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arXiv 2022年

作者： O’Sullivan, Cathal Sorenson, Jonathan P. Stahl, Aryn Mathematics Statistics and Actuarial Science Department Computer Science and Software Engineering Department Butler University IndianapolisIN United States Computer Science and Software Engineering Department Butler University IndianapolisIN United States Physics and Astronomy Department Computer Science and Software Engineering Department Butler University IndianapolisIN United States

We present and analyze algorithms to count and enumerate all integers n ≤ x that can be written as the sum of consecutive kth powers of primes, for fixed k > 1. We show that the number of such integers n is asymptotically bounded by ck x2/(k+1)/(log x)2k/(k+1), where ck is a constant depending solely on k, roughly k2 in magnitude. We also give an asymptotic lower bound of the form (k + 1)2/2 x2/(k+1)/(log x)2k/(k+1) . 2 Our enumeration algorithm is optimal, in that it constructs all such integers n ≤ x using a constant number of arithmetic operations for each n. Our algorithm to count such n takes time proportional to the number of primes up to x1/k, so that finding this list of primes is the bottleneck in its runtime. We also present some computational results, using our new algorithms, that provide empirical data to support our theoretical results. Our work extends the previous work by Tongsomporn, Wananiyakul, and Steuding [6] who examined sums of squares of consecutive *** Codes 11A41, 68Q25 Copyright © 2022, The Authors. All rights reserved.

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An Ontology-Based Approach to Automated Test Case Generation

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SN computer Science 2021年第1期2卷 35页

作者： Banerjee, Shreya Debnath, Narayan C. Sarkar, Anirban Department of Software Engineering Eastern International University Binh Duong Province Thu Dao Mot City Viet Nam Department of Computer Science and Engineering National Institute of Technology Durgapur India

software testing is as old as software itself. However, the techniques, tools, and processes used by researchers to ensure product quality are constantly evolving. Application of knowledge management technologies in automated test case generation is one of them. This paper addressed the issue of ontology-based automated test case generation in the case of black box testing. In this context, several challenges are present in existing literature. The prime challenges among are (1) major approaches are confined to a specific domain, (2) least consideration about modified domain knowledge, (3) lack of methodology for auto-identification of pre-conditions and different combinations among test input data and (4) poor requirements and domain coverage. The proposed methodology, in this paper, is aimed to resolve these issues by devising a rule-based reasoner that can auto generate the test cases. The proposed method takes an ontology-based requirements specification as an input. The novelty of the proposed method is the specification of domain independent inference rules based on which the devised reasoner can generate test cases for different domains and systems automatically. This contribution of the proposed work facilitates in improving both user’s requirements coverage and domain coverage. The devised reasoned, in this paper, is implemented in Apache Jena (Apache Jena, https://***., Accessed 2020/09/04). In addition, the usability of the proposed work is illustrated using a suitable case study. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. part of Springer Nature.

关键词： Automated test case Rule-based reasoner Test case generation tool Test case ontology

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Predicting Crop Prices using Machine Learning Algorithms for Sustainable Agriculture

Predicting Crop Prices using Machine Learning Algorithms for...

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IEEE Region 10 Symposium

作者： Iftekhar Mahmud Puja Rani Das Md. Habibur Rahman Ahmed Rafi Hasan Kamrul Islam Shahin Dewan Md. Farid Department of Computer Science and Engineering United International University United City Madani Avenue Badda Dhaka Bangladesh Software Engineering The Maersk Mc-Kinney Moller Institute University of Southern Denmark Denmark

ISBN: (数字)9798350364866

ISBN: (纸本)9798350364873

The agricultural sector is crucial for South Asia's economy, providing employment and driving GDP growth. Accurate price forecasting is essential for food security, market stability, and facilitating import-export activities. In this study, Decision Tree, AdaBoost, and Random Forest have proven effectiveness in predicting crop prices after analyzing different regression models. The Decision Tree has achieved R-squared $(R^{2})$ values of 0.996, 0.996, and 1 and Mean Squared Error MSE values of 0.242, 4.827, and 0.846 respectively for Rice, Onion, and Oil Seed. Similarly, the AdaBoost has also performed well with R-squared $(R^{2})$ values of 0.737, 0.959 and 1 and MSE values of 175.234, 14.566 and 1.643 respectively for Tomato, Potato and Oil Seed, indicating better prediction accuracy and lower prediction error. Lastly, Wheat has performed well with Linear Regression with R-squared $(R^{2})$ values of 0.980 and MSE values of 0.756. Random Forest Regression has shown consistent high R-squared $(R^{2})$ values and low MSE values. The effectiveness of Decision Tree, AdaBoost, and Random Forest in Bangladesh's agricultural price forecasting highlights their versatility, aiding informed decisions by farmers and policymakers.

关键词： Accuracy Machine learning algorithms Oils Linear regression Predictive models Stability analysis Seeds (agriculture) Forecasting Random forests Regression tree analysis

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A GUI Based Approach to Detect Energy Bugs in Android Applications 16

A GUI Based Approach to Detect Energy Bugs in Android Applic...

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16th International Conference on Emerging Technologies, ICET 2021

作者： Naseer, Ayesha Nadeem, Aamer Zaman, Qamar Uz Capital Universoty of Science Technology Department of Computer Science Islamabad Pakistan Capital Universoty of Science Technology Software Engineering Islamabad Pakistan Capital Universoty of Science Technology Department of Software Engineering Islamabad Pakistan

ISBN: (纸本)9781665494373

Smartphones have improved in terms of their processing speed and memory capacity. The increased usage of smartphones has led to the widespread availability of smartphone applications. However, many smartphone applications suffer from energy inefficiency problems due to improper usage of resources. When resources are left unreleased after use, they keep consuming smartphone's battery power even if the application is not using these resources. This behavior is called resource-leak which causes energy-bugs. Different solutions based on static, dynamic and hybrid analysis exist in the literature to detect energy-bugs due to resource-leaks. However, most of the existing solutions suffer from the problem of false positives due to energy-bugs detection at the method level. They consider each method in isolation and check that if the particular method has acquired a resource but has not released it within that method. In practice, it is common that resources are acquired in one method and released in another method. In this paper, we propose a dynamic analysis technique to perform energy-bug detection at the application level to overcome the problem of false-positives. Our aim is to detect energy bugs, because serious energy issues can arise in smartphones due to energy bugs. Besides, we have considered methods in which resource is acquired or released, and if both methods execute in a single path, then the resource will be released and there will be no energy bug at application level. To evaluate our proposed approach, we have performed experiments on 11 real-life Android applications. Experimental results show that our approach is able to identify real energy bugs at the application level as well as identify false positives. © 2021 IEEE.

关键词： Smartphones

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A Brief Overview of Deep Learning Approaches for IoT Security

A Brief Overview of Deep Learning Approaches for IoT Securit...

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International Conference on Computing, Mathematics and engineering Technologies (iCoMET)

作者： Muhammad Hassaan Khalid Hanan Sharif Faisal Rehman Muhammad Naeem Ullah Shahbaz Shaukat Hadia Maqsood Chaudhry Nouman Ali Ayaz Hussain Irfana Iftikhar Department of Computer Science & Information Technology Lahore Leads University Lahore Pakistan Department of Software Engineering Mehran university of Engineering and Technology SZAB Khairpur Mir's Pakistan

The continuous increasing usage of internet devices in many areas of human life is continuously growing and demanding a proper method to protect these IoT devices from cyber-attacks and vulnerabilities. In this aspect, deep learning neural networks are a very helpful and beneficial method to provide protection to internet devices in many aspects. This study's objective is to systematically research and examine the background of research about neural networks tactics functional to different internet-based devices' safety use-cases. We put the influences we looked at into many different groups to show where this research is lacking. This particular research or findings mainly captures the articles related to “Deep neural networks”, “Cyber risks” and “IOT” in four databanks, namely Science Direct, ACM Digital Library, IEEEXplore and Springer Link. These studies concern 3 main studies, which involve safety aspects, their own Deep Learning network designs, and the occupied datasets. The final round is to find out the loopholes to be examined in the future and vulnerabilities and drawbacks in the IoT security scenario.

关键词： Deep learning Systematics Neural networks Taxonomy Oral communication Mathematics Libraries

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Evaluating LoRaWAN performance in intentional and unintentional DoS attacks by legacy 900MHz network devices

Evaluating LoRaWAN performance in intentional and unintentio...

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International Conference on Advanced Communication Technologies and Networking (CommNet)

作者： Seokhyeon Bang Junyoung Jang Minju Ro Yuseon Choi Doyong Kwon Kangyeon Lee Anthony Smith School of Computer Science and Engineering Chung-Ang University Seoul Korea Department of Software Engineering Chonnam National University Gwangju Korea School of Computer Science and Engineering Kyungpook National University Daegu Korea Department of Computer and Information Technology Purdue University Indiana United States

The deployment of LoRaWAN on the Internet of Things (IoT) has increased since its advent and LoRaWAN now predominates the IoT market over other Low Powered Wide Area Networks (LPWAN). However, since LoRaWAN uses Chirp Spread Spectrum (CSS), it is susceptible to wideband jamming attacks. In this paper, we demonstrate with experiments and concrete numerical results that jamming US915 LoRaWAN frequency is possible by the usual data transmission and reception process of 900MHz Canopy, one of the legacy 900MHz network device. Intentional attack is possible in the same manner. The experiments emulate the real-world environment operated in medical and agriculture industries, in outdoor and indoor conditions, respectively. In addition, this paper introduces and utilizes the novel metric, Jamming Effect (JE), that indicates the network performance of wireless networks that spread the data on air.

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Transparency order versus confusion coefficient:a case study of NIST lightweight cryptography S‑Boxes

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Cybersecurity 2021年第1期4卷 541-560页

作者： Huizhong Li Guang Yang Jingdian Ming Yongbin Zhou Chengbin Jin Institute of Information Engineering Chinese Academy of SciencesBeijing 100093China School of Cyber Security University of Chinese Academy of SciencesBeijing 100049China School of Cyber Security Nanjing University of Science and TechnologyNanjing 210094China Department of Software Engineering and Software Evaluation Beijing Institute of Computer Technology and ApplicationBeijing 100039China

Side-channel resistance is nowadays widely accepted as a crucial factor in deciding the security assurance level of cryptographic *** most cases,non-linear components(e.g.S-Boxes)of cryptographic algorithms will be chosen as primary targets of side-channel attacks(SCAs).In order to measure side-channel resistance of S-Boxes,three theoretical metrics are proposed and they are reVisited transparency order(VTO),confusion coefficients variance(CCV),and minimum confusion coefficient(MCC),***,the practical effectiveness of these metrics remains still *** the 4-bit and 8-bit S-Boxes used in NIST Lightweight Cryptography candidates as concrete examples,this paper takes a comprehensive study of the applicability of these *** of all,we empirically investigate the relations among three metrics for targeted S-boxes,and find that CCV is almost linearly correlated with VTO,while MCC is inconsistent with the other ***,in order to verify which metric is more effective in which scenarios,we perform simulated and practical experiments on nine 4-bit S-Boxes under the nonprofiled attacks and profiled attacks,*** experiments show that for quantifying side-channel resistance of S-Boxes under non-profiled attacks,VTO and CCV are more reliable while MCC *** also obtain an interesting observation that none of these three metrics is suitable for measuring the resistance of S-Boxes against profiled ***,we try to verify whether these metrics can be applied to compare the resistance of S-Boxes with different ***,all of them are invalid in this scenario.

关键词： Side-channel attacks NIST lightweight cryptography S-Boxes Transparency order Confusion coefficient

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User Centric Semantic Communications

arXiv

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arXiv 2024年

作者： Liu, Xunze Sun, Yifei Wang, Zhaorui You, Lizhao Pan, Haoyuan Wang, Fangxin Cui, Shuguang FNii and SSE The Chinese University of Hong Kong at Shenzhen Shenzhen China Department of Information and Communication Engineering Xiamen University China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

Current studies on semantic communications mainly focus on efficiently extracting semantic information to save bandwidth between a transmitter and a user. Although significant process has been made, a fundamental design problem in the semantic communications is that the semantic information is extracted based on certain criteria at the transmitter side along, without considering the user’s actual requirements. As a result, the current semantic communications may cause the loss of critical information that is of primary interest to the user. In such cases, the semantic transmission makes no sense to the user since all the received information is irrelevant. To solve this problem, this paper presents a user centric semantic communication system, where the user sends its request for the desired semantic information to the transmitter at the start of each transmission. Then, the transmitter extracts the required semantic information accordingly. A key challenge is how the transmitter can understand the user’s requests for semantic information and extract the required semantic information in a reasonable and robust manner. We solve this challenge by designing a well-structured framework and leveraging off-the-shelf products, such as GPT-4, along with several specialized tools for detection and estimation. Evaluation results demonstrate the feasibility and effectiveness of the proposed user centric semantic communications. © 2024, CC BY.

关键词： Latent semantic analysis

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Iterative Optimal Attention and Local Model for Single Image Rain Streak Removal

arXiv

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arXiv 2025年

作者： Li, Xiangyu Fan, Wanshu Shen, Yue Wang, Cong Wang, Wei Yang, Xin Zhang, Qiang Zhou, Dongsheng National and Local Joint Engineering Laboratory of Computer Aided Design School of Software Engineering Dalian University Dalian China Department of Computing The Hong Kong Polytechnic University Hong Kong School of Cyber Science and Technology Sun Yat-Sen University Shenzhen China School of Computer Science and Technology Dalian University of Technology Dalian China National and Local Joint Engineering Laboratory of Computer Aided Design School of Software Engineering Dalian University School of Computer Science and Technology Dalian University of Technology Dalian China

High-fidelity imaging is crucial for the successful safety supervision and intelligent deployment of vision-based measurement systems (VBMS). It ensures high-quality imaging in VBMS, which is fundamental for reliable visual measurement and analysis. However, imaging quality can be significantly impaired by adverse weather conditions, particularly rain, leading to blurred images and reduced contrast. Such impairments increase the risk of inaccurate evaluations and misinterpretations in VBMS. To address these limitations, we propose an Expectation Maximization Reconstruction Transformer (EMResformer) for single image rain streak removal. The EMResformer retains the key self-attention values for feature aggregation, enhancing local features to produce superior image reconstruction. Specifically, we propose an Expectation Maximization Block seamlessly integrated into the single image rain streak removal network, enhancing its ability to eliminate superfluous information and restore a cleaner background image. Additionally, to further enhance local information for improved detail rendition, we introduce a Local Model Residual Block, which integrates two local model blocks along with a sequence of convolutions and activation functions. This integration synergistically facilitates the extraction of more pertinent features for enhanced single image rain streak removal. Extensive experiments validate that our proposed EMResformer surpasses current state-of-the-art single image rain streak removal methods on both synthetic and real-world datasets, achieving an improved balance between model complexity and single image deraining performance. Furthermore, we evaluate the effectiveness of our method in VBMS scenarios, demonstrating that high-quality imaging significantly improves the accuracy and reliability of VBMS tasks. Codes are at https://***/ghfkahfk/EMResformer. Copyright © 2025, The Authors. All rights reserved.

关键词： Rain

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Towards Secure Agile software Development Process: A Practice-Based Model

Towards Secure Agile Software Development Process: A Practic...

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Euromicro Conference on software engineering and Advanced Applications (SEAA)

作者： Abdulhamid A. Ardo Julian M. Bass Tarek Gaber Department of Computer Science & Software Engineering University of Salford Manchester UK

Agile methods are a well-established paradigm in the software development field. Agile adoption has contributed to improving software quality. However, software products are vulnerable to security challenges and susceptible to cyberattacks. This study aims to improve security of software products when using an agile software development process. A multi-methods qualitative research approach was adopted in this study. First, we conducted semi-structured interviews with 23 agile practitioners having varied years of cybersecurity experiences. An approach informed by grounded theory methodology was adopted for data analysis. Second, we developed a novel practice-based agile software development process model derived from the results of the data analysis conducted. Third, we validated the model through a focus group comprising five senior agile cybersecurity professionals to evaluate its relevancy and novelty. The study has identified 26 security practices, organized into the six - software development life-cycle phases: planning, requirements, design, implementation, testing, and deployment. We have mapped the practices onto four swim lanes each representing an agile role. The self-organizing team is exclusively involved in three security practices, the security specialist in nine, penetration tester in one and the DevOps team collaborates on one with the security specialist. There are also seven practices that are collaboratively performed by the self-organizing team and the security specialist. Each of the practices in the model was examined during the validation phase of the study. There are two contributions in this study. First, the paper proposes a novel practice-based model comprising of 26 security practices mapped to agile roles. Second, we propose a new practice, in response to an observed lack of collaborative ceremonies, to disseminate awareness of and hence compliance with security standards.

关键词： Data analysis Agile software development Collaboration software quality software Interviews computer crime

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