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International Workshop on Empirical software engineering in Practice (IWESEP)

作者： Ryo Ishizuka Hironori Washizaki Yoshiaki Fukazawa Shinobu Saito Saori Ouji Dept. of Computer Science and Engineering Waseda University Tokyo Japan Software Innovation Center NTT Corporation Tokyo Japan

ISBN: (数字)9781728155906

ISBN: (纸本)9781728155913

Acquiring knowledge and context of the ongoing project is one of the most challenging issues for new project members. New project members need to comprehend the contents of features already implemented in software systems. However, most software documents (e.g., flow chart and data-model) were initially created and not updated. Herein we focus on tickets issued during the project period because they are created based on stakeholders' requirements as a project evolves. We propose a novel approach to categorize and visualize tickets to better understand the features implemented in the existing software systems. Specifically, tickets are grouped by a clustering method and the number of clusters (i.e., ticket categories) is automatically estimated. Then the ticket categories are visualized by (i) creating a heatmap of the tickets lifetimes, (ii) extracting keywords of the ticket categories, and (iii) analyzing the relationships between ticket categories. We applied our approach to an NTT software development project. Additionally, we interviewed the project members and external experts to evaluate the effectiveness of our approach. Our approach helps comprehend the features of the software system.

关键词： Data visualization software computer science Text mining Machine learning Technological innovation Data collection

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Forecasting Measles Cases in Ethiopia using Neuro-Fuzzy Systems

Forecasting Measles Cases in Ethiopia using Neuro-Fuzzy Syst...

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International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

作者： Kaan Uyar Umit Ilhan Erkut Inan Iseri Ahmet Ilhan Dept. of Computer Engineering Near East University Mersin 10 Turkey Dept. of Software Engineering Near East University Mersin 10 Turkey Dept. of Biophysics Near East University Mersin 10 Turkey Dept. of Computer Programming Near East University Mersin 10 Turkey

Measles is still one of the deadly diseases that terrify the world. Making accurate decisions is necessary in organizing an effective fight against the disease. Forecasting is a very important tool for planning future needs of the health services including the vaccine stocks. Forecasting methods will help to watch over the critical stock levels of the medication as well as their expiration dates and perhaps take the necessary action to ensure a health stock flow. Governments and health institutions estimate the measles vaccine requirements using certain equations generally based on the size of the target population and the past consumption records. There are several studies that have examined the measles forecasting and conducted a vaccine requirement assessment. In this study genetic algorithm (GA) based trained recurrent fuzzy neural network (RFNN) and Adaptive neuro-fuzzy inference system (ANFIS) used to forecast the monthly measles cases in Ethiopia. The Ethiopia measles data was extracted from the World Health Organization Measles and Rubella Surveillance Data, which covers the period from January 2011 to December 2017. Out of total monthly measles cases, 80% were used for training, and 20% were chosen for testing. GA based trained RFNN shows better performance compared to ANFIS results.

关键词： Forecasting Testing Tools Organizations Diseases Vaccines Sociology

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optimizing UAV-to-Car Communications in 3D Environments Through Dynamic UAV Positioning

optimizing UAV-to-Car Communications in 3D Environments Thro...

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International Workshop/Symposium on Distributed Simulation and Real-Time Applications (DS-RT)

作者： Seilendria A. Hadiwardoyo Carlos T. Calafate Juan-Carlos Cano Kirill Krinkin Dmitry Klionskiy Enrique Hernández-Orallo Pietro Manzoni Dept. of Computer Engineering (DISCA) Universitat Politècnica de València Valencia Spain Dept. of Software Engineering & Computer Applications (MOEVM) St. Petersburg Electrotechnical University “LETT” St. Petersburg Russia

Unmanned Aerial Vehicles (UAVs) can act as re-lays in areas with limited infrastructure to support car-to-car communications. Prior studies on UAV-to-car communications showed that the irregularity of the terrains has a significant impact on link quality. Thus, in this paper, we propose a positioning technique that relies on Particle Swarm optimization (PSO) to optimize the positioning of a UAV in the vehicular environment by considering the irregularities of the terrains that might hinder Line-of-Sight (LOS) conditions. The proposed technique takes into account the path loss caused by the terrains. Simulation results show that the optimization algorithm allows us to determine the best position for the deployed UAVs throughout time by considering the movement of the cars, and also accounting for adjustments in terms of flight altitude. In particular, the latter is adjusted by considering the position of the cars on the ground and the profile of surrounding terrains to determine potential communications blockages, while respecting international regulations regarding flight altitude restrictions.

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Cloud Database Encryption Technology Based on Combinatorial Encryption

Cloud Database Encryption Technology Based on Combinatorial ...

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IEEE Global Communications Conference

作者： Meng Chen Xiao Fu Bin Luo Xiaojiang Du Mohsen Guizani State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Dept. of Computer and Information Sciences Temple University Philadelphia USA Dept. of Computer Science and Engineering Qatar University Qatar

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Traditional cloud database directly stores user plaintext information, information security is directly related to the security of Cloud server, which will create a great security risk. The user's information security is not guaranteed. In this paper, a database encryption technology is designed, which can balance the problem of information security and use efficiency well. In this paper, a simplified onion encryption model is designed and implemented, which can realize the full homomorphic encryption on the cloud database to a certain extent, and improve the efficiency of ciphertext operation to a certain extent.

关键词： Encryption Databases Cloud computing Servers Ciphers

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UnShadowNet: Illumination Critic Guided Contrastive Learning For Shadow Removal

arXiv

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arXiv 2022年

作者： Dasgupta, Subhrajyoti Das, Arindam Yogamani, Senthil Das, Sudip Eising, Ciarán Bursuc, Andrei Bhattacharya, Ujjwal Mila - Quebec AI Institute 6666 St-Urbain Street MontrealQCH2S 3H1 Canada Université de Montréal 2900 Edouard Montpetit Blvd MontrealQCH3T 1J4 Canada Dept. Driving Software and Systems Valeo India Chennai600130 India Dept. Electronic & Computer Engineering University of Limerick LimerickV94 T9PX Ireland Valeo Visions Systems IDA Business Park Dunmore Rd Demesne GalwayH54 Y276 Ireland University of Limerick Tierney Building LimerickV94 NYD3 Ireland Valeo.ai Paris75017 France Unit Indian Statistical Institute Kolkata700108 India

Shadows are frequently encountered natural phenomena that significantly hinder the performance of computer vision perception systems in practical settings, e.g., autonomous driving. A solution to this would be to eliminate shadow regions from the images before the processing of the perception system. Yet, training such a solution requires pairs of aligned shadowed and non-shadowed images which are difficult to obtain. We introduce a novel weakly supervised shadow removal framework UnShadowNet trained using contrastive learning. It is composed of a DeShadower network responsible for the removal of the extracted shadow under the guidance of an Illumination network which is trained adversarially by the illumination critic and a Refinement network to further remove artefacts. We show that UnShadowNet can be easily extended to a fully-supervised set-up to exploit the ground-truth when available. UnShadowNet outperforms existing state-of-the-art approaches on three publicly available shadow datasets (ISTD, adjusted ISTD, SRD) in both the weakly and fully supervised setups. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

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A Design of Firewall Based on Feedback of Intrusion Detection System in Cloud Environment

A Design of Firewall Based on Feedback of Intrusion Detectio...

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IEEE Global Communications Conference

作者： Xiaoyu Ma Xiao Fu Bin Luo Xiaojiang Du Mohsen Guizani State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Dept. of Computer and Information Sciences Temple University Philadelphia USA Dept. of Computer Science and Engineering Qatar University Qatar

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Security is critical to cloud services, this paper introduces a design of firewall, which based on IDS's feedback t change rules in order to detect attack flexible. It combines firewall and Intrusion Detection Systems (IDS) by using Intrusion Detection Systems, which detects ICMP, TCP, UDP attacks. Usually, a cloud service is a service built on a virtual machine. The virtual device is virtualized to achieve the purpose of multiplexing. Therefore, if you want to implement cloud security detection, you can listen to the physical device's network card. There are two types of Intrusion Detection System, one is host-based intrusion detection system (HIDS) and another is network intrusion detection system (NIDS). What's more, in order to highlight the importance of the firewall, the IDS monitoring data is analyzed and added to the firewall's defense strategy automatically. Finally, we measure the effectiveness of the system by False Negative (FN) and False Positive (FP), and verify that feedback plays a crucial role in improving the effectiveness of the system, improving the efficiency of the entire system filtering attacks.

关键词： Monitoring Cloud computing Firewalls (computing) Filtering Intrusion detection Virtual machining

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Sharing of vulnerability information among companies - A survey of Swedish companies

arXiv

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arXiv 2019年

作者： Olsson, Thomas Hell, Martin Host, Martin Franke, Ulrik Borg, Markus Software and Systems Engineering Lab RISE Research Institutes of Sweden Lund Dept. of Electrical and Information Technology Lund University Lund Dept. of Computer Science Lund University Lund Software and Systems Engineering Lab RISE Research Institutes of Sweden Kista

software products are rarely developed from scratch and vulnerabilities in such products might reside in parts that are either open source software or provided by another organization. Hence, the total cybersecurity of a product often depends on cooperation, explicit or implicit, between several organizations. We study the attitudes and practices of companies in software ecosystems towards sharing vulnerability information. Furthermore, we compare these practices to contemporary cybersecurity recommendations. This is performed through a questionnairebased qualitative survey. The questionnaire is divided into two parts: the providers' perspective and the acquirers' perspective. The results show that companies are willing to share information with each other regarding vulnerabilities. Sharing is not considered to be harmful neither to the cybersecurity nor their business, even though a majority of the respondents consider vulnerability information sensitive. However, the companies, despite being open to sharing, are less inclined to proactively sharing vulnerability information. Furthermore, the providers do not perceive that there is a large interest in vulnerability information from their customers. Hence, the companies' overall attitude to sharing vulnerability information is passive but open. In contrast, contemporary cybersecurity guidelines recommend active disclosure and sharing among actors in an ecosystem. Copyright © 2019, The Authors. All rights reserved.

关键词： Surveys

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Slurry Design for a Low Cost, High Capacity Magnesium Semi-Solid Flow Battery

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ECS Meeting Abstracts 2020年第2期MA2020-02卷

作者： Matt McPhail Rajan Kumar Vivek Subramanian Dept. of Electrical Engineering and Computer Sciences UC Berkeley Dept. of Materials Science and Engineering Stanford University Dept. of Microengineering École polytechnique fédérale de Lausanne

Semi solid flow batteries (SSFB) are developed by forming suspensions of electrochemically active and conductive particles for use as an anolyte or catholyte in a redox flow battery. By utilizing micron-scale powders from mature battery chemistries in a flowable suspension, the benefits of energy-dense intercalation chemistries with the scalability of flow battery architectures can be combined for low cost electrochemical storage. Presently, a narrow set of materials has been explored, focusing on chemistries with a lithium anode. In this work, a magnesium SSFB with an optimized MoS2 cathodic slurry is demonstrated as a low cost, high material abundance alternative to lithium-based chemistries. A mixed ionic-electronic conductive network is designed around a dual-ion (Mg, Li) electrolyte, by combining the all-phenyl complex (APC) + LiCl, MoS2, and ketjen black (KB) to form the cathodic slurry. The rheological, electrical, and electrochemical properties of MoS2-KB-APC slurries with varying compositions have been measured. Full cells, with a Mg foil anode and MoS2 slurry cathode, are shown to cycle reversibly for 20 cycles at C/5 in a non-flowing configuration, reaching 180 mAh/g discharge capacity. LiCl concentration and KB concentration are identified as critical to high capacity slurry cathodes. The relative impacts of Mg and Li ions are quantitatively analyzed, showing that both ions are reversibly intercalated during cycling. Finally, a custom flow cell is used to demonstrate 120 mAh/g discharge capacity at C/8, highlighting the flowable nature of the cathode suspension. This work provides experimental data and insight into how existing low cost material sets can be utilized in a semi solid flow battery architecture. Figure 1

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Detecting Default Payment Fraud in Credit Cards

Detecting Default Payment Fraud in Credit Cards

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IEEE International Conference on Intelligent Systems and Green Technology (ICISGT)

作者： S. S. Harshini Padmanabhuni Aditya Sai Kandukuri Debachudamani Prusti Santanu Kumar Rath Dept. of Computer Science of Engineering National Institute of Technology Rourkela Rourkela India Associate Software Engineer Micro Focus Bangalore India

ISBN: (数字)9781728114231

ISBN: (纸本)9781728114248

A credit card account is said to be in default if the payment into the credit card account is not done in due time because of credit card fraud. In many cases the default account credit card holders are found to be fraudsters. It is necessary for financial Institutions to determine which accounts may go into default so that they can take necessary preventive steps to curb any fraudulent transactions. The transactions of the clients can be observed and using this information if any account resembles a fraud, the financial institutions can take necessary actions like blocking the account. We have considered some standard machine learning algorithms for the classification of the default accounts. Later, we have proposed a model by combining the classification algorithms and critically examined it with other machine learning and deep learning models.

关键词： Credit cards Hidden Markov models Machine learning algorithms Biological neural networks Machine learning Forestry Decision trees

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Quantitative Verification of Zeroconf Protocol Based on Stochastic Games 10

Quantitative Verification of Zeroconf Protocol Based on Stoc...

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10th International Conference on Communication software and Networks, ICCSN 2018

作者： Guo, Xu Dept. of Computer Science and Software Engineering East China Normal University Shanghai China Dept. of Electronics and Information Shanghai Dianji University Shanghai China

ISBN: (纸本)9781538672235

Zeroconf protocol provides a solution to automatic IP address configuration. This paper focuses on quantitative performance analysis of zeroconf protocol. The analysis process contains two phrases: model construction and property verification. Since there exists competition relation among the hosts and their behaviors exhibit stochastic features, it is natural to model zeroconf protocol as turn-based stochastic game. Due to the absence of some necessary details of the original protocol, this paper also makes some assumptions about the model. The successful configuration probability and time cost are the most important concern of this protocol. This paper verifies maximum and minimum successful and unsuccessful configuration probabilities within certain periods. On the other hand, this paper also considers time cost to reach successful configuration. Experiments are performed with the tool PRISM-game which is for modeling and verification of stochastic games. Experimental results show that when the number of host is no more than 40,000, the performance of this protocol tends to be stable and when N is greater than 40,000, both the expected time cost for successful configuration and conflict probability will grow prominently. © 2018 IEEE.

关键词： Stochastic systems

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