Assessment of Wireless Technologies for deployment in Intelligent Transportation System based on Internet of Things

Use of Internet of Things (IoT) with modern wireless network is a trend of the emerging technologies for different systems which can be deployed in various kinds of environment to monitor, communicate with or control the associated elements in the system. The activities e.g., monitoring and communication by IoT can play an important role to design an Intelligent Transportation System (ITS). In this paper, we assess the suitability of IoT enabled wireless technology to be used for ITS. We performed some comparative study to find the best wireless technology that provides reliability, low cost, less power consumption and less data latency for next generation ITS.This technology will reduce energy consumption of the deployed IoT devices as well as ensure safety, efficiency and convenient for transportation systems

SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network

Blood hemoglobin level (Hgb) measurement has a vital role in the diagnosis, evaluation, and management of numerous diseases. We describe the use of smartphone video imaging and an artificial neural network (ANN) system to estimate Hgb levels non-invasively. We recorded 10 second-300 frame fingertip videos using a smartphone in 75 adults. Red, green, and blue pixel intensities were estimated for each of 100 area blocks in each frame and the patterns across the 300 frames were described. ANN was then used to develop a model using the extracted video features to predict hemoglobin levels. In our study sample, with patients 20-56 years of age, and gold standard hemoglobin levels of 7.6 to 13.5 g/dL., we observed a 0.93 rank order of correlation between model and gold standard hemoglobin levels. Moreover, we identified specific regions of interest in the video images which reduced the required feature space

e-ESAS: Evolution of a Participatory Design-based Solution for Breast Cancer (BC) Patients in Rural Bangladesh

Healthcare facility is scarce for rural women in the developing world. The situation is worse for patients who are suffering from diseases that require long-term feedback-oriented monitoring such as breast cancer. Lack of motivation to go to the health centers on patients’ side due to sociocultural barriers, financial restrictions and transportation hazards results in inadequate data for proper assessment. Fortunately, mobile phones have penetrated the masses even in rural communities of the developing countries. In this scenario, a mobile phone-based remote symptom monitoring system (RSMS) with inspirational videos can serve the purpose of both patients and doctors. Here, we present the findings of our field study conducted on 39 breast cancer patients in rural Bangladesh. Based on the results of extensive field studies, we have categorized the challenges faced by patients in different phases of the treatment process. As a solution, we have designed, developed and deployed e-ESAS—the first mobile-based RSMS in rural context. Along with the detail need assessment of such a system, we describe the evolution of e-ESAS and the deployment results. We have included the unique and useful design lessons that we learned as e-ESAS evolved through participatory design process. The findings show how e-ESAS addresses several challenges faced by patients and doctors and positively impact their lives

A 3D-collaborative wireless network: towards resilient communication for rescuing flood victims

Every year, floods result in huge damage and devastation both to lives and properties all over the world. Much of this devastation and its prolonged effects result from a lack of collaboration among the rescue agents as a consequence of the lack of reliable and resilient communication platform in the disrupted and damaged environments. In order to counteract this issue, this paper aims to propose a three-dimensional (3D)- collaborative wireless network utilizing air, water and ground based communication infrastructures to support rescue missions in flood-affected areas. Through simulated Search and Rescue(SAR) activities, the effectiveness of the proposed network model is validated and its superiority over the traditional SAR is demonstrated, particularly in the harsh flood environments. The model of the 3D-Collaborative wireless network is expected to significantly assist the rescuing teams in accomplishing their task more effectively in the corresponding disaster areas

Mother’s dietary diversity and association with stunting among children <2 years old in a low socio‐economic environment: A case–control study in an urban care setting in Dhaka, Bangladesh

Mothers are often responsible for preparing nutritious foods in their households. However, the quality of mother’s diets is often neglected, which may affect both mother’s and child’s nutrition. Because no single food contains all necessary nutrients, diversity in dietary sources is needed to ensure a quality diet. We aimed to study the association between mother’s dietary diversity and stunting in children <2 years attending Dhaka Hospital of icddr,b, a diarrhoeal disease hospital in Dhaka, Bangladesh. A case–control study (n = 296) was conducted from November 2016 to February 2017. Data were collected from mothers of stunted children <2 years (length‐for‐age z score [LAZ] < −2) as “cases” and nonstunted (LAZ ≥ −1) children <2 years as “controls.” Mothers were asked to recall consumption of 10 defined food groups 24 hr prior to the interview as per Guidelines for Minimum Dietary Diversity for Women. Among the mothers of cases, 58% consumed <5 food groups during the last 24 hr, compared with 45% in control mothers (P = 0.03). Children whose mothers consumed <5 food groups were 1.7 times more likely to be stunted than children whose mothers consumed ≥5 food groups (P = 0.04). Intake of food groups such as pulses, dairy, eggs, and vitamin A rich fruit was higher in control mothers. Proportion of mother’s illiteracy, short stature, monthly family income <BDT 11,480, absence of bank account, and poor sanitation was also found to be higher in stunted group. Further study particularly intervention or longitudinal study to see the causality of mother’s dietary diversity with child stunting is recommended.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148421/1/mcn12665.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148421/2/mcn12665_am.pd

Applications of artificial neural networks in engine cooling system

Artificial neural network (ANN) is a powerful method for nonlinear regression, classification, object detection, and clustering and is widely used in thermal analysis of the cooling system. Cooling system is an invaluable part of removing waste heat from an internal combustion engine. A few decades ago, the engine cooling system became more advanced for developing a higher-performance engine. To enhance the engine cooling system, ANN is a promising method. In this context, this paper presents a brief survey, which reviews the ANN-based engine cooling system. For this purpose, we describe the different types of ANNs which are pertinent to engine cooling systems. Different evaluation metrics which are used to evaluate the performance of ANN in engine cooling systems, as well as the activation functions and modelling of ANN, are also introduced in this paper. Furthermore, the basics of engine cooling systems and different applications of ANN in cooling systems are described briefly. Finally, some limitations of ANN and future research scope are also presented here

An overview of effect of activation functions on training and performance of artificial neural network modelling

This paper presents an overview of the effect of the activation functions on the training and performance of artificial neural network modelling. An artificial neural network's activation functions are mathematical formulas that are essential to its design. Activation functions are a critical component of artificial neural networks since they impact the performance of the ANN model to a considerable extent. It is a function that is utilized in order to obtain the output of the node. In an artificial neural network, defining an activation function is critical, as it directly affects the network's success rate. A concise summary of some of the most frequent activation functions that are utilized in neural networks. Activation functions are defined, their properties are compared, and their advantages and disadvantages are described in this paper. This review is provided with the definitions, features, performance comparisons, merits and demerits and applications of activation function in various areas. The activation function has an impact on the development of ANN models. It is found that sigmoid, Tanh and ReLU are the most used activation function and give better performance compared to others

Modeling lung functionality in volume-controlled ventilation for critical care patients

Mechanical ventilators are the instruments that assist breathing of the patients having respiratory diseases e.g., pneumonia and coronavirus disease 2019 (COVID-19). This paper presents a modified lung model under volume-controlled ventilation to describe the lung volume and air flow in terms of air pressure signal from the ventilator. A negative feedback is incorporated in the model to balance the lung volume that is influenced by a lung parameter called positive end expiration pressure. We partially solved the lung model equation which takes the form of a first-order differential equation and then unknown parameters associated with the model were computed using a nonlinear least-squares method. Experimental data required for parameter identification and validation of the lung model were obtained by running a volume-controlled ventilator connected to a reference device and an artificial lung. The proposed model considering negative feedback achieves a better accuracy than that without feedback as demonstrated by test results. The developed model can be used in intensive care units (ICU) to evaluate mechanical ventilation performance and lung functionality in real-time

Shonjibon cash and counselling : a community-based cluster randomised controlled trial to measure the effectiveness of unconditional cash transfers and mobile behaviour change communications to reduce child undernutrition in rural Bangladesh

Background: Undernutrition is strongly associated with poverty - levels of undernutrition are higher in poor countries than in better-off countries. Social protection especially cash transfer is increasingly recognized as an important strategy to accelerate progress in improving maternal and child nutrition. A critical method to improve nutrition knowledge and influence feeding practices is through behaviour change communication intervention. The Shonjibon Cash and Counselling study aims to assess the effectiveness of unconditional cash transfers combined with a mobile application on nutrition counselling and direct counselling through mobile phone in reducing the prevalence of stunting in children at 18 months. Method: The study is a longitudinal cluster randomised controlled trial, with two parallel groups, and cluster assignment by groups of villages. The cohort of mother-child dyads will be followed-up over the intervention period of approximately 24 months, starting from recruitment to 18 months of the child’s age. The study will take place in north-central Bangladesh. The primary trial outcome will be the percentage of stunted children at 18 m as measured in follow up assessments starting from birth. The secondary trial outcomes will include differences between treatment arms in (1) Mean birthweight, percentage with low birthweight and small for gestational age (2) Mean child length-for age, weight for age and weight-for-length Z scores (3) Prevalence of child wasting (4) Percentage of women exclusively breastfeeding and mean duration of exclusive breastfeeding (5) Percentage of children consuming > 4 food groups (6) Mean child intake of energy, protein, carbohydrate, fat and micronutrients (7) Percentage of women at risk of inadequate nutrient intakes in all three trimesters (8) Maternal weight gain (9) Household food security (10) Number of events for child suffering from diarrhoea, acute respiratory illness and fever (11) Average costs of mobile phone BCC and cash transfer, and benefit-cost ratio for primary and secondary outcomes. Discussion: The proposed trial will provide high-level evidence of the efficacy and cost-effectiveness of mobile phone nutrition behavior change communication, combined with unconditional cash transfers in reducing child undernutrition in rural Bangladesh. Trial registration: The study has been registered in the Australian New Zealand Clinical Trials Registry (ACTRN12618001975280)