Search results for: wireless body area networks (WBANs)

Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

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Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

Procedia PDF Downloads 82

Authors: Punitha Periyasamy, Mahalingam Sudalaimuthu, Sachikanta Nanda, Arasu Sundaram

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India holds 17.5% of the world’s population but has only 2% of the total geographical area of the world where 27.35% of the area is categorized as wasteland due to lack of or less groundwater. So there is a demand for excessive groundwater for agricultural and non agricultural activities to balance its growth rate. With this in mind, an attempt is made to find the groundwater potential zone in Gomukhi river sub basin of Vellar River basin, TamilNadu, India covering an area of 1146.6 Sq.Km consists of 9 blocks from Peddanaickanpalayam to Villupuram fall in the sub basin. The thematic maps such as Geology, Geomorphology, Lineament, Landuse, and Landcover and Drainage are prepared for the study area using IRS P6 data. The collateral data includes rainfall, water level, soil map are collected for analysis and inference. The digital elevation model (DEM) is generated using Shuttle Radar Topographic Mission (SRTM) and the slope of the study area is obtained. ArcGIS 10.1 acts as a powerful spatial analysis tool to find out the ground water potential zones in the study area by means of weighted overlay analysis. Each individual parameter of the thematic maps are ranked and weighted in accordance with their influence to increase the water level in the ground. The potential zones in the study area are classified viz., Very Good, Good, Moderate, Poor with its aerial extent of 15.67, 381.06, 575.38, 174.49 Sq.Km respectively.

Keywords: ArcGIS, DEM, groundwater, recharge, weighted overlay

Procedia PDF Downloads 430

Authors: Shreyas S. Hegde, Anindya Deb, Suresh Nagesh

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Computational bio-mechanics is developing rapidly as a non-invasive tool to assist the medical fraternity to help in both diagnosis and prognosis of human body related issues such as injuries, cardio-vascular dysfunction, atherosclerotic plaque etc. Any system that would help either properly diagnose such problems or assist prognosis would be a boon to the doctors and medical society in general. Recently a lot of work is being focused in this direction which includes but not limited to various finite element analysis related to dental implants, skull injuries, orthopedic problems involving bones and joints etc. Such numerical solutions are helping medical practitioners to come up with alternate solutions for such problems and in most cases have also reduced the trauma on the patients. Some work also has been done in the area related to the use of computational fluid mechanics to understand the flow of blood through the human body, an area of hemodynamics. Since cardio-vascular diseases are one of the main causes of loss of human life, understanding of the blood flow with and without constraints (such as blockages), providing alternate methods of prognosis and further solutions to take care of issues related to blood flow would help save valuable life of such patients. This project is an attempt to use computational fluid dynamics (CFD) to solve specific problems related to hemodynamics. The hemodynamics simulation is used to gain a better understanding of functional, diagnostic and theoretical aspects of the blood flow. Due to the fact that many fundamental issues of the blood flow, like phenomena associated with pressure and viscous forces fields, are still not fully understood or entirely described through mathematical formulations the characterization of blood flow is still a challenging task. The computational modeling of the blood flow and mechanical interactions that strongly affect the blood flow patterns, based on medical data and imaging represent the most accurate analysis of the blood flow complex behavior. In this project the mathematical modeling of the blood flow in the arteries in the presence of successive blockages has been analyzed using CFD technique. Different cases of blockages in terms of percentages have been modeled using commercial software CATIA V5R20 and simulated using commercial software ANSYS 15.0 to study the effect of varying wall shear stress (WSS) values and also other parameters like the effect of increase in Reynolds number. The concept of fluid structure interaction (FSI) has been used to solve such problems. The model simulation results were validated using in vivo measurement data from existing literature

Keywords: computational fluid dynamics, hemodynamics, blood flow, results validation, arteries

Procedia PDF Downloads 392

Authors: Hossein Vahedi, Zahra Soleymani Fard

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SefidKuh area in Baluchistan, Iran, is one of the impossible areas which the focused archeological investigations have not been on it. In the Sefidkuh area, there are colonies as if they were stopped in the Neolithic and Chalcolithic ages. These colonies exhibit culturally specific behaviors, which their study can reveal much of the cultural nature of the Neolithic, Chalcolithic inhabitants of the region. In the villages of this area, still, circular architecture is used in different types. The political management of the villages in the region is also the responsibility of Khan, whose characteristics can be compared to the prehistoric era. These people's livelihoods include hunting, animal husbandry, horticulture, and limited crop storage. Residents of Sefidkuh use the exchange of goods to obtain needed supplies that they themselves cannot produce. In this area, there are central location villages that are quite similar to the cluster model, and the Great Khan leads the surrounding villages.

Keywords: archaeology, social structure, neolithic, chalcolithic, Sefidkuh, Baluchistan

Procedia PDF Downloads 103

Authors: Hyoup-Sang Yoon

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The quality of video transmitted by mobile ad hoc networks (MANETs) can be influenced by several factors, including protocol layers; parameter settings of each protocol. In this paper, we are concerned with understanding the functional relationship between these influential factors and objective video quality in MANETs. We illustrate a systematic statistical design of experiments (DOE) strategy can be used to analyse MANET parameters and performance. Using a 2k factorial design, we quantify the main and interactive effects of 7 factors on a response metric (i.e., mean opinion score (MOS) calculated by PSNR with Evalvid package) we then develop a first-order linear regression model between the influential factors and the performance metric.

Keywords: evalvid, full factorial design, mobile ad hoc networks, ns-2

Procedia PDF Downloads 399

Authors: M. Abir Hossain, M. Shahjada Tarafder

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This paper deals with the analysis of potential flow past two-dimensional body by discretizing the body into panels where the Laplace equation was applied to each panel. The Laplace equation was solved at each panel by applying the boundary conditions. The boundary condition was applied at each panel to mathematically formulate the problem and then convert the problem into a computer-solvable problem. Kutta condition was applied at both the leading and trailing edges to see whether the condition is satisfied or not. Another approach that is applied for the analysis is Vortex Lattice Method (VLM). A vortex ring is considered at each control point. Using the Biot-Savart Law the strength at each control point is calculated and hence the pressure differentials are measured. For the comparison of the analytic result with the experimental result, different NACA section hydrofoil is used. The analytic result of NACA 0012 and NACA 0015 are compared with the experimental result of Abbott and Doenhoff and found significant conformity with the achieved result.

Keywords: Kutta condition, Law of Biot-Savart, pressure differentials, potential flow, vortex lattice method

Procedia PDF Downloads 178

Authors: B. Padmaja, V. V. Rama Prasad, K. V. N. Sunitha, E. Krishna Rao Patro

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Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. Constant exposure to stress is detrimental not only for mind but also body. Nevertheless, to cope with stress, one should first identify it. This paper provides an effective method for the cognitive stress level detection by using data provided from a physical activity tracker device Fitbit. This device gathers people’s daily activities of food, weight, sleep, heart rate, and physical activities. In this paper, four major stressors like physical activities, sleep patterns, working hours and change in heart rate are used to assess the stress levels of individuals. The main motive of this system is to use machine learning approach in stress detection with the help of Smartphone sensor technology. Individually, the effect of each stressor is evaluated using logistic regression and then combined model is built and assessed using variants of ordinal logistic regression models like logit, probit and complementary log-log. Then the quality of each model is evaluated using Akaike Information Criterion (AIC) and probit is assessed as the more suitable model for our dataset. This system is experimented and evaluated in a real time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that stress detection system should be less invasive as possible for the users.

Keywords: physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor

Procedia PDF Downloads 243

Authors: Mustafa Metin Donma, Orkide Donma

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Vitamin deficiencies are common in obese individuals. Particularly, the status of vitamin B12 and its association with vitamin B9 (folate) and vitamin D is under investigation in recent time. Vitamin B12 is closely related to many vital processes in the body. In clinical studies, its involvement in fat metabolism draws attention from the obesity point of view. Obesity, in its advanced stages and in combination with metabolic syndrome (MetS) findings, may be a life-threatening health problem. Pediatric obesity is particularly important because it may be a predictor of severe chronic diseases during the adulthood period of the child. Due to its role in fat metabolism, vitamin B12 deficiency may disrupt metabolic pathways of the lipid and energy metabolisms in the body. The association of low B12 levels with obesity degree may be an interesting topic to be investigated. Obesity indices may be helpful at this point. Weight- and fat-based indices are available. Of them, body mass index (BMI) is in the first group. Fat mass index (FMI), fat-free mass index (FFMI) and diagnostic obesity notation model assessment-II (D2I) index lie in the latter group. The aim of this study is to clarify possible associations between vitamin B12 status and obesity indices in the pediatric population. The study comprises a total of one hundred and twenty-two children. Thirty-two children were included in the normal body mass index (N-BMI) group. Forty-six and forty-four children constitute groups with morbid obese children without MetS and with MetS, respectively. Informed consent forms and the approval of the institutional ethics committee were obtained. Tables prepared for obesity classification by World Health Organization were used. Metabolic syndrome criteria were defined. Anthropometric and blood pressure measurements were taken. Body mass index, FMI, FFMI, D2I were calculated. Routine laboratory tests were performed. Vitamin B9, B12, D concentrations were determined. Statistical evaluation of the study data was performed. Vitamin B9 and vitamin D levels were reduced in MetS group compared to children with N-BMI (p>0.05). Significantly lower values were observed in vitamin B12 concentrations of MetS group (p<0.01). Upon evaluation of blood pressure as well as triglyceride levels, there exist significant increases in morbid obese children. Significantly decreased concentrations of high density lipoprotein cholesterol were observed. All of the obesity indices and insulin resistance index exhibit increasing tendency with the severity of obesity. Inverse correlations were calculated between vitamin D and insulin resistance index as well as vitamin B12 and D2I in morbid obese groups. In conclusion, a fat-based index, D2I, was the most prominent body index, which shows a strong correlation with vitamin B12 concentrations in the late stage of obesity in children. A negative correlation between these two parameters was a confirmative finding related to the association between vitamin B12 and obesity degree.

Keywords: body mass index, children, D2I index, fat mass index, obesity

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Authors: Yan Yu, Wang Yu, Chen Xintong, Liu Yi, Zhang Yanzhong, Wang Yanji, Chen Xingyu, Zhang Miaocheng, Tong Yi

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Neuromorphic computing based on spiking neural networks (SNNs) has emerged as a promising avenue for building the next generation of intelligent computing systems. Owing to its high-density integration, low power, and outstanding nonlinearity, memristors have attracted emerging attention on achieving SNNs. However, fabricating a low-power and robust memristor-based spiking neuron without extra electrical components is still a challenge for brain-inspired systems. In this work, we demonstrate a TiO₂-based threshold switching (TS) memristor to emulate a leaky integrate-and-fire (LIF) neuron without auxiliary circuits, used to realize single layer fully connected (FC) SNNs. Moreover, our TiO₂-based resistive switching (RS) memristors realize spiking-time-dependent-plasticity (STDP), originating from the Ag diffusion-based filamentary mechanism. This work demonstrates that TiO2-based memristors may provide an efficient method to construct hardware neuromorphic computing systems.

Keywords: leaky integrate-and-fire, memristor, spiking neural networks, spiking-time-dependent-plasticity

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Authors: C. Iraklis, G. Evmiridis, A. Iraklis

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Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid

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Authors: Peristera Baziana

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In this paper, we present a network configuration for a WDM LANs of passive star topology that assume that the set of data WDM channels is split into two separate sets of channels, with different access rights over them. Especially, a synchronous transmission WDMA access algorithm is adopted in order to increase the probability of successful transmission over the data channels and consequently to reduce the probability of data packets transmission cancellation in order to avoid the data channels collisions. Thus, a control pre-transmission access scheme is followed over a separate control channel. An analytical Markovian model is studied and the average throughput is mathematically derived. The performance is studied for several numbers of data channels and various values of control phase duration.

Keywords: access algorithm, channels division, collisions avoidance, wavelength division multiplexing

Procedia PDF Downloads 279

Authors: Michael Fundator

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Groundbreaking application of biomathematical and biochemical research in neural networks processes to formation of non-canonical bases, islands, and analog bases in DNA and mRNA at or near the transcription that contradicts the long anticipated statistical assumptions for the distribution of bases and analog bases compounds is implemented through statistical and stochastic methods apparatus with addition of quantum principles, where the usual transience of Poisson spike train becomes very instrumental tool for finding even almost periodical type of solutions to Fokker-Plank stochastic differential equation. Present article develops new multidimensional methods of finding solutions to stochastic differential equations based on more rigorous approach to mathematical apparatus through Kolmogorov-Chentsov continuity theorem that allows the stochastic processes with jumps under certain conditions to have γ-Holder continuous modification that is used as basis for finding analogous parallels in dynamics of neutral networks and formation of analog bases and transcription in DNA.

Keywords: Fokker-Plank stochastic differential equation, Kolmogorov-Chentsov continuity theorem, neural networks, translation and transcription

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Authors: Sekkal Nawel, Mahammed Nadir

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The proliferation of online activities on Online Social Networks (OSNs) has captured significant user attention. However, this growth has been hindered by the emergence of fraudulent accounts that do not represent real individuals and violate privacy regulations within social network communities. Consequently, it is imperative to identify and remove these profiles to enhance the security of OSN users. In recent years, researchers have turned to machine learning (ML) to develop strategies and methods to tackle this issue. Numerous studies have been conducted in this field to compare various ML-based techniques. However, the existing literature still lacks a comprehensive examination, especially considering different OSN platforms. Additionally, the utilization of bio-inspired algorithms has been largely overlooked. Our study conducts an extensive comparison analysis of various fake profile detection techniques in online social networks. The results of our study indicate that supervised models, along with other machine learning techniques, as well as unsupervised models, are effective for detecting false profiles in social media. To achieve optimal results, we have incorporated six bio-inspired algorithms to enhance the performance of fake profile identification results.

Keywords: machine learning, bio-inspired algorithm, detection, fake profile, system, social network

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Authors: Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

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Activation functions play a decisive role in determining the capacity of Deep Neural Networks (DNNs) as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused on the utility of monotonic or non-oscillatory functions, until Growing Cosine Unit (GCU) broke the taboo for a number of applications. In this paper, a Convolutional Neural Network (CNN) model named as ASU-CNN is proposed which utilizes recently designed activation function ASU across its layers. The effect of this non-monotonic and oscillatory function is inspected through feature map visualizations from different convolutional layers. The optimization of proposed network is offered by Adam with a fine-tuned adjustment of learning rate. The network achieved promising results on both training and testing data for the classification of CIFAR-10. The experimental results affirm the computational feasibility and efficacy of the proposed model for performing tasks related to the field of computer vision.

Keywords: amplifying sine unit, activation function, convolutional neural networks, oscillatory activation, image classification, CIFAR-10

Procedia PDF Downloads 87

Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

Procedia PDF Downloads 107

Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

Procedia PDF Downloads 134

Authors: Salma E. Ahmed

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Since the mid 50’s, enormous attention has been paid towards nanocarriers and their applications in drug and gene delivery. Among these vesicles, liposomes and micelles have been heavily investigated due to their many advantages over other types. Liposomes, for instance, are mostly distinguished by their ability to encapsulate hydrophobic, hydrophilic and amphiphilic drugs. Micelles, on the other hand, are self-assembled shells of lipids, amphiphilic or oppositely charged block copolymers that, once exposed to aqueous media, can entrap hydrophobic agents, and possess prolonged circulation in the bloodstream. Both carriers are considered compatible and biodegradable. Nevertheless, they have limited stabilities, chemical versatilities, and drug encapsulation efficiencies. In order to overcome these downsides, strategies for optimizing a novel drug delivery system that has the architecture of liposomes and polymeric characteristics of micelles have been evolved. Polymersomes are vehicles with fluidic cores and hydrophobic shells that are protected and isolated from the aqueous media by the hydrated hydrophilic brushes which give the carrier its distinctive polymeric bilayer shape. Similar to liposomes, this merit enables the carrier to encapsulate a wide range of agents, despite their affinities and solubilities in water. Adding to this, the high molecular weight of the amphiphiles that build the body of the polymersomes increases their colloidal and chemical stabilities and reduces the permeability of the polymeric membranes, which makes the vesicles more protective to the encapsulated drug. These carriers can also be modified in ways that make them responsive when targeted or triggered, by manipulating their composition and attaching moieties and conjugates to the body of the carriers. These appealing characteristics, in addition to the ease of synthesis, gave the polymersomes greater potentials in the area of drug delivery. Thus, their design and characterization, in comparison with liposomes and micelles, are briefly reviewed in this work.

Keywords: controlled release, liposomes, micelles, polymersomes, targeting

Procedia PDF Downloads 186

Authors: Ursula D. C. Resende, Yan G. Santos, Lucas M. de O. Andrade

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The recent and fast development of the internet, wireless, telecommunication technologies and low-power electronic devices has led to an expressive amount of electromagnetic energy available in the environment and the smart applications technology expansion. These applications have been used in the Internet of Things devices, 4G and 5G solutions. The main feature of this technology is the use of the wireless sensor. Although these sensors are low-power loads, their use imposes huge challenges in terms of an efficient and reliable way for power supply in order to avoid the traditional battery. The radio frequency based energy harvesting technology is especially suitable to wireless power sensors by using a rectenna since it can be completely integrated into the distributed hosting sensors structure, reducing its cost, maintenance and environmental impact. The rectenna is an equipment composed of an antenna and a rectifier circuit. The antenna function is to collect as much radio frequency radiation as possible and transfer it to the rectifier, which is a nonlinear circuit, that converts the very low input radio frequency energy into direct current voltage. In this work, a set of rectennas, mounted on a paper substrate, which can be used for the inner coating of buildings and simultaneously harvest electromagnetic energy from the environment, is proposed. Each proposed individual rectenna is composed of a 2.45 GHz patch antenna and a voltage doubler rectifier circuit, built in the same paper substrate. The antenna contains a rectangular radiator element and a microstrip transmission line that was projected and optimized by using the Computer Simulation Software (CST) in order to obtain values of S11 parameter below -10 dB in 2.45 GHz. In order to increase the amount of harvested power, eight individual rectennas, incorporating metamaterial cells, were connected in parallel forming a system, denominated Electromagnetic Wall (EW). In order to evaluate the EW performance, it was positioned at a variable distance from the internet router, and a 27 kΩ resistive load was fed. The results obtained showed that if more than one rectenna is associated in parallel, enough power level can be achieved in order to feed very low consumption sensors. The 0.12 m2 EW proposed in this work was able to harvest 0.6 mW from the environment. It also observed that the use of metamaterial structures provide an expressive growth in the amount of electromagnetic energy harvested, which was increased from 0. 2mW to 0.6 mW.

Keywords: electromagnetic energy harvesting, metamaterial, rectenna, rectifier circuit

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Authors: Nafsi K. Ashraf, C. V. Vipin, V. Anantha Subramanian

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This paper reports the design of a waterjet propulsion system for an amphibious vehicle based on circulation distribution over the camber line for the sections of the impeller and stator. In contrast with the conventional waterjet design, the inlet duct is straight for water entry parallel and in line with the nozzle exit. The extended nozzle after the stator bowl makes the flow more axial further improving thrust delivery. Waterjet works on the principle of volume flow rate through the system and unlike the propeller, it is an internal flow system. The major difference between the propeller and the waterjet occurs at the flow passing the actuator. Though a ducted propeller could constitute the equivalent of waterjet propulsion, in a realistic situation, the nozzle area for the Waterjet would be proportionately larger to the inlet area and propeller disc area. Moreover, the flow rate through impeller disk is controlled by nozzle area. For these reasons the waterjet design is based on pump systems rather than propellers and therefore it is important to bring out the characteristics of the flow from this point of view. The analysis is carried out using computational fluid dynamics. Design of waterjet propulsion is carried out adapting the axial flow pump design and performance analysis was done with three-dimensional computational fluid dynamics (CFD) code. With the varying environmental conditions as well as with the necessity of high discharge and low head along with the space confinement for the given amphibious vehicle, an axial pump design is suitable. The major problem of inlet velocity distribution is the large variation of velocity in the circumferential direction which gives rise to heavy blade loading that varies with time. The cavitation criteria have also been taken into account as per the hydrodynamic pump design. Generally, waterjet propulsion system can be parted into the inlet, the pump, the nozzle and the steering device. The pump further comprises an impeller and a stator. Analytical and numerical approaches such as RANSE solver has been undertaken to understand the performance of designed waterjet propulsion system. Unlike in case of propellers the analysis was based on head flow curve with efficiency and power curves. The modeling of the impeller is performed using rigid body motion approach. The realizable k-ϵ model has been used for turbulence modeling. The appropriate boundary conditions are applied for the domain, domain size and grid dependence studies are carried out.

Keywords: amphibious vehicle, CFD, impeller design, waterjet propulsion

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Authors: Alessandra Rossodivita, Alexei Tikhomirov, Andrey Trufanov, Nikolay Kinash, Olga Berestneva, Svetlana Nikitina, Fabio Casati, Alessandro Visconti, Tommaso Saporito

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It is well known that world and national societies are exposed to diverse threats: anthropogenic, technological, and natural. Anthropogenic ones are of greater risks and, thus, attract special interest to researchers within wide spectrum of disciplines in efforts to lower the pertinent risks. Some researchers showed by means of multilayered, complex network models how media promotes the prevention of disease spread. To go further, not only are mass-media sources included in scope the paper suggests but also personificated social bots (socbots) linked according to reflexive theory. The novel scope considers information spread over conscious and unconscious agents while counteracting both natural and man-made threats, i.e., infections and terrorist hazards. Contrary to numerous publications on misinformation disseminated by ‘bad’ bots within social networks, this study focuses on ‘good’ bots, which should be mobilized to counter the former ones. These social bots deployed mixture with real social actors that are engaged in concerted actions at spreading, receiving and analyzing information. All the contemporary complex network platforms (multiplexes, interdependent networks, combined stem networks et al.) are comprised to describe and test socbots activities within competing information sharing tools, namely mass-media hubs, social networks, messengers, and e-mail at all phases of disasters. The scope and concomitant techniques present evidence that embedding such socbots into information sharing process crucially change the network topology of actor interactions. The change might improve or impair robustness of social network environment: it depends on who and how controls the socbots. It is demonstrated that the topological approach elucidates techno-social processes within the field and outline the roadmap to a safer world.

Keywords: complex network platform, counterterrorism, information sharing topology, social bots

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Authors: Deviana Yuanitasari

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The rapid development of world commerce and trade nowadays has created fast-paced demand in every business activities and transactions. That also includes the need for ready to use and practical form of standard contract. For the company or business owner, the use of standard contract is an alternative way to achieve economic goals faster, effectively and efficiently. In the other hand, for the consumer the practice of using standard contract usually unfavorable, because the contract clauses usually have been defined by the company and cannot be individually negotiated. That means consumer cannot influence the substances of the contract clauses. The purpose of this study is to get deeper understanding and analyze the role of Consumer Dispute Settlement Body in the monitoring of standard clause inclusion by businesses and industries within the context of practicing consumer protection law. Furthermore, this study will focus on the procedure of sanction and the effectiveness of the sanction for the business practitioners which disregard the inclusion of the prohibited standard clause. Therefore, this study will depict the law issues and other phenomenon that related with the role of Consumer Dispute Settlement Body in monitoring the inclusion of standard clause and procedure of sanction for the business practitioners that still use exemption clause within Consumer Protection Law System. This study results that BPSK has been assigned to monitor the inclusion of standard clause and settle consumer dispute. At this stage, BPSK role is passive, which means BPSK only takes an action if there are consumer complaints. The procedure of sanction is not part of BPSK tasks, since should there be a violation of standard clause; BPSK can only ask the business practitioners to remove the prohibited clause and not give a sanction. As a result, the procedure of sanction rule for the Standard Clause violation in this context can be considered as ineffective.

Keywords: standard contract, standard clause, consumer protection law, consumer dispute settlement body

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Authors: Maria M. Giannakou, Athanasios K. Ziliaskopoulos

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Transmission pipelines carrying natural gas are often routed through populated cities, industrial and environmentally sensitive areas. While the need for these networks is unquestionable, there are serious concerns about the risk these lifeline networks pose to the people, to their habitat and to the critical infrastructures, especially in view of natural disasters such as earthquakes. This work presents an Integrated Pipeline Risk Management methodology (IPRM) for assessing the hazard associated with a natural gas pipeline failure due to natural or manmade disasters. IPRM aims to optimize the allocation of the available resources to countermeasures in order to minimize the impacts of pipeline failure to humans, the environment, the infrastructure and the economic activity. A proposed knapsack mathematical programming formulation is introduced that optimally selects the proper mitigation policies based on the estimated cost – benefit ratios. The proposed model is demonstrated with a small numerical example. The vulnerability analysis of these pipelines and the quantification of consequences from such failures can be useful for natural gas industries on deciding which mitigation measures to implement on the existing pipeline networks with the minimum cost in an acceptable level of hazard.

Keywords: cost benefit analysis, knapsack problem, natural gas distribution network, risk management, risk mitigation

Procedia PDF Downloads 277

Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

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Authors: Yuwaratu Syafira, Wahyu K. Y. Putra, Kusharisupeni Djokosujono

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Background/Objective: Body Mass Index (BMI) serves various purposes, including measuring the prevalence of obesity in a population, and also in formulating a patient’s diet at a hospital, and can be calculated with the equation = body weight (kg)/body height (m)². However, the BMI of an individual with difficulties in carrying their weight or standing up straight can not necessarily be measured. The aim of this study was to form a prediction model for the BMI of young adult students of Public Health Faculty of University of Indonesia. Subject/Method: This study used a cross sectional design, with a total sample of 132 respondents, consisted of 58 males and 74 females aged 21- 30. The dependent variable of this study was BMI, and the independent variables consisted of sex and anthropometric measurements, which included ulna length, arm length, tibia length, knee height, mid-upper arm circumference, and calf circumference. Anthropometric information was measured and recorded in a single sitting. Simple and multiple linear regression analysis were used to create the prediction equation for BMI. Results: The male respondents had an average BMI of 24.63 kg/m² and the female respondents had an average of 22.52 kg/m². A total of 17 variables were analysed for its correlation with BMI. Bivariate analysis showed the variable with the strongest correlation with BMI was Mid-Upper Arm Circumference/√Ulna Length (MUAC/√UL) (r = 0.926 for males and r = 0.886 for females). Furthermore, MUAC alone also has a very strong correlation with BMI (r = 0,913 for males and r = 0,877 for females). Prediction models formed from either MUAC/√UL or MUAC alone both produce highly accurate predictions of BMI. However, measuring MUAC/√UL is considered inconvenient, which may cause difficulties when applied on the field. Conclusion: The prediction model considered most ideal to estimate BMI is: Male BMI (kg/m²) = 1.109(MUAC (cm)) – 9.202 and Female BMI (kg/m²) = 0.236 + 0.825(MUAC (cm)), based on its high accuracy levels and the convenience of measuring MUAC on the field.

Keywords: body mass index, mid-upper arm circumference, prediction model, ulna length

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Authors: Richard Draper

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A supercomputer can be constructed from identical building blocks which are small parallel processors connected by a network referred to as the local network. The routers have unused ports which are used to interconnect the building blocks. These connections are referred to as the global network. The address space has a global and a local component (g, l). The conventional way to connect the building blocks is to connect (g, l) to (g’,l). If there are K blocks, this requires K global ports in each router. If a block is of size M, the result is a machine with KM routers having diameter two. To increase the size of the machine to 2K blocks, each router connects to only half of the other blocks. The result is a larger machine but also one with greater diameter. This is a crude description of how the network of the CRAY XC® is designed. In this paper, a family of interconnection networks using routers with K global and M local ports is defined. Coordinates are (c,d, p) and the global connections are (c,d,p)↔(c’,p,d) which swaps p and d. The network is denoted D3(K,M) and is called a Swapped Dragonfly. D3(K,M) has KM2 routers and has diameter three, regardless of the size of K. To produce a network of size KM2 conventionally, diameter would be an increasing function of K. The family of Swapped Dragonflies has other desirable properties: 1) D3(K,M) scales linearly in K and quadratically in M. 2) If L < K, D3(K,M) contains many copies of D3(L,M). 3) If L < M, D3(K,M) contains many copies of D3(K,L). 4) D3(K,M) can perform an all-to-all exchange in KM2+KM time which is only slightly more than the time to do a one-to-all. This paper makes several contributions. It is the first time that a swap has been used to define a linearly scalable family of networks. Structural properties of this new family of networks are thoroughly examined. A synchronizing packet header is introduced. It specifies the path to be followed and it makes it possible to define highly parallel communication algorithm on the network. Among these is an all-to-all exchange in time KM2+KM. To demonstrate the effectiveness of the swap properties of the network of the CRAY XC® and D3(K,16) are compared.

Keywords: all-to-all exchange, CRAY XC®, Dragonfly, interconnection network, packet switching, swapped network, topology

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Authors: Yasaman Zeinali, Farid Khosravikia

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This paper presents a multi-objective framework for sustainable urban development. The proposed framework aims to address different aspects of sustainability in urban development planning. These aspects include, but are not limited to education, health, job opportunities, architecture, culture, environment, mobility, energy, water, waste, and so on. Then, the proposed framework is applied to the Brackenridge Tract (an area in downtown Austin, Texas), to redevelop that area in a sustainable way. The detail of the implementation process is presented in this paper. The ultimate goal of this paper is to develop a sustainable area in downtown Austin with ensuring that it locally meets the needs of present and future generations with respect to economic, social, environmental, health as well as cultural aspects. Moreover, it helps the city with the population growth problem by accommodating more people in that area.

Keywords: urban planning, sustainability, sustainable urban development, environmental impacts of human activities

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Authors: C. Busuioc, I. Stancu, A. Nicoara, A. Zamfirescu, A. Evanghelidis

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The field of tissue engineering has expanded its potential due to the use of composite biomaterials belonging to increasingly complex systems, leading to bone substitutes with properties that are continuously improving to meet the patient's specific needs. Furthermore, the development of biomaterials based on ceramic and polymeric phases is an unlimited resource for future scientific research, with the final aim of restoring the original tissue functionality. Thus, in the first stage, composite scaffolds based on polycaprolactone (PCL) or polylactic acid (PLA) and inorganic powders were prepared by employing the electrospinning technique. The targeted powders were: commercial and laboratory synthesized hydroxyapatite (HAp), as well as barium titanate (BT). By controlling the concentration of the powder within the precursor solution, together with the processing parameters, different types of three-dimensional architectures were achieved. In the second stage, both the mineral powders and hybrid composites were investigated in terms of composition, crystalline structure, and microstructure so that to demonstrate their suitability for tissue engineering applications. Regarding the scaffolds, these were proven to be homogeneous on large areas and loaded with mineral particles in different proportions. The biological assays demonstrated that the addition of inorganic powders leads to modified responses in the presence of simulated body fluid (SBF) or cell cultures. Through SBF immersion, the biodegradability coupled with bioactivity were highlighted, with fiber fragmentation and surface degradation, as well as apatite layer formation within the testing period. Moreover, the final composites represent supports accepted by the cells, favoring implant integration. Concluding, the purposed fibrous materials based on bioresorbable polymers and mineral powders, produced by the electrospinning technique, represent candidates with considerable potential in the field of tissue engineering. Future improvements can be attained by optimizing the synthesis process or by simultaneous incorporation of multiple inorganic phases with well-defined biological action in order to fabricate multifunctional composites.

Keywords: barium titanate, electrospinning, fibre networks, hydroxyapatite, smart scaffolds

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Authors: Chukwu Fidelis Ndubuisi, Madufor Michael Ozims, Asogwa Vivian Ndidiamaka, Egenamba Juliet Ngozi, Okonkwo Stephen C., Kamah Chukwudi David

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Deflection of the vertical is a quantity used in reducing geodetic measurements related to geoidal networks to the ellipsoidal plane; and it is essential in Geoid modeling processes. Computing the deflection of the vertical component of a point in a given area is necessary in evaluating the standard errors along north-south and east-west direction. Using combined approach for the determination of deflection of the vertical component provides improved result but labor intensive without appropriate method. Least square method is a method that makes use of redundant observation in modeling a given sets of problem that obeys certain geometric condition. This research work is aimed to computing the deflection of vertical component of Owerri West local government area of Imo State using geometric method as field technique. In this method combination of Global Positioning System on static mode and precise leveling observation were utilized in determination of geodetic coordinate of points established within the study area by GPS observation and the orthometric heights through precise leveling. By least square using Matlab programme; the estimated deflections of vertical component parameters for the common station were -0.0286 and -0.0001 arc seconds for the north-south and east-west components respectively. The associated standard errors of the processed vectors of the network were computed. The computed standard errors of the North-south and East-west components were 5.5911e-005 and 1.4965e-004 arc seconds, respectively. Therefore, including the derived component of deflection of the vertical to the ellipsoidal model will yield high observational accuracy since an ellipsoidal model is not tenable due to its far observational error in the determination of high quality job. It is important to include the determined deflection of the vertical component for Owerri West Local Government in Imo State, Nigeria.

Keywords: deflection of vertical, ellipsoidal height, least square, orthometric height

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Authors: Omari W. Keeles

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Attention to social class and race processes could illuminate within- group differences in Black students' experiences that help explain variation in adjustment. Of interest is how social class relates to development of intragroup connections with other Black students on campus in ways that promote or inhibit well-being. The present study’s findings suggest that students from lower class backgrounds may be more restrictive or limited in opportunities around their intragroup friendship networks than more affluent students. Furthermore, Black social relationship networks were related to positive mental health adjustment important to healthy psychological functioning and development.

Keywords: black students, social class, homophily, psychological adjustment

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Authors: Desi Meriyanti, Delina Puspa Rosana Firdaus, Ristia Rinati

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Nowadays, the presence of free radicals become a big concern due to its negative impact to the body, which can triggers the formation of degenerative diseases such as cancer, heart disease cardiovascular, diabetic mellitus and others. Free radical oxidation can be prevented by the presence of antioxidants. Naturally, the human body produces its own antioxidants. Because of the free radicals exposure are so intense, especially from the environment, it is necessary to supply antioxidants needed from outside, through the consumption of functional foods with high antioxidant content. Gethuk is one of the traditional snacks in Indonesia. Gethuk is made from cassava with minimal processing such as boiling, destructing, and forming. Gethuk is classified as a familiar snack in the community, so it has a potential for developing, especially into a functional food. The low content of antioxidants in gethuk can be overcome with the development of a product called Gethuk Marillo. Gethuk Marillo is gethuk with the addition of natural antioxidants from mangosteen pericarp extract which has a high content of xanthones, these compounds are classified into flavonoids and act as antioxidants in the body. Gethuk Marillo served along with tamarillo fruit sauce which is also high in antioxidants such as anthocyanin. The combination between 300 grams gethuk Marillo and sauce contain flavonoid about 31% of human antioxidant needs per day. Gethuk Marillo called as a functional food because of high flavonoids content which can prevent degenerative diseases namely cancer, as many studies that the xanthone and anthocyanins compounds can effectively prevent the formation of cancer cells in human body.

Keywords: Gethuk marillo, xanthones, anthocyanin, high antioxidants, anti-cancer

Procedia PDF Downloads 643