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Association of Musculoskeletal Pain with Poor Quality of Sleep Among E-Gamers in a Private University in Malaysia
No full textBackground: Electronic sports (e-sports) requires prolonged sitting and repetitive movements which makes e-gamers susceptible to develop musculoskeletal pain in different body parts. Moreover, their quality of sleep may also be affected. It is very important for physiotherapist to identify the relationship between musculoskeletal pain and poor quality of sleep among e-gamers, so as to develop more precise treatment plan and provide higher quality of patient education.
Objective: The purpose of this study was to analyse the association between musculoskeletal pain with poor quality of sleep among e-gamers in a private university in Malaysia.
Methodology: The sample consisted of 42 e-gamers from a private university in Malaysia. A cross-sectional study was conducted by using Nordic Musculoskeletal Questionnaire and Sleep Quality Scale. The association between musculoskeletal pain and poor sleep quality was evaluated using chi-square test.
Results: The results showed that more than half of the study population reported with a higher prevalence of neck pain in the past year and in the previous week, followed by shoulders, wrists and hands. Besides, half of the participants also reported that they had very poor sleep quality (50%), followed by the category of poor quality of sleep (23.8%). E-gamers with poor sleep quality showed significant association with musculoskeletal pain in neck (p= 0.004), shoulder (p= 0.052), upper back (p=0.043), wrist and hands (p= 0.004).
Conclusion: Our findings revealed that musculoskeletal pain in neck, shoulder, upper back, wrist and hands was significantly associated with poor sleep quality among e-gamers. Health promotion actions that contribute towards improvement in quality of sleep and prevention of musculoskeletal pain should be considered, so the performance and quality of life among the e-gamers could be improved
Factors Determining the Customers' Intention to Purchase OTC Products through E-Pharmacies
No full textIn the health care system, over-the-counter (non-prescribed) drugs play a crucial role in the medication process. Over-the-counter (OTC) drugs are medicinal products sold without a doctor's prescription. Without seeking care from health professionals, OTC medications are safe and effective for the general public usage. Generally, OTCs and self-medicines are used to treat mild health issues in a simpler and inexpensive way. Cold-and-cough medicines, vitamins, analgesics, digestive medicine (i.e., anti-acids), and dermatological medicines are the categories that dominate the world's top five OTC market-share. Limited studies in India aimed at evaluating OTC purchasing behaviour in e-pharmacies. Therefore, this study aimed to identify influential E-pharmacy factors that are affecting consumers during OTC products purchase. This study also examined the consumers' intention to purchase OTC products across major cities of Tamil Nadu. A total of 153 responses were collected from e-pharmacy customers through self-administered questionnaires across 4 major cities of Tamil Nadu. E-pharmacy customers who made at least one purchase on the e-pharmacy website were considered for the study. Based on the results, analgesic drugs are the most preferred OTC category in the online purchase mode. The results also demonstrated that post-purchase behaviour aspects like on-time delivery of the product and providing the shift response to solve the queries raised by the e-pharmacy customers play a significant role in enhancing customer satisfaction across e-pharmacy sites
Movie Recommendation System Based on Sentiment Analysis on Movie Reviews
No full textA movie review plays a significant role in determining whether the movie is recommended to them. Nowadays, movie reviews are filled with paid, sarcasm, and fake reviews that give users mixed feelings about the movie. With a movie recommendation system based on sentiment, the movie review is analyzed with specific keywords that give the user an absolute result on whether it is recommended or not recommended. The system uses three classifiers, Naïve Bayes, Support Vector Machines (SVM), and Deep Learning to determine the best classifier that gives better accuracy for user purposes. The core approach of this project is to provide the user with a simplified view that analyses all accumulated reviews into one single view. The project results show that SVM produces the best results with 81.17% accuracy. That result is because of the nature of the classification that works best in categorization. This project includes future works, adding more lists of movies and user input for better interactivity between users and machines
WEAP Analysis of Water Supply and Demand in Langat Catchment of Malaysia
No full textRecently, there have been water shortages in the state of Selangor of Peninsular Malaysia due to pollution from surrounding river tributaries, increase in destruction and degradation of water catchments. This study serves to look into the water demand and supply issues by analyzing the trend and relationship between demand and supply of water in Langat catchment, evaluating the current water availability and water demand for different sectors, such as agriculture, industry, and domestic using and analyzing the status of future scenarios of the water supply system. Water Resource Modelling tool called Water Evaluation and Planning (WEAP) obtain meteorological, population and climate data from relevant authorities and entering the data into WEAP which will simulate results based on the data entered and scenarios suggested by the users. The results obtained from the simulation show that an increase in population growth rate will result in increased demand for water, as found that in 2009 the demand for water is 370 million cubic meters and in 2040 it is 560 million in cubic meters, low population growth rate however shows that as population growth rate decreases demand and unmet demand for water decreases which shows that demand for water in 2009 the demand for water is 370 million cubic meters and in it is 280 million cubic meters. Hence this will help water management authorities to plan and allocate available resources accordingly so that it does not affect water availability for future generations
Monitoring Social Distancing Compliance Using Image Processing Algorithm
No full textSince the outbreak in December 2019, Malaysia has been in the throes of the Covid-19 pandemic, which has had a particularly enormous impact on both the country and the people. Although the government has actively constructed a set of effective standard operating procedures (SOP) to ease the epidemic, such as wearing masks, washing hands often, and maintaining social distance, these have had little effect, and the pandemic continues to grow. As a result, many people have been unable to maintain social distance, allowing the disease to spread to others. According to this viewpoint, a social distancing monitoring system could be a useful tool for monitoring and reminding people to maintain adequate social distance in real time. This system allows for real-time video and CCTV surveillance, as well as effective distance analysis to determine whether the effective social distance has been attained. This strategy can also be used in a variety of venues, including school cafeterias, malls, public spaces, and so on. Otherwise, because shopping malls have a lot of CCTV cameras, the technology can also be deployed there. When a site has a significant number of people but no social distance between them, the system will warn management to improve the location's security measures
Sentiment Analysis on Natural Skincare Products
No full textSkincare Industry was increasing rapidly year by year. In contrast, many skincare companies have brought their products and originality to attract many customers. However, due to many controversial cases involving the chemical substance in skincare products, the company switched to something more natural: natural skincare. With much natural skincare in the shop, many customers face the problem of which one to buy. This research helps customers by giving a guideline for the customers to make the decision. Sentiment Analysis is used to analyze the reviews from past customers and create a visualization containing positivity and negativity of all the reviews. Five classifiers were used to produce the best result: Naïve Bayes, KNN, SVM, Decision Tree, and Deep Learning. The reviews were collected from Sephora.com websites, and the tools used in analyzing the reviews are Python and RapidMiner. Reviews collected are 10000 data from a website. The result shows that Deep Learning and Decision Tree are classifiers in sentiment analysis with almost 80% accuracy and 60% F1 measurement. F1 measure is a measure of a test's accuracy. For future enhancements, the data collected can be more than this research, and no data imbalance was created
Potential of Microalgae for Biofuel and Food Production
No full textWith the continuous increase of global population, energy and hunger are the critical crisis that humankind facing in this century. Microalgae has been proposed as the solution due to the presence of the various metabolite and their attractive features. This review summaries the potential of microalgae as the feedstock for biofuel and food production. The literature indicated that the abundance of suitable fatty acid in microalgae can be used for biodiesel production while other bio-components such as carbohydrate can be used for biogas and bioethanol production. Apart from biofuel production, presence of high-quality protein, fatty acid, polysaccharides, vitamin, minerals and other bio-components with benefit biological properties in microalgae spur it as dedicated candidates for food production. However, the microalgae derived biofuel and food are still not available at the moment. The challenges that might need to be confront prior to industrial production are also briefly discussed in this review
Classification of MTI Student Thesis Documents at Bina Darma University Palembang Using Naïve Bayes
No full textOne of the resources that students might use as a guide when conducting research is the university
library. A research thesis written by former students serves as reference material. Students must
arrange the thesis documents following the concept or topic of their research because they are
typically organized by faculty and department. Researchers, therefore, attempt to classify student
thesis documents according to themes or subjects so that students can be more precise in their
search for references to themes or topics that relate to the research they will do. The title, abstract,
and important keta from the thesis document will be used as the study's data, which will then be
classified using the best classification technique, the Naive Bayes Classification (NBC) approach.
The learning stage and the testing stage are the two steps used in the naive Bayes classifier
method's classification process. After establishing the Category and the quantity of data learning
documents, probability calculations were then carried out for each category
Palembang Aerodrome Weather Forecast for Palembang Sultan Mahmud Badaruddin II Airport
No full textSMB II Palembang Meteorological Station is one of the weather observation points owned by
BMKG in charge of carrying out weather observations, analysis, and weather forecasts at Sultan
Mahmud Badaruddin II Airport Palembang. Weather information has an important role in the
world of aviation, so accurate airport weather forecasts are needed. Random Forest, Naive Bayes
Classifier, and Support Vector Machine methods are classification methods used to forecast rain
in this study. The data used is weather parameter data from December 2012 to December 2021.
Rain forecast using the SVM method produces an accuracy rate of 72%, the NBC method 66%,
and the Random Forest method produces an accuracy rate of 74%. Heavy rains and very heavy
rains can’t be predicted accurately using the SVM, NBC, and Random Forest methods. Based on
the feature selection method, the attribute that has the most influence on rain forecasts is the
average humidity
Health Benefits and Pharmacological Properties of Stigmasterol
No full textStigmasterol is an unsaturated phytosterol belonging to the class of tetracyclic triterpenes. It is one of the most common plant sterols, found in a variety of natural sources, including vegetable fats or oils from many plants. Currently, stigmasterol has been examined via in vitro and in vivo assays and molecular docking for its various biological activities on different metabolic disorders. The findings indicate potent pharmacological effects such as anticancer, anti-osteoarthritis, anti-inflammatory, anti-diabetic, immunomodulatory, antiparasitic, antifungal, antibacterial, antioxidant, and neuroprotective properties. Indeed, stigmasterol from plants and algae is a promising molecule in the development of drugs for cancer therapy by triggering intracellular signaling pathways in numerous cancers. It acts on the Akt/mTOR and JAK/STAT pathways in ovarian and gastric cancers. In addition, stigmasterol markedly disrupted angiogenesis in human cholangiocarcinoma by tumor necrosis factor-α (TNF-α) and vascular endothelial growth factor receptor-2 (VEGFR-2) signaling down-regulation. The association of stigmasterol and sorafenib promoted caspase-3 activity and down-regulated levels of the anti-apoptotic protein Bcl-2 in breast cancer. Antioxidant activities ensuring lipid peroxidation and DNA damage lowering conferred to stigmasterol chemoprotective activities in skin cancer. Reactive oxygen species (ROS) regulation also contributes to the neuroprotective effects of stigmasterol, as well as dopamine depletion and acetylcholinesterase inhibition. The anti-inflammatory properties of phytosterols involve the production of anti-inflammatory cytokines, the decrease in inflammatory mediator release, and the inhibition of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). Stigmasterol exerts anti-diabetic effects by reducing fasting glucose, serum insulin levels, and oral glucose tolerance. Other findings showed the antiparasitic activities of this molecule against certain strains of parasites such as Trypanosoma congolense (in vivo) and on promastigotes and amastigotes of the Leishmania major (in vitro). Some stigmasterol-rich plants were able to inhibit Candida albicans, virusei, and tropicalis at low doses. Accordingly, this review outlines key insights into the pharmacological abilities of stigmasterol and the specific mechanisms of action underlying some of these effects. Additionally, further investigation regarding pharmacodynamics, pharmacokinetics, and toxicology is recommended