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1st International Conference on Advances in Science, engineering and Robotics Technology, ICASERT 2019

作者： Afrin, Rumana Sadi, Muhammad Sheikh Jurjens, Jan Khulna University of Engineering Techonology Department of Computer Science Engineering Khulna9203 Bangladesh University of Koblenz-Landau Fraunhofer-Institute for Software and Systems Engineering ISST Department of Computer Science Koblenz Germany

ISBN: (纸本)9781728134451

Ternary Content Addressable Memory (TCAM) is a kind of extraordinary memory which is used to search operations in routers, firewalls, network address translators, and entire content in a single clock cycle. It is a special kind of memory which is used in highly reliable network applications. These systems require high reliability since a single error may interrupt any computation which may cause total system failure. However, TCAM is facing serious reliability challenges due to soft errors. The probability of soft errors in TCAM is increasing progressively due to alpha-particle, cosmic rays, high-vitality particles, and ionizing impacts of barometrical neutron. In order to minimize the risks of soft errors in TCAM, a new idea is proposed in this paper where the search key is constructed in a tricky way and the contents of the TCAM are ordered in a sequential pattern. The proposed method provides soft error tolerance with a low data overhead. Experimental study shows how the proposed method outperforms the existing method to tolerate soft error. © 2019 IEEE.

关键词： Reliability

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Emergency response UAS logistics models for coastal and offshore locations

Emergency response UAS logistics models for coastal and offs...

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2019 Institute of Industrial and systems Engineers Annual Conference and Expo, IISE 2019

作者： Rau, James Babiceanu, Radu F. Seker, Remzi Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL United States

ISBN: (纸本)9781713814092

Recently there has been a rapid increase in the advancements and use of Small Unmanned Aerial systems (sUAS) for a wide range of applications ranging from precision agriculture, to environmental monitoring, and to the delivery of commercial products from logistic companies. Fixed wing, vertical takeoff-landing (FW-VTOL) sUAS offer significant usability and safety advantages over its rival systems. During emergencies, frequent transportation and delivery of medical materials, such as blood derivatives, among hospitals, and to mass causality scenes and offshore vessels are needed. This research considers sUAS logistics supply networks to all end locations within a 40 nautical miles radius, based from a central hub location. Units of medical materials will be continuously distributed outwards and return with emergency location samples. The optimization of this sUAS logistics supply model is based on transporting the most number of units between the hub and network nodes at the lowest cost of deployment and the shortest amount of time. At a first stage, the optimization model will include only one node of the network per flight, constraint to be relaxed at a second iteration where two or more nodes could be visited per each flight. © 2019 IISE Annual Conference and Expo 2019. All rights reserved.

关键词： Location

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Data Resolution Improvement for Ocean of Things Based on Improved FCM

Data Resolution Improvement for Ocean of Things Based on Imp...

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2020 International Conference on Computing, Networking and Communications, ICNC 2020

作者： Yang, Jiachen Wen, Jiabao Jiang, Bin Song, Hoibing Kong, Fanhii Zhen, Zhizhio Tianjin University School of Electrical and Information Engineering Tianjin China Embry-Riddle Aeronautical University Department of Electrical Computer Software and Systems Engineering Daytona Beach United States Tianjin University of Technology School of Management Tianiin China Hebei University of Technology School of Artificial Intelligence Tianiin China

ISBN: (纸本)9781728149059

In Ocean of Things, information prediction is an important part of marine data processing. Due to a variety of marine acquisition devices, the distribution of marine information is discrete. The marine area is wide, and the resolution of the collected data is small, which causes the IoT device to accurately calculate the information of a small sea area. Processing discrete and sparse data is the main job of marine information processing equipment. The main purpose of this paper is to predict the information of the blind area based on the collected data. In order to increase the resolution of sea surface information, the availability of marine data in the Internet of Things is improved. This paper proposes a method for predicting information on marine blind spots. This method is based on the improved machine learning algorithm FCM. This method is used to predict sea surface temperature and improve the resolution of sea surface data. Finally, this paper has done a number of simulation experiments, based on different methods to predict the sea surface temperature. The experimental results are discussed and the performance of the proposed method is analyzed. © 2020 IEEE.

关键词： Surface temperature

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An Exploratory Study on the Introduction and Removal of Different Types of Technical Debt

arXiv

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arXiv 2021年

作者： Liu, Jiakun Huang, Qiao Xia, Xin Shihab, Emad Lo, David Li, Shanping College of Computer Science and Technology Zhejiang University China PengCheng Laboratory China College of Computer Science and Technology Zhejiang University China Faculty of Information Technology Monash University Melbourne Australia Department of Computer Science and Software Engineering Concordia University Canada School of Information Systems Singapore Management University Singapore

To complete tasks faster, developers often have to sacrifice the quality of the software. Such compromised practice results in the increasing burden to developers in future development. The metaphor, technical debt, describes such practice. Prior research has illustrated the negative impact of technical debt, and many researchers investigated how developers deal with a certain type of technical debt. However, few studies focused on the removal of different types of technical debt in practice. To fill this gap, we use the introduction and removal of different types of self-admitted technical debt (i.e., SATD) in 7 deep learning frameworks as an example. This is because deep learning frameworks are some of the most important software systems today due to their prevalent use in life-impacting deep learning applications. Moreover, the field of the development of different deep learning frameworks is the same, which enables us to find common behaviors on the removal of different types of technical debt across projects. By mining the file history of these frameworks, we find that design debt is introduced the most along the development process. As for the removal of technical debt, we find that requirement debt is removed the most, and design debt is removed the fastest. Most of test debt, design debt, and requirement debt are removed by the developers who introduced them. Based on the introduction and removal of different types of technical debt, we discuss the evolution of the frequencies of different types of technical debt to depict the unresolved sub-optimal trade-offs or decisions that are confronted by developers along the development process. We also discuss the removal patterns of different types of technical debt, highlight future research directions, and provide recommendations for practitioners. © 2021, CC BY.

关键词： Economic and social effects

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Natidroid: Cross-language android permission specification

arXiv

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arXiv 2021年

作者： Li, Chaoran Chen, Xiao Sun, Ruoxi Xue, Jason Wen, Sheng Ahmed, Muhammad Ejaz Camtepe, Seyit Xiang, Yang School of Software and Electrical Engineering Swinburne University of Technology HawthornVIC3122 Australia Department of Software Systems and Cybersecurity Faculty of IT Monash University ClaytonVIC3800 Australia School of Computer Science University of Adelaide North TerraceSA5005 Australia CSIRO Data61 Australia

The Android system manages access to sensitive APIs by permission enforcement. An application (app) must declare proper permissions before invoking specific Android APIs. However, there is no official documentation providing the complete list of permission-protected APIs and the corresponding permissions to date. Researchers have spent significant efforts extracting such API protection mapping from the Android API framework, which leverages static code analysis to determine if specific permissions are required before accessing an API. Nevertheless, none of them has attempted to analyze the protection mapping in the native library (i.e., code written in C and C++), an essential component of the Android framework that handles communication with the lower-level hardware, such as cameras and sensors. While the protection mapping can be utilized to detect various security vulnerabilities in Android apps, such as permission over-privilege and component hijacking, imprecise mapping will lead to false results in detecting such security vulnerabilities. To fill this gap, we thereby propose to construct the protection mapping involved in the native libraries of the Android framework to present a complete and accurate specification of Android API protection. We develop a prototype system, named NATIDROID, to facilitate the cross-language static analysis to benchmark against two state-of-the-art tools, termed AXPLORER [1] and ARCADE [2]. We evaluate NATIDROID on more than 11,000 Android apps, including system apps from custom Android ROMs and third-party apps from the Google Play. Our NATIDROID can identify up to 464 new API-permission mappings, in contrast to the worst-case results derived from both AXPLORER and ARCADE, where approximately 71% apps have at least one false positive in permission over-privilege and up to 3.6% apps have at least one false negative in component hijacking. Additionally, we identify that 24 components with at least one Native-triggered component hij

关键词： Mobile security

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From sensing to energy savings: A comprehensive survey on integrating emerging technologies for energy efficiency in WBANs

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Digital Communications and Networks 2024年

作者： Shumaila Javaid Hamza Fahim Sherali Zeadally Bin He Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai 201804 China National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University Shanghai 201210 China Frontiers Science Center for Intelligent Autonomous Systems Shanghai 201210 China Department of Computer Science Faculty of Computer Sciences Ilma University Karachi 75190 Pakistan College of Communication and Information University of Kentucky Lexington KY USA Academy of Computer Science & Software Engineering University of Johannesburg Johannesburg South Africa

Energy is essential for human existence, and its high consumption is a growing concern in today's technology-driven society. Global initiatives aim to reduce energy consumption and pollution by developing and deploying energy-efficient sensing technologies for long-term monitoring, control, automation, security, and interactions. Wireless Body Area Networks (WBANs) benefit a lot from the continuous monitoring capabilities of these sensing devices, which include medical sensors worn on or implanted in the human body for healthcare monitoring. Despite significant advancements, achieving energy efficiency in WBANs remains a significant challenge. A deep understanding of the WBAN architecture is essential to identify the causes of its energy inefficiency and develop novel energy-efficient solutions. We investigate energy efficiency issues specific to WBANs. We discuss the transformative impact that artificial intelligence and Machine Learning (ML) can have on achieving the energy efficiency of WBANs. Additionally, we explore the potential of emerging technologies such as quantum computing, nano-technology, biocompatible energy harvesting, and Simultaneous Wireless Information and Power Transfer (SWIPT) in enabling energy efficiency in WBANs. We focus on WBANs' architecture, hardware, and software components to identify key factors responsible for energy consumption in the WBAN environment. Based on our comprehensive review, we introduce an innovative, energy-efficient three-tier architecture for WBANs that employs ML and edge computing to overcome the limitations inherent in existing energy-efficient solutions. Finally, we summarize the lessons learned and highlight future research directions that will enable the development of energy-efficient solutions for WBANs.

关键词： Artificial intelligence Energy Healthcare Sensors Wireless body area networks

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EER: Enterprise expert ranking using employee reputation

arXiv

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arXiv 2020年

作者： Mahmood, Saba Ghani, Anwar Daud, Ali Saqlain, Syed Muhammad Department of Computer Science and Software Engineering International Islamic University Islamabad Department of Computer Science Bahria University Islamabad Department of Information Systems and Technology College of Computer Science and Engineering University of Jeddah Jeddah Saudi Arabia

The emergence of online enterprises spread across continents, have given rise to the need of expert identification in this domain. Scenarios that includes the intention of the employer to find tacit expertise and knowledge of an employee that is not documented or self-disclosed has been addressed in this article. The existing reputation based approaches towards expertise ranking in enterprises utilize pagerank ,normal distribution and hidden markov model for expertise ranking. These models suffer issue of negative referral, collusion ,reputation inflation and dynamism. The authors have however proposed a Bayesian approach utilizing beta probability distribution based reputation model for employee ranking in enterprises. The experimental results reveal improved performance compared to previous techniques in terms of Precision and Mean Average Error (MAE) with almost 7% improvement in precision on average for the three data sets. The proposed technique is able to differentiate categories of interactions in dynamic context. The results reveal that the technique is independent of the rating pattern and density of data. Copyright © 2020, The Authors. All rights reserved.

关键词： Personnel

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A regularized CNN approach for detecting cervical cancer

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AIP Conference Proceedings 2024年第1期3220卷

作者： Jesse Jeremiah Tanimu Mohamed Hamada Mohammed Hassan Tsentob Joy Samson Jane Simon Parah Department of computer Science Bayero Unoiversity Kano Kano Nigeria Division of information systems University of Aizu Aizu Japan Department of Software Engineering Bayero University Kano Kano Nigeria Department of computer Science Air Force Institute of Technology Kaduna Kaduna Nigeria Department of Mathematical and Physical Science Glorious Vision University Ogwa Benin Nigeria

This study delved into leveraging deep learning techniques to classify different types of cervical cancer images, recognizing the disease’s prevalence and criticality. We employed a dataset comprising cervical images and investigated the utilization of the VGG16 model as a foundational architecture. To enhance performance, we incorporated various improvements, such as L2 regularization and data augmentation. The outcomes underscored the efficacy of these enhancements, with the refined model achieving a remarkable accuracy of 94%, surpassing the VGG16 model’s baseline accuracy of 89%. These findings demonstrate the potential of deep learning to improve the classification of cervical cancer.

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Methods of On-Line Computation Acceleration in systems with Direct Connection between Units

Methods of On-Line Computation Acceleration in Systems with ...

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IEEE International Conference on Dependable systems, Services and Technologies (DESSERT)

作者： Valerii Zhabin Valentina Zhabina Department of Computer Engineering Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Department of Computer Systems Software Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine

ISBN: (数字)9781728199573

ISBN: (纸本)9781728199580

A possibility to increase the effectiveness of the parallel systems with direct connections by means of data between computation units, which are connected one to another in accordance with data flow graph, is considered. Operations correspond to the graph vertices and data correspond to the graph arcs. In the computation units operations are performed in redundant symmetric number system. It enables to overlap digit-by-digit input of operands, their processing and digit-by-digit output starting with the high digits. A result digit we get does not require further correction and can be used as an operand digit within the next computation cycle in other computation units. It gives an opportunity to perform sequences of operations connected by means of data in the concurrency mode at the level of operand digit processing. An algorithm and a structure of a computation unit, which permits to form a result digit within one tact, are proposed. Dependence of the operation execution time on the number system base is considered. It is shown that due to digit-by-digit data representation the required number of internal connections between the units, as well as of the chip pinouts, is reduced.

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Blocks' Network: Redesign architecture based on blockchain technology 2

Blocks' Network: Redesign architecture based on blockchain t...

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2nd IEEE International Conference on Industrial Internet Cloud, ICII 2019

作者： Hanif, Moataz Song, Houbing Department of Electrical Computer Software and Systems Engineering Embry-Riddle Aeronautical University Daytona BeachFL32114 United States

ISBN: (纸本)9781728129778

The internet is a global network that uses communication protocols. It is considered the most important system reached by humanity, which no one can abandon [1]. However, this technology has become a weapon that threatens the privacy of users, especially in the client-server model, where data is stored and managed privately. Additionally, users have no power over their data that store in a private server, which means users' data may interrupt by government or might be sold via service provider for-profit purposes. Furthermore, blockchain is a technology that we can rely on to solve issues related to client-server model if appropriately used. However, blockchain technology uses consensus protocol, which is used for creating an incontrovertible system of agreement between members across a distributed network [2]. Thus, the consensus protocol is used to slow all member down from generating too fast in order to control the network creation pattern, which leads to scalability and latency problems. This paper will present a platform that leverages modernize blockchain called Blocks' Network. The system is taking into consideration the issues related to privacy and confidentiality from the client-side model, and scalability and latency issues from the blockchain technology side. Blocks' network is a public and a permissioned network that use a multi-dimensional hash to generate multiple chains for the purpose of a systematic approach. The proposed platform is users' assembly point to create a decentralized network via P2P protocols. The system has a high data flow due to frequent use by participants (e.g., the use of the Internet). Besides, the system will store all traffic of the network overtly via Blocks' Network. © 2019 IEEE.

关键词： Blockchain

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