A Novel Real-Time Non-invasive Hemoglobin Level Detection Using Video Images from Smartphone Camera

Hemoglobin level detection is necessary for evaluating health condition in the human. In the laboratory setting, it is detected by shining light through a small volume of blood and using a colorimetric electronic particle counting algorithm. This invasive process requires time, blood specimens, laboratory equipment, and facilities. There are also many studies on non-invasive hemoglobin level detection. Existing solutions are expensive and require buying additional devices. In this paper, we present a smartphone-based non-invasive hemoglobin detection method. It uses the video images collected from the fingertip of a person. We hypothesized that there is a significant relation between the fingertip mini-video images and the hemoglobin level by laboratory gold standard. We also discussed other non-invasive methods and compared with our model. Finally, we described our findings and discussed future works

Right for the Right Reason: Training Agnostic Networks

We consider the problem of a neural network being requested to classify images (or other inputs) without making implicit use of a "protected concept", that is a concept that should not play any role in the decision of the network. Typically these concepts include information such as gender or race, or other contextual information such as image backgrounds that might be implicitly reflected in unknown correlations with other variables, making it insufficient to simply remove them from the input features. In other words, making accurate predictions is not good enough if those predictions rely on information that should not be used: predictive performance is not the only important metric for learning systems. We apply a method developed in the context of domain adaptation to address this problem of "being right for the right reason", where we request a classifier to make a decision in a way that is entirely 'agnostic' to a given protected concept (e.g. gender, race, background etc.), even if this could be implicitly reflected in other attributes via unknown correlations. After defining the concept of an 'agnostic model', we demonstrate how the Domain-Adversarial Neural Network can remove unwanted information from a model using a gradient reversal layer.Comment: Author's original versio

Experimental study to determine the effect of wire mesh pore size on natural draft chimney performance

Chimney is an important part of the industries to remove waste heat from the processes side to the atmosphere. The increased demand of energy helps to restart to think about the efficiency of chimney as well as to find out a valid option to replace forced draft chimney system from industries. In this study natural draft chimney model is air flow rate; exit air temperature and pressure losses are studied through modification with wire mesh screen and compare the results with without wire mesh screen chimney model. The heat load is varies from 0.1 kW to 1kW and three different wire mesh screens that have pore size 0.15 mm2, 0.40 mm2 and 4.0 mm2 respectively are used. The experimental results show that natural draft chimney model with wire mesh screens significantly restored the flow losses compared to the system without wire mesh screen. The natural draft chimney model with 0.40 mm2 pore size wire mesh screen can minimize the draft losses better than others and able to enhance velocity about 54 % exit air temperature about 41% and pressure loss decreased by about 20%. Therefore, it can be decided that the wire mesh screens significantly minimize the draft losses in the natural draft chimney and 0.40 mm2 pore size screen will be a suitable optio

A chimney of low height to diameter ratio for solar crops dryer

Sabah, Malaysia is rich with solar energy where the daily mean daylight is the for is available for 4–8h. The sunlight can be used effectively in a suitable solar crops drying system. Solar crops dryer with mechanical system is an efficient and suitable option for crops drying. Mechanical system can be replaced with a modified chimney and a conceptual design is proposed. Previously, in the laboratory, a number of experiments had been conducted by using conventional chimney and modified chimney with four different heat loads varied from 1 to 2.5kW and also for different chimney heights varying from 0.3 to 1.2m as well as three different types of chimney model with face areas of 0.56, 1.00, and 2.25m2. It had been found that the modified chimney significantly reduced the effect of flow reversal or cold inflow and restored the loss in flow rate. The current study using computational fluid dynamics (CFD) managed to show draft enhancement by the modified chimney and revealed the pressure prior to exit to be higher than ambient compared with the lower pressure in normal chimney, indicating vulnerability of normal chimneys to flow reversal but positive prevention in a modified chimney

Automatic interpretation of unordered point cloud data for UAV navigation in construction

© 2016 IEEE. The objective of this work is to develop a data processing system that can automatically generate waypoints for navigation of an unmanned aerial vehicle (UAV) to inspect surfaces of structures like buildings and bridges. The input includes data recorded by two 2D laser scanners, orthogonally mounted on the UAV, and an inertial measurement unit (IMU). To achieve the goal, algorithms are developed to process the data collected. They are separated into three major groups: (i) the data registration and filtering to generate a 3D model of the structure and control the density of point clouds for data completeness enhancement; (ii) the surface and obstacle detection to assist the UAV in monitoring tasks; and (iii) the waypoint generation to set the flight path. Experiments on different data sets show that the developed system is able to reconstruct a 3D point cloud of the structure, extract its surfaces and objects, and generate waypoints for the UAV to accomplish inspection tasks

Challenges in Developing Applications for Aging Populations

Elderly individuals can greatly benefit from the use of computer applications, which can assist in monitoring health conditions, staying in contact with friends and family, and even learning new things. However, developing accessible applications for an elderly user can be a daunting task for developers. Since the advent of the personal computer, the benefits and challenges of developing applications for older adults have been a hot topic of discussion. In this chapter, the authors discuss the various challenges developers who wish to create applications for the elderly computer user face, including age-related impairments, generational differences in computer use, and the hardware constraints mobile devices pose for application developers. Although these challenges are concerning, each can be overcome after being properly identified

Realization of SOC behavior in a dc glow discharge plasma

Experimental observations consistent with Self Organized Criticality (SOC) have been obtained in the electrostatic floating potential fluctuations of a dc glow discharge plasma. Power spectrum exhibits a power law which is compatible with the requirement for SOC systems. Also the estimated value of the Hurst exponent (self similarity parameter), H being greater than 0.5, along with an algebraic decay of the autocorrelation function, indicate the presence of temporal long-range correlations, as may be expected from SOC dynamics. This type of observations in our opinion has been reported for the first time in a glow discharge system.Comment: Key Words: Glow discharge; Self Organized Criticality; Hurst exponent; R/S technique; Power spectrum; Autocorrelation function; Nongaussian probability distribution function. Phys Lett A (article in Press