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13th International Conference Perspective Technologies and Methods in MEMS Design, MEMSTECH 2017

作者： Pala, Zeydin Yamli, Veysi Ünlük, Ibrahim Halil Computer Engineering Department Mus Alparslan University Turkey Computer Programming Department Bitlis Eren University Turkey Computer Programming Department Mus Alparslan University Turkey

ISBN: (纸本)9781538640005

Deep learning (DL) is deployed in Deep Neural Networks (DNNs), Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Deep Stacked Networks (DSNs), Deep Belief Networks (DBNs), and Deep Boltzmann Machines (DBMs). DL continues to take powerful steps to become a part of almost any software in the future. DL is one of the most popular research areas of machine learning. What makes it so popular is the exciting applications of recent times. Nowadays, improvement in machine learning provide ability to determine what an object in a picture does. The aim of this study is to reveal academic studies in the field of Deep Learning in Turkey and to evaluate their numerical results. Dataset search for studies in the field of DL were done in both the YÖKSIS database in Turkey and the internationally operated Web of Science and Scopus services. Finally, some evaluations were made to emphasize the importance of DL for the country. © 2017 IEEE.

关键词： Recurrent neural networks

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Encryption Time Comparison of AES on FPGA and computer

Encryption Time Comparison of AES on FPGA and Computer

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3rd International Conference on Computational Science, engineering and Information Technology, CCSEIT 2013

作者： Akman, Yasin Yerlikaya, Tarik Computer Programming Department Selcuk University Konya Turkey Computer Engineering Department Trakya University Edirne Turkey

ISBN: (纸本)9783319009506

Advanced Encryption Standard (AES), which is approved and published by Federal Information Processing Standard (FIPS), is a cryptographic algorithm that can be used to protect electronic data. The AES algorithm can be programmed in software or hardware. This paper presents encryption time comparison of the AES algorithm on FPGA and computer. In the study, Verilog HDL and C programming language is used on the FPGA and computer, respectively. The AES algorithm with 128-bit input and key length 128-bit (AES-128) was simulated on Xilinx ISE Design Suite 13.3. It was observed that, the AES algorithm runs on the FPGA faster than on a computer. We measured the time of encryption on FPGA and computer. Encryption time is 390ns of AES on FPGA and 11 μs of AES on a computer.

关键词： Field programmable gate arrays (FPGA)

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Forming the logical conclusion about sufficiency of information of software requirements specification for software quality assessment by ISO 25010:2011 1

Forming the logical conclusion about sufficiency of informat...

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1st IEEE Ukraine Conference on Electrical and computer engineering, UKRCON 2017

作者： Hovorushchenko, Tetiana Computer Engineering and System Programming Department Khmelnitsky National University Khmelnitsky Ukraine

ISBN: (纸本)9781509030064

The aim of this study is the development of the method of generating and filling the template of ontology for the quality of the concrete software and method of forming the logical conclusion about the sufficiency of information of software requirements specification (SRS) for software quality assessment (by ISO 25010:2011). The first time proposed method of generating and filling the template of ontology for the quality of the concrete software leaves in the relevant ontology only measures, which are available in the SRS for the concrete software. It provides forming the ontology for the quality of the concrete software. The first time developed method of forming the logical conclusion about the sufficiency of the SRS information for software quality assessment provides the conclusion about the sufficiency or insufficiency of the SRS information for software quality assessment by ISO 25010:2011. If the SRS information is insufficient, this method: provides the conclusion for which characteristics and sub-characteristics the information is insufficient;creates the sorted list of missing measures as the recommended priority of their addition in the SRS;evaluates the veracity of software quality assessment based on the available in the SRS measures. © 2017 IEEE.

关键词： Ontology

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A novel Frei-Chen based fragile watermarking method for authentication of an image

A novel Frei-Chen based fragile watermarking method for auth...

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作者： Renklier, Ayhan Öztürk, Serkan Computer Programming Department Kayseri University Kayseri Turkey Computer Engineering Department Erciyes University Kayseri Turkey

In recent years, the protection of the intellectual property rights of digital media has become a considerable issue. Especially using digital image editing tools has made it very easy and fast to manipulate images. Therefore, manipulation detection of digital images has become a necessity. This article presents a novel Frei-Chen based self-embedding fragile watermarking technique implemented to (Formula presented.) blocks for image manipulate detection. The block key and the Frei-Chen based block feature are calculated from the non-overlapping image blocks of size (Formula presented.). Exclusive-OR operations are applied to the Frei-Chen based block feature and the block key. After, a nine bit block authentication key is generated from the Frei-Chen based block feature and the block key. Then the generated authentication key is embedded in the least significant bits of each block. Experimental results prove the effectiveness of the proposed method through the detection of the various attacks and obtain the excellent visual quality of watermarked images. Also, the results demonstrate that the proposed method detects all of the manipulated areas plainly. © 2022 John Wiley & Sons, Ltd.

关键词： Authentication

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Reliable Code Generation and Test Environment demonstrated on a PI-Controller Design

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IFAC-PapersOnLine 2016年第3期49卷 465-470页

作者： Schwarz, M.H. Sheng, H. Üstoglu, I. Chabaan, W. Börcsök, J. Safety Computer Technology University of Kassel Germany Control and Automation Engineering Department Yildiz Technical University Istanbul Turkey Computer Architecture and System Programming University of Kassel Germany

This paper focuses on the latest version of a tool developed within the department to guide developer through the various steps of requirements, test-procedures and documentations to finally download the derived algorithm on a safety programmable logic controller (PLC). Requirements on how to develop and how to test software are steadily increasing due to international standards, which have to be obeyed in industries in general, and in the process- and automation industries in particular. A simple model is derived to be used to develop a PI controller that has to pass several steps to be qualified for execution on a PLC. The paper explains the different steps and describes the various problems that might occur. © 2016

关键词： Controllers Accident prevention Reliability Software testing Automated code generation Automation industry International standards P i controller designs PI control Programmable Logic Controller (PLC) Simple modeling Test Environment

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Relations of attention and meditation level with learning in engineering education 9

Relations of attention and meditation level with learning in...

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9th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2017

作者： Ülker, Büsra Tabakcioǧlu, Mehmet Bariş Çizmeci, Hüseyin Ayberkin, Doruk Electrical-Electronics Engineering Department Bursa Technical University Bursa Turkey Computer Programming Department Hitit University Çorum Turkey Computer Programming Department Bayburt University Bayburt Turkey

ISBN: (纸本)9781509064571

Neurons use electricity in order to communicate to each other. Due to numerous signals sent by neurons, there are oodles of electrical activity in the brain. Sensitive equipment like electroencephalogram (EEG) biosensor perceives the brainwaves emanated from neurons. Beta waves are responsible for problem solving or decision making and associated with attention. Alpha waves are associated with now and meditation. Neurosky EEG biosensor perceives the brainwaves and transforms these brainwaves into attention and meditation values. In this study, Neurosky EEG biosensor is used for measuring the attention and meditation levels of students. A program is developed in C# medium. The developed program records raw brainwave data, attention and meditation average while the students are studying. As the attention and meditation levels are high, the students learn the subjects in the course. If predetermined meditation and attention level are not caught, the developed program does not give permission to pass to another subject. Because of that the students have less meditation and attention average than the predetermined value;they get fewer grades in the exam. © 2017 IEEE.

关键词： Brain computer interface

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Mathematical Model of Crane Scheduling for a Defined Slab Storage Locations Assignment in a Continuous Cast Billet Warehouse

Mathematical Model of Crane Scheduling for a Defined Slab St...

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2024 International Russian Automation Conference, RusAutoCon 2024

作者： Shchegolikhin, Ivan S. Andreev, Sergey M. Nosov Magnitogorsk State Technical University Department of Computer Engineering and Programming Magnitogorsk Russia

An increasing number of steel factories around the world are integrating two processes: continuous casting and hot rolling. The slab warehouse is the link between these two processes. Slabs of certain sizes are cast on the continuous casting machine streams and then transported to the slab warehouse. In the warehouse, overhead cranes move the slabs to storage locations, into stacks. The sequence of slabs arriving at the slab warehouse plays an important role: slabs that arrive earlier should, as a rule, be stacked earlier. If several cranes may be operating in a warehouse in an adjacent space, the scheduling of cranes becomes much more difficult: a safe distance must be maintained between the cranes. This paper proposes a mathematical model of crane scheduling for a defined solution to the storage location assignment problem in a slab warehouse. This mathematical model considers a large number of constraints specific to the mentioned process, such as: orthogonality of crane movement;order of slab processing;minimum distance between cranes;maximum and minimum height of stacks;and many others. The developed mathematical model takes into account the space-time characteristics of the warehouse and crane trajectories, which allows its application to create a digital twin of the slab warehouse, which will allow to check the acceptability of the crane schedule for some solution of the problem of storage location assignment. © 2024 IEEE.

关键词： Continuous casting

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Heterogeneous ensemble classifier in medical decision support systems 5

Heterogeneous ensemble classifier in medical decision suppor...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Povoroznyuk, Anatol Y. Povoroznyuk, Oksana Filatova, Anna Department of Computer Engineering and Programming National Technical University "Kharkiv Polytechnic Institute Kharkiv Ukraine

ISBN: (纸本)9798350384499

The work is devoted to solving the current scientific and technical problem of constructing a diagnostic decision support system in medicine based on a heterogeneous ensemble classifier model that implements two approaches to formulating a diagnostic conclusion: a probabilistic one based on the analysis of the training sample, and expert information on the structure of symptom complexes. The choice of prototype matching method as a probabilistic component is justified. Formalization of expert information on the structure of symptom complexes was carried out by representing symptom complexes of diseases with numerical intervals of linguistic variables. Options for taking into account expert assessments about the structure of symptom complexes in an ensemble classifier are considered. Test verification of the developed classifier was done on real medical data and confirmed the effectiveness of its work. ©2024 IEEE.

关键词： Expert systems

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Optimization of neural network calculations using integer arithmetic 5

Optimization of neural network calculations using integer ar...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Zakovorotnyi, Oleksandr Khulap, Andrii Department of Computer Engineering Programming National Technical University Kharkiv Polytechnic Institute" Kharkiv Ukraine

ISBN: (纸本)9798350384499

Most of the sensor devices in the Internet of Things systems are based on energy-efficient microcontrollers, the computing resources of which are limited, as well as the amount of available memory. Increasing the security of the use of such devices with the help of neural networks is an important and urgent problem. The article describes the possibility of using artificial neural networks in small microcontrollers with limited resources. The purpose of this work is to check the possibility of calculating neural networks based on integer arithmetic to reduce the time of calculating a neural network and eliminate data normalization operations, as well as to evaluate the feasibility of using such neural networks in the field of security of the Internet of Things in comparison with traditional methods, such as black lists and white lists. The following results were obtained: when switching to integer arithmetic, compared to floating point, the accuracy of the result calculations is within the permissible error of neural network training, that is, it has not changed. Execution time decreased by 30-96%, depending on the architecture of the microcontroller. The program size is reduced by 22-48%, also depending on the microcontroller architecture. Conclusions: the possibility and expediency of using neural networks optimized for microcontrollers with limited resources was proved. This will increase the security of Internet of Things systems, especially against device authentication threats and intrusion detection. Prospects for further research are determined. ©2024 IEEE.

关键词： microcontroller neural network optimization software implementation

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New neural networks for determining proximity and distance functions when comparing binary objects 3

New neural networks for determining proximity and distance f...

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3rd IEEE KhPI Week on Advanced Technology, KhPI Week 2022

作者： Dmitrienko, Valerii Zakovorotniy, Aleksandr Leonov, Sergey National Technical University 'Kharkiv Polytechnic Institute' Computer Engineering and Programming Department Kharkiv Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

Artificial neural networks are effectively used to solve various problems (recognition, clustering, classification, etc.) in conditions where information about objects is given by vectors with binary components. The Hamming neural network is an effective tool for solving these problems when the initial information is given in the form of bipolar vectors. However, when comparing binary objects with qualitative features, more than 70 different distances (proximity measures) and proximity functions of binary objects are used. Synthesizing dozens of neural networks for matching binary objects is too laborious. Therefore, a universal approach to the synthesis of such neural networks is proposed. In addition, the Hamming network can select only one object from its memory that is closest to the input. It cannot function normally if there are two or more such objects. The proposed neural network does not have this shortcoming. And last but not least, a neural network with this architecture allows you to calculate various distances and similarity measures of the input data and data stored in the network memory © 2022 IEEE.

关键词： Neural networks

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