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Frontiers in Education (FIE) Conference

作者： Omar Ochoa Miralda Rodney Massood Towhidnejad Salamah Salamah Department of Electrical Computer Software & Systems Engineering Embry-Riddle Aeronautical University Daytona Beach FL USA Department Computer Science Univeristy of Texas at El Paso El Paso TX USA

ISBN: (纸本)9781538611753;9781538611746

In this paper, we explore the benefits of teaching heavyweight process life cycle models to young software engineering students to better prepare them in the use of agile methods. The benefits of agile methods compared to process-heavy models include the ability to respond faster to the changing needs of customers and the short feedback loop between customers and developers. Since agile methods depend significantly on the competence of the individual, teaching traditional approaches (e.g. waterfall) can be advantageous to the understanding of students about what the major activities associated with software development are, by providing a well-defined structure that naturally aligns with the novice student. Towards this goal, we conducted a survey with different types of software engineers, ranging from novice undergraduates to software engineering professionals. The survey provides data on the exposure of traditional and agile process, the level of experience in using traditional and agile process models, and the perceived most optimal learning sequence. Based on the analysis of the collected data, we argue that teaching traditional software engineering process-oriented approaches prior to introducing agile methods, is highly beneficial to students' understanding and optimal use of agile techniques.

关键词： software software engineering Education Agile software development Testing Modeling Knowledge engineering

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A Time Effect based Collaborative Filtering Approach for User Preference Statistics and Recommendation

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Journal of Physics: Conference Series 2020年第1期1453卷

作者： Yuxi Chen Xiaotong Zhang Qing Zhao Faheem Akhtar School of Statistics and Mathematics Country Central University of Finance and Economics Beijing 100081 China Harpur College of Arts and Sciences Binghamton University-SUNY New York 13902 America Faculty of Information Technology Beijing University of Technology Beijing 100124 China. Department of Computer Science Vrije Universiteit Amsterdam 1081 HV The Netherlands School of Software Engineering Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing 100124 China Department of Computer Science Sukkur IBA University Sukkur 65200 Pakistan

With the rapid development of the information technologies in the financial field, extracting meaningful information from a massive amount of data is hugely significant for efficient business decision making. The recommendation system is an intelligent system that applies historical knowledge of users to infer their preferences and make a personalized recommendation. However, it suffers from the problem of time effect of user's behaviour, which means a user's interests may change over time. To overcome this problem, we propose a time effect based collaborative filtering approach to adaptively statistics the change of user preferences. Firstly, Item-based collaborative filtering is used to calculate rating similarity between items. Since an Item-based collaborative filtering algorithm doesn't consider the time effect; next, the time decay function is proposed to statistics the change of user interests. Experimental results show that the proposed scheme retained higher accuracy compare to traditional collaborative filtering method.

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Secure Beamforming Design for MISO SWIPT systems: An Indirectly Optimized Approach

Secure Beamforming Design for MISO SWIPT Systems: An Indirec...

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2019 IEEE Global Communications Conference (GLOBECOM)

作者： Yao Yu Siyu Wang Shumei Liu Lei Guo Zhaolong Ning Shimin Gong Mohammad S. Obaidat School of Computer Science and Engineering Northeastern University Shenyang China Chongqing University of Posts and Telecommunications China State Key Laboratory for Novel Software Technology Nanjing University China School of Intelligent Systems Engineering Sun Yat-sen University China ECE Department Nazarbayev University Astana Kazakhstan College of Computing and Informatics University of Sharjah UAE The King Abdullah II School of Information Technology The University of Jordan Amman Jordan University of Science and Technology Beijing China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

By considering the Simultaneous Wireless Information and Power Transfer (SWIPT) schemes, this paper focuses on secure transmission model design in multiple-input-single-output (MISO) channels. In these channels, the channel state information is assumed to be perfect. Our objective is to maximize the worst-case secrecy rate with respect to both potential eavesdroppers and obvious eavesdroppers under the constraints of energy-harvesting and total transmission power. We present an optimization model to indirectly obtain maximum security rate in a single receiver system. Due to the high computational complexity of the solution process caused by the formulated non-convex optimization problem, we propose a novel indirect method to handle this issue. Then, a Semi-Definite Programming (SDP) relaxation method is used to approach the optimal solution. Moreover, we reveal the conditions for ensuring that the above semi-definite relaxation is compact. Simulation results demonstrate that the gained performance in our system is much better than those of the existing competing schemes.

关键词： Receivers Interference Signal to noise ratio Transmitters Optimization Security Communication system security

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One-Time-Username: A Threshold-based Authentication System

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Procedia computer science 2018年 129卷 426-432页

作者： Abdulrahman Alhothaily Arwa Alrawais Chunqiang Hu Wei Li Department of Computer Science The George Washington University Washington DC 20052 USA General Department of Payment Systems Saudi Arabian Monetary Authority Riyadh KSA College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University KSA School of Software Engineering Chongqing University Chongqing 400044 China Department of Computer Science Georgia State University Atlanta GA 30303 USA

Due to the complexity and volume, memorizing static usernames and passwords is deemed to be one of the most cumbersome tasks for ordinary users. Nevertheless, verifying the access legitimacy of a user without using a verification table and securely granting permissions based on an access control policy assigned to the user are two critical challenges to build an authentication scheme which is practical and effective. Traditional approaches either completely ignore the importance of user-centric access control or rely on a single point of verification or a third party authority; but in practice, access control and distributed verifiers are important for enhancing security and dealing with the dynamics caused by the user online browsing activities. In this paper, we propose a threshold-based authentication system leveraging user computing devices and allowing users to designate various permissions. Various (t,n) physical or virtual devices can participate to run an authentication protocol and provide the user with a one-time credential to access an online banking system. Our evaluation and results show that the solution is not only practical, but it also minimizes the risks associated with traditional approaches.

关键词： Security Authentication Threshold Cryptosystem One-Time Username RSA Access Control

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Cloud workload prediction based on workflow execution time discrepancies

arXiv

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arXiv 2018年

作者： Kecskemeti, Gabor Nemeth, Zsolt Kertesz, Attila Ranjan, Rajiv Department of Computer Science Liverpool John Moores University Laboratory of Parallel and Distributed Systems MTA SZTAKI Software Engineering Department University of Szeged School of Computing Newcastle University

Infrastructure as a service clouds hide the complexity of maintaining the physical infrastructure with a slight disadvantage: they also hide their internal working details. Should users need knowledge about these details e.g., to increase the reliability or performance of their applications, they would need solutions to detect behavioural changes in the underlying system. Existing runtime solutions for such purposes offer limited capabilities as they are mostly restricted to revealing weekly or yearly behavioural periodicity in the infrastructure. This article proposes a technique for predicting generic background workload by means of simulations that are capable of providing additional knowledge of the underlying private cloud systems in order to support activities like cloud orchestration or workflow enactment. Our technique uses long-running scientific workflows and their behaviour discrepancies and tries to replicate these in a simulated cloud with known (trace-based) workloads. We argue that the better we can mimic the current discrepancies the better we can tell expected workloads in the near future on the real life cloud. We evaluated the proposed prediction approach with a biochemical application on both real and simulated cloud infrastructures. The proposed algorithm has shown to produce significantly (∼20%) better workload predictions for the future of simulated clouds than random workload selection. Copyright © 2018, The Authors. All rights reserved.

关键词： Infrastructure as a service (IaaS)

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Authentic Learning Secure software Development (SSD) in Computing Education

Authentic Learning Secure Software Development (SSD) in Comp...

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Frontiers in Education (FIE) Conference

作者： Kai Qian Dan Lo Reza Parizi Fan Wu Emmanuel Agu Bei-Tseng Chu Computer Science Department Kennesaw State University Kennesaw GA USA Software Engineering and Game Design Kennesaw State University Kennesaw GA USA Computer Science Department Tuskegee University Tuskegee AL USA Computer Science Department Worcester Polytechnic Institute Worcester MA USA Department of Software and Information Systems University of North Carolina at Charlotte Charlotte NC USA

ISBN: (纸本)9781538611753;9781538611746

As mobile computing is now becoming more and more popular, the security threats to mobile applications are also growing explosively. Mobile app flaws and security defects could open doors for hackers to break into them and access sensitive information. Most vulnerabilities should be addressed in the early stage of mobile software development. However, many software development professionals lack awareness of the importance of security vulnerability and the necessary security knowledge and skills at the development stage. The combination of the prevalence of mobile devices and the rapid growth of mobile threats has resulted in a shortage of secure software development professionals. Many schools offer mobile app development courses in computing curriculum; however, secure software development is not yet well represented in most schools' computing curriculum. This paper addresses the needs of authentic and active pedagogical learning materials for SSD and challenges of building Secure software Development (SSD) capacity through effective, engaging, and investigative approaches. In this paper, we present an innovative authentic and active SSD learning approach through a collection of transferrable learning modules with hands-on companion labs based on the Open Web Application Security Project (OWASP) recommendations. The preliminary feedback from students is positive. Students have gained hands-on real world SSD learning experiences with Android mobile platform and also greatly promoted self-efficacy and confidence in their mobile SSD learning.

关键词： software Security Education Programming profession Mobile handsets

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Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing 7

Fuzzy adaptive teaching learning-based optimization strategy...

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7th IEEE International Conference on System engineering and Technology, ICSET 2017

作者： Din, Fakhrud Zamli, Kamal Z. Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Kuantan Pahang Malaysia Department of Computer Science and IT University of Malakand KPK Pakistan

ISBN: (纸本)9781538603833

Pairwise strategies have tested effectively a range of software and hardware systems. These testing strategies offer solutions that can substitute exhaustive testing. In simple terms, a pairwise testing strategy significantly minimizes large input parameter values (or configuration options) of a system into a smaller set based on pairwise interaction (or combination). Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm is an improved form of Teaching Learning-based Optimization (TLBO) algorithm. ATLBO employs Mamdani fuzzy inference system to select adaptively either teacher phase or learner phase based on performance instead of blind sequential application as in original TLBO. In this paper, two pairwise testing strategies based on ATLBO and TLBO are proposed. Experimental results suggest that the proposed strategies are capable to be part of testers' toolkit as they outperformed competing meta-heuristic based pairwise testing strategies and tools on many pairwise benchmarks. Moreover, ATLBO based strategy generated optimal pairwise test suites than the one based on TLBO. © 2017 IEEE.

关键词： software testing

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A Scalable Deep Attention Mechanism of Instance Segmentation for the Investigation of Chromosome

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SLAS technology 2025年 33卷 100306页

作者： Neelam Umbreen Sara Ali Hasan Sajid Yasar Ayaz Shrooq Alsenan Yunyoung Nam So Yeon Kim Muhammad Baber Sial National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: neelamumbreen.phd@smme.edu.pk. National University of Sciences and Technology (NUST) Islamabad Pakistan Suzhou Industrial Park (SIP) Monash Research Institute of Science and Technology Monash University 8Q9C+R6W Suzhou Jiangsu China. School of Mechanical and Manufacturing Engineering (SMME) National University of Sciences and Technology (NUST) Islamabad NUST-COVENTRY Human-Robot Interaction (NC-HRI) Laboratory Pakistan Intelligent Field Robotics Laboratory (IFRL) National Center for Artificial Intelligence (NCAI) National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: sarababer@smme.nust.edu.pk. National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: hasan.sajid@smme.nust.edu.pk. Intelligent Field Robotics Laboratory (IFRL) National Center for Artificial Intelligence (NCAI) National University of Sciences and Technology (NUST) Islamabad Pakistan. Electronic address: yasar@smme.nust.edu.pk. Information Systems Department College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O. Box 84428 Riyadh 11671 Saudi Arabia. Electronic address: shalsenan@pnu.edu.sa. Emotional and Intelligent Child Care Convergence Research Center Soonchunhyang University Asan 31538 Korea. Electronic address: ynam@sch.ac.kr. Department of Artificial Intelligence Department of Software and Computer Engineering Ajou University. Electronic address: jebi1771@ajou.ac.kr. School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China. Electronic address: babersial@***.

Chromosome segmentation in metaphase images is a critical yet challenging task in cytogenetics and genomics due to the inherent complexity, variability in chromosome shapes, and the scarcity of high-quality annotated datasets. This study proposes a robust instance segmentation framework that integrates an automated annotation pipeline with an enhanced deep learning architecture to address these challenges. A novel dataset is introduced, comprising metaphase images and corresponding karyograms, annotated with precise instance segmentation information across 24 chromosome classes in COCO format. To overcome the labor-intensive manual annotation process, a feature-based image registration technique leveraging SIFT and homography is employed, enabling the accurate mapping of chromosomes from karyograms to metaphase images and significantly improving annotation quality and segmentation performance. The proposed framework includes a custom Mask R-CNN model enhanced with an Attention-based Feature Pyramid Network (AttFPN), spatial attention mechanisms, and a LastLevelMaxPool block for superior multi-scale feature extraction and focused attention on critical regions of the image. Experimental evaluations demonstrate the model's efficacy, achieving a mean average precision (mAP) of 0.579 at IoU = 0.50:0.95, surpassing the baseline Mask R-CNN and Mask R-CNN with AttFPN by 3.94% and 5.97% improvements in mAP and AP50, respectively. Notably, the proposed architecture excels in segmenting small and medium-sized chromosomes, addressing key limitations of existing methods. This research not only introduces a state-of-the-art segmentation framework but also provides a benchmark dataset, setting a new standard for chromosome instance segmentation in biomedical imaging. The integration of automated dataset creation with advanced model design offers a scalable and transferable solution, paving the way for tackling similar challenges in other domains of biomedical and cytogenetic imagi

关键词： Chromosome segmentation Instance segmentation, cytogenetics Mask R-CNN attention mechanism biomedical imaging multi-scale feature fusion

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Noise invariant frame selection: A simple method to address the background noise problem for text-independent speaker verification

arXiv

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arXiv 2018年

作者： Song, Siyang Zhang, Shuimei Schuller, Björn W. Shen, Linlin Valstar, Michel School of Computer Science University of Nottingham United Kingdom Department of Electrical and Computer Engineering Temple University United States Group on Language Audio and Music Imperial College London United Kingdom Embedded Intelligence for Health Care and Wellbeing Augsburg University Germany School of Computer Science and Software Engineering Shenzhen University China

The performance of speaker-related systems usually degrades heavily in practical applications largely due to the presence of background noise. To improve the robustness of such systems in unknown noisy environments, this paper proposes a simple pre-processing method called Noise Invariant Frame Selection (NIFS). Based on several noisy constraints, it selects noise invariant frames from utterances to represent speakers. Experiments conducted on the TIMIT database showed that the NIFS can significantly improve the performance of Vector Quantization (VQ), Gaussian Mixture Model-Universal Background Model (GMM-UBM) and i-vector-based speaker verification systems in different unknown noisy environments with different SNRs, in comparison to their baselines. Meanwhile, the proposed NIFS-based speaker verification systems achieves similar performance when we change the constraints (hyper-parameters) or features, which indicates that it is robust and easy to reproduce. Since NIFS is designed as a general algorithm, it could be further applied to other similar tasks. Copyright © 2018, The Authors. All rights reserved.

关键词： Noise pollution

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Role Playing Game Quest Design in Multiplayer Educational Game

Role Playing Game Quest Design in Multiplayer Educational Ga...

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第22届全球华人计算机教育应用大会

作者： Zhong-Xiu, Lu Xue, Luo Maiga, Chang Rita, Kuo Kuo-Chen, Li School of Software Engineering Tongji University School of Computing and Information Systems Athabasca University Department of Information Management Chung Yuan Christian University Department of Computer Science and Engineering New Mexico Institute of Mining and Technology

In this research,we discuss how to design learning activities in the educational role-playing games with balance between fun and *** major stages in integrating learning contents into the educational role-playing games are proposed in this ***,four principles are recommended for designing learning activities in the *** with the two stages and four principles,the earning activities for Fundamental Java Programming are designed in a multiplayer on-line role playing *** evaluate whether the learning activities designed by the research team can engage students' learning motivation or not,a semester-long experiment in designed in 2018 Spring in north Taiwan.

关键词： Game-based Learning Role-Playing Game Quests Design Java Programming language

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