cheras Kuala Lumpur56000 Malaysia

ISBN: (纸本)9781450371681

A country’s exchange rate and commodity price forms a two-way relationship. However, past researches showed that the exchange rate has weaker effects towards commodity price. Hence, This study focuses on the behaviour of exchange rate in response to commodity price. This work will analyzed the behaviour of Malaysia and Australia in response to commodity price is to forecast future exchange rate. This study will determine if there exists a trend in the historical commodity price and exchange rate of Australia and Malaysia over the period of 2005 to 2015. Other than observing the relationship, the exchange rate for the 2016 was also forecast by using the historical data. Historical data of price of petroleum in Malaysia and price of iron ore in Australia will be used to predict the following year’s price Historical data are fitted into two prediction models which are Purchasing Power Parity (PPP) model and Autoregressive models. The most appropriate and accurate model was evaluated. Result showed that autoregressive models was found to be the best prediction model and is used to predict the future exchange rate. Using the autoregressive model, forecasted the exchange rate in 2016 was 3.417 AUD/MYR. © 2019 Association for computing Machinery.

关键词： Forecasting

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The use of Neural Network Modeling for the Selection of Thermophysical Coefficients 2

The use of Neural Network Modeling for the Selection of Ther...

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2nd international conference on Electrical, Communication and Computer Engineering, ICECCE 2020

作者： Platov, Sergey Latypov, Oleg Dema, Roman Kalugina, Olga Institute of Metallurgy Mechanical Engineering and Material Processing Nosov Magnitogorsk StateTehnical University Magnitogorsk Russia National University of Science and Tehnology MISIS Magnitogorsk Russia Computer Sciense and Information Security Nosov Magnitogorsk StateTehnical University Magnitogorsk Russia

ISBN: (数字)9781728171166

ISBN: (纸本)9781728171166

In this work, a simulation model of the thermal state of the work rolls at the hot rolling mill 2000 (m) of Public Joint-Stock Corporation Magnitogorsk iron and steel works (PJSC MMK) is built. A neural network was used as a tool for adjusting the thermophysical transfer coefficients of hot rolling mills. The constructed neural network is a multilayer perceptron, consisting of an input layer, two hidden layers, and an output layer. The neural network is implemented in PyTorch, a scientific computing package based on the interpreted Python programming language. To train the neural network, we used the basic data array obtained from the control system of the hot rolling mill. During industrial experiments, the temperature of the work rolls was measured using HotFind-DXT series thermal imagers developed by SDS. A neural network has been built that allows adapting the thermophysical heat transfer coefficients with an average relative error of 11.7%. A neural network will speed up and simplify the selection of thermophysical coefficients for models of the thermal state of work rolls and adequately assess the current thermal state of work rolls during the rolling process. Using a neural network, a model of the thermal state of work rolls was developed. © 2020 IEEE.

关键词： Hot rolling

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Innovation on the performance management index system of public hospital based on balanced scorecard: A case study of s hospital 2019

Innovation on the performance management index system of pub...

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2nd international conference on data Storage and data Engineering, DSDE 2019

作者： Lu, Di Hao, Jing International Business School Shaanxi Normal University No. 620 West Chang’an Avenue Chang'an District Xi'an710119 China Shaanxi Provincial People’s Hospital No. 256 West Youyi Road Xi'an710068 China

ISBN: (纸本)9781450372169

The new medical reform policy has been gradually implemented, and drug addition in tertiary hospitals have been abolished. The implementation of graded diagnosis and treatment system makes the policy and competition environment of large public hospitals unprecedentedly severe. In 2016, the Ministry of Finance promoted the application of management accounting in public institutions, providing new ideas for the performance management of public hospitals. This paper studies the existing performance assessment system of S hospital based on the balance of revenue and expenditure. Through the study of the existing problems, the balanced scorecard is introduced into the performance management of public hospitals. By means of expert consultation and literature research, a three-level index system of performance evaluation is established. In this paper, Saaty relative importance scale and analytic hierarchy process are used to calculate the weight of indexes at all levels, and its operability is studied. Finally, it gives suggestions for the implementation of the assessment system. © 2019 Association for computing Machinery

关键词： Diagnosis

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Chinese semantic role labeling with hybrid model 2

Chinese semantic role labeling with hybrid model

引用

2nd international conference on Algorithms, computing and Artificial Intelligence, ACAI 2019

作者： Zheng, Xinping Zhou, Bin Huang, Jiuming Liu, Yunxuan Wei, Feng College of Computer National University of Defense Technology Changsha China Hunan Singhand Intelligent Data Technology Co. Ltd Changsha China

ISBN: (纸本)9781450372619

To this date, most of the Chinese Semantic Role Labeling (SRL) methods based on deep learning still rely on complex feature or architecture engineering, which more or less weaken the generalization ability of model and increase the complexity of this task. In this article, we proposed a deep hybrid model, which is composed of Bi-directional Long Short Term Memory (Bi-LSTM), Self-Attention and Conditional Random Field (CRF), as an end to-end system without using any pre-defined features. We just took the sentences that have been segmented as input, and depended on the competence of model to extract potential context dependency information. After that, we used sentence level tag information via a CRF layer to get the final labeling results. Experimental results on Chinese Proposition Bank (CPB) shows that our model is really effective for this task, which can achieve 81.2% F1 score. © 2019 ACM.

关键词： Long short-term memory

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A speculative parallel optimization method for industrial big data algorithms 2

A speculative parallel optimization method for industrial bi...

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2nd IEEE international conference on Industrial Internet Cloud, ICII 2019

作者： Wang, Zhoukai Wang, Huaijun Li, Junhuai College of Computer Science and Engineering Xi'An University of Technology Xi'an China

ISBN: (纸本)9781728129778

Apache Spark is one of the most advanced distributed computing platforms at present, more and more industrial big data algorithms are implemented on this platform to achieve better performance. However, some of the algorithms cannot be executed on Apache Spark in parallel because of their complex inner control dependencies. In order to solve the problem, by introducing software Thread-Level Speculation technique, this paper proposes a method to optimize industrial big data algorithms, and makes them run on Apache Spark in parallel. Specifically, the proposed method analyzes how complex inner dependencies affect algorithm's parallelism, then speculatively partitions the algorithm into subtasks to conquer these dependencies, and predicts inputs for the subtasks. After executing the subtasks in parallel, the results are collected and validated, the correct results are kept and committed while the incorrect ones are abandoned. By this way the optimal parallelism for industrial big data algorithms can be achieved. The experiments show that by the proposed method, the particle swarm optimization algorithm can achieve speedup by 150%-230% comparing with the unspeculative one. Therefore, the execution efficiency of low parallelized algorithm on Apache Spark can be markedly enhanced by the proposed optimization method. © 2019 IEEE.

关键词： Big data

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Recurrent Neural Network Based Classification of Fetal Heart Rate Using Cardiotocograph 2nd

Recurrent Neural Network Based Classification of Fetal Heart...

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2nd international conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2018

作者： Das, Sahana Mukherjee, Himadri Obaidullah, Sk. Md. Santosh, K.C. Roy, Kaushik Saha, Chanchal Kumar Department of Computer Science West Bengal State University Kolkata India Department of Computer Science and Engineering Aliah University Kolkata India Department of Computer Science The University of South Dakota VermillionSD United States Biraj Mohini Matrisadan and Hospital Kolkata India

ISBN: (纸本)9789811391835

Perinatal mortality and morbidity occurs mainly due to intrauterine fetal hypoxia. This can eventually lead to severe neurological damage like cerebral palsy and in extreme cases to fetal demise. It is thus necessary to monitor the fetus during intrapartum and antepartum period. Cardiotocograph (CTG) as a method of assessing the status of the fetus had been in use since the 1960s. Nowadays it is the most widely used non-invasive technique for the continuous monitoring of the fetal heart rate (FHR) and the uterine contraction pressure (UCP). Though its introduction limited the birth related problems, the accuracy of interpretation was hindered by quite a few factors. Different guidelines that are provided for the interpretation are based on crisp logic which fails to capture the inherent uncertainty present in the medical diagnosis. Misinterpretations had led to inaccurate diagnosis which resulted in many medico-legal litigations. The vagueness present in the physician’s evaluation is best modeled using soft-computing based techniques. In this paper authors used the CTG dataset from UCI Irvine Machine Learning data Repository which contains 2126 data. Re-current neural network (RNN) was used for classification of CTG using five-fold cross-validation. The result was compared with a previous work using Fuzzy Unordered Rule Induction Algorithm (FURIA) and Fuzzy Membership Function (FMF) techniques. The obtained accuracy was 98%. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Diagnosis

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Discussion on the application of big data in rail transit organization 2nd

Discussion on the application of big data in rail transit or...

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2nd international conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2018

作者： Du, Guobao Zhang, Xuepeng Ni, Shaoquan Transport Office China Railway Chengdu Bureau Group Co. Ltd Chengdu610031 China School of Transportation and Logistics Southwest Jiaotong University Chengdu610031 China National Railway Train Operation Diagram Research and Training Center Southwest Jiaotong University Chengdu610031 China National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation Southwest Jiaotong University Chengdu610031 China

ISBN: (纸本)9783030045814

At present, the Internet technology has been widely used in people’s life. In this "information" era, the application of big data technology in the field of rail transport is particularly necessary. In view of this, the industry background and the theoretical basis of application is analyzed first in this paper, and then the application of big data in rail transportation field on the basis of railway passenger and freight marketing, railway operation and dispatching, railway passenger and freight service is discussed. At the same time, according to the dynamic planning of the railway transport organization system, the transport organization theory innovation and information system innovation are briefly analyzed. © Springer Nature Switzerland AG 2019.

关键词： Big data

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Intellectual Property Risks and Protection Mechanisms of Big data 18

Intellectual Property Risks and Protection Mechanisms of Big...

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2nd international conference on Big data Research (ICBDR)

作者： He, Juan Qiao, Lin Tsinghua Univ Grad Sch Shenzhen Shenzhen 518055 Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781450364768

In order to deepen the innovative application of big data in different industries and accelerate the research on big data technologies, it is important to clarify the intellectual property risks of big data and to understand the intellectual property protection mechanisms. In data processing, attention should be paid to the risk of copyright infringement of web crawlers in data acquisition process;the risk of copyright infringement of cloud computing platform in data storage process;and the risk of personal privacy infringement caused by big data analysis and mining. When big data is integrated with traditional industries such as retail industry, logistics industry and health care industry, intellectual property protection mechanisms such as copyright protection of database, trade secrets protection, anti-competition regulation of data monopolies, and data privacy regulation should be given extensive attention.

关键词： Big data Intellectual Property data Processing Risk Protection Mechanism

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data Compression Using Content Addressable Memories 1

引用

2nd international conference on soft computing Systems (ICSCS)

作者： Santhosh, Ashwin Malikarjun, Harish Kittur VIT Vellore Sch Elect Engn Dept Micro & Nano Elect Vellore Tamil Nadu India

This paper presents a 16 bit CAM of 16 words for data compression. The input data is searched for match among the 16 stored data. The match produces compressed data output. The average compression time is also calcula... 详细信息

ISBN: (数字)9789811319365

ISBN: (纸本)9789811319365;9789811319358

关键词： Content-Addressable memory NAnd cell XNOR CAM

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A dynamic security control architecture for industrial cyber-physical system 2

A dynamic security control architecture for industrial cyber...

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2nd IEEE international conference on Industrial Internet Cloud, ICII 2019

作者： Zhang, Xin Cai, Xiaobo Wang, Chaogang Han, Ke Zhang, Shujuan Department of Information Technology Yunnan College of Business Management Kunming China College of Big Data Yunnan Agricultural University Kunming China Yunnan College of Business Management Kunming China School of Electrical and Mechanical Engineering Kunming Metallurgy College Kunming China

ISBN: (纸本)9781728129778

According to the information security requirements of the industrial control system and the technical features of the existing defense measures, a dynamic security control strategy based on trusted computing is proposed. According to the strategy, the Industrial Cyber-Physical System system information security solution is proposed, and the linkage verification mechanism between the internal fire control wall of the industrial control system, the intrusion detection system and the trusted connection server is provided. The information exchange of multiple network security devices is realized, which improves the comprehensive defense capability of the industrial control system, and because the trusted platform module is based on the hardware encryption, storage, and control protection mode, It overcomes the common problem that the traditional repairing and stitching technique based on pure software leads to easy breakage, and achieves the goal of significantly improving the safety of the industrial control system. At the end of the paper, the system analyzes the implementation of the proposed secure industrial control information security system based on the trustworthy calculation. © 2019 IEEE.

关键词： Cyber Physical System

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