EMG Signals Analysis of BF and RF Muscles In Autism Spectrum Disorder (ASD) During Walking

This paper presents the analysis of Electromyography (EMG) signals at lower limb muscles during walking. The muscles of Biceps Femoris (BF) and Rectus Femoris (RF) were examined between ASD and TD children. The EMG signals pattern will be observed over one gait cycle and the statistical analysis will be used to compare the significant difference of two muscles between ASD and TD children. The result shows that there are significant differences in RF muscle for both ASD and TD children at 70% of gait cycle (p value is equal to 0.007) and at 90% of gait cycle (p value is equal to 0.023). From this result, the RF muscle shall be considered as the vital muscle for rehabilitation plan

Sposol: 5 In 1 Smart Portable Solar Light

Smart Portable Solar Light is a project based on a circuit obtained through the internet connection.A few modifications have been done to the original circuit; original circuit uses eight LEDs while this project only uses one main LED.The main source of this system is harvest form the sun.The sun’s radiation is converted to electrical energy that is supplied to a battery,which acts as a power storage for the system.Another set of batteries is used as the structure of the lamp is design to be portable

Application of Long-Short Term Memory for Accurate Biochemical Oxygen Demand Prediction in Rivers through Water Quality Parameters

Evaluating water quality is crucial for preserving the quality of river water. However, the typical technique of getting biochemical oxygen demand (BOD) values via laboratory testing might take several days, delaying the application of real-time measurement to improve water quality. This paper suggests using machine learning to predict BOD values from eight water quality measurements. The BOD rate in the Klang River, Selangor, Malaysia, was estimated using the long short-term memory (LSTM) method. The model was trained using historical data collected from eleven water collection points along the river. The predictive test results indicated that the LSTM model with 8 water parameters as input gave the most accurate predictions compared to the models with 5 and 3 water parameters. The results of this study indicate that machine learning methods can be used to predict BOD levels in real-time. It enables water quality managers to enhance water quality and safeguard human health proactively

Design A Simple Solar Tracker For Hybrid Power Supply

This paper presents a smart power supply by using solar energy as the sources.It reduces the use of fuel in order to achieve maximize generation of electricity (during day time).The project equipped with solar tracker device which is absorbs the ultraviolet (UV) from the sun in maximum condition.The tracker operates with dual axis rotation where it can be rotating with 360° or which is 180° vertical/horizontals.This circuit is activated when light dependent resistor (LDR) detecting the light where four sensors are placed at east,west,north and south position.The solar panel is embedded with gear system to control the speed of the tracker and also obtain full charge of the 12V rechargeable lead acid battery