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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Mei Hashimoto Michiharu Niimi Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan

ISBN: (数字)9798350367331

ISBN: (纸本)9798350367348

This paper proposes a method that allows users to easily convert a large number of still images into movies by displaying photos in sync with memories or favorite songs, which offers a new media viewing method for users to look back at the vast number of photos in their photo folders. We assume here that users select a song and have images stored in local PC. One method of synchronization involves selecting images based on elapsed time of song. However, since lyrics convey meaning, it can be better to display the images that align with both lyrics’ meaning and images’ meaning matched. In order to do this, we need the space which shares the concept of both lyrics and images, and select colors as the concept. Displayed images are determined based on the distance between points that are mapped from words and images to color space. Specifically, the color concepts from words are extracted using the Color Image Scale, and that from images are determined as the most frequent colors by cluster analysis. Experimental results show that it is possible to easily create movies where images with colors that match the mood of the lyrics are displayed.

关键词： Image color analysis Mood Refining Asia Information processing Color Media Motion pictures Synchronization

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Detection of Diffusion-Generated Images Using Sparse Coding

Detection of Diffusion-Generated Images Using Sparse Coding

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Daishi Tanaka Michiharu Niimi Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan

ISBN: (数字)9798350367331

ISBN: (纸本)9798350367348

This paper proposes a method for detecting images generated by diffusion models using sparse coding. In the diffusion model, an image can be generated by removing noise from a noisy image. This different generation process from real images leads us to believe that there may be a statistical difference in pixels between the real and the generated images. Specifically, the image is divided into small patch regions, and all patch images are reconstructed using the basis image. In this process, sparse coefficients that contain many zeros are obtained using sparse coding, and features are calculated from the obtained coefficients. Then, a simple discriminator using the features as input is trained with a small number of data to discriminate the diffusion-generated images. In our experiments, we evaluated the proposed method on six datasets created using three diffusion models and two real image datasets. Experiments were also conducted to evaluate the robustness of the proposed method against JPEG compression. Experimental results show that our proposed method is sufficiently robust against JPEG compression with as few as 1800 training data.

关键词： Image coding Noise Transform coding Training data Information processing Diffusion models Feature extraction Robustness Noise measurement Image reconstruction

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Improved Ultimate Link without Markers for Projective Transformation

Improved Ultimate Link without Markers for Projective Transf...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Keiji Yamadera Michiharu Niimi Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology Iizuka Japan

ISBN: (数字)9798350367331

ISBN: (纸本)9798350367348

In our previous work, we have proposed a method that links character string having a certain semantic meaning on papers in real world to the digital content in cyberspace, and call it "Ultimate Link." Ultimate Link adds additional information to characters by drawing colored circles on top of the characters without changing the shape of the characters. A URL can be generated by connecting additional information of semantically organized character strings from an image taken with a digital device. The conventional Ultimate Link drew markers to normalize the drawn circles (markers for projective transformation), similar to the finder pattern in a QR code. In order to achieve a more realistic application, it is desirable it. We report on an improved Ultimate Link that can handle complex multiple character strings. Specifically, improvements were made to enable extraction of information by identifying character strings with embedded additional information from sheets of paper printed with multiple character strings. As a result of experiments, we confirmed that information could be successfully embedded and extracted for both character strings in the target image.

关键词： Uniform resource locators Shape Semantics Lighting Web pages Personal digital devices QR codes Information processing Information retrieval Data mining

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2.45 GHz Frequency- Tracking Electro-Optic Imaging Using Polarization CMOS Image Sensor

2.45 GHz Frequency- Tracking Electro-Optic Imaging Using Pol...

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2024 IEEE Asia-Pacific Microwave Conference, APMC 2024

作者： Okada, Ryoma Mizuno, Maya Takehara, Hironari Haruta, Makito Tashiro, Hiroyuki Ohta, Jun Sasagawa, Kiyotaka Graduate School of Science and Technology Nara Institute of Science and Technology Nara Ikoma Japan Radio Research Institute National Institute of Information and Communications Technology Koganei Tokyo Japan Graduate School of Science and Technology Nara Institute of Science and Technology Chitose Institute of Science and Technology Department of Opto-Electronic System Engineering Nara Hokkaido Chitose Ikoma Japan Graduate School of Science and Technology Nara Institute of Science and Technology Kyushu University Faculty of Medical Sciences Fukuoka Maidashi Ikoma Japan Institute for Research Initiatives Nara Institute of Science and Technology Nara Ikoma Japan

ISBN: (纸本)9798350363548

In this study, we developed an optical local oscillator signal generation system that tracks the frequency of the electric field to be observed. This system was applied to our highly sensitive electric field imaging system using the electro-optic (EO) effect. It enables electric field imaging by tracking a time-varying frequency wave source, such as frequency modulation (FM). Using this configuration, we successfully imaged at the edge of a PCB antenna with a signal modulated at 2.45 GHz, FM deviation of 100 kHz, and sweep frequency of 100 kHz. © 2024 IEEE.

关键词： CMOS integrated circuits

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A novel myocarditis detection combining deep reinforcement learning and an improved differential evolution algorithm

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CAAI Transactions on Intelligence technology 2024年第6期9卷 1347-1360页

作者： Jing Yang Touseef Sadiq Jiale Xiong Muhammad Awais Uzair Aslam Bhatti Roohallah Alizadehsani Juan Manuel Gorriz Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala LumpurMalaysia Centre for Artificial Intelligence Research(CAIR) Department of Information and Communication TechnologyUniversity of AgderGrimstadNorway Department of Creative Technologies Air UniversityIslamabadPakistan School of Information and Communication Engineering Hainan UniversityHaikouHainanChina Institute for Intelligent Systems Research and Innovation(IISRI) Deakin UniversityWaurn PondsVictoriaAustralia Data Science and Computational Intelligence Institute University of GranadaGranadaSpain

Myocarditis is a serious cardiovascular ailment that can lead to severe consequences if not promptly *** is triggered by viral infections and presents symptoms such as chest pain and heart *** detection is crucial for successful treatment,and cardiac magnetic resonance imaging(CMR)is a valuable tool for identifying this ***,the detection of myocarditis using CMR images can be challenging due to low contrast,variable noise,and the presence of multiple high CMR slices per *** overcome these challenges,the approach proposed incorporates advanced techniques such as convolutional neural networks(CNNs),an improved differential evolution(DE)algorithm for pre-training,and a reinforcement learning(RL)-based model for *** this method presented a significant challenge due to the imbalanced classification of the Z-Alizadeh Sani myocarditis dataset from Omid Hospital in *** address this,the training process is framed as a sequential decision-making process,where the agent receives higher rewards/penalties for correctly/incorrectly classifying the minority/majority ***,the authors suggest an enhanced DE algorithm to initiate the backpropagation(BP)process,overcoming the initialisation sensitivity issue of gradient-based methods like back-propagation during the training *** effectiveness of the proposed model in diagnosing myocarditis is demonstrated through experimental results based on standard performance ***,this method shows promise in expediting the triage of CMR images for automatic screening,facilitating early detection and successful treatment of myocarditis.

关键词： classification differential evolution myocarditis reinforcement learning

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Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection systems

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computers, Materials & Continua 2023年第2期74卷 2695-2709页

作者： Reem Alkanhel Doaa Sami Khafaga El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Rashid Amin Mostafa Abotaleb B.M.El-den Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of System Programming South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： Metaheuristics grey wolf optimization dipper throated optimization dataset balancing locality sensitive hashing SMOTE

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Dipper Throated Optimization for Detecting Black-Hole Attacks inMANETs

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computers, Materials & Continua 2023年第1期74卷 1905-1921页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security and privacy,mobile ad-hoc network(MANET)continues to be in demand for additional debate and *** more MANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,MANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost MANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-MLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

关键词： Black-hole attack mobile ad-hoc network optimization dipper throated optimization

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Integrating Minecraft Education in Curriculum Design to Enhance Chemistry Learning 28th

Integrating Minecraft Education in Curriculum Design to Enha...

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28th International Conference on Knowledge Based and Intelligent information and engineering systems, KES 2024

作者： Furukado, Ryousuke Zhu, Yan Hagiwara, Goichi Faculty of Engineering Integrated System Engineering Nishinippon Institute of Technology 1-11 Aratsu Miyako-gun Fukuoka800-0394 Japan Faculty of Human Science Department of Sport Science and Health Kyushu Sangyo University 2-3-1 Matsukadai Higasgi-ku Fukuoka-shi Fukuoka813-8503 Japan

This study aimed to develop an information and communication technology-based chemistry curriculum for Japanese junior high school students, utilizing the learning platform provided by Minecraft Education. We crafted content for a series of seven lessons, aiming to evaluate the short-term educational impacts of Minecraft Education and enhance the review process, which is often neglected. Features were integrated to maximize the game's functionality, increase its entertainment value, and sustain student motivation. Future work will focus on delineating the necessary teaching skills for educators to effectively utilize Minecraft Education and on the collection and assessment of empirical data. © 2024 The Authors.

关键词： Students

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Message Verification Protocol Based on Bilinear Pairings and Elliptic Curves for Enhanced Security in Vehicular Ad Hoc Networks

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computers, Materials & Continua 2024年第10期81卷 1029-1057页

作者： Vincent Omollo Nyangaresi Arkan A.Ghaib Hend Muslim Jasim Zaid Ameen Abduljabbar Junchao Ma Mustafa A.Al Sibahee Abdulla J.Y.Aldarwish Ali Hasan Ali Husam A.Neamah Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and TechnologyBondo40601Kenya Department of Applied Electronics Saveetha School of EngineeringSIMATSChennaiTamilnadu602105India Information Technology Department Management Technical CollegeSouthern Technical UniversityBasrah61004Iraq Department of Computer Science College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq College of Big Data and Internet Shenzhen Technology UniversityShenzhen518118China Huazhong University of Science and Technology Shenzhen InstituteShenzhen518000China National Engineering Laboratory for Big Data System Computing Technology Shenzhen UniversityShenzhen518060China Computer Technology Engineering Department Iraq University CollegeBasrah61004Iraq Department of Mathematics College of Education for Pure SciencesUniversity of BasrahBasrah61004Iraq Institute of Mathematics University of DebrecenDebrecenH-4002Hungary Department of Electrical Engineering and Mechatronics Faculty of EngineeringUniversity of DebrecenDebrecen4028Hungary

Vehicular ad hoc networks(VANETs)provide intelligent navigation and efficient route management,resulting in time savings and cost reductions in the transportation ***,the exchange of beacons and messages over public channels among vehicles and roadside units renders these networks vulnerable to numerous attacks and privacy *** address these challenges,several privacy and security preservation protocols based on blockchain and public key cryptography have been proposed ***,most of these schemes are limited by a long execution time and massive communication costs,which make them inefficient for on-board units(OBUs).Additionally,some of them are still susceptible to many *** such,this study presents a novel protocol based on the fusion of elliptic curve cryptography(ECC)and bilinear pairing(BP)*** formal security analysis is accomplished using the Burrows–Abadi–Needham(BAN)logic,demonstrating that our scheme is verifiably *** proposed scheme’s informal security assessment also shows that it provides salient security features,such as non-repudiation,anonymity,and ***,the scheme is shown to be resilient against attacks,such as packet replays,forgeries,message falsifications,and *** the performance perspective,this protocol yields a 37.88%reduction in communication overheads and a 44.44%improvement in the supported security ***,the proposed scheme can be deployed in VANETs to provide robust security at low overheads.

关键词： Attacks bilinear elliptic curve cryptography(ECC) privacy security vehicular ad hoc network(VANET)

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Single Block Encoder-Decoder Transformer Model for Multi-Step Traffic Flow Forecasting 6

Single Block Encoder-Decoder Transformer Model for Multi-Ste...

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6th IEEE Symposium on computers and Informatics, ISCI 2024

作者： Omar, Mas Yakub, Fitri Talip, Mohamad Sofian Abu Maslan, Mohd Nazmin Sinha, Vijay Kumar Muljono, Muljono Universiti Teknologi Malaysia Wee Laboratory Malaysia-Japan International Institute of Technology Kuala Lumpur Malaysia Universiti Teknologi Malaysia Malaysia-Japan International Institute of Technology Department of Electronic System Engineering Kuala Lumpur Malaysia University of Malaya Faculty of Engineering Department of Electrical Engineering Kuala Lumpur Malaysia Universiti Teknikal Malaysia Faculty of Industrial and Manufacturing Technology and Engineering Melaka Malaysia Chitkara University School of Engineering & Technology Department of Computer Science & Engineering Himachal Pradesh India Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350353853

Accurate traffic flow forecasting is crucial for managing and planning urban transportation systems. Despite the widespread use of sequence modelling models like Long Short-Term Memory (LSTM) for this purpose, the potential of Transformer models remains underexplored. This is particularly true for the simplest form of a single block encoder-decoder Transformer model, which can be finely tuned through optimised hyperparameters. This paper examines the performance of a singular horizon-step forecasting method for multi-step traffic flow forecasting using a proposed Single Block Encoder-Decoder Transformer model optimised with a Grid Search algorithm. Results demonstrate that this model can enhance forecasting accuracy compared to the state-of-the-art LSTM model typically used for multi-step forecasting. The model effectively captures long-range temporal dependencies within a single road traffic flow dataset. It was tested on hourly traffic flow data to forecast the next 24 hours for the I5-North freeway in California, sourced from the Caltrans Performance Measurement system. The optimal configuration included an embedding dimension of 32, a feed-forward dimension of 128, and 8 attention heads. Results show a significant improvement, with a 4.7% reduction in Root Mean Squared Error compared to an LSTM model with two hidden layers of 100 neurons each, showcasing the potential of Single Block Encoder-Decoder Transformer models for real-world traffic prediction applications. © 2024 IEEE.

关键词： Mean square error

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