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Co-pyrolysis of plastics and food waste mixture under flue gas condition for bio-oil production
No full textGrowing global population increased the energy demand and generation of municipal solid wastes (MSW). MSW can be utilized to produce green renewable fuels via pyrolysis technology. This study investigated the co-pyrolysis of MSW represented by mixtures of food and plastic wastes, in a downdraft pyrolyzer using synthetic flue gas composition. The food wastes in this study included fish and chicken bones, and leftover rice, and plastics included polypropylene and polyethylene (high density and low density) plastics respectively. The effect of pyrolysis temperature and types of feedstocks on the bio-oil yield and quality were determined. Although the highest bio-oil yield was obtained at 400 °C for all feedstocks, GC–MS results indicated major compounds such as fatty acids, esters, amides, nitriles, sugars were more notable at 300 °C. The bio-oil exhibited high water contents due to combustion from the flue gas. Fish bone and plastic mixture has the lowest O/C ratio and the best calorific value of 33.9 MJ/kg compared to the other two feedstocks, however extensive treatments were required to be used as fuel. Overall, bio-oil from this study has the potential to be used as an alternative fuel from co-pyrolysis of food and plastic wastes with further treatments and processing
Awareness and Practices of Injury Prevention Strategies Among Ultimate Frisbee Players in Selangor, Malaysia
No full textIntroduction: Among all club sports, Ultimate frisbee has one of the highest numbers of reported injuries. To reduce the
overall burden of injury, developing and implementing effective, sport-specific injury prevention strategies should be a top
priority. This study aimed to investigate the awareness on injury prevention strategies as well as commonly used injury
prevention strategies among Ultimate frisbee players in Selangor, Malaysia. Methods: A cross-sectional study was
conducted using an online self-administered questionnaire. Participants were recruited through various Ultimate frisbee
clubs from social media via purposive sampling. Results: 211 eligible responses were obtained and over 72% of the
players consider using proper technique in the game is important for preventing injuries. Over 50% of the
participants were aware of factors such as proper technique (72.5%), stretching during warm-up (65.4%), warm-up
(62.6%) and strength training as extremely important. Majority of participants practices injury prevention strategies
such as stretching (82.9%), pre match general warm up (79.6%), fluid consumption following match (75.8%) and
training session (73.9%). Conclusion: Hence, education for Ultimate frisbee players is recommended to promote the
importance and benefits of different sports related injury prevention strategies to reduce the likelihood of injuries thus,
enhancing sports performance
Load Optimization with Shortest Distance Approach
No full textThe most beneficial results or values are produced through an optimization technique. Load optimization is a problem that the logistics sector faces, despite the fact that there are many other optimization-related concerns. This problem has a connection to the knapsack problem, which is the combination of the number of items that can fit into a container with a capacity when one set of items has both weight and volume. The following problem is referred to as "Bin packing," which is an optimization problem in which objects of various sizes must be packed into a finite number of bins or containers, each of which has a specific capacity, while utilizing the fewest number of bins. By merging these two issues, the best payload value will be produced. In order to optimize the volume and weight of product preparation and arrangement based on delivery destinations (in terms of distance) on previously operational vehicles, a program will simulate the combination of these concerns. The initial load item carried by the original driver was compared in this study using experimental data to the outcomes of the load optimization approach. Results after the shortest distance approach's improvement were compared to the results obtained before. According to the comparison, the shortest-distance approach led to better outcomes
The Effect of WhatsApp Usage on Employee Innovative Performance at the Workplace: Perspective from the Stressor–Strain–Outcome Model
No full textSocial media applications have increasingly become a valuable platform for personal communication and knowledge sharing in working life. Several researchers have considered the direct role of social media usage in influencing job performance. However, limited studies explore how social media use may impact employees’ job performance, especially in innovativeness. Moreover, inconsistencies in the findings exist in the literature regarding whether social media improves employees’ job performance or causes harm. By adapting the stressor–strain–outcome (SSO) model, the present study investigates how WhatsApp use at work can predict social media overloads that might induce technostress and, subsequently, affect employees’ innovative job performance. Thus, 206 Malaysian employees from the government and private sectors participated in this study and the data were analyzed using partial least squares structural equation modeling (PLS-SEM). The findings show that social media, predominantly WhatsApp, used at work has a mild but statistically significant influence on information overload, communication overload, and social overload. In addition, information overload and communication overload positively influence technostress, except for social overload. Subsequently, technostress does not have an impact on innovative job performance. This study provides theoretical and practical implications for extending the knowledge and mitigating plans and efforts to improve employees’ performance at work. Therefore, this study helps mitigate the dearth of research pertaining to the roles of social media use at work on employees’ innovative job performance
Microwave-Assisted in the Preparation of Nitrogen-DopedTiO2for the Photogradation of Organic Dyes: Effect of pH and Catalyst Dosage
No full textThe unmodified TiO2was modified using a microwave technique to produce a visible light active nitrogen (N) doped TiO2. The modified photocatalyst was prepared by mechanical mixing of unmodified TiO2with various amounts of urea and various irradiation power of micrcowave .It was observed that the N doped TiO2at 800 W of microwave power irradiation with urea content 3 g was defined as the optimum condition for a modified photocatalyst. N doped TiO2then was characterized using X-ray photoelectron spectroscopy (XPS), photoluminescence (PL) and UV-Vis diffuse reflectance spectra (UV-Vis/DRS) analyses. The XPS and PL proved that the successful nitrogen doped into the TiO2. XPS results presented with two peaks with binding energy 404.8 and 400.2 eV that indicates the formation of chemical interaction N with titania forming N doped TiO2.In addition, UV-Vis/DRS confirmed that the introduction of nitrogen into TiO2by decreasing the bandgap energy value from 3.02 eV to 2.9 eV. The photocatalytic activity study of N doped TiO2was carried out by irradiating 25 mL of 30, 10 and 5 mg L-1of anionic Reactive Red 4 (RR4), cationic Methyl Violet (MV) and cationic Janus Green dyes (JG) in the presence of fluorescent light and visible light (UV cut-off) with the rate of photodegradation was estimated from aliquot concentration spectrophotometrically. The irradiation of N doped TiO2was conducted using two parameters namely the effect of catalyts dosage and the effect of pH. It can be observed that 0.0012 g /mL of catalyst dosages that givesan optimum photocatalytic degradation for both anionic and cationic dyes. Effect of pH was conducted based on the optimum catalyst dosage and conclude that pH 4 and 8 were the optimum pH for anionic and cationic dyes respectivel
Uncovering Relationship between Sleep Disorder and Lifestyle using Predictive Analytics
No full textSleep disorder refers to the conditions that affect the ability of someone to sleep well regularly whether they are caused by health problems or other outside influences. Occasionally most people experience a sleeping problem due to various reasons. However, when this issue keeps occurring and interferes with daily life, this may indicate a sleeping disorder. In some cases, a sleep disorder may be a symptom of another medical or mental health condition and eventually gone once treatment is obtained for the underlying cause. The treatment normally involves a combination of medical treatments and lifestyle changes. Previous research reported that someone’s lifestyle may affect the sleep length and its quality. For example, food choice affects sleep quality and caffeine consumption affects sleep length. This paper aims to uncover the relationship between sleep disorder and lifestyle by performing data investigation using predictive analytics. This study employs Cross Industry Standard Process for Data Mining (CRISP-DM) as methodology. Starting with collection of raw datasets, which were acquired from SleepFoundation.org, one of the leading sources of evidence-based pertaining sleep health information. From there, 1000 data records with 77 attributes are selected and categorized into five class labels i.e. Personal, Diet, Technology, Disease, and Environment. The 77 attributes including depression, anxiety disorder, felt sad, overall health, etc. are then measured using Cramer’s value and visualize using Mosaic plots. The Correlation Coefficient and P-value methods are employed to define the relationship among those attributes with a sleep disorder. As for the predictive analytics, we exploit three data mining methods i.e. Support Vector Machine (SVM), Conditional Inference Tree (CTree) and Recursive Partitioning (Rpart). Results show that SVM lead the accuracy level up to 80.288% outperformed Rpart (71.428%) and Ctree (66.499%)
Comparison of the Effects of Task Oriented Balance Training Versus Blindfolded Balance Training in Patients with Parkinson’s Disease
No full textObjectives: The purpose of this study was to find the efficacy of task oriented balance training and blindfold balance training to improve postural balance in patients with Parkinson’s disease.
Materials and Methods: A comparative study was done with 20 samples. The study was conducted in kriston clinic. The duration of treatment was 8 weeks. Both male and female individuals with Parkinson’s disease in concern about falling, instability and balance problem, between the age group of 50-55 were included. PD with other neurologic diagnosis, severe impairments, cardiac problem, uncooperative are excluded. The measurements were taken using Unified Parkinson’s Disease Rating Scale (UPDRS) and Berg balance scale (BBS).
Based on inclusion and exclusion criteria and outcome measures, 20 subjects with Parkinson disease (PD) were divided into two groups. Group A- 10 subjects were treated by using Blind folded balance training and Group B-10 subjects were treated by using Task Oriented balance training. Before the onset of treatment protocol, the technique was explained to the patients and informed concern was taken from the patients. The baseline measurements were taken by using Unified Parkinson’s Disease Rating Scale (UPDRS) and Berg balance scale (BBS). The procedure was done by performing Blind folded balance training for 4 times a week for 8 weeks for group A and Task Oriented balance training is performed for 4 times a week for 8 weeks for group B. After the study, pre and post test measurement were taken and compared using Unified Parkinson’s Disease Rating Scale (UPDRS) and Berg balance scale (BBS).The collected data were tabulated and analyzed using IBM SPSS VERSION 20.0 SOFTWARE. The collected data were analyzed and tabulated with the descriptive and inferential statistics. For the descriptive statistics, the mean and standard deviation were calculated and for the inferential statistics, the parametric variables were treated with t-test. The results were tabulated and the results were plotted accordingly.
Results: On comparing pre test and post test values within the Group A and B on Unified Parkinson’s Disease Rating Scale (UPDRS) and Berg balance scale (BBS) shows significant difference in mean values at p< 0.005.
Conclusions: This study concluded that blindfolded balance training is effective in improving Balance in Parkinson’s disease patients with balance impairment, when compared to task oriented balance training
THE IMPACT OF VIRAL MARKETING IN THE TOURISM INDUSTRY IN MALAYSIA POST COVID-19 PANDEMIC
No full textViral marketing played a major role in tourism marketing for the government and private sector. This marketing strategies often referred to as electronic word-of-mouth (eWOM). Extensive research studies have been carried out on the mechanism and importance of viral marketing. However, there is a research gap on the viral marketing impact on the tourist destination in the COVID-19 pandemic crisis. The purpose of this paper is to discuss the impact of viral marketing or electronic WOM (eWOM) on a tourism destination choice after COVID-19, using the theory of planned behaviour (TPB). The intended outcome and purpose of the study is look at possible adaptive marketing strategies and approaches in the endemic stage of COVID-19. The effectiveness of viral marketing in promoting tourist destinations in Malaysia is studied in this literature view to identify the influence of viral content in tourist decision-making
Twitter Sentiment Analysis on Automotive Companies
No full textMany users would use social media to express their opinions on their products or services. The expression can be good or bad. This project proposed a sentiment analysis on the automotive company where the users' opinions are analysed through this feedback. The data are collected from the social media of Twitter and followed by data mining techniques which are tokenization, removing stop words, and stemming. A sentiment classifier is implemented after the data have been converted into valuable data. Naïve Bayes classification is employed in this project by using Python language. Based on the dataset that we use, the article may analyse market demand for the automobile industry. According to the findings, Honda and Mazda had the highest positive sentiment, with more than 85 percent. This project is beneficial to the automotive industry, especially to teams' production. This finding supports a better understanding between the industry and their customer, to enhance the business strategies and find out the weaknesses
The Simulation and Analysis of Erosion Corrosion of CO2 Pipelines - A Review
No full textOil and gas production activities use pipeline to distribute raw materials of oil from reservoir to the other processing facilities. These raw materials of oil/crude oils composes elements such as CO2 gas and solid particles which are potential to damage pipe wall through erosion corrosion reactions. Unpredicted design gives fatal impact to the operational process and interrupt continuity of oil distributions. Therefore, it needs corrosion prediction to manage integrity strategies in oil companies. Considering multiple effects created by various corrosive factors, fundamental knowledge to understand corrosion mechanism is important to study in designing corrosion prediction software. To date, numerous corrosion predictions models with different approaches have been developed by oil and gas companies. This paper reviews the applications of fundamental theories of corrosion used by software (ECE, Norsok, Freecorp) in calculating erosion corrosion rate of carbon steel pipes. The concept of existing corrosion software is discussed. Parameters used and range of conditions are also studied. From the results of studies, it can be notified that corrosion predictions software have a prospective tool for determining degradation rate of carbon steel pipes in future. They also have benefits in selecting materials for pipelines and predicting service life of the pipes accurately