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IEEE International Conference on Joint Cloud Computing (JCC)

作者： Jianfei Liu Huaimin Wang Peichang Shi Yaojie Li Penghui Ma Guodong Yi National Key Laboratory of Parallel and Distributed Computing College of Computer Science National University of Defense Technology Changsha 410073 China Key Laboratory of Software Engineering for Complex Systems College of Computer Science National University of Defense Technology Changsha 410073 China Xiangjiang Lab Changsha 410073 China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha 410073 China

As a new stage in the development of the cloud computing paradigm, serverless computing has the high-level abstraction characteristic of shielding underlying details. This makes it extremely challenging for users to choose a suitable serverless platform. To address this, targeting the jointcloud computing scenario of heterogeneous serverless platforms across multiple clouds, this paper presents a jointcloud collaborative mechanism called FCloudless with cross-cloud detection of the full lifecycle performance of serverless platforms. Based on the benchmark metrics set that probe performance critical stages of the full lifecycle, this paper proposes a performance optimization algorithm based on detected performance data that takes into account all key stages that affect the performance during the lifecycle of a function and predicts the overall performance by combining the scores of local stages and dynamic weights. We evaluate FCloudless on AWS, AliYun, and Azure. The experimental results show that FCloudless can detect the underlying performance of serverless platforms hidden in the black box and its optimization algorithm can select the optimal scheduling strategy for various applications in a jointcloud environment. FCloudless reduces the runtime by 23.3% and 24.7% for cold and warm invocations respectively under cost constraints.

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Word-level BERT-CNN-RNN Model for Chinese Punctuation Restoration 6

Word-level BERT-CNN-RNN Model for Chinese Punctuation Restor...

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6th IEEE International Conference on computer and Communications, ICCC 2020

作者： Zhang, Zhe Liu, Jie Chi, Lihua Chen, Xinhai Science and Technology on Parallel and Distributed Processing Laboratory Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China College of Computer Science and Electronic Engineering Hunan University Changsha China

ISBN: (纸本)9781728186351

Punctuation restoration in speech recognition has a wide range of application scenarios. Despite the widespread success of neural networks methods at performing punctuation restoration for English, there have been only limited attempts for Chinese punctuation restoration. Due to the differences between Chinese and English in terms of grammar and basic semantic units, existing methods for English is not suitable for Chinese punctuation restoration. To tackle this problem, we propose a hybrid model combining the kernel of Bidirectional Encoder Representations from Transformers (BERT), Convolution Neural Network (CNN) and Recurrent Neural Network (RNN). This model employs a flexible structure and special CNN design which can extract word-level features for Chinese language. We compared the performance of the hybrid model with five widely-used punctuation restoration models on the public dataset. Experimental results demonstrate that our hybrid model is simple and efficient. It outperforms other models and achieves an accuracy of 69.1%. © 2020 IEEE.

关键词： Recurrent neural networks

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A Review of Algorithms’s Complexities on Different Valued Sorted and Unsorted Data

A Review of Algorithms’s Complexities on Different Valued S...

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IT and Industrial Technologies (ICIT), International Conference on

作者： Attia Shabbir Asad Majeed Mahnoor Iftikhar Raja Hashim Ali Usama Arshad Muhammad Zeeshan Shabbir Ali Zeeshan Ijaz Nisar Ali Ali Aftab Faculty of Computer Science & Engineering GIK Institute of Engg. Sciences & Technology Topi Pakistan Dept. of Technology & Software Engineering University of Europe for Applied Sciences Berlin Germany Department of Electrical Engineering University of Engineering & Technology (UET) Lahore Pakistan Faculty of Electronic Systems Engineering University of Regina Regina Canada

Sorting and searching are critical processes for effecttive data analysis. In this paper, we evaluate the performance of various sorting and searching algorithms and compare their time and space complexities on both sorted and unsorted data. The algorithms we analyzed include six common sorting algorithms (insertion, radix, bucket, merge, bubble, and quick sort) and three search algorithms (linear, binary, and jump search). The results of our study provide insights into the best algorithms to use for different input sizes and types of data. It was found that for small input sizes, all algorithms perform similarly, but for larger input sizes, insertion and radix sorts are better for time complexity while bubble sort is better for space complexity. Additionally, jump search outperformed linear and binary search algorithms in both time and space complexity. Besides, difference between time and space complexity of sorted and unsorted data was significant.

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Using Orthogonal Signals to Hide Information in Images 4

Using Orthogonal Signals to Hide Information in Images

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4th IEEE International Conference on Advanced Information and Communication Technologies, AICT 2021

作者： Kuznetsov, Alexandr Lokotkova, Iryna Smirnov, Oleksii Kuznetsova, Tetiana Florov, Serhii Lebid, Oksana Vn Karazin Kharkiv National University Department of Information Systems and Technologies Security Kharkiv Ukraine Central Ukrainian National Technical University Cybersecurity and Software Academic Department Kropivnitskiy Ukraine Dnipro University of Technology Department of Information Security and Telecommunications Dnipro Ukraine University of Customs and Finance Department of Computer Science and Software Engineering Dnipro Ukraine

ISBN: (纸本)9781665406185

Spread-Spectrum Steganography (SSS) technology is used to hide information messages in image containers. For this purpose, propagating discrete signals are used, in specially formed pseudo-random sequences (PRS) with special correlation properties. This technology is similar to the direct-sequence spread spectrum (DSSS) used in telecommunications systems to reduce the effects of random noise in information channels. The properties of expansion PRS directly affect the quality of communication in DSSS and, accordingly, the efficiency of SSS. This article investigates various methods of PRS formation and conducts experiments to assess the intensity of bit errors and the quality of the image container. We show that it is most appropriate to use orthogonal discrete Walsh-Hadamard signals that provide the best performance. © 2021 IEEE.

关键词： Signal to noise ratio

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S2KAN-SLAM: Elastic Neural LiDAR SLAM with SDF Submaps and Kolmogorov-Arnold Networks

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IEEE Transactions on Circuits and systems for Video Technology 2025年

作者： Wang, Zhong Zhang, Lin Wang, Hesheng Shanghai Jiao Tong University State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China Tongji University School of Computer Science and Technology National Pilot Software Engineering School with Chinese Characteristics Shanghai201804 China

Traditional LiDAR SLAM approaches prioritize localization over mapping, yet high-precision dense maps are essential for numerous applications involving intelligent agents. Recent advancements have introduced methods leveraging neural fields to enhance mapping capabilities;however, these approaches still face several limitations. Firstly, concerning scene representation, they typically employ neural fields with high-dimensional features and multi-layer perceptron decoders utilizing non-continuous activation functions. This results in low learning efficiency and challenges in capturing high-frequency signals. Secondly, in terms of scene organization, these methods often treat the entire scene as a singular neural field, leading to inefficiencies, inflexibility, and difficulties in rectifying accumulated errors when mapping large-scale environments over extended periods. To tackle the first issue, we propose a lightweight continuous SDF regression approach by encoding the scene in single-valued embeddings and decoding SDF values from a Kolmogorov-Arnold Network. By minimizing discrepancies in measuring range, sampling distance, and decoded SDF values, we facilitate iterative frame-to-model tracking and bundle adjustment neural mapping. To mitigate the second challenge, we propose structuring the whole scene into multiple neural SDF submaps. By establishing node-node, node-submap, and loop closure constraints into a global pose graph, the system can create dense neural maps with global consistency across large-scale scenes. Experimental evaluations in both real-world and simulated settings indicate that our system achieves superior mapping completeness and accuracy, enhanced learning efficiency, reduced memory consumption, and greater flexibility compared to its counterparts. © 2025 IEEE.

关键词： Mapping

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A Perspective on the Role of Human Behaviors in software Development: Voice and Silence

arXiv

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arXiv 2023年

作者： Sánchez-Gordón, Mary Colomo-Palacios, Ricardo Akbar, Muhammad Azeem Holone, Monica Kristiansen Department of Computer Science and Communication Øsfold University College Halden Norway Escuela Técnica Superior de Ingenieros Informáticos Universidad Politécnica de Madrid Madrid Spain Software Engineering Department and Systems LUT University Lappeenranta Finland

Context: Most software companies strive to have high-performing teams and mitigate withdrawal behaviors like being present but unproductive. In this context, psychological safety and developers’ perceived impact are suggested as potential drivers of voice and silence behaviors. However, understanding these social aspects of software development entails the incorporation of social science theories . Objective: This study aims to empirically demonstrate whether such a new theory about voice and silence at work actually applies to the software development context. Method: We plan to use a survey questionnaire design. This study will collect data from software development teams and analyze the result using structural equation modeling (SEM) technique. It can contribute to extent of the body of knowledge about the topic. Copyright © 2023, The Authors. All rights reserved.

关键词： Social aspects

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Authentic Learning on DevOps Security with Labware: Git Hooks To Facilitate Automated Security Static Analysis

Authentic Learning on DevOps Security with Labware: Git Hook...

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IEEE Annual International computer software and Applications Conference (COMPSAC)

作者： Md Mostafizur Rahman MD Abdul Barek Mst Shapna Akter Abm Kamrul Islam Riad Md Abdur Rahman Hossain Shahriar Akond Rahman Fan Wu Department of Information Technology University of West Florida Florida USA Department of Intelligent Systems and Robotics University of West Florida Florida USA Center for Cyber Security University of West Florida Florida USA Dept. of Computer Science and Software Engineering Auburn University USA Tuskegee University Alabama USA

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

This paper presents an innovative approach to DevOps security education, addressing the dynamic landscape of cybersecurity threats. We propose a student-centered learning methodology by developing comprehensive hands-on learning modules. Specifically, we introduce labware modules designed to automate static security analysis, empowering learners to identify known vulnerabilities efficiently. These modules offer a structured learning experience with pre-lab, hands-on, and post-lab sections, guiding students through DevOps concepts and security challenges. In this paper, we introduce hands-on learning modules that familiarize students with recognizing known security flaws through the application of Git Hooks. Through prac-tical exercises with real-world code examples containing security flaws, students gain proficiency in detecting vulnerabilities using relevant tools. Initial evaluations conducted across educational institutions indicate that these hands-on modules foster student interest in software security and cybersecurity and equip them with practical skills to address DevOps security vulnerabilities.

关键词： Learning systems DevOps Codes Education Static analysis Dynamic scheduling software

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DESIGN OF MECHANISMS FOR ENSURING THE EXECUTION OF TASKS IN PROJECT PLANNING

arXiv

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arXiv 2025年

作者： Mulesa, Oksana Horvat, Petro Radivilova, Tamara Sabadosh, Volodymyr Baranovskyi, Oleksii Duran, Sergii Department of Software Systems Uzhhorod National University Narodna sq. 3 Uzhhorod88000 Ukraine Department of Computer Systems and Networks Uzhhorod National University Narodna sq. 3 Uzhhorod88000 Ukraine V. V. Popovskyy Department of Infocommunication Engineering Kharkiv National University of Radio Electronics Nauky ave. 14 Kharkiv61166 Ukraine Intellias Company Kapushanska str. 177 А Uzhhorod88000 Ukraine Department of Computer Science Blekinge Institute of Technology Blekinge Karlskrona37179 Sweden

This paper reports an analysis of aspects of the project planning stage. The object of research is the decision-making processes that take place at this stage. This work considers the problem of building a hierarchy of tasks, their distribution among performers, taking into account restrictions on financial costs and duration of project implementation. Verbal and mathematical models of the task of constructing a hierarchy of tasks and other tasks that take place at the stage of project planning were constructed. Such indicators of the project implementation process efficiency were introduced as the time, cost, and cost-time efficiency. In order to be able to apply these criteria, the tasks of estimating the minimum value of the duration of the project and its minimum required cost were considered. Appropriate methods have been developed to solve them. The developed iterative method for assessing the minimum duration of project implementation is based on taking into account the possibility of simultaneous execution of various tasks. The method of estimating the minimum cost of the project is to build and solve the problem of Boolean programming. The values obtained as a result of solving these problems form an «ideal point», approaching which is enabled by the developed iterative method of constructing a hierarchy of tasks based on the method of sequential concessions. This method makes it possible to devise options for management decisions to obtain valid solutions to the problem. According to them, the decision maker can introduce a concession on the value of one or both components of the «ideal point» or change the input data to the task. The models and methods built can be used when planning projects in education, science, production, *** Codes 90B50 Copyright © 2025, The Authors. All rights reserved.

关键词： Efficiency

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Development of a prototype of an intelligent system for predicting the quality of dairy manufacture

Development of a prototype of an intelligent system for pred...

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International IEEE Conference on Intelligent systems, IS

作者： Yaroslav Smitiukh Yuliia Samoilenko Yuliia Kostiuk Olena Kryvoruchko Kateryna Stepashkina department of automation and computer technologies of control systems National University of Food Technologies Kyiv Ukraine department of software engineering and cyber security State University of Trade and Economics Kyiv Ukraine

ISBN: (纸本)9781665492768

The technological process of the churning process in continuous butter manufacture were considered. The qualitative indicator of the water content of butter was modeled on the basis of a set of industrial data using an artificial neural network (ANN). The prototype of an intelligent system for predicting of the water content of butter allows to increase the information support of the operator-technologist. The proposed model predicts the water content of butter with an error of less than 2%. The input variables of the forecast model prototype are cream fat content, cream ripening temperature, cream supply temperature, frequency of revolutions of the stirrer of the whipping device, and consumption of the normalizing component. Further research is aimed at the development of a decision support information system for dairy manufacture and should be integrated into the subsystem of automated control of the technological process to ensure proper functioning in real time.

关键词： Productivity Dairy products Simulation Prototypes Process control Artificial neural networks Predictive models

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Automative Video Compression for Remote Driving via Safety Considerations

Automative Video Compression for Remote Driving via Safety C...

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IEEE Conference on Standards for Communications and Networking (CSCN)

作者： Dan Peled Armin Shmilovici Ofer Hadar The Department of Software and Information Systems Engineering Ben-Gurion University of the Negev P.O.Box 653 Beer Sheva Israel School of Electrical and Computer Engineering Ben-Gurion University of the Negev P.O.Box 653 Beer Sheva Israel

Remote driving serves as a viable solution in situations where fully autonomous vehicles encounter critical events, such as sensor failures. However, implementing remote driving poses certain technical challenges, including the need to ensure high-quality video transmission to the remote driver. Additionally, in scenarios involving poor road conditions, multiple autonomous vehicles may simultaneously require remote driving assistance at specific locations, straining the communication infrastructure. To address these challenges, we propose a novel approach that involves compression of the driving video using a driving safety model. This model intelligently prioritizes key objects within the frame, resulting in improved compression quality. An initial experiment demonstrated that 60% of the required bitrate can be reduced while retaining 90% of the perceived quality.

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