Search results for: body area networks

Authors: Lopita Pal, Suresh V. Madha

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Wetlands are areas of marsh, fen, peat land or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six metres. The rapidly expanding human population, large scale changes in land use/land cover, burgeoning development projects and improper use of watersheds all has caused a substantial decline of wetland resources in the world. Major degradations have been impacted from agricultural, industrial and urban developments leading to various types of pollutions and hydrological perturbations. Regular fishing activities and unsustainable grazing of animals are degrading the wetlands in a slow pace. The paper focuses on the spatio-temporal change detection of the area of the water body and the main cause of this depletion. The total area under study (22°19’87’’ N, 88°20’23’’ E) is a wetland region in West Bengal of 213 sq.km. The procedure used is the Normalized Difference Water Index (NDWI) from multi-spectral imagery and Landsat to detect the presence of surface water, and the datasets have been compared of the years 2016, 2006 and 1996. The result shows a sharp decline in the area of water body due to a rapid increase in the agricultural practices and the growing urbanization.

Keywords: spatio-temporal change, NDWI, urbanization, wetland

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Authors: Dimitra Alexiou

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In an urban area the allocation placement of an emergency service mobile units, such as ambulances, police patrol must be designed so as to achieve a prompt response to demand locations. In this paper, a partition of a given urban network into distinct sub-networks is performed such that; the vertices in each component are close and simultaneously the difference of the sums of the corresponding population in the sub-networks is almost uniform. The objective here is to position appropriately in each sub-network a mobile emergency unit in order to reduce the response time to the demands. A mathematical model in the framework of graph theory is developed. In order to clarify the corresponding method a relevant numerical example is presented on a small network.

Keywords: graph partition, emergency service, distances, location

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Authors: P. Strakos, M. Jaros, T. Karasek, T. Kozubek, P. Vavra, T. Jonszta

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In medical imaging, segmentation of different areas of human body like bones, organs, tissues, etc. is an important issue. Image segmentation allows isolating the object of interest for further processing that can lead for example to 3D model reconstruction of whole organs. Difficulty of this procedure varies from trivial for bones to quite difficult for organs like liver. The liver is being considered as one of the most difficult human body organ to segment. It is mainly for its complexity, shape versatility and proximity of other organs and tissues. Due to this facts usually substantial user effort has to be applied to obtain satisfactory results of the image segmentation. Process of image segmentation then deteriorates from automatic or semi-automatic to fairly manual one. In this paper, overview of selected available software applications that can handle semi-automatic image segmentation with further 3D volume reconstruction of human liver is presented. The applications are being evaluated based on the segmentation results of several consecutive DICOM images covering the abdominal area of the human body.

Keywords: image segmentation, semi-automatic, software, 3D volumetric reconstruction

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Authors: Shaimaa M. Mohamed, Haitham S. Hamza, Imane A. Saroit

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Many wireless sensor network applications require K-coverage of the monitored area. In this paper, we propose a scalable harmony search based algorithm in terms of execution time, K-Coverage Enhancement Algorithm (KCEA), it attempts to enhance initial coverage, and achieve the required K-coverage degree for a specific application efficiently. Simulation results show that the proposed algorithm achieves coverage improvement of 5.34% compared to K-Coverage Rate Deployment (K-CRD), which achieves 1.31% when deploying one additional sensor. Moreover, the proposed algorithm is more time efficient.

Keywords: Wireless Sensor Networks (WSN), harmony search algorithms, K-Coverage, Mobile WSN

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Authors: A.L. Tamm, N. Šott, J. Jürimäe, E. Lätt, A. Orav, Ü. Parm

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Coffee is one of the most frequently consumed beverages in the world but still its effects on human organism are not completely understood. Coffee has also been used as a method for weight loss, but its effectiveness has not been proved. There is also not similar comprehension in classifying overweight in choosing between body mass index (BMI) and fat percentage (fat%). The aim of the study was to determine associations between coffee consumption and body composition. Secondly, to detect which measure (BMI or fat%) is more accurate to use describing overweight. Altogether 103 persons enrolled the study and divided into three groups: coffee non-consumers (n=39), average coffee drinkers, who consumed 1 to 4 cups (1 cup = ca 200ml) of coffee per day (n=40) and excessive coffee consumers, who drank at least five cups of coffee per day (n=24). Body mass (medical electronic scale, A&D Instruments, Abingdon, UK) and height (Martin metal anthropometer to the nearest 0.1 cm) were measured and BMI calculated (kg/m2). Participants´ body composition was detected with dual energy X-ray absorptiometry (DXA, Hologic) and general data (history of chronic diseases included) and information about coffee consumption, and physical activity level was collected with questionnaires. Results of the study showed that excessive coffee consumption was associated with increased fat-free mass. It could be foremost due to greater physical activity level in school time or greater (not significant) male proportion in excessive coffee consumers group. For estimating the overweight the fat% in comparison to BMI recommended, as it gives more accurate results evaluating chronical disease risks. In conclusion coffee consumption probably does not affect body composition and for estimating the body composition fat% seems to be more accurate compared with BMI.

Keywords: body composition, body fat percentage, body mass index, coffee consumption

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Authors: M. Bolacalı, Y. Öztürk, O. Yılmaz, M. Küçük, M. A. Karslı

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The aim of the study was to determine various body measurements from the birth to the 30-day age of Boer x Hair goats F1 crossbred kids and pure Hair goat kids raised in Van in Eastern Anatolia region, and reveal factors such as the effects of year, dame body weight, genotype, dame age, birth type and sex on this parameter. 49 kids born in 2012 and 76 kids born in 2014 were utilized in the study. In the statistical analysis of various body measurements data was performed using the General Lineer Model procedure in SPSS software. Duncan's multiple range test was used for multiple comparisons. Boer x Hair goats F1 crossbred kids and pure Hair goat kids from various body measurements cidago height, body length, chest length, chest depth, chest circumference, circumference of leg, cannon bone circumference, chest width were determinated in general respectively 29.90 and 27.88 cm; 29.49 and 27.93 cm; 17.28 and 16.68 cm; 13.34 and 12.82 cm; 31.74 and 29.85 cm; 28.43 and 23.95 cm; 5.41 and 5.15 cm; 8.71 and 7.63 cm at birth, respectively; 35.01 and 32.98 cm; 35.20 and 33.30 cm; 18.82 and 18.17 cm; 15.64 and 14.83 cm; 39.08 and 37.30 cm; 34.29 and 29.25 cm; 5.80 and 5.42 cm; 9.87 and 8.85 cm at 30 days age, respectively. Among factors affecting cidago height in this study, the effect of dame body weight and sex were not significant, but genotype, dame age and birth type were significant (P < 0,05 and P < 0,01) at birth; dame body weight effect of the cidago height was not significant, but the effect of genotype, birth type, of dame age and sex were significant (P < 0.05, P < 0.05 and P<0.001) at 30-day age. The effect of genotype and sex of body length were not significant, but dam age, dame body weight and birth type were significant (P < 0.05, P < 0.05 and P<0.001, respectively) at birth; the effect of sex to body length was not significant, but genotype, dame age, dame body weight and birth type were significant (P < 0.01, P < 0.05, P < 0.05 and P < 0.001, respectively) at 30-day age. While circumference of leg was insignificant the effect of dame age and sex, genotype, dame body weight and type of the birth were significant (P < 0.001, P < 0.05 and P < 0.001) at birth; the circumstance of leg at 30-day age was found to be important the effect of examined other factors except for sex (P < 0.05 and P < 0.001). The obtained results, when considered in terms of a variety of body sizes, from birth to 30-day age growth period, showed that the kids of Boer x Hair Goat F1 hybrids have higher values than the kids of Hair Goats.

Keywords: Boer x hair goat F1 crossbred, hair goat, body measurements, cidago height

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Authors: A. Grilec, S. Petrak, M. Mahnic Naglic

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Technological development and the globalization in production and sales of clothing in the last decade have significantly influenced the changes in consumer relationship with the industrial-fashioned apparel and in the way of clothing purchasing. The Internet sale of clothing is in a constant and significant increase in the global market, but the possibilities offered by modern computing technologies in the customization segment are not yet fully involved, especially according to the individual customer requirements and body sizes. Considering the growing trend of online shopping, the main goal of this paper is to investigate the differences in customer perceptions towards online apparel shopping and particularly to discover the main differences in perceptions between customers regarding three different body sizes. In order to complete the research goal, the quantitative study on the sample of 85 Croatian consumers was conducted in 2017 in Zagreb, Croatia. Respondents were asked to indicate their level of agreement according to a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5). To analyze attitudes of respondents, simple and descriptive statistics were used. The main findings highlight the differences in respondent perception of 3D body scanning, using 3D body scanning in Internet shopping, online apparel shopping habits regarding their body sizes.

Keywords: consumer behavior, Internet, 3D body scanning, body types

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Authors: Kelsey Scanlon

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Introduction: With the rate of female collegiate and professional athletes on the rise in recent decades, fluctuations in physical performance in relation to the menstrual cycle is an important area of study. PURPOSE: The purpose of this research was to compare differences in upper and lower body maximal anaerobic capacities across a single menstrual cycle. Methode: Participants (n=11) met a total of four times; once for familiarization and again on day 1 of menses (follicular phase), day 14 (ovulation), and day 21 (luteal phase) respectively. Upper body power was assessed using a bench press weight of ~50% of the participant’s predetermined 1-repetition maximum (1-RM) on a ballistic measurement system and variables included peak force (N), mean force (N), peak power (W), mean power (W), and peak velocity (m/s). Lower body power output was collected using a standard Wingate test. The variables of interest were anaerobic capacity (w/kg), peak power (W), mean power (W), fatigue index (W/s), and total work (J). Result: Statistical significance was not observed (p > 0.05) in any of the aforementioned variables after completing multiple one ways of analyses of variances (ANOVAs) with repeated measures on time. Conclusion: Within the parameters of this research, neither female upper nor lower body power output differed across the menstrual cycle when analyzed using 50% of one repetition (1RM) maximal bench press and the 30-second maximal effort cycle ergometer Wingate test. Therefore, researchers should not alter their subject populations due to the incorrect assumption that power output may be influenced by the menstrual cycle.

Keywords: anaerobic, athlete, female, power

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Authors: Maitreyee Datta

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In Anātmalaksana Sutra, Buddha talks about the importance of anattā (no-self). This notion of no-self is a critical response towards the Brahmanical tradition of classical India in which self has been taken to be eternal. Though self is taken to be eternal, ‘I’ refer to Person who is the self as determined by non-eternal body. Buddha raises questions regarding the possibility of the association between eternal self and non-eternal body. According to him, such an association is not possible. Thus, instead of an eternal self and its association with the non-eternal body, he speaks about association among five different non-eternal parts (skandhas). He holds that ‘I’ refers to Person, but this Person is not eternal self as determined by the non-eternal body. It is the combination of five different skandhas each of which is non-eternal. So according to Buddha, there is no eternal self which in association with non-eternal body is referred to as ‘I,’ but ‘I’ is a convenient designator which designates the combination of five non-eternal skandhas. If ‘I’ is taken to refer the combination of five non-eternal skandhas, then the problematic of the association between eternal self (attā) and non-eternal body will not be there. The realization that ‘I’ does not refer to any eternal self as determined by non-eternal body, but instead refer to the combination of five non-eternal skandhas leads to the cessation of suffering (duhkkha). The root of suffering lies in craving for something or the other. Thus, as soon as one realizes that the person is not constituted of any eternal self but is constituted of non-eternal skandhas, his desire to acquire and possess will be stopped. Thus, in the whole conceptual framework of Buddhist philosophy, anattā occupies a pivotal role the realization of which is admitted to be the cause of the cessation of suffering. In the present paper, an effort will be made to analyse this notion of anattā to show how the realization of the truth that person is a combination of five skandhas each of which is non-eternal helps an individual to get rid of the bondage. If eternal self is to be admitted, then there always remains the problem of connecting the eternal self with the non-eternal body, because this connection only gives rise to the notion of person in such framework.

Keywords: anatta, atta, duhkkha, skandha

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: Lauren Currell, Gemma Hurst

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Introduction: The present study experimentally investigated the impact of attractive Instagram images on female’s body image. It also examined whether physical appearance perfectionism and cognitive coping predicted body image following upward comparisons to idealised bodies on Instagram. Methods: One-hundred and fifty-eight females (mean age 24.35 years) were randomly assigned to an experimental (where they compared their bodies to those of Instagram models) or control condition (where they critiqued landscape painting). All participants completed measures on physical appearance perfectionism, cognitive coping, and pre- and post-measures of body image. Results: Comparing one’s body to idealised bodies on Instagram resulted in increased appearance and weight dissatisfaction and decreased confidence, compared to the control condition. Physical appearance perfectionism and cognitive coping both predicted body image outcomes for the experimental condition. Discussion: Clinical implications, such as the prevention and treatment of body dissatisfaction, are discussed. Strengths and limitations of the current study are also noted, and suggestions for future research are provided.

Keywords: perfectionism, cognitive coping, body image, social media

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Authors: Hosseini Siahi Zohreh, Sana Mohammad Jafar

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With increase in fat and over weight in children and its undesirable effects on different organisms of the body and since many of the sicknesses are due to over weight and with losing weight these sicknesses disappear, and on the other hand with mal nutrition and under weight in children other kind of sicknesses such as derogation of body's security system, frequent infection, insufficient growth, shortness, and delay in maturity etc. are some of the signs of being under weight. Therefore recognition of signs of over weight and under weight and their prevalence in children are important. To determine this difficulty we have used the body mass index as screening tool since it is very prevalent and a good and important guide and has very good relation with body fat in children. In this study 2321 students from primary schools in Behbahan have been chosen randomly and evaluated by height and weight and their body mass index have been calculated and then recorded on the BMI percentile diagram which is for age and gender. The following results obtained: The amount of total fat, over weight and slimness are 9.3, 12.1 and 12.32 percent respectively. Therefore 21.4% of the children were over weighted. It did not show any meaningful statistical relation in fat conditions among boys and girls, but there has been a meaningful statistical relation in slimness among boys and girls.

Keywords: assessment, students, Behbahan, Body Mass Index

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Authors: Dumith Kulasekara

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This paper examines the representation of the body that particularly stresses the anatomical organs and the psychic conditions in contemporary art. The paper looks closely at the works that address personal and social meanings implying psychic conditions by bringing the internal hidden anatomical organs of the body to the surface of the visual language. The paper argues that contemporary artists conceptualize the idea of the body as a site of generating psychic conditions by excavating the body as material, subject, and object in art practice. The paper conceptualizes this excavating process of the body acts similarly to the idea of dissecting the corporeal body to understand its internal organism that again shapes the materiality of the surface of the body. In doing so, the paper brings together this argument, knowledge produced in the historical and contemporary anatomical education in art and science, and psychoanalytical approaches to the theme to develop new interpretations of representing psyche in the anatomical-bodied. The present paper defines this new form of body conceptually and materially addresses the issues related to psychic conditions: sexual desires, gender, traumas, and memories. The paper suggests that representation of the anatomical-bodied brings a new direction of the multidisciplinary approach introduced by artists to visualize the body and psyche in the contemporary context. The paper also presents an in-depth- discussion on technological, scientific, and philosophical knowledge employed in representing the idea of the body in addressing different psychic conditions to challenge the experiencing the body in contemporary art. Therefore, the paper focuses on examining the theme in the different forms of visual language and contexts in contemporary art. Finally, this research aims to offer a theoretical and conceptual background to curate an exhibition on the title of the anatomical-bodied and psyche in contemporary art with the body of work discussed in this paper.

Keywords: anatomy, body, contemporary art, psyche, psychoanalysis, representation, trauma

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Authors: Nantakrit Yodpijit, Teppakorn Sittiwanchai

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The number of older adults is rising rapidly. The world’s population becomes aging. Falls is one of common and major health problems in the elderly. Falls may lead to acute and chronic injuries and deaths. The fall-prone individuals are at greater risk for decreased quality of life, lowered productivity and poverty, social problems, and additional health problems. A number of studies on falls prevention using fall detection system have been conducted. Many available technologies for fall detection system are laboratory-based and can incur substantial costs for falls prevention. The utilization of alternative technologies can potentially reduce costs. This paper presents the new design and development of a wearable-based fall detection system using an Accelerometer and Gyroscope as motion sensors for the detection of body orientation and movement. Algorithms are developed to differentiate between Activities of Daily Living (ADL) and falls by comparing Threshold-based values with Artificial Neural Networks (ANN). Results indicate the possibility of using the new threshold-based method with neural network algorithm to reduce the number of false positive (false alarm) and improve the accuracy of fall detection system.

Keywords: aging, algorithm, artificial neural networks (ANN), fall detection system, motion sensorsthreshold

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Authors: Putri Alya Ramadhani

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This research analysed how women writers represent their beauty in a platform called Magdalene. With the vision “Supporting diversity, empowering minds,” Magdalene is a new media that seeks to represent women's voices rarely heard in mainstream media. This research elaborates further on how women writers, through their writing, use their body politic to subvert patriarchal values. This research used a qualitative method with an explorative design by using text analysis based on the representation theory of Stuart Hall and in-dept-interview with Women Writers in Magdalene. The result illustrated that women writers represent their beauty in Magdalene to subvert body and beauty-representation in mainstream discourse. Furthermore, the authors have identified an identity negotiation as tension from inevitable oppression and power towards and from women’s bodies. In addition, Women Writers showed the power of their bodies through the redefinition of beauty practices and self. Hence, they subvert body dichotomy to redefine body values in society. In conclusion, this study shows various representations of beauty and body that are underrepresented in the mainstream media through the innovative new medium, Magdalena.

Keywords: women writers, beauty-representation, body politic, new media, identity negotiation

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Authors: Aicha Koulou, Norelislam El Hami, Nabil Hmina

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This paper aims at presenting basic concepts and principles in order to develop a methodology to set up sustainable interoperability within collaborative networks. Definitions and clarifications related to the concept of interoperability and sustainability are given. Interoperability levels and cycle that are components supporting the methodology are presented; a structured approach and related phases are proposed.

Keywords: Interoperability, sustainability, collaborative networks, sustainable Interoperability

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: S. Mousavian, A. Abedianpour, A. Khanmohammadi, S. Hematian, Gh. Eidi Veisi

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Ionic liquids are finding a wide range of applications from reaction media to separations and materials processing. In these applications, Vapor–Liquid equilibrium (VLE) is the most important one. VLE for six systems at 353 K and activity coefficients at infinite dilution 〖(γ〗_i^∞) for various solutes (alkanes, alkenes, cycloalkanes, cycloalkenes, aromatics, alcohols, ketones, esters, ethers, and water) in the ionic liquids (1-ethyl-3-methylimidazolium bis (trifluoromethylsulfonyl)imide [EMIM][BTI], 1-hexyl-3-methyl imidazolium bis (trifluoromethylsulfonyl) imide [HMIM][BTI], 1-octyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide [OMIM][BTI], and 1-butyl-1-methylpyrrolidinium bis (trifluoromethylsulfonyl) imide [BMPYR][BTI]) have been used to train neural networks in the temperature range from (303 to 333) K. Densities of the ionic liquids, Hildebrant constant of substances, and temperature were selected as input of neural networks. The networks with different hidden layers were examined. Networks with seven neurons in one hidden layer have minimum error and good agreement with experimental data.

Keywords: ionic liquid, neural networks, VLE, dilute solution

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Authors: Mhaned Oubounyt, Jan Baumbach

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Differences in co-expression networks between two or multiple cells (sub)types across conditions is a pressing problem in single-cell RNA sequencing (scRNA-seq). A key challenge is to define those co-variations that differ between or among cell types and/or conditions and phenotypes to examine small regulatory networks that can explain mechanistic differences. To this end, we developed SCANet, an all-in-one Python package that uses state-of-the-art algorithms to facilitate the workflow of a combined single-cell GCN (Gene Correlation Network) and GRN (Gene Regulatory Networks) pipeline, including inference of gene co-expression modules from scRNA-seq, followed by trait and cell type associations, hub gene detection, co-regulatory networks, and drug-gene interactions. In an example case, we illustrate how SCANet can be applied to identify regulatory drivers behind a cytokine storm associated with mortality in patients with acute respiratory illness. SCANet is available as a free, open-source, and user-friendly Python package that can be easily integrated into systems biology pipelines.

Keywords: single-cell, co-expression networks, drug-gene interactions, co-regulatory networks

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Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

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Authors: Mohammad Yahaghifar

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Nowadays Wireless system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications. Evolving future communication network generation cellular wireless networks are envisioned to overcome the fundamental challenges of existing cellular networks, for example, higher data rates, excellent end-to-end performance, and user coverage in hot-spots and crowded areas with lower latency,energy consumption and cost per information transfer. In this paper we propose a potential cellular architecture that separates indoor and outdoor scenarios and discuss various promising technologies for future wireless communication systemssystems, such as massive MIMO, energy-efficient communications,cognitive radio networks, and visible light communications and we disscuse about 5G that is next generation of wireless networks.

Keywords: future challenges in networks, cellur architecture, visible light communication, 5G wireless technologies, spatial modulation, massiva mimo, cognitive radio network, green communications

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Authors: Makan Cheraghpour, Seyed Ahmad Hosseini, Damoon Ashtary-Larky, Saeed Shirali, Matin Ghanavati, Meysam Alipour

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Background: In addition to reducing body weight, the low-calorie diets can reduce the lean body mass. It is hypothesized that in addition to reducing the body weight, the low-calorie diets can maintain the lean body mass. So, the current study aimed at evaluating the effects of high-protein diet with calorie restriction on body composition in overweight and obese individuals. Methods: 36 obese and overweight subjects were divided randomly into two groups. The first group received a normal-protein, low-energy diet (RDA), and the second group received a high-protein, low-energy diet (2×RDA). The anthropometric indices including height, weight, body mass index, body fat mass, fat free mass, and body fat percentage were evaluated before and after the study. Results: A significant reduction was observed in anthropometric indices in both groups (high-protein, low-energy diets and normal-protein, low-energy diets). In addition, more reduction in fat free mass was observed in the normal-protein, low-energy diet group compared to the high -protein, low-energy diet group. In other the anthropometric indices, significant differences were not observed between the two groups. Conclusion: Independently of the type of diet, low-calorie diet can improve the anthropometric indices, but during a weight loss, high-protein diet can help the fat free mass to be maintained.

Keywords: diet, high-protein, body mass index, body fat percentage

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Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

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Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: cooperative networks, normalized capacity, sensing time

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Authors: Hisham Mughrabi

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Osteoporosis is one of the most common diseases in the world and, its seriousness lies in the lack of clear symptoms. The researcher aims to identify the impact of sports activities on osteoporosis and the body component of those with mild intellectual disabilities of students in the schools in Saudi Arabia -Medina. The research sample was selected in an intentional manner and consisted of 45 students and they were divided into two groups. The first group consisted of 23 individuals participate in sports and the second group consisted of 22 individuals does not participate in sports. The researcher used the descriptive method and collected the data by measuring osteoporosis using and ultrasound osteoporosis screening device (OSTEO PRO B.M. Tech) and measured the body composition by using a Tanita devise (Body Composition Analyzer TBF- 300 Tanita). The results indicated that there was a statistical significant difference between the two comparing groups in osteoporosis measurement and body composition for the benefit of the group of sport participants. The researcher recommended the need to involve individuals with mild intellectual disabilities in physical activities to improve their rate of osteoporosis and body composition as well as to develop sports programs for individuals with mild intellectual disabilities.

Keywords: body composition, mild intellectual disabilities, osteoporosis, physical activities

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Authors: Yu-Ting Tsai, Chiun-Chieh Hsu, Yu-Chun Chu

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In recent years, due to the development of wireless network technology, many researchers have devoted to the study of wireless sensor networks. The applications of wireless sensor network mainly use the sensor nodes to collect the required information, and send the information back to the users. Since the sensed area is difficult to reach, there are many restrictions on the design of the sensor nodes, where the most important restriction is the limited energy of sensor nodes. Because of the limited energy, researchers proposed a number of ways to reduce energy consumption and balance the load of sensor nodes in order to increase the network lifetime. In this paper, we proposed the Energy-Balanced Clustering method with Auxiliary Members on Wireless Sensor Networks（EBCAM）based on the cluster routing. The main purpose is to balance the energy consumption on the sensed area and average the distribution of dead nodes in order to avoid excessive energy consumption because of the increasing in transmission distance. In addition, we use the residual energy and average energy consumption of the nodes within the cluster to choose the cluster heads, use the multi hop transmission method to deliver the data, and dynamically adjust the transmission radius according to the load conditions. Finally, we use the auxiliary cluster members to change the delivering path according to the residual energy of the cluster head in order to its load. Finally, we compare the proposed method with the related algorithms via simulated experiments and then analyze the results. It reveals that the proposed method outperforms other algorithms in the numbers of used rounds and the average energy consumption.

Keywords: auxiliary nodes, cluster, load balance, routing algorithm, wireless sensor network

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Authors: Shaharuddin Salleh, Sara Marouf, Hosein Mohammadi

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Directional sensor networks (DSNs) have recently attracted a great deal of attention due to their extensive applications in a wide range of situations. One of the most important problems associated with DSNs is covering a set of targets in a given area and, at the same time, maximizing the network lifetime. This is due to limitation in sensing angle and battery power of the directional sensors. This problem gets more complicated by the possibility that targets may have different coverage requirements. In the present study, this problem is referred to as priority-based target coverage (PTC). As sensors are often densely deployed, organizing the sensors into several cover sets and then activating these cover sets successively is a promising solution to this problem. In this paper, we propose a learning automata-based algorithm to organize the directional sensors into several cover sets in such a way that each cover set could satisfy coverage requirements of all the targets. Several experiments are conducted to evaluate the performance of the proposed algorithm. The results demonstrated that the algorithms were able to contribute to solving the problem.

Keywords: directional sensor networks, target coverage problem, cover set formation, learning automata

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Authors: Howard Gomwe, Eunice Seekoe, Philemon Lyoka, Chioneso Show Marange, Dennyford Mafa

Abstract:

There is arguably a lack of literature regarding body physical fitness and body composition amongst primary school learners in South Africa. For this reason, the study is aimed at investigating and accessing how body composition relates to physical fitness amongst primary school learners in the Eastern Cape Province of South Africa. In order to achieve this, a school-based cross-sectional survey was carried out among 876 primary school learners aged 9 to 14 years. Body composition indicators were measured and/or calculated, whilst physical fitness was evaluated according to the EUROFIT fitness standards by a 20 m shuttle run, push-ups, sit and reach as well as sit-ups. Out of 876 participants, a total of 870 were retained. Of these, 351 (40.34%) were boys, and 519 (59.66%) were girls. The average age of learners was 11.04 ± 1.50 years, with boys having a significantly (p = 0.002) higher mean age (M = 11.24; SD = 1.51 years) as compared to that of girls (M = 10.91; SD = 1.48 years). The non-parametric Spearman Rho correlation coefficients revealed several significant and negative relationships between body composition measurements with physical fitness characteristics, which were stronger in girls than in boys. The findings advocate for policymakers and responsible authorities to initiate the development of policies and interventions targeted at encouraging physical activity and health promotion among primary school learners in South Africa, especially in girls.

Keywords: BMI, body composition, body fat, children, physical fitness, primary school

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Authors: Amal Abo El-Maaty, Amira Mohamed, Nashwa Abu-Aita, Hisham Morgan

Abstract:

For estimating markers of overweight or obesity of brood mares used for riding and training, 17 mares of different body conditions were subjected to blood sampling and ultrasound examination to measure rump fat thickness and monitor ovulation for six consecutive weeks. Also length (L), heart girth (G) and withers height (H) were measured to estimate body weight (BW), body fat %, body fat mass (BFM) and body mass index (BMI). Mares were classified into three groups according to both body condition score (BCS) and rump back fat (BF). Overweight mares (O) were having BCS > 7 and BF thickness >7mm, moderate body condition (M) mares were having BCS >3and ≤7and BF <3and <7mm, and emaciated mares (E) were having BCS ≤3 and BF ≤3mm. glucose, triglycerides, nitric oxide, ovarian, thyroid, insulin, insulin like growth factor-I (IGF-1), and leptin hormones were measured. Results revealed that BCS, G, L, L*G*H, BW, BF, fat %, BFM were significantly (P<0.0001) decreasing linearly from O to E. T4 concentrations of E were significantly high (P=0.04) compared to M and O but T3 concentrations tended to decrease in E (P>0.05). Insulin and IGF-1 concentrations tended to be high in O (P>0.05) and decrease with the decrease of body condition. M had (P=0.007) the highest leptin, but E mares had the lowest P4 concentrations (P=0.01). Concentrations of glucose and NO decreased with the decrease of BCS and BF but triglycerides of O were insignificantly high. In conclusion, exercise could prevent the development of metabolic syndrome in horses and back fat and morphometric measurements were the easiest and simple assessment of overweight and deviation to obesity.

Keywords: body condition score, insulin, leptin, mares, rump fat

Procedia PDF Downloads 297

Authors: Ferruh Taspinar, Ismail Saracoglu, Emrah Afsar, Eda O. Okur, Gulce K. Seyyar, Gamze Kurt, Betul Taspinar

Abstract:

Although it is thought that abdominal adiposity is one of the risk factor for postural deviation, such as increased lumbar lordosis, the body mass index is not sufficient to indicate effects of abdominal adiposity on spinal alignment and postural changes. The aim of this study was to investigate the correlation with detailed body composition and spine alignment in healthy young adults. This cross-sectional study was conducted with sixty seven healthy volunteers (37 men and 30 women) whose ages ranged between 19 and 27 years. All participants’ sagittal spinal curvatures of lumbar and thoracic region were measured via Spinal mouse® (Idiag, Fehraltorf, Switzerland). Also, body composition analysis (whole body fat ratio, whole body muscle ratio, abdominal fat ratio, and trunk muscle ratio) estimation by means of bioelectrical impedance was evaluated via Tanita Bc 418 Ma Segmental Body Composition Analyser (Tanita, Japan). Pearson’s correlation was used to analysis among the variables. The mean lumbar lordosis and thoracic kyphosis angles were 21.02°±9.39, 41.50°±7.97, respectively. Statistically analysis showed a significant positive correlation between whole body fat ratio and lumbar lordosis angle (r=0.28, p=0.02). Similarly, there was a positive correlation between abdominal fat ratio and lumbar lordosis angle (r=0.27, p=0.03). The thoracic kyphosis angle showed also positive correlation with whole body fat ratio (r=0.33, p=0.00) and abdominal fat ratio (r=0.40, p=0.01). The whole body muscle ratio showed negative correlation between lumbar lordosis (r=-0.28, p=0.02) and thoracic kyphosis angles (r=-0.33, p=0.00), although there was no statistically correlation between trunk muscle ratio, lumbar and thoracic curvatures (p>0.05). The study demonstrated that an increase of fat ratio and decrease of muscle ratio in abdominal region or whole body shifts the spinal alignment which may adversely affect the spinal loading. Therefore, whole body composition should be taken into account in spine rehabilitation.

Keywords: body composition, lumbar lordosis, spinal alignment, thoracic kyphosis

Procedia PDF Downloads 355

Authors: Sorin Valcan, Mihail Gaianu

Abstract:

Labeling is a very costly and time consuming process which aims to generate datasets for training neural networks in several functionalities and projects. For driver monitoring system projects, the need for labeled images has a significant impact on the budget and distribution of effort. This paper presents the modifications done to an algorithm used for the generation of ground truth data for 2D eyes location on infrared images with drivers in order to improve the quality of the data and performance of the trained neural networks. The algorithm restrictions become tougher, which makes it more accurate but also less constant. The resulting dataset becomes smaller and shall not be altered by any kind of manual label adjustment before being used in the neural networks training process. These changes resulted in a much better performance of the trained neural networks.

Keywords: labeling automation, infrared camera, driver monitoring, eye detection, convolutional neural networks

Procedia PDF Downloads 80