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2nd International Conference on Advances in Cyber Security, ACeS 2020

作者： Qassim, Qais Saif Jamil, Norziana Daud, Maslina Ja’affar, Norhamadi Kamarulzaman, Wan Azlan Wan Mahdi, Mohammed Najah Ibri College of Technology Ibri Oman Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Kajang Malaysia Cybersecurity Malaysia Perak Malaysia Tenaga Nasional Berhad Kuala Lumpur Malaysia

ISBN: (纸本)9789813368347

Supervisory Control and Data Acquisition (SCADA) systems perform monitoring and controlling services in critical national infrastructures such as electrical power generation and distribution, transportation networks, water supply and manufacturing, and production facilities. Cyber-attacks that compromise data integrity in SCADA systems such as an unauthorised manipulation of sensor or control signals could have a severe impact on the operation of the critical national infrastructure as it misleads system operators into making wrong decisions. This work investigates the man-in-the-middle (MITM) attack that aims explicitly at compromising data integrity of SCADA systems. The IEC 60870-5-104 tele-control communication protocol is used as the subject focus because it is a commonly used communication protocol in electrical power SCADA systems for tele-control and monitoring. We conducted several MITM attacks: covering the capturing, modification and injection of control commands, on IEC 60870-5-104 in our power grid SCADA system testbed. We described and performed the attacks in detail, together with several use cases. Based on the Proof-of-Concept (POC) conducted and data that we gathered, it shows that IEC 60870-5-104 is vulnerable against MITM attacks and it can be an entry point of cyberattacks, be it sophisticated or otherwise. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Cybersecurity

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A Preliminary Analysis of energy Consumption in Academic Buildings 3

A Preliminary Analysis of Energy Consumption in Academic Bui...

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2020 3rd Asia Conference on energy and Electrical Engineering, ACEEE 2020

作者： Dzulkifly, Sumayyah Cheong Hou, Yew Aris, Hazleen Hashim, Wahidah Jorgensen, Bo Norregaard Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Malaysia Center for Energy Informatics M rsk Mc-Kinney Moller Institute University of Southern Denmark Denmark

Current technological advancement and pressing environmental issues emphasise the need for better energy management to minimise wasting depleting resources. energy consumption can generally be divided into two, namely residential and commercial. Commercial energy consumption involves commercial buildings that include, but not limited to, banks, hotels, offices and academic buildings. While awareness on optimising energy use is more evident now, there is still a lack of understanding of the parametric values that are crucial in analysing the energy consumption of a commercial building that is unique to the building's function. This study aims to identify the relationships between a number of identified variables and the overall building energy consumption. The study intended to become the preliminary case study in identifying the correlations between selected variables and energy consumption. The analysis was carried out using covariance matrix on identified variables such as electricity consumption, user traffics, the maximum outdoor temperature of the month and the academic term. This study identified positive relationships between electricity consumption, user traffic, and maximum outdoor temperature. © Published under licence by IOP Publishing Ltd.

关键词： Covariance matrix

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Analysis of the Publications on Ontology-Based Smart Grid Applications: A Bird’s Eye View 1st

Analysis of the Publications on Ontology-Based Smart Grid Ap...

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1st International Conference on Applied computing Research to Support Industry: Innovation and Technology, ACRIT 2019

作者： Mahmoud, Moamin A. Maseleno, Andino Tang, Alicia Y. C. Lim, Fung-Cheng Kasim, Hairoladenan Bin Yong, Christine Insitute of Informatics and Computing Energy Universiti Tenaga Nasional Kajang Malaysia College of Computing and Informatics Universiti Tenaga Nasional Kajang Malaysia Tenaga Nasional Berhad Kuala Lumpur Malaysia

ISBN: (纸本)9783030387518

Smart grid ontology is a field of research recently viewed from the field of smart grid research as well as from the field of ontology research. The integration between smart grid and ontology is expected to enable the sharing of ontology among applications and stakeholders. By using the same language, the common problems that occur during applications interoperability will be prevented and solved. This brief paper intended to help researchers get an overview of the current smart grid ontology research in the world and also to know the connection between smart grid ontology paper publications with research attention leading to smart grid ontology. To do so, we conduct a comprehensive survey on three databases which are IEEE Xplore, Springer, and Elsevier ScienceDirect. From the survey, we obtained the number of smart grid ontology research studies, their citations, and the country. From the number of papers and their citations, it can be known which country has an interest in smart grid ontology research. From the results of this review, it was found that countries in continental Europe are the most widely issued publication about smart grid ontology. Similarly, the papers that cite largely dominated by countries in continental Europe. © 2020, Springer Nature Switzerland AG.

关键词： Smart power grids

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Social Distancing Detection with Deep Learning Model 8

Social Distancing Detection with Deep Learning Model

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8th International Conference on Information Technology and Multimedia, ICIMU 2020

作者： Hou, Yew Cheong Baharuddin, Mohd Zafri Yussof, Salman Dzulkifly, Sumayyah Institute of Informatics and Computing in Energy Malaysia College of Engineering Universiti Tenaga Nasional Kajang Malaysia

ISBN: (数字)9781728173108

ISBN: (纸本)9781728173108

The paper presents a methodology for social distancing detection using deep learning to evaluate the distance between people to mitigate the impact of this coronavirus pandemic. The detection tool was developed to alert people to maintain a safe distance with each other by evaluating a video feed. The video frame from the camera was used as input, and the open-source object detection pre-trained model based on the YOLOv3 algorithm was employed for pedestrian detection. Later, the video frame was transformed into top-down view for distance measurement from the 2D plane. The distance between people can be estimated and any noncompliant pair of people in the display will be indicated with a red frame and red line. The proposed method was validated on a pre-recorded video of pedestrians walking on the street. The result shows that the proposed method is able to determine the social distancing measures between multiple people in the video. The developed technique can be further developed as a detection tool in realtime application. © 2020 IEEE.

关键词： Convolutional neural networks

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Fractional-calculus analysis of the dynamics of T cells and human immunodeficiency viruses

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The European Physical Journal Special Topics 2024年 1-13页

作者： Alshammari, Abdulrahman Obaid Ahmad, Imtiaz Jan, Rashid Idris, Sahar Ahmed Department of Mathematics College of Science Jouf University Sakaka Saudi Arabia Institute of Informatics and Computing in Energy (IICE) Universiti Tenaga Nasional (UNITEN) Putrajaya Campus Kajang Malaysia Institute of Energy Infrastructure (IEI) Department of Civil Engineering College of Engineering Universiti Tenaga Nasional (UNITEN) Putrajaya Campus Kajang Malaysia Faculty of Engineering Department of Industrial Engineering King Khalid University Abha Saudi Arabia

Combination antiretroviral Therapy (cART) is the standard treatment approach for human immunodeficiency virus (HIV), involving the use of various antiretroviral drugs to effectively suppress the virus’s replication in the body. The objective of cART is to decrease the viral load in the blood to undetectable levels, enhance the immune system’s function, and ultimately prolong the patient’s life by preventing the progression to AIDS and associated opportunistic infections. In this work, we formulated the dynamics of HIV infection, including the effects of cART, within a fractional framework. This paper presents a numerical study that investigates the complex dynamics of HIV infection in $$\text {CD4}^{+}$$ T cells. The proposed HIV model incorporates the impact of antiretroviral medication via the Caputo–Fabrizio derivative. To comprehend the dynamics of the proposed HIV infection model, a numerical approach is employed. The dynamic behavior of the system is illustrated by examining the influence of various input parameters, aiming to capture the system’s sensitivity to these factors. Furthermore, this modeling approach highlights the interaction between the immune system and the virus. Through numerical simulations utilizing specific input values, we explore the chaotic and periodic behavior of HIV infection and provide insights into its intricate dynamics.

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Information Overload: The Effects of Large Amounts of Information 1

Information Overload: The Effects of Large Amounts of Inform...

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1st International Conference Information Technology to Enhance E-Learning and other Application, IT-ELA 2020

作者： Mahdi, Mohammed N. Ahmad, Abdul R. Ismail, Roslan Subhi, Mohammed A. Abdulrazzaq, Mohammed M. Qassim, Qais S. Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Selangor Malaysia Universiti Tenaga Nasional College of Computing Informatics Department of Computing Selangor Malaysia Institute of Informatics and Computing in Energy College of Computing Informatics Universiti Tenaga Nasional Selangor Malaysia Universiti Kebangsaan Faculty of Engineering and Built Environment Department of Electric and Electronic Engineering Selangor Malaysia International Islamic University Kulliyyah of Information and Communication Technology Kuala Lumpur Malaysia Ibri College Department of Information Technology Oman

ISBN: (纸本)9781728182339

There is an immense amount of information available on the web. In no small part, this wealth of knowledge has challenged scientists continued to search for ways to make the information as easy as possible for end-users. Exploratory quest is transparent and has many characteristics that allow users to find relevant information and to improve their comprehension of the task involved. A comprehensive study is performed on various findings focused on the solutions to the overload issue and has shown that the use of faceted filters minimizes the abundance of information. This paper also discusses information overload and exploratory testing features, such as facial scanning, which can mitigate the effect of clear marine filters. © 2020 IEEE.

关键词： Exploratory search Faceted energy Faceted search Information filtering Information overload

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Polymer-Enhanced glucose biosensors with UV sensitivity: advancements in photoelectrochemical energy systems using response surface methodology

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Microchemical Journal 2025年 214卷

作者： Siti Nur Ashakirin Binti Mohd Nashruddin Faridah Hani Mohamed Salleh Nur Fatin Sulaiman Mohd Farhanulhakim M. Razipwee Institute of Informatics and Computing in Energy (IICE) Department of Computing College of Computing & Informatics University of Tenaga Nasional Malaysia Institute of Microengineering and Nanoelectronics (IMEN) Universiti Kebangsaan Malaysia (UKM) Bangi 43600 Selangor Malaysia

Electrochemical biosensor detection based on enzymes for monitoring biochemical substances remains appealing. This study investigates an innovative glucose biosensor with enhanced ultraviolet (UV) light sensitivity using a composite nanomaterial of poly(3,4-ethylenedioxythiophene): polystyrene sulfonate (PEDOT:PSS), MXene (Ti 3 C 2 ), and graphene quantum dots (GQD) modified onto a screen-printed carbon electrode (SPCE). The immobilization of glucose oxidase (GOx) on this PEDOT/MXene/GQD-modified SPCE exhibited superior electrochemical behavior, characterized through FTIR, XPS, SEM, cyclic voltammetry (CV), and differential pulse voltammetry (DPV). The biosensor showed a linear voltammetric response within a glucose concentration range of 0–500 μM, with a low detection limit and consistent performance under ambient, dark, and UV light conditions, indicating robustness in stability and selectivity. Response surface methodology (RSM) was applied to optimize operational parameters, revealing through ANOVA that current density (F-value = 22.44) was the most critical factor. Glucose was determined with a sensitivity of 5.41 μAμM −1 cm −2 and the limit of detection (LOD) was 44.60 μM. These UV light photo-sensing biosensors enhance glucose detection and demonstrate potential for applications in biomedical diagnostics energy conversion efficiency and system monitoring, underscoring their role in advancing sustainable electrochemical energy systems.

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Dense Compounded Features and Data Association Based Multiple People Tracking

Dense Compounded Features and Data Association Based Multipl...

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2021 International Conference on Communication and Information Technology, ICICT 2021

作者： Al-Faris, Mahmoud Chiverton, John Ndzi, David Alhabo, Mohanad Informatics Telecommunications Public Company Ministry of Communications Baghdad Iraq University of Portsmouth School of Energy and Electronic Engineering United Kingdom University of the West of Scotland School of Computing Engineering and Physical Sciences United Kingdom

ISBN: (纸本)9781665439145

People tracking is a wide area of research in computer vision and machine learning. The challenging problem of multiple objects tracking (MOT) is further complicated by factors such as occlusion, varying number of targets, illumination variations and objects' appearances which may be similar. In this paper, a significant approach is proposed for MOT with a single static camera based on dense valuable global and local features. This includes cascaded HOG-III features, texture, and motion information of objects in order to build a robust tracking system. To speed up the system, a simple data association method is employed using Hungarian algorithm to associate candidate response to the target objects. Genetic algorithm is also used to provide a heuristic data association based multiple objects tracking. A comparison between two association algorithms is made based on the tracking results. TUD-crossing and TUD-campus datasets are used for validation purposes. A system's performance can be evaluated using a wide metrics of MOT performance indicators (MOTA, MOTP). The results reach (82.89 and 81.96) in terms of TUD-crossing dataset and (79.30 and 73.06) in terms of TUD-campus dataset respectively. The experiments show that the proposed method can be suitably employed during scale changes or in the presence of a cluttered background environment, in addition, our method achieves competitive results in comparison with state of the art approaches. © 2021 IEEE.

关键词： Genetic algorithms

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A Mathematical Study of the Relation Between Discharges, Froude Number, Bed Width in Dividing Open Channel Flows 5th

A Mathematical Study of the Relation Between Discharges, Fro...

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5th International Conference on Water Resources, ICWR 2021

作者： Harmizi, Puteri Nadia Shafiqah Zawawi, Iskandar Shah Mohd Haniffah, Mohd Ridza Mohd Khairudin, Taufiq Khairi Ahmad Aris, Hazleen Faculty of Computer and Mathematical Sciences Kompleks Al-Khawarizmi Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Department of Water and Environment Engineering School of Civil Engineering Faculty of Engineering Universiti Teknologi Malaysia Johor Johor Bahru81310 Malaysia Faculty of Science Universiti Teknologi Malaysia Johor Johor Bahru81310 Malaysia Institute of Informatics and Computing in Energy Universiti Tenaga Nasional Selangor Kajang43000 Malaysia

ISBN: (纸本)9789811959462

Open-channel with branches makes the channel flow more complex and difficult to analyse due to the complex variables and a large number of geometric properties related to the junction. The aim of this paper is to employ the mathematical model to investigate the relationship between discharge, Froude number and bed width in the dividing open-channel flow. Several assumptions have been made and input values are taken from the literature to solve the proposed model. Results indicated that the highest discharge ratio is obtained when the dividing angle at channel 2 is The discharge ratio slightly increases as the Froude number decreases for all angles. However, the Froude number of subcritical flows had a significant effect on the bed width ratio. For angles 30°, 45°, 60° and 75°, the discharge ratio decreases when the bed width ratio increases, but it remains unchanged when the angle is 90°. In conclusion, there is a linear relationship between discharges, Froude number and bed width ratio at certain dividing angles. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Froude number

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Real-Time Substation Detection and Monitoring Security Alarm System

Real-Time Substation Detection and Monitoring Security Alarm...

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IEEE Conference on Systems, Process & Control (ICSPC)

作者： Yong Tzia Yiong Ahmad Rafiq Mohd Khairudin Redia Mohd Redzuwan Sarawak Energy Berhad Department of Electrical Electronics Engineering College of Engineering Universiti Tenaga Nasional Selangor Malaysia Institute of Informatics and Computing in Energy College of Engineering Universiti Tenaga Nasional Selangor Malaysia Department of Electrical Electronics Engineering College of Engineering Universiti Tenaga Nasional Selangor Malaysia

In real-world scenarios, conventional security alarms are commonly used to monitor and record occurrences. However, these alarms are often impractical as they lack the ability to warn security administrators in real-time when security threats are present. To address this issue, this project proposes an automated continuous security surveillance system utilizing Raspberry Pi 3B and Raspberry Pi Camera, along with deep learning tools namely Open-Source Computer Vision Library (OpenCV), You Only Look Once tiny version 4 (YOLOv4-tiny), Google Drive, Colab Notebook, and DarkNet framework. The proposed system aims to detect specific classes, such as people, cars, or fires, within a designated range and promptly send out alert notifications and sound an alarm in real-time. To achieve this, the YOLOv4-tiny machine learning model is used for object detection, and OpenCV is employed for image pre-processing tasks like scaling and normalization [21]. To overcome the computational limitations of the Raspberry Pi 3B, the YOLOv4-tiny model is trained on a custom dataset using the DarkNet framework, and Colab Notebook is utilized for training and optimizing the model, which is then saved on Google Drive for easy access. Various techniques like model quantization and network pruning are employed to improve the system's performance and efficiency. The experimental results demonstrate that the proposed system achieves high accuracy in detecting specific classes while remaining computationally efficient. Overall, this project offers a reliable and efficient solution by integrating the concepts of object recognition and detection, showcasing its potential for various practical applications.

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