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Artificial Intelligence-Based Facial Expression Recognition for Identifying Customer satisfaction on Products
No full textFacial Expression Recognition (FER) for Identifying Customer Satisfaction on Products is one of the most powerful and challenging research tasks in social communication. Artificial intelligence (AI)-based emotion recognition harnesses the collective strength of machine learning, deep learning, and computer vision to decipher the subtleties of human emotions. By intricately analyzing facial expression, including the nuanced movements of the mouth, eyes, and eyebrows. Recent innovations have driven notable progress in face detection and recognition that enhance performance and reliability. This study focuses on leveraging AI-based facial expression recognition to identify customer satisfaction with products. The objective of this research is to develop a robust and accurate facial expression recognition system capable of analyzing customer emotions and determining their satisfaction levels based on their facial expressions. The proposed study used a hybrid convolutional neural network (CNN) and deep neural networks (DNN) model to extract meaningful features from facial images and classify them into different emotional states. The trained model is to be evaluated using a separate test dataset to measure its performance in accurately recognizing customer emotions and assessing satisfaction levels. The evaluation metrics include accuracy, precision, recall, and F1-score. The proposed experiment achieved excellent result with a real-time image-based dataset.
Manuscript received:7 Mar 2025 | Revised: 22 May 2025 | Accepted: 11 Jun 2025 | Published: 30 Jul 202
Some Insights on Pythagorean Neutrosophic Graphs
No full textPythagorean neutrosophic graphs (PNeuGr) are a specialized extension of the neutrosophic graphical idea, where the total sum range of memberships is adjusted by squaring each membership. This article is furnished to enhance the handling of uncertain events in a complex environment. The discussion encloses the irregular properties of the PNeuGr and its practical implications
Manuscript received:9 Apr 2025 | Revised: 28 May 2025 | Accepted: 19 Jun 2025 | Published: 30 Jul 202
The Challenges of Autonomous Vehicles In Malaysia: From The Perspective Of Motorcycle Traffic Crashes: DOI: https://doi.org/10.33093/ijomfa.2025.6.1.3
No full textThe Level 3 autonomous vehicle (AV) is now a reality on the public roads. While the emergence of AV is to eliminate the traffic crashes due to human error by 90%, the unexpected or errant drivings on the roads would, however lead to traffic crashes as the operation of AVs are depending on the artificial intelligence, which involve constantly teaching the computer to learn. In Malaysia, motorcycle fatalities accounted for about 60% of the total traffic fatalities, of which the majority of the fatalities were due to human errors. - The presence of motorcyclists in the traffic stream then becomes challenge to the operation of AVs due to the unpredictable and inconsistent behaviour of the motorcyclists. Therefore, to ensure the safe deployment of AVs in the country, this study is taken to unveil the characteristics of certain traffic crashes involving motorcyclists. The findings show that as high as 40% of the motorcycle casualties were due to the motorcycles’ faults. Careless driving, speeding, dangerous overtaking and turning are among the causal factors. The findings shed important insights to AV software programm developers in the process of detecting and processing necessary response plans. Besides, the car makers can also propose more crashworthiness vehicles from the perspective of vulnerable road users.
The role of financial literacy in driving sustainable entrepreneurial success: A case study of Lapo Microfinance Institution (MFI), Nigeria
No full textEven with access to microfinance loans, many small and medium enterprises (SMEs) in Nigeria still find it challenging to achieve sustainable growth; thus, this systematic study investigates the role of financial literacy in driving the sustainable entrepreneurial success of clients of Lapo Microfinance Institution (MFI), Nigeria. A representative sample of Lapo MFI clients who have participated in their financial literacy training programmes was surveyed and interviewed, providing qualitative and quantitative data. The findings demonstrate a positive correlation between participation in Lapo MFI's financial literacy training programmes and sustainable business success among their clients. The novelty of this research is that it establishes a link between financial literacy and SME success. This study offers valuable direction or guidance for other MFIs in developing targeted financial literacy interventions to support the sustainable growth of their clients' businesses
“Stay” or “Leave”: assessing the determinants of turnover intention of private sector employees
No full textEmployee turnover is a critical issue of great concern for organizations. The challenge is exacerbated when the human resources that leave the organization are highly knowledgeable employees with high expertise and distinctive work competencies. To understand the factors that lead to employee turnover, this study examined the determinants of private sector employee turnover intentions, including salary level, workload, job satisfaction, and management support. Data were obtained from private sector employees in Selangor, Malaysia. The results revealed that the turnover intention level was medium. Second, significant relationships were found between salary level, workload, job satisfaction, management support, and turnover intention. Third, workload is the most significant predictor of turnover intention. Thus, the organization needs to take the necessary steps to curb the outflow of valuable employees. Management can use the findings of this study to review human resource management policies related to salaries and wages, develop a work environment that prioritizes employee welfare, and strengthen the relationships between employees
Financing green futures: renewable energy investment and economic growth in Germany
No full textGlobal efforts to mitigate greenhouse gas emissions have been driven by increasingly evident adverse impacts of climate change. Countries are adopting renewable energy sources, such as solar, wind, hydropower, geothermal, and bioenergy, which provide cleaner alternatives to fossil fuels. Investments in renewable energy facilitate the decarbonization of the energy sector, while simultaneously stimulating the economy through job creation, technological advancement, and innovation. This study examines the relationship between renewable energy financing and economic growth in Germany. Annual time series data from 1986 to 2022 and a Nonlinear Autoregressive Distributed Lag model were used. The research findings indicate a correlation between renewable energy financing and economic growth. The study indicates that a disturbance in combustible renewable energy and waste will, according to the long-term findings, exert a negative impact of 0.21 on economic growth. In general, financing renewable energy is believed to play a role in Germany’s economic growth. The study recommends that policymakers enhance their funding for colleges and research institutions to develop more viable ways to enhance renewable energy production and adoption
Comprehensive Review of CAN Bus Security: Vulnerabilities, Cryptographic and IDS Approaches, and Countermeasures
No full textVehicle connectivity environments and advancements in vehicular technologies offer users both functional convenience and safety features, including remote diagnosis and assistance. To enable these capabilities, modern vehicles utilize various automotive serial protocols such as FlexRay, Local Interconnect Network (LIN), and the popular Controller Area Network (CAN). The CAN bus serves as a key protocol for in-vehicle networks (IVNs), facilitating the exchange of vehicle parameters among Electronic Control Units (ECUs). Despite its merits, the CAN bus has been found to have internal and external vulnerabilities. While numerous countermeasures are currently in place, the continuous advancements in vehicular interfaces have introduced new attack vectors, necessitating the development of additional safeguards. Existing research has primarily focused on CAN attacks initiated through direct interfaces, telematics and infotainment systems, and sensors. In this study, we aim to present an adversarial model for the CAN bus while also evaluating cryptographic and Intrusion Detection System (IDS) approaches considering real-time constraints and other relevant variables. Furthermore, we will classify available countermeasures into relevant categories and discuss their effectiveness. By conducting a comprehensive analysis of published works, our goal is to provide a comprehensive overview of CAN-related studies. This includes exploring potential mitigation techniques and identifying new research opportunities for IVNs. The synthesis of this information will offer valuable insights into the current state of CAN security, the challenges it faces, and the directions for future exploration. In summary, our study aims to address the vulnerabilities of the CAN bus, considering both existing and emerging attack vectors. By examining cryptographic and IDS approaches, we will assess their viability in real-time scenarios. Additionally, we will categorize and discuss the effectiveness of available countermeasures. Through this analysis, we strive to provide a holistic understanding of CAN-related research, paving the way for prospective mitigation techniques and identifying new horizons for IVNs.
Manuscript Received: 10 January 2024, Accepted: 28 May 2024, Published: 15 March 2025, ORCiD: 0009-0005-3915-681
Experimental and Numerical Study of Shape Memory Alloys for Vibration Amplitude Reduction in Mechanical Structures
No full textThis study explores the effectiveness of Shape Memory Alloys (SMAs) for adaptive vibration control in mechanical structures through both experimental and numerical methods. SMAs were integrated into a cantilever beam, and their performance was assessed across different temperatures and vibration frequencies. The results demonstrate that SMAs can reduce vibration amplitudes by up to 45%, particularly at resonant frequencies when activated at elevated temperatures (75°C). A finite element model was developed to simulate the behavior of the system, showing strong correlation with experimental data, with a root mean square error (RMSE) of less than 4%. The validated model was further used to predict SMA performance under conditions not tested experimentally, confirming its reliability for broader applications. These findings show the potential of SMAs as compact, adaptive, and energy-efficient solutions for vibration control in sectors such as aerospace, automotive, and civil engineering. Future research should focus on optimizing activation response times, improving long-term durability, and exploring more complex structural designs for enhanced performance.
Manuscript Received: 7 December 2024, Accepted: 23 January 2025, Published: 15 March 2025, ORCiD: 0000-0002-2016-482
Maximum Power Enhancement of Partially Shaded Photovoltaic Array by Advanced Total Cross-Tied Based Configuration
No full textPartial shading in solar photovoltaic arrays reduce the maximum power produced. Partial shading conditions in PV arrays can be caused by water, dust, tree shadows, bird-drops, nearby building, etc. Special configuration is needed to reduce the effect of partial shadings. In this study, 8 × 8 symmetric photovoltaic arrays configured in different configurations such series-parallel (SP), total cross-tied (TCT), modified complementary sudoku puzzle (MCSDKP) and symmetric matric total cross-tied (SMTCT) are studied under row shading of 25% shaded area and 50% shaded area with two different shading irradiance conditions of uniform shading irradiance and non-uniform shading irradiance. All of the performance results are carried out by MATLAB/Simulink. This study shows that advanced total cross-tied based configurations perform higher than other configurations in all conditions. The objective of this study is to understand the importance of array configurations and to get maximum power under partial shaded conditions.
Manuscript Received: 1 August 2024, Accepted: 27 August 2024, Published: 15 March 2025, ORCiD: 0009-0007-8806-550
Adaptive Strategies to Mitigate DDoS Attacks in IoT-Devices Through A Moving Target Defense Approach in SDN
No full textThe surge of IoT devices has revolutionized the world, but the inherent complexity and vulnerabilities of these devices pose significant security risks. Among security challenges, distributed denial of service (DDoS) attacks stands out as a major cybersecurity issue aimed at interfering with regular systems. This paper conducts a gap analysis of existing research on DDoS attacks in the context of SDN oriented IoT devices. The research focus is on comparing algorithms and mitigation strategies proposed in different research papers and evaluating their efficiency and cost-effectiveness as previous research efforts have taken a variety of approaches, some focused on inexpensive but ineffective procedures, while others focused on expensive but effective procedures. However, few studies have investigated both cost and performance effectiveness simultaneously. The main objective of this research paper is to evaluate and compare different strategies proposed in the literature to protect Software Defined Network oriented IoT devices from DDoS attacks through an active approach using MTD (Moving Target Defense) technique. The goal of this strategy is to protect the network from attacks while remaining cost-effective through gap analysis to suggest that the Moving Target Defense technique is less complex than previous approaches to provide better security measures and protection against DDoS attacks on networks