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2nd International Conference of Modern Applications on information and Communication Technology, ICMAICT 2020

作者： Al-Dosary, Duaa Ali Alheeti, Khattab M. Al-Rawi, Salah Sleibi College of Computer and Information Technology Computer Sciences Department University of Anbar Anbar Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq College of Computer and Information Technology Information Systems Dept. University of Anbar Anbar Iraq

The interesting with embedded systems is related to the matters of providing privacy and security. There is a need to ensure the integrity and authenticity of the system. The methods such as passwords can be stolen or forgotten therefore the security of any data kept on the system can be exposed by any unauthorised access. In this paper, a new proposal is introduced that exploits Integrated Circuit Metrics (ICMetric) technology to provide identification and improve system security. ICMetric generates device identification based on the features of a device. In this paper, device identification can be generated by using the MEMS sensors, which are gyroscope and magnetometer embedded in many devices. The experiment is based on sensors embedded in intelligent wheelchair. Readings are obtained from the sensors and analysed mathematically and statistically to generate ICMetric number that used to provide identification of the device. ICMetric number is integrated to the dataset extracted from the trace file generated by network simulator version two (ns-2). If the system is attacked, there will be no theft because the ICMetric is not stored on the system and can be regenerated when necessary. The proposed system shows that the using of MEMS sensors to generate ICMetric number increase authentication and security of the system. The simulation results have been compared and studied for high levels of performance metrics and detection capability. © Published under licence by IOP Publishing Ltd.

关键词： Embedded systems

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A Sequential Pattern Mining Approach for Situation-Aware Human Activity Projection

A Sequential Pattern Mining Approach for Situation-Aware Hum...

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IEEE International Conference on systems, Man and Cybernetics

作者： Giuseppe D'Aniello Roberto Falcone Matteo Gaeta Zia Ur Rehman Giancarlo Fortino Dept. Information and Electrical Engineering and Applied Mathematics University of Salerno Fisciano SA Italy Dept. Computer Engineering Modeling Electronics and Systems University of Calabria Rende Cs Italy

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Human activity prediction has become increasingly prevalent in a plethora of time-critical applications. To realize accurate identification and prediction of human behaviour, we propose a situation-aware wearable computing system. A wearable computing system has the capability to perceive, comprehend and project situations by analyzing the human behavioral patterns in different environments. In particular, this work proposes a situation-aware human activity prediction (SA-HAP) approach based on sequential pattern mining that aims to anticipate future activities and tailor its responses according to situations by analyzing frequent sequential patterns and their correlations to understand how these situations are interrelated. The approach not only improves prediction accuracy but also provide the foundation for a more informed decision-making process, as the projected situations can be explained using the identified behavioral patterns. The approach is compared with other traditional techniques for activity prediction (LSTM and HMM), achieving better performance on the Extrasensory dataset.

关键词： Accuracy Correlation Decision making Hidden Markov models Medical services Predictive models Time factors Wearable devices Long short term memory Cybernetics

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Mobile-Based Monitoring Application for Self-Isolation of COVID-19 Patients

Mobile-Based Monitoring Application for Self-Isolation of CO...

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International Conference of computer and Informatics Engineering (IC2IE)

作者： Eka Miranda Alfi Yusrotis Zakiyyah Richard Mediyana Arvuni Meyske Kumbangsila Albert Verasius Dian Sano Dept. of Information Systems School of Information Systems Bina Nusantara University Karawang Indonesia Dept. of Mathematics School of Computer Science Bina Nusantara University Jakarta Indonesia Medical Doctor Community Health Service Jakarta Indonesia Dept. of Computer Science School of Computer Science Bina Nusantara University Jakarta Indonesia

This researcher intended to create a mobile-based Covid-19 patient monitoring application for primary health care as a safeguard for public health services to answer the research question of how to build a mobile-based monitoring application for self-isolation of Covid-19 patients for medical doctor view. Patients could be adequately monitored by doctors while self-isolating with this application. The Sawah Besar primary health care center in central Jakarta served as our research subject. We employed the Agile Design Science Research Methodology (ADSRM) during our study and development of this application. Following that, we evaluated our application result using the user acceptability technique and estimated the readiness of our application result using the Indonesian Ministry of Research, technological, and Higher Education (Ristekdikti) framework's technological readiness level (TKT). The evaluation found that a medical doctor accepted our application to help them with their work of monitoring Covid-19 patients' self-isolation. Furthermore, Based on the TKT framework, our application achieved level 5, which indicated that our application validated components/subsystems in a relevant context.

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Assessment of IT Governance Maturity Level for Yemeni Telecom Sector Using COBIT 2019 Framework 1

Assessment of IT Governance Maturity Level for Yemeni Teleco...

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Ghallab, Abdullatif Alswari, Tahani Alhazbi, Saleh Al-Fuhaidi, Belal Hadwan, Mohammed Al-Fahaidy, Farouk Al-Dowail, Mohammed Maqtary, Naseebah Department of Computer Science University of Science and Technology Sana’a Yemen Department of IT Open University Malaysia Sana’a Yemen Dept. of Computer Science & Eng. Qatar University Doha Qatar Department of IT Qassim University Buraydah Saudi Arabia Department of Electrical Engineering Ibb University Ibb Yemen Department of Information Systems University of Science and Technology Sana’a Yemen

ISBN: (纸本)9798331533557

information technology (IT) plays a crucial role in business operations most organizations rely on IT resources for gaining competitive advantages and creating innovative and continuous values. This increased the importance of enterprise IT governance (EGIT) and developed the recent version of the control objectives for information and related technology (COBIT), COBIT 2019 framework. It identifies the seven components of an effective EGIT system: processes, organizational structures, information flows and items, people, skills and competencies, policies and procedures, culture, ethics and behavior, services, infrastructure, and applications. The EGIT maturity level (ITGML) assessment helps to align the EGIT with strategic objectives. This study aims to assess the ITGML of the Yemeni telecom sector using COBIT 2019 framework. A quantitative method was applied, with a 73.6% response rate (148 out of 201 questionnaires collected). The study revealed that the current ITGML is 3.48, reflecting a defined maturity level. The findings suggested that IT governance practices based on COBIT 2019 are well documented and standardized within the Yemeni telecom sector. © 2024 IEEE.

关键词： Telecommunication industry

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The Cubic Bipolar Neutrosophic Sets theory and Uncertainty Management in Environmental Data Analysis

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Neutrosophic Sets and systems 2024年 72卷 60-133页

作者： Salama, A.A. Khalid, Huda E. Mabrouk, Ahmed G. Dept. of Math and Computer Sci. Faculty of Science Port Said Univ. Egypt Dean of higher Institute of Computer Science and Information Systems Ministry of Higher Education October City Egypt Telafer University Telafer Iraq Higher Institute of Computer Science and Information Systems Ministry of Higher Education October City Egypt

Environmental data analysis often faces uncertainties in measurements. Cubic Bipolar Neutrosophic Sets (CBN Sets) provide a powerful framework to address this challenge. This paper explores the mathematical foundations of CBN Sets and highlights their practical applications through illustrative examples. We demonstrate how CBN Sets effectively capture varying degrees of certainty, possibility, and impermanence in environmental parameters. The concept of inclusion relations facilitates comparisons and information fusion. Fundamental set operations (intersection, union, complement) are explored for manipulating and analyzing uncertain environmental data. We present the application of CBN Sets in water quality assessment, highlighting their ability to analyze parameters while accounting for measurement uncertainties. The potential for air quality monitoring using CBN Sets is also discussed. Finally, distance measures and similarity coefficients are introduced to quantify relationships between air quality characteristics from different stations. By leveraging CBN Sets and their associated operations, researchers can gain a more nuanced understanding of environmental data, enabling informed decision-making for a healthier planet. © 2024, University of New Mexico. All rights reserved.

关键词： Environmental monitoring

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Transfer Learning in Ensemble Convolutional Neural Networks Toward the Detection of Microscopic Fusarium Oxysporum 3

Transfer Learning in Ensemble Convolutional Neural Networks ...

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3rd International Conference on Electrical, Communication and computer Engineering, ICECCE 2021

作者： Ong, Josh Daniel L. Abigan, Erinn Giannice T. Cajucom, Luis Gabriel A. Abu, Patricia Angela R. Estuar, Ma. Regina Justina E. Ateneo de Manila University Dept. of Information Systems and Computer Science Quezon City Philippines

ISBN: (纸本)9781665438971

The Panama disease, also known as the Fusarium wilt, is a deadly disease known to affect banana plants all over the world. Caused by a fungal pathogen known as Fusarium oxysporum f. sp. cubense (Foc), the disease has been a constant threat to banana producers considering that it cannot be eradicated once it has infected the soil. A new strain that emerged in 1989 called Tropical Race 4 (TR4) is now threatening the Cavendish cultivar, the most popular banana variety being grown today. Furthermore, symptoms of the disease are not visible until late stages of the infection. While there are methods that accurately determine the presence of Foc in a soil sample, these are costly and inaccessible to most banana producers. Thus, we propose the use of convolutional neural networks in the automatic detection of Foc TR4 in soil samples with the use of microscopy. This study utilized a dataset containing microscopy images of various fungal species captured using three distinct microscopy techniques: brightfield, darkfield, and fluorescent. Transfer learning has shown to make significant improvements to the performance of the models in classifying microscopic fungi. The best performing individual model was trained exclusively on brightfield images and has achieved an accuracy score of 93.92% while the best ensemble model was able to achieve an accuracy of 97.55%. Furthermore, tests on a subset meant to simulate realistic appearances of Foc have shown that the final model is viable for actual field use. © 2021 IEEE.

关键词： Convolutional neural networks

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Co-Design of Network Topology and Qubit Allocation for Distributed Quantum Computing

Co-Design of Network Topology and Qubit Allocation for Distr...

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Quantum Communications, Networking, and Computing (QCNC), International Conference on

作者： Jiyao Liu Lei Fan Yuanxiong Guo Zhu Han Yu Wang Department of Computer and Information Sciences Temple University Philadelphia USA Dept. of Engineering Technology University of Houston Houston USA Dept. of Electrical and Computer Engineering University of Houston Houston USA Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio USA

ISBN: (数字)9798331531591

ISBN: (纸本)9798331531607

Distributed Quantum Computing (DQC) enables the execution of quantum circuits across multiple interconnected quantum processing units (QPUs), but requiring efficient qubit allocation and network topology design to optimize computational performance. Proper qubit allocation minimizes entanglement costs across QPUs, balances computational workload, and ensures efficient execution of quantum computing tasks. Meanwhile, network topology plays a crucial role in reducing entanglement routing complexity and communication overhead for remote quantum gate operations. In this paper, we propose a joint optimization framework for network topology design and qubit allocation in DQC to minimize the communication overhead. We formulate the problem as a tractable integer nonlinear programming model that explicitly incorporates entanglement routing, thereby ensuring a more tractable optimization process. To further improve computational efficiency, we present a partially linearized version of the problem, making it solvable using any classical optimization solver. Extensive simulations on both random and real-world quantum circuits validate the effectiveness of our proposed approach, demonstrating its capability to handle complex quantum circuits while reducing communication costs in DQC.

关键词： Costs Network topology Computational modeling Qubit Topology Computational efficiency Resource management Quantum circuit Integrated circuit modeling Optimization

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Comprehensive Security Solution for an Industry 4.0 Garment Manufacturing System 3

Comprehensive Security Solution for an Industry 4.0 Garment ...

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3rd International Conference on Advancements in Computing, ICAC 2021

作者： Kalhara, Dasunpriya De Alwis, Udara Jinadasa, Anuka Randunu, Dinuwan Nuwanthika, Wellalage Sasini Abeygunawardhana, Pradeep K. W. Sri Lanka Institute of Information Technology Dept. Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9781665408622

Industry 4.0, digital transformation towards Internet of Things (IoT) focuses on productivity rather than security, therefore often face cybersecurity challenges. To overcome such, a centralized security solution focusing on four major areas 1) Standardization, 2) Security configurations with update management, 3) Authentication and physical access control and 4) Intrusion detection was applied to Cyber Physical System (CPS) based garment manufacturing system to overcome the security gap. Security policies based on ISO 27001:2013 and IEC 62443 security standards were applied to the security configuration management system in the design stage to achieve 'security by design' concept. Security and audit configurations were applied using Ansible for the automated tool that can be customized based on requirements. A Raspberry Pi 4 was utilized as IDS (Intrusion Detection System) to evaluate performance. The physical access control prevents unauthorized access and access monitoring was done using logs. The proposed system enhances security, reaching for a cost-effective, efficient, reusable solution, and provides a comprehensive security solution for potential challenges of current and future smart manufacturing. The system is secured in terms of strategy, design, and operations rather than securing the system after deployment. © 2021 IEEE.

关键词： Industry 4.0

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Enhancing Human Resources Management with Blockchain Technology: A Case Study Approach

Enhancing Human Resources Management with Blockchain Technol...

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Dian Indiyati Untung Rahardja Umi Rusilowati Shofiyul Millah Adam Faturahman Anandha Fitriani School of Economics and Business Telkom University Bandung Indonesia Dept. of Computer Science Universiti Teknologi Malaysia Johor Malaysia Dept. of Management Pamulang University South Tangerang Indonesia Dept. of Information Systems University of Raharja Tangerang Indonesia Dept. of Computer Systems University of Raharja Tangerang Indonesia Dept. of Digital Business CAI Sejahtera Indonesia0 Tangerang Indonesia

ISBN: (数字)9798350367492

ISBN: (纸本)9798350367508

Blockchain technology has emerged as a transformative force in various sectors, including Human Resources (HR), promising enhanced security, transparency, and efficiency. The objective of this study is to explore the integration of blockchain in HR through a comprehensive case study analysis. Methodologically, the research employs Structural Equation Modeling (SEM) facilitated by SmartPLS, investigating the impact of blockchain adoption on data security enhancement, transparency, trust, efficiency in HR processes, and ultimately, employee satisfaction. A survey of 200 HR professionals was conducted to capture insights into their perceptions and experiences with blockchain integration. The results indicate a significant shift in HR management practices, where blockchain adoption not only improves data security but also fosters transparency and trust within HR processes. Additionally, the study highlights blockchain’s role in streamlining HR operations, leading to increased efficiency and higher employee satisfaction. However, challenges in implementation and adaptation persist. The conclusion emphasizes the necessity for HR departments to embrace blockchain technology, recognizing its potential to revolutionize traditional HR practices. By leveraging blockchain’s capabilities, organizations can mitigate data breaches, enhance process efficiency, and foster a more engaged workforce. This research adds to the growing body of literature on blockchain in HR, providing valuable insights and recommendations for organizations aiming to harness blockchain for HR innovation and optimization.

关键词： Surveys Technological innovation Numerical analysis Data security Force Organizations Mathematical models Blockchains Resource management Optimization

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Automated detection and cropping of hyphae in microscopic images of various fungi

Automated detection and cropping of hyphae in microscopic im...

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2021 IEEE International Conference on Electrical, computer, Communications and Mechatronics Engineering, ICECCME 2021

作者： Cajucom, Luis Gabriel A. Abigan, Erinn Giannice T. Ong, Josh Daniel L. Abu, Patricia Angela R. Estuar, Ma. Regina Justina E. Ateneo de Manila University Dept. of Information Systems and Computer Science Quezon City Philippines

ISBN: (纸本)9781665412629

Fusarium oxysporum f. sp. cubense is a soil-borne fungi that has become a major threat to the current banana industry. The presence of this fungi can destroy entire plantations if not detected and stopped early enough. The purpose of this study is to create a Convolutional Neural Network (CNN) that can detect hyphae in microscopic images. By detecting hyphae, the presence of fungi in the soil can be confirmed. To create a model that can detect hyphae, a dataset of various microscopic images of fungi was sorted into hyphae images and non-hyphae images (labeled as others). Four subsequent datasets were created from this, namely: (1) bright field, (2) dark field, (3) fluorescent, and (4) all microscopy techniques. Pretrained ResNet34 and ResNet152 models were used for each of the datasets and the use of heatmaps on these models was done to analyze how the models looked for hyphae. The ResNet34 model achieved accuracies of 86.38% for bright field, 87.31% for dark field, 88.37% for fluorescent, and 87.60% for all microscopy techniques. The ResNet152 model achieved accuracies of 87.97% for bright field, 86.79% for dark field, 89.37% for fluorescent, and 87.69% for all microscopy techniques. Additionally, to improve the accuracy even further, automated cropping using edge detection and contour detection was done on the datasets to create cropped photos of hyphae. This resulted in average test accuracies of 87.17% for bright field, 86.90% for dark field, 91.22% for fluorescent, and 89.99% for all microscopy techniques. Generally, fluorescent consistently performed the best, but the heatmaps generated from each model show that hyphae can also be detected using the other microscopy techniques. This study can act as a steppingstone for future studies involving the classification of fungi through hyphae and other features. © 2021 IEEE.

关键词： Fungi

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