Search results for: Template Knowledge Models

Authors: Essam A. Al-Bahkali, Mahir H. Es-saheb, Jonny Herwan

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In this study the elastic-plastic stress distribution in weld-bonded joint, fabricated from austenitic stainless steel (AISI 304) sheet of 1.00 mm thickness and Epoxy adhesive Araldite 2011, subjected to axial loading is investigated. This is needed to improve design procedures and welding codes, and saving efforts in the cumbersome experiments and analysis. Therefore, a complete 3-D finite element modelling and analysis of spot welded, bonded and weld-bonded joints under axial loading conditions is carried out. A comprehensive systematic experimental program is conducted to determine many properties and quantities, of the base metals and the adhesive, needed for FE modelling, such like the elastic – plastic properties, modulus of elasticity, fracture limit, the nugget and heat affected zones (HAZ) properties, etc. Consequently, the finite element models developed, for each case, are used to evaluate stresses distributions across the entire joint, in both the elastic and plastic regions. The stress distribution curves are obtained, particularly in the elastic regions and found to be consistent and in excellent agreement with the published data. Furthermore, the stresses distributions are obtained in the weld-bonded joint and display the best results with almost uniform smooth distribution compared to spot and bonded cases. The stress concentration peaks at the edges of the weld-bonded region, are almost eliminated resulting in achieving the strongest joint of all processes.

Keywords: Spot Welded, Weld-Bonded, Load-Displacement curve, Stress distribution

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Authors: Hynek Chlup, Lukas Horny, Rudolf Zitny, Svatava Konvickova, Tomas Adamek

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Coronary artery bypass grafts (CABG) are widely studied with respect to hemodynamic conditions which play important role in presence of a restenosis. However, papers which concern with constitutive modeling of CABG are lacking in the literature. The purpose of this study is to find a constitutive model for CABG tissue. A sample of the CABG obtained within an autopsy underwent an inflation–extension test. Displacements were recoredered by CCD cameras and subsequently evaluated by digital image correlation. Pressure – radius and axial force – elongation data were used to fit material model. The tissue was modeled as onelayered composite reinforced by two families of helical fibers. The material is assumed to be locally orthotropic, nonlinear, incompressible and hyperelastic. Material parameters are estimated for two strain energy functions (SEF). The first is classical exponential. The second SEF is logarithmic which allows interpretation by means of limiting (finite) strain extensibility. Presented material parameters are estimated by optimization based on radial and axial equilibrium equation in a thick-walled tube. Both material models fit experimental data successfully. The exponential model fits significantly better relationship between axial force and axial strain than logarithmic one.

Keywords: Constitutive model, coronary artery bypass graft, digital image correlation, fiber reinforced composite, inflation test, saphenous vein.

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Authors: Sitansu Kumar Verma, Soni Yadav, Jitendra Singh, Shraddha, Ajay Kumar

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MicroRNAs (miRNAs), a class of approximately 22 nucleotide long non coding RNAs which play critical role in different biological processes. The mature microRNA is usually 19–27 nucleotides long and is derived from a bigger precursor that folds into a flawed stem-loop structure. Mature micro RNAs are involved in many cellular processes that encompass development, proliferation, stress response, apoptosis, and fat metabolism by gene regulation. Resent finding reveals that certain viruses encode their own miRNA that processed by cellular RNAi machinery. In recent research indicate that cellular microRNA can target the genetic material of invading viruses. Cellular microRNA can be used in the virus life cycle; either to up regulate or down regulate viral gene expression Computational tools use in miRNA target prediction has been changing drastically in recent years. Many of the methods have been made available on the web and can be used by experimental researcher and scientist without expert knowledge of bioinformatics. With the development and ease of use of genomic technologies and computational tools in the field of microRNA biology has superior tremendously over the previous decade. This review attempts to give an overview over the genome wide approaches that have allow for the discovery of new miRNAs and development of new miRNA target prediction tools and databases.

Keywords: MicroRNAs, computational tools, gene regulation, databases, RNAi.

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Authors: Farhad Asadi, S. Hossein Sadati

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Bayesian approach can be used for parameter identification and extraction in state space models and its ability for analyzing sequence of data in dynamical system is proved in different literatures. In this paper, adaptive Kalman filter with Bayesian approach for identification of variances in measurement parameter noise is developed. Next, it is applied for estimation of the dynamical state and measurement data in discrete linear dynamical system. This algorithm at each step time estimates noise variance in measurement noise and state of system with Kalman filter. Next, approximation is designed at each step separately and consequently sufficient statistics of the state and noise variances are computed with a fixed-point iteration of an adaptive Kalman filter. Different simulations are applied for showing the influence of noise variance in measurement data on algorithm. Firstly, the effect of noise variance and its distribution on detection and identification performance is simulated in Kalman filter without Bayesian formulation. Then, simulation is applied to adaptive Kalman filter with the ability of noise variance tracking in measurement data. In these simulations, the influence of noise distribution of measurement data in each step is estimated, and true variance of data is obtained by algorithm and is compared in different scenarios. Afterwards, one typical modeling of nonlinear state space model with inducing noise measurement is simulated by this approach. Finally, the performance and the important limitations of this algorithm in these simulations are explained. 

Keywords: adaptive filtering, Bayesian approach Kalman filtering approach, variance tracking

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Authors: Jing Zhou, Weiqun Su, Naying Luo, Min Shang, Li Wu

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The coupling of land use system in geographical research is mainly the coupling of pattern and process, which is essentially the human-land coupling, and is an important part of the research and discussion of human-land relationship. Based on the Web of Science database, the paper titles, authors, keywords, and references from 1997-2020 related to land use coupling were used as data sources to explore the research progress of land use coupling. Cite Space bibliometric tool was used for co-occurrence analysis of the issuing country, issuing institution, co-cited author, disciplinary institution, and keywords. The results are shown as follows: (1) From 1997 to 2020, the United States, China, and Germany rank the top, with more than 250 published papers. Although China ranks second in the number of published papers on foreign literature, it has less centrality and less influence. (2) The top 10 institutions (universities) in the number of published papers (more than 300 articles) are mainly from the United States and China, and the University of Chinese Academy of Sciences has the highest output of papers. At the same time, the phenomenon of multi-institutional cooperation has increased in the field of land use coupling research. (3) From 1997 to 2020, land sensitivity research and the impact of climate change on land use patterns are the main directions of land use coupling research. However, in the past five years, scholars have mainly focused on the coupling research methods of land use and the coupling relationship between ecological and environmental factors and land use.

Keywords: Land use coupling, cite space, knowledge graph, visual analysis, research progress.

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Authors: Mehrnoush Shamsfard, Azadeh Nematzadeh, Sarah Motiee

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Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques for extracting phrases and stemming words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula

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Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility and overhead & profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Keywords: Construction cost factors, neural networks, roadworks, Zambian Construction Industry.

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Authors: Mukesh Singh Boori, Venerando Eustáquio Amaro

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The objective of this study was to improve our understanding of vulnerability and environmental change; it's causes basically show the intensity, its distribution and human-environment effect on the ecosystem in the Apodi Valley Region, This paper is identify, assess and classify vulnerability and environmental change in the Apodi valley region using a combined approach of landscape pattern and ecosystem sensitivity. Models were developed using the following five thematic layers: Geology, geomorphology, soil, vegetation and land use/cover, by means of a Geographical Information Systems (GIS)-based on hydro-geophysical parameters. In spite of the data problems and shortcomings, using ESRI-s ArcGIS 9.3 program, the vulnerability score, to classify, weight and combine a number of 15 separate land cover classes to create a single indicator provides a reliable measure of differences (6 classes) among regions and communities that are exposed to similar ranges of hazards. Indeed, the ongoing and active development of vulnerability concepts and methods have already produced some tools to help overcome common issues, such as acting in a context of high uncertainties, taking into account the dynamics and spatial scale of asocial-ecological system, or gathering viewpoints from different sciences to combine human and impact-based approaches. Based on this assessment, this paper proposes concrete perspectives and possibilities to benefit from existing commonalities in the construction and application of assessment tools.

Keywords: Vulnerability, Land use/cover, Ecosystem, Remotesensing, GIS.

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Authors: B. Likar, K. Širok

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The paper presents a new method for efficient innovation process management. Even though the innovation management methods, tools and knowledge are well established and documented in literature, most of the companies still do not manage it efficiently. Especially in SMEs the front end of innovation - problem identification, idea creation and selection - is often not optimally performed. Our eMIPS methodology represents a sort of "umbrella methodology" - a well-defined set of procedures, which can be dynamically adapted to the concrete case in a company. In daily practice, various methods (e.g. for problem identification and idea creation) can be applied, depending on the company's needs. It is based on the proactive involvement of the company's employees supported by the appropriate methodology and external experts. The presented phases are performed via a mixture of face-to-face activities (workshops) and online (eLearning) activities taking place in eLearning Moodle environment and using other e-communication channels. One part of the outcomes is an identified set of opportunities and concrete solutions ready for implementation. The other also very important result is connected to innovation competences for the participating employees related with concrete tools and methods for idea management. In addition, the employees get a strong experience for dynamic, efficient and solution oriented managing of the invention process. The eMIPS also represents a way of establishing or improving the innovation culture in the organization. The first results in a pilot company showed excellent results regarding the motivation of participants and also as to the results achieved.

Keywords: Creativity, distance learning, front end, innovation, problem.

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Authors: Achela K. Fernando, Xiujuan Zhang, Peter F. Kinley

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A feed-forward, back-propagation Artificial Neural Network (ANN) model has been used to forecast the occurrences of wastewater overflows in a combined sewerage reticulation system. This approach was tested to evaluate its applicability as a method alternative to the common practice of developing a complete conceptual, mathematical hydrological-hydraulic model for the sewerage system to enable such forecasts. The ANN approach obviates the need for a-priori understanding and representation of the underlying hydrological hydraulic phenomena in mathematical terms but enables learning the characteristics of a sewer overflow from the historical data. The performance of the standard feed-forward, back-propagation of error algorithm was enhanced by a modified data normalizing technique that enabled the ANN model to extrapolate into the territory that was unseen by the training data. The algorithm and the data normalizing method are presented along with the ANN model output results that indicate a good accuracy in the forecasted sewer overflow rates. However, it was revealed that the accurate forecasting of the overflow rates are heavily dependent on the availability of a real-time flow monitoring at the overflow structure to provide antecedent flow rate data. The ability of the ANN to forecast the overflow rates without the antecedent flow rates (as is the case with traditional conceptual reticulation models) was found to be quite poor.

Keywords: Artificial Neural Networks, Back-propagationlearning, Combined sewer overflows, Forecasting.

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Authors: Fadi Eleiwi, Taous Meriem Laleg-Kirati

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This paper presents a complete dynamic modeling of a membrane distillation process. The model contains two consistent dynamic models. A 2D advection-diffusion equation for modeling the whole process and a modified heat equation for modeling the membrane itself. The complete model describes the temperature diffusion phenomenon across the feed, membrane, permeate containers and boundary layers of the membrane. It gives an online and complete temperature profile for each point in the domain. It explains heat conduction and convection mechanisms that take place inside the process in terms of mathematical parameters, and justify process behavior during transient and steady state phases. The process is monitored for any sudden change in the performance at any instance of time. In addition, it assists maintaining production rates as desired, and gives recommendations during membrane fabrication stages. System performance and parameters can be optimized and controlled using this complete dynamic model. Evolution of membrane boundary temperature with time, vapor mass transfer along the process, and temperature difference between membrane boundary layers are depicted and included. Simulations were performed over the complete model with real membrane specifications. The plots show consistency between 2D advection-diffusion model and the expected behavior of the systems as well as literature. Evolution of heat inside the membrane starting from transient response till reaching steady state response for fixed and varying times is illustrated.

Keywords: Membrane distillation, Dynamical modeling, Advection-diffusion equation, Thermal equilibrium, Heat equation.

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Authors: Meng Fanchao, Zhan Dechen, Xu Xiaofei

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Software reuse can be considered as the most realistic and promising way to improve software engineering productivity and quality. Automated assistance for software reuse involves the representation, classification, retrieval and adaptation of components. The representation and retrieval of components are important to software reuse in Component-Based on Software Development (CBSD). However, current industrial component models mainly focus on the implement techniques and ignore the semantic information about component, so it is difficult to retrieve the components that satisfy user-s requirements. This paper presents a method of business component retrieval based on specification matching to solve the software reuse of enterprise information system. First, a business component model oriented reuse is proposed. In our model, the business data type is represented as sign data type based on XML, which can express the variable business data type that can describe the variety of business operations. Based on this model, we propose specification match relationships in two levels: business operation level and business component level. In business operation level, we use input business data types, output business data types and the taxonomy of business operations evaluate the similarity between business operations. In the business component level, we propose five specification matches between business components. To retrieval reusable business components, we propose the measure of similarity degrees to calculate the similarities between business components. Finally, a business component retrieval command like SQL is proposed to help user to retrieve approximate business components from component repository.

Keywords: Business component, business operation, business data type, specification matching.

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Authors: M. L. Arias, J. D’Adamo, M. N. Novosad, P. A. Raffo, H. P. Burbridge, G. O. Artana

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Shale oils are highly paraffinic and, consequently, can create wax deposits that foul pipelines during transportation. Several factors must be considered when designing pipelines or treatment programs that prevent wax deposition: including chemical species in crude oils, flowrates, pipes diameters and temperature. This paper describes the wax deposition study carried out within the framework of YPF Tecnolgía S.A. (Y-TEC) flow assurance projects, as part of the process to achieve a better understanding on wax deposition issues. Laboratory experiments were performed on a medium size, 1 inch diameter, wax deposition loop of 15 meters long equipped with a solid detector system, online microscope to visualize crystals, temperature, and pressure sensors along the loop pipe. A baseline test was performed with diesel with no added paraffin or additive content. Tests were undertaken with different temperatures of circulating and cooling fluid at different flow conditions. Then, a solution formed with a paraffin incorporated to the diesel was considered. Tests varying flowrate and cooling rate were again run. Viscosity, density, WAT (Wax Appearance Temperature) with DSC (Differential Scanning Calorimetry), pour point and cold finger measurements were carried out to determine physical properties of the working fluids. The results obtained in the loop were analyzed through momentum balance and heat transfer models. To determine possible paraffin deposition scenarios temperature and pressure loop output signals were studied. They were compared with WAT static laboratory methods.

Keywords: Paraffin deposition, wax, oil pipelines, experimental pipe loop.

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the elearning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery.

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Authors: Natalia Moreira, Trevor Wood-Harper

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The acceptance of sustainable products by the final consumer is still one of the challenges of the industry, which constantly seeks alternative approaches to successfully be accepted in the global market. A large set of methods and approaches have been discussed and analysed throughout the literature. Considering the current need for sustainable development and the current pace of consumption, the need for a combined solution towards the development of new products became clear, forcing researchers in product development to propose alternatives to the previous standard product development models. This paper presents, through a systemic analysis of the literature on product development, eco-design and consumer involvement, a set of alternatives regarding consumer involvement towards the development of sustainable products and how these approaches could help improve the sustainable industry’s establishment in the general market. Still being developed in the course of the author’s PhD, the initial findings of the research show that the understanding of the benefits of sustainable behaviour lead to a more conscious acquisition and eventually to the implementation of sustainable change in the consumer. Thus this paper is the initial approach towards the development of new sustainable products using the fashion industry as an example of practical implementation and acceptance by the consumers. By comparing the existing literature and critically analysing it, this paper concluded that the consumer involvement is strategic to improve the general understanding of sustainability and its features. The use of consumers and communities has been studied since the early 90s in order to exemplify uses and to guarantee a fast comprehension. The analysis done also includes the importance of this approach for the increase of innovation and ground breaking developments, thus requiring further research and practical implementation in order to better understand the implications and limitations of this methodology.

Keywords: Consumer involvement, Products development, Sustainability.

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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Authors: Atif Mehmood, Said M. Easa

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This paper develops driver reaction-time models for car-following analysis based on human factors. The reaction time was classified as brake-reaction time (BRT) and acceleration/deceleration reaction time (ADRT). The BRT occurs when the lead vehicle is barking and its brake light is on, while the ADRT occurs when the driver reacts to adjust his/her speed using the gas pedal only. The study evaluates the effect of driver characteristics and traffic kinematic conditions on the driver reaction time in a car-following environment. The kinematic conditions introduced urgency and expectancy based on the braking behaviour of the lead vehicle at different speeds and spacing. The kinematic conditions were used for evaluating the BRT and are classified as normal, surprised, and stationary. Data were collected on a driving simulator integrated into a real car and included the BRT and ADRT (as dependent variables) and driver-s age, gender, driving experience, driving intensity (driving hours per week), vehicle speed, and spacing (as independent variables). The results showed that there was a significant difference in the BRT at normal, surprised, and stationary scenarios and supported the hypothesis that both urgency and expectancy had significant effects on BRT. Driver-s age, gender, speed, and spacing were found to be significant variables for the BRT in all scenarios. The results also showed that driver-s age and gender were significant variables for the ADRT. The research presented in this paper is part of a larger project to develop a driversensitive in-vehicle rear-end collision warning system.

Keywords: Brake reaction time, car-following, human factors, modeling.

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Authors: Srinivasan Aruchamy, Partha Bhattacharjee, Goutam Sanyal

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Optic disk segmentation plays a key role in the mass screening of individuals with diabetic retinopathy and glaucoma ailments. An efficient hardware-based algorithm for optic disk localization and segmentation would aid for developing an automated retinal image analysis system for real time applications. Herein, TMS320C6416DSK DSP board pixel intensity based fractal analysis algorithm for an automatic localization and segmentation of the optic disk is reported. The experiment has been performed on color and fluorescent angiography retinal fundus images. Initially, the images were pre-processed to reduce the noise and enhance the quality. The retinal vascular tree of the image was then extracted using canny edge detection technique. Finally, a pixel intensity based fractal analysis is performed to segment the optic disk by tracing the origin of the vascular tree. The proposed method is examined on three publicly available data sets of the retinal image and also with the data set obtained from an eye clinic. The average accuracy achieved is 96.2%. To the best of the knowledge, this is the first work reporting the use of TMS320C6416DSK DSP board and pixel intensity based fractal analysis algorithm for an automatic localization and segmentation of the optic disk. This will pave the way for developing devices for detection of retinal diseases in the future.

Keywords: Color retinal fundus images, Diabetic retinopathy, Fluorescein angiography retinal fundus images, Fractal analysis.

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Authors: Bilgehan Gültekin, Tuba Gültekin

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It is quite essential to form dialogue mechanisms and dialogue channels to solve intercultural communication issues. Therefore, every country should develop a intercultural education project which aims to resolve international communication issues. For proper mediation training, the first step is to reach an agreement on the actors to run the project. The strongest mediation mechanisms in the world should be analyzed and initiated within the educational policies. A communication-based mediation model should be developed for international mediation training. Mediators can use their convincing communication skills as a part of this model. At the first, fundamental stages of the mediation training should be specified within the scope of the model. Another important topic at this point is common sence and peace leaders to act as an ombudsman in this process. Especially for solving some social issues and conflicts, common sense leaders acting as an ombudsman would lead to effective communication. In mediation training that is run by universities and non-governmental organizations, another phase is to focus on conducting the meetings. In intercultural mediation training, one of the most critical topics is to conduct the meeting traffic and performing a shuttle diplomacy. Meeting traffic is where the mediator organizes meetings with the parties with initiative powers, in order to contribute to the solution of the issue, and schedule these meetings. In this notice titled “ Intercultural mediation training and the training process of common sense leaders by the leadership of universities communication and artistic campaigns" , communication models and strategies about this topic will be constructed and an intercultural art activities and perspectives will be presented.

Keywords: Intercultural communication, mediation education, common sense leaders, artistic sensitivity

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Authors: N. Talisa, K. Rungsarid, P. Chakrit

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The objectives of the research are to study the existing agricultural patterns, and to evaluate the sustainability of agricultural on economic, social and environmental aspects. The samplings were the representatives of the agriculturist group from Ban Paew district, Samut Sakorn province by purposive sampling method of 30 households. The tools being used were interview forms together with the Rapid Rural Appraisal (RRA) and the Participation Rural Appraisal (PRA). The information collected was analyzed with the principle of Content Analysis andusing Descriptive Statistics. After that all the information gotten was analyze the sustainability on the household level and village level. The research result can be concluded as follows: The agricultural Patterns: For most of the cultivation main crop was fruit trees planted and the supplement crop was around the patch or added other plants in the trenches. There were trenches for the cultivating water. The product distribution was by selling (97.5%) and the selling to middle man was the highest number (62.5%). Evaluating the sustainability of the agricultural by the indicators which were appropriate to the area: For the agricultural sustainability on the household level it was found that only one household had sustainable, others household had conditioned sustainable. For on the village level it was found that the sustainability on the issue of agricultural knowledge training had the lowest level (Sustainability index = 31.67%). Secondary was the acknowledging about soil information (Sustainability index = 35.0), and the household labors on agriculture, net return over cash cost (Sustainability index = 55.0%) respectively. Performance percentage is 48.81 %. It was brought to the conclusion that this area did not have the agricultural sustainability.

Keywords: Sustainability of agricultural, sustainability indicators, sustainability index.

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Authors: Triloksingh G. Arora, Mohan V. Aware, Dhananjay R. Tutakne

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Thyristor based firing angle controlled voltage regulators are extensively used for speed control of single phase induction motors. This leads to power saving but the applied voltage and current waveforms become non-sinusoidal. These non-sinusoidal waveforms increase voltage and thermal stresses which result into accelerated insulation aging, thus reducing the motor life. Life models that allow predicting the capability of insulation under such multi-stress situations tend to be very complex and somewhat impractical. This paper presents the fuzzy logic application to investigate the synergic effect of voltage and thermal stresses on intrinsic aging of induction motor insulation. A fuzzy expert system is developed to estimate the life of induction motor insulation under multiple stresses. Three insulation degradation parameters, viz. peak modification factor, wave shape modification factor and thermal loss are experimentally obtained for different firing angles. Fuzzy expert system consists of fuzzyfication of the insulation degradation parameters, algorithms based on inverse power law to estimate the life and defuzzyficaton process to output the life. An electro-thermal life model is developed from the results of fuzzy expert system. This fuzzy logic based electro-thermal life model can be used for life estimation of induction motors operated with non-sinusoidal voltage and current waveforms.

Keywords: Aging, Dielectric losses, Insulation and Life Estimation.

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Authors: Federico Pittino, Dominik Holzmann, Krithika Sayar-Chand, Stefan Moser, Sebastian Pliessnig, Thomas Arnold

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The shredding of waste materials is a key step in the recycling process towards circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need of frequent maintenance of critical components. The maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for several months and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring a very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

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Authors: Anwaar Ahmed, Muhammad Bilal Khurshid, Samuel Labi

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The effect of trucks on the level of service is determined by considering passenger car equivalents (PCE) of trucks. The current version of Highway Capacity Manual (HCM) uses a single PCE value for all tucks combined. However, the composition of truck traffic varies from location to location; therefore, a single PCE value for all trucks may not correctly represent the impact of truck traffic at specific locations. Consequently, present study developed separate PCE values for single-unit and combination trucks to replace the single value provided in the HCM on different freeways. Site specific PCE values, were developed using concept of spatial lagging headways (that is the distance between rear bumpers of two vehicles in a traffic stream) measured from field traffic data. The study used data from four locations on a single urban freeway and three different rural freeways in Indiana. Three-stage-leastsquares (3SLS) regression techniques were used to generate models that predicted lagging headways for passenger cars, single unit trucks (SUT), and combination trucks (CT). The estimated PCE values for single-unit and combination truck for basic urban freeways (level terrain) were: 1.35 and 1.60, respectively. For rural freeways the estimated PCE values for single-unit and combination truck were: 1.30 and 1.45, respectively. As expected, traffic variables such as vehicle flow rates and speed have significant impacts on vehicle headways. Study results revealed that the use of separate PCE values for different truck classes can have significant influence on the LOS estimation.

Keywords: Level of Service, Capacity Analysis, Lagging Headway.

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Authors: Achim Washington, Reece Clothier, Jose Silva

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System Safety Regulations (SSR) are a central component to the airworthiness certification of Unmanned Aircraft Systems (UAS). There is significant debate on the setting of appropriate SSR for UAS. Putting this debate aside, the challenge lies in how to apply the system safety process to UAS, which lacks the data and operational heritage of conventionally piloted aircraft. The limited knowledge and lack of operational data result in uncertainty in the system safety assessment of UAS. This uncertainty can lead to incorrect compliance findings and the potential certification and operation of UAS that do not meet minimum safety performance requirements. The existing system safety assessment and compliance processes, as used for conventional piloted aviation, do not adequately account for the uncertainty, limiting the suitability of its application to UAS. This paper discusses the challenges of undertaking system safety assessments for UAS and presents current and envisaged research towards addressing these challenges. It aims to highlight the main advantages associated with adopting a risk based framework to the System Safety Performance Requirement (SSPR) compliance process that is capable of taking the uncertainty associated with each of the outputs of the system safety assessment process into consideration. Based on this study, it is made clear that developing a framework tailored to UAS, would allow for a more rational, transparent and systematic approach to decision making. This would reduce the need for conservative assumptions and take the risk posed by each UAS into consideration while determining its state of compliance to the SSR.

Keywords: Part 1309 regulations, unmanned aircraft systems, system safety, uncertainty.

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Authors: Paula A. Cruise, Carvell McLeary

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Employee turnover leads to lowered productivity, decreased morale and work quality, and psychological effects associated with employee separation and replacement. Yet, it remains unknown why talented employees willingly withdraw from organizations. This uncertainty is worsened as studies; a) priorities organizational over individual predictors resulting in restriction in range in turnover measurement; b) focus on actual rather than intended turnover thereby limiting conceptual understanding of the turnover construct and its relationship with other variables and; c) produce inconsistent findings across cultures, contexts and industries despite a clear need for a unified perspective. The current study addressed these gaps by adopting the theory of planned behavior (TPB) framework to examine socio-cognitive factors in organizational trust and individual turnover intentions among bankers and energy employees in Jamaica. In a comparative study of n=369 [n_bank= 264; male=57 (22.73%); n_energy =105; male =45 (42.86)], it was hypothesized that organizational trust was a predictor of employee turnover intention, and the effect of individual, group, cognitive and socio-affective variables varied across industry. Findings from structural equation modelling confirmed the hypothesis, with a model of both cognitive and socio-affective variables being a better fit [CMIN (χ²) = 800.067, df = 364, p ≤ .000; CFI = 0.950; RMSEA = 0.057 with 90% C.I. (0.052 - 0.062); PCLOSE = 0.016; PNFI = 0.818 in predicting turnover intention. The findings are discussed in relation to socio-cognitive components of trust models and predicting negative employee behaviors across cultures and industries.

Keywords: Context-specific organizational trust, cross-cultural psychology, theory of planned behavior, employee turnover intention.

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Authors: Ali Ben Abbes, ImedRiadh Farah, Vincent Barra

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Remotely sensed data are a significant source for monitoring and updating databases for land use/cover. Nowadays, changes detection of urban area has been a subject of intensive researches. Timely and accurate data on spatio-temporal changes of urban areas are therefore required. The data extracted from multi-temporal satellite images are usually non-stationary. In fact, the changes evolve in time and space. This paper is an attempt to propose a methodology for changes detection in urban area by combining a non-stationary decomposition method and stochastic modeling. We consider as input of our methodology a sequence of satellite images I₁, I₂, … I_n at different periods (t = 1, 2, ..., n). Firstly, a preprocessing of multi-temporal satellite images is applied. (e.g. radiometric, atmospheric and geometric). The systematic study of global urban expansion in our methodology can be approached in two ways: The first considers the urban area as one same object as opposed to non-urban areas (e.g. vegetation, bare soil and water). The objective is to extract the urban mask. The second one aims to obtain a more knowledge of urban area, distinguishing different types of tissue within the urban area. In order to validate our approach, we used a database of Tres Cantos-Madrid in Spain, which is derived from Landsat for a period (from January 2004 to July 2013) by collecting two frames per year at a spatial resolution of 25 meters. The obtained results show the effectiveness of our method.

Keywords: Multi-temporal satellite image, urban growth, Non-stationarity, stochastic modeling.

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Authors: Mrinalini Amritkar, Disha Patil, Swapna Kulkarni, Sukratu Barve, Suresh Gosavi

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Micro-mixers play an important role in the lab-on-a-chip applications and micro total analysis systems to acquire the correct level of mixing for any given process. The mixing process can be classified as active or passive according to the use of external energy. Literature of microfluidics reports that most of the work is done on the models of steady laminar flow; however, the study of unsteady laminar flow is an active area of research at present. There are wide applications of this, out of which, we consider nanoparticle synthesis in micro-mixers. In this work, we have developed a model for unsteady flow to study the mixing performance of a passive micro mixer for reactants used for such synthesis. The model is developed in Finite Volume Method (FVM)-based software, OpenFOAM. The model is tested by carrying out the simulations at Re of 0.5. Mixing performance of the micro-mixer is investigated using simulated concentration values of mixed species across the width of the micro-mixer and calculating the variance across a line profile. Experimental validation is done by passing dyes through a Y shape micro-mixer fabricated using polydimethylsiloxane (PDMS) polymer and comparing variances with the simulated ones. Gold nanoparticles are later synthesized through the micro-mixer and collected at two different times leading to significantly different size distributions. These times match with the time scales over which reactant concentrations vary as obtained from simulations. Our simulations could thus be used to create design aids for passive micro-mixers used in nanoparticle synthesis.

Keywords: Lab-on-chip, micro-mixer, OpenFOAM, PDMS.

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Authors: A. Iaaly, O. Jadayel, R. Jadayel

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This paper explores the effectiveness of approaches used for the implementation of technology within central governments specifically Geographic Information Systems (GIS). It examines the extent to which various strategies to GIS implementation and its roll out to users within an organization is crucial for its long term assimilation. Depending on the contextual requirements, various implementation strategies exist spanning from the most revolutionary to the most evolutionary, which have an influence on the success of GIS projects and the realization of resulting business benefits within the central governments. This research compares between two strategies of GIS implementation within the Lebanese Municipalities. The first strategy is the “Technological Approach” which is focused on technology acquisition, overlaid on existing governmental frameworks. This approach gives minimal attention to capability building and the long term sustainability of the implemented program. The second strategy, referred to as the “Ecological Approach”, is naturally oriented to the function of the organization. This approach stresses on fostering the evolution of the program and on building the human capabilities. The Union of the Joumeh Municipalities will be presented as a case study under the “Ecological Approach” and the role of the GIS Center at the University of Balamand will be highlighted. Thus, this research contributes to the development of knowledge on technology implementation and the vital role of academia in the specific context of the Lebanese public sector so that this experience may pave the way for further applications.

Keywords: Ecological Approach, GIS, low income countries, technological approach.

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Authors: Mahdi Karimi

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One of the most basic standards of fair trial is the right to defense, hire an attorney and its presence in the hearing stages. On the one hand, based on the reason and justice, as the legal issues, particularly criminal affairs, become complicated, the accused must benefit from an attorney in the court in order to defend itself which requires legal knowledge. On the other hand, as the judicial system has jurists such as investigation judges at its disposal, the accused must enjoy the same right to defend itself and reject allegations so that the balance is maintained between the litigating parties based on the principle of "equality of arms". The right to adequate time and facilities for defense is cited among the principles and rights relevant to the proceedings in international regulations such as the International Covenant on Civil and Political Rights. The innovations made in the Code of Criminal Procedure in 2013 guaranteed the presence of the accused’s attorney in the proceedings. The present study aims at assessing the result of the aforementioned guarantee in practice and made attempts to investigate the effect of the presence of accused’s attorney on reducing the punishment by asking the question and addressing the statistical population of this study including 48 judges of lower courts and courts of appeal. It seems that in despite of guarantees provided in the new Code of Criminal Procedure, Iran's penal system, does not tolerate the presence of an attorney in practice.

Keywords: Defense attorney, equality of arms, fair trial, reducing the penalty, right to defense.

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Authors: Gesine Hellwig

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Functional imaging procedures for the non-invasive assessment of tissue microcirculation are highly requested, but require a mathematical approach describing the trans- and intercapillary passage of tracer particles. Up to now, two theoretical, for the moment different concepts have been established for tracer kinetic modeling of contrast agent transport in tissues: pharmacokinetic compartment models, which are usually written as coupled differential equations, and the indicator dilution theory, which can be generalized in accordance with the theory of lineartime- invariant (LTI) systems by using a convolution approach. Based on mathematical considerations, it can be shown that also in the case of an open two-compartment model well-known from functional imaging, the concentration-time course in tissue is given by a convolution, which allows a separation of the arterial input function from a system function being the impulse response function, summarizing the available information on tissue microcirculation. Due to this reason, it is possible to integrate the open two-compartment model into the system-theoretic concept of indicator dilution theory (IDT) and thus results known from IDT remain valid for the compartment approach. According to the long number of applications of compartmental analysis, even for a more general context similar solutions of the so-called forward problem can already be found in the extensively available appropriate literature of the seventies and early eighties. Nevertheless, to this day, within the field of biomedical imaging – not from the mathematical point of view – there seems to be a trench between both approaches, which the author would like to get over by exemplary analysis of the well-known model.

Keywords: Functional imaging, Tracer kinetic modeling, LTIsystem, Indicator dilution theory / convolution approach, Two-Compartment model.

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