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23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

作者： Sava, Cezar Deaconescu, Razvan Kroning, Martin Monti, Antonello Turcanu, Dinu POLITEHNICA of Bucharest Computer Science and Engineering Department Bucharest Romania RWTH Aachen University Institute for Automation of Complex Power Systems Aachen Germany Fraunhofer Center Digital Energy Fraunhofer FIT Aachen Germany University of Moldova Department of Software Engineering and Automatics Technical Chişinǎu Moldova

ISBN: (纸本)9798331540388

Educational operating systems are crucial for facilitating learning in the digital age, as they exist at the intersection of technology and education. While their technical role is well understood, improving their educational value requires enhancing traditional approaches. This paper explores ways to enrich educational operating systems not just through technological advancement, but also by integrating pedagogical principles. In an ever-changing world, the need for an adaptive and responsive educational operating system to meet diverse student needs is crucial. Through case studies, we analyze how design, interactivity, and accessibility can transform these systems into effective and appealing learning environments. We propose a series of recommendations for the future development of educational operating systems, focusing on enhancing the learning experience and promoting student autonomy, thereby offering a fresh perspective on how technology and education can blend harmoniously and efficiently. © 2024 IEEE.

关键词： Contrastive Learning

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Maize Crop Yield Prediction Using Machine Learning Regression Approach 5th

Maize Crop Yield Prediction Using Machine Learning Regressio...

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5th International Conference on Advances in Distributed Computing and Machine Learning, ICADCML 2024

作者： Bedane, Tarikwa Tesfa Kebede, Kidistie Bizuneh Mohapatra, Sudhir Kumar Das, Tapan Kumar Tripathy, Asis Kumar Department of Software Engineering Addis Ababa Science and Technology University Addis Ababa Ethiopia Agricultural Transformation Institute Addis Ababa Ethiopia Faculty of Emerging Technologies Sri Sri University Cuttack India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9789819735228

Given maize’s significant role as a staple crop, it becomes imperative to carry out precise crop yield prediction to ensure food security. This research employs machine learning algorithms to analyze historical data related to maize crop yields, with the aim of developing a predictive model. The outcome of this study can serve as a valuable tool for pre-harvest planning and measuring crop production per unit of land area. The dataset utilized in this research spans from 2010 to 2021 and was sourced from Ethiopia’s Central Statistical Agency. Three machine learning regression algorithms—Logistic Regression, XGBoost, and Random Forest—were employed to design the predictive model. After data preparation and preprocessing, a total of 436,358 records were used for model development. The models were further trained with reduced features using principal component analysis (PCA). The experimental results demonstrate that the Random Forest algorithm, trained with a reduced number of features through PCA, yielded superior performance, with a lower error rate and a high R2 score of 0.98. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Machine learning

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The Queue’s Automated Creation of Doctor’s Calls by Patients in the Hospital with Visualization via the Mobile Application

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Journal of Mobile Multimedia 2023年第3期19卷 897-934页

作者： Zhuravska, Iryna Dvoretskyi, Mykhailo Kulakovska, Inessa Boiko, Anzhela Dvoretska, Svitlana Department of Computer Engineering Petro Mohyla Black Sea National University Mykolaiv Ukraine Software Engineering Department Petro Mohyla Black Sea National University Mykolaiv Ukraine Department of Intelligent Information Systems Petro Mohyla Black Sea National University Mykolaiv Ukraine

The spread of the COVID-19 virus is challenging society to provide medical care to a growing number of patients in the hospital. It is important to determine the patient from whom an urgent appeal was received earlier and to automate the creation of the calls’ queue. Determining the direction of the sound source, which is the patient’s voice, can be realized using the passive acoustic location method. In this case, it is necessary to place sound sensors in the wards with patients. In such a case, these sensors it is expedient to build in the lighting equipment executed in the shape of Platonic polyhedra. The microcontroller system, located inside such a spatial structure, ensures the transmission of sound to a server computer system. The above system alternately records the receipt of urgent appeals, analyzes the location of the sound source, and sends the relevant data to the doctor’s smartphone. The mobile application visualizes information about the location of the patients who need consultation or help. The proposed solution for intelligent analysis of voice appeals by inpatients may also be useful for post-stroke, post-infarction, and other bedridden patients who are unable to call medical staff otherwise than a voice. © 2023 River Publishers.

关键词： Automatic doctor calls’ queue determining the direction of the sound source microcontroller system mobile application Platonic polyhedra

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Security Aspects of Container Orchestration in Kubernetes Environments

Security Aspects of Container Orchestration in Kubernetes En...

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Sava Stanišić Milan Vesković Olga Ristić Borislav Đorđević Department of Computer and Software Engineering Faculty of Technical Sciences Čačak Republic of Serbia IMP Computer Systems Mihajlo Pupin Institute Belgrade Republic of Serbia

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

Security is one of the key challenges in container orchestration, especially in complex environments. This paper explores the security aspects of implementing containerized applications using Docker within a Kubernetes cluster. The first part of the paper describes Docker, Kubernetes, and various ways of applying them within DevOps methodology. It then presents potential vulnerabilities during the implementation of these technologies, as well as vulnerabilities specific to Docker and Kubernetes. Subsequently, some solutions for securing a Kubernetes environment are described.

关键词： DevOps Scalability Organizations Containers Stability analysis Malware Complexity theory Security Object recognition Resilience

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Dimensions in Measuring Performance of Agile software Development Projects: A Literature Review

Dimensions in Measuring Performance of Agile Software Develo...

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2022 Applied Informatics International Conference, AiIC 2022

作者： Beh, Hooi Ching Jusoh, Yusmadi Yah Abdullah, Rusli Hassan, Sa'Adah Universiti Tunku Abdul Rahman Department of Internet Engineering and Computer Science Selangor Malaysia Universiti Putra Malaysia Department of Software Engineering and Information Systems Selangor Malaysia

ISBN: (数字)9781728184289

ISBN: (纸本)9781728184289

Adopting and implementing Agile principles and practices in a software development project is not new these days. With the flexibility to manage changes in requirements and the rapid delivery of work products, many organisations transition from a plan-driven approach to an agile-driven one, ultimately promising high-quality work products. Some studies reported that it is a struggle for some development teams to measure the performance in agile-based projects. The purpose of this paper is to review the current literature on performance measurement frameworks or models, especially in an agile context. By conducting the literature searches and reviews, this paper provides information on the implementation of measurement metrics in agile software development projects. There are many different dimensions in measuring the performance of agile-based projects: organisational, process, project/team and individual. Each dimension is not an independent entity but intertwined in many ways. For organisations working on agile software development projects, further research is required to gain insight into the metrics of each dimension, the relationships between dimensions, and the possible integration of multiple dimensions. © 2022 IEEE.

关键词： Requirements engineering

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Aspect-Based Sentiment Analysis on Amharic Text for Evaluating Ethio-Telecom Services 2

Aspect-Based Sentiment Analysis on Amharic Text for Evaluati...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Tesfa, Tarikwa Belete, Befikadu Abera, Samuel Mohapatra, Sudhir Kumar Das, Tapan Kumar Addis Ababa Science and Technology University Department of Software Engineering Addis Ababa Ethiopia Ethio Telecom Services Addis Ababa Ethiopia Sri Sri University Faculty of Emerging Technologies Cuttack India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350328202

People are increasingly expressing their views and opinions about a company's goods or service on social media these days. For all types of businesses and organizations, sentiment analysis in text can be used to find prospective customers and obtain quick feedback on the services or goods they provided. As a result, the organization has a better chance and opportunity to meet the needs of the consumer. Using sentiment analysis, we may extract important information from the thoughts and emotions of an organization's supporters and clients. It examines natural language content produced about services and goods. Detailed opinion mining at the aspect/feature level to serve consumer and organizational needs. In this study, three different machine learning algorithms, these are Naïve Bayes (NB), Support Vector Machine (SVM), and K- Nearest Neighbor (KNN) are used to build the proposed aspect-based sentiment analysis model from the customer comments in Amharic text which is collected from Ethio-telecom official Facebook page. The collected data is annotated into sentiment polarity and aspect-based sentiment classes by the help of five annotators. After data annotation, different preprocessing tasks were implemented. Bag of words and TF-IDF word representation techniques were used to represent each unique word to their vector representation. The experiment was conducted on those three models and the result was validated. The labeled aspects were not balanced so that a SMOTE class imbalance handling technique was employed to the dataset. Finally, SVM model trained with TF-IDF word representation technique with SMOTE oversampled dataset has achieved the highest accuracy result of 98% as compared to NB and KNN. © 2024 IEEE.

关键词： Sentiment analysis

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Intelligent Agriculture Robot for Tea Plantation Preservation - TeaBot 25

Intelligent Agriculture Robot for Tea Plantation Preservatio...

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25th International Multi Topic Conference, INMIC 2023

作者： Gunawardana, Imalka Perera, Varnavi Premathilake, Thulya Bamunusinghe, Gayan Lokuliyana, Shashika Gamage, Narmada Silva, Rajitha De Sliit Dept. of Software Engineering Malabe Sri Lanka Sliit Dept. of It Malabe Sri Lanka Sliit Dept. of Computer Systems Engineering Malabe Sri Lanka University of Lincoln Agri-Robotics Lincoln United Kingdom

ISBN: (纸本)9798350317701

Tea cultivation stands out as one of the most significant export products that contribute to the Gross Domestic Product (GDP). In the previous decades, the substantial work-force gradually transitioned to different occupations. Compared to other crops, tea cultivation demands costly and meticulous upkeep. With a shortage of labor, maintaining tea estates grew tougher, leading to decreased yields. In reaction, estate owners transitioned to cultivating low-maintenance crops. The TeaBot is an advanced robot designed to replace human labor for watering and fertilizing vast tea estates. The TeaBot distinguishes itself by operating in rough outdoor terrain and infrastructure-free navigation in real tea plantations. Given that tea plants demand continuous hydration and nutrients for optimal crop yield, TeaBot plays a pivotal role in enhancing efficiency while reducing water and fertilizer wastage. Mainly four motor-powered wheels move accurately by translating linear and angular velocities using a precise motor control algorithm. An autonomous navigation algorithm was developed using two distinct approaches, which include deep learning-based computer vision and classical computer vision. The selection of the classical computer vision method was predicated upon its notable attributes, including high precision, minimal resource utilization, and optimal efficiency. A deep learning-based stem identification model was trained based on MobileNetV2 architecture to detect where the plant stem meets the ground for efficient hydration of individual plants. This lightweight model achieved 90% detection accuracy. The precise results of stem detection have made the liquid fertilization process more efficient. © 2023 IEEE.

关键词： computer vision

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F-IKOS: An Abstract Interpretation-based Static Analyzer for Fortran Programs 12

F-IKOS: An Abstract Interpretation-based Static Analyzer for...

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12th International Workshop on Quantitative Approaches to software Quality, QuASoQ 2024

作者： Zou, Sheng Chen, Liqian Fan, Guangsheng Huang, Renjie Yin, Banghu College of Computer Science and Technology National University of Defense Technology Changsha410073 China State Key Laboratory of Complex & Critical Software Environment Changsha410073 China College of Systems Engineering National University of Defense Technology Changsha410073 China

The Fortran programming language is widely utilized in numerical computation and scientific computing. Fortran programs are prone to potential runtime errors related to numerical properties due to the large number of numerical operations. In this paper, we present F-IKOS, an abstract interpretation-based static analyzer for Fortran programs on top of IKOS, which soundly handles floating-point types in Fortran programs. Firstly, we translate Fortran programs to LLVM IR using compiler front-end Flang. After that, we extend IKOS to support sound floating-point analysis and then employ it to analyze the translated LLVM IR. Particularly, when analyzing floating-point types in programs, we first abstract floating-point expressions into real-number expressions with interval coefficients, and then linearize these expressions into real-number expressions with scalar coefficients. These linear expressions are subsequently handled by abstract domains originally designed for real-number types to produce sound analysis results. We have conducted experiments on representative Fortran programs to show the efficiency and effectiveness of F-IKOS. The experimental results are encouraging: F-IKOS soundly analyzes runtime errors in complex programs, outperforming other analyzers. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： FORTRAN (programming language)

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Optimizing Multilingual Sentiment Analysis in Low-Resource Languages with Adaptive Pretraining and Strategic Language Selection

Optimizing Multilingual Sentiment Analysis in Low-Resource L...

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Computing and Machine Intelligence (ICMI), International Conference on

作者： Nilanjana Raychawdhary Amit Das Sutanu Bhattacharya Gerry Dozier Cheryl D. Seals Computer Science & Software Engineering Auburn University Auburn AL USA Computer Science & Computer Information Systems Auburn University at Montgomery Montgomery AL USA

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

In the realm of natural language processing (NLP), sentiment analysis has traditionally focused on resource-rich languages like English, often overlooking the linguistic diversity and potential of low-resource languages. This research aims to ad-dress this imbalance by concentrating on multilingual sentiment classification in twelve African languages: Hausa, Yoruba, Igbo, Nigerian Pidgin, Amharic, Algerian Arabic, Moroccan Arabic Darija, Swahili, Kinyarwanda, Twi, Mozambican Portuguese, and Xitsonga. Recognizing the critical lack of comprehensive datasets for these languages, our research not only highlights the need for such resources but also endeavors to fill this gap by assessing current NLP techniques and devising novel methodologies specifically tailored to these linguistically diverse yet under- resourced languages. Central to our study is the development and deployment of a transformer-based language model that is intricately adapted for African languages with limited resources. By refining the XLM-R model on the AfriSenti-SemEval 2023 Shared Task 12 multilingual sentiment classification datasets, we explore the model's efficacy in handling sentiment analysis tasks across these languages. The empirical results demonstrate the model's capability to perform sentiment analysis with considerable accuracy, even in languages that have traditionally been marginalized in the digital sphere due to minimal linguistic resources. This research not only contributes to the field of NLP by extending its reach to less-researched African languages but also underscores the importance of linguistic inclusivity in the development of AI technologies. By successfully navigating the challenges posed by multilingual sentiment classification in low-resource languages, our study takes a significant stride in closing the digital language divide. It emphasizes the potential of NLP to be a tool for cultural and linguistic preservation and highlights the necessity of developing technolog

关键词： Adaptation models Sentiment analysis Analytical models Navigation Transfer learning Refining Linguistics

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Blockchain-Enhanced Framework for Secure Third-Party Vendor Risk Management and Vigilant Security Controls

Blockchain-Enhanced Framework for Secure Third-Party Vendor ...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Gupta, Deepti Elluri, Lavanya Jain, Avi Moni, Shafika Showkat Aslan, Omer Texas A&m University - Central Texas Dept. of Computer Information Systems TX United States College of Business University of Tampa FL United States Embry-Riddle Aeronautical University Dept. of Electrical Engineering and Computer Science FL United States Bandirma Onyedi Eylül University Department of Software Engineering Bandirma Turkey

ISBN: (纸本)9798350362480

In an era of heightened digital interconnectedness, businesses increasingly rely on third-party vendors to enhance their operational capabilities. However, this growing dependency introduces significant security risks, making it crucial to develop a robust framework to mitigate potential vulnerabilities. This paper proposes a comprehensive secure framework for managing third-party vendor risk, integrating blockchain technology to ensure transparency, traceability, and immutability in vendor assessments and interactions. By leveraging blockchain, the framework enhances the integrity of vendor security audits, ensuring that vendor assessments remain up-to-date and tamperproof. This proposed framework leverages smart contracts to reduce human error while ensuring real-time monitoring of compliance and security controls. By evaluating critical security controls - such as data encryption, access control mechanisms, multi-factor authentication, and zero-trust architecture - this approach strengthens an organization's defense against emerging cyber threats. Additionally, continuous monitoring enabled by blockchain ensures the immutability and transparency of vendor compliance processes. In this paper, a case study on iHealth's transition to AWS Cloud demonstrates the practical implementation of the framework, showing a significant reduction in vulnerabilities and marked improvement in incident response times. Through the adoption of this blockchain-enabled approach, organizations can mitigate vendor risks, streamline compliance, and enhance their overall security posture. Our findings highlight the importance of employing blockchain to enforce security controls and maintain compliance with healthcare regulations such as HIPAA. In this paper, we present a comprehensive set of security controls and demonstrate how blockchain technology enhances their effectiveness, ensuring greater transparency, accountability, and automation in vendor assessments. By reducing human error, e

关键词： Smart contract

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