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ETHACA - A Container-Based Cyber Range for Research and Education 29

ETHACA - A Container-Based Cyber Range for Research and Educ...

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29th IEEE International Workshop on computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2024

作者： Chouliaras, Nestoras Kantzavelou, Ioanna Pantziou, Grammati Maglaras, Leandros Chouliara-Sidera, Panagiota Adamakos, Antonis Chalatsakos, Panagiotis University of West Attica Department of Informatics and Computer Engineering Athens Greece School of Computing Edinburgh Napier University EdinburghEH10 5DT United Kingdom University of Thessaly Department of Computer Science and Biomedical Infromatics Lamia Greece Senior Software Engineer at *** Athens Greece Open University of Cyprus Faculty of Pure and Applied Sciences Nicosia Cyprus

ISBN: (纸本)9798350377644

The advent of Industry 4.0 and the Industrial Internet of Things (IIoT) has revolutionized manufacturing and production systems, enhancing efficiency and communication through the integration of advanced technologies such as IoT devices and AI. However, this increased digitization has also led to heightened cybersecurity risks, with a notable rise in the frequency and complexity of cyber-attacks. Cyber Ranges emerges as a critical solution in addressing these challenges, offering a controlled environment for simulating cyber-attack scenarios, training cybersecurity teams, and developing robust defense strategies. The escalating demand for cybersecurity professionals has highlighted the crucial need for effective training solutions. This article presents an open-source Cyber Range constructed on container-based architecture, meticulously engineered for efficient operation with minimal resource consumption. In response to the scarcity of cybersecurity experts, this platform prioritizes extensive scalability and robust isolation between exercises, ensuring secure learning environments, and also integrates a complex developed exercise series aimed at strengthening cybersecurity learning experiences. These exercises encompass a variety of scenarios and challenges, catering to professionals at different skill levels. Each exercise replicates real-world cyber threats, offering practical, hands-on learning opportunities. Additionally, a comprehensive questionnaire accompanies these exercises, designed to gather feedback on participants' experiences. © 2024 IEEE.

关键词： Cyber attacks

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Voice Enabled Intelligent Programming Assistant 4

Voice Enabled Intelligent Programming Assistant

引用

4th International Conference on Advancements in Computing, ICAC 2022

作者： Wataketiya, Ravindu Chandrasiri, Navinda Kithsiri, Ramesh Malwatta, Hirush Nadeeshani, Madhuka Siriwardana, Samanthi Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

In modern era where software development is of vital importance, software developers are challenged with conditions like Repetitive Strain Injury (RSI) which hinders their ability to work effectively. Furthermore, people with difficulties with using their hands also find it challenging to program in the traditional manner. As a solution, coding with one's voice has been experimented with, but current solutions lack interactivity and are harder to use and setup leaving much room for improvement in this domain. In this research work, by using input classifier models with accuracies over 90%, intent classifiers with accuracies over 70%, code parsing and various human computer interaction techniques, we developed a conversationally interactive, programming language agnostic, easy to setup and easy to use Voice Coding Assistant. This will potentially help a global audience of programmers to achieve their goals and improve productivity and lead a healthier life. We have named the system thus developed, "Venic". © 2022 IEEE.

关键词： Human computer interaction

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Development of Low Resource Machine Learning Models for Child Cognitive Ability Assessments 4

Development of Low Resource Machine Learning Models for Chil...

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Kahawanugoda, Adithya Gnanarathna, Kulanika Meegoda, Nilan Monarawila, Randika Samarasinghe, Pradeepa Lindamulage, Asiri Gawesha Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

Automated cognitive assessment tools are state-of-the-art in assessing cognition development. Due to the low availability of resources, building automated cognitive ability evaluation tools is challenging. This study focuses on developing machine learning models using a limited amount of data to assess Reasoning IQ, Knowledge IQ, Mental Chronometry and Attention-levels of Sinhala-speaking children between the age of 7 to 9 years. Our solution includes Sinhala speech recognition systems, image classification models, gaze estimation, blink count detection and facial expression recognition models to evaluate the above four cognitive ability measuring factors. Open domain speech recognition has been used to evaluate complex Sinhala child verbal responses and limited vocabulary responses were assessed using an end-to-end speech recognition system, respectively achieving 40.1% WER and 97.14% accuracy. Additionally, the image classification models for handwritten Sinhala letter recognition and two shape recognition models have gained 97%, 89% and 99% accuracy. The linear regression model for attention level evaluation that utilizes the inputs from a combination of eye-gaze estimation, facial expression recognition and blink rate detection models has gained 85% accuracy. © 2022 IEEE.

关键词： Image classification

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Accurate Real-World Co-ordinate Finding and the Object Classification for the Robot Manipulator

Accurate Real-World Co-ordinate Finding and the Object Class...

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Embedded Systems and Artificial Intelligence (ESAI), International Conference on

作者： Sudeep Sharan Hung Do Thanh Peter Nauth Juan José Domínguez-Jiménez Faculty of Computer Science and Engineering Frankfurt University of Applied Sciences Frankfurt am Main Germany UCASE Software Engineering Group School of Engineering University of Cádiz Cádiz Spain

ISBN: (数字)9798331522056

ISBN: (纸本)9798331522063

This paper presents an object detection and classification of the objects using Deep Learning (DL). The integration of object detection algorithms and depth camera developed is capable of providing robots, such as self developed assistive intelligent robot called “ROSWITHA” (RObot System WITH Autonomy) with the ability to detect an object and interpret their surrounding environment. It also provides the real-world coordinates/position of the object in that environment, which helps the robot to perform some applications, such as grabbing and serving, etc. You Only Look Once (YOLO) is one of the most popular object detection algorithms which is treated as a single regression problem and is processed by a single neural network. In this work, the YOLOv5 (YOLO version 5) network is implemented on a depth camera “RealSense” for processing object detection and estimating the position of the objects. The model is trained on reduced/filtered application-required objects (e.g. bottle and cup) from the available COCO dataset, and the training outcome alongside the performance of the overall system was evaluated. The results exhibited a satisfactory performance of the model in accurately detecting and classifying the objects with a high confidence score ranging from the least to $\mathbf{7 2 \%}$ to the highest of $\mathbf{9 0 \%}$. The confidence score could also be adjusted by the user on the developed GUI to attain the most certain predictions.

关键词： YOLO Training Accuracy Robot kinematics Current measurement Robot vision systems Cameras Manipulators Distance measurement Robots

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Smart UML - Assignment Management Tool for UML Diagrams 4

Smart UML - Assignment Management Tool for UML Diagrams

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Weerasinghe, D.N.H. Thiwanka, K.A.T. Jayasith, H.B.C. Onella Natalie, P.A.D. Samantha Rajapaksha, U.U. Karunasena, Anuradha Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

The great majority of manual processes have been automated in the current day. Nonetheless, there is no reliable approach for evaluating UML diagrams for plagiarism and correctness. Unified Modeling Language (UML) provides the basis for UML diagrams. UML Diagrams are typically used to graphically express a system's stakeholders, activities, objects, and classes to get a deep knowledge of a particular system. UML diagrams are widely used by industry experts as well as beginners. Class diagrams and use case diagrams are the most commonly used diagrams in UML. Though most computer science-related students get assessed in UML modelling, diagram plagiarism isn't considered in most exams since it's a tedious task to perform. The proposed system automates capturing details in UML diagram components and generating a model answer from the given question scenario to compare the diagrams and calculate the plagiarism percentage with the correction percentage. © 2022 IEEE.

关键词： Unified Modeling Language

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Digital Platform to Empower the Self-Employment in Sri Lanka 6

Digital Platform to Empower the Self-Employment in Sri Lanka

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6th International Conference on Information Technology Research, ICITR 2021

作者： Wickramasinghe, H.C.P. Thebuwana, T.D. Wijesinghe, G.K.H.S. Dissanayake, U.N. Kodagoda, Nuwan Suriyawansa, Kushnara Faculty of Computing Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Sri Lanka

ISBN: (纸本)9781665420006

Unemployment is a huge problem around the world because a lack of job opportunities. People are unable to find the job opportunities according to their preferences and qualifications. As a solution for this, many countries are attempting to empower self-employment. Most of current world problems have been solved using modern technologies. Therefore, the development of self-employment also can be achieved through modern technology. The objective of our proposed platform, HIRELANCER, is empowering self-employment using modern technologies. HIRELANCER is bringing the consumers, service providers, and suppliers into the same platform. HIRELANCER will consist of innovative features that go beyond comparatively to other platforms such as an advanced mechanism to find best suitable service providers/suppliers for the service, handling the virtual front-desk, cost estimation for the services prior to contacting a service provider, and advanced facility to find a suitable career path for the people who are seeking career guidance. This research paper discusses how the innovative features of HIRELANCER will be beneficial for consumers, service providers, and suppliers and ultimately achieve our main objective, which is empowering self-employment in Sri Lanka. © 2021 IEEE.

关键词： Employment

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Ontological View-driven Intensional Semantic Integration for Information Systems in a Decentralized Environment 14

Ontological View-driven Intensional Semantic Integration for...

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14th International Conference on Knowledge engineering and Ontology Development, KEOD 2022 as part of 14th International Joint Conference on Knowledge Discovery, Knowledge engineering and Knowledge Management, IC3K 2022

作者： Ali Adhnouss, Fateh Mohamed Ali El-Asfour, Husam M. McIsaac, Kenneth El-Feghia, Idris Aburukba, Raafat Wahaishi, Abdulmutalib Dept. of Electrical & Computer Engineering University of Western London Canada Faculty of Information Technology Misurata University Libya Department of Computer Science and Engineering American University of Sharjah Sharjah United Arab Emirates Software Engineering Rochester Institute of Technology New York United States

ISBN: (纸本)9789897586149

Ontologies are an essential component of semantic integration approaches for information systems . In a decentralized environment, each specification of the domain reflects an Ontological view. However, the semantics characterization of information systems in such decentralized environment poses a significant issue related to their integration. Information systems are viewed as independent intensional entities with their own beliefs, distinct from those held by others. Such autonomy is distorted by traditional extensional semantics. Other entities’ beliefs are introduced into a given entity, thus affecting their beliefs. Additionally, the information that one entity provides to another entity may not be consistent with the information known by the latter. We need an alternative semantics for information integration, which is not dependent on the extension, but rather on the underlying conceptualization. This paper proposes a classification of the environment where the information systems lives and a novel modelling paradigm for information integration using intensional logic to model the ontological views. The model comprises a formal modeling approach for the conceptualization as well as for the semantic integration process. Copyright © 2022 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved.

关键词： Semantics

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Smart Farmer Education System for Disease Identification, Severity Assessment and Infestation Management (Brinjal) 17

Smart Farmer Education System for Disease Identification, Se...

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17th IEEE International Conference on Industrial and Information Systems, ICIIS 2023

作者： Bandara, Keshara Vidhanaarachchi, Samitha Nanayakkara, A.A.E. Kulasinghe, Kavindu Rajapakshe, Sanka Wickramasinghe, Asela Yapa, Kanishka Sri Lanka Institute of Information Technology Department of Information Technology New Kandy Road Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka University of Ruhuna Faculty of Agriculture Department of Soil Science Mapalana Kamburupitiya Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350323634

The agriculture industry is one of the most significant sources of foreign exchange and employment in the Sri Lankan market. Therefore, small crops play a crucial role in ensuring the food security of the population as they are integral components of Sri Lankan cuisine. However, industry experts have identified inefficient disease and pest management as a hindrance to production. This issue requires immediate attention and proper action, which can be effectively addressed through the utilization of ICT technologies. Consequently, this research paper proposes a smart system that aims to assist farmers and agriculture professionals by providing them with farmer education, disease and infestation management tools, as well as progression level calculations. The implementation of this system aims to uplift the agriculture industry in Sri Lanka. The developed 'AI-based mobile application system for Brinjal Diseases,' which is based on analyzing the eating patterns of leafhopper damage, presents an innovative approach to identify the most significant threats to Brinjal, specifically focusing on leafhopper damage. This proposed system effectively informs various stakeholders, including the Area Agricultural Research Officer, Seed Certification and Plant Protection Center (SCPPC), Agricultural Service Center, Office of the Register of Pesticides (ROP), Plant Protection Service (PPS), as well as farmers, regarding the dispersion and prevention of brinjal diseases and pest infections. © 2023 IEEE.

关键词： Crowdsourcing

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A Roadmap for Artificial Intelligence Augmented software Development Life Cycle: Aspects of Knowledge Vaporization

A Roadmap for Artificial Intelligence Augmented Software Dev...

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International Conference on Information Technology (ICIT)

作者： Wael Alzyadat Mohammad Al-Madi Mohammad Muhairat Nagham Al-Madi Feras Altarawneh Department of Software Engineering Faculty of Science and IT Alzaytoonah University of Jordan Amman Jordan Computer Science Al-Zaytoonah University of Jordan Amman Jordan Artificial Intelligence Faculty of Science and IT Alzaytoonah University of Jordan Amman Jordan Department of Software Engineering Faculty of Science and IT Al-Zaytoonah University of Jordan Amman Jordan

Artificial Intelligence Augmented software Development Life Cycle is a process for developing software that incorporates AI techniques and technologies. One aspect of AIASDLC is knowledge vaporization, which refers to the process of extracting and encapsulating knowledge from the AI model during development and making it available for use in other parts of the software development life cycle. The advantages of AIASDLC include; improved performance, increased efficiency, better decision-making, better user experience, better scalability, better security and compliance, and knowledge vaporization. Requirement engineering is the process of gathering, analyzing, and specifying the requirements for a software system. The context boundary, domain knowledge, application domain, and system boundary are all important concepts in requirement engineering that help define the scope and constraints of the system being developed. Understanding the context boundary is important because it helps identify the external factors that will affect the requirements of the system. Domain knowledge is the understanding and expertise in a specific field or area that is necessary for effective requirement engineering. The application domain is the specific area or field where the system will be used, and it is important to understand the application domain to gather and document the correct requirements for the system

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Smart Advertising Based on Customer Preferences and Manage the Supermarket 4

Smart Advertising Based on Customer Preferences and Manage t...

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Eishan Dinuka, W.H.A. Wickramasinghe, A.Y.S.W. Weerasinghe, W.S.H. Karunaratne, K.P.G. Liyanapathirana, Chethana Rupasinghe, Lakmal Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

As a developing country, Sri Lanka needs to go along with cutting-edge technologies. In the beginning phase of this digital advertising, multiple advertisements were displayed on the users' feeds, including advertisements despite their preferences. This was a terrible user experience for the users. However, smart advertising based on customer preferences can manage the flow of advertisements on the feed as per the users' preferences. This same technique can be used in handling advertisements while shopping at supermarkets. These advertisements can be directed based on demographic characteristics like face and gender and previous customer transactions. Additionally, providing the nearest supermarket they can reach based on their current location. Queue management is the next most crucial facility that needs to be provided to a supermarket. However, the manual system of queue management is not effective. But with a modernized queue management system, overcrowded supermarkets can be managed effectively. This proposed system also considers providing a chatbot service to manage customer inquiries in a reliable strategy. In this system, we mainly used the Keras model called VGGFace for face detection, the Conventional Neural Network and Keras-based model for gender detection, the TensorFlow model called Single Shot MultiBox Detection MobileNet for queue and crowd detection, the Apriori algorithm base model for predicting the buying pattern, a Keras-based model for Artificial Intelligence chatbot and finally, google map Application Programming Interface for the nearest supermarket finding are models and technology. This system was developed to manage a supermarket properly. © 2022 IEEE.

关键词： Sales

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