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GenReGait: Gender Recognition using Gait Features
No full textGender recognition based on gait features has gained significant interest due to its wide range of applications in various fields. This paper proposes GenReGait, a robust method for gender recognition utilizing gait features. Gait, the unique walking pattern of individuals, contains distinct gender-specific characteristics, such as stride length, step frequency, and body posture, making it a promising modality for gender estimation. The proposed GenReGait method begins by extracting landmark positions on the human body using a human keypoint estimation technique. These landmarks serve as informative cues for estimating gender based on their spatial and temporal characteristics. However, environmental factors can impact gait patterns and introduce fluctuations in landmark points, affecting the accuracy of gender estimation. To overcome this challenge, GenReGait introduces a robust preprocessing technique known as Weighted Exponential Moving Average to smoothen the gait signals and reduce noise caused by environmental factors. The smoothed signals are then fed into a deep learning network trained to perform gender estimation based on the gait features extracted from the landmark positions. By leveraging deep learning algorithms, the proposed GenReGait method effectively captures complex patterns and relationships within the gait features, enhancing the accuracy and reliability of gender recognition. Experimental evaluations conducted on the Gait in the Wild dataset and a self-collected dataset validate the robustness and effectiveness of the proposed GenReGait approach
Traffic Impact Assessment System using Yolov5 and ByteTrack
No full textMonitoring software for traffic is not too much in this era of digital. Even cheaper is decent traffic monitoring software. You can gauge the quality of the software. It should be possible to assess the code's performance outside of a test environment. The most useful metrics are frequently those that support the program's ability to fulfil business requirements. Therefore, this project is planning to develop a traffic assessment system. The main purpose of development is to improve heavy traffic in this country – Malaysia. This system includes function vehicle detection using YOLOv5, vehicle counting with a different type (such as bus, car, truck), vehicle classification, vehicle idling time by each region, and vehicle counting for each junction. Users can draw regions and lines for each camera/video to count and record vehicles. After the traffic analysis, intelligent signal light systems that respond to loads and timing can be helpful in easing traffic congestion. Smart traffic lights may adapt to the patterns of bustle at junctions and other important road traffic places based on the number of cars, data from queue detectors, and images from cameras. Also, this report includes comparisons with StrongSORT, OC-SORT and ByteTrack and accuracy test for vehicle counting
The Application of Augmented Reality Platform for Chemistry Learning
No full textIn this project, a new learning platform was developed. This project uses the technology of Augmented Reality (AR) to develop a graphic animation platform for learning purposes. By applying virtual objects with animations for learning, it helps to engage users and increase their learning efficiency. Besides, the AR platform combines hardware (i.e.s smartphone, headset, and target marker) and software (i.e., Unity, Vuforia, and C#) for the operation. The AR application allow the interaction of the virtual objects by grabbing target marker toward each other or touching the virtual button in real environment. This can increase the immersion and interaction of the user when learning chemistry. In additional, the “Chemical Learn” experiments was designed to study the effectiveness of the AR platform compared to traditional platform as well as to conduct user satisfaction surveys. The overall results showed that the AR learning platform can improved learning efficiency of users in chemistry compared to traditional learning methods. Moreover, users who participate in the survey are generally satisfied with the AR. It is believed that with the rising trend of technology, it is only a matter of time before people become familiar with the AR platform.
Manuscript received: 1 May 2023 | Revised: 13 July2023 | Accepted: 24 August 2023 | Published: 30 September 202
The Necessity of Financial Literacy for Women Business Triumph: A Qualitative Study: DOI: https://doi.org/10.33093/ijomfa.2023.4.2.8
No full textWomen entrepreneurs continue to be the torchbearers of society and nations in their pursuit of economic growth and social development through employment creation, innovation and poverty reduction. Nonetheless, financial literacy is an intangible resource that is required for growth, success, and long-term competitive advantage. However, a notable hindrance to the progress of women entrepreneurs is the absence of adequate financial literacy. The objective of this research was to ascertain the importance of financial literacy concerning the achievement of women entrepreneurs. In order to achieve the research objectives, a qualitative investigation was conducted, wherein interview data was gathered according to the OECD core competencies framework on financial literacy for entrepreneurs from a sample of twenty-three women entrepreneurs. The participants were selected based on the criteria of having a business that has been operational for at least five years. The results indicate that financial literacy considering the three dimensions assessed: financial knowledge, skills and attitude significantly influences the efficacy of women entrepreneurship. Consequently, it is recommended that women entrepreneurs engage in group-based and targeted training programmes to acquire the necessary skills to enhance their financial literacy
A critical review of FOMO behaviour among young investors
No full textThe fear of missing out (FOMO) is the emotional feeling of missing out on the opportunity to gain a fulfilling experience. FOMO is a behavioural trait that influences an individual’s decisions such as utilising social media, adopting new technology, crowdfunding, and investing in the equity market. Young investors with FOMO behaviour might mimic what other investors do in fear of missing out on the opportunity for a higher return in the financial market. The purpose of this paper is to understand the concept of FOMO and review what researchers have discovered about FOMO behaviour among young investors. Based on these recent findings on FOMO behaviour, it can be concluded that a volatile market, risk-averse investors, and perceived market efficiency are critical factors of FOMO behaviour among young investors. The risk-averse attitude, subjective norms of perceived market efficiency and perceived control behaviour during market volatility could be examined based on the TPB model
Stacking Ensemble Approach for Churn Prediction: Integrating CNN and Machine Learning Models with CatBoost Meta-Learner
No full textIn the telecom industry, predicting customer churn is crucial for improving customer retention. In literature, the use of single classifiers is predominantly focused. Customer data is complex data due to class imbalance and contain multiple factors that exhibit nonlinear dependencies. In these complex scenarios, single classifiers may be unable to fully utilize the available information to capture the underlying interactions effectively. In contrast, ensemble learning that combines various base classifiers empowers a more thorough data analysis, leading to improved prediction performance. In this paper, a heterogeneous ensemble model is proposed for churn prediction in the telecom industry. The model involves exploratory data analysis, data pre-processing and data resampling to handle class imbalance. In this proposed model, multiple trained base classifiers with different characteristics are integrated through a stacking ensemble technique. Specifically, convolutional-based neural network, logistic regression, decision tree and Support Vector Machine (SVM) are considered as the base classifiers in this work. The proposed stacking ensemble model utilizes the unique strengths of each base classifier and leverages collective knowledge to improve prediction performance with a meta-learner. The efficacy of the proposed model is assessed on a real-world dataset, i.e., Cell2Cell. The empirical results demonstrate the superiority of the proposed model in churn prediction with 62.4 % f1-score and 60.62 % recall.
Manuscript Received: 22 June 2023, Accepted: 1 August 2023, Published: 15 September 2023, ORCiD: 0000-0002-3781-662
Legislative Update: Malaysian Space Board Act 2022: Its Major Legal Frameworks
No full textMalaysian Space Board Act 2022 (Act 834) was gazetted on January 25, 2022. It is a new outer space legislation that was passed by the Malaysian Parliament. This Act is designed to regulate Malaysian outer space activities that are carried out nationally or internationally. This paper discusses the major legal frameworks of the Malaysian Space Board Act 2022. They are the establishment of the Malaysian Space Board, modes of authorisation of space activities, registration of space objects, liability and indemnification, prohibition of activities and offences, event of incident and accident, power of enforcement of public officers, and other relevant legal matters. The methodology used is by analysing the provisions stated in the Malaysian Space Board Act 2022, works of authoritative writers, and United Nations space conventions and treaties. The paper concludes that the Act is a good space legislation, however, certain matters need to be given consideration like the obligation of constant monitoring and supervision of space activities, and the liability insurance clause
AIRA: An Intelligent Recommendation Agent Application for Movies
No full textAn intelligent Recommendation App has been developed to assist caregivers. This project's primary objective is to assist parents in determining whether a particular movie/cartoon/drama is adequate for their children by providing ratings that will assist them in identifying age-appropriate content. This application will provide reliable evaluations, reviews, and recommendations to parents. Each rating and review are based on fundamental, essential child development principles. Intelligent Recommendation Agent aids families in making intelligent media selections. It provides the most extensive and reliable database of learning ratings, age recommendations, and content evaluations for films, television series, and dramas. In addition, there will be a list of abusive words from the content with its subtitles so that parents can identify appropriate content for children. By limiting their child's exposure to violent acts, parents can play a positive role in their child's life by using this application. Movies with positive role models can also have a positive effect on children