Search results for: adaptive type-I hybrid progressive censoring

Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

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The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Alexander Babin, Leonid Savin

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In the present paper, increasing of energy efficiency of a thrust hybrid bearing with a central feeding chamber is considered. The mathematical model was developed to determine the pressure distribution and the reaction forces, based on the Reynolds equation and static characteristics’ equations. The boundary problem of pressure distribution calculation was solved using the method of finite differences. For various types of lubricants, geometry and operational characteristics, axial gaps can be determined, where the minimal friction coefficient is provided. The next part of the study considers the application of servovalves in order to maintain the desired position of the rotor. The report features the calculation results and the analysis of the influence of the operational and geometric parameters on the energy efficiency of mechatronic fluid-film bearings.

Keywords: active bearings, energy efficiency, mathematical model, mechatronics, thrust multipad bearing

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Authors: Peggy M. Randon, Lisa Randon

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Introduction: The post-COVID-19 era has presented unique challenges for addressing complex mental health issues, particularly due to exacerbated stress, increased social isolation, and disrupted continuity of care. This article outlines relevant health disparities and policy implications within the context of the United States while maintaining international relevance. Methods: A comprehensive literature review (including studies, reports, and policy documents) was conducted to examine concerns related to childhood-onset schizophrenia and the impact on patients and their families. Qualitative and quantitative data were synthesized to provide insights into the complex etiology of schizophrenia, the effects of the pandemic, and the challenges faced by socioeconomically disadvantaged populations. Case studies were employed to illustrate real-world examples and areas requiring policy reform. Results: Early intervention in childhood is crucial for preventing or mitigating the long-term impact of complex psychotic disorders, particularly schizophrenia. A comprehensive understanding of the genetic, environmental, and physiological factors contributing to the development of schizophrenia is essential. The COVID-19 pandemic worsened symptoms and disrupted treatment for many adolescent patients with schizophrenia, emphasizing the need for adaptive interventions and the utilization of virtual platforms. Health disparities, including stigma, financial constraints, and language or cultural barriers, further limit access to care, especially for socioeconomically disadvantaged populations. Policy implications: Current US health policies inadequately support patients with schizophrenia. The limited availability of longitudinal care, insufficient resources for families, and stigmatization represent ongoing policy challenges. Addressing these issues necessitates increased research funding, improved access to affordable treatment plans, and cultural competency training for healthcare providers. Public awareness campaigns are crucial to promote knowledge, awareness, and acceptance of mental health disorders. Conclusion: The unique challenges faced by children and families in the US affected by schizophrenia and other psychotic disorders have yet to be adequately addressed on institutional and systemic levels. The relevance of findings to an international audience is emphasized by examining the complex factors contributing to the onset of psychotic disorders and their global policy implications. The broad impact of the COVID-19 pandemic on mental health underscores the need for adaptive interventions and global responses. Addressing policy challenges, improving access to care, and reducing the stigma associated with mental health disorders are crucial steps toward enhancing the lives of adolescents and young adults with schizophrenia and their family members. The implementation of virtual platforms can help overcome barriers and ensure equitable access to support and resources for all patients, enabling them to lead healthy and fulfilling lives.

Keywords: childhood, schizophrenia, policy, United, States, health, disparities

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Authors: Abdullah A. Al Qurashi, Hattan A. Hassani, Bader K. Alaslap

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Arrhythmogenic Right Ventricular Dysplasia/Cardiomyopathy (ARVD/C) is an uncommon, inheritable cardiac disorder characterized by the progressive substitution of cardiac myocytes by fibro-fatty tissues. This pathologic substitution predisposes patients to ventricular arrhythmias and right ventricular failure. The underlying genetic defect predominantly involves genes encoding for desmosome proteins, particularly plakophilin-2 (PKP2). These aberrations lead to impaired cell adhesion, heightening the susceptibility to fibrofatty scarring under conditions of mechanical stress. Primarily, ARVD/C affects the right ventricle, but it can also compromise the left ventricle, potentially leading to biventricular heart failure. Clinical presentations can vary, spanning from asymptomatic individuals to those experiencing palpitations, syncopal episodes, and, in severe instances, sudden cardiac death. The establishment of a diagnostic criterion specifically tailored for ARVD/C significantly aids in its accurate diagnosis. Nevertheless, the task of early diagnosis is complicated by the disease's frequently asymptomatic initial stages, and the overall rarity of ARVD/C cases reported globally. In some cases, as exemplified by the adult female patient in this report, the disease may advance to terminal stages, rendering therapies like Ventricular Tachycardia (VT) ablation ineffective. This case underlines the necessity for increased awareness and understanding of ARVD/C to aid in its early detection and management. Through such efforts, we aim to decrease morbidity and mortality associated with this challenging cardiac disorder.

Keywords: arrhythmogenic right ventricular dysplasia, cardiac disease, interventional cardiology, cardiac electrophysiology

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Authors: Argyris Karapetsas, Maria Bampou, Andriani Mitropoulou

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The aim of the present work is to study the role of brain function in social awareness processing. Mind controls all the psychosomatic functions. Mind’s functioning enables individual not only to recognize one's own self and propositional attitudes, but also to assign such attitudes to other individuals, and to consider such observed mental states in the elucidation of behavior. Participants and Methods: Twenty (n=20) undergraduate students (mean age 18 years old) were involved in this study. Students participated in a clinical assessment, being conducted in Laboratory of Neuropsychology, at University of Thessaly, in Volos, Greece. Assessment included both electrophysiological (i.e.Event Related Potentials (ERPs) esp.P300 waveform) and neuropsychological tests (Raven's Progressive Matrices (RPM) and Sally-Anne test). Results: Initial assessment’s results confirmed statistically significant differences between the males and females, as well as in score performance to the tests applied. Strong correlations emerged between prefrontal lobe functioning, RPM, Sally-Anne test and P300 latencies. Also, significant dysfunction of mind has been found, regarding its three dimensions (straight, circular and helical). At the end of the assessment, students received consultation and appropriate guidelines in order to improve their intrapersonal and interpersonal skills. Conclusions: Mind and social awareness phenomena play a vital role in human development and may act as determinants of the quality of one’s own life. Meanwhile, brain function is highly correlated with social awareness and it seems that different set of brain structures are involved in social behavior.

Keywords: brain activity, emotions, ERP's, social awareness

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Authors: Fajar Ajie Setiawan, Ratu Azima Mayangsari, Bunga Aprilia

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The emergence of creative hubs around the world, including in Bandung, was primarily driven by the needs of collaborative-innovative spaces for creative industry activities such as the Maker Movement and the Coworking Movement. These activities pose challenges for identification and formulation of sets of indicators for modeling creative hubs in Bandung to help stakeholders in formulating strategies. This study intends to identify their characteristics. This research was conducted using a qualitative approach comparing three concepts of creative hub categorization and integrating them into a single instrument to analyze 12 selected creative hubs. Our results showed three new functions of creative hubs in Bandung: (1) cultural, (2) retail business, and (3) community network. Results also suggest that creative hubs in Bandung are commonly established for networking and community activities. Another result shows that there was a shifting pattern of creative hubs before the 2000s and after the 2000s, which also creates a hybrid group of creative hubs.

Keywords: creative industry, creative hubs, Ngariung, Bandung

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Authors: Erjola Reufi, Jozefita Marku, Thomas Bier

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Ultrasonic pulse velocity (UPV) method has been shown for some time to provide a reliable means of estimating properties and offers a unique opportunity for direct, quick and safe control of building damaged by earthquake, fatigue, conflagration and catastrophic scenarios. On this investigation hybrid reinforced concrete has been investigated by UPV method. Hooked end steel fiber of length 50 and 30 mm was added to concrete in different proportion 0, 0.25, 0.5, and 1 % by the volume of concrete. On the other hand, polypropylene fiber of length 12, 6, 3 mm was added to concrete of 0.1, 0.2, and 0.4 % by the volume of concrete. Fifteen different mixture has been prepared to investigate the relation between compressive strength and UPV values and also to investigate on the effect of volume and type of fiber on UPV values.

Keywords: compressive strength, polypropylene fiber, steel fiber, ultrasonic pulse velocity, volume, type of fiber

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Authors: Jazim Sohail, Filipe Teixeira-Dias

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Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

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Authors: Tarek Aboueldahab, Hanan Farag

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Parallel Job Shop Scheduling Problem (JSP) is a multi-objective and multi constrains NP- optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution, so we propose a hybrid Artificial Intelligence model (AI) with Discrete Breeding Swarm (DBS) added to traditional Artificial Intelligence to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization.

Keywords: parallel job shop scheduling problem, artificial intelligence, discrete breeding swarm, car sequencing and operator allocation, cost minimization

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Authors: Mohammad Moezzibadi, Isabelle Charpentier, Adrien Wanko, Robert Mosé

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The calibration of hydrodynamic parameters for subsurface constructed wetlands (CWs) is a sensitive process since highly non-linear equations are involved in unsaturated flow modeling. CW systems are engineered systems designed to favour natural treatment processes involving wetland vegetation, soil, and their microbial flora. Their significant efficiency at reducing the ecological impact of urban runoff has been recently proved in the field. Numerical flow modeling in a vertical variably saturated CW is here carried out by implementing the Richards model by means of a mixed hybrid finite element method (MHFEM), particularly well adapted to the simulation of heterogeneous media, and the van Genuchten-Mualem parametrization. For validation purposes, MHFEM results were compared to those of HYDRUS (a software based on a finite element discretization). As van Genuchten-Mualem soil hydrodynamic parameters depend on water content, their estimation is subject to considerable experimental and numerical studies. In particular, the sensitivity analysis performed with respect to the van Genuchten-Mualem parameters reveals a predominant influence of the shape parameters α, n and the saturated conductivity of the filter on the piezometric heads, during saturation and desaturation. Modeling issues arise when the soil reaches oven-dry conditions. A particular attention should also be brought to boundary condition modeling (surface ponding or evaporation) to be able to tackle different sequences of rainfall-runoff events. For proper parameter identification, large field datasets would be needed. As these are usually not available, notably due to the randomness of the storm events, we thus propose a simple, robust and low-cost numerical method for the inverse modeling of the soil hydrodynamic properties. Among the methods, the variational data assimilation technique introduced by Le Dimet and Talagrand is applied. To that end, a variational data assimilation technique is implemented by applying automatic differentiation (AD) to augment computer codes with derivative computations. Note that very little effort is needed to obtain the differentiated code using the on-line Tapenade AD engine. Field data are collected for a three-layered CW located in Strasbourg (Alsace, France) at the water edge of the urban water stream Ostwaldergraben, during several months. Identification experiments are conducted by comparing measured and computed piezometric head by means of the least square objective function. The temporal variability of hydrodynamic parameter is then assessed and analyzed.

Keywords: automatic differentiation, constructed wetland, inverse method, mixed hybrid FEM, sensitivity analysis

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Authors: Noritaka Shigei, Kazuto Matsumoto, Yoshiki Nakashima, Hiromi Miyajima

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Although Mobile Wireless Sensor Networks (MWSNs), which consist of mobile sensor nodes (MSNs), can cover a wide range of observation region by using a small number of sensor nodes, they need to construct a network to collect the sensing data on the base station by moving the MSNs. As an effective method, the network construction method based on Virtual Rails (VRs), which is referred to as VR method, has been proposed. In this paper, we propose two types of effective techniques for the VR method. They can prolong the operation time of the network, which is limited by the battery capabilities of MSNs and the energy consumption of MSNs. The first technique, an effective arrangement of VRs, almost equalizes the number of MSNs belonging to each VR. The second technique, an adaptive movement method of MSNs, takes into account the residual energy of battery. In the simulation, we demonstrate that each technique can improve the network lifetime and the combination of both techniques is the most effective.

Keywords: mobile sensor node, relay of sensing data, residual energy, virtual rail, wireless sensor network

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Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

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Authors: Lojaine Okacha

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In the past half-century, researchers started paying attention to enhancing the performance of urban spaces. Their idea of performance comprised urban climate performance, space synthesis, economic performance, and enhancing the quality of life in space. However, they all agreed that the key to achieving any of the previously mentioned development projects is good governance. Having good governance allows citizens to participate freely in the urbanization or development projects within cities. Consequently, using the city resources and assets as efficiently as possible, and ensures the fulfillment of the users’ needs and requests. This paper aims to propose an effective participation framework to help citizens have their voices heard and participate in the decisions that will affect their living situation. The framework allows governments to use their public resources to their best. However, this study focuses on public participation in third-world countries with unitary decentralized governance systems such as Egypt. It summarizes the challenges facing the participation practices, identifies the keys to a successful participation process, and draws on dominant effective participation practice lying on the relationship between the levels of participation, stakeholders participating, the urban development stages, the city-systems, and participation process. These components are integrated to create a real-world effective participation Framework. The results of the analysis were incredible and produced a functional and progressive approach for effective public participation to introduce to the governments. The model itself is combined with additional principles allowing the best practice to the process. The framework is finally compared with a real case of urban development.

Keywords: public participation, good governance, urban development, city systems

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Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

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Authors: H. Sezgin, O. B. Berkalp, R. Mishra, J. Militky

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In the last few decades, due to their advanced properties, there has been an increasing interest in hybrid composite materials. In this study, the effect of different stacking sequences of jute and carbon fabric plies on dynamic mechanical properties of composite laminates were investigated. Vacuum bagging system was used to fabricate the composite samples. Each composite laminate was reinforced with two plies of jute fabric and two plies of carbon fabric by varying the position of layers. Dynamic mechanical analyzer (DMA) was used to examine the dynamic mechanical properties of composite laminates with increasing temperature. Results showed that the composite sample, which has carbon fabric at the outer layers, has the highest storage and loss modulus. Besides, it was observed that glass transition temperature (T_g) of samples are close to each other and at about 75 °C.

Keywords: differential scanning calorimetry dynamic mechanical analysis, textile reinforced composites, thermogravimetric analysis

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Authors: Moaine Jebara, Lionel Boillereaux, Sofiane Belhabib, Michel Havet, Alain Sarda, Pierre Mousseau, Rémi Deterre

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Energy consumption efficiency is a major concern for the material processing industry such as thermoforming process and molding. Indeed, these systems should deliver the right amount of energy at the right time to the processed material. Recent technical development, as well as the particularities of the heating system dynamics, made the Model Predictive Control (MPC) one of the best candidates for thermal control of several production processes like molding and composite thermoforming to name a few. The main principle of this technique is to use a dynamic model of the process inside the controller in real time in order to anticipate the future behavior of the process which allows the current timeslot to be optimized while taking future timeslots into account. This study presents a procedure based on a predictive control that brings balance between optimality, simplicity, and flexibility of its implementation. The development of this approach is progressive starting from the case of a single zone before its extension to the multizone and/or multisource case, taking thus into account the thermal couplings between the adjacent zones. After a quadratic formulation of the MPC criterion to ensure the thermal control, the linear expression is retained in order to reduce calculation time thanks to the use of the ARMAX linear decomposition methods. The effectiveness of this approach is illustrated by experiment and simulation.

Keywords: energy efficiency, linear decomposition methods, model predictive control, mold heating systems

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Authors: Yousif Mohamed Y. Abdallah, Razan Manofely, Rajab M. Ben Yousef

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X-Ray images are very popular as a first tool for diagnosis. Automating the process of analysis of such images is important in order to help physician procedures. In this practice, teeth segmentation from the radiographic images and feature extraction are essential steps. The main objective of this study was to study correction preprocessing of x-rays images using local adaptive filters in order to evaluate contrast enhancement pattern in different x-rays images such as grey color and to evaluate the usage of new nonlinear approach for contrast enhancement of soft tissues in x-rays images. The data analyzed by using MatLab program to enhance the contrast within the soft tissues, the gray levels in both enhanced and unenhanced images and noise variance. The main techniques of enhancement used in this study were contrast enhancement filtering and deblurring images using the blind deconvolution algorithm. In this paper, prominent constraints are firstly preservation of image's overall look; secondly, preservation of the diagnostic content in the image and thirdly detection of small low contrast details in diagnostic content of the image.

Keywords: enhancement, x-rays, pixel intensity values, MatLab

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Authors: R. Vigneswaran, S. Thilakanathan

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Variable time-stepping algorithms for solving dynamical systems performed poorly for long time computations which pass close to a fixed point. To overcome this difficulty, several authors considered phase space error controls for numerical simulation of dynamical systems. In one generalized phase space error control, a step-size selection scheme was proposed, which allows this error control to be incorporated into the standard adaptive algorithm as an extra constraint at negligible extra computational cost. For this generalized error control, it was already analyzed the forward Euler method applied to the linear system whose coefficient matrix has real and negative eigenvalues. In this paper, this result was extended to the linear system whose coefficient matrix has complex eigenvalues with negative real parts. Some theoretical results were obtained and numerical experiments were carried out to support the theoretical results.

Keywords: adaptivity, fixed point, long time simulations, stability, linear system

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Authors: Rajkumar Ghosh

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The Sutlej River Valley in Himachal Pradesh, India, is home to four Out-of-Sequence Thrusts (OOST) in the Higher Himalaya. These OOSTs include Jhakri Thrust (JT), Sarahan Thrust (ST), Chaura Thrust (CT), and Jeori Dislocation (JD). The study focuses on the rock types of these OOSTs, including ductile sheared gneisses and upper greenschist-amphibolite facies metamorphosed schists. Microstructural tests reveal a progressive increase in strain approaching the Jakhri thrust zone, with temperatures increasing from 400 to 750°C. The Chaura Thrust is assumed to be folded with this anticlinorium, with various branches that make up the thrust system. Fieldwork and microstructural research have revealed the following: (a) initial top-to-SW sense of ductile shearing (Chaura thrust); (b) brittle-ductile extension (Jeori Dislocation); and (c) uniform top-to-SW sense of brittle shearing (Jhakri thrust). Samples of Rampur Quartzite from the Rampur Group of Lesser Himalayan Crystalline and schistose rock from the Jutogh Group of Greater Himalayan Crystalline were examined.The study emphasizes the value of microscopic research in detecting different types of crenulated schistosity and documenting mylonitized zones. The paper explains the field evidence for the OOST and comes to the conclusion that the Chaura Thrust is not a blind thrust. The paper describes the box fold and its characteristics in the Himachal Himalayan regional geology.

Keywords: Out-of-sequence thrust (OOST), jakhri thrust (JT), sarahan thrust (ST), chaura thrust (CT), jeori dislocation (JD)

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

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In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: Tzu-Ping Lin, Shing-Ru Yang

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Climate change has a significant impact on human living environment, while the traditional settlement may suffer extreme thermal stress due to its specific building type and living behavior. This study selected Lutaoyang, which is the largest settlement in mountainous areas of Tainan County, for the investigation area. The microclimate parameters, such as air temperature, relative humidity, wind speed, and mean radiant temperature. The micro climate parameters were also simulated by the ENVI-met model. The results showed the banyan tree area providing good thermal comfort condition due to the shading. On the contrary, the courtyard (traditionally for the crops drying) surrounded by low rise building and consisted of artificial pavement contributing heat stress especially in summer noon. In the climate change simulations, the courtyard will become very hot and are not suitable for residents activities. These analytical results will shed light on the sustainability related to thermal environment in traditional settlements and develop adaptive measure towards sustainable development under the climate change challenges.

Keywords: thermal environment, traditional settlement, ENVI-met, Taiwan

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Authors: S. Jaramillo, Y. Montoya, W. Agudelo, J. Bustamante

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Cardiovascular diseases (CVD) are related to affectations of the heart and blood vessels, within these are pathologies such as coronary or peripheral heart disease, caused by the narrowing of the vessel wall (atherosclerosis), which is related to the accumulation of Low-Density Lipoproteins (LDL) in the arterial walls that leads to a progressive reduction of the lumen of the vessel and alterations in blood perfusion. Currently, the main therapeutic strategy for this type of alteration is drug treatment with statins, which inhibit the enzyme 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMG-CoA reductase), responsible for modulating the rate of cholesterol production and other isoprenoids in the mevalonate pathway. This enzyme induces the expression of LDL receptors in the liver, increasing their number on the surface of liver cells, reducing the plasma concentration of cholesterol. On the other hand, when the blood vessel presents stenosis, a surgical procedure with vascular implants is indicated, which are used to restore circulation in the arterial or venous bed. Among the materials used for the development of vascular implants are Dacron® and Teflon®, which perform the function of re-waterproofing the circulatory circuit, but due to their low biocompatibility, they do not have the ability to promote remodeling and tissue regeneration processes. Based on this, the present research proposes the development of a hydrolyzed collagen and polyethylene oxide electrospun membrane reinforced with medium and high-intensity statins, so that in future research it can favor tissue remodeling processes from its microarchitecture.

Keywords: atherosclerosis, medium and high-intensity statins, microarchitecture, electrospun membrane

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Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.

Keywords: hybrid MAC protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node dataprocessing, Z-MAC

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Authors: Sundaram Chandrasekaran, Seung Hyun Hur

Abstract:

Exploring strategies for oxygen vacancy engineering under mild conditions and understanding the relationship between dislocations and photoelectrochemical (PEC) cell performance are challenging issues for designing high performance PEC devices. Therefore, it is very important to understand that how the oxygen vacancies (VO) or other defect states affect the performance of the photocatalyst in photoelectric transfer. So far, it has been found that defects in nano or micro crystals can have two possible significances on the PEC performance. Firstly, an electron-hole pair produced at the interface of photoelectrode and electrolyte can recombine at the defect centers under illumination of light, thereby reducing the PEC performances. On the other hand, the defects could lead to a higher light absorption in the longer wavelength region and may act as energy centers for the water splitting reaction that can improve the PEC performances. Even if the dislocation growth of ZnO has been verified by the full density functional theory (DFT) calculations and local density approximation calculations (LDA), it requires further studies to correlate the structures of ZnO and PEC performances. Exploring the hybrid structures composed of graphene oxide (GO) and ZnO nanostructures offer not only the vision of how the complex structure form from a simple starting materials but also the tools to improve PEC performances by understanding the underlying mechanisms of mutual interactions. As there are few studies for the ZnO growth with other materials and the growth mechanism in those cases has not been clearly explored yet, it is very important to understand the fundamental growth process of nanomaterials with the specific materials, so that rational and controllable syntheses of efficient ZnO-based hybrid materials can be designed to prepare nanostructures that can exhibit significant PEC performances. Herein, we fabricated various ZnO nanostructures such as hollow sphere, bucky bowl, nanorod and triangle, investigated their pH dependent growth mechanism, and correlated the PEC performances with them. Especially, the origin of well-controlled dislocation-driven growth and its transformation mechanism of ZnO nanorods to triangles on the GO surface were discussed in detail. Surprisingly, the addition of GO during the synthesis process not only tunes the morphology of ZnO nanocrystals and also creates more oxygen vacancies (oxygen defects) in the lattice of ZnO, which obviously suggest that the oxygen vacancies be created by the redox reaction between GO and ZnO in which the surface oxygen is extracted from the surface of ZnO by the functional groups of GO. On the basis of our experimental and theoretical analysis, the detailed mechanism for the formation of specific structural shapes and oxygen vacancies via dislocation, and its impact in PEC performances are explored. In water splitting performance, the maximum photocurrent density of GO-ZnO triangles was 1.517mA/cm-2 (under UV light ~ 360 nm) vs. RHE with high incident photon to current conversion Efficiency (IPCE) of 10.41%, which is the highest among all samples fabricated in this study and also one of the highest IPCE reported so far obtained from GO-ZnO triangular shaped photocatalyst.

Keywords: dislocation driven growth, zinc oxide, graphene oxide, water splitting

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Authors: M. Sangeetha, D. Chamundeeswari, C. Saravanababu, C. Rose, V. Gopal

Abstract:

Rheumatoid arthritis (RA) is a chronic, progressive, systemic inflammatory disorder affecting the synovial joints and typically producing symmetrical arthritis that leads to joint destruction, which is responsible for the deformity and disability. Despite improvements in the treatment of RA over the past decade, there still is a need for new therapeutic agents that are efficacious, less expensive, and free of severe adverse reactions. The present study aimed to investigate role of inflammatory markers in arthritic rats treated with ethanolic bark extract of Albizia procera. The protective effect of ethanolic bark extract of Albizia procera against complete Freund’s adjuvant (CFA) induced arthritis in rats. Arthritis was induced by an intradermal injection of 0.1 ml FCA in the foot pad of left hind limb of rats. ETBE (100 and 200 mg/kg b.wt./p.o) and the reference drug diclofenac (25 mg/kg b.wt./p.o) were administered to arthritic rats. Paw volume was measured for all the animals before inducing arthritis and thereafter once in seven days by using plethysmometer for 42 days. Gene expression of inflammatory markers such as IL-1β and IL-10 were investigated in paw tissues. Up regulation of IL-1β and Down regulation IL-10 were observed in CFA injected rats when compared to normal rats. ETBE attenuated these alterations dose dependently when compared to the vehicle treated rats. These results provide insights into the mechanism of anti-arthritic activity, and unravel potential therapeutic use of Albizia procera in arthritis.

Keywords: CFA-Complete Freund’s adjuvant, ETBE – ethanolic bark extract, IL- interleukins, RA-rheumatoid arthritis

Procedia PDF Downloads 283

Authors: Vishwambhar Prasad Sati

Abstract:

India’s economy is agriculture dominated. About 70% of the total population depends on practicing agriculture. Out of an estimated 140.3 million ha net cultivated area, 79.44 million ha (57%) is rain-fed, contributing 44% of the total food grain production. Meanwhile, India ranks second and shares 11.3% of the arable land of the world. It means that India has a high potential to harness agricultural resources for present and future food security. However, about 21.9% of people are living below the poverty line, and similarly, a large number of people are deprived or insecure about food. This situation is most critical in rural areas, where about 70% population lives. The study examines the present status, future trends, and challenges of food and agriculture in India. Time series data of the last three decades was gathered from secondary sources on area, production, and yield of crops; irrigated area; production of major crops; area, production, and yield of crops in the major food-producing states of India; food storage and poverty. The data were analyzed using descriptive statistics, correlation methods, and a regression model. State-level data on area, production, and yield of crops and irrigation facilities were indexed into levels, and the potentials of food production in the major food-producing states were observed. It was noted that the progressive growth rate of food production is higher than the population, which means that food is enough to feed the population; however, it is not accessible to all optimally because of wastage, leakage, lack of food storage, and proper distribution of food. If food is stored and distributed properly, there would not be any food shortage in India, the study revealed.

Keywords: agriculture, food production, population growth, poverty, future trends

Procedia PDF Downloads 99

Authors: Valentina Narvaez Gaitan, Paula K. Rodriguez Ramirez, Derian D. Espinosa

Abstract:

Corrective orthosis has great importance in orthopedic treatments providing assistance in improving mobility and stability in order to improve the quality of life for a different patient. The corrective orthosis studied in this article can correct deformities, reduce pain, and improve the ability to perform daily activities. This work describes the design and evaluation of a corrective orthosis for knee hyperextension. This orthosis is capable of generating a progressive and variable alignment of the joint, limiting the range of motion according to medical criteria. The main objective was to design a corrective knee orthosis capable of correcting knee hyperextension progressively to return to its natural angle with greater economic affordability and adjustable size. The limiting mechanism is based on a goniometer to determine the desired angles. The orthosis was made of acrylic to reduce costs and maintenance; neoprene is also used to make comfortable contact; additionally, Velcro was used in order to adjust the orthosis for various sizes. Simulations of static and fatigue analysis of the mechanism were performed to verify its resistance and durability under normal conditions. A biomechanical gait study of gait was carried out on 10 healthy subjects without the orthosis and limiting their knee extension capacity in a normal gait cycle with the orthosis to observe the efficiency of the proposed system. In the results obtained, the knee angle curves show that the maximum extension angle was the established angle by the orthosis. Showing the efficiency of the proposed design for different leg sizes.

Keywords: biomechanical study, corrective orthosis, efficiency, goniometer, knee hyperextension.

Procedia PDF Downloads 76

Authors: A. G. Miah, U. Salma, K. Schellander

Abstract:

Relaxin was first described in 1926 by Frederick Hisaw. Previously it was considered as only the hormone of pregnant mammals due to its important roles in pregnancy and parturition. From the last decade, the physiological role of relaxin in male reproduction has been given experimental attention, and the results have made it clear that relaxin can no longer be considered strictly as only the hormone of female reproduction. The accessory glands (specially, the prostate glands) of the male reproductive system are the source of seminal relaxin, which is secreted into the seminal plasma and saturated with spermatozoa just after ejaculation. Several studies have reported that relaxin has important roles in improving motility in human sperm. Thereafter, the growing interest on relaxin has intensified efforts to investigate the role of relaxin in other sperm physiological phenomena like, capacitation, acrosome reaction, and their mediating factors associated with successful fertilization. Therefore, this review aims to provide up-to-date information about the physiological roles of relaxin in sperm motility, capacitation, acrosome reaction, and their mediating factors, such as, utilization of glucose, cholesterol efflux, Ca2+-influx, intracellular cAMP and protein tyrosine phosphorylation. Some studies have shown relaxin to increase the percentage of progressive motility and induce capacitation and acrosome reaction through increasing the utilization of glucose and mediating the cholesterol efflux, Ca2+-influx, intracellular cAMP and protein tyrosine phosphorylation. Thus, the review suggests that the supplementation of relaxin into the capacitating medium may contribute the possible beneficial roles in fresh and cryopreserved spermatozoal prefertilization events.

Keywords: relaxin, physiological roles, prefertilizing activities, spermatozoa

Procedia PDF Downloads 567