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Cognitive Complexity Analysis and Optimization Tool for Java 1

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： De Silva, D. I. Wijesundara, D. A. R. Perera, V. H. P. Rathnayake, M. R. T. N. Udumulla, C. J. Godapitiya, V. Sri Lanka Inst Informat Technol Malabe Sri Lanka

ISBN: (数字)9789819735624

ISBN: (纸本)9789819735617;9789819735624

Cognitive complexity, often neglected initially, becomes a significant challenge as software systems expand. This article introduces the Cognitive Complexity Analysis and Optimization Tool to address this issue comprehensively. Cognitive Complexity Analysis and Optimization Tool incorporates various metrics, graphical visualizations, and suggestions for complexity reduction, enhancing code quality and maintainability. The study outlines specific objectives: reducing cognitive complexity, enhancing code reliability, streamlining software maintenance, providing reporting and visualization capabilities, and offering an interface for automatic code complexity reduction. This research focuses on modern software development challenges, emphasizing the importance of lower cognitive complexity and streamlined maintenance processes. The article reviews extensive research in cognitive complexity metrics, highlighting the limitations of existing methods and introducing the Improved CB measure as the proposed tool's primary metric. The methodology adheres to the Institute of Electrical and Electronics Engineers Standard for Software Quality Metric Methodology, ensuring rigorous quality standards. In conclusion, the proposed tool automates the computation of cognitive complexity, code size, and code maintainability, offering enhanced insights into Java-based system development. It streamlines code refactoring and provides optimized code suggestions, contributing to cost and time savings in software development and maintenance.

关键词： Cognitive complexity ICB metric Maintainability index Large language model

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Smart Grid and Renewable Energy Security Challenges: A Review 13th

Smart Grid and Renewable Energy Security Challenges: A Revie...

引用

13th Computer Science Online Conference

作者： Ali, Zahraa Abdullah Abduljabbar, Zaid Ameen AL-Asadi, Hamid Ali Abed Nyangaresi, Vincent Omollo Aldarwish, Abdulla J. Y. Neamah, Husam A. Univ Basrah Dept Comp Sci Coll Educ Pure Sci Basrah 61004 Iraq Jaramogi Oginga Odinga Univ Sci & Technol Dept Comp Sci & Software Engn Bondo 40601 Kenya SIMATS Saveetha Sch Engn Dept Appl Elect Chennai 602105 Tamil Nadu India Gujarat Univ Dept Comp Sci Ahmadabad 380009 Gujarat India Univ Debrecen Dept Elect Engn & Mechatron Fac Engn Otemeto U 4-5 H-4028 Debrecen Hungary

ISBN: (纸本)9783031702990;9783031703003

Today, with the diversity of electric power sources and the huge size of electrical power networks, and because of the harmful waste from non-renewable energy sources, the trend of the current world has led to the use of smart energy networks and devices, especially smart meters, which facilitate the management and make it easy to control the energy network efficiently, reliably, and safely. The integration and use of renewable energy resources in the smart grid, such as wind, sunlight, and others, has led to the mitigation of the effects of harmful waste on the environment, but these networks are not free of many risks and challenges, especially cyber-attacks and their effects on these networks, where strict preventive measures require the prevention of these attacks. One of them, the use of early detection systems, protection, and security measures, requires the integration of renewable energy sources with the smart grid to modify the infrastructure to ensure secure and efficient management of energy. The use of modern communication technologies and protocols improves the transmission of energy. One of the most important issues facing the modern energy economy is the development and implementation of a smart grid for energy supply. Smart grid uses two-way digital technology to transfer electricity from producers to consumers and enables consumers to control factory machinery and household appliances to save energy while lowering costs, boosting reliability and promoting transparency. To address supply security, global warming, and energy independence, numerous countries are endorsing this contemporary electrical infrastructure, with the smart grid being a vital infrastructure. These large and complex systems are exposed to many types of cyber-attacks In this paper provides a glimpse of the attacks on smart networks and the proposed solutions to reduce these attacks and enhance the security of smart networks. A summary of SCADA networks in renewable energy sources,

关键词： Smart power grids

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Making Learning Effective on Smart Mobile Online Educational Games 1

引用

Computing Conference

作者： Eng, Bah Tee Song, Insu James Cook Univ 149 Sims Dr Singapore Singapore

ISBN: (数字)9783031622731

ISBN: (纸本)9783031622755;9783031622731;9783031622724

Puzzle game continues to be a popular mobile game genre in 2023. Popular pattern-matching non-educational puzzle games like Candy Crush Saga, Bejeweled and Toon Blast with their simple gameplay, intuitive interface and colourful graphics are found to be quite addictive for both young and old as there are always challenges and rewards at every level of the game. To capitalise on the success of these pattern matching non-educational puzzle games, using the pattern matching game mechanics in educational game is therefore an attractive idea. We modified the Toon Blast game to create SmashingPatterns, a pattern matching educational puzzle game to teach Mathematics (linear equations). We evaluated the learning effectiveness of using SmashingPatterns by a control experimental study involving a group comprising twenty students who use SmashingPatterns instruction and a control group of twenty studentswho receive the classroom-based PowerPoint instruction. Both groups take the assessment test before and after their instructions. The results showed we managed to prove the learning experience hypothesis set out for this study. However, there is no significant evidence that learning is effective using the SmashingPatterns instruction. In conclusion, using learning content from classroom activities together with popular pattern-matching game mechanics can be a successful combination for learning.

关键词： Learning effective Smart mobile online educational games Learning content

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Predicting Health Status of Maize Crops by Integrating IoT Technology and Inception-v3 Convolutional Neural Network in Precision Agriculture 1

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9th International Congress on Information and Communication Technology (ICICT)

作者： Jururyishya, G. Bisetsa Nzanywayingoma, F. Musabe, R. Habimana, J. Claude Abingabiye, C. Univ Rwanda Coll Sci & Technol African Ctr Excellence Internet Things Kigali Rwanda Univ Madras Chennai India

ISBN: (数字)9789819733057

ISBN: (纸本)9789819733040;9789819733057

In Africa, particularly in Rwanda, maize serves as a significant income source. However, the growth of maize is often hampered by various diseases, resulting in decreased yield production. To mitigate these challenges and reduce human errors, farmers may take advantage of current emerging technologies such as artificial intelligence (AI) and Internet of things (IoT) for automating their farms by monitoring or regulating crucial resources like soil features, crops pests, and insects. The study specifically explores the utilization of an IoT-based system integrated with Inception-v3 of convolutional neural networks machine learning algorithm. The proposed solution incorporates a BME280 sensor to measure field pressure, humidity, and temperature in maize crops, along with an Inception-v3 convolutional neural network model to predict maize crop health status and provide real-time data insight to the farmers. The outcomes demonstrate exceptional performance, with an accuracy rate of 99.5%. Furthermore, the model has significantly reduced losses from 54 to 2%.

关键词： Machine learning Inception-v3 IoT Precision agriculture Maize crops health status

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Multidimensional Air Pollution Sensitivity Analysis for Intelligent Decision Modeling by Means of Quasi-Monte Carlo Sequences

Multidimensional Air Pollution Sensitivity Analysis for Inte...

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Todorov, Venelin Georgiev, Slavi Georgiev, Ivan Traneva, Velichka Tranev, Stoyan Bulgarian Acad Sci Inst Math & Informat Dept Informat Modeling 8 Acad Georgi Bonchev St Sofia 1113 Bulgaria Bulgarian Acad Sci Inst Informat & Commun Technol Dept Parallel Algorithms & Machine Learning Neurotechnol Lab 25A Acad Georgi Bonchev St Sofia 1113 Bulgaria Angel Kanchev Univ Ruse Dept Appl Math & Stat 8 Stidentska St Ruse 7004 Bulgaria Prof Dr Asen Zlatarov Univ Bourgas Dept Math Informat & Phys 1 Prof Yakim Yakimov Blvd Burgas 8010 Bulgaria Prof Dr Asen Zlatarov Univ Bourgas Dept Ind Technol & Management 1 Prof Yakim Yakimov Blvd Burgas 8010 Bulgaria

ISBN: (纸本)9783031671913;9783031671920

In this paper, we introduce a sophisticated method of sensitivity analysis for air pollution simulation, employing cutting-edge stochastic techniques within a comprehensive, long-distance air pollutant transport model, specifically the Unified Danish Eulerian Model (UNI-DEM). This model plays a crucial role in examining the detrimental impacts of elevated air pollution levels. We employ these stochastic algorithms to calculate global Sobol sensitivity indices, which help in understanding the impact of different input variables on key air pollutants in several European cities, each with its distinct geographical context. The aim of this study is to enhance our comprehension of the elements influencing air pollution and to aid in developing effective approaches to reduce its negative impact on the environment.

关键词： Sensitivity analysis Air pollution Monte Carlo

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0/1 1-D Bin Packing Problem Solved by a Recent Nature-Inspired Optimizer 13th

0/1 1-D Bin Packing Problem Solved by a Recent Nature-Inspir...

引用

13th Computer Science Online Conference

作者： Olivare, Rodrigo Medina, Sebastian Godoy, Jaime Univ Valparaiso Escuela Ingenieria Informat Valparaiso Chile

ISBN: (纸本)9783031705946;9783031705953

Optimization is an entire field that aims to improve efficiency and effectiveness across various domains. Its primary objective is to minimize costs, time, and risks while maximizing gains, quality, and efficiency. In this context, the 0/1 1-D bin packing problem is one of combinatorial optimization's most challenging and extensively studied problems. This problem holds significant practical applications in supply chain management, packaging design, and resource optimization. This work solves the 0/1 1-D bin packing problem using a nature-inspired golden eagle optimizer. The hunting behavior of golden eagles inspires this bio-solver, and it employs swarm intelligence-based strategies to approximate solutions. We perform a comparative analysis of the bio-inspired algorithm to evidence its yield. We use twenty instances of the 1-D bin packing problem. Computational results show that the golden eagle optimizer exhibits better results in convergence time than well-known bio-inspired algorithms.

关键词： Optimization problems Bin packing problem Metaheuristics Golden Eagle Optimizer

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Information Security Primitives Automatic Variable Key Approaches and Cryptic Mining

Information Security Primitives Automatic Variable Key Appro...

引用

2024 International Conference on Computing, Communication, Cybersecurity and AI

作者： Prajapat, Shaligram Devi Ahilya Univ Int Inst Profess Studies Indore India

ISBN: (纸本)9783031744426;9783031744433

The scope of cryptic mining and AI-enabled cryptanalysis is critical for advancing information security and enhancing cryptosystems. For this, we have focused on Cryptographic Methods for information systems. These are essential to conceal patterns of input, On the other hand data mining techniques aim to uncover them. In this paper ten fundamental operations (Cryptographic Primitive) namely Encryption/Decryption, Hash Functions, Authentication, Access Control, Key Management, Digital Signatures, Secure Communication Protocols (SCP), Intrusion Detection systems (IDS), Security Auditing and Logging and Secure Random Number Generation are discussed as core functionality of Cryptosystems. To analyze them cryptic mining concepts are also discussed. This paper presents the algorithms of cryptosystems with their complexity analysis. It also highlights the conceptual description of Cryptic mining algorithms. The paper throws light on applications to Honeypot and Honey Net systems.

关键词： Information security primitives AVK Cryptic Mining Cryptosystems

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Real-Time Obstacle Detection Using YOLOv8 on Raspberry Pi 4 for Visually Challenged People 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Upadhyaya, Bijoy Kumar Pramanik, Pijush Kanti Dutta Roy, Priyanka Sen, Rituparna Tripura Inst Technol Dept Elect & Commun Engn Narsingarh Tripura India Galgotias Univ Sch Comp Applicat & Technol Greater Noida India

ISBN: (数字)9789819713202

ISBN: (纸本)9789819713196;9789819713202

Visual impairment poses significant challenges to individuals' daily lives, particularly in navigating and comprehending their surroundings. In recent years, notable advancements in computer vision technology have facilitated the development of novel applications specifically designed to cater to the requirements of individuals with visual impairments. Developing a system that allows users to identify and locate obstructing objects in their immediate surroundings requires real-time and accurate object detection. Among the cutting-edge algorithms, You Only Look Once (YOLO) marks itself due to its remarkable efficiency and precision. This research article aims to implement YOLOv8, a state-of-the-art computer vision algorithm on Raspberry Pi 4, an affordable, portable, and small single-board computer. The system's ability to detect and recognise common indoor objects is evaluated through extensive testing with multiple real-case scenarios.

关键词： Object detection Raspberry Pi 4 Visually challenged YOLOv8

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Learning Factory for Integrating Engineering Technology and Business Management Education 14th

Learning Factory for Integrating Engineering Technology and ...

引用

14th International Conference on Learning Factories (CLF)

作者： Wanyama, Tom Centea, Dan Mehrtash, Moein McMaster Univ Hamilton ON L8S 4L8 Canada

ISBN: (纸本)9783031653995;9783031654008

Advanced manufacturing demands seamless integration of manufacturing, information, and communication technologies to facilitate real-time information sharing across the entire value chain. Teaching the intricate art of integrating these technologies and associated business models is a challenge. This paper explores the potential of learning factories in bridging this educational gap, leveraging their proven effectiveness in fostering practical competencies in engineering, technology, and business. While learning factories are recognized for their effectiveness in teaching multidisciplinary skills, most are limited in scope, focusing on specific facets of manufacturing, such as lean management, resource efficiency, quality control, and logistics. This paper discusses how the School of Engineering Practice and Technology (SEPT) Learning Factory at McMaster University, has been tailored to support courses spanning various domains of manufacturing, including Industry 4.0, industrial systems integration, and business management. The SEPT Learning Factory operates using an innovative model, producing marketable products that are either sold in the open market or donated to deserving community members. This way, the factory effectively addresses two crucial limitations commonly associated with such educational facilities. Firstly, it tackles the issue of low return on investment, often linked to the substantial resources required for learning factory development and operation. Secondly, it expands the scope of resources available for learning, breaking free from the confines of examining only select aspects of industrial production. Finally, this paper presents the SEPT Learning Factory's role as an enabler of integrated practice-based education, elucidating how it fosters a holistic understanding of modern manufacturing technologies and business management.

关键词： Advanced Manufacturing Industry 4.0 Integrated Practice-based Education Learning Factory Engineering Technology and Business Education

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Evaluation of Nano-Object Magnetization Using Artificial Intelligence 1

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2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI)

作者： Goranov, V. A. Mikhaltsou, S. Surpi, A. Cardellini, J. Pineiro, Y. Rivas, J. Valle, F. Dediu, V. A. BioDevice Syst Sro 10 Vrsovice996-20 Prague 10100 Czech Republic CNR Ist Studio Mat Nanostrut ISMN Via Gobetti 101 I-40129 Bologna Italy Univ Firenze Dipartimento Chim Ugo Schiff Via Lastruccia 3 I-500129 Sesto Fiorentino Italy Consorzio Sistemi Grande Interfase CSGI Via Lastruccia 3 I-500129 Sesto Fiorentino Italy Univ Santiago De Compostela NANOMAG Lab iMATUS Santiago De Compostela 15782 Spain CNR Ist Microelettron & Microsistemi I-40129 Bologna Italy

ISBN: (数字)9783031608407

ISBN: (纸本)9783031608391;9783031608407

Despite the immense potential of magnetic nanoparticles in biomedicine, their widespread application is hindered by the lack of experimental methodologies for the widely available measure of fundamental physical parameters such as hydrodynamic radius and magnetization. In this study, we propose employing "artificial intelligence-based" image analysis to extract these parameters from videos of experiments with magnetic nanoparticle concentration under the influence of magnetic field. Various solutions of magnetic nanoparticles and their complexes with liposomes, each having different magnetization levels, display distinctive temporal dynamics. The videos captured during these experiments were used to create a dataset of time-dynamic video frames, which was then processed using machine-learning techniques. For semantic segmentation of analyzed frames within a specific experiment, neural network architectures based on U-Net have been trained. We achieve quite accurate predictions of nano-object relative magnetization (RM) within a percentage error range of 11.4% to 24.1% across a spectrum of nano-object magnetizations ranging from 12 to 68 emu/g.

关键词： machine learning neural network magnetic nanoparticles magnetic field artificial intelligence biomedical application

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