Teaching Al-Quran among the Army Personels to increase the Level of Discipline

Discipline has been characterised by several scholars as mental and moral activities that ensure conformity to rules and regulations for the development of society. In any organisation, the core problem that needs to be tackled is the disciplinary problem. Islam has promoted discipline as the interjecting factor which leads to success in this world and hereafter. This descriptive study will be discussing on the disciplinary problems among the army personnel, the contributing factors to the problem as well as coming up with Islamic approach solutions to the problem. Discipline and the military are synonymous and the ability to adhere to the rules that have been determined is the decisive factor which can lead to one's career excellence in the military. Zina, gambling, alcoholism is some of the criminal cases that have been committed by these personnel. It is believed that the occurrences of these cases are due to their lack of religious knowledge and practices (not performing prayers and being ignorant towards the Al-Quran), lack of parental guidance and family problems. This paper will investigate how the principles of Al-Quran can assist in the instillation of discipline as outlined in Islamic teachings among the military personnel. This study will use a qualitative method by reviewing related documents, interviews and carrying out observations. In order to establish high discipline levels within the Malaysian Armed Forces, a more in-depth assessment of the existing disciplinary problems, their contributing elements, and resolving actions based on the principles of the Al-Quran will be conducted

Media Sosial dan Impak Negatif Menurut Islam

Media sosial semakin menjadi daya tarikan kepada semua individu seluruh dunia dan membantu berkongsi maklumat penting dan berguna kepada masyarakat. Di sebalik kemajuan internet dan media massa, media sosial mampu memberi impak negatif kepada semua penggunanya. Artikel ini membahaskan tentang media sosial dan impak negatif menurut Islam. Dapatan kajian menunjukkan media sosial mampu mempengaruhi perkembangan fizikal, akademik dan akhlak bagi seseorang individu. Hubungan sesama ahli keluarga, jiran tetangga dan rakan sebaya boleh terjejas dan tiada persefahaman akibat penyalahgunaan media sosial. Imej dan maruah negara juga turut menjadi taruhan kepada negara lain. Oleh itu, penggunaan media sosial haruslah dikawal dan sentiasa berfikir tentang kesan dan impak bagi setiap tindakan yang bakal dilakukan sebelum dikongsi di media sosial

A conceptual model for e-learning supporting tools design based on cue model and Kansei engineering

The Covid-19 pandemic has triggered changes in learning due to the practice of social distancing to curb the spread of the virus. E-learning platforms have become the main platform for learning throughout the pandemic. However, e-learning does have challenges when it comes to ensuring student’s optimum participation throughout the learning experience that require extensive research about techniques and methods for an optimum e-learning experience. This includes various e-learning supporting tools that provides easy communication and immediate assistance to enhance user experience. The supporting tools or software usability and functionality design determined as imperative in enhancing the e-learning user experience. Thus, this research proposes a conceptual model for designing the e-learning supporting tools based on the CUE Model, integrated with Kansei Engineering for optimum user experience that can serve as a guideline for the e-learning supporting tools designer. The outcome of this research will create new research fields that incorporate multiple domains, including the e-learning domain, software and supporting tools design, emotions and user experience

Dynamic QoS: Automatically Modifying QoS Queue's Maximum Bandwidth Rate-Limit of Network Devices for Network Improvement

The heterogeneous data traffic of today's network is a huge challenge to existing best-effort network technology, particularly in the context of large Ethernet, which handles hundreds to thousands of users. The existing conventional best-effort network technology is no longer efficient to handle the diversity of traffic types in the network and requires network management equipment such as Quality of Service (QOS). Usually, QOS is implemented on the gateway router. However, for better network performance and management, to guarantee high priority for sensitive traffic like video conferencing, Voice over Internet Protocol (VoIP), and streaming media within an internal network, it is nice to have QoS implemented on each router in the LAN network, starting from the access router to the gateway router. This paper is to demonstrate the effectiveness of the proposed dynamic QoS that has been developed and deployed in the LAN, purposely to provide adequate bandwidth for sensitive traffic when the network utilization is high and congested, by automatically modifying the QoS Queue's Maximum Bandwidth Rate-Limit of the best-effort traffic queue of the related router. The performance of the proposed developed dynamic QoS was evaluated via a comparison study before and after the dynamic QoS was presented in the network simulation environment that was built using Mininet. Results from the testing show that the developed dynamic QoS can improve the network's performance by automatically giving the appropriate bandwidth for sensitive traffic on the fly while needed/on demand

Aggressive movement detection using optical flow features base on digital & thermal camera

Detection and tracking of people in digital images has been subject to extensive research in the past decades.Following the growing availability of thermal cameras and the distinctive thermal signature of humans, research effort has been focusing on developing people detection and tracking methodologies applicable to this sensing modality.Thermal imaging technology can be used to detect aggressive levels in humans based on the radiated heat from their face and body. Previous research proposed an approach to figure out human aggressive features using Horn-Schunck optical flow algorithm in order to find the flow vector for all video frames using digital camera only. However, still not strong enough to confirm and verify the existence of an aggressive movement. Then, we propose another approach using thermal videos to detect aggressive features in human aggressive movement.Video frames are collected using thermal camera and then extracted into thermal images. This research also guides and discovers the patterns of body distracted movement.Result below will show the comparison between both cameras digital and thermal camera

Characteristics of clients with nicotine dependence and short-term abstinence: findings from the USM Tobacco Quitline Service in Malaysia

Background Globally, quitlines have been shown to be an effective means for smoking cessation. The success of quitting among smokers is contributed by many factors such as nicotine dependence, motivation, income and educational levels, previous quit attempts, environmental characteristics and quit methods. This study will determine the characteristics of clients with nicotine dependence and short- term abstinence (one month duration) among those registered with the USM Tobacco Quitline Service. Methods Secondary analysis of USM Tobacco Quitline clients with the age range between 18-80 years old who completed initial assessment (one week pre Quit Date (QD)) and have been followed-up within one month post QD. The Fagerstrom Test for Nicotine Dependence (FTND), which is a validated six-item scale, was used to assess the nicotine dependence among those that registered for Quitline service one week prior to QD. Continuous abstinence (relapse or continue quitting) data was obtained for one month post QD. Results Of the 418 registered clients, 68.2% (n=285) confirmed their registration. Sixty four clients completed their initial assessment and were followed-up within one month post QD. Majority (93.8%) of them were males with the mean age of 44. All clients with high FTND score and 95.5% clients with moderate FTND score successfully achieved one month smoke- free (short-term abstinence) higher than clients with mild FTND score. Conclusions The findings showed that smokers with high and moderate FTND scores were able to achieve better short-term abstinence compared to those with mild FTND score. Further research needs to be conducted to understand the reason for this behaviour. This result does not take into account other abstinence factors. A long-term abstinence data would provide an insight on the ways to improve the service particularly in the diverse client background

Political Security Threat Prediction Framework Using Hybrid Lexicon-Based Approach and Machine Learning Technique

The internet offers a powerful medium for expressing opinions, emotions and ideas, using online platforms supported by smartphone usage and high internet penetration. Most internet posts are textual based and can include people’s emotional feelings for a particular moment or sentiment. Monitoring online sentiments or opinions is important for detecting any excessive emotions triggered by citizens which can lead to unintended consequences and threats to national security. Riots and civil war, for instance, must be addressed due to the risk of jeopardizing social stability and political security, which are crucial elements of national security. Mining opinions according to the national security domain is a relevant research topic that must be enhanced. Mechanisms and techniques that can mine opinions in the aspect of political security require significant improvements to obtain optimum results. Researchers have noted that there is a strong relationship between emotion, sentiment and political security threats. This study proposes a new theoretical framework for predicting political security threats using a hybrid technique: the combination of lexicon-based approach and machine learning in cyberspace. In the proposed framework, Decision Tree, Naive Bayes, and Support Vector Machine have been deployed as threat classifiers. To validate our proposed framework, an experimental analysis is accomplished. The performance of each technique used in the experiments is reported. In this study, our proposed framework reveals that the hybrid Lexicon-based approach with the Decision Tree classifier recorded the highest performance score for predicting political security threats. These findings offer valuable insight to ongoing research on opinion mining in predicting threats based on the political security domain