Search results for: network diagnostic tool
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10298

Search results for: network diagnostic tool

4238 Social Networking Sites and Employee Engagement

Authors: Sultan Ali Suleiman AlMazrouei

Abstract:

Purpose: The purpose of this paper is to examine the effect of communication through social networking sites (Facebook, Twitter) on employee engagement. Methodology: A quantitative survey was used to collect data from 440 employees from the Ministry of Education in Oman. SPSS software was used to analyze the data. Findings: The results revealed a positive significant relationship between communication via Facebook and employee engagement. However, communication via Twitter does not influence employee engagement significantly. Practical implications: Managers can benefit from the study by understanding the importance of communication via Facebook with employees in order to increase their engagement. They should post their views and thoughts on Facebook and encourage their employees to be members which would be reflected on their psychological side positively. That gives them a feeling of belonging to a network. Originality/value: The study enriches the human resources management literature by examining a theoretical framework about the influence of social networking sites usage on employee engagement. This is one of the few studies that focus on the relationship of social networking sites usage with employees' engagement. It is the first study in an Omani context.

Keywords: employee engagement, social networking sites, Facebook, Twitter

Procedia PDF Downloads 335
4237 The Impacts of Export in Stimulating Economic Growth in Ethiopia: ARDL Model Analysis

Authors: Natnael Debalklie Teshome

Abstract:

The purpose of the study was to empirically investigate the impacts of export performance and its volatility on economic growth in the Ethiopian economy. To do so, time-series data of the sample period from 1974/75 – 2017/18 were collected from databases and annual reports of IMF, WB, NBE, MoFED, UNCTD, and EEA. The extended Cobb-Douglas production function of the neoclassical growth model framed under the endogenous growth theory was used to consider both the performance and instability aspects of export. First, the unit root test was conducted using ADF and PP tests, and data were found in stationery with a mix of I(0) and I(1). Then, the bound test and Wald test were employed, and results showed that there exists long-run co-integration among study variables. All the diagnostic test results also reveal that the model fulfills the criteria of the best-fitted model. Therefore, the ARDL model and VECM were applied to estimate the long-run and short-run parameters, while the Granger causality test was used to test the causality between study variables. The empirical findings of the study reveal that only export and coefficient of variation had significant positive and negative impacts on RGDP in the long run, respectively, while other variables were found to have an insignificant impact on the economic growth of Ethiopia. In the short run, except for gross capital formation and coefficients of variation, which have a highly significant positive impact, all other variables have a strongly significant negative impact on RGDP. This shows exports had a strong, significant impact in both the short-run and long-run periods. However, its positive and statistically significant impact is observed only in the long run. Similarly, there was a highly significant export fluctuation in both periods, while significant commodity concentration (CCI) was observed only in the short run. Moreover, the Granger causality test reveals that unidirectional causality running from export performance to RGDP exists in the long run and from both export and RGDP to CCI in the short run. Therefore, the export-led growth strategy should be sustained and strengthened. In addition, boosting the industrial sector is vital to bring structural transformation. Hence, the government has to give different incentive schemes and supportive measures to exporters to extract the spillover effects of exports. Greater emphasis on price-oriented diversification and specialization on major primary products that the country has a comparative advantage should also be given to reduce value-based instability in the export earnings of the country. The government should also strive to increase capital formation and human capital development via enhancing investments in technology and quality of education to accelerate the economic growth of the country.

Keywords: export, economic growth, export diversification, instability, co-integration, granger causality, Ethiopian economy

Procedia PDF Downloads 84
4236 Predictive Models for Compressive Strength of High Performance Fly Ash Cement Concrete for Pavements

Authors: S. M. Gupta, Vanita Aggarwal, Som Nath Sachdeva

Abstract:

The work reported through this paper is an experimental work conducted on High Performance Concrete (HPC) with super plasticizer with the aim to develop some models suitable for prediction of compressive strength of HPC mixes. In this study, the effect of varying proportions of fly ash (0% to 50% at 10% increment) on compressive strength of high performance concrete has been evaluated. The mix designs studied were M30, M40 and M50 to compare the effect of fly ash addition on the properties of these concrete mixes. In all eighteen concrete mixes have been designed, three as conventional concretes for three grades under discussion and fifteen as HPC with fly ash with varying percentages of fly ash. The concrete mix designing has been done in accordance with Indian standard recommended guidelines i.e. IS: 10262. All the concrete mixes have been studied in terms of compressive strength at 7 days, 28 days, 90 days and 365 days. All the materials used have been kept same throughout the study to get a perfect comparison of values of results. The models for compressive strength prediction have been developed using Linear Regression method (LR), Artificial Neural Network (ANN) and Leave One Out Validation (LOOV) methods.

Keywords: high performance concrete, fly ash, concrete mixes, compressive strength, strength prediction models, linear regression, ANN

Procedia PDF Downloads 452
4235 Aging Time Effect of 58s Microstructure

Authors: Nattawipa Pakasri

Abstract:

58S (60SiO2-36CaO-4P2O5), three-dimensionally ordered macroporous bioactive glasses (3DOM-BGs) were synthesized by the sol-gel method using dual templating methods. non-ionic surfactant Brij56 used as templates component produced mesoporous and the spherical PMMA colloidal crystals as one template component yielded either three-dimensionally ordered microporous products or shaped bioactive glass nanoparticles. The bioactive glass with aging step for 12 h at room temperature, no structure transformation occurred and the 3DOM structure was produced (Figure a) due to no shrinkage process between the aging step. After 48 h time of o 3DOM structure remained and, nanocube with ∼120 nm edge lengths and nanosphere particle with ∼50 nm was obtained (Figure c, d). PMMA packing templates have octahedral and tetrahedral holes to make 2 final shapes of 3DOM-BGs which is rounded and cubic, respectively. The ageing time change from 12h, 24h and 48h affected to the thickness of interconnecting macropores network. The wall thickness was gradually decrease after increase aging time.

Keywords: three-dimensionally ordered macroporous bioactive glasses, sol-gel method, PMMA, bioactive glass

Procedia PDF Downloads 120
4234 Local Tax Map Software System Development

Authors: Smithinun Thairoongrojana

Abstract:

This research is a qualitative research with three main purposes: (1) to develop the local tax map software system to be linked to the main Local Tax Map System (LTAX3000) system; (2) to design and develop a program for tax data fieldwork on wireless devices and link it to LTAX3000 database of Surat Thani Municipality; (3) to develop the human resource responsible for the fieldwork to be able to use the program and maintain the system and also to be able to work with the dynamic of technologies. In-depth interviews with the two groups of samples, the board of Surat Thani Municipality and operation staff responsible for observing and taxing fieldworks were conducted. The result of this study demonstrates the new developed fieldworks system that can be used both stand-alone usage and networking usage. The fieldworks system to collect and store the variety of taxing information within Surat Thani Municipality will be explained. Then the fieldwork operation process development and the replacement of transferring and storing the information via the network communication.

Keywords: Local tax map, software system development, wireless devices, human resource

Procedia PDF Downloads 195
4233 Logistic and Its Importance in Turkish Food Sector and an Analysis of the Logistics Sector in Turkey

Authors: Şule Turhan, Özlem Turan

Abstract:

Permanence in the international markets for many global companies is about being known as having effective logistics which targets customer satisfaction management and lower costs. Under competitive conditions, the necessity of providing the products to customers quickly and on time for the companies which constantly aim to improve their profitability increased the strategic importance of the logistics concept. Food logistic is one of the most difficult areas in logistics. In the process from manufacturer to final consumer, quality and hygiene standards must be provided constantly. In food logistics, reliable and extensive service network has great importance and on time delivery is the target. Developing logistics industry provide the supply of foods in the country and the development of export markets more quickly and has an important role in providing added value to the country's economy. Turkey that creates a bridge between the east and the west is an attractive market for logistics companies. In this study, by examining both the place and the importance of logistics in Turkish food sector, recommendations will be made for the food industry.

Keywords: logistics, Turkish food industry, competition, food industry

Procedia PDF Downloads 375
4232 The Urban Project and the Urban Improvement to the Test of the Participation, Case: Project of Modernization of Constantine

Authors: Mouhoubi Nedjima, Sassi Boudemagh Souad

Abstract:

In the framework of the modernization of the city of Constantine, and in order to restore its status as a regional metropolis and introduce it into the network of cities international metropolises, a major urban project was launched: project of modernization and of metropolitanization of the city of Constantine (PMMC). Our research project focuses on the management of the project for the modernization of the city of Constantine (PMMC) focusing on the management of some aspects of the urban project whose participation, with the objective assessment of the managerial approach business. Among the cases revealing taken into account in our research work on the question of participation of actors and their organizations, the operation relating to "the urban improvement in the city of the Brothers FERRAD in the district of Zouaghi". This operation with the objective of improving the living conditions of citizens has faced several challenges and obstacles that have been in major part the factors of its failure. Through this study, we examine the management process and the mode of organization of the actors of the project as well as the level of participation of the citizen to finally propose managerial solutions to conflict situations observed.

Keywords: the urban project, the urban improvement, participation, Constantine

Procedia PDF Downloads 408
4231 Analyzing Behaviour of the Utilization of the Online News Clipping Database: Experience in Suan Sunandha Rajabhat University

Authors: Siriporn Poolsuwan, Kanyarat Bussaban

Abstract:

This research aims to investigate and analyze user’s behaviour towards the utilization of the online news clipping database at Suan Sunandha Rajabhat University, Thailand. Data is gathered from 214 lecturers and 380 undergraduate students by using questionnaires. Findings show that most users knew the online news clipping service from their friends, library’s website and their teachers. The users learned how to use it by themselves and others learned by training of SSRU library. Most users used the online news clipping database one time per month at home and always used the service for general knowledge, up-to-date academic knowledge and assignment reference. Moreover, the results of using the online news clipping service problems include the users themselves, service management, service device- computer and tools – and the network, service provider, and publicity. This research would be benefit for librarians and teachers for planning and designing library services in their works and organization.

Keywords: online database, user behavior, news clipping, library services

Procedia PDF Downloads 320
4230 Transfer Rate of Organic Water Contaminants through a Passive Sampler Membrane of Polyethersulfone (PES)

Authors: Hamidreza Sharifan, Audra Morse

Abstract:

Accurate assessments of contaminant concentrations based on traditional grab sampling methods are not always possible. Passive samplers offer an attractive alternative to traditional sampling methods that overcomes these limitations. The POCIS approach has been used as a screening tool for determining the presence/absence, possible sources and relative amounts of organic compounds at field sites. The objective for the present research is on mass transfer of five water contaminants (atrazine, caffeine, bentazon, ibuprofen, atenolol) through the Water Boundary Layer (WBL) and membrane. More specific objectives followed by establishing a relationship between the sampling rate and water solubility of the compounds, as well as comparing the molecular weight of the compounds and concentration of the compounds at the time of equilibrium. To determine whether water boundary layer effects transport rate through the membrane is another main objective in this paper. After GC mass analysis of compounds, regarding the WBL effect in this experiment, Sherwood number for the experimental tank developed. A close relationship between feed concentration of compound and sampling rate has been observed.

Keywords: passive sampler, water contaminants, PES-transfer rate, contaminant concentrations

Procedia PDF Downloads 459
4229 Career Development for Benjarong Porcelain Handicraft Communities in Central Thailand

Authors: Chutikarn Sriwiboon, Suwaree Yordchim

Abstract:

Benjarong handicraft product is one of the most important handicraft products from Thailand. It involves the management of traditional wisdom of arts and Thai culture. This paper drew upon data collection from local communities by using an in-depth interview technique which was conducted in Thailand during summer of 2014. The survey was structured primarily to obtain local wisdom and concerns toward their career development. This research paper was a qualitative research conducted by focus groups with a total of 51 cooperative women and occupational groups around Thailand which produced the Benjarong products. The data were significantly collected from many sources and many communities, which totaled 24,430 handicraft products, in which the 668 different patterns of Benjarong products were produced by 51 local community network groups in Thailand. The findings revealed that after applying the Philosophy of Sufficiency Economy, there was a significantly positive change in their career development and the process of knowledge management enables local community to enhance their personal development and career.

Keywords: Benjarong, career development, community, handicraft

Procedia PDF Downloads 386
4228 Factors Influencing the Use Intention of Unmanned Retail Stores

Authors: Yen-Ting Chiu, Chia-Ying Lin, Pei-Hsuan Ho

Abstract:

New technologies can help solve the problem of labor shortage and the decline of birthrate. Technologies can improve human’s life and reduce the burden on the staff and bring convenience to people. That’s why unmanned retail store X-Store was established in Taiwan to create more valuable services and shopping experiences based on smart retailing. The purpose of this study is to examine the impact of unmanned stores, X-Store, on customers’ behavioral intentions. It uses the Unified theory of acceptance and use of technology (UTAUT) model as a basis and adds a perceived value factor to explain customer willingness to use the X-Store. In addition, the study further divided the sample into gender and age groups to compare behavioral differences between different groups. The study collected 214 valid questionnaires through online questionnaires. Using SPSS as a statistical analysis tool, the results of the study show that effort expectancy, social influence, facilitating conditions, and perceived value have a significant impact on behavioral intention to use X-Store. However, performance expectancy is not significant. This research concludes with managerial implications and suggestions for retail practitioners.

Keywords: perceived value, smart retailing, unmanned store, UTAUT, X-Store

Procedia PDF Downloads 94
4227 Numerical Study of Fatigue Crack Growth at a Web Stiffener of Ship Structural Details

Authors: Wentao He, Jingxi Liu, De Xie

Abstract:

It is necessary to manage the fatigue crack growth (FCG) once those cracks are detected during in-service inspections. In this paper, a simulation program (FCG-System) is developed utilizing the commercial software ABAQUS with its object-oriented programming interface to simulate the fatigue crack path and to compute the corresponding fatigue life. In order to apply FCG-System in large-scale marine structures, the substructure modeling technique is integrated in the system under the consideration of structural details and load shedding during crack growth. Based on the nodal forces and nodal displacements obtained from finite element analysis, a formula for shell elements to compute stress intensity factors is proposed in the view of virtual crack closure technique. The cracks initiating from the intersection of flange and the end of the web-stiffener are investigated for fatigue crack paths and growth lives under water pressure loading and axial force loading, separately. It is found that the FCG-System developed by authors could be an efficient tool to perform fatigue crack growth analysis on marine structures.

Keywords: crack path, fatigue crack, fatigue live, FCG-system, virtual crack closure technique

Procedia PDF Downloads 573
4226 Detection and Classification of Rubber Tree Leaf Diseases Using Machine Learning

Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

Abstract:

Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

Procedia PDF Downloads 83
4225 An Alternative Stratified Cox Model for Correlated Variables in Infant Mortality

Authors: K. A. Adeleke

Abstract:

Often in epidemiological research, introducing stratified Cox model can account for the existence of interactions of some inherent factors with some major/noticeable factors. This research work aimed at modelling correlated variables in infant mortality with the existence of some inherent factors affecting the infant survival function. An alternative semiparametric Stratified Cox model is proposed with a view to take care of multilevel factors that have interactions with others. This, however, was used as a tool to model infant mortality data from Nigeria Demographic and Health Survey (NDHS) with some multilevel factors (Tetanus, Polio, and Breastfeeding) having correlation with main factors (Sex, Size, and Mode of Delivery). Asymptotic properties of the estimators are also studied via simulation. The tested model via data showed good fit and performed differently depending on the levels of the interaction of the strata variable Z*. An evidence that the baseline hazard functions and regression coefficients are not the same from stratum to stratum provides a gain in information as against the usage of Cox model. Simulation result showed that the present method produced better estimates in terms of bias, lower standard errors, and or mean square errors.

Keywords: stratified Cox, semiparametric model, infant mortality, multilevel factors, cofounding variables

Procedia PDF Downloads 561
4224 Contention Window Adjustment in IEEE 802.11-based Industrial Wireless Networks

Authors: Mohsen Maadani, Seyed Ahmad Motamedi

Abstract:

The use of wireless technology in industrial networks has gained vast attraction in recent years. In this paper, we have thoroughly analyzed the effect of contention window (CW) size on the performance of IEEE 802.11-based industrial wireless networks (IWN), from delay and reliability perspective. Results show that the default values of CWmin, CWmax, and retry limit (RL) are far from the optimum performance due to the industrial application characteristics, including short packet and noisy environment. An adaptive CW algorithm (payload-dependent) has been proposed to minimize the average delay. Finally a simple, but effective CW and RL setting has been proposed for industrial applications which outperforms the minimum-average-delay solution from maximum delay and jitter perspective, at the cost of a little higher average delay. Simulation results show an improvement of up to 20%, 25%, and 30% in average delay, maximum delay and jitter respectively.

Keywords: average delay, contention window, distributed coordination function (DCF), jitter, industrial wireless network (IWN), maximum delay, reliability, retry limit

Procedia PDF Downloads 423
4223 Platform Urbanism: Planning towards Hyper-Personalisation

Authors: Provides Ng

Abstract:

Platform economy is a peer-to-peer model of distributing resources facilitated by community-based digital platforms. In recent years, digital platforms are rapidly reconfiguring the public realm using hyper-personalisation techniques. This paper aims at investigating how urban planning can leapfrog into the digital age to help relieve the rising tension of the global issue of labour flow; it discusses the means to transfer techniques of hyper-personalisation into urban planning for plasticity using platform technologies. This research first denotes the limitations of the current system of urban residency, where the system maintains itself on the circulation of documents, which are data on paper. Then, this paper tabulates how some of the institutions around the world, both public and private, digitise data, and streamline communications between a network of systems and citizens using platform technologies. Subsequently, this paper proposes ways in which hyper-personalisation can be utilised to form a digital planning platform. Finally, this paper concludes by reviewing how the proposed strategy may help to open up new ways of thinking about how we affiliate ourselves with cities.

Keywords: platform urbanism, hyper-personalisation, digital inventory, urban accessibility

Procedia PDF Downloads 120
4222 Observer-Based Control Design for Double Integrators Systems with Long Sampling Periods and Actuator Uncertainty

Authors: Tomas Menard

Abstract:

The design of control-law for engineering systems has been investigated for many decades. While many results are concerned with continuous systems with continuous output, nowadays, many controlled systems have to transmit their output measurements through network, hence making it discrete-time. But it is well known that the sampling of a system whose control-law is based on the continuous output may render the system unstable, especially when this sampling period is long compared to the system dynamics. The control design then has to be adapted in order to cope with this issue. In this paper, we consider systems which can be modeled as double integrator with uncertainty on the input since many mechanical systems can be put under such form. We present a control scheme based on an observer using only discrete time measurement and which provides continuous time estimation of the state, combined with a continuous control law, which stabilized a system with second-order dynamics even in the presence of uncertainty. It is further shown that arbitrarily long sampling periods can be dealt with properly setting the control scheme parameters.

Keywords: dynamical system, control law design, sampled output, observer design

Procedia PDF Downloads 188
4221 Aryne Mediated, Transition-Metal Free Arylations of Quinolines for Medicinal and Materials Applications

Authors: Rakesh Kumar, Shashi Janeoo, Ankit Dhiman, Siddharth Chopra

Abstract:

Arynes are versatile reactive intermediates that offer broad opportunities in green organic synthesis. Arynes are potential aryl group surrogates for the transition metal-free environment friendly arylation reactions. Regioselective arylations of quinolines were achieved by the reactions of quinoline N-oxides with aryne intermediates generated in situ from the Kobayashi precursors. Various 2-substituted quinolines provided 3-arylated-2-substituted quinolines under ambient conditions. Acridine N-oxides also reacted well and provided unusual 4-arylacridines. Various fluorine containing 2,3-diarylquinaolines prepared using this approach were evaluated for antibacterial activity and two compounds inhibited the drug-resistant strains of S-aureus with a good selectivity index. Further, the 2,3-diarylquinolines as the potential optoelectronic materials were prepared by the aryne chemistry approach and their optical and electronic properties for such applications are under study. The aryne intermediates provide an effective Green Chemistry tool to achieve versatile arylated heteroarenes for diverse applications.

Keywords: arynes, arylation, quinolines, acridines.

Procedia PDF Downloads 99
4220 Towards Integrating Statistical Color Features for Human Skin Detection

Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

Abstract:

Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

Procedia PDF Downloads 465
4219 Topology Optimization of the Interior Structures of Beams under Various Load and Support Conditions with Solid Isotropic Material with Penalization Method

Authors: Omer Oral, Y. Emre Yilmaz

Abstract:

Topology optimization is an approach that optimizes material distribution within a given design space for a certain load and boundary conditions by providing performance goals. It uses various restrictions such as boundary conditions, set of loads, and constraints to maximize the performance of the system. It is different than size and shape optimization methods, but it reserves some features of both methods. In this study, interior structures of the parts were optimized by using SIMP (Solid Isotropic Material with Penalization) method. The volume of the part was preassigned parameter and minimum deflection was the objective function. The basic idea behind the theory was considered, and different methods were discussed. Rhinoceros 3D design tool was used with Grasshopper and TopOpt plugins to create and optimize parts. A Grasshopper algorithm was designed and tested for different beams, set of arbitrary located forces and support types such as pinned, fixed, etc. Finally, 2.5D shapes were obtained and verified by observing the changes in density function.

Keywords: Grasshopper, lattice structure, microstructures, Rhinoceros, solid isotropic material with penalization method, TopOpt, topology optimization

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4218 DocPro: A Framework for Processing Semantic and Layout Information in Business Documents

Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

Abstract:

With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

Procedia PDF Downloads 221
4217 Recognizing Human Actions by Multi-Layer Growing Grid Architecture

Authors: Z. Gharaee

Abstract:

Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

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4216 Collaborative Implementation of Master Plans in Afghanistan's Context Considering Land Readjustment as Case Study

Authors: Ahmad Javid Habib, Tetsuo Kidokoro

Abstract:

There is an increasing demand for developing urban land to provide better living conditions for all citizens in Afghanistan. Most of the development will involve the acquisition of land. And the current land acquisition method practiced by central government is expropriation, which is a cash-based transaction method that imposes heavy fiscal burden on local municipalities and central government, and it does not protect ownership rights and social equity of landowners besides it relocates the urban poor to remote areas with limited access to jobs and public services. The questionnaire analysis, backed by observations of different case studies in countries where land readjustment is used as a collaborative land development tool indicates that the method plays a key role in valuing landowners’ rights, giving other community members and stakeholders the opportunity to collaboratively implement urban development projects. The practice of the method is reducing the heavy fiscal burden on the local and central governments and is a better option to deal with the current development challenges in Afghanistan.

Keywords: collaboration, land readjustment, master plan, expropriation

Procedia PDF Downloads 299
4215 Enhanced Multi-Scale Feature Extraction Using a DCNN by Proposing Dynamic Soft Margin SoftMax for Face Emotion Detection

Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

Abstract:

Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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4214 Evaluation of the Effects of Lead on Some Physiological and Hormonal Biomarkeurs among Workers

Authors: Mansouri Ouarda, Adbdennour Cherif, Boukarma Ziad

Abstract:

Environmental and biological monitoring are used for the evaluation of exposure to industrial chemicals, and provide a tool for assessing workers’ exposure to chemicals. The organs or tissues where the first biological effects can be observed with increasing amounts of lead toxicity. This study aims at evaluating the effect of the metal element-trace; lead, on the sex hormones in male workers, exposed to this metal on the level of the manufacturing plant of lead accumulators. The results indicate a significant reduction of the testosterone concentration in exposed workers compared to the control. However, the rate of LH was strongly increased at the individuals exposed to Pb. A significant difference concerning the rate of FSH, the hormone Prolactin and cortisol was recorded. The indicators of the lead poisoning indicate a very highly significant increase in the value of Pbs which vary between (142-796 µg/L) among which 50% of the workers present a high lead poisoning and the value of PPZ which vary between (43-554µg/L). The biochemical parameters show a significant increase in the rate of the créatinine, the urea and the acid urique. The hepatic results show no significant differentiation in the rate of TGO and TGP between both groups of study. However the rates of the enzyme phosphatase alkaline, triglyceride, and cholesterol a significant difference were registered.

Keywords: hormons, parameters, physilogical, Pbs, PPZ

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4213 Using Computational Fluid Dynamics to Model and Design a Preventative Application for Strong Wind

Authors: Ming-Hwi Yao, Su-Szu Yang

Abstract:

Typhoons are one of the major types of disasters that affect Taiwan each year and that cause severe damage to agriculture. Indeed, the damage exacted during a typical typhoon season can be up to $1 billion, and is responsible for nearly 75% of yearly agricultural losses. However, there is no consensus on how to reduce the damage caused by the strong winds and heavy precipitation engendered by typhoons. One suggestion is the use of windbreak nets, which are a low-cost and easy-to-use disaster mitigation strategy for crop production. In the present study, we conducted an evaluation to determine the optimal conditions of a windbreak net by using a computational fluid dynamics (CFD) model. This model may be used as a reference for crop protection. The results showed that CFD simulation validated windbreak nets of different mesh sizes and heights in the experimental area; thus, CFD is an efficient tool for evaluating the effectiveness of windbreak nets. Specifically, the effective wind protection length and height were found to be 6 and 1.3 times the length and height of the windbreak net, respectively. During a real typhoon, maximum wind gusts of 18 m s-1 can be reduced to 4 m s-1 by using a windbreak net that has a 70% blocking rate. In short, windbreak nets are significantly effective in protecting typhoon-affected areas.

Keywords: computational fluid dynamics, disaster, typhoon, windbreak net

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4212 Gender Mainstreaming in Public Universities in Mexico

Authors: Carlos David Carrillo Trujillo, Rebelín Echeverría Echeverría, Nancy Evia Alamilla, Rocío Quintal López

Abstract:

Gender as a social construct is a term now widely studied. Within the social sciences it has become very important. In this sense, psychology tries to make some contributions from your area. The intention is to promote equal opportunities for men and women. Social, employment and educational inequities perpetuate sexism, violence and other important social problems in Mexico. The gender perspective is conceptualized as a tool to promote laws, policies, plans, programs and procedures where women are made ​​visible and empowered. The aim of this is the pursuit of equality. Thus, gender mainstreaming is one of the main challenges of education in Mexico. Only a few universities have programs, research or subjects related to the topic. Human resources, and time allocated to teachers are identified as obstacles to the institutionalization of gender. The objective was to make a diagnosis on course offerings and policies on gender. A documentary study and interviews with managers of at least 20 higher education institutions (IES's) were performed. The results indicate the need for greater gender courses, research projects and intervention. The need to promote policies that seek equal opportunities between men and women is also noted.

Keywords: gender mainstreaming, institutionalization, universities, intervention

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4211 Deep learning with Noisy Labels : Learning True Labels as Discrete Latent Variable

Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

Abstract:

In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

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4210 Rejuvenate: Face and Body Retouching Using Image Inpainting

Authors: Hossam Abdelrahman, Sama Rostom, Reem Yassein, Yara Mohamed, Salma Salah, Nour Awny

Abstract:

In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result.

Keywords: generative adversarial network, large mask inpainting, stable diffusion inpainting, plastic surgery

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4209 Nanomechanical Characterization of Healthy and Tumor Lung Tissues at Cell and Extracellular Matrix Level

Authors: Valeria Panzetta, Ida Musella, Sabato Fusco, Paolo Antonio Netti

Abstract:

The study of the biophysics of living cells drew attention to the pivotal role of the cytoskeleton in many cell functions, such as mechanics, adhesion, proliferation, migration, differentiation and neoplastic transformation. In particular, during the complex process of malignant transformation and invasion cell cytoskeleton devolves from a rigid and organized structure to a more compliant state, which confers to the cancer cells a great ability to migrate and adapt to the extracellular environment. In order to better understand the malignant transformation process from a mechanical point of view, it is necessary to evaluate the direct crosstalk between the cells and their surrounding extracellular matrix (ECM) in a context which is close to in vivo conditions. In this study, human biopsy tissues of lung adenocarcinoma were analyzed in order to define their mechanical phenotype at cell and ECM level, by using particle tracking microrheology (PTM) technique. Polystyrene beads (500 nm) were introduced into the sample slice. The motion of beads was obtained by tracking their displacements across cell cytoskeleton and ECM structures and mean squared displacements (MSDs) were calculated from bead trajectories. It has been already demonstrated that the amplitude of MSD is inversely related to the mechanical properties of intracellular and extracellular microenvironment. For this reason, MSDs of particles introduced in cytoplasm and ECM of healthy and tumor tissues were compared. PTM analyses showed that cancerous transformation compromises mechanical integrity of cells and extracellular matrix. In particular, the MSD amplitudes in cells of adenocarcinoma were greater as compared to cells of normal tissues. The increased motion is probably associated to a less structured cytoskeleton and consequently to an increase of deformability of cells. Further, cancer transformation is also accompanied by extracellular matrix stiffening, as confirmed by the decrease of MSDs of matrix in tumor tissue, a process that promotes tumor proliferation and invasiveness, by activating typical oncogenic signaling pathways. In addition, a clear correlation between MSDs of cells and tumor grade was found. MSDs increase when tumor grade passes from 2 to 3, indicating that cells undergo to a trans-differentiation process during tumor progression. ECM stiffening is not dependent on tumor grade, but the tumor stage resulted to be strictly correlated with both cells and ECM mechanical properties. In fact, a greater stage is assigned to tumor spread to regional lymph nodes and characterized by an up-regulation of different ECM proteins, such as collagen I fibers. These results indicate that PTM can be used to get nanomechanical characterization at different scale levels in an interpretative and diagnostic context.

Keywords: cytoskeleton, extracellular matrix, mechanical properties, particle tracking microrheology, tumor

Procedia PDF Downloads 283