Performance Evaluation of Energy Harvesting Method on Intelligent Wearable Travel Aid Device for Blind Person

The intelligent wearable travel aid device has been developed for blind person usage for traveling purposes. The intelligent wearable travel aid device will be used along with the long cane that is usually used to detect any obstructions around the blind person. However, the problem on power supply to supply the electrical energy for the intelligent wearable travel aid device to work properly always been occurred. In order to fit the energy harvesting device on the intelligent wearable travel aid device, the comparison of the solar panel and photodiode is done. The performance evaluation to compare theenergy harvesting method on the developed intelligent wearable travel aid device for blind person has been conductedbased on the experiment result. The photodiode is proposed in this study due to small size and easy to arrange on top of developed wearable travel aid device compared to the solar panel which big size but commonly used as energy harvesting device. Consequently, the experimental result of the intelligent wearable travel aid device in terms of voltage, current and light intensity for the improved version with different type of configuration is proven respectively

The Level of Ischemic Modified Albumin (IMA) as Risk Marker for Cardio Vascular D isease (CVD) among some diabetic patients (type II) in Khartoum state -Sudan

Background. Recent literature reports show large interest in ischemic modified albumin (IMA) biochemical marker for detection of myocardial injury. Special attention is focused in estimation of IMA test for the diagnosis and evaluation of myocardial ischemia as well as others acute coronary syndrome in emergency patients.Objective : evaluation of ischemia-modified albumin (IMA) in well controlled and uncontrolled patients with type 2 diabetes mellitus and estimation of its connection with cardiovascular disease.Measurement thelevelof IMA asrisk marker forcardio vascular disease (CVD) in diabetic patients that arrivedtoemergency department with signs and symptoms of CVD.Methodology. 140 subjects enrolled in thisstudy ,70 diabetes mellitus patients with signs and symptoms of CVD, and other 70 apparently non diabetic healthy subjects' as controls, , the levels of biomarker IMA was measured as the risk marker ofCVDin controlled and uncontrolleddiabeticpatients with type2,the Diagnostic potential was evaluated by receiver operating characteristic analysis and their relationships were analyzed. This study was donein Shab Hospital, Khartoum.Period from 1st of February 2015 to October 2015.Results: The results showed that CVD were predominant among diabetic female 57 % and peaked at age 75.5 years among 40-75 year old. The IMA was significantly increase in diabetic patients when compare with normal healthy group with cut off value ( 0.97 IU/L ), and there is also significantly increase in IMA level in uncontrolled diabetic patients (Mean ± SD; 14.70 + 10.66) that presented with acute chest pain and havea signs and symptoms of cardiac ischemia when compared with the well-controlled diabetic patients(Mean ± SD; 3.74 + 3.68). controlled and uncontrolled diabetic patients were determined by the level of their HBA1c and comparison with the means of IMA level in their serum.Conclusions: increase IMA level in poor control and long stand diabetic patients could help to identify the higher risk for develop to CVD, and The most common complication such as suffering from local or systemic hypoxic conditions, as acute ischemic stroke, peripheral vascular disease.Keywords: Ischemia, Type 2 diabetes mellitus, cardiovascular disease, Ischemic Modified Albumi

The level of Ischemic Modified Albumin (IMA) as risk marker for Cardio Vascular Disease (CVD) among some diabetic patients (type II) in Khartoum State-Sudan

Background: Recent literature reports show large interest in ischemic modified albumin (IMA) biochemical marker for detection of myocardial injury. Special attention is focused in estimation of IMA test for the diagnosis and evaluation of myocardial ischemia as well as others acute coronary syndrome in emergencypatients.Objective: evaluation of ischemia-modified albumin (IMA) in well controlled and uncontrolled patients with type 2 diabetes mellitus and estimation of its connection with cardiovascular disease.Measurement the levelof IMA as risk marker for cardio vascular disease (CVD) in diabetic patients that arrived to emergency department with signs and symptoms of CVD.Methodology: 140 subjects enrolled in this study ,70 diabetes mellitus patients with signs and symptoms of CVD, and other 70 apparently non diabetic healthy subjects’ as controls, , the levels of biomarker IMA was measured as the risk marker of CVDin controlled and uncontrolled diabeticpatients with type2,the Diagnostic potential was evaluated by receiver operating characteristic analysis and their relationships were analyzed. This study was done in Shab Hospital, Khartoum. Period from 1st of February 2015 to October 2015.Results: The results showed that CVD were predominant among diabetic female 57 % and peaked at age 75.5 years among 40-75 year old. The IMA was significantly increase in diabetic patients when compare with normal healthy group with cut off value ( 0.97 IU/L ), and there is also significantly increase in IMA level in uncontrolled diabetic patients (Mean ± SD; 14.70 + 10.66) that presented with acute chest pain and havea signs and symptoms of cardiac ischemia when compared with the wellcontrolled diabetic patients (Mean ± SD; 3.74 ± 3.68). controlled and uncontrolled diabetic patients were determined by the level of their HBA1c and comparison with the means of IMA level in their serum.Conclusions: increase IMA level in poor control and long stand diabetic patients could help to identify the higher risk for develop to CVD, and The most common complication such as suffering from local or systemic hypoxic conditions, as acute ischemic stroke, peripheral vascular disease.Keywords: Ischemia, Type 2 diabetes mellitus, cardiovascular disease, Ischemic Modified Albumi

Transparent, Lightweight, and High Strength Polyethylene Films by a Scalable Continuous Extrusion and Solid-State Drawing Process

The continuous production of transparent high strength ultra-drawn high-density polyethylene films or tapes is explored using a cast film extrusion and solid-state drawing line. Two methodologies are explored to achieve such high strength transparent polyethylene films; i) the use of suitable additives like 2-(2H-benzotriazol-2-yl)-4,6-ditertpentylphenol (BZT) and ii) solid-state drawing at an optimal temperature of 105 °C (without additives). Both methodologies result in highly oriented films of high transparency (≈91%) in the far field. Maximum attainable modulus (≈33 GPa) and tensile strength (≈900 MPa) of both types of solid-state drawn films are similar and are an order of magnitude higher than traditional transparent plastics such as polycarbonate (PC) and poly(methyl methacrylate). Special emphasis is devoted to the effect of draw down and pre-orientation in the as-extruded films prior to solid-state drawing. It is shown that pre-orientation is beneficial in improving mechanical properties of the films at equal draw ratios. However, pre-orientation lowers the maximum attainable draw ratio and as such the ultimate modulus and tensile strength of the films. Potential applications of these high strength transparent flexible films lie in composite laminates, automotive or aircraft glazing, high impact windows, safety glass, and displays

Physical Activity Recognition Based on a Parallel Approach for an Ensemble of Machine Learning and Deep Learning Classifiers

Human activity recognition (HAR) by wearable sensor devices embedded in the Internet of things (IOT) can play a significant role in remote health monitoring and emergency notification, to provide healthcare of higher standards. The purpose of this study is to investigate a human activity recognition method of accrued decision accuracy and speed of execution to be applicable in healthcare. This method classifies wearable sensor acceleration time series data of human movement using efficient classifier combination of feature engineering-based and feature learning-based data representation. Leave-one-subject-out cross-validation of the method with data acquired from 44 subjects wearing a single waist-worn accelerometer on a smart textile, and engaged in a variety of 10 activities, yields an average recognition rate of 90%, performing significantly better than individual classifiers. The method easily accommodates functional and computational parallelization to bring execution time significantly down