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Multi-Task Visual Semantic Embedding Network for Image-Text Retrieval

Journal of computer science & Technology 2024年第4期39卷 811-826页

作者： Xue-Yang Qin Li-Shuang Li Jing-Yao Tang Fei Hao Mei-Ling Ge Guang-Yao Pang School of Computer Science and Technology Dalian University of TechnologyDalian 116024China School of Computer Science Shaanxi Normal UniversityXi’an 710119China School of Computer Engineering Weifang UniversityWeifang 261061China Guangxi Colleges and Universities Key Laboratory of Intelligent Industry Software Wuzhou UniversityWuzhou 543002 China

Image-text retrieval aims to capture the semantic correspondence between images and texts,which serves as a foundation and crucial component in multi-modal recommendations,search systems,and online *** mainstream methods primarily focus on modeling the association of image-text pairs while neglecting the advantageous impact of multi-task learning on image-text *** this end,a multi-task visual semantic embedding network(MVSEN)is proposed for image-text ***,we design two auxiliary tasks,including text-text matching and multi-label classification,for semantic constraints to improve the generalization and robustness of visual semantic embedding from a training ***,we present an intra-and inter-modality interaction scheme to learn discriminative visual and textual feature representations by facilitating information flow within and between ***,we utilize multi-layer graph convolutional networks in a cascading manner to infer the correlation of image-text *** results show that MVSEN outperforms state-of-the-art methods on two publicly available datasets,Flickr30K and MSCOCO,with rSum improvements of 8.2%and 3.0%,respectively.

关键词： image-text retrieval cross-modal retrieval multi-task learning graph convolutional network

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A Survey on Evolutionary Computation Based Drug Discovery

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IEEE Transactions on Evolutionary Computation 2024年第3期29卷 1-1页

作者： Yu, Qiyuan Lin, Qiuzhen Ji, Junkai Zhou, Wei He, Shan Zhu, Zexuan Tan, Kay Chen College of Computer Science and Software Engineering Shenzhen University Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China School of Computer Science University of Birmingham Bir-mingham UK Department of Computing The Hong Kong Poly-technic University Hong Kong Hong Kong

Drug discovery is an expensive and risky process. To combat the challenges in drug discovery, an increasing number of researchers and pharmaceutical companies recognize the benefits of utilizing computational techniques. Evolutionary computation (EC) offers promise as most drug discovery problems are essentially complex optimization problems beyond conventional optimization algorithms. EC methods have been widely applied to solve these complex optimization problems especially in lead com-pound generation and molecular virtual evaluation, substantially speeding up the process of drug discovery and development. This article presents a comprehensive survey of EC-based drug discovery methods. Particularly, a new taxonomy of the methods is provided and the advantages and limitations of the methods are reviewed. In addition, the potential future directions of EC-based drug discovery are discussed and the publicly available resources including databases and computational tools are compiled for the convenience of researchers seeking to pursue this field. IEEE

关键词： Lead compounds

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Survey of Distributed Computing Frameworks for Supporting Big Data Analysis

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Big Data Mining and Analytics 2023年第2期6卷 154-169页

作者： Xudong Sun Yulin He Dingming Wu Joshua Zhexue Huang College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen 518107China

Distributed computing frameworks are the fundamental component of distributed computing *** provide an essential way to support the efficient processing of big data on clusters or *** size of big data increases at a pace that is faster than the increase in the big data processing capacity of ***,distributed computing frameworks based on the MapReduce computing model are not adequate to support big data analysis tasks which often require running complex analytical algorithms on extremely big data sets in *** performing such tasks,these frameworks face three challenges:computational inefficiency due to high I/O and communication costs,non-scalability to big data due to memory limit,and limited analytical algorithms because many serial algorithms cannot be implemented in the MapReduce programming *** distributed computing frameworks need to be developed to conquer these *** this paper,we review MapReduce-type distributed computing frameworks that are currently used in handling big data and discuss their problems when conducting big data *** addition,we present a non-MapReduce distributed computing framework that has the potential to overcome big data analysis challenges.

关键词： distributed computing frameworks big data analysis approximate computing MapReduce computing model

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Enhancing Communication Accessibility:UrSL-CNN Approach to Urdu Sign Language Translation for Hearing-Impaired Individuals

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computer Modeling in engineering & sciences 2024年第10期141卷 689-711页

作者： Khushal Das Fazeel Abid Jawad Rasheed Kamlish Tunc Asuroglu Shtwai Alsubai Safeeullah Soomro Department of Computer Engineering Modeling Electronics and Systems EngineeringUniversity of CalabriaRende Cosenza87036Italy Department of Information Systems University of Management and TechnologyLahore54770Pakistan Department of Computer Engineering Istanbul Sabahattin Zaim UniversityIstanbul34303Turkey Department of Software Engineering Istanbul Nisantasi UniversityIstanbul34398Turkey Department of Computer Science COMSATS University IslamabadLahore CampusLahore54700Pakistan Faculty of Medicine and Health Technology Tampere UniversityTampere33720Finland Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam Bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Second Department of Computer Science College of Engineering and ComputingGeorge Mason UniversityFairfaxVA 4418USA

Deaf people or people facing hearing issues can communicate using sign language(SL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other SLs,the visuals of the Urdu Language are *** study presents a novel approach to translating Urdu sign language(UrSL)using the UrSL-CNN model,a convolutional neural network(CNN)architecture specifically designed for this *** existingworks that primarily focus on languageswith rich resources,this study addresses the challenge of translating a sign language with limited *** conducted experiments using two datasets containing 1500 and 78,000 images,employing a methodology comprising four modules:data collection,pre-processing,categorization,and *** enhance prediction accuracy,each sign image was transformed into a greyscale image and underwent noise *** analysis with machine learning baseline methods(support vectormachine,GaussianNaive Bayes,randomforest,and k-nearest neighbors’algorithm)on the UrSL alphabets dataset demonstrated the superiority of UrSL-CNN,achieving an accuracy of ***,our model exhibited superior performance in Precision,Recall,and F1-score *** work not only contributes to advancing sign language translation but also holds promise for improving communication accessibility for individuals with hearing impairments.

关键词： Convolutional neural networks Pakistan sign language visual language

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WIP: An Engaging Undergraduate Intro to Model Checking in software engineering Using TLA+ 54

WIP: An Engaging Undergraduate Intro to Model Checking in So...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Läufer, Konstantin Mertin, Gunda Thiruvathukal, George K. Loyola University Software and Systems Laboratory Department of Computer Science Chicago United States Institute for Software Engineering and Programming Languages University of Lübeck Germany

ISBN: (纸本)9798350351507

Background: In this Innovative Practice Work in Progress, we present our initial efforts to integrate formal methods, with a focus on model-checking specifications written in Temporal Logic of Actions (TLA+), into computer science education, targeting undergraduate juniors/seniors and graduate students. Many safety-critical systems and services crucially depend on correct and reliable behavior. Formal methods can play a key role in ensuring correct and safe system behavior, yet remain underutilized in educational and industry contexts. Aims: We aim to (1) qualitatively assess the state of formal methods in computer science programs, (2) construct level-appropriate examples that could be included midway into one's undergraduate studies, (3) demonstrate how to address successive 'failuresy' through progressively stringent safety and liveness requirements, and (4) establish an ongoing framework for assessing interest and relevance among students. Methods: We detail our pedagogical strategy for embedding TLA+ into an intermediate course on formal methods at our institution. After starting with a refresher on mathematical logic, students specify the rules of simple puzzles in TLA+ and use its included model checker (known as TLC) to find a solution. We gradually escalate to more complex, dynamic, event-driven systems, such as the control logic of a microwave oven, where students will study safety and liveness requirements. We subsequently discuss explicit concurrency, along with thread safety and deadlock avoidance, by modeling bounded counters and buffers. Results: Our initial findings suggest that through careful curricular design and choice of examples and tools, it is possible to inspire and cultivate a new generation of software engineers proficient in formal methods. Conclusions: Our initial efforts suggest that 84% of our students had a positive experience in our formal methods course. Our future plans include a longitudinal analysis within our own institution and

关键词： Students

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Gastrointestinal Diseases Classification Using Deep Transfer Learning and Features Optimization

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computers, Materials & Continua 2023年第4期75卷 2227-2245页

作者： Mousa Alhajlah Muhammad Nouman Noor Muhammad Nazir Awais Mahmood Imran Ashraf Tehmina Karamat College of Applied Computer Science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Engineering HITEC UniversityTaxila47080Pakistan Department of Software Engineering Foundation University IslamabadIslamabad44000Pakistan

Gastrointestinal diseases like ulcers, polyps’, and bleeding areincreasing rapidly in the world over the last decade. On average 0.7 millioncases are reported worldwide every year. The main cause of gastrointestinaldiseases is a Helicobacter Pylori (H. Pylori) bacterium that presents in morethan 50% of people around the globe. Many researchers have proposeddifferent methods for gastrointestinal disease using computer vision *** of them focused on the detection process and the rest of themperformed classification. The major challenges that they faced are the similarityof infected and healthy regions that misleads the correct classificationaccuracy. In this work, we proposed a technique based on Mask Recurrent-Convolutional Neural Network (R-CNN) and fine-tuned pre-trainedResNet-50 and ResNet-152 networks for feature extraction. Initially, the region ofinterest is detected using Mask R-CNN which is later utilized for the trainingof fine-tuned models through transfer learning. Features are extracted fromfine-tuned models that are later fused using a serial approach. Moreover, anImproved Ant Colony Optimization (ACO) algorithm has also opted for thebest feature selection from the fused feature vector. The best-selected featuresare finally classified using machine learning techniques. The experimentalprocess was conducted on the publicly available dataset and obtained animproved accuracy of 96.43%. In comparison with state-of-the-art techniques,it is observed that the proposed accuracy is improved.

关键词： Diseases deep learning endoscopy gastrointestinal tract transfer learning

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Dynamic Multimedia Encryption Using a Parallel File System Based on Multi-Core Processors 4

Dynamic Multimedia Encryption Using a Parallel File System B...

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4th IEEE International Conference on Data engineering and Communication Systems, ICDECS 2024

作者： Simi Margarat, G. Malathi, S. Pasumpon Pandian, A. Anakath, A.S. Kannadasan, R. New Prince Shri Bhavani College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Grt Institute of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Tiruttani India Care College of Engineering Department of Computer Science and Engineering Trichy India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India School of Computer Science and Engineering Department of Software Systems Tamil Nadu Vellore India

ISBN: (纸本)9798350393354

A new parallel file system and multi-core processor-based dynamic multimedia encryption method is presented in this study. Multimedia encryption efficiency and security were the main goals, addressing massive data sets and high-speed processing. We created a dynamic encryption algorithm for multimedia content, supported by a strong parallel file system and tuned for multi-core processing. Multiple tests showed significant improvements in encryption and decryption times, retaining short durations for real-time applications. After encryption, the system maintained multimedia content quality and accuracy with data integrity rates nearing 100%. Balanced CPU utilization showed efficient resource use and processor load management. The system's excellent throughput efficiency showed its capacity to process enormous amounts of data. These results indicate that parallel file systems and multi-core CPUs may solve multimedia encryption problems. Adaptable and scalable, the system supports many multimedia formats and sizes. This paper proposes a multimedia encryption system that improves performance data security and integrity, paving the way for safe multimedia processing advances. © 2024 IEEE.

关键词： Cryptography

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Less Traces Are All It Takes: Efficient Side-Channel Analysis on AES

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IEEE Transactions on computer-Aided Design of Integrated Circuits and Systems 2024年第6期44卷 2080-2092页

作者： Xiao, Zhiyuan Wang, Chen Shen, Jian Wu, Q. M. Jonathan He, Debiao Zhejiang Sci-Tech University School of Information Science and Engineering School of Cyber Science and Technology the Zhejiang Provincial Key Laboratory of Digital Fashion and Data Governance Zhejiang Provincial International Cooperation Base for Science and Technology on Cloud Computing Security and Data Aggregation Hangzhou310018 China University of Windsor Department of Electrical and Computer Engineering WindsorON Canada Wuhan University State Key Laboratory of Software Engineering Computer School Wuhan430072 China

In cryptography, side-channel analysis (SCA) is a technique used to recover cryptographic keys by examining the physical leakages that occur during the operation of cryptographic devices. Recent advancements in Deep Learning (DL) have greatly enhanced the extraction of crucial information from intricate leakage patterns. A considerable amount of research is dedicated to studying the SubByte (SB) operations of the advanced encryption standard (AES). This is because the SB process, which generates numerous transitions between 0s and 1s during encryption, results in significant energy leakage. However, traditional analysis models primarily focus on the initial round of SB operations in AES, which are less effective on mobile terminals where it is difficult to collect enough signals. These models often neglect additional operations and subsequent rounds, thus providing limited insights from small datasets. Consequently, this limitation has a direct impact on the accuracy and efficiency of key recovery. Our study uses ρ-test analysis to show that significant leakage occurs not only during the S-box operation but also during the AddRoundKey (AR) phase of AES. To address these challenges, we propose a new SCA method that is optimized for small sample sizes. This method includes a new comprehensive round trace labeling algorithm, which simultaneously analyzes the SB and AR stages of each AES round. Additionally, we introduce the peak precise localization algorithm to accurately identify the points of energy leakage during each encryption round. Our experiments, conducted with power and Electromagnetic (EM) datasets from the STM32F303 microcontroller, demonstrate that our method can reliably recover keys with as few as 20 traces. These results highlight the enhanced capability of our method in handling the complexities of small sample datasets in cryptographic analysis. © 2024 IEEE.

关键词： Information leakage

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Programming Education for Young People using the Falling-Puzzle Game, 'Puyo Puyo' 14

Programming Education for Young People using the Falling-Puz...

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14th IEEE Global engineering Education Conference, EDUCON 2023

作者： Saito, Daisuke Tian, Ruochen Washizaki, Hironori Fukazawa, Yoshiaki Waseda University Global Software Engineering Laboratory Tokyo Japan Waseda University Department of Computer Science and Engineering Tokyo Japan

ISBN: (纸本)9798350399431

This study utilizes the game rules of a falling-puzzle game, developed as a consumer-oriented digital game, in programming education for young people. When digital games are used in programming education, they are often designed specifically for that purpose. In this study, we focused on the game rules of the consumer falling-object puzzle game, 'Puyo Puyo.' Learning impact was investigated on 23 Japanese elementary, junior high, and senior high school students. The results show that the concepts of branching and arraying in programming were taught effectively;thus, consumer digital game rules can be used as a case study for programming education. © 2023 IEEE.

关键词： E-learning

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Improved Belief Propagation Decoder for LDPC-CRC-Polar Codes with Bit-Freezing

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China Communications 2024年第7期21卷 135-148页

作者： Qasim Jan Yin Chao Pan Zhiwen Muhammad Furqan Zakir Ali You Xiaohu National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211100China Department of Computer Science National University of Computer and Emerging Sciences Peshawar Campus 25100Pakistan Department of Software Engineering Capital University of Science and Technology(CUST)Islamabad 44000Pakistan Department of Computer Sciences Bahria University Lahore CampusPakistan

Though belief propagation bit-flip(BPBF)decoding improves the error correction performance of polar codes,it uses the exhaustive flips method to achieve the error correction performance of CA-SCL decoding,thus resulting in high decoding complexity and *** alleviate this issue,we incorporate the LDPC-CRC-Polar coding scheme with BPBF and propose an improved belief propagation decoder for LDPC-CRC-Polar codes with bit-freezing(LDPCCRC-Polar codes BPBFz).The proposed LDPCCRC-Polar codes BPBFz employs the LDPC code to ensure the reliability of the flipping set,i.e.,critical set(CS),and dynamically update *** modified CS is further utilized for the identification of error-prone *** proposed LDPC-CRC-Polar codes BPBFz obtains remarkable error correction performance and is comparable to that of the CA-SCL(L=16)decoder under medium-to-high signal-to-noise ratio(SNR)*** gains up to 1.2dB and 0.9dB at a fixed BLER=10-4compared with BP and BPBF(CS-1),*** addition,the proposed LDPC-CRC-Polar codes BPBFz has lower decoding latency compared with CA-SCL and BPBF,i.e.,it is 15 times faster than CA-SCL(L=16)at high SNR regions.

关键词： belief propagation bit-flipping concatenated codes LDPC-CRC-Polar codes polar codes

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