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International Conference for Convergence of Technology (I2CT)

作者： Suvi Lasan De Silva Nalaka Dissanayaka Software Engineering Informatics Institute of Technology Colombo SriLanka

Autism students has difficulties in understanding written language. They are unable to visualize a correct image in their mind by reading a sentence so they tend take more time to understand a concept from a written text. Teachers and parents has to spend more time supporting children with autism to understand the text sentence. Psychologist and researchers observed that the Autistic students grab concepts in image and sound formats more than the concepts from text sentence. The researchers have come up with some learning techniques, among these techniques Multisensory learning technique is more advanced because it contains both visual and auditory representations. There are systems which converts text sentence into 3d scene which benefits only for the visual learners in Autistic students. Identify the issues in existing text to 3d scene systems and include auditory output to create multisensory learning style approach leads to a sophisticated learning platform which helpful for both visual and auditory learners in students with Autism spectrum disorder to understand the text sentence.

关键词： Three-dimensional displays Visualization Autism Databases Object recognition Sensors Education

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An improved simulation model for pedestrian crowd evacuation

arXiv

引用

arXiv 2020年

作者： Muhammed, Danial A. Rashid, Tarik A. Alsadoon, Abeer Bacanin, Nebojsa Fattah, Polla Mohammadi, Mokhtar Banerjee, Indradip Computer Department College of Science University of Sulaimani SulaymaniyahKRG46001 Iraq Computer Science and Engineering Department University of Kurdistan Hewler ErbilKRG44001 Iraq Department of Information Technology School of Computing and Mathematics Charles Sturt University Sydney BathurstNSW2795 Australia Faculty of Informatics and Computing Vice-dean Singidunum University Belgrade11000 Serbia Software and Informatics Engineering Dept Engineering College Salahaddin University-Erbil ErbilKRG44001 Iraq Department of Information Technology Lebanese French University ErbilKRG44001 Iraq Department of Computer Science and Engineering University Institute of Technology The University of Burdwan BurdwanWest Bengal713101 India

This paper works on one of the most recent pedestrian crowd evacuation models, i.e., "a simulation model for pedestrian crowd evacuation based on various AI techniques", developed in late 2019. This study adds a new feature to the developed model by proposing a new method and integrating it with the model. This method enables the developed model to find a more appropriate evacuation area design, among others regarding safety due to selecting the best exit door location among many suggested locations. This method is completely dependent on the selected model's output, i.e., the evacuation time for each individual within the evacuation process. The new method finds an average of the evacuees’ evacuation times of each exit door location;then, based on the average evacuation time, it decides which exit door location would be the best exit door to be used for evacuation by the evacuees. To validate the method, various designs for the evacuation area with various written scenarios were used. The results showed that the model with this new method could predict a proper exit door location among many suggested locations. Lastly, from the results of this research using the integration of this newly proposed method, a new capability for the selected model in terms of safety allowed the right decision in selecting the finest design for the evacuation area among other designs. © 2020, CC BY.

关键词： Location

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Corrigendum to “DeepQSP: Identification of Quorum Sensing Peptides Through Neural Network Model” [Results in engineering 24 (2024) 102878]

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Results in engineering 2024年 24卷

作者： Md. Ashikur Rahman Md. Mamun Ali Kawsar Ahmed Imran Mahmud Francis M. Bui Li Chen Santosh Kumar Mohammad Ali Moni Department of Software Engineering Daffodil International University Daffodil Smart City Birulia Dhaka 1216 Bangladesh Division of Biomedical Engineering University of Saskatchewan 57 Campus Drive Saskatoon SK S7N 5A9 Canada Department of Electrical and Computer Engineering University of Saskatchewan 57 Campus Drive Saskatoon SK S7N 5A9 Canada Bio-photomatiχ Information and Communication Technology Mawlana Bhashani Science and Technology University Santosh Tangail 1902 Bangladesh Health Informatics Research Lab Department of Computer Science and Engineering Daffodil International University Daffodil Smart City Birulia Dhaka 1216 Bangladesh Department of Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh 522302 India AI & Digital Health Technology Artificial Intelligence & Cyber Future Institute Charles Sturt University Bathurst NSW 2795 Australia AI & Digital Health Technology Rural Health Research Institute Charles Sturt University Orange NSW 2800 Australia

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English proficiency and academic achievement of technical undergraduates

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AIP Conference Proceedings 2022年第1期2617卷

作者： Yasmin Yahya Nurhadiana Nurulmatin Nurul Sharaz Azmanuddin Norhatta Mohd 1Informatics and Analytics Section Malaysian Institute of Information Technology (MIIT) Universiti Kuala Lumpur 50250 Kuala Lumpur Malaysia 2Student Development Section Malaysian Institute of Information Technology (MIIT) Universiti Kuala Lumpur 50250 Kuala Lumpur Malaysia 3Software Engineering Section Malaysian Institute of Information Technology (MIIT) Universiti Kuala Lumpur 50250 Kuala Lumpur Malaysia 4Foundation Centre Malaysian Institute of Information Technology (MIIT) Universiti Kuala Lumpur 50250 Kuala Lumpur Malaysia

This study identifies the factors that contribute to the students’ English language proficiency among Malaysian institute of Information Technology (MIIT) undergraduates. It further explores the impacts of the undergraduates’ language proficiency towards their academic performance. A quantitative and non-experimental approach were used for data collection purposes where data were collected through online questionnaire. There were 116 participants from Universiti Kuala Lumpur (UniKL) MIIT undergraduates involved in this study. Data analyses were made using inferential and descriptive statistical analyses. Statistical analyses revealed that the undergraduates’ academic achievement was influenced by their attitude towards the use of English and their high school English performance. In contrast, the findings indicated that the undergraduates’ residency did not contribute to their English language proficiency. It was also indicated that there was a significant difference between the undergraduates’ level of English Language Proficiency based on their academic achievement. In brief, the findings of this study provide useful insights on how undergraduates’ English language proficiency is influenced by many external factors that eventually affect their academic performance. It is crucial to be proficient in English language so that not only students are able to perform excellently in school but also in tertiary institutions. After all, graduates who are proficient in English will be in demand specially to cater the need to work in the English medium environment. Thus, this research paper will provide some improvements and recommendations in assisting the tertiary institutions to produce more in demand graduates who are able to compete at the international level.

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BitterEN: A novel ensemble model for the identification of bitter peptide

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Computers in Biology and Medicine 2025年 195卷

作者： Md Fahim Sultan Tasmin Karim Md Shazzad Hossain Shaon Md Mamun Ali Sobhy M. Ibrahim Mst Shapna Akter Kawsar Ahmed Francis M. Bui Mohammad Ali Moni Department of Computer Science and Engineering Oakland University Rochester MI 48309 USA Division of Biomedical Engineering University of Saskatchewan 57 Campus Drive Saskatoon SK S7N 5A9 Canada Department of Software Engineering Daffodil International University Daffodil Smart City (DSC) Birulia Savar Dhaka 1216 Bangladesh Department of Biochemistry College of Science King Saud University P.O. Box: 2455 Riyadh 11451 Saudi Arabia Department of Electrical and Computer Engineering University of Saskatchewan 57 Campus Drive Saskatoon SK S7N 5A9 Canada Health Informatics Research Lab Department of Computer Science and Engineering Daffodil International University Daffodil Smart City (DSC) Birulia Savar Dhaka 1216 Bangladesh AI & Digital Health Technology Artificial Intelligence & Cyber Future Institute Charles Sturt University Bathurst NSW 2795 Australia AI & Digital Health Technology Rural Health Research Institute Charles Sturt University Orange NSW 2800 Australia

Bitter peptides are short amino acid chains that produce a bitter taste. These peptides are made primarily in food processing through the chemical reduction of peptides. The bitterness arises from the specific sequence of amino acids in peptides, which interact with the bitter taste receptors on the human tongue. These peptides influence nutrition and health, offering insights into protein digestion and bioactive advantages. Hence, correctly identifying bitter peptides is pivotal for revealing the biochemical properties of efficient medication. The computational approach is most suitable for identifying bitterness, where most studies obtained insufficient outcomes. Therefore, the current study developed an ensemble-based framework called “BitterEN”, where we integrate the Gradient Boosting (GB) and Multi-layer Perception (MLP) methods. Our proposed method improved more than 3 % of accuracy compare to all of the state-of-the-arts methods, where the proposed approach achieved 0.995 accuracy in merged feature extractions with the Random Forest (RF) feature selection method. We used 50 iterations over the performance evaluation phases to enable a more exact generalization of model performance. In addition, we provided a convenient GitHub-based version of our bitter peptide identification. It highlights the practical applicability of these findings. We are optimistic that the proposed approach might benefit many fields, including healthcare development and nutritional science.

关键词： Bitter peptides Nutritional science Healthcare Feature extractions Ensemble learning

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Flexible production systems: Automated generation of operations plans based on ISA-95 and PDDL

arXiv

引用

arXiv 2019年

作者： Wally, Bernhard Vyskočil, Jiří Novák, Petr Huemer, Christian Šindelář, Radek Kadera, Petr Mazak, Alexandra Wimmer, Manuel CDL for Model-Integrated Smart Production Department of Business Informatics Software Engineering Johannes Kepler University Linz Linz4040 Austria Department of Intelligent Systems for Industry and Smart Distribution Networks Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague160 00 Czech Republic Business Informatics Group Institute of Information Systems Engineering Technische Universitat Wien Vienna1040 Austria

Model-driven engineering (MDE) provides tools and methods for the manipulation of formal models. In this letter, we leverage MDE for the transformation of production system models into flat files that are understood by general purpose planning tools and that enable the computation of "plans", i.e., sequences of production steps that are required to reach certain production goals. These plans are then merged back into the production system model, thus enriching the formalized production system knowledge. Copyright © 2019, The Authors. All rights reserved.

关键词： Factory automation

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Analysis of Historical Accident Data to Determine Accident Prone Locations and Cause of Accidents

Analysis of Historical Accident Data to Determine Accident P...

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International Conference on Intelligent Systems, Modelling and Simulation (ISMS)

作者： Arshardh Ifthikar Saman Hettiarachchi Department of Software Engineering Informatics Institute of Technology Colombo Srilanka

ISBN: (纸本)9781538665404;9781538665398

Road traffic accidents is a severe issue which causes great distress and destroys lives of many individuals. In spite of different attempts to solve this problem, it still resides as a major cause of death. This paper discusses several attempts made to identify causes for road accidents. Finally, a system is proposed to analyze historical accident data and subsequently identify accident-prone areas and their relevant causes via clustering accident location coordinates. This system, once developed, can be used to warn drivers and also to aid fully autonomous automobiles to take precautions at accident-prone areas.

关键词： Roads Entropy Clustering algorithms Wind Road accidents

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A Comparative Study of Link Analysis Algorithms

A Comparative Study of Link Analysis Algorithms

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International Conference on Intelligent Systems, Modelling and Simulation (ISMS)

作者： Chamath Palihawadana Guhanathan Poravi Department of Software Engineering Informatics Institute of Technology Colombo Sri Lanka

ISBN: (纸本)9781538665404;9781538665398

With the advancement of technology, the internet has become a growing place with huge amounts of information. Retrieving information is not a hard task, but ranking the retrieved information according to the relevancy is a very complex task. Search engines provides users to query and assess results instantly. Behind these search engines there runs vast amounts of algorithms to give out the best results. One such algorithm type is the link analysis algorithms which is used to rank pages and content. This paper reviews and compares the most commonly used link analysis algorithms.

关键词： Search engines Web pages software algorithms informatics Task analysis

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Valuation of Used Vehicles: A Computational Intelligence Approach

Valuation of Used Vehicles: A Computational Intelligence App...

引用

International Conference on Intelligent Systems, Modelling and Simulation (ISMS)

作者： Amjadh Ifthikar Kaneeka Vidanage Department of Software Engineering Informatics Institute of Technology Colombo Sri Lanka

ISBN: (纸本)9781538665404;9781538665398

In most of the countries in the world, the number of vehicles has increased exponentially in the past decade. As a result, the used vehicle trade has flourished. In order to determine the resale value of a vehicle or for financial requirements such as vehicle leasing services, used vehicle valuation is paramount. In order to meet the future demand, a proper mechanism using computational intelligence is needed for vehicle valuation in order to overcome the inefficiencies of conventional and subjective valuation mechanisms. This paper focuses on discussing aspects regarding used vehicle valuation, previous work related to the domain as well as the proposed solution. The proposed solution intends to use real-time web scraping and machine learning in order to determine the value of a given vehicle.

关键词： Cost accounting Petroleum Support vector machines Machine learning Artificial neural networks Data models Manuals

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Integration of smart grid with Industry 5.0: Applications, challenges and solutions

Measurement: Energy

引用

Measurement: Energy 2025年 5卷

作者： Sunawar khan Tehseen Mazhar Tariq Shahzad Muhammad Amir khan Ateeq Ur Rehman Habib Hamam Department of Software Engineering Islamia University of Bahawalpur Bahawalnagar 62300 Pakistan Department of Computer Science and Information Technology School Education Department Government of Punjab Layyah 31200 Pakistan School of Computer Science National College of Business Administration and Economics Lahore 54000 Pakistan Department of Computer Science COMSATS University Islamabad Sahiwal Campus Sahiwal 57000 Pakistan School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA 40450 Shah Alam Selangor Malaysia School of Computing Gachon University Seongnam 13120 Republic of Korea Faculty of Engineering Uni de Moncton Moncton NB E1A3E9 Canada School of Electrical Engineering University of Johannesburg Johannesburg 2006 South Africa International Institute of Technology and Management (IITG) Av. Grandes Ecoles Libreville BP 1989 Gabon Bridges for Academic Excellence - Spectrum Tunis Tunisia

Introduction In this study, an investigation of the nexus between state-of-the-art technology and green industrial processes with a view to how smart grid systems can be incorporated into industry 5.0 is done. Industry 5.0 stresses human-machine collaboration together with Artificial Intelligence, the Internet of Things, and Big Data while the recent electrical networks enriched by digital communication technologies are defined as the contemporary smart grids. Notwithstanding advances in both domains, there is a major research gap at the intersection of the two. Objectives In this study, the essential elements, advantages, and potential impacts of coupling smart grids with Industry 5.0 will be examined. These aims are aimed at sustaining and improving the reliability and efficiency of industrial processes maximizing resource consumption and minimizing ecological damage. Method ology: The use and benefits of this integration are analyzed using case studies from industrialized countries. It assesses technological developments, challenges and the emerging trends dealing with the combination of smart grid technologies with Industry 5.0. Findings and discussion In addition, smart grid technology can make industrial processes more dependable and efficient; resulting in more appropriate resource utilization and lower emissions. It promises to revolutionize the energy management systems and production procedures. Conclusion Drawing from this research, this integration offers the capabilities of developing a technologically advanced and environment-friendly industrial ecosystem that enables a truly sustainable future.

关键词： Smart grid Energy efficiency Industry 5.0 Haman-machine collaboration Advanced metering infrastructure (AMI) Real-time data analytics

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