Search results for: performance prism model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 25968

Search results for: performance prism model

17478 Experimental Investigation of the Thermal Performance of Fe2O3 under Magnetic Field in an Oscillating Heat Pipe

Authors: H. R. Goshayeshi, M. Khalouei, S. Azarberamman

Abstract:

This paper presents an experimental investigation regarding the use of Fe2O3 nano particles added to kerosene as a working fluid, under magnetic field. The experiment was made on Oscillating Heat Pipe (OHP). The experiment was performed in order to measure the temperature distribution and compare the heat transfer rate of the oscillating heat pipe with and without magnetic Field. Results showed that the addition of Fe2o3 nano particles under magnetic field improved thermal performance of OHP, compare with non-magnetic field. Furthermore applying a magnetic field enhance the heat transfer characteristic of Fe2O3 in both start up and steady state conditions. This paper presents an experimental investigation regarding the use of Fe2O3 nano particles added to kerosene as a working fluid, under magnetic field. The experiment was made on Oscillating Heat Pipe (OHP). The experiment was performed in order to measure the temperature distribution and compare the heat transfer rate of the oscillating heat pipe with and without magnetic Field. Results showed that the addition of Fe2o3 nano particles under magnetic field improved thermal performance of OHP, compare with non-magnetic field. Furthermore applying a magnetic field enhance the heat transfer characteristic of Fe2O3 in both start up and steady state conditions.

Keywords: experimental, oscillating heat pipe, heat transfer, magnetic field

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17477 Priming through Open Book MCQ Test: A Tool for Enhancing Learning in Medical Undergraduates

Authors: Bharti Bhandari, Bharati Mehta, Sabyasachi Sircar

Abstract:

Medical education is advancing in India, with its advancement newer innovations are being incorporated in teaching and assessment methodology. Our study focusses on a teaching innovation that is more student-centric than teacher-centric and is the need of the day. The teaching innovation was carried out in 1st year MBBS students of our institute. Students were assigned control and test groups. Priming was done for the students in the test group with an open-book MCQ based test in a particular topic before delivering formal didactic lecture on that topic. The control group was not assigned any such exercise. This was followed by formal didactic lecture on the same topic. Thereafter, both groups were assessed on the same topic. The marks were compiled and analysed using appropriate statistical tests. Students were also given questionnaire to elicit their views on the benefits of “self-priming”. The mean marks scored in theory assessment by the test group were statistically higher than the marks scored by the controls. According to students’ feedback, the ‘self-priming “process was interesting, helped in better orientation during class-room lectures and better understanding of the topic. They want it to be repeated for other topics with moderate difficulty level. Better performance of the students in the primed group validates the combination of student-centric priming model and didactic lecture as superior to the conventional, teacher-centric methods alone. If this system is successfully followed, the present teacher-centric pedagogy should increasingly give way to student-centric activities where the teacher is only a facilitator.

Keywords: medical education, open-book test, pedagogy, priming

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17476 GGE-Biplot Analysis of Nano-Titanium Dioxide and Nano-Silica Effects on Sunflower

Authors: Naser Sabaghnia, Mohsen Janmohammadi, Mehdi Mohebodini

Abstract:

Present investigation is performed to evaluate the effects of foliar application of salicylic acid, glycine betaine, ascorbic acid, nano-silica, and nano-titanium dioxide on sunflower. Results showed that the first two principal components were sufficient to create a two-dimensional treatment by trait biplot, and such biplot accounted percentages of 49% and 19%, respectively of the interaction between traits and treatments. The vertex treatments of polygon were ascorbic acid, glycine betaine, nano-TiO2, and control indicated that high performance in some important traits consists of number of days to seed maturity, number of seeds per head, number heads per single plant, hundred seed weight, seed length, seed yield performance, and oil content. Treatments suitable for obtaining the high seed yield were identified in the vector-view function of biplot and displayed nano-silica and nano titanium dioxide as the best treatments suitable for obtaining of high seed yield.

Keywords: drought stress, nano-silicon dioxide, oil content, TiO2 nanoparticles

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17475 A 3d Intestine-On-Chip Model Allows Colonization with Commensal Bacteria to Study Host-Microbiota Interaction

Authors: Michelle Maurer, Antonia Last, Mark S. Gresnigt, Bernhard Hube, Alexander S. Mosig

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The intestinal epithelium forms an essential barrier to prevent translocation of microorganisms, toxins or other potentially harmful molecules into the bloodstream. In particular, dendritic cells of the intestinal epithelium orchestrate an adapted response of immune tolerance to commensals and immune defense against invading pathogens. Systemic inflammation is typically associated with a dysregulation of this adapted immune response and is accompanied by a disruption of the epithelial and endothelial gut barrier which enables dissemination of pathogens within the human body. To understand the pathophysiological mechanisms underlying the inflammation-associated gut barrier breakdown, it is crucial to elucidate the complex interplay of the host and the intestinal microbiome. A microfluidically perfused three-dimensional intestine-on-chip model was established to emulate these processes in the presence of immune cells, commensal bacteria, and facultative pathogens. Multi-organ tissue flow (MOTiF) biochips made from polystyrene were used for microfluidic perfusion of the intestinal tissue model. The biochips are composed of two chambers separated by a microporous membrane. Each chamber is connected to inlet and outlet channels allowing independent perfusion of the individual channels and application of microfluidic shear stress. Human umbilical vein endothelial cells (HUVECs), monocyte-derived macrophages and intestinal epithelial cells (Caco-2) were assembled on the biochip membrane. Following 7 – 14 days of growth in the presence of physiological flow conditions, the epithelium was colonized with the commensal bacterium Lactobacillus rhamnosus, while the endothelium was perfused with peripheral blood mononuclear cells (PBMCs). Additionally, L. rhamnosus was co-cultivated with the opportunistic fungal pathogen Candida albicans. Within one week of perfusion, the epithelial cells formed self-organized and well-polarized villus- and crypt-like structures that resemble essential morphological characteristics of the human intestine. Dendritic cells were differentiated in the epithelial tissue that specifically responds to bacterial lipopolysaccharide (LPS) challenge. LPS is well-tolerated at the luminal epithelial side of the intestinal model without signs of tissue damage or induction of an inflammatory response, even in the presence of circulating PBMC at the endothelial lining. In contrast, LPS stimulation at the endothelial side of the intestinal model triggered the release of pro-inflammatory cytokines such as TNF, IL-1β, IL-6, and IL-8 via activation of macrophages residing in the endothelium. Perfusion of the endothelium with PBMCs led to an enhanced cytokine release. L. rhamnosus colonization of the model was tolerated in the immune competent tissue model and was demonstrated to reduce damage induced by C. albicans infection. A microfluidic intestine-on-chip model was developed to mimic a systemic infection with a dysregulated immune response under physiological conditions. The model facilitates the colonization of commensal bacteria and co-cultivation with facultative pathogenic microorganisms. Both, commensal bacteria alone and facultative pathogens controlled by commensals, are tolerated by the host and contribute to cell signaling. The human intestine-on-chip model represents a promising tool to mimic microphysiological conditions of the human intestine and paves the way for more detailed in vitro studies of host-microbiota interactions under physiologically relevant conditions.

Keywords: host-microbiota interaction, immune tolerance, microfluidics, organ-on-chip

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17474 Design and Analysis of Crankshaft Using Al-Al2O3 Composite Material

Authors: Palanisamy Samyraj, Sriram Yogesh, Kishore Kumar, Vaishak Cibi

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The project is about design and analysis of crankshaft using Al-Al2O3 composite material. The project is mainly concentrated across two areas one is to design and analyze the composite material, and the other is to work on the practical model. Growing competition and the growing concern for the environment has forced the automobile manufactures to meet conflicting demands such as increased power and performance, lower fuel consumption, lower pollution emission and decrease noise and vibration. Metal matrix composites offer good properties for a number of automotive components. The work reports on studies on Al-Al2O3 as the possible alternative material for a crank shaft. These material have been considered for use in various components in engines due to the high amount of strength to weight ratio. These materials are significantly taken into account for their light weight, high strength, high specific modulus, low co-efficient of thermal expansion, good air resistance properties. In addition high specific stiffness, superior high temperature, mechanical properties and oxidation resistance of Al2O3 have developed some advanced materials that are Al-Al2O3 composites. Crankshafts are used in automobile industries. Crankshaft is connected to the connecting rod for the movement of the piston which is subjected to high stresses which cause the wear of the crankshaft. Hence using composite material in crankshaft gives good fuel efficiency, low manufacturing cost, less weight.

Keywords: metal matrix composites, Al-Al2O3, high specific modulus, strength to weight ratio

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17473 Designing an Enterprise Architecture for Mining Company by Using Togaf Framework

Authors: Rika Yuliana, Budi Rahardjo

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The Role of ICT in the organization will continue to experience growth in line with business growth. However, in reality, there is a gap between ICT initiatives with the development (needs) of company business that is caused by yet inadequate of ICT strategic alignment. Therefore, this study was conducted with the aim to create an enterprise architectural model rule, particularly in mining companies, using the TOGAF framework. The results from the design development phase of the mining enterprise architecture meta model represents the domain of business, applications, data, and technology. The results of the design as a whole were analyzed from four perspectives, namely the perspective of contextual, conceptual, logical and physical. In the end, the quality assessment of the mining enterprise architecture is conducted to assess the suitability of the design standards and architectural principles.

Keywords: design and development the information technology architecture, enterprise architecture, enterprise architecture design result, TOGAF architecture development method (ADM)

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17472 The Relationship between Coping Styles and Internet Addiction among High School Students

Authors: Adil Kaval, Digdem Muge Siyez

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With the negative effects of internet use in a person's life, the use of the Internet has become an issue. This subject was mostly considered as internet addiction, and it was investigated. In literature, it is noteworthy that some theoretical models have been proposed to explain the reasons for internet addiction. In addition to these theoretical models, it may be thought that the coping style for stressing events can be a predictor of internet addiction. It was aimed to test with logistic regression the effect of high school students' coping styles on internet addiction levels. Sample of the study consisted of 770 Turkish adolescents (471 girls, 299 boys) selected from high schools in the 2017-2018 academic year in İzmir province. Internet Addiction Test, Coping Scale for Child and Adolescents and a demographic information form were used in this study. The results of the logistic regression analysis indicated that the model of coping styles predicted internet addiction provides a statistically significant prediction of internet addiction. Gender does not predict whether or not to be addicted to the internet. The active coping style is not effective on internet addiction levels, while the avoiding and negative coping style are effective on internet addiction levels. With this model, % 79.1 of internet addiction in high school is estimated. The Negelkerke pseudo R2 indicated that the model accounted for %35 of the total variance. The results of this study on Turkish adolescents are similar to the results of other studies in the literature. It can be argued that avoiding and negative coping styles are important risk factors in the development of internet addiction.

Keywords: adolescents, coping, internet addiction, regression analysis

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17471 Adding a Degree of Freedom to Opinion Dynamics Models

Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Within agent-based modeling, opinion dynamics is the field that focuses on modeling people's opinions. In this prolific field, most of the literature is dedicated to the exploration of the two 'degrees of freedom' and how they impact the model’s properties (e.g., the average final opinion, the number of final clusters, etc.). These degrees of freedom are (1) the interaction rule, which determines how agents update their own opinion, and (2) the network topology, which defines the possible interaction among agents. In this work, we show that the third degree of freedom exists. This can be used to change a model's output up to 100% of its initial value or to transform two models (both from the literature) into each other. Since opinion dynamics models are representations of the real world, it is fundamental to understand how people’s opinions can be measured. Even for abstract models (i.e., not intended for the fitting of real-world data), it is important to understand if the way of numerically representing opinions is unique; and, if this is not the case, how the model dynamics would change by using different representations. The process of measuring opinions is non-trivial as it requires transforming real-world opinion (e.g., supporting most of the liberal ideals) to a number. Such a process is usually not discussed in opinion dynamics literature, but it has been intensively studied in a subfield of psychology called psychometrics. In psychometrics, opinion scales can be converted into each other, similarly to how meters can be converted to feet. Indeed, psychometrics routinely uses both linear and non-linear transformations of opinion scales. Here, we analyze how this transformation affects opinion dynamics models. We analyze this effect by using mathematical modeling and then validating our analysis with agent-based simulations. Firstly, we study the case of perfect scales. In this way, we show that scale transformations affect the model’s dynamics up to a qualitative level. This means that if two researchers use the same opinion dynamics model and even the same dataset, they could make totally different predictions just because they followed different renormalization processes. A similar situation appears if two different scales are used to measure opinions even on the same population. This effect may be as strong as providing an uncertainty of 100% on the simulation’s output (i.e., all results are possible). Still, by using perfect scales, we show that scales transformations can be used to perfectly transform one model to another. We test this using two models from the standard literature. Finally, we test the effect of scale transformation in the case of finite precision using a 7-points Likert scale. In this way, we show how a relatively small-scale transformation introduces both changes at the qualitative level (i.e., the most shared opinion at the end of the simulation) and in the number of opinion clusters. Thus, scale transformation appears to be a third degree of freedom of opinion dynamics models. This result deeply impacts both theoretical research on models' properties and on the application of models on real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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17470 Combined Effect of Heat Stimulation and Delay Addition of Superplasticizer with Slag on Fresh and Hardened Property of Mortar

Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro

Abstract:

The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.

Keywords: NARX (Nonlinear Autoregressive Exogenous Model), prediction, stock market, time series

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17469 Numerical Investigation of Fluid Outflow through a Retinal Hole after Scleral Buckling

Authors: T. Walczak, J. K. Grabski, P. Fritzkowski, M. Stopa

Abstract:

Objectives of the study are i) to perform numerical simulations that permit an analysis of the dynamics of subretinal fluid when an implant has induced scleral intussusception and ii) assess the impact of the physical parameters of the model on the flow rate. Computer simulations were created using finite element method (FEM) based on a model that takes into account the interaction of a viscous fluid (subretinal fluid) with a hyperelastic body (retina). The purpose of the calculation was to investigate the dependence of the flow rate of subretinal fluid through a hole in the retina on different factors such as viscosity of subretinal fluid, material parameters of the retina, and the offset of the implant from the retina’s hole. These simulations were performed for different speeds of eye movement that reflect the behavior of the eye when reading, REM, and saccadic movements. Similar to other works in the field of subretinal fluid flow, it was assumed stationary, single sided, forced fluid flow in the considered area simulating the subretinal space. Additionally, a hyperelastic material model of the retina and parameterized geometry of the considered model was adopted. The calculations also examined the influence the direction of the force of gravity due to the position of the patient’s head on the trend of outflow of fluid. The simulations revealed that fluid outflow from the retina becomes significant with eyeball movement speed of 100°/sec. This speed is greater than in the case of reading but is four times less than saccadic movement. The increase of viscosity of the fluid increased beneficial effect. Further, the simulation results suggest that moderate eye movement speed is optimal and that the conventional prescription of the avoidance of routine eye movement following retinal detachment surgery should be relaxed. Additionally, to verify numerical results, some calculations were repeated with use of meshless method (method of fundamental solutions), which is relatively fast and easy to implement. The paper has been supported by 02/21/DSPB/3477 grant.

Keywords: CFD simulations, FEM analysis, meshless method, retinal detachment

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17468 Land Degradation Vulnerability Modeling: A Study on Selected Micro Watersheds of West Khasi Hills Meghalaya, India

Authors: Amritee Bora, B. S. Mipun

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Land degradation is often used to describe the land environmental phenomena that reduce land’s original productivity both qualitatively and quantitatively. The study of land degradation vulnerability primarily deals with “Environmentally Sensitive Areas” (ESA) and the amount of topsoil loss due to erosion. In many studies, it is observed that the assessment of the existing status of land degradation is used to represent the vulnerability. Moreover, it is also noticed that in most studies, the primary emphasis of land degradation vulnerability is to assess its sensitivity to soil erosion only. However, the concept of land degradation vulnerability can have different objectives depending upon the perspective of the study. It shows the extent to which changes in land use land cover can imprint their effect on the land. In other words, it represents the susceptibility of a piece of land to degrade its productive quality permanently or in the long run. It is also important to mention that the vulnerability of land degradation is not a single factor outcome. It is a probability assessment to evaluate the status of land degradation and needs to consider both biophysical and human induce parameters. To avoid the complexity of the previous models in this regard, the present study has emphasized on to generate a simplified model to assess the land degradation vulnerability in terms of its current human population pressure, land use practices, and existing biophysical conditions. It is a “Mixed-Method” termed as the land degradation vulnerability index (LDVi). It was originally inspired by the MEDALUS model (Mediterranean Desertification and Land Use), 1999, and Farazadeh’s 2007 revised version of it. It has followed the guidelines of Space Application Center, Ahmedabad / Indian Space Research Organization for land degradation vulnerability. The model integrates the climatic index (Ci), vegetation index (Vi), erosion index (Ei), land utilization index (Li), population pressure index (Pi), and cover management index (CMi) by giving equal weightage to each parameter. The final result shows that the very high vulnerable zone primarily indicates three (3) prominent circumstances; land under continuous population pressure, high concentration of human settlement, and high amount of topsoil loss due to surface runoff within the study sites. As all the parameters of the model are amalgamated with equal weightage further with the help of regression analysis, the LDVi model also provides a strong grasp of each parameter and how far they are competent to trigger the land degradation process.

Keywords: population pressure, land utilization, soil erosion, land degradation vulnerability

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17467 Size Effect on Shear Strength of Slender Reinforced Concrete Beams

Authors: Subhan Ahmad, Pradeep Bhargava, Ajay Chourasia

Abstract:

Shear failure in reinforced concrete beams without shear reinforcement leads to loss of property and life since a very little or no warning occurs before failure as in case of flexural failure. Shear strength of reinforced concrete beams decreases as its depth increases. This phenomenon is generally called as the size effect. In this paper, a comparative analysis is performed to estimate the performance of shear strength models in capturing the size effect of reinforced concrete beams made with conventional concrete, self-compacting concrete, and recycled aggregate concrete. Four shear strength models that account for the size effect in shear are selected from the literature and applied on the datasets of slender reinforced concrete beams. Beams prepared with conventional concrete, self-compacting concrete, and recycled aggregate concrete are considered for the analysis. Results showed that all the four models captured the size effect in shear effectively and produced conservative estimates of the shear strength for beams made with normal strength conventional concrete. These models yielded unconservative estimates for high strength conventional concrete beams with larger effective depths ( > 450 mm). Model of Bazant and Kim (1984) captured the size effect precisely and produced conservative estimates of shear strength of self-compacting concrete beams at all the effective depths. Also, shear strength models considered in this study produced unconservative estimates of shear strength for recycled aggregate concrete beams at all effective depths.

Keywords: reinforced concrete beams; shear strength; prediction models; size effect

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17466 Modification of Fick’s First Law by Introducing the Time Delay

Authors: H. Namazi, H. T. N. Kuan

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Fick's first law relates the diffusive flux to the concentration field, by postulating that the flux goes from regions of high concentration to regions of low concentration, with a magnitude that is proportional to the concentration gradient (spatial derivative). It is clear that the diffusion of flux cannot be instantaneous and should be some time delay in this propagation. But Fick’s first law doesn’t consider this delay which results in some errors especially when there is a considerable time delay in the process. In this paper, we introduce a time delay to Fick’s first law. By this modification, we consider that the diffusion of flux cannot be instantaneous. In order to verify this claim an application sample in fluid diffusion is discussed and the results of modified Fick’s first law, Fick’s first law and the experimental results are compared. The results of this comparison stand for the accuracy of the modified model. The modified model can be used in any application where the time delay has considerable value and neglecting its effect reflects in undesirable results.

Keywords: Fick's first law, flux, diffusion, time delay, modified Fick’s first law

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17465 Development of pm2.5 Forecasting System in Seoul, South Korea Using Chemical Transport Modeling and ConvLSTM-DNN

Authors: Ji-Seok Koo, Hee‑Yong Kwon, Hui-Young Yun, Kyung-Hui Wang, Youn-Seo Koo

Abstract:

This paper presents a forecasting system for PM2.5 levels in Seoul, South Korea, leveraging a combination of chemical transport modeling and ConvLSTM-DNN machine learning technology. Exposure to PM2.5 has known detrimental impacts on public health, making its prediction crucial for establishing preventive measures. Existing forecasting models, like the Community Multiscale Air Quality (CMAQ) and Weather Research and Forecasting (WRF), are hindered by their reliance on uncertain input data, such as anthropogenic emissions and meteorological patterns, as well as certain intrinsic model limitations. The system we've developed specifically addresses these issues by integrating machine learning and using carefully selected input features that account for local and distant sources of PM2.5. In South Korea, the PM2.5 concentration is greatly influenced by both local emissions and long-range transport from China, and our model effectively captures these spatial and temporal dynamics. Our PM2.5 prediction system combines the strengths of advanced hybrid machine learning algorithms, convLSTM and DNN, to improve upon the limitations of the traditional CMAQ model. Data used in the system include forecasted information from CMAQ and WRF models, along with actual PM2.5 concentration and weather variable data from monitoring stations in China and South Korea. The system was implemented specifically for Seoul's PM2.5 forecasting.

Keywords: PM2.5 forecast, machine learning, convLSTM, DNN

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17464 Steam Reforming of Acetic Acid over Microwave-Synthesized Ce0.75Zr0.25O2 Supported Ni Catalysts

Authors: Panumard Kaewmora, Thirasak Rirksomboon, Vissanu Meeyoo

Abstract:

Due to the globally growing demands of petroleum fuel and fossil fuels, the scarcity or even depletion of fossil fuel sources could be inevitable. Alternatively, the utilization of renewable sources, such as biomass, has become attractive to the community. Biomass can be converted into bio-oil by fast pyrolysis. In water phase of bio-oil, acetic acid which is one of its main components can be converted to hydrogen with high selectivity over effective catalysts in steam reforming process. Steam reforming of acetic acid as model compound has been intensively investigated for hydrogen production using various metal oxide supported nickel catalysts and yet they seem to be rapidly deactivated depending on the support utilized. A catalyst support such as Ce1-xZrxO2 mixed oxide was proposed for alleviating this problem with the anticipation of enhancing hydrogen yield. However, catalyst preparation methods play a significant role in catalytic activity and performance of the catalysts. In this work, Ce0.75Zr0.25O2 mixed oxide solid solution support was prepared by urea hydrolysis using microwave as heat source. After that nickel metal was incorporated at 15 wt% by incipient wetness impregnation method. The catalysts were characterized by several techniques including BET, XRD, H2-TPR, XRF, SEM, and TEM as well as tested for the steam reforming of acetic acid at various operating conditions. Preliminary results showed that a hydrogen yield of ca. 32% with a relatively high acetic conversion was attained at 650°C.

Keywords: acetic acid, steam reforming, microwave, nickel, ceria, zirconia

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17463 Deep-Learning Based Approach to Facial Emotion Recognition through Convolutional Neural Network

Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

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17462 Agent-Base Modeling of IoT Applications by Using Software Product Line

Authors: Asad Abbas, Muhammad Fezan Afzal, Muhammad Latif Anjum, Muhammad Azmat

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The Internet of Things (IoT) is used to link up real objects that use the internet to interact. IoT applications allow handling and operating the equipment in accordance with environmental needs, such as transportation and healthcare. IoT devices are linked together via a number of agents that act as a middleman for communications. The operation of a heat sensor differs indoors and outside because agent applications work with environmental variables. In this article, we suggest using Software Product Line (SPL) to model IoT agents and applications' features on an XML-based basis. The contextual diversity within the same domain of application can be handled, and the reusability of features is increased by XML-based feature modelling. For the purpose of managing contextual variability, we have embraced XML for modelling IoT applications, agents, and internet-connected devices.

Keywords: IoT agents, IoT applications, software product line, feature model, XML

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17461 Solutions of Fractional Reaction-Diffusion Equations Used to Model the Growth and Spreading of Biological Species

Authors: Kamel Al-Khaled

Abstract:

Reaction-diffusion equations are commonly used in population biology to model the spread of biological species. In this paper, we propose a fractional reaction-diffusion equation, where the classical second derivative diffusion term is replaced by a fractional derivative of order less than two. Based on the symbolic computation system Mathematica, Adomian decomposition method, developed for fractional differential equations, is directly extended to derive explicit and numerical solutions of space fractional reaction-diffusion equations. The fractional derivative is described in the Caputo sense. Finally, the recent appearance of fractional reaction-diffusion equations as models in some fields such as cell biology, chemistry, physics, and finance, makes it necessary to apply the results reported here to some numerical examples.

Keywords: fractional partial differential equations, reaction-diffusion equations, adomian decomposition, biological species

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17460 Metabolome-based Profiling of African Baobab Fruit (Adansonia Digitata L.) Using a Multiplex Approach of MS and NMR Techniques in Relation to Its Biological Activity

Authors: Marwa T. Badawy, Alaa F. Bakr, Nesrine Hegazi, Mohamed A. Farag, Ahmed Abdellatif

Abstract:

Diabetes Mellitus (DM) is a chronic disease affecting a large population worldwide. Africa is rich in native medicinal plants with myriad health benefits, though less explored towards the development of specific drug therapy as in diabetes. This study aims to determine the in vivo antidiabetic potential of the well-reported and traditionally used fruits of Baobab (Adansonia digitata L.) using STZ induced diabetic model. The in-vitro cytotoxic and antioxidant properties were examined using MTT assay on L-929 fibroblast cells and DPPH antioxidant assays, respectively. The extract showed minimal cytotoxicity with an IC50 value of 105.7 µg/mL. Histopathological and immunohistochemical investigations showed the hepatoprotective and the renoprotective effects of A. digitata fruits’ extract, implying its protective effects against diabetes complications. These findings were further supported by biochemical assays, which showed that i.p., injection of a low dose (150 mg/kg) of A. digitata twice a week lowered the fasting blood glucose levels, lipid profile, hepatic and renal markers. For a comprehensive overview of extract metabolites composition, ultrahigh performance (UHPLC) analysis coupled to high-resolution tandem mass spectrometry (HRMS/MS) in synchronization with molecular networks led to the annotation of 77 metabolites, among which 50% are reported for the first time in A. digitata fruits.

Keywords: adansonia digital, diabetes mellitus, metabolomics, streptozotocin, Sprague, dawley rats

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17459 Antecedents and Loyalty of Foreign Tourists towards Attractions in Bangkok Metropolitan Area, Thailand

Authors: Arunroong Wongkungwan

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This study aimed to investigate the influence of selected antecedents, which were tourists’ satisfaction towards attractions in Bangkok, perceived value of the attractions, feelings of engagement with the attractions, acquaintance with the attractions, push factors, pull factors and motivation to seek novelty, on foreign tourist’s loyalty towards tourist attractions in Bangkok. By using multi stage sampling technique, 400 international tourists were sampled. After that, Semi Structural Equation Model was utilized in the analysis stage by LISREL. The Semi Structural Equation Model of the selected antecedents of tourist’s loyalty attractions had a correlation with the empirical data through the following statistical descriptions: Chi- square = 3.43, df = 4, P- value = 0.48893; RMSEA = 0.000; CFI = 1.00; CN = 1539.75; RMR = 0.0022; GFI = 1.00 and AGFI = 0.98. The findings indicated that all antecedents were able together to predict the loyalty of the foreign tourists who visited Bangkok at 73 percent.

Keywords: antecedent, Bangkok, foreign tourists, loyalty, tourist attractions

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17458 Adoption and Diffusion of E-Government Services in India: The Impact of User Demographics and Service Quality

Authors: Sayantan Khanra, Rojers P. Joseph

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This study attempts to analyze the impact of demography and service quality on the adoption and diffusion of e-Government services in the context of India. The objective of this paper is to study the users' perception about e-Government services and investigate the key variables that are most salient to the Indian populace. At the completion of this study, a research model that would help to understand the relationship involving the demographic variables and service quality dimensions, and the willingness to adopt e-Government services is expected to be developed. Dedicated authorities, particularly those in developing economies, may use that model or its augmented versions to design and update e-Government services and promote their use among citizens. After all, enhanced public participation is required to improve efficiency, engagement and transparency in the implementation of the aforementioned services.

Keywords: adoption and diffusion of e-government services, demographic variables, hierarchical regression analysis, service quality dimensions

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17457 Energy Saving in Handling the Air-Conditioning Latent-Load Using a Liquid Desiccant Air Conditioner: Parametric Experimental Analysis

Authors: Mustafa Jaradat

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Reasonable energy saving for dehumidification is feasible with the use of desiccants. Desiccants are able to lower the humidity content in the air irrespective of the dew point temperature. In this paper, a tube bundle liquid desiccant air conditioner was experimentally designed and evaluated using lithium chloride as a desiccant. Several experiments were conducted to evaluate the influence of the inlet parameters on the dehumidifier performance. The results show a reduction in the relative humidity in the range of 17 to 46%, and the change in the humidity ratio was between 1.5 to 4.7 g/kg, depending on the inlet conditions. A water removal rate in the range between 0.54 and 1.67 kg/h was observed. The effects of air relative humidity and the desiccant flow rate on the dehumidifier’s performance were investigated. It was found that the moisture removal rate remarkably increased with increasing desiccant flow rate and air inlet humidity ratio. The dehumidifier effectiveness increased sharply with increasing desiccant flow rate. Also, it was found that the dehumidifier effectiveness slightly decreased with air humidity ratio.

Keywords: air conditioning, dehumidification, desiccant, lithium chloride, tube bundle

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17456 Various Shaped ZnO and ZnO/Graphene Oxide Nanocomposites and Their Use in Water Splitting Reaction

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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17455 Factors Affecting Students' Performance in the Examination

Authors: Amylyn F. Labasano

Abstract:

A significant number of empirical studies are carried out to investigate factors affecting college students’ performance in the academic examination. With a wide-array of literature-and studies-supported findings, this study is limited only on the students’ probability of passing periodical exams which is associated with students’ gender, absences in the class, use of reference book, and hours of study. Binary logistic regression was the technique used in the analysis. The research is based on the students’ record and data collected through survey. The result reveals that gender, use of reference book and hours of study are significant predictors of passing an examination while students’ absenteeism is an insignificant predictor. Females have 45% likelihood of passing the exam than their male classmates. Students who use and read their reference book are 38 times more likely pass the exam than those who do not use and read their reference book. Those who spent more than 3 hours in studying are four (4) times more likely pass the exam than those who spent only 3 hours or less in studying.

Keywords: absences, binary logistic regression, gender, hours of study prediction-causation method, periodical exams, random sampling, reference book

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17454 A New Index for the Differential Diagnosis of Morbid Obese Children with and without Metabolic Syndrome

Authors: Mustafa M. Donma, Orkide Donma

Abstract:

Metabolic syndrome (MetS) is a severe health problem which is common among obese individuals. The components of MetS are rather stable in adults compared to the components discussed for children. Due to the ambiguity in this group of the population, how to diagnose MetS in morbid obese (MO) children still constitutes a matter of discussion. For this purpose, a formula, which facilitates the diagnosis of MetS in MO children, was investigated. The aim of this study was to develop a formula which was capable of discriminating MO children with and without MetS findings. Study population comprised MO children. Age and sex-dependent body mass index (BMI) percentiles of the children were above 99. Metabolic syndrome components were also determined. Elevated systolic and diastolic blood pressures (SBP and DBP), elevated fasting blood glucose (FBG), elevated triglycerides (TRG), and/or depressed high density lipoprotein cholesterol (HDL-C) in addition to central obesity were listed as MetS components for each child. Presence of at least two of these components confirmed that the case was MetS. Two groups were constituted. In the first group, there were forty-two MO children without MetS components. Second group was composed of forty-four MO children with at least two MetS components. Anthropometric measurements, including weight, height, waist, and hip circumferences, were performed following physical examination. Body mass index and homeostatic model assessment of insulin resistance values were calculated. Informed consent forms were obtained from the parents of the children. Institutional Non-Interventional Ethics Committee approved the study design. Blood pressure values were recorded. Routine biochemical analysis, including FBG, insulin (INS), TRG, HDL-C were performed. The performance and the clinical utility of the Diagnostic Obesity Notation Model Assessment Metabolic Syndrome Index (DONMA MetS index) [(INS/FBG)/(HDL-C/TRG)*100] was tested. Appropriate statistical tests were applied to the study data. p value smaller than 0.05 was defined as significant. Metabolic syndrome index values were 41.6±5.1 in MO group and 104.4±12.8 in MetS group. Corresponding values for HDL-C values were 54.5±13.2 mg/dl and 44.2±11.5 mg/dl. There were statistically significant differences between the groups (p<0.001). Upon evaluation of the correlations between MetS index and HDL-C values, a much stronger negative correlation was found in MetS group (r=-0.515; p=0.001) in comparison with the correlation detected in MO group (r=-0.371; p=0.016). From these findings, it was concluded that the statistical significance degree of the difference between MO and MetS groups was highly acceptable for this recently introduced MetS index as expected. This was due to the involvement of all of the biochemically defined MetS components into the index. This is particularly important because each of these four parameters used in the formula is cardiac risk factor. Aside from discriminating MO children with and without MetS findings, MetS index introduced in this study is important from the cardiovascular risk point of view in MetS group of children.

Keywords: children, fasting blood glucose, high density lipoprotein cholesterol, index, insulin, metabolic syndrome, morbid obesity, triglycerides.

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17453 A Markov Model for the Elderly Disability Transition and Related Factors in China

Authors: Huimin Liu, Li Xiang, Yue Liu, Jing Wang

Abstract:

Background: As one of typical case for the developing countries who are stepping into the aging times globally, more and more older people in China might face the problem of which they could not maintain normal life due to the functional disability. While the government take efforts to build long-term care system and further carry out related policies for the core concept, there is still lack of strong evidence to evaluating the profile of disability states in the elderly population and its transition rate. It has been proved that disability is a dynamic condition of the person rather than irreversible so it means possible to intervene timely on them who might be in a risk of severe disability. Objective: The aim of this study was to depict the picture of the disability transferring status of the older people in China, and then find out individual characteristics that change the state of disability to provide theory basis for disability prevention and early intervention among elderly people. Methods: Data for this study came from the 2011 baseline survey and the 2013 follow-up survey of the China Health and Retirement Longitudinal Study (CHARLS). Normal ADL function, 1~2 ADLs disability,3 or above ADLs disability and death were defined from state 1 to state 4. Multi-state Markov model was applied and the four-state homogeneous model with discrete states and discrete times from two visits follow-up data was constructed to explore factors for various progressive stages. We modeled the effect of explanatory variables on the rates of transition by using a proportional intensities model with covariate, such as gender. Result: In the total sample, state 2 constituent ratio is nearly about 17.0%, while state 3 proportion is blow the former, accounting for 8.5%. Moreover, ADL disability statistics difference is not obvious between two years. About half of the state 2 in 2011 improved to become normal in 2013 even though they get elder. However, state 3 transferred into the proportion of death increased obviously, closed to the proportion back to state 2 or normal functions. From the estimated intensities, we see the older people are eleven times as likely to develop at 1~2 ADLs disability than dying. After disability onset (state 2), progression to state 3 is 30% more likely than recovery. Once in state 3, a mean of 0.76 years is spent before death or recovery. In this model, a typical person in state 2 has a probability of 0.5 of disability-free one year from now while the moderate disabled or above has a probability of 0.14 being dead. Conclusion: On the long-term care cost considerations, preventive programs for delay the disability progression of the elderly could be adopted based on the current disabled state and main factors of each stage. And in general terms, those focusing elderly individuals who are moderate or above disabled should go first.

Keywords: Markov model, elderly people, disability, transition intensity

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17452 Silver Nanoparticles Synthesized in Plant Extract Against Acute Hepatopancreatic Necrosis of Shrimp: Estimated By Multiple Models

Authors: Luz del Carmen Rubí Félix Peña, Jose Adan Felix-Ortiz, Ely Sara Lopez-Alvarez, Wenceslao Valenzuela-Quiñonez

Abstract:

On a global scale, Mexico is the sixth largest producer of farmed white shrimp (Penaeus vannamei). The activity suffered significant economic losses due to acute hepatopancreatic necrosis (AHPND) caused by a strain of Vibrio parahaemolyticus. For control, the first option is the application of antibiotics in food, causing changes in the environment and bacterial communities, which has produced greater virulence and resistance of pathogenic bacteria. An alternative treatment is silver nanoparticles (AgNPs) generated by green synthesis, which have shown an antibacterial capacity by destroying the cell membrane or denaturing the cell. However, the doses at which these are effective are still unknown. The aim is to calculate the minimum inhibitory concentration (MIC) using the Gompertz, Richard, and Logistic model of biosynthesized AgNPs against a strain of V. parahaemolyticus. Through the testing of different formulations of AgNPs synthesized from Euphorbia prostrate (Ep) extracts against V. parahaemolyticus causing AHPND in white shrimp. Aqueous and ethanol extracts were obtained, and the concentration of phenols and flavonoids was quantified. In the antibiograms, AgNPs were formulated in ethanol extracts of Ep (20 and 30%). The inhibition halo at well dilution test were 18±1.7 and 17.67±2.1 mm against V. parahaemolyticus. A broth microdilution was performed with the inhibitory agents (aqueous and ethanolic extracts and AgNPs) and 20 μL of the inoculum of V. parahaemolyticus. The MIC for AgNPs was 6.2-9.3 μg/mL and for ethanol extract of 49-73 mg/mL. The Akaike index (AIC) was used to choose the Gompertz model for ethanol extracts of Ep as the best data descriptor (AIC=204.8, 10%; 45.5, 20%, and 204.8, 30%). The Richards model was at AgNPs ethanol extract with AIC=-9.3 (10%), -17.5 (20 and 30%). The MIC calculated for EP extracts with the modified Gompertz model were 20 mg/mL (10% and 20% extract) and 40 mg/mL at 30%, while Richard was winner for AgNPs-synthesized it was 5 μg/mL (10% and 20%) and 8 μg/mL (30%). The solver tool Excel was used for the calculations of the models and inhibition curves against V.parahaemolyticus.

Keywords: green synthesis, euphorbia prostata, phenols, flavonoids, bactericide

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17451 Innovations in Enterprises (with References to Micro, Small and Medium Enterprises in Visakhapatnam District, India)

Authors: D. Lalitha Rani, K. Sankar Rao

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MSMEs, due to their unique characteristics, are found to have inherent capabilities to undertake technological and non-technological innovations successfully across industries and nations. While there is considerable empirical evidence to throw light on SME innovation contributions in the context of developed countries, there is hardly any evidence to reveal how innovative SMEs are in rapidly industrializing economies like India. Indian MSMEs are largely incremental innovators, prompted by their customers and involved in product and/or process innovations. But majority carried out innovations with internal efforts only whereas the minority which obtained external support, had better technical strength, indulged in more frequent and both product & process innovations. Such MSMEs achieved better innovation performance as well as better economic performance. Some of them internationalized themselves in the process. However such achievements are “an oasis” in the vast Indian SME sector. How to promote (i) innovations, (ii) quality of innovations and (iii) patenting culture among the SMEs is a challenge for Indian Policy Makers. However this paper examines what are the innovation practices which are being carried out in this sector and identified the barriers for innovations in this sector and concludes with proposing some policy recommendations for promoting innovations in MSME sector in India.

Keywords: MSMEs, incremental innovators, policies, non-technological innovations

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17450 Probabilistic Approach to Contrast Theoretical Predictions from a Public Corruption Game Using Bayesian Networks

Authors: Jaime E. Fernandez, Pablo J. Valverde

Abstract:

This paper presents a methodological approach that aims to contrast/validate theoretical results from a corruption network game through probabilistic analysis of simulated microdata using Bayesian Networks (BNs). The research develops a public corruption model in a game theory framework. Theoretical results suggest a series of 'optimal settings' of model's exogenous parameters that boost the emergence of corruption. The paper contrasts these outcomes with probabilistic inference results based on BNs adjusted over simulated microdata. Principal findings indicate that probabilistic reasoning based on BNs significantly improves parameter specification and causal analysis in a public corruption game.

Keywords: Bayesian networks, probabilistic reasoning, public corruption, theoretical games

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17449 Hand Gesture Recognition for Sign Language: A New Higher Order Fuzzy HMM Approach

Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

Abstract:

Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

Procedia PDF Downloads 447