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11th International Conference on Information Technology, Computer and Electrical engineering, ICITACEE 2024

作者： Nudin, Salamun Rohman Gernowo, Rahmat Somantri, Maman Wibowo, Adi Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Diponegoro University Faculty of Engineering Department of Electrical Engineering Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Informatics Semarang Indonesia

ISBN: (纸本)9798350389289

This paper presents a comprehensive review of deep learning methods for the Big Five personality traits prediction using multi-task classification. The purpose of the review is to determine the performance of models developed in previous research to describe research opportunities and challenges in the future. The Big Five model is a framework in psychology that categorizes human personality into five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. The review begins by analyzing 22 articles from the science Direct, IEEE Xplore, and Scopus databases by applying screening using the Big Five Personality keywords. Then study the concepts of deep learning for model development such as: input, architecture, method, dataset, and performance to identify the strengths and limitations of each approach. The review results of the highest average accuracy by modality such as unimodal text with essay dataset (80.98%), unimodal image with ImageNet dataset (95.36%), unimodal audio with SSPNet dataset (79.48%), bimodal image and audio with Chalearn Video First Impression dataset (91.67%), multimodal text, image, and audio with Chalearn Video First Impression dataset (91.88%). The average accuracy of the Big Five Personality traits was highest (95.36%) and lowest (59%). This highlights the need for standard benchmarks, interpretable models and interdisciplinary collaboration to improve the accuracy, reliability and ethical implications of personality prediction. Future research is expected to pave the way for advancements in understanding human personality through deep learning approaches using other modalities such as EEG, GSR, and PPG. © 2024 IEEE.

关键词： Contrastive Learning

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Effect of tin on the texture of nonoriented electrical steels

Effect of tin on the texture of nonoriented electrical steel...

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Materials Processing and Texture - 15th International Conference on Textures of Materials, ICOTOM 15

作者： Hou, Chun-Kan Lee, Tong-Han Liao, Chun-Chih Department of Mechanical Engineering National Yunlin University of Science and Technology I23 University Road Section 3 Douliou Yunlin 64002 Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology I23 University Road Section 3 Douliou Yunlin 64002 Taiwan

ISBN: (纸本)9780470408346

The effect of tin (range from 0.029-0.21 wt%) on the inclusion size in hot bands, grain size and texture of four non-oriented electrical steels after final annealing has been investigated. The steel ingots were reheated to 1200C and finished rolled at 950C. Then hot bands were annealed at 750C for two hours and cold rolled to 0.5mm. After annealing the cold rolled sheets at 750-950 °C for one minute, both X-ray diffractometer with texture attachment and EBSD analyses were conducted to measure specimen texture. It was found that 5-10 μm coarse MnS + AlN inclusions existed in the hot bands containing 0.029 wt% tin. However, 1-2 μm fine MnS+AlN inclusions were found in the hot bands containing 0.21 wt% tin. After final annealing, grain size decreased with increasing tin content and began to level off when tin reached 0.10wt%. At the same cold rolled annealing temperature, the intensity of {011} texture increased with increasing tin content. In the same steel, the intensity of {011} texture increased with increasing annealing texture and reached a maximum value and then declined sharply. The temperature to obtain maximum intensity of {011} texture strongly correlated with tin content, EBSD showed that the number and volume fraction of {011} grain per mm2 increased with increasing tin content. It is concluded that adding tin in the range of 0.100-0.210wt% to non-oriented electrical steels can enhance the volume fraction of Goss grain, The mechanisms are that tin not only enhances the nucleation of Goss grain, but also promotes its growth. Conversely, adding 0.055wt% tin to non-oriented electrical steels can lead to the best cube texture. This tin content maximizes the nucleation density of cube grains during annealing at 850C.

关键词： Annealing

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Dynamic laplace: Efficient centrality measure for weighted or unweighted evolving networks

arXiv

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arXiv 2018年

作者： Cordeiro, Mário Sarmento, Rui Portocarrero Brazdil, Pavel Gama, João Doctoral Program in Informatics Engineering Faculty of Engineering University of Porto INESC TEC - Institute for Systems and Computer Engineering Technology and Science

With its origin in sociology, Social Network Analysis (SNA), quickly emerged and spread to other areas of research, including anthropology, biology, information science, organizational studies, political science, and computer science. Being it's objective the investigation of social structures through the use of networks and graph theory, Social Network Analysis is, nowadays, an important research area in several domains. Social Network Analysis cope with different problems namely network metrics, models, visualization and information spreading, each one with several approaches, methods and algorithms. One of the critical areas of Social Network Analysis involves the calculation of different centrality measures (i.e.: the most important vertices within a graph). Today, the challenge is how to do this fast and efficiently, as many increasingly larger datasets are available. Recently, the need to apply such centrality algorithms to non static networks (i.e.: networks that evolve over time) is also a new challenge. Incremental and dynamic versions of centrality measures are starting to emerge (betweenness, closeness, etc). Our contribution is the proposal of two incremental versions of the Laplacian Centrality measure, that can be applied not only to large graphs but also to, weighted or unweighted, dynamically changing networks. The experimental evaluation was performed with several tests in different types of evolving networks, incremental or fully dynamic. Results have shown that our incremental versions of the algorithm can calculate node centralities in large networks, faster and efficiently than the corresponding batch version in both incremental and full dynamic network setups. Copyright © 2018, The Authors. All rights reserved.

关键词： Laplace transforms

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Reversible JPEG Data Hiding Based on EMD

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通讯和计算机（中英文版） 2012年第10期9卷 1135-1141页

作者： Wen-Chung Kuo Shao-Hung Kuo Department of Computer Science and Information Engineering National Yunlin University of Science & Technology Yunlin 672 Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology Yunlin 640 Taiwan

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An effect of humid climate on micro structure and chemical component of natural composite (Boehmeria nivea-Albizia falcata) based wind turbine blade 2

An effect of humid climate on micro structure and chemical c...

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2nd International Conference on Energy, Environmental and Information System, ICENIS 2017

作者： Sudarsono, S. Purwanto, P. Sudarsono, Johny W. Department of Mechanical Engineering Institut Sains Dan Teknoogi AKPRIND Yogyakarta Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Diponegoro Indonesia Doctoral Program of Environmental Science School of Postgraduate Studies Universitas Diponogero Semarang Indonesia Depart. of Material and Metallurgy Faculty of Engineering Universitas Indonesia Jakarta Indonesia

In this work, wind turbine blade NACA 4415 is fabricated from natural composite of Boehmeria nivea and Albizia falcate. The composite fabrication method used is hand lay up method. The aim of the work is to investigate an effect of humid climate of coastal area on micro structure and chemical composition of composite material of the blade. The wind turbine is tested at Pantai Baru, Bantul, Yogyakarta for 5.5 months. The micro structure scanning is performed with Scanning Electron Microscope (SEM) and material component is measured with Energy Dispersive X-ray spectrometer (EDS). The samples are tested before and after the use within 5.5 month at the location. The results show that composite material inexperienced interface degradation and insignificant change of micro structure. From EDS test, it is observed that Na filtration reduces C and increases O in composite material after 5.5 months. © 2018 The Authors, published by EDP sciences.

关键词： Microstructure

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Role of delamination fracture for enhanced impact toughness in 0.05 %P doped high strength steel with ultrafine elongated grain structure

Role of delamination fracture for enhanced impact toughness ...

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7th International Conference on Processing and Manufacturing of Advanced Materials, THERMEC'2011

作者： Jafari, Meysam Kimura, Yuuji Tsuzaki, Kaneaki Doctoral Program in Materials Science and Engineering Graduate School of Pure and Applied Science University of Tsukuba 1-2-1 Sengen Tsukuba Ibaraki 305-0047 Japan Structural Metals Center National Institute for Materials Science 1-2-1 Sengen Tsukuba Ibaraki 305-0047 Japan

ISBN: (纸本)9783037853047

Ultrafine elongated grain (UFEG) structures with strong 〈110〉// rolling direction (RD) fiber deformation texture were produced by warm caliber-rolling at 773 K, namely tempforming in the 1200 MPa-class medium-carbon low-alloy steel with phosphorous (P) contents of 0.001 and 0.053 mass%. Charpy impact tests were performed at temperature range of -196 to 150 °C on the UFEG structure. Regardless of P content, high upper shelf energy about 145 J and a very low ductile to brittle transition temperature (DBTT) of around -175 °C were obtained. P segregation embrittlement completely disappeared in the 0.053 %P steel and both steels showed ductile fracture on the planes normal to RD at temperature range of -150 to 150 °C. The main reason for the high upper shelf energy and very low DBTT in the 0.053 %P steel would be delamination fracture along RD when both 0.001 and 0.053 %P steels showed quite similar microstructures including texture. Since the occurrence of delamination requires relatively weak interfaces or planes, P segregated to the ferrite grain boundaries and interfaces of cementite particles-ferrite matrix and made them feasible paths for crack branching and consequently delamination occurred. We showed in this work the advantage of delamination (crack arrester-type) on the high absorbed energy obtained by 0.053 %P steel in comparison with 0.001 %P steel. © (2012) Trans Tech Publications, Switzerland.

关键词： Fracture toughness

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Authenticated secret sharing scheme based on GMEMD

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9569卷 395-405页

作者： Kuo, Wen-Chung Kuo, Shao-Hung Chang, Hong-Yi Wuu, Lih-Chyau Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Douliu Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology Douliu Taiwan

ISBN: (纸本)9783319319599

In secret image sharing schemes, all legal participants provide legitimate shared images and then they can extract the correct secret message. Recently, Wu et al. proposed a high quality data hiding secret sharing scheme with authentication ability. The major contribution of this scheme maintains good stego image quality while being able to verify secret message integrity. However, to ensure the process can work, the secret image’s pixel values larger than 250 must be changed to 250 for Wu’s scheme. Otherwise, extracting the secret image may fail. In other words, for a secret image, a few errors do not make the big difference but it could be distorted severely for some sensitive secrets. In order to improve this shortcoming, a secret image sharing scheme based on General Multi-Exploiting Modification Direction (GMEMD) data hiding technology will be proposed in this paper. According to simulation results and analysis, we can show that the stego image quality in Wu et al.’s scheme or our proposed scheme is larger than 43dB. We also demonstrate the authentication capability to find unauthorized participants. Furthermore, if all participants are legitimate, then the proposed scheme can extract the secret completely without any distortion. © Springer International Publishing Switzerland 2016.

关键词： Authentication

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A Study on Text Feature Selection Using Ant Colony and Grey Wolf Optimization 7

A Study on Text Feature Selection Using Ant Colony and Grey ...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Widians, Joan Angelina Wardoyo, Retantyo Hartati, Sri Universitas Gadjah Mada Doctoral Program Dept. of Computer Science and Electronics Indonesia Universitas Mulawarman Faculty of Engineering Dept. of Informatics Samarinda Indonesia Universitas Gadjah Mada Faculty of Mathematics and Natural Sciences Dept. of Computer Science and Electronics Yogyakarta Indonesia

ISBN: (纸本)9798350345711

Text classification (TC) is widely used for organizing digital documents. The issues in TC are numerous characteristics and high-element dimensions. Many pattern classification issues require feature selection (FS), which is pertinent. FS removes unneeded and redundant data from the dataset. The Ant Colony Optimization (ACO) and Grey Wolf Optimizer (GWO) for FS are the main topics of our thorough assessment of the literature on the Swarm Intelligence (SI) algorithm. Furthermore, it illustrates how the hybrid SI technique is used in FS across various sectors. The hybrid SI technique uses applicable data from various FS methods to find feature subsets with smaller sizes and better classification performance than those found by regular FS algorithms. © 2022 IEEE.

关键词： Ant colony optimization

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Thermal reaction characteristics and microstructure evolution of aluminium nano-powder in various mixtures of oxygen and nitrogen atmosphere

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Process Safety and Environmental Protection 2023年 170卷 45-53页

作者： Qu, Jiao Deng, Jun Luo, Zhen-Min Xiao, Yang Shu, Chi-Min Post-doctoral Program Research Centre Xi'an University of Science and Technology No. 58 Yanta Mid. Rd. Shaanxi Xi'an710054 China School of Safety Science and Engineering Xi'an University of Science and Technology No. 58 Yanta Mid. Rd. Shaanxi Xi'an710054 China Shaanxi Key Laboratory of Prevention and Control of Coal Fire No. 58 Yanta Mid. Rd. Shaanxi Xi'an710054 China Department of Safety Health and Environmental Engineering National Yunlin University of Science and Technology Yunlin 64002 Taiwan

Aluminium nano-powder has a small particle size, large specific surface area, and high surface energy, therefore when using it, the risk of fires or explosions is high. In this study, synchronous thermal analyser was used to determine the thermal reaction characteristics of aluminium nano-powder for various oxygen and nitrogen mixtures. The results showed that the oxidation behaviour of aluminium nano-powder could be considered to occur in four stages, according to the characteristic temperature points and polymorphic phase changes. Under experimental heating rates of 5, 10, 15, and 20 K/min, the mass gain and thermal effects of the samples were tested, and also for different oxygen concentrations of 9, 15, and 21 vol%. Changes in the microstructure of the samples were analysed. Oxide layer thickness was found to increase as temperature increased, and this trend was the same for mass change. Surface morphology images of the aluminium particles exhibited agglomeration, melting deformation, rupture, and fragmentation at the different pretreated temperatures of 500, 650, 800, and 900 °C. The results of this study could be used as a basis for exploring oxidation kinetics, and had significance for explosion-proofing technology, particularly with respect to aluminium nano-powder. © 2022 The Institution of Chemical Engineers

关键词： Surface morphology

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Research on Performance of Terrain Matching Algorithm for Underwater Autonomous Vehicle Based on Particle Filter

Research on Performance of Terrain Matching Algorithm for Un...

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2019年第五届机械工程及自动化科技国际会议

作者： ShenJian Xiong Lu Ba Ning Post-doctoral program on control science and engineering Naval University of Engineering Department of Radar system OrdnanceNCO Academy of Army engineering university

AUV is a powerful tool for exploration and development of marine resources. Underwater terrain matching navigation is an emerging passive autonomous navigation method, which improves the long-term and high-precision navigation capability of AUV. The underwater terrain matching algorithm based on particle filter(PF) use a large number of particle sampling to approximate the system state, which can avoid the Taylor expansion truncation error caused by the terrain linearization method, and has good matching precision and terrain adaptability. However, due to the strong nonlinearity and the uneven distribution of the underwater terrain features, it is difficult to achieve the full-range terrain matching optimize with a single configuration parameter of PF underwater terrain matching algorithm. For this reason, this paper has comprehensively studied the PF terrain matching algorithm(referred to as PF matching algorithm). The principle, accuracy and implementation steps of PF algorithm are analyzed. With the UKF algorithm as a reference, the advantages and disadvantages of PF-based algorithm are studied through computer simulation of terrain matching navigation. The matching precision and terrain adaptability of PF-based algorithm has been tested. From the simulation results, it is concluded that the particle diversity decline is one of the main factors affecting the matching performance, which provides a basis for algorithm performance improvement and engineering adaptability improvement.

关键词： Gaussian AUV MSE UKF Research on Performance of Terrain Matching Algorithm for Underwater Autonomous Vehicle Based on Particle Filter

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