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International Conference on Advanced Learning Technologies (ICALT)

作者： S. Chatzinotas D. Sampson Advanced e-Services for the Knowledge Society Research Unit Informatics and Telematics Institute Centre for Research and Technology Hellas Athens Greece Department of Technology Education and Digital Systems University of Piraeus Piraeus Greece

Educational metadata can significantly enhance the effective description, search and retrieval of online learning objects and educational resources. Thus a number of international efforts have been initiated during the past few years and have defined educational metadata standards for the common description of educational resources. This paper presents the architectural components and the fundamental functionalities of a software toolkit (eMAP), which aims to assist and facilitate the process of designing and implementing an educational metadata application profile by modifying and combining one or more educational metadata standards.

关键词： Software tools XML Application software Educational technology Process design Software standards Standards development Informatics Telematics Digital systems

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ASK-CDM-ECTS: A Tool for Facilitating Common European University Course Description towards Higher Education Integration

ASK-CDM-ECTS: A Tool for Facilitating Common European Univer...

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International Conference on Advanced Learning Technologies (ICALT)

作者： Demetrios G. Sampson Panayiotis Zervas Renos Limnatitis Department of Digital Systems University of Piraeus Greece Advanced e-Services for the Knowledge Society Research Unit Informatics and Telematics Institute Centre for Research and Technology Greece University of Pireaus Piraeus GR

In this paper, we present ASK-CDM-ECTS, a Web based authoring environment for describing higher education study programmes and courses, as well as, their educational material, following an application profile of the course description metadata specification (CDM), namely, CDM-ECTS, that supports the specific requirements of the European credit transfer and accumulation system (ECTS).

关键词： Electrical capacitance tomography Educational institutions Helium Educational programs Educational technology Packaging Information retrieval Digital systems Societies Informatics

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A Case Study of Absolute- and Comparative-Based Life Cycle Assessment of Greek Organic Red Wine as it Affects "Climate Change"

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SSRN 2022年

作者： Tsalidis, Georgios Archimidis Kryona, Zoi-Panagiota Hatzisavva, Kiriaki Korevaar, Gijsbert Rapsomanikis, Spyridon Environmental and Networking Technologies and Applications Unit Athena - Research and Innovation Center in Information Communication and Knowledge Technologies Greece Biotechnology Department Delft University of Technology Netherlands Engineering Systems and Services Department Delft University of Technology Netherlands

Agriculture may play a crucial role in mitigating climate change due to the sequestration of atmospheric carbon dioxide. Environmental life cycle assessment (E-LCA) indicates which product has the lowest global warming potential (GWP), and the planetary boundaries (PBs) concept provides the safe operating space (SOS) in which human activity should occur, to mitigate the parameters that affect climate change. This study aims to apply E-LCA and the PBs concept to calculate the respective comparative and absolute environmental performance of a bottle of Greek red organic wine in 2021 and 2026, when the "case study" vineyard will have reached full capacity. Two scenarios were investigated for 2026 because viticulture may produce a minimum (2026 Low) or a maximum (2026 High) yield. The functional unit was a bottle of 0.75 L of wine and the system was modeled based on the product environmental footprint category rules for still wine. The SOS was developed based on four partitioning methods: grandfathering, economic, agri-land, and calorific content. The results show that 2021, 2026-Low, and 2026-High yields result in a GWP of 1.14, 0.76, and 0.69 kg ***-1, and the zeolite used in the grape-growing stage was the largest contributor to this result. The largest SOS was derived from the "economic partitioning" method due to the significance of the wine industry in the Greek economy. The carbon balance of 2021, 2026-Low, and 2026-High yields remains within the SOS. However, the margin for the 2021 yield is small, while the margin for the 2026-Low, and 2026-High yields is large enough for the wine producer to make even significant changes in the viticulture or winemaking stages. To conclude, the case study shows that red organic wine production and consumption in Greece results in climate change mitigation, and determining actual carbon sequestration in the viticulture stage is crucial. © 2022, The Authors. All rights reserved.

关键词： Carbon dioxide

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Increasing Diagnostic Accuracy by Meta Optimization of Fuzzy Rule Bases

Increasing Diagnostic Accuracy by Meta Optimization of Fuzzy...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Mario Drobics Janos Botzheim Laszlo T. Koczy Section on Medical Expert and Knowledge-Based Systems Core Unit for Medical Statistics and Informatics Medical University of Vienna Vienna Austria Department of Telecommunications and Media Informatics Budapest University슠of슠Technology슠and슠Economics Budapest Hungary

In medicine the decision on which test to choose for a given decision problem is a delicate problem. On the one hand a positive test should be a reliable indicator on the presence of a disease, while on the other hand a negative test is required to be an indicator on the absence of a disease. Of course, these two goals are conflicting and a balanced decision according to the current situation is required. Inductive learning methods for (fuzzy) rule bases are, however, typically not capable of optimizing such complex and problem depending goal functions. We therefore present a meta-learning algorithm which selects a subset from a previously generated set of fuzzy rules using bacterial evolutionary algorithms. We also present a study where the proposed method is used to generate a model for predicting the presence/absence of hepatitis, based on laboratory results.

关键词： Testing Diseases Medical diagnostic imaging Medical tests Learning systems Optimization methods Fuzzy sets Microorganisms Evolutionary computation Predictive models

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Intrusion Detection in 5G Cellular Network Using Machine Learning

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Computer systems Science & Engineering 2023年第11期47卷 2439-2453页

作者： Ishtiaque Mahmood Tahir Alyas Sagheer Abbas Tariq Shahzad Qaiser Abbas Khmaies Ouahada Knowledge Unit of Systems and Technology UMT Sialkot CampusSialkot51040Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Faculty of Computer Science National College of Business Administration and EconomicsLahore54660Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Faculty of Computer and Information Systems Islamic University of Madinah Madinah42351Saudi Arabia Department of Computer Science&IT University of SargodhaSargodha40100Pakistan Department of Electrical and Electronic Engineering Science University of JohannesburgP.O Box 524Auckland ParkJohannesburg2006South Africa

Attacks on fully integrated servers,apps,and communication networks via the Internet of Things(IoT)are growing *** devices’effectiveness harms end users,increases cyber threats and identity theft,raises costs,and negatively impacts income as problems brought on by the Internet of Things network go unnoticed for extended *** on Internet of Things interfaces must be closely monitored in real time for effective safety and *** the 1,2,3,and 4G cellular networks,the 5th generation wireless 5G network is indeed the great invasion of mankind and is known as the global advancement of cellular *** to this day,experts are working on the evolution’s sixth generation(6G).It offers amazing capabilities for connecting everything,including gadgets and machines,with wavelengths ranging from 1 to 10 mm and frequencies ranging from 300 MHz to 3 *** gives you the most recent *** countries have already established this technology within their *** is the most crucial aspect of using a 5G *** of the absence of study and network deployment,new technology first introduces new gaps for attackers and *** Protocol(IP)attacks and intrusion will become more prevalent in this *** efficient approach to detect intrusion in the 5G network using a Machine Learning algorithm will be provided in this *** research will highlight the high accuracy rate by validating it for unidentified and suspicious circumstances in the 5G network,such as intruder hackers/*** applying different machine learning algorithms,obtained the best result on Linear Regression Algorithm’s implementation on the dataset results in 92.12%on test data and 92.13%on train data with 92%precision.

关键词： Intrusion detection system machine learning confidentiality integrity availability

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Energy-efficient routing to prevent void holes in heterogeneous 5G wireless sensor network using game theory

Energy-efficient routing to prevent void holes in heterogene...

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Smart Computing and Application (ICSCA), International Conference on

作者： Abdul Mateen Abdul Ahad Salam Zia Ibraheem Shayea Sawsan Ali Knowledge Unit of Systems and Technology (KUST) University of Management and Technology Sialkot Pakistan Istanbul Technical University of Turkey Department of Computer Science University of Sialkot Sialkot Pakistan Department of Electronics and Communication Engineering Istanbul Technical University Department of Computer Science and Engineering University of Ha'il Ha'il Saudi Arabia

Heterogenous 5G wireless Sensor Networks face several constraints throughout the routing process. Reduced costs, minimal energy use, and reliable data transmission between nodes are the primary problems of a heterogenous 5G wireless sensors network. During the transmission process of nodes, vacant holes use the most energy. The two most problematic aspects of heterogenous 5G WSNs are the location mentioned above mistake and the battery drain on individual nodes. However, the network's performance suffers significantly due to data packet loss and excessive energy consumption. Thus, many routing protocols incorporate various energy-saving techniques. In contrast, a routing strategy is suggested in this research to prevent void holes and maximize network stability. In addition, the scalability and efficacy of the proposed protocol are demonstrated by comparing it with state-of-the-art protocols. This study also introduces the idea of location error to increase the network's efficiency. In addition, a scalability study of the suggested systems has been conducted. Extensive simulations were also conducted to evaluate the effectiveness of the proposed technique. The findings confirm that the recommended routing strategy outperforms the competing schemes.

关键词： Wireless sensor networks 5G mobile communication Scalability Packet loss Routing Stability analysis Routing protocols

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Brain-Controlled Computer Tasks for Paralyzed Persons: Framework Overview

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Procedia Computer Science 2024年 237卷 28-35页

作者： Amna Imran Haider Chaudhary Maimoona Tariq Zahra Ali Abdul Ahad Hammad Naqvi Paulo Jorge Coelho Ivan Miguel Pires Knowledge Unit of Science and Technology University of Management and Technology Sialkot Pakistan School of Software Northwestern Polytechnical University Xian Shaanxi 710072 P. R. China Department of Computer Science Istanbul Technical University Turkey Polytechnic of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra Coimbra Portugal Instituto de Telecomunicações Universidade da Beira Interior Covilhã Portugal

To bridge the digital barrier between those with disabilities and those without impairments, several applications can be operated by brain signals. It highlights the importance of employing brain-computer interfaces (BCI) and mentions a specific system called the "Brain-Controlled Computer System" that can control a computer cursor and perform mouse actions using brain signals.. The system can control the cursor and provide mouse left/right click with brain signals using a low-cost Brainlink Lite device. Based on this system, we employed machine learning and deep learning methodologies to develop a system that classifies brain signals for cursor movement. The methodology involved gathering user input through surveys, interviews, and comparison studies, as well as utilizing pre-developed datasets collected using a mind sensor. We initially trained a model on a previous dataset, achieving approximately 70% accuracy. However, when applied to the new dataset, the accuracy dropped to 49%. To improve the results, we experimented with more complex models, including additional layers and a dropout layer to prevent overfitting. Despite these enhancements, the accuracy only reached a maximum of 52%. The research team collected a dataset tailored to their specific application. They made a groundbreaking discovery by applying a convolutional neural network (CNN), typically used for image analysis, to process continuous brainwave data. Despite this non-standard use, their hypothesis proved correct, with the CNN model achieving an impressive 80% accuracy in classifying brain signals for controlling a cursor.

关键词： Brain-Controlled Brainlink Lite EEG Machine Learning Deep learning

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Ransomware Detection and Classification using Ensemble Learning: A Random Forest Tree Approach

Ransomware Detection and Classification using Ensemble Learn...

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International Conference on Wireless Networks and Mobile Communications (WINCOM)

作者： Shahid Anwar Abdul Ahad Mudassar Hussain Ibraheem Shayea Ivan Miguel Pires Knowledge Unit of Systems and Technology (KUST) University of Management and Technology Sialkot Pakistan School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University Instituto de Telecomuniocações Covilhã Portugal Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Viruses significantly threaten computer systems, potentially causing extensive damage and data loss. All users must prioritize cybersecurity by installing effective antivirus software, safeguarding their PCs against potential harm. Even though there are many different kinds of malware, ransomware is particularly dangerous since it prevents victims from accessing their vital data or locks files permanently unless they pay a ransom to the attackers. Recent ransomware strains must be categorized promptly. Data for the present investigation was gathered from a variety of web resources, including Kaggle and ***. Concerning using Kaggle to acquire harmless datasets, *** is retrieved for use in a study on ransomware. Many preprocessing methods, such as Normalisation and Imputation, are used to polish our datasets. The most recent additions to the dataset were classified using the Random Forest tree classifier, with a final accuracy of 99.9%. Random Forest Tree fared exceptionally well compared to the KNN and SVM algorithms. We also highlighted that additional preprocessing methods can enhance outcomes for SVM and KNN.

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Improving Accuracy in Cloud Service Provider Ranking: Integrating TOPSIS with CAIQ-based QoS Assessment

Improving Accuracy in Cloud Service Provider Ranking: Integr...

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International Conference on Wireless Networks and Mobile Communications (WINCOM)

作者： Zahra Ali Abdul Ahad Ibraheem Shayea Ivan Miguel Pires Knowledge Unit of Systems and Technology (KUST) University of Management and Technology Sialkot Pakistan School of Software Northwestern Polytechnical University Xian Shaanxi P.R. China Department of Electronics and Communication Engineering Istanbul Technical University Instituto de Telecomuniocações Covilhã Portugal Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

The search for a reliable cloud service provider has become increasingly complex due to the increasing reliance on them. Researchers have developed a multi-criteria decision-making (MCDM) method, including the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for ranking. However, the selection process often relies on only a few aspects of service quality, known as Quality of Service (QoS) parameters. This research proposes a comprehensive methodology, using the Consensus Assessment Initiative Questionnaire (CAIQ) to select standardized QoS parameters and then applying the MCDM method, incorporating TOPSIS, to rank cloud service providers based on their performance. This approach aims to improve the accuracy and reliability of the selection process, enabling individuals and organizations to confidently identify and choose the most trustworthy cloud service providers for their specific needs.

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Reports of the AAAI 2009 spring symposia

Reports of the AAAI 2009 spring symposia

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作者： Bao, Jie Bojars, Uldis Choudhury, Tanzeem Ding, Li Greaves, Mark Kapoor, Ashish Louchart, Sandy Mehta, Manish Nebel, Bernhard Nirenburg, Sergei Oates, Tim Roberts, David L. Sanfilippo, Antonio Stojanovic, Nenad Stubbs, Kristen Thomaz, Andrea L. Tsui, Katherine Woelfl, Stefan Tetherless World Constellation Rensselaer Polytechnic Institute United States Social Software Unit of DERI Galway Ireland Computer Science Department Dartmouth College United States Knowledge Systems at Vulcan Inc United States Adaptive Systems and Interaction Group Microsoft Research Redmond United States School for Mathematics and Computer Sciences Heriot-Watt University United Kingdom School ot Interactive Computing Georgia Institute of Technology United States Department of Computer Science University of Freiburg Germany Computer Science and Electrical Engineering Department University of Maryland Baltimore County United States Pacific Northwest National Laboratory Richland WA United States University of Karlsruhe Germany IRobot Corporation United States University of Massachusetts Lowell United States

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, was pleased to present the 2009 Spring Symposium Series, held Monday through Wednesday, March 23-25, 2009, at Stanford University. The titles of the nine symposia were Agents That Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning systems, Experimental Design for Real- World systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents That Learn from Human Teachers symposium was to investigate how we can enable software and robotics agents to leam from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Experimental Design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more Al-based approaches in event pro-cessing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies IIAAAI symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic

关键词： Benchmarking

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