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A soft set approach for clustering student assessment datasets

Journal of Computational and Theoretical Nanoscience 2015年第12期12卷 5928-5939页

作者： Suhirman Herawan, Tutut Yanto, Iwan Tri Riyadi Zain, Jasni Mohamad Hongwu, Qin Abdullah, Zailani Universitas Teknologi Yogyakarta Yogyakarta Indonesia Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Gambang Kuantan Pahang Malaysia AMCS Research Center Yogyakarta Indonesia University Ahmad Dahlan Yogyakarta Yogyakarta Indonesia Universiti Malaysia Terengganu Terengganu Malaysia

Educational data mining has been studied extensively as it provides useful information for educators to make more accurate decisions concerning their students, and to adapt their teaching strategies accordingly. Data clustering as one of data mining techniques can be considered as an alternative method for educational data mining. In this paper, a data clustering technique based on soft set theory is presented. The Maximum Degree of Domination in soft set theory (MDDS) is proposed and further applied to select the best attribute in educational data clustering. To find meaningful clusters from a dataset, clustering attribute selection is conducted so that attributes within the clusters made will have a high correlation or high interdependence to each other while the attributes in other clusters are less correlated or more independent. The datasets are taken from a survey from a number of courses at the Information engineering and the Architecture Departments of the University Technology of Yogyakarta, Indonesia. The evaluation criteria uses score range from 0 to 100. Student name, age, race, and attendance are not required in this assessment. In the results, we show how to determine the dominant attributes of a set of attributes of an assessment list by using the proposed technique. The results obtained can potentially contribute to give a recommendation in awarding the final grade of a course more quickly and accurately. Copyright © 2015 American Scientific Publishers All rights reserved.

关键词： Students

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Switching Transient of Multi-step 3-Phase Capacitor Bank in 66/11 kV Bhutan Silicon Metal Private Ltd

Switching Transient of Multi-step 3-Phase Capacitor Bank in ...

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International Electrical engineering Congress (iEECON)

作者： Chophel Thanapong Suwanasri Phanupong Fuangpian Cattreeya Suwanasri Warunee Srisongkram Electrical and Software System Engineering The Sirindhorn International Thai-German Graduate School of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Nonthaburi Thailand

Capacitor banks are finding greater acceptability in application with the integration of many Ferro Silicon Industries in Bhutan; however, switching of capacitor banks is one of the most challenging operations because many inherent characteristics are accompanied with these events that needs to be studied carefully. This paper presents the switching transients of multi-step 3-phase back-to-back capacitor bank of 66/11kV Bhutan Silicon Metal Private Limited. Simulation were carried out to observe the magnitude of peak inrush current, frequency of transient oscillation and peak oscillating voltage during energizing/de-energizing of capacitor banks. The result shows that the magnitude is very high without current limiting reactor but with current limiting reactor the magnitude is reduced to a permissible limit thereby mechanical stresses to the nearby electrical equipment is reduced. Capacitor bank with grounded system is recommended because the transient recovery voltage and the rate of rise of recovery voltage across circuit breaker contact are less than the standard value of 2S kV and the limit of equipment capability 28 kV/75 μs = 0.37 kV/μs as per ANSI C37.06-2000.

关键词： Capacitors Circuit breakers Transient analysis Limiting Inductors Silicon Metals

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A pilot study of pre- post anxiety treatment to improve academic performance for engineering students

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Procedia - Social and Behavioral Sciences 2011年 15卷 3826-3830页

作者： Prima Vitasari Muhammad Nubli Abdul Wahab Tutut Herawan Ahmad Othman Suriya Kumar Sinnadurai Faculty of Manufacturing Engineering and Technology Management Universiti Malaysia Pahang Lebuhraya Tun Razak 26300 Kuantan Pahang MALAYSIA Center of Modern Language and Human Science Universiti Malaysia Pahang Lebuhraya Tun Razak 26300 Kuantan Pahang MALAYSIA Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Lebuhraya Tun Razak 26300 Kuantan Pahang MALAYSIA

In this paper, we present a pilot study of pre- post treatment toward overcoming anxiety in improving academic performance for engineering's students. The anxiety level measurement was used to examine the effect of the intervention, as well to acquire the prior finding on the effectiveness of a treatment to reduce anxiety in improving academic performance. It is based on a pre post design to evaluate the effect of intervention by using breath per-minute (bpm) and grade point average (GPA). Six males and females engineering's students participated in this study. They received six sessions of treatment each for two hours of intervention. It includes breathing retreatment, relaxation, study coping skills. The results show that, the number of anxieties was significantly reduced which bpm shows t (2;5)= 4.788; p=.005 (p<.05). Furthermore, for GPA the difference is not significant with t (0;5)= -1.894; p=.117 (p>.05). Since all participants had reduced their anxiety level and improve their academic performance, we recommend that this intervention as an effective approach in reducing anxiety level.

关键词： Pilot study Treatment Anxiety Academic performance engineering student.

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A secure self-destruction scheme with IBE for the internet content privacy

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Jisuanji Xuebao/Chinese Journal of computers 2014年第1期37卷 139-150页

作者： Xiong, Jin-Bo Yao, Zhi-Qiang Ma, Jian-Feng Li, Feng-Hua Liu, Xi-Meng Faculty of Software Fujian Normal University Fuzhou 350108 China School of Computer Science and Technology Xidian University Xi'an 710071 China State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100093 China Shaanxi Key Laboratory of Network and System Security Xidian University Xi'an 710071 China

With the rapid emerging of novelty Web services and cloud services, privacy information and documents of users become increasingly easy to be exposed in the Internet. To tackle the issue of lifecycle security of the privacy information and documents in the Internet, in this paper, we propose the idea of combining the three security methods of multilevel security, identity-based encryption (IBE), and distributed hash table (DHT) network. And we further propose an IBE-based secure self-destruction (ISS) scheme to protect the confidentiality and privacy of the Internet content by self-destruction after a predefined time. In our proposed ISS security scheme, the Internet content is first partitioned into many segments with diverse security levels, and each segment is encrypted with a symmetric key to obtain primitive ciphertext. By applying the methods of association and extraction, the primitive ciphertext is turned to associated ciphertext, which is then divided into extracted ciphertext and encapsulated ciphertext. The latter is encapsulated into the Internet content self-destructing object (CDO), which is stored into the storage services provider. Furthermore, to protect the privacy security when the CDO expired, the symmetric key is encrypted using the IBE algorithm based on the identity of the authorized user. The combination of this key's ciphertext and the extracted ciphertext, by means of Lagrange polynomial processing, generates mixture ciphertext shares. Then those shares are distributed into nodes within the DHT network and will be automatically discarded over the deadline when the primitive ciphertext and the symmtric key are unrecoverable. Consequently, the ISS scheme achieves the aim of secure self-destruction. Comprehensive analysis shows that the ISS scheme is able to satisfy all the design demands and is more secure than existing schemes. The ISS scheme can resist against not only the traditional cryptanalysis and brute-force attack, but also the Sybil

关键词： Access control

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Smart Home Gas Sensor Optimization Using Kalman Filter for Data Processing

Smart Home Gas Sensor Optimization Using Kalman Filter for D...

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International Conference on Informatics and Computing (ICIC)

作者： Somantri Muhamad Ikhsan Thohir Alun Sujjada Deni Setiawan Ilham Komara Fikri Ardiansyah Efendi Muhamad Muslih Zubaile Bin Abdullah Mohd Zainuri Saringat Department of Software Engineering University Tun Hussein Onn Malaysia Informatics Engineering Study Program Nusa Putra University Sukabumi Indonesia Informatics Engineering Study Program Nusa Putra University Sukabumi Indonesia Department of Software Engineering University Tun Hussein Onn Malaysia Sukabumi Indonesia Department of Information System Nusa Putra University Sukabumi Indonesia Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Johor Bahru Malaysia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

The integration of Internet of Things (IoT) technologies into modern homes has enhanced safety and comfort, particularly in detecting gas leaks, which pose serious fire hazards. Gas leaks can often be detected by smell, but this method fails when no one is present. Previous research using microcontrollers and sensors to detect gas leaks faced challenges with accuracy due to noise interference. This paper proposes the use of a Kalman filter, developed by Rudolf Emil Kalman in 1960, to improve gas leak detection accuracy by filtering out noise. The system comprises an Arduino Nano, ESP8266 WiFi module, MQ-2 gas sensor, buzzer, and ThingSpeak cloud platform. By applying the Kalman filter, noise and data oscillations are reduced, enhancing detection accuracy. Experimental results show the system effectively detects gas leaks, provides real-time data, and triggers alarms. Future improvements could include additional sensors and features to further increase the system’s reliability and functionality.

关键词： Accuracy Noise Sensor phenomena and characterization Sensor systems Real-time systems Kalman filters Internet of Things Reliability Leak detection Gas detectors

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Real time traffic congestion degree computation for minor sensorless roads using cost efficient context reasoning

Real time traffic congestion degree computation for minor se...

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International IEEE Conference on Intelligent Transportation systems

作者： Raphiphan, Panraphee Prathombutr, Passakon Zaslavsky, Arkady Meesad, Phayung Caulfield School of Information Technology Monash University 900 Dandenong Rd Caulfield East VIC 3145 Australia 112 Thailand Science Park Phahon Yothin Rd Pathumthani 12120 Thailand Department of Computer Science and Electrical Engineering Luleå University of Technology Luleå Sweden Centre for Distributed System and Software Engineering Monash University Australia Department of Teacher Training in Electrical Education Faculty of Technical Education King Mongkut's University of Technology North Bangkok 1518 Pibulsongkram Rd Bangsue Bangkok 10800 Thailand

ISBN: (纸本)9781424476572

Traffic congestion is the cause of pollution and economic loss. The Real time traffic state report can alleviate this problem by assisting drivers for route planning and choosing unblocked roads. More traffic information could lead to more accurate route planning and greater awareness of traffic situations and road conditions for drivers. However, investment into sensor infrastructure for small minor roads is rarely available. In this paper, we present a cost efficient approach to compute real time traffic congestion degrees for non-sensor infrastructure roads, such as small minor roads, based on context fusion and context reasoning method. Our framework intends to utilize real time acquirable context instead of relying on traffic sensory data which made our approach suitable for insufficient sensor infrastructure environment. The evaluation throughout several experimentations conducted in Bangkok has proven the feasibility of our approach. Besides, the experimental result indicated that the methodology of our experiment can be used as an alternative cost efficient tool for infrastructure investment decision making. ©2010 IEEE.

关键词： Traffic congestion

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An Approach to Improve the Robustness of Substitution Techniques of Audio Steganography

An Approach to Improve the Robustness of Substitution Techni...

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2009 2nd IEEE International Conference on computer Science and Information Technology（ICCSIT 2009）

作者： Mazdak Zamani Azizah Bt Abdul Manaf Rabiah Bt Ahmad Akram M.Zeki Faculty of Computer Science and Information System University of Technology Malaysia 54100 Kuala Lumpur Malaysia College of Science and Technology University of Technology Malaysia 54100 Kuala Lumpur Malaysia Centre for Advanced Software Engineering University of Technology Malaysia 54100 Kuala Lumpur Malaysia

Steganography is a technique used to transmit hidden information by modifying an audio signal in an imperceptible *** transmission must be possible in spite of subsequent imperceptible alterations(attacks)of the modified *** propose a novel approach of substitution technique of audio *** genetic algorithm,message bits are embedded into multiple,vague and higher LSB layers,resulting in increased *** robustness specially would be increased against those intentional attacks which try to reveal the hidden message and also some unintentional attacks like noise addition as well.

关键词： data hiding substitution techniques audio steganography artificial intelligence genetic algorithm.

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Utilizing Information from Task-Independent Aspects via GAN-Assisted Knowledge Transfer

Utilizing Information from Task-Independent Aspects via GAN-...

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International Joint Conference on Neural Networks

作者： Lunkai Fu Jun Li Langxiong Zhou Zhenyuan Ma Shaopeng Liu Zhiyong Lin Mukesh Prasad School of Computer Science Guangdong Polytechnic Normal University Guangzhou China School of Software and Centre for Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia School of Mathematics and System Sciences Guangdong Polytechnic Normal University Guangzhou China

Observed data often have multiple labels with respect to different aspects. For example, a picture can have one label specifying the contents in terms of the object category such as aeroplane, building, cat, etc. and in the meanwhile have another label describing the image style such as photo-realistic or artistic. The central idea of this work is that any annotation of the data contains precious knowledge and is not to be foregone: an analytic task focusing on one aspect of the data can benefit from the knowledge transferred from the other aspects. We propose a passive knowledge transfer scheme for deep neural network training based on the generative adversarial nets (GANs). The adversarial training scheme encourages the nets to encode data into representations that are both discriminative for the target aspect and invariant with respect to the irrelevant aspects. We show that the scheme mixes the conditional distributions of the encoded data on the irrelevant aspects, by the theory on the link between the GAN framework and the Wasserstein metric in distribution spaces. Moreover, we empirically verified the method by i) classifying images despite influence by geometric transform and ii) recognizing the movements (geometric transform) regardless the image contents.

关键词： Task analysis Neural networks Knowledge transfer Gallium nitride Generators Training Measurement

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EventTrojan: Manipulating Non-Intrusive Speech Quality Assessment via Imperceptible Events

EventTrojan: Manipulating Non-Intrusive Speech Quality Asses...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Ying Ren Kailai Shen Zhe Ye Diqun Yan Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Juphoon System Software Co. Ltd Ningbo China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology (Shandong Academy of Sciences) China

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

Non-Intrusive speech quality assessment (NISQA) has gained significant attention for predicting speech’s mean opinion score (MOS) without requiring the reference speech. Researchers have gradually started to apply NISQA to various practical scenarios. However, little attention has been paid to the security of NISQA models. Backdoor attacks represent the most serious threat to deep neural networks (DNNs) due to the fact that backdoors possess a very high attack success rate once embedded. However, existing backdoor attacks assume that the attacker actively feeds samples containing triggers into the model during the inference phase. This is not adapted to the specific scenario of NISQA. And current backdoor attacks on regression tasks lack an objective metric to measure the attack performance. To address these issues, we propose a novel backdoor triggering approach (EventTrojan) that utilizes an event during the usage of the NISQA model as a trigger. Moreover, we innovatively provide an objective metric for backdoor attacks on regression tasks. Extensive experiments on four benchmark datasets demonstrate the effectiveness of the EventTrojan attack. Besides, it also has good resistance to several defense methods.

关键词： Measurement Resistance Adaptation models Multimedia systems Current measurement Artificial neural networks Benchmark testing

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GAN2C: Information Completion GAN with Dual Consistency Constraints

GAN2C: Information Completion GAN with Dual Consistency Cons...

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International Joint Conference on Neural Networks (IJCNN)

作者： Lujuan Zhang Jun Li Tao Huang Zhenyuan Ma Zhiyong Lin Mukesh Prasad School of Mathematics and System Sciences Guangdong Polytechnic Normal University Guangzhou China School of Software and Center for Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia School of Computer Science Guangdong Polytechnic Normal University Guangzhou China

This paper proposes an information completion technique, GAN2C, by imposing dual consistency constraints (2C) to a closed loop encoder-decoder architecture based on the generative adversarial nets (GAN). When adopting deep neural networks as function approximators, GAN2C enables highly effective multi-modality image conversion with sparse observation in the target modes. For empirical demonstration and model evaluation, we show that trained deep neural networks in GAN2C can infer colors for grayscale images, as well as estimate rich 3D information of a scene by densely predicting the depths. The results of the experiments show that in both tasks GAN2C as a generic framework has been comparable to or advanced the state-of-the-art performance which are achieved by highly specialized systems. Code is available at https://***/AdalinZhang/GAN2C.

关键词： Image color analysis Gallium nitride Task analysis Neural networks Gray-scale Generative adversarial networks Probabilistic logic

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