Search results for: path loss models

Authors: Jahar Sarkar

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In the present study, a steady-state simulation model has been developed to evaluate the system performance of a transcritical carbon dioxide heat pump system for simultaneous water cooling and heating. Both the evaporator (including both two-phase and superheated zone) and gas cooler models consider the highly variable heat transfer characteristics of CO2 and pressure drop. The numerical simulation model of transcritical CO2 heat pump has been validated by test data obtained from experiments on the heat pump prototype. Comparison between the test results and the model prediction for system COP variation with compressor discharge pressure shows a modest agreement with a maximum deviation of 15% and the trends are fairly similar. Comparison for other operating parameters also shows fairly similar deviation between the test results and the model prediction. Finally, the simulation results are presented to study the effects of operating parameters such as, temperature of heat exchanger fluid at the inlet, discharge pressure, compressor speed on system performance of CO2 heat pump, suitable in a dairy plant where simultaneous cooling at 4oC and heating at 73oC are required. Results show that good heat transfer properties of CO2 for both two-phase and supercritical region and efficient compression process contribute a lot for high system COPs.

Keywords: CO2 heat pump, dairy system, experiment, simulation model, validation.

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: Artificial neural networks, fuel consumption, machine learning, regression, statistical tests.

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Authors: Kurniawan D. Irianto, Demetres D. Kouvatsos

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The growth of wireless devices affects the availability of limited frequencies or spectrum bands as it has been known that spectrum bands are a natural resource that cannot be added. Meanwhile, the licensed frequencies are idle most of the time. Cognitive radio is one of the solutions to solve those problems. Cognitive radio is a promising technology that allows the unlicensed users known as secondary users (SUs) to access licensed bands without making interference to licensed users or primary users (PUs). As cloud computing has become popular in recent years, cognitive radio networks (CRNs) can be integrated with cloud platform. One of the important issues in CRNs is security. It becomes a problem since CRNs use radio frequencies as a medium for transmitting and CRNs share the same issues with wireless communication systems. Another critical issue in CRNs is performance. Security has adverse effect to performance and there are trade-offs between them. The goal of this paper is to investigate the performance related to security trade-off in CRNs with supporting cloud platforms. Furthermore, Queuing Network Models with preemptive resume and preemptive repeat identical priority are applied in this project to measure the impact of security to performance in CRNs with or without cloud platform. The generalized exponential (GE) type distribution is used to reflect the bursty inter-arrival and service times at the servers. The results show that the best performance is obtained when security is disabled and cloud platform is enabled.

Keywords: Cloud Platforms, Cognitive Radio Networks, GEtype Distribution, Performance Vs Security.

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Authors: Naoto Suzuki

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A decline in visual sensitivity at arbitrary points on the retina can be measured using a precise perimetry apparatus along with a fundus camera. However, the retinal layer associated with this decline cannot be identified accurately with current medical technology. To investigate cryptogenic diseases, such as macular dystrophy, acute zonal occult outer retinopathy (AZOOR), and multiple evanescent white dot syndrome (MEWDS), we evaluated an electroretinogram (ERG) function that allows moving the center of the multifocal hexagonal stimulus array to a chosen position. Macular dystrophy is a generalized term used for a variety of functional disorders of the macula lutea, and the ERG shows a diminution of the b-wave in these disorders. AZOOR causes an acute functional disorder to an outer layer of the retina, and the ERG shows a-wave and b-wave amplitude reduction as well as delayed 30 Hz flicker responses. MEWDS causes acute visual loss and the ERG shows a decrease in a-wave amplitude. We combined an electroretinographic optical system and a perimetric optical system into an experimental apparatus that has the same optical system as that of a fundus camera. We also deployed an EO-50231 Edmund infrared camera, a 45-degree cold mirror, a lens with a 25-mm focal length, a halogen lamp, and an 8-inch monitor. Then, we also employed a differential amplifier with gain 10, a 50 Hz notch filter, a high-pass filter with a 21.2 Hz cut-off frequency, and two non-inverting amplifiers with gains 1001 and 11. In addition, we used a USB-6216 National Instruments I/O device, a NE-113A Nihon Kohden plate electrode, a SCB-68A shielded connector block, and LabVIEW 2017 software for data retrieval. The software was used to generate the multifocal hexagonal stimulus array on the computer monitor with C++Builder 10.2 and to move the center of the array toward the left and right and up and down. Cone and bright flash ERG results were observed using the moving ERG function. The a-wave, b-wave, c-wave, and the photopic negative response were identified with cone ERG. The moving ERG function allowed the identification of the retinal layer causing visual alterations.

Keywords: Moving ERG, multifocal ERG, precise perimetry, retinal layers, visual sensitivity

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Authors: Yongsheng Guo, Shuchao Li

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This study explores Chinese Foreign Direct Investment (FDI) in Europe and the cross-cultural cooperation between Chinese and European managers. The aim of this research is to shed light on the phenomenon of investments in developed countries from an emerging market and to gain insights into the cooperation process. A grounded theory approach is adopted, and 46 semi-structured interviews were conducted with 10 case companies in Germany and 13 case companies in the UK. Grounded theory models are developed from primary data and interview quotes are used to support the themes. The interviewees perceived differences between the two parties in cultural traits, management concepts, knowledge structure and resource endowment between the two parties. Chinese and European partners can take advantage of different resources and cooperate in innovative ways to improve corporate performance. Moreover, both parties appreciate different ethical and cultural characteristics and complement each other to develop a combined organizational culture. This study proposes an ethical and cultural diversity theory in international management arguing that a team with diversified values and behaviours may be more excited and motivated. This study suggests that “resource complement” and “cross-cultural cooperation” might be an advantage for international investment. Firms are encouraged to open their minds and cooperate with partners with different resources and cultures. The authorities may review the FDI policies to reduce social and political barriers.

Keywords: Cross-culture, FDI, China, Europe.

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Authors: Tomasz Dubiel, Tadeusz Balawender, Mirosław Osetek

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The paper presents the influence of non-metallic inclusions on the multi-stage forging process and the mechanical properties of the dodecagon socket bolt used in the automotive industry. The detected metallurgical defect was so large that it directly influenced the mechanical properties of the bolt and resulted in failure to meet the requirements of the mechanical property class. In order to assess the defect, an X-ray examination and metallographic examination of the defective bolt were performed, showing exogenous non-metallic inclusion. The size of the defect on the cross section was 0.531 mm in width and 1.523 mm in length; the defect was continuous along the entire axis of the bolt. In analysis, a finite element method (FEM) simulation of the multi-stage forging process was designed, taking into account a non-metallic inclusion parallel to the sample axis, reflecting the studied case. The process of defect propagation due to material upset in the head area was analyzed. The final forging stage in shaping the dodecagonal socket and filling the flange area was particularly studied. The effect of the defect was observed to significantly reduce the effective cross-section as a result of the expansion of the defect perpendicular to the axis of the bolt. The mechanical properties of products with and without the defect were analyzed. In the first step, the hardness test confirmed that the required value for the mechanical class 8.8 of both bolt types was obtained. In the second step, the bolts were subjected to a static tensile test. The bolts without the defect gave a positive result, while all 10 bolts with the defect gave a negative result, achieving a tensile strength below the requirements. Tensile strength tests were confirmed by metallographic tests and FEM simulation with perpendicular inclusion spread in the area of the head. The bolts were damaged directly under the bolt head, which is inconsistent with the requirements of ISO 898-1. It has been shown that non-metallic inclusions with orientation in accordance with the axis of the bolt can directly cause loss of functionality and these defects should be detected even before assembling in the machine element.

Keywords: continuous casting, multi-stage forging, non-metallic inclusion, upset bolt head

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Authors: Y. Duvarci, S. Mizokami

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Today, the preferences and participation of the TD groups such as the elderly and disabled is still lacking in decision-making of transportation planning, and their reactions to certain type of policies are not well known. Thus, a clear methodology is needed. This study aimed to develop a method to extract the preferences of the disabled to be used in the policy-making stage that can also guide to future estimations. The method utilizes the combination of cluster analysis and data filtering using the data of the Arao city (Japan). The method is a process that follows: defining the TD group by the cluster analysis tool, their travel preferences in tabular form from the household surveys by policy variableimpact pairs, zones, and by trip purposes, and the final outcome is the preference probabilities of the disabled. The preferences vary by trip purpose; for the work trips, accessibility and transit system quality policies with the accompanying impacts of modal shifts towards public mode use as well as the decreasing travel costs, and the trip rate increase; for the social trips, the same accessibility and transit system policies leading to the same mode shift impact, together with the travel quality policy area leading to trip rate increase. These results explain the policies to focus and can be used in scenario generation in models, or any other planning purpose as decision support tool.

Keywords: Transportation Disadvantaged, Disabled, Mixed Preference, Stated Preference Data.

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Authors: Murat Ayyıldız, Oya Kalıpsız, Sırma Yavuz

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Software project effort estimation is frequently seen as complex and expensive for individual software engineers. Software production is in a crisis. It suffers from excessive costs. Software production is often out of control. It has been suggested that software production is out of control because we do not measure. You cannot control what you cannot measure. During last decade, a number of researches on cost estimation have been conducted. The metric-set selection has a vital role in software cost estimation studies; its importance has been ignored especially in neural network based studies. In this study we have explored the reasons of those disappointing results and implemented different neural network models using augmented new metrics. The results obtained are compared with previous studies using traditional metrics. To be able to make comparisons, two types of data have been used. The first part of the data is taken from the Constructive Cost Model (COCOMO'81) which is commonly used in previous studies and the second part is collected according to new metrics in a leading international company in Turkey. The accuracy of the selected metrics and the data samples are verified using statistical techniques. The model presented here is based on Multi-Layer Perceptron (MLP). Another difficulty associated with the cost estimation studies is the fact that the data collection requires time and care. To make a more thorough use of the samples collected, k-fold, cross validation method is also implemented. It is concluded that, as long as an accurate and quantifiable set of metrics are defined and measured correctly, neural networks can be applied in software cost estimation studies with success

Keywords: Software Metrics, Software Cost Estimation, Neural Network.

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Authors: Ali Jahanfar, Brajesh Dubey, Bahram Gharabaghi, Saber Bayat Movahed

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Ever increasing population growth of major urban centers and environmental challenges in siting new landfills have resulted in a growing trend in design of mega-landfills some with extraordinary heights and dangerously steep slopes. Landfill failure mobility risk analysis is one of the most uncertain types of dynamic rheology models due to very large inherent variabilities in the heterogeneous solid waste material shear strength properties. The waste flow of three historic dumpsite and two landfill failures were back-analyzed using run-out modeling with DAN-W model. The travel distances of the waste flow during landfill failures were calculated approach by taking into account variability in material shear strength properties. The probability distribution function for shear strength properties of the waste material were grouped into four major classed based on waste material compaction (landfills versus dumpsites) and composition (high versus low quantity) of high shear strength waste materials such as wood, metal, plastic, paper and cardboard in the waste. This paper presents a probabilistic method for estimation of the spatial extent of waste avalanches, after a potential landfill failure, to create maps of vulnerability scores to inform property owners and residents of the level of the risk.

Keywords: Landfill failure, waste flow, Voellmy rheology, friction coefficient, waste compaction and type.

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Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

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The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: Autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS.

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Authors: Karam Y. Maalawi, Hanan E.M EL-Sayed

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This paper presents an exact analytical model for optimizing stability of thin-walled, composite, functionally graded pipes conveying fluid. The critical flow velocity at which divergence occurs is maximized for a specified total structural mass in order to ensure the economic feasibility of the attained optimum designs. The composition of the material of construction is optimized by defining the spatial distribution of volume fractions of the material constituents using piecewise variations along the pipe length. The major aim is to tailor the material distribution in the axial direction so as to avoid the occurrence of divergence instability without the penalty of increasing structural mass. Three types of boundary conditions have been examined; namely, Hinged-Hinged, Clamped- Hinged and Clamped-Clamped pipelines. The resulting optimization problem has been formulated as a nonlinear mathematical programming problem solved by invoking the MatLab optimization toolbox routines, which implement constrained function minimization routine named “fmincon" interacting with the associated eigenvalue problem routines. In fact, the proposed mathematical models have succeeded in maximizing the critical flow velocity without mass penalty and producing efficient and economic designs having enhanced stability characteristics as compared with the baseline designs.

Keywords: Functionally graded materials, pipe flow, optimumdesign, fluid- structure interaction

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Authors: Angelina A. Tzacheva, Jaishree Ranganathan

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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: Actionable pattern discovery, education, emotion, data mining.

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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Authors: Sabri Mrayed, David Maccioni, Greg Leslie

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Seawater desalination has been accepted as one of the most effective solutions to the growing problem of a diminishing clean drinking water supply. Currently two desalination technologies dominate the market – the thermally driven multi-stage flash distillation (MSF) and the membrane based reverse osmosis (RO). However, in recent years membrane distillation (MD) has emerged as a potential alternative to the established means of desalination. This research project intended to determine the viability of MD as an alternative process to MSF and RO for seawater desalination. Specifically the project involves conducting thermodynamic analysis of the process based on the second law of thermodynamics to determine the efficiency of the MD. Data was obtained from experiments carried out on a laboratory rig. To determine exergy values required for the exergy analysis, two separate models were built in Engineering Equation Solver – the ’Minimum Separation Work Model’ and the ‘Stream Exergy Model’. The efficiency of MD process was found to be 17.3 % and the energy consumption was determined to be 4.5 kWh to produce one cubic meter of fresh water. The results indicate MD has potential as a technique for seawater desalination compared to RO and MSF. However it was shown that this was only the case if an alternate energy source such as green or waste energy was available to provide the thermal energy input to the process. If the process was required to power itself, it was shown to be highly inefficient and in no way thermodynamically viable as a commercial desalination process.

Keywords: Desalination, Exergy, Membrane distillation, Second law efficiency.

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Authors: Herti Utami, Sutijan, Roto, Wahyudi Budi Sediawan

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α-Pinene is the main component of the most turpentine oils. The hydration of α-pinene with acid catalysts leads to a complex mixture of monoterpenes. In order to obtain more valuable products, the α-pinene in the turpentine can be hydrated in dilute mineral acid solutions to produce α-terpineol. The design of separation processes requires information on phase equilibrium and related thermodynamic properties. This paper reports the results of study on liquid-liquid equilibrium (LLE) of system containing α- pinene + water and α-terpineol + water. Binary LLE for α-pinene + water system, and α-terpineol + water systems were determined by experiment at 301K and atmospheric pressure. The two component mixture was stirred for about 30min, then the mixture was left for about 2h for complete phase separation. The composition of both phases was analyzed by using a Gas Chromatograph. The experimental data were correlated by considering both NRTL and UNIQUAC activity coefficient models. The LLE data for the system of α-pinene + water and α-terpineol + water were correlated successfully by the NRTL model. The experimental data were not satisfactorily fitted by the UNIQUAC model. The NRTL model (α =0.3) correlates the LLE data for the system of α-pinene + water at 301K with RMSD of 0.0404%. And the NRTL model (α =0.61) at 301K with RMSD of 0.0058 %. The NRTL model (α =0.3) correlates the LLE data for the system of α- terpineol + water at 301K with RMSD of 0.1487% and the NRTL model (α =0.6) at 301K with RMSD of 0.0032%, between the experimental and calculated mole fractions.

Keywords: α-Pinene, α-Terpineol, Liquid-liquid Equilibrium, NRTL model, UNIQUAC model

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Authors: Marco Raciti Castelli, Alberto Castelli, Ernesto Benini

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The construction of a civil structure inside a urban area inevitably modifies the outdoor microclimate at the building site. Wind speed, wind direction, air pollution, driving rain, radiation and daylight are some of the main physical aspects that are subjected to the major changes. The quantitative amount of these modifications depends on the shape, size and orientation of the building and on its interaction with the surrounding environment.The flow field over a flat roof model building has been numerically investigated in order to determine two-dimensional CFD guidelines for the calculation of the turbulent flow over a structure immersed in an atmospheric boundary layer. To this purpose, a complete validation campaign has been performed through a systematic comparison of numerical simulations with wind tunnel experimental data.Several turbulence models and spatial node distributions have been tested for five different vertical positions, respectively from the upstream leading edge to the downstream bottom edge of the analyzed model. Flow field characteristics in the neighborhood of the building model have been numerically investigated, allowing a quantification of the capabilities of the CFD code to predict the flow separation and the extension of the recirculation regions.The proposed calculations have allowed the development of a preliminary procedure to be used as a guidance in selecting the appropriate grid configuration and corresponding turbulence model for the prediction of the flow field over a twodimensional roof architecture dominated by flow separation.

Keywords: CFD, roof, building, wind.

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Authors: Mohammad Rohani, Gholamali Shafabakhsh, Abdolhosein Haddad, Ehsan Asnaashari

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Visual simulation has emerged as a key planning tool in built environment because it enables architects, engineers and project managers to visualize construction process evolution before the project actual commences. This provides an efficient technology for reducing time and cost through planning and controlling resources, machines and materials. With the development of infrastructure projects and the massive civil constructions such as bridges, urban tunnels and highways as well as sensitivity of their construction operations, it is very necessary to apply proper planning methods. Implementation of visual techniques into management of construction projects can provide a fundamental foundation for projects with massive activities and duplicate items. So, the purpose of this paper is to develop visual simulation management techniques for infrastructure projects such as highways bridges by the use of Four-Dimensional Computer-Aided design Models. This project simulates operational assembly-line for Box-Girder Concrete Bridges which it would be able to optimize the sequence and interaction of project activities and on the other hand, it would minimize any unintended conflicts prior to project start. In this paper, after introducing the various planning methods by building information model and concrete bridges in highways, an executive case study is demonstrated and then a visual technique (4D CAD) will be applied for the case. In the final step, the user feedback for interacting by this system evaluated according to six criteria.

Keywords: 4D application area, Box-Girder concrete bridges, CAD model, visual planning.

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Authors: Hadi Gholizadeh, Ali Tajdin

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To have effective production planning, it is necessary to control the quality of processes. This paper aims at improving the performance of the disposable essentials process using statistical quality control and goal programming in a vague environment. That is expressed uncertainty because there is always a measurement error in the real world. Therefore, in this study, the conditions are examined in a vague environment that is a distance-based environment. The disposable essentials process in Kach Company was studied. Statistical control tools were used to characterize the existing process for four factor responses including the average of disposable glasses’ weights, heights, crater diameters, and volumes. Goal programming was then utilized to find the combination of optimal factors setting in a vague environment which is measured to apply uncertainty of the initial information when some of the parameters of the models are vague; also, the fuzzy regression model is used to predict the responses of the four described factors. Optimization results show that the process capability index values for disposable glasses’ average of weights, heights, crater diameters and volumes were improved. Such increasing the quality of the products and reducing the waste, which will reduce the cost of the finished product, and ultimately will bring customer satisfaction, and this satisfaction, will mean increased sales.

Keywords: Goal programming, quality control, vague environment, disposable glasses’ optimization, fuzzy regression.

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Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva

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Every year, fog formation over the Indo-Gangetic Plains (IGPs) of Indian region during the winter months of December and January is believed to create numerous hazards, inconvenience, and economic loss to the inhabitants of this densely populated region of Indian subcontinent. The aim of the paper is to analyze the spatial and temporal variability of winter fog over IGPs. Long term ground observations of visibility and other meteorological parameters (1971-2010) have been analyzed to understand the formation of fog phenomena and its relevance during the peak winter months of January and December over IGP of India. In order to examine the temporal variability, time series and trend analysis were carried out by using the Mann-Kendall Statistical test. Trend analysis performed by using the Mann-Kendall test, accepts the alternate hypothesis with 95% confidence level indicating that there exists a trend. Kendall tau’s statistics showed that there exists a positive correlation between time series and fog frequency. Further, the Theil and Sen’s median slope estimate showed that the magnitude of trend is positive. Magnitude is higher during January compared to December for the entire IGP except in December when it is high over the western IGP. Decade wise time series analysis revealed that there has been continuous increase in fog days. The net overall increase of 99 % was observed over IGP in last four decades. Diurnal variability and average daily persistence were computed by using descriptive statistical techniques. Geo-statistical analysis of fog was carried out to understand the spatial variability of fog. Geo-statistical analysis of fog revealed that IGP is a high fog prone zone with fog occurrence frequency of more than 66% days during the study period. Diurnal variability indicates the peak occurrence of fog is between 06:00 and 10:00 local time and average daily fog persistence extends to 5 to 7 hours during the peak winter season. The results would offer a new perspective to take proactive measures in reducing the irreparable damage that could be caused due to changing trends of fog.

Keywords: Fog, climatology, Mann-Kendall test, trend analysis, spatial variability, temporal variability, visibility.

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Authors: Munazza A. Mirza, Khawar Khurshid

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Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.

Keywords: Learning style, VARK, sensory preferences, identification model, didactic practices.

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Authors: Nazira Kakulia

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The analysis of transformation of institutional changes outlines two important characteristics. These are: the speed of the changes and their sequence. Successful transformation must be carried out in three different stages; On the first stage, macroeconomic stabilization must be achieved with the help of fiscal and monetary tools. Two-tier banking system should be established and the active functions of central bank should be replaced by the passive ones (reserve requirements and refinancing rate), together with the involvement growth of private sector. Fiscal policy by itself here means the creation of tax system which must replace previously existing direct state revenues; the share of subsidies in the state expenses must be reduced also. The second stage begins after reaching the macroeconomic stabilization at a time of change of formal institutes which must stimulate the private business. Corporate legislation creates a competitive environment at the market and the privatization of state companies takes place. Bankruptcy and contract law is created. he third stage is the most extended one, which means the formation of all state structures that is necessary for the further proper functioning of a market economy. These three stages about the cycle period of political and social transformation and the hierarchy of changes can also be grouped by the different methodology: on the first and the most short-term stage the transfer of power takes place. On the second stage institutions corresponding to new goal are created. The last phase of transformation is extended in time and it includes the infrastructural, socio-cultural and socio-structural changes. The main goal of this research is to explore and identify the features of such kind of models.

Keywords: Competitive, environment, fiscal policy, macro-economic stabilization.

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Authors: Mayuresh Thombre, Prajyot Borkar, Mangirish Bhobe

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New advancement of technology and never satisfying demands of the civilization are putting huge pressure on the natural fuel resources and these resources are at a constant threat to its sustainability. To get the best out of the automobile, the optimum balance between performance and fuel economy is important. In the present state of art, either of the above two aspects are taken into mind while designing and development process which puts the other in the loss as increase in fuel economy leads to decrement in performance and vice-versa. In-depth observation of the vehicle dynamics apparently shows that large amount of energy is lost during braking and likewise large amount of fuel is consumed to reclaim the initial state, this leads to lower fuel efficiency to gain the same performance. Current use of Kinetic Energy Recovery System is only limited to sports vehicles only because of the higher cost of this system. They are also temporary in nature as power can be squeezed only during a small time duration and use of superior parts leads to high cost, which results on concentration on performance only and neglecting the fuel economy. In this paper Kinetic Energy Recovery System for storing the power and then using the same while accelerating has been discussed. The major storing element in this system is a Flat Spiral Spring that will store energy by compression and torsion.

The use of spring ensure the permanent storage of energy until used by the driver unlike present mechanical regeneration system in which the energy stored decreases with time and is eventually lost. A combination of internal gears and spur gears will be used in order to make the energy release uniform which will lead to safe usage. The system can be used to improve the fuel efficiency by assisting in overcoming the vehicle’s inertia after braking or to provide instant acceleration whenever required by the driver. The performance characteristics of the system including response time, mechanical efficiency and overall increase in efficiency are demonstrated. This technology makes the KERS (Kinetic Energy Recovery System) more flexible and economical allowing specific application while at the same time increasing the time frame and ease of usage.

Keywords: Electric control unit, Energy, Mechanical KERS, Planetary Gear system, Power, Smart braking, Spiral Spring.

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Authors: Pankaj Chandna, Surinder Deswal, Arunesh Chandra, SK Sharma

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Noise has adverse effect on human health and comfort. Noise not only cause hearing impairment, but it also acts as a causal factor for stress and raising systolic pressure. Additionally it can be a causal factor in work accidents, both by marking hazards and warning signals and by impeding concentration. Industry workers also suffer psychological and physical stress as well as hearing loss due to industrial noise. This paper proposes an approach to enable engineers to point out quantitatively the noisiest source for modification, while multiple machines are operating simultaneously. The model with the point source and spherical radiation in a free field was adopted to formulate the problem. The procedure works very well in ideal cases (point source and free field). However, most of the industrial noise problems are complicated by the fact that the noise is confined in a room. Reflections from the walls, floor, ceiling, and equipment in a room create a reverberant sound field that alters the sound wave characteristics from those for the free field. So the model was validated for relatively low absorption room at NIT Kurukshetra Central Workshop. The results of validation pointed out that the estimated sound power of noise sources under simultaneous conditions were on lower side, within the error limits 3.56 - 6.35 %. Thus suggesting the use of this methodology for practical implementation in industry. To demonstrate the application of the above analytical procedure for estimating the sound power of noise sources under simultaneous operating conditions, a manufacturing facility (Railway Workshop at Yamunanagar, India) having five sound sources (machines) on its workshop floor is considered in this study. The findings of the case study had identified the two most effective candidates (noise sources) for noise control in the Railway Workshop Yamunanagar, India. The study suggests that the modification in the design and/or replacement of these two identified noisiest sources (machine) would be necessary so as to achieve an effective reduction in noise levels. Further, the estimated data allows engineers to better understand the noise situations of the workplace and to revise the map when changes occur in noise level due to a workplace re-layout.

Keywords: Industrial noise, sound power level, multiple noise sources, sources contribution.

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Authors: Imali T. Jayamanne, K. P. Asoka Ramanayake

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Transition from tertiary level education to employment is one of the challenges that many fresh university graduates face after graduation. The transition period or the waiting time to obtain the first employment varies with the socio-economic factors and the general characteristics of a graduate. Compared to other fields of study, Arts graduates in Sri Lanka, have to wait a long time to find their first employment. The objective of this study is to identify the determinants of the transition from higher education to employment of these graduates using survival models. The study is based on a survey that was conducted in the year 2016 on a stratified random sample of Arts graduates from Sri Lankan universities who had graduated in 2012. Among the 469 responses, 36 (8%) waiting times were interval censored and 13 (3%) were right censored. Waiting time for the first employment varied between zero to 51 months. Initially, the log-rank and the Gehan-Wilcoxon tests were performed to identify the significant factors. Gender, ethnicity, GCE Advanced level English grade, civil status, university, class received, degree type, sector of first employment, type of first employment and the educational qualifications required for the first employment were significant at 10%. The Cox proportional hazards model was fitted to model the waiting time for first employment with these significant factors. All factors, except ethnicity and type of employment were significant at 5%. However, since the proportional hazard assumption was violated, the lognormal Accelerated failure time (AFT) model was fitted to model the waiting time for the first employment. The same factors were significant in the AFT model as in Cox proportional model.

Keywords: AFT model, first employment, proportional hazard, survey design, waiting time.

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Authors: Indiramma M., K. R. Anandakumar

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Trust management and Reputation models are becoming integral part of Internet based applications such as CSCW, E-commerce and Grid Computing. Also the trust dimension is a significant social structure and key to social relations within a collaborative community. Collaborative Decision Making (CDM) is a difficult task in the context of distributed environment (information across different geographical locations) and multidisciplinary decisions are involved such as Virtual Organization (VO). To aid team decision making in VO, Decision Support System and social network analysis approaches are integrated. In such situations social learning helps an organization in terms of relationship, team formation, partner selection etc. In this paper we focus on trust learning. Trust learning is an important activity in terms of information exchange, negotiation, collaboration and trust assessment for cooperation among virtual team members. In this paper we have proposed a reinforcement learning which enhances the trust decision making capability of interacting agents during collaboration in problem solving activity. Trust computational model with learning that we present is adapted for best alternate selection of new project in the organization. We verify our model in a multi-agent simulation where the agents in the community learn to identify trustworthy members, inconsistent behavior and conflicting behavior of agents.

Keywords: Collaborative Decision making, Trust, Multi Agent System (MAS), Bayesian Network, Reinforcement Learning.

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Authors: Edison Muzenda, Corina M Mateescu

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Group contribution methods such as the UNIFAC are very useful to researchers and engineers involved in synthesis, feasibility studies, design and optimization of separation processes. They can be applied successfully to predict phase equilibrium and excess properties in the development of chemical and separation processes. The main focus of this work was to investigate the possibility of absorbing selected volatile organic compounds (VOCs) into polydimethylsiloxane (PDMS) using three selected UNIFAC group contribution methods. Absorption followed by subsequent stripping is the predominant available abatement technology of VOCs from flue gases prior to their release into the atmosphere. The original, modified and effective UNIFAC models were used in this work. The thirteen selected VOCs that have been considered in this research are: pentane, hexane, heptanes, trimethylamine, toluene, xylene, cyclohexane, butyl acetate, diethyl acetate, chloroform, acetone, ethyl methyl ketone and isobutyl methyl ketone. The computation was done for solute VOC concentration of 8.55x10-8 which is well in the infinite dilution region. The results obtained in this study compare very well with those published in literature obtained through both measurements and predictions. The phase equilibrium obtained in this study show that PDMS is a good absorbent for the removal of VOCs from contaminated air streams through physical absorption.

Keywords: Absorption, Computation, Feasibility studies, Infinite dilution, Volatile organic compounds

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Authors: K. Ö. Kartal, L. Maul, M. Hägele

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With the development of new technologies come additional opportunities for the founding of companies and new markets to be created. The barriers to entry are lowered and technology makes old business models obsolete. Incumbent companies have to be adaptable to this quickly changing environment. They have to start the process of digital maturation and they have to be able to adapt quickly to new and drastic changes that might arise. One of the biggest barriers for organizations in order to do so is their culture. This paper shows the core elements of a corporate culture that supports the process of digital maturation in incumbent organizations. Furthermore, it is explored how ideation and innovation can be used in a strategy in order to facilitate these core elements of culture that promote digital maturity. Focus areas are identified for the design of ideation strategies, with the aim to make the facilitation and incitation process more effective, short to long term. Therefore, one in-depth case study is conducted with data collection from interviews, observation, document review and surveys. The findings indicate that digital maturity is connected to cultural shift and 11 relevant elements of digital culture are identified which have to be considered. Based on these 11 core elements, five focus areas that need to be regarded in the design of a strategy that uses ideation and innovation to facilitate the cultural shift are identified. These are: Focus topics, rewards and communication, structure and frequency, regions and new online formats.

Keywords: Digital transformation, innovation management, ideation strategy, creativity culture, change.

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Authors: Arash Esmaeili, Zhibang Liu, Yang Xiang, Jimmy Yun, Lei Shao

Abstract:

High pressure carbon dioxide (CO2) absorption from a specific off-gas in a conventional column has been evaluated for the environmental concerns by the Aspen HYSYS simulator using a wide range of single absorbents and piperazine (PZ) blended solutions to estimate the outlet CO2 concentration, CO2 loading, reboiler power supply and regeneration heat duty to choose the most efficient solution in terms of CO2 removal and required heat duty. The property package, which is compatible with all applied solutions for the simulation in this study, estimates the properties based on electrolyte non-random two-liquid (E-NRTL) model for electrolyte thermodynamics and Peng-Robinson equation of state for vapor phase and liquid hydrocarbon phase properties. The results of the simulation indicate that PZ in addition to the mixture of PZ and monoethanolamine (MEA) demand the highest regeneration heat duty compared with other studied single and blended amine solutions respectively. The blended amine solutions with the lowest PZ concentrations (5wt% and 10wt%) were considered and compared to reduce the cost of process, among which the blended solution of 10wt%PZ+35wt%MDEA (methyldiethanolamine) was found as the most appropriate solution in terms of CO2 content in the outlet gas, rich-CO2 loading and regeneration heat duty.

Keywords: Absorption, amine solutions, Aspen HYSYS, CO2 loading, piperazine, regeneration heat duty.

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behaviour of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: Factors, fuzzy cognitive map, group decision, integrated waste management system.

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Authors: Somchai Supattarakul, Anya Khanthavit

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This study aims at providing empirical evidence on a comparison of two equity valuation models: (1) the dividend discount model (DDM) and (2) the residual income model (RIM), in estimating equity values of Thai firms during 1995-2004. Results suggest that DDM and RIM underestimate equity values of Thai firms and that RIM outperforms DDM in predicting cross-sectional stock prices. Results on regression of cross-sectional stock prices on the decomposed DDM and RIM equity values indicate that book value of equity provides the greatest incremental explanatory power, relative to other components in DDM and RIM terminal values, suggesting that book value distortions resulting from accounting procedures and choices are less severe than forecast and measurement errors in discount rates and growth rates. We also document that the incremental explanatory power of book value of equity during 1998-2004, representing the information environment under Thai Accounting Standards reformed after the 1997 economic crisis to conform to International Accounting Standards, is significantly greater than that during 1995-1996, representing the information environment under the pre-reformed Thai Accounting Standards. This implies that the book value distortions are less severe under the 1997 Reformed Thai Accounting Standards than the pre-reformed Thai Accounting Standards.

Keywords: Dividend Discount Model, Equity Valuation Model, Residual Income Model, Thai Stock Market

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