Search results for: regression models.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3085

Search results for: regression models.

865 Active Vibration Control of Passenger Seat with HFPIDCR Controlled Suspension Alternatives

Authors: Devdutt, M. L. Aggarwal

Abstract:

In this paper, passenger ride comfort issues are studied taking active quarter car model with three degrees of freedom. A hybrid fuzzy – PID controller with coupled rules (HFPIDCR) is designed for vibration control of passenger seat. Three different control strategies are considered. In first case, main suspension is controlled. In second case, passenger seat suspension is controlled. In third case, both main suspension and passenger seat suspensions are controlled. Passenger seat acceleration and displacement results are obtained using bump and sinusoidal type road disturbances. Finally, obtained simulation results of designed uncontrolled and controlled quarter car models are compared and discussed to select best control strategy for achieving high level of passenger ride comfort.

Keywords: Active suspension system, HFPIDCR controller, passenger ride comfort, quarter car model.

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864 Statistical Analysis and Optimization of a Process for CO2 Capture

Authors: Muftah H. El-Naas, Ameera F. Mohammad, Mabruk I. Suleiman, Mohamed Al Musharfy, Ali H. Al-Marzouqi

Abstract:

CO2 capture and storage technologies play a significant role in contributing to the control of climate change through the reduction of carbon dioxide emissions into the atmosphere. The present study evaluates and optimizes CO2 capture through a process, where carbon dioxide is passed into pH adjusted high salinity water and reacted with sodium chloride to form a precipitate of sodium bicarbonate. This process is based on a modified Solvay process with higher CO2 capture efficiency, higher sodium removal, and higher pH level without the use of ammonia. The process was tested in a bubble column semi-batch reactor and was optimized using response surface methodology (RSM). CO2 capture efficiency and sodium removal were optimized in terms of major operating parameters based on four levels and variables in Central Composite Design (CCD). The operating parameters were gas flow rate (0.5–1.5 L/min), reactor temperature (10 to 50 oC), buffer concentration (0.2-2.6%) and water salinity (25-197 g NaCl/L). The experimental data were fitted to a second-order polynomial using multiple regression and analyzed using analysis of variance (ANOVA). The optimum values of the selected variables were obtained using response optimizer. The optimum conditions were tested experimentally using desalination reject brine with salinity ranging from 65,000 to 75,000 mg/L. The CO2 capture efficiency in 180 min was 99% and the maximum sodium removal was 35%. The experimental and predicted values were within 95% confidence interval, which demonstrates that the developed model can successfully predict the capture efficiency and sodium removal using the modified Solvay method.

Keywords: Bubble column reactor, CO2 capture, Response Surface Methodology, water desalination.

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863 Dissolved Oxygen Prediction Using Support Vector Machine

Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

Abstract:

In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, Water Temperature, and Conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: Dissolved oxygen, Water quality, predication DO, Support Vector Machine.

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862 Influence of Drought on Yield and Yield Components in White Bean

Authors: Gholamreza Habibi

Abstract:

In order to study seed yield and seed yield components in bean under reduced irrigation condition and assessment drought tolerance of genotypes, 15 lines of White beans were evaluated in two separate RCB design with 3 replications under stress and non stress conditions. Analysis of variance showed that there were significant differences among varieties in terms of traits under study, indicating the existence of genetic variation among varieties. The results indicate that drought stress reduced seed yield, number of seed per plant, biological yield and number of pod in White been. In non stress condition, yield was highly correlated with the biological yield, whereas in stress condition it was highly correlated with harvest index. Results of stepwise regression showed that, selection can we done based on, biological yield, harvest index, number of seed per pod, seed length, 100 seed weight. Result of path analysis showed that the highest direct effect, being positive, was related to biological yield in non stress and to harvest index in stress conditions. Factor analysis were accomplished in stress and nonstress condition a, there were 4 factors that explained more than 76 percent of total variations. We used several selection indices such as Stress Susceptibility Index ( SSI ), Geometric Mean Productivity ( GMP ), Mean Productivity ( MP ), Stress Tolerance Index ( STI ) and Tolerance Index ( TOL ) to study drought tolerance of genotypes, we found that the best Stress Index for selection tolerance genotypes were STI, GMP and MP were the greatest correlations between these Indices and seed yield under stress and non stress conditions. In classification of genotypes base on phenotypic characteristics, using cluster analysis ( UPGMA ), all allels classified in 5 separate groups in stress and non stress conditions.

Keywords: Cluster analysis, factor analysis, path analysis, selection index, White bean

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861 Present and Future Climate Extreme Indices over Sinai Peninsula, Egypt

Authors: Mahmoud Roushdi, Hany Mostafa, Khaled Kheireldin

Abstract:

Sinai Peninsula and Suez Canal Corridor are promising and important economic regions in Egypt due to the unique location and development opportunities. Thus, the climate change impacts should be assessed over the mentioned area. Accordingly, this paper aims to assess the climate extreme indices in through the last 35 year over Sinai Peninsula and Suez Canal Corridor in addition to predict the climate extreme indices up to 2100. Present and future climate indices were analyzed with using different RCP scenarios 4.5 and 8.5 from 2010 until 2100 for Sinai Peninsula and Suez Canal Corridor. Furthermore, both CanESM and HadGEM2 global circulation models were used. The results indicate that the number of summer days is predicted to increase, on the other hand the frost days is predicted to decrease. Moreover, it is noted a slight positive trend for the percentile of wet and extremely days R95p and R99p for RCP4.5 and negative trend for RCP8.5.

Keywords: Climate change, extreme indices, RCP, Sinai Peninsula.

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860 Decision Support System for a Pilot Flash Flood Early Warning System in Central Chile

Authors: D. Pinto, L. Castro, M.L. Cruzat, S. Barros, J. Gironás, C. Oberli, M. Torres, C. Escauriaza, A. Cipriano

Abstract:

Flash Floods, together with landslides, are a common natural threat for people living in mountainous regions and foothills. One way to deal with this constant menace is the use of Early Warning Systems, which have become a very important mitigation strategy for natural disasters. In this work we present our proposal for a pilot Flash Flood Early Warning System for Santiago, Chile, the first stage of a more ambitious project that in a future stage shall also include early warning of landslides. To give a context for our approach, we first analyze three existing Flash Flood Early Warning Systems, focusing on their general architectures. We then present our proposed system, with main focus on the decision support system, a system that integrates empirical models and fuzzy expert systems to achieve reliable risk estimations.

Keywords: Decision Support System, Early Warning Systems, Flash Flood, Natural Hazard.

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859 Ecotoxicological Safety of Wastewater Treated with Lignocellulosic Adsorbents

Authors: Luísa P. Cruz-Lopes, Artur Figueirinha, Isabel Brás, Bruno Esteves

Abstract:

Portugal is an important wine and olive oil producer, activities which generate a high quantity of residues commonly called grape stalks and olive cake, respectively. In this work grape stalks and olive cake were used as lignocellulosic adsorbents for wastewater containing lead treatment. To attain a better knowledge of the factors that could influence the quality of the treated wastewater, a chemical characterization of the materials used in the treatment was done. To access the ecotoxicological safety of the treated wastewater, several tests were performed.

The results of the toxicity test show that the samples leachate has a mild effect on the living models tested. The tests performed in lemna and bacteria were the most sensible to toxicity effects of the samples. The results obtained in this work evidenced the importance of use of simple and fast toxicity tests to predict impacts in the environment.

Keywords: Chemical composition, ecotoxicological, lignocellulosic residues, safety.

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858 Mental Illness Stigma and Causal Beliefs: Among Potential Mental Health Professionals

Authors: Josephine S. Larkings, Patricia M. Brown

Abstract:

Mental health professionals views about mental illness is an important issue which has not received enough attention. The negative stigma associated with mental illness can have many negative consequences. Unfortunately, health professionals working with the mentally ill can also exhibit stigma. It has been suggested that causal explanations or beliefs around the causes of mental illness may influence stigma. This study aims to gain a greater insight into stigma through examining stigma among potential mental health professionals. Firstly, results found that potential mental health professionals had relatively low social distance t(205) = -3.62, p <.001. Secondly, an ANOVA indicated that the participants endorsed some causal beliefs more than others, F(1.82, 311.55) = 88.47, p < .001, partial n2 = .34. Moreover, participants endorsed the biological causal explanation the most. Thirdly, results indicated that combined contact (quality and quantity) and causal beliefs (biological, psychological, and environmental) explained a significant proportion of the variance in stigma, R2 = .35, adjusted R2 = .33, F(5, 153) = 16.66, p < .001. Quality of contact was the strongest predictor, with greater quality of contact associated with lower desired social distance. Also, quantity of contact, psychological and environmental causal explanations were also significant predictors of stigma. Greater quantity of contact and higher levels of environmental causal beliefs were associated with lower levels of stigma while psychological causal explanations were associated with higher levels of stigma. A series of multiple regression analyses were conducted that showed the three causal beliefs had different impacts on four factors of stigma (Authoritarian, Benevolence, Social restrictiveness, and Community mental health ideology). These analyses showed that psychological causal beliefs had the most positive impact. More research is required on this topic as it has important implications to the treatment and recovery for people suffering from mental illness.

Keywords: Causal beliefs, contact, health professionals, mental illness stigma, social distance.

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857 Director Compensation, CEO Duality, State Ownership, and Firm Performance in China: Proof from Panel Data of Publicly Listed Enterprises from 1999 to 2020

Authors: Wanda Luen-Wun Siu, Xiaowen Zhang

Abstract:

This paper offered the primary methodical proof on how director remuneration related to enterprise earnings in listed firms in China in light of most evidence focusing on cross-sectional data or data in a short span of time. Using full economic and business panel data on China’s publicly listed enterprise from 1999 to 2020 over two decades in the China Stock Market & Accounting Research database, we found statistically significant positive associations between director pay and firm performance in privately owned firms over this period, supporting the agency theory. In contrast, among the state-owned enterprises, there was a reverse relation between director compensation and firm financial performance, contributing to the existing literature. But the results also revealed that state-owned enterprises financially performed as well as private enterprises. Such findings suggested that state ownership might line up officials’ career incentives with party prime concern rather than pecuniary incentives. Also, CEO duality enhanced firm performance. As such, allegiance to the party and possible advancement to an upper-level political position would motivate company directors in state-owned enterprises. On the other hand, directors in privately owned enterprises might be motivated by monetary incentives. In addition, a statistical regression model was proposed and tested to get the results of the performance of state-owned enterprises. Finally, some suggestions were made about how to improve the institutional management of government-owned corporations in China.

Keywords: China’s listed Firm, director compensation, CEO duality, firm performance, panel analysis.

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856 An Investigation into the Role of Market Beta in Asset Pricing: Evidence from the Romanian Stock Market

Authors: Ioan Popa, Radu Lupu, Cristiana Tudor

Abstract:

In this paper, we apply the FM methodology to the cross-section of Romanian-listed common stocks and investigate the explanatory power of market beta on the cross-section of commons stock returns from Bucharest Stock Exchange. Various assumptions are empirically tested, such us linearity, market efficiency, the “no systematic effect of non-beta risk" hypothesis or the positive expected risk-return trade-off hypothesis. We find that the Romanian stock market shows the same properties as the other emerging markets in terms of efficiency and significance of the linear riskreturn models. Our analysis included weekly returns from January 2002 until May 2010 and the portfolio formation, estimation and testing was performed in a rolling manner using 51 observations (one year) for each stage of the analysis.

Keywords: Bucharest Stock Exchange, Fama-Macbeth methodology, systematic risk, non-linear risk-return dependence.

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855 Vr-GIS and Ar-GIS In Education: A Case Study

Authors: Ilario Gabriele Gerloni, Vincenza Carchiolo, Alessandro Longheu, Ugo Becciani, Eva Sciacca, Fabio Vitello

Abstract:

ICT tools and platforms endorse more and more educational process. Many models and techniques for people to be educated and trained about specific topics and skills do exist, as classroom lectures with textbooks, computers, handheld devices and others. The choice to what extent ICT is applied within learning contexts is related to personal access to technologies as well as to the infrastructure surrounding environment. Among recent techniques, the adoption of Virtual Reality (VR) and Augmented Reality (AR) provides significant impulse in fully engaging users senses. In this paper, an application of AR/VR within Geographic Information Systems (GIS) context is presented. It aims to provide immersive environment experiences for educational and training purposes (e.g. for civil protection personnel), useful especially for situations where real scenarios are not easily accessible by humans. First acknowledgments are promising for building an effective tool that helps civil protection personnel training with risk reduction.

Keywords: Education, virtual reality, augmented reality, civil protection.

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854 Cloud Computing Support for Diagnosing Researches

Authors: A. Amirov, O. Gerget, V. Kochegurov

Abstract:

One of the main biomedical problem lies in detecting dependencies in semi structured data. Solution includes biomedical portal and algorithms (integral rating health criteria, multidimensional data visualization methods). Biomedical portal allows to process diagnostic and research data in parallel mode using Microsoft System Center 2012, Windows HPC Server cloud technologies. Service does not allow user to see internal calculations instead it provides practical interface. When data is sent for processing user may track status of task and will achieve results as soon as computation is completed. Service includes own algorithms and allows diagnosing and predicating medical cases. Approved methods are based on complex system entropy methods, algorithms for determining the energy patterns of development and trajectory models of biological systems and logical–probabilistic approach with the blurring of images.

Keywords: Biomedical portal, cloud computing, diagnostic and prognostic research, mathematical data analysis.

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853 A Quality-Oriented Approach toward Strategic Positioning in Higher Education Institutions

Authors: M. M. Mashhadi, K. Mohajeri, M. D. Nayeri

Abstract:

Positioning the organization in the strategic environment of its industry is one of the first and most important phases of the organizational strategic planning and in today knowledge-based economy has its importance been duplicated for higher education institutes as the centers of education, knowledge creation and knowledge worker training. Up to now, various models with diverse approaches have been applied to investigate organizations- strategic position in different industries. Regarding the essential importance and strategic role of quality in higher education institutes, in this study, a quality-oriented approach has been suggested to positioning them in their strategic environment. Then the European Foundation of Quality Management (EFQM) model has been adopted to position the top Iranian business schools in their strategic environment. The result of this study can be used in strategic planning of these institutes as well as the other Iranian business schools.

Keywords: Strategic planning, Strategic positioning, Quality, EFQM model, Higher education institutions.

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852 Semi Empirical Equations for Peak Shear Strength of Rectangular Reinforced Concrete Walls

Authors: Ali Kezmane, Said Boukais, Mohand Hamizi

Abstract:

This paper presents an analytical study on the behavior of reinforced concrete walls with rectangular cross section. Several experiments on such walls have been selected to be studied. Database from various experiments were collected and nominal shear wall strengths have been calculated using formulas, such as those of the ACI (American), NZS (New Zealand), Mexican (NTCC), and Wood and Barda equations. Subsequently, nominal shear wall strengths from the formulas were compared with the ultimate shear wall strengths from the database. These formulas vary substantially in functional form and do not account for all variables that affect the response of walls. There is substantial scatter in the predicted values of ultimate shear strength. Two new semi empirical equations are developed using data from tests of 57 walls for transitions walls and 27 for slender walls with the objective of improving the prediction of peak strength of walls with the most possible accurate.

Keywords: Shear strength, reinforced concrete walls, rectangular walls, shear walls, models.

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851 The Relationship between Motivation for Physical Activity and Level of Physical Activity over Time

Authors: Keyvan Molanorouzi, Selina Khoo, Tony Morris

Abstract:

In recent years, there has been a decline in physical activity among adults. Motivation has been shown to be a crucial factor in maintaining physical activity. The purpose of this study was to whether PA motives measured by the Physical Activity and Leisure Motivation Scale PALMS predicted the actual amount of PA at a later time to provide evidence for the construct validity of the PALMS. A quantitative, cross-sectional descriptive research design was employed. The Demographic Form, PALMS, and International Physical Activity Questionnaire Short form (IPAQ-S) questionnaires were used to assess motives and amount for physical activity in adults on two occasions. A sample of 489 male undergraduate students aged 18 to 25 years (mean ±SD; 22.30±8.13 years) took part in the study. Participants were divided into three types of activities, namely exercise, racquet sport, and team sports and female participants only took part in one type of activity, namely team sports. After 14 weeks, all 489 undergraduate students who had filled in the initial questionnaire (Occasion 1) received the questionnaire via email (Occasion 2). Of the 489 students, 378 males emailed back the completed questionnaire. The results showed that not only were pertinent sub-scales of PALMS positively related to amount of physical activity, but separate regression analyses showed the positive predictive effect of PALMS motives for amount of physical activity for each type of physical activity among participants. This study supported the construct validity of the PALMS by showing that the motives measured by PALMS did predict amount of PA. This information can be obtained to match people with specific sport or activity which in turn could potentially promote longer adherence to the specific activity.

Keywords: Physical activity, motivation, the level of physical activity, types of physical activities.

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850 Localization of Near Field Radio Controlled Unintended Emitting Sources

Authors: Nurbanu Guzey, S. Jagannathan

Abstract:

Locating Radio Controlled (RC) devices using their unintended emissions has a great interest considering security concerns. Weak nature of these emissions requires near field localization approach since it is hard to detect these signals in far field region of array. Instead of only angle estimation, near field localization also requires range estimation of the source which makes this method more complicated than far field models. Challenges of locating such devices in a near field region and real time environment are analyzed in this paper. An ESPRIT like near field localization scheme is utilized for both angle and range estimation. 1-D search with symmetric subarrays is provided. Two 7 element uniform linear antenna arrays (ULA) are employed for locating RC source. Experiment results of location estimation for one unintended emitting walkie-talkie for different positions are given.

Keywords: Localization, angle of arrival (AoA), range estimation, array signal processing, ESPRIT, uniform linear array (ULA).

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849 The Use Support Vector Machine and Back Propagation Neural Network for Prediction of Daily Tidal Levels along the Jeddah Coast, Saudi Arabia

Authors: E. A. Mlybari, M. S. Elbisy, A. H. Alshahri, O. M. Albarakati

Abstract:

Sea level rise threatens to increase the impact of future  storms and hurricanes on coastal communities. Accurate sea level  change prediction and supplement is an important task in determining  constructions and human activities in coastal and oceanic areas. In  this study, support vector machines (SVM) is proposed to predict  daily tidal levels along the Jeddah Coast, Saudi Arabia. The optimal  parameter values of kernel function are determined using a genetic  algorithm. The SVM results are compared with the field data and  with back propagation (BP). Among the models, the SVM is superior  to BPNN and has better generalization performance.

 

Keywords: Tides, Prediction, Support Vector Machines, Genetic Algorithm, Back-Propagation Neural Network, Risk, Hazards.

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848 A Collaborative Platform for Multilingual Ontology Development

Authors: Ahmed Tawfik, Fausto Giunchiglia, Vincenzo Maltese

Abstract:

Ontologies provide a common understanding of a specific domain of interest that can be communicated between people and used as background knowledge for automated reasoning in a wide range of applications. In this paper, we address the design of multilingual ontologies following well-defined knowledge engineering methodologies with the support of novel collaborative development approaches. In particular, we present a collaborative platform which allows ontologies to be developed incrementally in multiple languages. This is made possible via an appropriate mapping between language independent concepts and one lexicalization per language (or a lexical gap in case such lexicalization does not exist). The collaborative platform has been designed to support the development of the Universal Knowledge Core, a multilingual ontology currently in English, Italian, Chinese, Mongolian, Hindi and Bangladeshi. Its design follows a workflow-based development methodology that models resources as a set of collaborative objects and assigns customizable workflows to build and maintain each collaborative object in a community driven manner, with extensive support of modern web 2.0 social and collaborative features.

Keywords: Knowledge Diversity, Knowledge Representation, Ontology Development.

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847 Towards a Complete Automation Feature Recognition System for Sheet Metal Manufacturing

Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

Abstract:

Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: Feature recognition, automation, sheet metal manufacturing, CAM, CAD.

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846 Krylov Model Order Reduction of a Thermal Subsea Model

Authors: J. Šindler, A. Suleng, T. Jelstad Olsen, P. Bárta

Abstract:

A subsea hydrocarbon production system can undergo planned and unplanned shutdowns during the life of the field. The thermal FEA is used to simulate the cool down to verify the insulation design of the subsea equipment, but it is also used to derive an acceptable insulation design for the cold spots. The driving factors of subsea analyses require fast responding and accurate models of the equipment cool down. This paper presents cool down analysis carried out by a Krylov subspace reduction method, and compares this approach to the commonly used FEA solvers. The model considered represents a typical component of a subsea production system, a closed valve on a dead leg. The results from the Krylov reduction method exhibits the least error and requires the shortest computational time to reach the solution. These findings make the Krylov model order reduction method very suitable for the above mentioned subsea applications.

Keywords: Model order reduction, Krylov subspace, subsea production system, finite element.

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845 Lattice Boltzmann Simulation of MHD Natural Convection Heat Transfer of Cu-Water Nanofluid in a Linearly/Sinusoidally Heated Cavity

Authors: Bouchmel Mliki, Chaouki Ali, Mohamed Ammar Abbassi

Abstract:

In this numerical study, natural convection of Cu–water nanofluid in a cavity submitted to different heating modes on its vertical walls is analyzed. Maxwell-Garnetts (MG) and Brinkman models have been utilized for calculating the effective thermal conductivity and dynamic viscosity of nanofluid, respectively. Influences of Rayleigh number (Ra = 103−106), nanoparticle volume concentration (f = 0-0.04) and Hartmann number (Ha = 0-90) on the flow and heat transfer characteristics have been examined. The results indicate that the Hartmann number influences the heat transfer at Ra = 106 more than other Raleigh numbers, as the least effect is observed at Ra = 103. Moreover, the results show that the solid volume fraction has a significant influence on heat transfer, depending on the value of Hartmann, heat generation or absorption coefficient and Rayleigh numbers.

Keywords: Heat transfer, linearly/sinusoidally heated, Lattice Boltzmann Method, natural convection, nanofluid.

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844 Human Motion Capture: New Innovations in the Field of Computer Vision

Authors: Najm Alotaibi

Abstract:

Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture.

Keywords: Human Motion Capture, Computer Vision, Vision based, Tracking.

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843 Assessment of the Response of Seismic Refraction Tomography and Resistivity Imaging to the Same Geologic Environment: A Case Study of Zaria Basement Complex in North Central Nigeria

Authors: Collins C. Chiemeke, I. B. Osazuwa, Ibe S. O., Egwuonwu G. N., Ani C. D., Chii E. C.

Abstract:

The study area is Zaria, located in the basement complex of northern Nigeria. The rock type forming the major part of the Zaria batholith is granite. This research work was carried out to compare the responses of seismic refraction tomography and resistivity tomography in the same geologic environment and under the same conditions. Hence, the choice of the site that has a visible granitic outcrop that extends across a narrow stream channel and is flanked by unconsolidated overburden, a neutral profile that was covered by plain overburden and a site with thick lateritic cover became necessary. The results of the seismic and resistivity tomography models reveals that seismic velocity and resistivity does not always simultaneously increase with depth, but their responses in any geologic environment are determined by changes in the mechanical and chemical content of the rock types rather than depth.

Keywords: Environment, Resistivity, Response, Seismic, Velocity.

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842 Future Logistics - Challenges, Requirements and Solutions for Logistics Networks

Authors: Martin Roth, Axel Klarmann, Bogdan Franczyk

Abstract:

The importance of logistics has changed enormously in the last few decades. While logistics was formerly one of the core functions of most companies, logistics or at least parts of their functions are nowadays outsourced to external logistic service providers in terms of contracts. As a result of this shift new business models like the fourth party logistics provider emerged, which designs, plans and monitors the resulting logistics networks. This new business model and topics such as Synchromodality or Big Data impose new requirements on the underlying IT, which cannot be met with conventional concepts and approaches. In this paper, the challenges of logistics network monitoring are outlined by using a scenario. The most common layers in a logical multilayered architecture for an information system are used to point out the arising challenges for IT. In addition, first appropriate solution approaches are introduced.

 

Keywords: Complex Event Processing, Fourth Party Logistics Service Provider, Logistics monitoring, Synchromodality.

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841 Scaling Strategy of a New Experimental Rig for Wheel-Rail Contact

Authors: Meysam Naeimi, Zili Li, Rolf Dollevoet

Abstract:

A new small–scale test rig developed for rolling contact fatigue (RCF) investigations in wheel–rail material. This paper presents the scaling strategy of the rig based on dimensional analysis and mechanical modelling. The new experimental rig is indeed a spinning frame structure with multiple wheel components over a fixed rail-track ring, capable of simulating continuous wheelrail contact in a laboratory scale. This paper describes the dimensional design of the rig, to derive its overall scaling strategy and to determine the key elements’ specifications. Finite element (FE) modelling is used to simulate the mechanical behavior of the rig with two sample scale factors of 1/5 and 1/7. The results of FE models are compared with the actual railway system to observe the effectiveness of the chosen scales. The mechanical properties of the components and variables of the system are finally determined through the design process.

Keywords: New test rig, rolling contact fatigue, rail, small scale.

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840 Artificial Neural Network Prediction for Coke Strength after Reaction and Data Analysis

Authors: Sulata Maharana, B Biswas, Adity Ganguly, Ashok Kumar

Abstract:

In this paper, the requirement for Coke quality prediction, its role in Blast furnaces, and the model output is explained. By applying method of Artificial Neural Networking (ANN) using back propagation (BP) algorithm, prediction model has been developed to predict CSR. Important blast furnace functions such as permeability, heat exchanging, melting, and reducing capacity are mostly connected to coke quality. Coke quality is further dependent upon coal characterization and coke making process parameters. The ANN model developed is a useful tool for process experts to adjust the control parameters in case of coke quality deviations. The model also makes it possible to predict CSR for new coal blends which are yet to be used in Coke Plant. Input data to the model was structured into 3 modules, for tenure of past 2 years and the incremental models thus developed assists in identifying the group causing the deviation of CSR.

Keywords: Artificial Neural Networks, backpropagation, CokeStrength after Reaction, Multilayer Perceptron.

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839 A Taxonomy Proposal on Criterion Structure for Evaluating Freight Village Concepts in Early-Stage Design Projects

Authors: Rıza Gürhan Korkut, Metin Çelik, Süleyman Özkaynak

Abstract:

The early-stage design and development projects for the freight village initiatives require a comprehensive analysis of both qualitative and quantitative data. Considering the literature review on structural and operational management requirements, this study proposed an original taxonomy on criterion structure to assess freight village conceptualization. The potential challenges and uncertainties of the developed taxonomy are extended. Besides requirement analysis, this study is also expected to contribute to forthcoming research on benchmarking of freight villages in different regions. The methodology used in this research is a systematic review on several articles as per their modelling approaches, sustainability, entities and decisions made together with the uncertainties and features of their models taken into consideration. The major findings of the study that are the categories for assessing the projects attributes on their environmental, socio-economical, accessibility and location aspects.

Keywords: Freight village, logistics centers, operational management, taxonomy.

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838 Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data

Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

Abstract:

The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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837 A Retrospective Cross-Sectional Study on the Prevalence and Factors Associated with Virological Non-Suppression among HIV-Positive Adult Patients on Antiretroviral Therapy in Woliso Town, Oromia, Ethiopia

Authors: Teka Haile, Behailu Hawulte, Solomon Alemayehu

Abstract:

Background: HIV virological failure still remains a problem in HV/AIDS treatment and care. This study aimed to describe the prevalence and identify the factors associated with viral non-suppression among HIV-positive adult patients on antiretroviral therapy in Woliso Town, Oromia, Ethiopia. Methods: A retrospective cross-sectional study was conducted among 424 HIV-positive patient’s attending antiretroviral therapy (ART) in Woliso Town during the period from August 25, 2020 to August 30, 2020. Data collected from patient medical records were entered into Epi Info version 2.3.2.1 and exported to SPSS version 21.0 for analysis. Logistic regression analysis was done to identify factors associated with viral load non-suppression, and statistical significance of odds ratios were declared using 95% confidence interval and p-value < 0.05. Results: A total of 424 patients were included in this study. The mean age (± SD) of the study participants was 39.88 (± 9.995) years. The prevalence of HIV viral load non-suppression was 55 (13.0%) with 95% CI (9.9-16.5). Second-line ART treatment regimen (Adjusted Odds Ratio (AOR) = 8.98, 95% Confidence Interval (CI): 2.64, 30.58) and routine viral load testing (AOR = 0.01, 95% CI: 0.001, 0.02) were significantly associated with virological non-suppression. Conclusion: Virological non-suppression was high, which hinders the achievement of the third global 95 target. The second-line regimen and routine viral load testing were significantly associated with virological non-suppression. It suggests the need to assess the effectiveness of antiretroviral drugs for epidemic control. It also clearly shows the need to decentralize third-line ART treatment for those patients in need.

Keywords: Virological non-suppression, HIV-positive, ART, Woliso Town, Ethiopia.

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836 On-line Control of the Natural and Anthropogenic Safety in Krasnoyarsk Region

Authors: T. Penkova, A. Korobko, V. Nicheporchuk., L. Nozhenkova, A. Metus

Abstract:

This paper presents an approach of on-line control of the state of technosphere and environment objects based on the integration of Data Warehouse, OLAP and Expert systems technologies. It looks at the structure and content of data warehouse that provides consolidation and storage of monitoring data. There is a description of OLAP-models that provide a multidimensional analysis of monitoring data and dynamic analysis of principal parameters of controlled objects. The authors suggest some criteria of emergency risk assessment using expert knowledge about danger levels. It is demonstrated now some of the proposed solutions could be adopted in territorial decision making support systems. Operational control allows authorities to detect threat, prevent natural and anthropogenic emergencies and ensure a comprehensive safety of territory.

Keywords: Decision making support systems, Emergency risk assessment, Natural and anthropogenic safety, On-line control, Territory.

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