Joy Learning: Smartphone Application For Children With Parkinson Disease

Parkinson's is a Neurologic disorder that not only affects the human body but also their social and personal life. Especially children having the Parkinson's disease come up with infinite difficulties in different areas of life mostly in social interaction, communication, connectedness, and other skills such as thinking, reasoning, learning, remembering. This study gives the solution to learning social skills by using smartphone applications. The children having Parkinson's disease (juvenile) can learn to solve social and common problems by observing real-life situations that cannot be explained properly by instructors. The result shows that the application will enhance their involvement in learning and solving a complex problem

Impact of Capital Structure on Banking Performance

This paper examines the impact of capital structure on bank performance. The study spreads empirical work on capital structure determinants of banks within country and foreign country. Multiple reversion models are useful to evaluation the relationship between capital structure and banking performance. Performance is measured by return on assets, return on equity and earnings per share. Determinants of capital structure contains long term debt to capital ratio, short term debt to capital ratio and total debt to capital ratio. Results of the study validated a positive relationship between factors of capital structure and performance of banking industry. Keywords: Banking Performance, Optimal Capital Structure, Return on Assets, Return on Equity, Earning Per Share

Food safety knowledge, beliefs and behaviour among health sciences-related field undergraduate students at a local university

Foodborne disease is among the primary illness that causes morbidity and mortality in the world. Several studies show that most students do not have adequate food safety knowledge to protect themselves against foodborne diseases. This study aimed to determine the food safety knowledge, behaviour, and beliefs among undergraduate students at a local university in Malaysia. This cross-sectional study involves 121 respondents from three health science-related faculties at the studied institution. The questionnaire was distributed via an online platform. This study used multiple-choice-format questions for Food Safety Knowledge and a Likert type scale for Food Safety Behaviour and Belief question statements. Most of the respondents were female (78%). About 16% of the respondents have experience working /volunteering in food services, and half of them are involved in food handling during their services. This study recorded a moderate score in all sections (knowledge, behaviour, beliefs) with a total percentage score of 60.3%, 60.3%, and 66.1%, respectively. A strong but not significant correlation between food safety knowledge and beliefs (r = 0.69 p > 0.05) and between food safety knowledge and behaviour (r = 0.83 p > 0.05) were observed. This study is useful as a basis to develop a targeted food safety education program among undergraduate students. Students with high knowledge of food safety will increase food safety beliefs and behaviour, thus preventing them from getting any foodborne illness

The Influence of Service Quality and Price Perspective on Customer Satisfaction Users of Transport Services Online Taxi Car in Makassar City

Grab-Car is an online taxi service from GRAB which is currently very much needed by the public in the transportation sector to facilitate community mobility. The development of this application-based online taxi transportation business is very easy to use for the community, whenever and wherever the public can use online-based taxi transportation services. This study aims to see the effect of service quality and price perceptions on customer satisfaction using Grab-Car online taxi transportation services in Makassar City. The sample in this study is the people who live in the city of Makassar who have used the Grab-Car service. Data collection techniques are observations and questionnaires given to Grab-Car customers as many as 100 respondents. This research is a quantitative study using statistical methods using the IBM SPSS Statistics Version 25 application. Based on the results of statistical tests, it can be seen partially that service quality and price perceptions have a positive and significant impact on customer satisfaction using Grab-Car online taxi transportation services

Design and Implementation of Brain-Based Home Automation System

This paper supports the utilization of EEG signals to control a smart home automation system. The study involves calculating the human brain's attention level using EEG data and subsequently employing this information to operate various devices based on the attention value obtained. The process commences with multichannel EEG recordings, which are then processed using MATLAB software. The first channel (FP1) is isolated from the multichannel EEG data, and subsequent steps involve noise and artifact removal through a bandpass filter ranging from 0.3 to 100 Hz. The Alpha and Beta sub-bands of the EEG data are computed, and the Power Spectral Density is derived from the Alpha and Beta waves. By analyzing the intensities of the Alpha and Beta PSD signals, the subject's attention level is computed and categorized. This attention level indicator is then used to control the operation of smart home electrical devices. The study demonstrates the viability and effectiveness of the proposed EEG-based system for controlling domestic appliances, confirming its successful functionality

Synthesis of 1,2-Dihydro-Substituted Aniline Analogues Involving N-Phenyl-3-aza-Cope Rearrangement Using a Metal-Free Catalytic Approach

An efficient metal-free domino reaction leading to structural/electronically divergent 1,2-dihydropyridines from easily accessible propargyl vinyl anilines via N-phenyl 3-aza-Cope sigmatropic rearrangement is reported with good to excellent yields using 1,2-dichlorobenzene as solvent under thermal conditions. Spirocyclic substitution is also tolerated under the present optimized conditions

Kabul River Flow Prediction Using Automated ARIMA Forecasting: A Machine Learning Approach

The water level in a river defines the nature of flow and is fundamental to flood analysis. Extreme fluctuation in water levels in rivers, such as floods and droughts, are catastrophic in every manner; therefore, forecasting at an early stage would prevent possible disasters and relief efforts could be set up on time. This study aims to digitally model the water level in the Kabul River to prevent and alleviate the effects of any change in water level in this river downstream. This study used a machine learning tool known as the automatic autoregressive integrated moving average for statistical methodological analysis for forecasting the river flow. Based on the hydrological data collected from the water level of Kabul River in Swat, the water levels from 2011–2030 were forecasted, which were based on the lowest value of Akaike Information Criterion as 9.216. It was concluded that the water flow started to increase from the year 2011 till it reached its peak value in the year 2019–2020, and then the water level will maintain its maximum level to 250 cumecs and minimum level to 10 cumecs till 2030. The need for this research is justified as it could prove helpful in establishing guidelines for hydrological designers, the planning and management of water, hydropower engineering projects, as an indicator for weather prediction, and for the people who are greatly dependent on the Kabul River for their survival