Search results for: Power Systems.

Authors: Ronald F. Gonzales, Gordon W. Romney, Pradip Peter Dey, Mohammad Amin, Bhaskar Raj Sinha

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A virtualized and virtual approach is presented on academically preparing students to successfully engage at a strategic perspective to understand those concerns and measures that are both structured and not structured in the area of cyber security and information assurance. The Master of Science in Cyber Security and Information Assurance (MSCSIA) is a professional degree for those who endeavor through technical and managerial measures to ensure the security, confidentiality, integrity, authenticity, control, availability and utility of the world-s computing and information systems infrastructure. The National University Cyber Security and Information Assurance program is offered as a Master-s degree. The emphasis of the MSCSIA program uniquely includes hands-on academic instruction using virtual computers. This past year, 2011, the NU facility has become fully operational using system architecture to provide a Virtual Education Laboratory (VEL) accessible to both onsite and online students. The first student cohort completed their MSCSIA training this past March 2, 2012 after fulfilling 12 courses, for a total of 54 units of college credits. The rapid pace scheduling of one course per month is immensely challenging, perpetually changing, and virtually multifaceted. This paper analyses these descriptive terms in consideration of those globalization penetration breaches as present in today-s world of cyber security. In addition, we present current NU practices to mitigate risks.

Keywords: Cyber security, information assurance, mitigate risks, virtual machines, strategic perspective.

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Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

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Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: Airborne laser scanning, digital terrain models, filtering, forested areas.

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige

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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.

Keywords: Discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability.

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Authors: Jehad Al Dallal, Paul Sorenson

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An application framework provides a reusable design and implementation for a family of software systems. Frameworks are introduced to reduce the cost of a product line (i.e., family of products that share the common features). Software testing is a time consuming and costly ongoing activity during the application software development process. Generating reusable test cases for the framework applications at the framework development stage, and providing and using the test cases to test part of the framework application whenever the framework is used reduces the application development time and cost considerably. Framework Interface Classes (FICs) are classes introduced by the framework hooks to be implemented at the application development stage. They can have reusable test cases generated at the framework development stage and provided with the framework to test the implementations of the FICs at the application development stage. In this paper, we conduct a case study using thirteen applications developed using three frameworks; one domain oriented and two application oriented. The results show that, in general, the percentage of the number of FICs in the applications developed using domain frameworks is, on average, greater than the percentage of the number of FICs in the applications developed using application frameworks. Consequently, the reduction of the application unit testing time using the reusable test cases generated for domain frameworks is, in general, greater than the reduction of the application unit testing time using the reusable test cases generated for application frameworks.

Keywords: FICs, object-oriented framework, object-orientedframework application, software testing.

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Authors: Moustafa Osman Mohammed

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This paper will explore formation of HCl aerosol at atmospheric boundary layers and encourages the uptake of environmental modeling systems (EMSs) as a practice evaluation of gaseous emissions (“framework measures”) from small and medium-sized enterprises (SMEs). The conceptual model predicts greenhouse gas emissions to ecological points beyond landfill site operations. It focuses on incorporation traditional knowledge into baseline information for both measurement data and the mathematical results, regarding parameters influence model variable inputs. The paper has simplified parameters of aerosol processes based on the more complex aerosol process computations. The simple model can be implemented to both Gaussian and Eulerian rural dispersion models. Aerosol processes considered in this study were (i) the coagulation of particles, (ii) the condensation and evaporation of organic vapors, and (iii) dry deposition. The chemical transformation of gas-phase compounds is taken into account photochemical formulation with exposure effects according to HCl concentrations as starting point of risk assessment. The discussion set out distinctly aspect of sustainability in reflection inputs, outputs, and modes of impact on the environment. Thereby, models incorporate abiotic and biotic species to broaden the scope of integration for both quantification impact and assessment risks. The later environmental obligations suggest either a recommendation or a decision of what is a legislative should be achieved for mitigation measures of landfill gas (LFG) ultimately.

Keywords: Air dispersion model, landfill management, spatial analysis, environmental impact and risk assessment.

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Authors: M. Mohebbi, K. Shakeri

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In the real application of active control systems to mitigate the response of structures subjected to sever external excitations such as earthquake and wind induced vibrations, since the capacity of actuators is limited then the actuators saturate. Hence, in designing controllers for linear and nonlinear structures under sever earthquakes, the actuator saturation should be considered as a constraint. In this paper optimal design of active controllers for nonlinear structures by considering the actuator saturation has been studied. To this end a method has been proposed based on defining an optimization problem which considers the minimizing of the maximum displacement of the structure as objective when a limited capacity for actuator has been used as a constraint in optimization problem. To evaluate the effectiveness of the proposed method, a single degree of freedom (SDF) structure with a bilinear hysteretic behavior has been simulated under a white noise ground acceleration of different amplitudes. Active tendon control mechanism, comprised of pre-stressed tendons and an actuator, and extended nonlinear Newmark method based instantaneous optimal control algorithm have been used as active control mechanism and algorithm. To enhance the efficiency of the controllers, the weights corresponding to displacement, velocity, acceleration and control force in the performance index have been found by using the Distributed Genetic Algorithm (DGA). According to the results it has been concluded that the proposed method has been effective in considering the actuator saturation in designing optimal controllers for nonlinear frames. Also it has been shown that the actuator capacity and the average value of required control force are two important factors in designing nonlinear controllers for considering the actuator saturation.

Keywords: Active control, Actuator Saturation, Nonlinear, Optimization.

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Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

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Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: Energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning.

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Authors: Dalyah Y. Al-Jamal, Maryam H. Eshtaiwi, Liyakathunisa Syed

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Connecting health services with technology has a huge demand as people health situations are becoming worse day by day. In fact, engaging new technologies such as Internet of Things (IOT) into the medical services can enhance the patient care services. Specifically, patients suffering from chronic diseases such as cardiac patients need a special care and monitoring. In reality, some efforts were previously taken to automate and improve the patient monitoring systems. However, the previous efforts have some limitations and lack the real-time feature needed for chronic kind of diseases. In this paper, an improved process model for patient monitoring system specialized for cardiac patients is presented. A survey was distributed and interviews were conducted to gather the needed requirements to improve the cardiac patient monitoring system. Business Process Model and Notation (BPMN) language was used to model the proposed process. In fact, the proposed system uses the IOT Technology to assist doctors to remotely monitor and follow-up with their heart patients in real-time. In order to validate the effectiveness of the proposed solution, simulation analysis was performed using Bizagi Modeler tool. Analysis results show performance improvements in the heart monitoring process. For the future, authors suggest enhancing the proposed system to cover all the chronic diseases.

Keywords: Business process model and notation, cardiac patient, cardiac monitoring, heart monitoring, healthcare, internet of things, remote patient monitoring system, process model, telemedicine, wearable sensors.

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Authors: Sumathi Poobal, G. Ravindran

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Medical imaging uses the advantage of digital technology in imaging and teleradiology. In teleradiology systems large amount of data is acquired, stored and transmitted. A major technology that may help to solve the problems associated with the massive data storage and data transfer capacity is data compression and decompression. There are many methods of image compression available. They are classified as lossless and lossy compression methods. In lossy compression method the decompressed image contains some distortion. Fractal image compression (FIC) is a lossy compression method. In fractal image compression an image is coded as a set of contractive transformations in a complete metric space. The set of contractive transformations is guaranteed to produce an approximation to the original image. In this paper FIC is achieved by PIFS using quadtree partitioning. PIFS is applied on different images like , Ultrasound, CT Scan, Angiogram, X-ray, Mammograms. In each modality approximately twenty images are considered and the average values of compression ratio and PSNR values are arrived. In this method of fractal encoding, the parameter, tolerance factor Tmax, is varied from 1 to 10, keeping the other standard parameters constant. For all modalities of images the compression ratio and Peak Signal to Noise Ratio (PSNR) are computed and studied. The quality of the decompressed image is arrived by PSNR values. From the results it is observed that the compression ratio increases with the tolerance factor and mammogram has the highest compression ratio. The quality of the image is not degraded upto an optimum value of tolerance factor, Tmax, equal to 8, because of the properties of fractal compression.

Keywords: Fractal image compression, IFS, PIFS, PSNR, Quadtree partitioning.

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Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh

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One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.

Keywords: Software certification model, user centric approach, software quality factors, metrics and measurements, web-based system.

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Authors: Roy Y. C. Huang, J. S. Kuang, Hamdolah Behnam

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Beam-column connections play an important role in the reinforced concrete moment resisting frame (RCMRF), which is one of the most commonly used structural systems around the world. The premature failure of such connections would severely limit the seismic performance and increase the vulnerability of RCMRF. In the past decades, researchers primarily focused on investigating the structural behaviour and failure mechanisms of conventional beam-column joints, the beam width of which is either smaller than or equal to the column width, while studies in wide beam-column joints were scarce. This paper presents the preliminary experimental results of two full-scale exterior wide beam-column connections, which are mainly designed and detailed according to ACI 318-14 and ACI 352R-02, under reversed cyclic loading. The ratios of the design shear force to the nominal shear strength of these specimens are 1.0 and 1.7, respectively, so as to probe into differences of the joint shear strength between experimental results and predictions by design codes of practice. Flexural failure dominated in the specimen with ratio of 1.0 in which full-width plastic hinges were observed, while both beam hinges and post-peak joint shear failure occurred for the other specimen. No sign of premature joint shear failure was found which is inconsistent with ACI codes’ prediction. Finally, a modification of current codes of practice is provided to accurately predict the joint shear strength in wide beam-column joint.

Keywords: Joint shear strength, reversed cyclic loading, seismic codes, wide beam-column joints.

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Authors: Kohtaroh Miyamoto

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As enterprise computing becomes more and more complex, the costs and technical challenges of IT system maintenance and support are increasing rapidly. One popular approach to managing IT system maintenance is to prepare and use a FAQ (Frequently Asked Questions) system to manage and reuse systems knowledge. Such a FAQ system can help reduce the resolution time for each service incident ticket. However, there is a major problem where over time the knowledge in such FAQs tends to become outdated. Much of the knowledge captured in the FAQ requires periodic updates in response to new insights or new trends in the problems addressed in order to maintain its usefulness for problem resolution. These updates require a systematic approach to define the exact portion of the FAQ and its content. Therefore, we are working on a novel method to hierarchically structure the FAQ and automate the updates of its structure and content. We use structured information and the unstructured text information with the timelines of the information in the service incident tickets. We cluster the tickets by structured category information, by keywords, and by keyword modifiers for the unstructured text information. We also calculate an urgency score based on trends, resolution times, and priorities. We carefully studied the tickets of one of our projects over a 2.5-year time period. After the first 6 months we started to create FAQs and confirmed they improved the resolution times. We continued observing over the next 2 years to assess the ongoing effectiveness of our method for the automatic FAQ updates. We improved the ratio of tickets covered by the FAQ from 32.3% to 68.9% during this time. Also, the average time reduction of ticket resolution was between 31.6% and 43.9%. Subjective analysis showed more than 75% reported that the FAQ system was useful in reducing ticket resolution times.

Keywords: FAQ System, Resolution Time, Service Incident Tickets, IT System Maintenance.

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

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

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

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Authors: A. Al Hinai, H. Jayasuriya, H. Kotagama

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Most Gulf Cooperation Council (GCC) countries with oil-based economy like Oman are looking for other potential revenue generation options as the crude oil price is regularly fluctuating due to changing geopolitical environment. Oman has advantage of possessing world-heritage nature tourism hotspots around the country and the government is making investments and strategies to uplift the tourism industry following Oman Vision 2040 strategies. Oman’s agriculture is not significantly contributing to the economy, but possesses specific and diversified arid cropping systems. Oman has modern farms; nevertheless some of the agricultural production activities are done with cultural practices and styles that would be attractive to tourists. The aim of this paper is to investigate the potentials for promoting agritourism industry in Oman; recognize potential sites, commodities and activities, and predict potential revenue generation as a projection from that of the tourism sector. Moreover, the study enables to foresee possible auxiliary advantages of agritourism such as, empowerment of women and youth, enhancement in the value-addition industry for agricultural produce through technology transfer and capacity building, and producing export quality products. Agritourism could increase employability, empowerment of women and youth, improve value-addition industry and export-oriented agribusiness. These efforts including provision of necessary technology-transfer and capacity-building should be rendered by the collaboration of academic institutions, relevant ministries and other public and private sector stakeholders.

Keywords: Agritourism, nature-based tourism, potentials, revenue generation, value addition.

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Authors: Erfan Niazi, Marianne Fenech

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Red Blood Cells (RBCs) or erythrocytes tend to form chain-like aggregates under low shear rate called rouleaux. This is a reversible process and rouleaux disaggregate in high shear rates. Therefore, RBCs aggregation occurs in the microcirculation where low shear rates are present but does not occur under normal physiological conditions in large arteries. Numerical modeling of RBCs interactions is fundamental in analytical models of a blood flow in microcirculation. Population Balance Modeling (PBM) is particularly useful for studying problems where particles agglomerate and break in a two phase flow systems to find flow characteristics. In this method, the elementary particles lose their individual identity due to continuous destructions and recreations by break-up and agglomeration. The aim of this study is to find RBCs aggregation in a dynamic situation. Simplified PBM was used previously to find the aggregation rate on a static observation of the RBCs aggregation in a drop of blood under the microscope. To find aggregation rate in a dynamic situation we propose an experimental set up testing RBCs sedimentation. In this test, RBCs interact and aggregate to form rouleaux. In this configuration, disaggregation can be neglected due to low shear stress. A high-speed camera is used to acquire video-microscopic pictures of the process. The sizes of the aggregates and velocity of sedimentation are extracted using an image processing techniques. Based on the data collection from 5 healthy human blood samples, the aggregation rate was estimated as 2.7x10³(±0.3 x10³) 1/s.

Keywords: Red blood cell, Rouleaux, microfluidics, image processing, population balance modeling.

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Authors: A. Driouiche, S. Mohareb, A. Hadfi

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In Morocco’s Agadir region, the reuse of treated wastewater for irrigation of green spaces has faced the problem of scaling of the pipes of these waters. This research paper aims at studying the phenomenon of scaling caused by the treated wastewater from the Mzar sewage treatment plant. These waters are used in the irrigation of golf turf for the Ocean Golf Resort. Ocean Golf, located about 10 km from the center of the city of Agadir, is one of the most important recreation centers in Morocco. The course is a Belt Collins design with 27 holes, and is quite open with deep challenging bunkers. The formation of solid deposits in the irrigation systems has led to a decrease in their lifetime and, consequently, a loss of load and performance. Thus, the sprinklers used in golf turf irrigation are plugged in the first weeks of operation. To study this phenomenon, the wastewater used for the irrigation of the golf turf was taken and analyzed at various points, and also samples of scale formed in the circuits of the passage of these waters were characterized. This characterization of the scale was performed by X-ray fluorescence spectrometry, X-ray diffraction (XRD), thermogravimetric analysis (TGA), differential thermal analysis (DTA), and scanning electron microscopy (SEM). The results of the physicochemical analysis of the waters show that they are full of bicarbonates (653 mg/L), chloride (478 mg/L), nitrate (412 mg/L), sodium (425 mg/L) and calcium (199mg/L). Their pH is slightly alkaline. The analysis of the scale reveals that it is rich in calcium and phosphorus. It is formed of calcium carbonate (CaCO₃), silica (SiO₂), calcium silicate (Ca₂SiO₄), hydroxylapatite (Ca₁₀P₆O₂₆), calcium carbonate and phosphate (Ca₁₀(PO₄) 6CO₃) and silicate calcium and magnesium (Ca₅MgSi₃O₁₂).

Keywords: Agadir, irrigation, scaling water, wastewater.

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Authors: T. Delval, C. Sauvage, Q. Jullien, R. Viano, T. Diallo, B. Collignan, G. Picinbono

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In the context of the international spread of COVID-19, the Centre Scientifique et Technique du Bâtiment (CSTB) has led a joint research with the French government authorities Hauts-de-Seine department, to analyse the risk in school spaces according to their configuration, ventilation system and spatial segmentation strategy. This paper describes the main results of this joint research. A multidisciplinary team involving experts in indoor air quality/ventilation, pedestrian movements and IT domains was established to develop a COVID risk analysis tool based on Building Information Model. The work started with specific analysis on two pilot schools in order to provide for the local administration specifications to minimize the spread of the virus. Different recommendations were published to optimize/validate the use of ventilation systems and the strategy of student occupancy and student flow segmentation within the building. This COVID expertise has been digitized in order to manage a quick risk analysis on the entire building that could be used by the public administration through an easy user interface implemented in a free BIM Management software. One of the most interesting results is to enable a dynamic comparison of different ventilation system scenarios and space occupation strategy inside the BIM model. This concurrent engineering approach provides users with the optimal solution according to both ventilation and pedestrian flow expertise.

Keywords: BIM, knowledge management, system expert, risk management, indoor ventilation, pedestrian movement, integrated design.

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Authors: Sudhir Agashe, Ashok Ghatol, Sujata Agashe

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In this paper the development of a heat exchanger as a pilot plant for educational purpose is discussed and the use of neural network for controlling the process is being presented. The aim of the study is to highlight the need of a specific Pseudo Random Binary Sequence (PRBS) to excite a process under control. As the neural network is a data driven technique, the method for data generation plays an important role. In light of this a careful experimentation procedure for data generation was crucial task. Heat exchange is a complex process, which has a capacity and a time lag as process elements. The proposed system is a typical pipe-in- pipe type heat exchanger. The complexity of the system demands careful selection, proper installation and commissioning. The temperature, flow, and pressure sensors play a vital role in the control performance. The final control element used is a pneumatically operated control valve. While carrying out the experimentation on heat exchanger a welldrafted procedure is followed giving utmost attention towards safety of the system. The results obtained are encouraging and revealing the fact that if the process details are known completely as far as process parameters are concerned and utilities are well stabilized then feedback systems are suitable, whereas neural network control paradigm is useful for the processes with nonlinearity and less knowledge about process. The implementation of NN control reinforces the concepts of process control and NN control paradigm. The result also underlined the importance of excitation signal typically for that process. Data acquisition, processing, and presentation in a typical format are the most important parameters while validating the results.

Keywords: Process identification, neural network, heat exchanger.

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: Diesel engine, machine learning, NOx emission, semi-empirical.

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Authors: Maksudur Rahman Khan, Kar Min Chan, Huei Ruey Ong, Chin Kui Cheng, Wasikur Rahman

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Microbial fuel cells (MFCs) represent a promising technology for simultaneous bioelectricity generation and wastewater treatment. Catalysts are significant portions of the cost of microbial fuel cell cathodes. Many materials have been tested as aqueous cathodes, but air-cathodes are needed to avoid energy demands for water aeration. The sluggish oxygen reduction reaction (ORR) rate at air cathode necessitates efficient electrocatalyst such as carbon supported platinum catalyst (Pt/C) which is very costly. Manganese oxide (MnO2) was a representative metal oxide which has been studied as a promising alternative electrocatalyst for ORR and has been tested in air-cathode MFCs. However the single MnO2 has poor electric conductivity and low stability. In the present work, the MnO2 catalyst has been modified by doping Pt nanoparticle. The goal of the work was to improve the performance of the MFC with minimum Pt loading. MnO2 and Pt nanoparticles were prepared by hydrothermal and sol gel methods, respectively. Wet impregnation method was used to synthesize Pt/MnO2 catalyst. The catalysts were further used as cathode catalysts in air-cathode cubic MFCs, in which anaerobic sludge was inoculated as biocatalysts and palm oil mill effluent (POME) was used as the substrate in the anode chamber. The asprepared Pt/MnO2 was characterized comprehensively through field emission scanning electron microscope (FESEM), X-Ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and cyclic voltammetry (CV) where its surface morphology, crystallinity, oxidation state and electrochemical activity were examined, respectively. XPS revealed Mn (IV) oxidation state and Pt (0) nanoparticle metal, indicating the presence of MnO2 and Pt. Morphology of Pt/MnO2 observed from FESEM shows that the doping of Pt did not cause change in needle-like shape of MnO2 which provides large contacting surface area. The electrochemical active area of the Pt/MnO2 catalysts has been increased from 276 to 617 m2/g with the increase in Pt loading from 0.2 to 0.8 wt%. The CV results in O2 saturated neutral Na2SO4 solution showed that MnO2 and Pt/MnO2 catalysts could catalyze ORR with different catalytic activities. MFC with Pt/MnO2 (0.4 wt% Pt) as air cathode catalyst generates a maximum power density of 165 mW/m3, which is higher than that of MFC with MnO2 catalyst (95 mW/m3). The open circuit voltage (OCV) of the MFC operated with MnO2 cathode gradually decreased during 14 days of operation, whereas the MFC with Pt/MnO2 cathode remained almost constant throughout the operation suggesting the higher stability of the Pt/MnO2 catalyst. Therefore, Pt/MnO2 with 0.4 wt% Pt successfully demonstrated as an efficient and low cost electrocatalyst for ORR in air cathode MFC with higher electrochemical activity, stability and hence enhanced performance.

Keywords: Microbial fuel cell, oxygen reduction reaction, Pt/MnO2, palm oil mill effluent, polarization curve.

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Authors: Robson C. Santos, Julio C. P. Ribeiro, Iorran M. de Castro, Luan C. F. Rodrigues, Sandro R. L. Silva, Diego M. Quesada

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The work aims to develop a robot in the form of autonomous vehicle to detect, inspection and mapping of underground pipelines through the ATmega328 Arduino platform. Hardware prototyping is very similar to C / C ++ language that facilitates its use in robotics open source, resembles PLC used in large industrial processes. The robot will traverse the surface independently of direct human action, in order to automate the process of detecting buried pipes, guided by electromagnetic induction. The induction comes from coils that send the signal to the Arduino microcontroller contained in that will make the difference in intensity and the treatment of the information, and then this determines actions to electrical components such as relays and motors, allowing the prototype to move on the surface and getting the necessary information. This change of direction is performed by a stepper motor with a servo motor. The robot was developed by electrical and electronic assemblies that allowed test your application. The assembly is made up of metal detector coils, circuit boards and microprocessor, which interconnected circuits previously developed can determine, process control and mechanical actions for a robot (autonomous car) that will make the detection and mapping of buried pipelines plates. This type of prototype can prevent and identifies possible landslides and they can prevent the buried pipelines suffer an external pressure on the walls with the possibility of oil leakage and thus pollute the environment.

Keywords: Robotic, metal detector, embedded system, pipeline.

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Authors: James Kuria, John Kihiu

Abstract:

This work presents a numerical model developed to simulate the dynamics and vibrations of a multistage tractor gearbox. The effect of time varying mesh stiffness, time varying frictional torque on the gear teeth, lateral and torsional flexibility of the shafts and flexibility of the bearings were included in the model. The model was developed by using the Lagrangian method, and it was applied to study the effect of three design variables on the vibration and stress levels on the gears. The first design variable, module, had little effect on the vibration levels but a higher module resulted to higher bending stress levels. The second design variable, pressure angle, had little effect on the vibration levels, but had a strong effect on the stress levels on the pinion of a high reduction ratio gear pair. A pressure angle of 25o resulted to lower stress levels for a pinion with 14 teeth than a pressure angle of 20o. The third design variable, contact ratio, had a very strong effect on both the vibration levels and bending stress levels. Increasing the contact ratio to 2.0 reduced both the vibration levels and bending stress levels significantly. For the gear train design used in this study, a module of 2.5 and contact ratio of 2.0 for the various meshes was found to yield the best combination of low vibration levels and low bending stresses. The model can therefore be used as a tool for obtaining the optimum gear design parameters for a given multistage spur gear train.

Keywords: bending stress levels, frictional torque, gear designparameters, mesh stiffness, multistage gear train, vibration levels.

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Authors: J. Martin, A. Dannenberg, G. Detrell, R. Ewald, S. Fasoulas

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Microalgae-based photobioreactors (PBR) for Life Support Systems (LSS) are currently being investigated for future space missions such as a crewed base on planets or moons. Biological components may help reducing resupply masses by closing material mass flows with the help of regenerative components. Via photosynthesis, the microalgae use CO₂, water, light and nutrients to provide oxygen and biomass for the astronauts. These capabilities could have synergies with Earth applications that tackle current problems and the developed technologies can be transferred. For example, a current worldwide discussed issue is the increased nitrate and phosphate pollution of ground water from agricultural waste waters. To investigate the potential use of a biological system based on the ability of the microalgae to extract and use nitrate and phosphate for the treatment of polluted ground water from agricultural applications, a scalable test stand is being developed. This test stand investigates the maximization of intake rates of nitrate and quantifies the produced biomass and oxygen. To minimize the required energy, for the uptake of nitrate from artificial waste water (AWW) the Flashing Light Effect (FLE) and the adaption of the illumination spectrum were realized. This paper describes the composition of the AWW, the development of the illumination unit and the possibility of non-invasive process optimization and control via the adaption of the illumination spectrum and illumination cycles. The findings were a doubling of the energy related growth rate by adapting the illumination setting.

Keywords: Microalgae, illumination, nitrate uptake, flashing light effect.

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Authors: Shekhar Parajulee

Abstract:

Nepal practiced a centralized unitary governing system for long and has gone through the federal system after the promulgation of the new constitution on 20 September 2015. There is a big paradigm shift in terms of governance after it. Now, there are three levels of governments, one federal government in the center, seven provincial governments and 753 local governments. Federalism refers to a political governing system with multiple tiers of government working together with coordination. It is preferred for self and shared rule. Though it has opened the door for rights of the people, political stability, state restructuring, and sustainable peace and development, there are many prospects and challenges for its proper implementation. This research analyzes the discourses of federalism implementation in Nepal with special reference to one of seven provinces, Gandaki. Federalism is a new phenomenon in Nepali politics and informed debates on it are required for its right evolution. This research will add value in this regard. Moreover, tracking its evolution and the exploration of the attitudes and behaviors of key actors and stakeholders in a new experiment of a new governing system is also important. The administrative and political system of Gandaki province in terms of service delivery and development will critically be examined. Besides demonstrating the performances of the provincial government and assembly, it will analyze the inter-governmental relation of Gandaki with the other two tiers of government. For this research, people from provincial and local governments (elected representatives and government employees), provincial assembly members, academicians, civil society leaders and journalists are being interviewed. The interview findings will be analyzed by supplementing with published documents. Just going into the federal structure is not the solution. As in the case of other provincial governments, Gandaki also had to start from scratch. It gradually took a shape of government and has been functioning sluggishly. The provincial government has many challenges ahead, which has badly hindered its plans and actions. Additionally, fundamental laws, infrastructures and human resources are found to be insufficient at the sub-national level. Lack of clarity in the jurisdiction is another main challenge. The Nepali Constitution assumes cooperation, coexistence and coordination as the fundamental principles of federalism which, unfortunately, appear to be lacking among the three tiers of government despite their efforts. Though the devolution of power to sub-national governments is essential for the successful implementation of federalism, it has apparently been delayed due to the centralized mentality of bureaucracy as well as a political leader. This research will highlight the reasons for the delay in the implementation of federalism. There might be multiple underlying reasons for the slow pace of implementation of federalism and identifying them is very tough. Moreover, the federal spirit is found to be absent in the main players of today's political system, which is a big irony. So, there are some doubts about whether the federal system in Nepal is just a keepsake or a substantive achievement.

Keywords: federalism, inter-governmental relations, Nepal, provincial government

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Authors: Sidharth Talan, Sanjay Kumar Sharma, Eoin Joseph Wallace, Nikita Agrawal

Abstract:

Underground mining is at the core of rapidly evolving metals and minerals sector due to the increasing mineral consumption globally. Even though the surface mines are still more abundant on earth, the scales of industry are slowly tipping towards underground mining due to rising depth and complexities of orebodies. Thus, the efficient and productive functioning of underground operations depends significantly on the synchronized performance of key elements such as operating site, mining equipment, manpower and mine services. Production drilling is the process of conducting long hole drilling for the purpose of charging and blasting these holes for the production of ore in underground metal mines. Thus, production drilling is the crucial segment in the underground metal mining value chain. This paper presents the process mapping tool to evaluate the production drilling process in the underground metal mining operation by dividing the given process into three segments namely Input, Process and Output. The three segments are further segregated into factors and sub-factors. As per the study, the major input factors crucial for the efficient functioning of production drilling process are power, drilling water, geotechnical support of the drilling site, skilled drilling operators, services installation crew, oils and drill accessories for drilling machine, survey markings at drill site, proper housekeeping, regular maintenance of drill machine, suitable transportation for reaching the drilling site and finally proper ventilation. The major outputs for the production drilling process are ore, waste as a result of dilution, timely reporting and investigation of unsafe practices, optimized process time and finally well fragmented blasted material within specifications set by the mining company. The paper also exhibits the drilling loss matrix, which is utilized to appraise the loss in planned production meters per day in a mine on account of availability loss in the machine due to breakdowns, underutilization of the machine and productivity loss in the machine measured in drilling meters per unit of percussion hour with respect to its planned productivity for the day. The given three losses would be essential to detect the bottlenecks in the process map of production drilling operation so as to instigate the action plan to suppress or prevent the causes leading to the operational performance deficiency. The given tool is beneficial to mine management to focus on the critical factors negatively impacting the production drilling operation and design necessary operational and maintenance strategies to mitigate them. 

Keywords: Process map, drilling loss matrix, availability, utilization, productivity, percussion rate.

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Authors: Seyyed Abbas Mojtabavi, Mojtaba Fatzaneh Moghadam, Masoud Mahdavi

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Steel Metal Shear Wall is one of the most common and widely used energy dissipation systems in structures, which is used today as a damping system due to the increase in the construction of metal structures. In the present study, the shear wall of the steel plate with dimensions of 5×3 m and thickness of 0.024 m was modeled with 2 floors of total height from the base level with finite element method in Abaqus software. The loading is done as a concentrated load at the upper point of the shear wall on the second floor based on step type buckle. The mesh in the model is applied in two directions of length and width of the shear wall, equal to 0.02 and 0.033, respectively, and the mesh in the models is of sweep type. Finally, it was found that the steel plate shear wall with cavity (CSPSW) compared to the SPSW model, S (Mises), Smax (In-Plane Principal), Smax (In-Plane Principal-ABS), Smax (Min Principal) increased by 53%, 70%, 68% and 43%, respectively. The presence of cavities has led to an increase in the estimated stresses, but their presence has caused critical stresses and critical deformations created to be removed from the inner surface of the shear wall and transferred to the desired sections (regular cavities) which can be suggested as a solution in seismic design and improvement of the structure to transfer possible damage during the earthquake and storm to the desired and pre-designed location in the structure.

Keywords: Steel plate shear wall, Abacus software, finite element method, boundary element, seismic structural improvement, Von misses Stress.

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Authors: Mawloud Mosbah, Bachir Boucheham

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Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Keywords: CBIR, Color Global Histogram, Color Local Histogram, Weak Segmentation, Euclidean Distance.

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Authors: Claudineia Brazil, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Rafael Haag

Abstract:

Renewable energy sources are dependent on climatic variability, so for adequate energy planning, observations of the meteorological variables are required, preferably representing long-period series. Despite the scientific and technological advances that meteorological measurement systems have undergone in the last decades, there is still a considerable lack of meteorological observations that form series of long periods. The reanalysis is a system of assimilation of data prepared using general atmospheric circulation models, based on the combination of data collected at surface stations, ocean buoys, satellites and radiosondes, allowing the production of long period data, for a wide gamma. The third generation of reanalysis data emerged in 2010, among them is the Climate Forecast System Reanalysis (CFSR) developed by the National Centers for Environmental Prediction (NCEP), these data have a spatial resolution of 0.50 x 0.50. In order to overcome these difficulties, it aims to evaluate the performance of solar radiation estimation through alternative data bases, such as data from Reanalysis and from meteorological satellites that satisfactorily meet the absence of observations of solar radiation at global and/or regional level. The results of the analysis of the solar radiation data indicated that the reanalysis data of the CFSR model presented a good performance in relation to the observed data, with determination coefficient around 0.90. Therefore, it is concluded that these data have the potential to be used as an alternative source in locations with no seasons or long series of solar radiation, important for the evaluation of solar energy potential.

Keywords: Climate, reanalysis, renewable energy, solar radiation.

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Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

Abstract:

Farm management and operations will drastically change due to access to real-time data, real-time forecasting and tracking of physical items in combination with Internet of Things (IoT) developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm decision-making process does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyze on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue and environmental impact. Evolutionary Computing (EC) can be very effective in finding the optimal combination of sets of some objects and finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and EC in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management and its uptake has become a continuing trend.

Keywords: Big data, evolutionary computing, cloud, precision technologies

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Authors: Yesubai Rubavathi Charles, Ravi Ramraj

Abstract:

In order to retrieve images efficiently from a large database, a unique method integrating color and texture features using genetic programming has been proposed. Opponent color histogram which gives shadow, shade, and light intensity invariant property is employed in the proposed framework for extracting color features. For texture feature extraction, fast discrete curvelet transform which captures more orientation information at different scales is incorporated to represent curved like edges. The recent scenario in the issues of image retrieval is to reduce the semantic gap between user’s preference and low level features. To address this concern, genetic algorithm combined with relevance feedback is embedded to reduce semantic gap and retrieve user’s preference images. Extensive and comparative experiments have been conducted to evaluate proposed framework for content based image retrieval on two databases, i.e., COIL-100 and Corel-1000. Experimental results clearly show that the proposed system surpassed other existing systems in terms of precision and recall. The proposed work achieves highest performance with average precision of 88.2% on COIL-100 and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3% on Corel. Thus, the experimental results confirm that the proposed content based image retrieval system architecture attains better solution for image retrieval.

Keywords: Content based image retrieval, Curvelet transform, Genetic algorithm, Opponent color histogram, Relevance feedback.

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