Search results for: system reliability optimization

Authors: Rosana Choy, Fabiola Henostroza

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Actual theory suggests social-ecological factors as the main framework of bullying. Most previous research in this phenomenon is focused on the identification of bullying attitudes and conducts in puberty and adolescence periods. For this reason, this study is considered as a contribution to the existing knowledge in measuring matters, because of its non-traditional way of evaluation (graphic items), and because of its approach to a distinctive age group, children from 7 to 9 years-old, not regularly examined in current studies in this field. The research used a transversal descriptive investigation design for the development of a graphic test for bullying predisposition. The process began with the operationalization of the variable bullying predisposition, the structuring of the factors and variable indicators of a pilot instrument, evaluation by experts of the items representation, and finally it continued with the test application to children of two types of regular school population in Lima-Peru: private and public schools. The reliability level was 0.85 and the validity of the test corroborated the three-factor structure proposed by the researchers.

Keywords: bullying, graphic test, reliability, validity

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Authors: Mohammad Yousefikia, Sara Moridpour, Ehsan Mazloumi

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Perceiving track geometry deterioration decisively influences the optimization of track maintenance operations. The effective management of this deterioration and increasingly utilized system with limited financial resources is a significant challenge. This paper provides a review of degradation models relevant for railroad tracks. Furthermore, due to the lack of long term information on the condition development of tram infrastructures, presents the methodology which will be used to derive degradation models from the data of Melbourne tram network.

Keywords: deterioration modeling, asset management, railway, tram

Procedia PDF Downloads 379

Authors: F. A. Thomas, M. Schrafl-Altermatt, R. Treier, S. Kaufmann

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Stroke is the main cause of adult disability. Especially upper limb function is affected in most patients. Recently, cooperative hand movements have been shown to be a promising type of upper limb training in stroke rehabilitation. In these movements, which are frequently found in activities of daily living (e.g. opening a bottle, winding up a blind), the force of one upper limb has to be equally counteracted by the other limb to successfully accomplish a task. The use of standardized and reliable clinical assessments is essential to evaluate the efficacy of therapy and the functional outcome of a patient. Many assessments for upper limb function or impairment are available. However, the evaluation of cooperative hand movement tasks are rarely included in those. Thus, the aim of this study was (i) to develop a novel clinical assessment (CASA - Cooperative Activity Stroke Assessment) for the evaluation of patients’ capacity to perform cooperative hand movements and (ii) to test its inter- and interrater reliability. Furthermore, CASA scores were compared to current gold standard assessments for upper extremity in stroke patients (i.e. Fugl-Meyer Assessment, Box & Blocks Test). The CASA consists of five cooperative activities of daily living including (1) opening a jar, (2) opening a bottle, (3) open and closing of a zip, (4) unscrew a nut and (5) opening a clipbox. Here, the goal is to accomplish the tasks as fast as possible. In addition to the quantitative rating (i.e. time) which is converted to a 7-point scale, also the quality of the movement is rated in a 4-point scale. To test the reliability of CASA, fifteen stroke subjects were tested within a week twice by the same two raters. Intra-and interrater reliability was calculated using the intraclass correlation coefficient (ICC) for total CASA score and single items. Furthermore, Pearson-correlation was used to compare the CASA scores to the scores of Fugl-Meyer upper limb assessment and the box and blocks test, which were assessed in every patient additionally to the CASA. ICC scores of the total CASA score indicated an excellent- and single items established a good to excellent inter- and interrater reliability. Furthermore, the CASA score was significantly correlated to the Fugl-Meyer and Box & Blocks score. The CASA provides a reliable assessment for cooperative hand movements which are crucial for many activities of daily living. Due to its non-costly setup, easy and fast implementation, we suggest it to be well suitable for clinical application. In conclusion, the CASA is a useful tool in assessing the functional status and therapy related recovery in cooperative hand movement capacity in stroke patients.

Keywords: activitites of daily living, clinical assessment, cooperative hand movements, reliability, stroke

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Authors: Dheyaa W. Abbood, Rafa H. AL-Suhaili, May S. Saleh

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A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs length sand their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy.The optimization carried out subjected to constraints that ensure a safe structure against the uplift pressure force and sufficient protection length at the downstream side of the structure to overcome an excessive exit gradient. The Geo-studios oft ware, was used to analyze 1200 different cases. For each case the length of protection and volume of structure required to satisfy the safety factors mentioned previously were estimated. An ANN model was developed and verified using these cases input-output sets as its data base. A MatLAB code was written to perform a genetic algorithm optimization modeling coupled with this ANN model using a formulated optimization model. A sensitivity analysis was done for selecting the cross-over probability, the mutation probability and level ,the number of population, the position of the crossover and the weights distribution for all the terms of the objective function. Results indicate that the most factor that affects the optimum solution is the number of population required. The minimum value that gives stable global optimum solution of this parameters is (30000) while other variables have little effect on the optimum solution.

Keywords: inclined cutoff, optimization, genetic algorithm, artificial neural networks, geo-studio, uplift pressure, exit gradient, factor of safety

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Authors: Prateep Wajeetongratana

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The objective of this research is to examine the effects of internal audit innovation on firm performance effectiveness influences of financial report reliability, organizational process improvement, and risk management effectiveness. This paper drew upon the survey data collected from 400 employees survey conducted at Nonthaburi province, Thailand. The statistics utilized in this paper included percentage, mean, standard deviation, and regression analysis. The findings revealed that the majority of samples were between 31-40 years old, married, held an undergraduate degree, and had an average income between 10,000-15,000 baht. And also the results show that auditing integration has only influence on financial report reliability. Moreover, corporate risk evaluation has effect on firm performance by risk management effectiveness and control self-assessment has effect influence on firm performance by organizational process improvement and risk management effectiveness as well.

Keywords: corporate risk evaluation, firm performance effectiveness, internal audit innovation, marketing management

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Authors: Moustafa Osman Mohammed

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Integration sustainability outcomes give attention to construction ecology in the design review of urban environments to comply with Earth’s System that is composed of integral parts of the (i.e., physical, chemical and biological components). Naturally, exchange patterns of industrial ecology have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. When engineering topology is affecting internal and external processes in system networks, it postulated the valence of the first-level spatial outcome (i.e., project compatibility success). These instrumentalities are dependent on relating the second-level outcome (i.e., participant security satisfaction). Construction ecology approach feedback energy from resources flows between biotic and abiotic in the entire Earth’s ecosystems. These spatial outcomes are providing an innovation, as entails a wide range of interactions to state, regulate and feedback “topology” to flow as “interdisciplinary equilibrium” of ecosystems. The interrelation dynamics of ecosystems are performing a process in a certain location within an appropriate time for characterizing their unique structure in “equilibrium patterns”, such as biosphere and collecting a composite structure of many distributed feedback flows. These interdisciplinary systems regulate their dynamics within complex structures. These dynamic mechanisms of the ecosystem regulate physical and chemical properties to enable a gradual and prolonged incremental pattern to develop a stable structure. The engineering topology of construction ecology for integration sustainability outcomes offers an interesting tool for ecologists and engineers in the simulation paradigm as an initial form of development structure within compatible computer software. This approach argues from ecology, resource savings, static load design, financial other pragmatic reasons, while an artistic/architectural perspective, these are not decisive. The paper described an attempt to unify analytic and analogical spatial modeling in developing urban environments as a relational setting, using optimization software and applied as an example of integrated industrial ecology where the construction process is based on a topology optimization approach.

Keywords: construction ecology, industrial ecology, urban topology, environmental planning

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Authors: Chung To Kong, Siu Ming Yiu

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Rubik's cube was invented in 1974. Since then, speedcubers all over the world try their best to break the world record again and again. The newest record is 3.47 seconds. There are many factors that affect the timing, including turns per second (tps), algorithm, finger trick, hardware of the cube. In this paper, the lower bound of the cube solving time will be discussed using convex optimization. Extended analysis of the world records will be used to understand how to improve the timing. With the understanding of each part of the solving step, the paper suggests a list of speed improvement techniques. Based on the analysis of the world record, there is a high possibility that the 3 seconds mark will be broken soon.

Keywords: Rubik's Cube, speed, finger trick, optimization

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Azeez Balogun

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Inexperienced building score practices are continually evolving and vary across areas. Yet, a few middle ideas stay steady, such as website selection, design, energy efficiency, water and material conservation, indoor environmental great, operational optimization, and waste discount. The essence of green building lies inside the optimization of 1 or more of those standards. This paper conducts a comparative analysis of 7 extensively recognized sustainable score structures—BREEAM, CASBEE, green GLOBES, inexperienced superstar, HK-BEAM, IGBC green homes, and LEED—based totally on the perceptions and opinions of stakeholders in Nigeria certified in green constructing rating systems. The purpose is to pick out and adopt an appropriate green building rating device for Nigeria. Numerous components of those systems had been tested to determine the high-quality health of the Nigerian built environment. The findings imply that LEED, the important machine within the USA and Canada, is the most suitable for Nigeria due to its sturdy basis, extensive funding, and confirmed blessings. LEED obtained the highest rating of eighty out of one hundred points on this assessment.

Keywords: structure, built surroundings, inexperienced building score gadget, Nigeria Inexperienced Constructing Council, sustainability

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Authors: Li Long, Thomas Ortlepp

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A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor, and sensor layout geometrical form factor. Based on the properties of electrons, phonons, grain boundaries, and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of the Boltzmann transport equation. The model includes the effect of grain structure, grain boundary trap properties, and doping concentration. The layer structure factor is analyzed with respect to the infrared absorption coefficient. The optimization of layout design is characterized by the form factor, which is calculated for different sensor designs. A double-layer polycrystalline silicon thermopile infrared sensor on a suspended membrane has been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed by measurement results.

Keywords: polycrystalline silicon, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor

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Authors: Xiaoming Jiang, Jinqiao Shi, Qingfeng Tan, Wentao Zhang, Xuebin Wang, Muqian Chen

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Nowadays, big companies such as Google, Microsoft, which have adequate proxy servers, have perfectly implemented their web crawlers for a certain website in parallel. But due to lack of expensive proxy servers, it is still a puzzle for researchers to crawl large amounts of information from a single website in parallel. In this case, it is a good choice for researchers to use free public proxy servers which are crawled from the Internet. In order to improve efficiency of web crawler, the following two issues should be considered primarily: (1) Tasks may fail owing to the instability of free proxy servers; (2) A proxy server will be blocked if it visits a single website frequently. In this paper, we propose Proxisch, an optimization approach of large-scale unstable proxy servers scheduling, which allow anyone with extremely low cost to run a web crawler efficiently. Proxisch is designed to work efficiently by making maximum use of reliable proxy servers. To solve second problem, it establishes a frequency control mechanism which can ensure the visiting frequency of any chosen proxy server below the website’s limit. The results show that our approach performs better than the other scheduling algorithms.

Keywords: proxy server, priority queue, optimization algorithm, distributed web crawling

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Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

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Authors: Katarina Rogulj, Ivana Racetin, Jelena Kilic

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In this study, the fuzzy logic approach (FLA) was developed for construction project management (CPM) under uncertainty and duality. The focus was on decision making in selecting the type of the glass facade for a residential-commercial building in the main design. The adoption of fuzzy sets was capable of reflecting construction managers’ reliability level over subjective judgments, and thus the robustness of the system can be achieved. An α-cuts method was utilized for discretizing the fuzzy sets in FLA. This method can communicate all uncertain information in the optimization process, taking into account the values of this information. Furthermore, FLA provides in-depth analyses of diverse policy scenarios that are related to various levels of economic aspects when it comes to the construction projects' valid decision making. The developed approach is applied to CPM to demonstrate its applicability. Analyzing the materials of glass facades, variants were defined. The development of the FLA for the CPM included relevant construction projec'ts stakeholders that were involved in the criteria definition to evaluate each variant. Using fuzzy Decision-Making Trial and Evaluation Laboratory Method (DEMATEL) comparison of the glass facade was conducted. This way, a rank, according to the priorities for inclusion into the main design, of variants is obtained. The concept was tested on a residential-commercial building in the city of Rijeka, Croatia. The newly developed methodology was then compared with the existing one. The aim of the research was to define an approach that will improve current judgments and decisions when it comes to the material selection of buildings facade as one of the most important architectural and engineering tasks in the main design. The advantage of the new methodology compared to the old one is that it includes the subjective side of the managers’ decisions, as an inevitable factor in each decision making. The proposed approach can help construction projects managers to identify the desired type of glass facade according to their preference and practical conditions, as well as facilitate in-depth analyses of tradeoffs between economic efficiency and architectural design.

Keywords: construction projects management, DEMATEL, fuzzy logic approach, glass façade selection

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Authors: Ankur Sachan

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The ability to make quick yet intelligent and value-added decisions to develop new fields has always been of great significance. In situations where the capital expenses and subsurface risk are high, carefully analyzing the inherent uncertainties in the reservoir and how they impact the predicted hydrocarbon accumulation and production becomes a daunting task. The problem is compounded in offshore environments, especially in the presence of heavy oils and disconnected sands where the margin for error is small. Uncertainty refers to the degree to which the data set may be in error or stray from the predicted values. To understand and quantify the uncertainties in reservoir model is important when estimating the reserves. Uncertainty parameters can be geophysical, geological, petrophysical etc. Identification of these parameters is necessary to carry out the uncertainty analysis. With so many uncertainties working at different scales, it becomes essential to have a consistent and efficient way of incorporating them into our analysis. Ranking the uncertainties based on their impact on reserves helps to prioritize/ guide future data gathering and uncertainty reduction efforts. Assigning probabilistic ranges to key uncertainties also enables the computation of probabilistic reserves. With this in mind, this paper, with the help the uncertainty and optimization process in petrel RE shows how the most influential uncertainties can be determined efficiently and how much impact so they have on the reservoir model thus helping in determining a cost effective and accurate model of the reservoir.

Keywords: uncertainty, reservoir model, parameters, optimization analysis

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Authors: Sukant Mehra, Parth Gupta, Varun Arora, Sarvoday Singh, Amit Kohli

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The study was emphasised on dry sliding wear behavior of AISI 1042 steel. Dry sliding wear tests were performed using pin-on-disk apparatus under normal loads of 5, 7.5 and 10 kgf and at speeds 600, 750 and 900 rpm. Response surface methodology (RSM) was utilized for finding optimal values of process parameter and experiment was based on rotatable, central composite design (CCD). It was found that the wear followed linear pattern with the load and rpm. The obtained optimal process parameters have been predicted and verified by confirmation experiments.

Keywords: central composite design (CCD), optimization, response surface methodology (RSM), wear

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Authors: Suraj Kumar Mukti

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Enterprise Resource Planning (ERP) system is a management tool to integrate all departments in an organization. It integrates business processes, manages resources efficiently and provides an appropriate decision support system to management. ERP system implementation is a typical and time taking process as well as money consuming process. Articles related to key success factors of ERP system implementation are available in the literature, but rare authors have focused on roadmap of successful ERP system implementation. Postponement is better if the organization is not ready to implement ERP system in better way; hence checking of organization’s preparation to adopt new system is an important prerequisite to ensure the success of ERP system implementation in an organization. Then comes what will be called as success of ERP system implementation. Benefits achieved by ERP system may be categorized into two categories; viz. tangible and intangible benefits. This research article presents a roadmap to ensure the success of ERP system implementation and benefits achieved through the new system as in success indicator. A case study is presented to evaluate the success and benefit achieved through the new system. The article gives a comprehensive approach to academicians and a roadmap to the organizations seeking to implement the ERP system.

Keywords: ERP system, decision support system, tangible, intangible

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Authors: Murray L. Ireland, Kevin J. Worrall, Rebecca Mackenzie, Thaleia Flessa, Euan McGookin, Douglas Thomson

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Robotic rovers which are designed to work in extra-terrestrial environments present a unique challenge in terms of the reliability and availability of systems throughout the mission. Should some fault occur, with the nearest human potentially millions of kilometres away, detection and identification of the fault must be performed solely by the robot and its subsystems. Faults in the system sensors are relatively straightforward to detect, through the residuals produced by comparison of the system output with that of a simple model. However, faults in the input, that is, the actuators of the system, are harder to detect. A step change in the input signal, caused potentially by the loss of an actuator, can propagate through the system, resulting in complex residuals in multiple outputs. These residuals can be difficult to isolate or distinguish from residuals caused by environmental disturbances. While a more complex fault detection method or additional sensors could be used to solve these issues, an alternative is presented here. Using inverse simulation (InvSim), the inputs and outputs of the mathematical model of the rover system are reversed. Thus, for a desired trajectory, the corresponding actuator inputs are obtained. A step fault near the input then manifests itself as a step change in the residual between the system inputs and the input trajectory obtained through inverse simulation. This approach avoids the need for additional hardware on a mass- and power-critical system such as the rover. The InvSim fault detection method is applied to a simple four-wheeled rover in simulation. Additive system faults and an external disturbance force and are applied to the vehicle in turn, such that the dynamic response and sensor output of the rover are impacted. Basic model-based fault detection is then employed to provide output residuals which may be analysed to provide information on the fault/disturbance. InvSim-based fault detection is then employed, similarly providing input residuals which provide further information on the fault/disturbance. The input residuals are shown to provide clearer information on the location and magnitude of an input fault than the output residuals. Additionally, they can allow faults to be more clearly discriminated from environmental disturbances.

Keywords: fault detection, ground robot, inverse simulation, rover

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Authors: Lucile Soudani, Hervé Illy, Rémi Bouchié

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Mould growth in living environments has been widely reported for decades all throughout the world. A higher level of moisture in housings can lead to building degradation, chemical component emissions from construction materials as well as enhancing mould growth within the envelope elements or on the internal surfaces. Moreover, a significant number of studies have highlighted the link between mould presence and the prevalence of respiratory diseases. In recent years, the proportion of biobased materials used in construction has been increasing, as seen as an effective lever to reduce the environmental impact of the building sector. Besides, bio-based materials are also hygroscopic materials: when in contact with the wet air of a surrounding environment, their porous structures enable a better capture of water molecules, thus providing a more suitable background for mould growth. Many studies have been conducted to develop reliable models to be able to predict mould appearance, growth, and decay over many building materials and external exposures. Some of them require information about temperature and/or relative humidity, exposure times, material sensitivities, etc. Nevertheless, several studies have highlighted a large disparity between predictions and actual mould growth in experimental settings as well as in occupied buildings. The difficulty of considering the influence of all parameters appears to be the most challenging issue. As many complex phenomena take place simultaneously, a preliminary study has been carried out to evaluate the feasibility to sadopt a reliability approach rather than a deterministic approach. Both epistemic and random uncertainties were identified specifically for the prediction of mould appearance and growth. Several studies published in the literature were selected and analysed, from the agri-food or automotive sectors, as the deployed methodology appeared promising.

Keywords: bio-based materials, mould growth, numerical prediction, reliability approach

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Authors: Syed Ahsan, Saleh Alshomrani, Ishtiaq Rasool, Ali Hassan

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In this oral presentation, we will provide an overview of the technical and semantic architecture of a desert border security and critical infrastructure protection security system. Modern border security systems are designed to reduce the dependability and intrusion of human operators. To achieve this, different types of sensors are use along with video surveillance technologies. Application of these technologies in a harsh desert environment of Saudi Arabia poses unique challenges. Environmental and geographical factors including high temperatures, desert storms, temperature variations and remoteness adversely affect the reliability of surveillance systems. To successfully implement a reliable, effective system in a harsh desert environment, the following must be achieved: i) Selection of technology including sensors, video cameras, and communication infrastructure that suit desert environments. ii) Reduced power consumption and efficient usage of equipment to increase the battery life of the equipment. iii) A reliable and robust communication network with efficient usage of bandwidth. Also, to reduce the expert bottleneck, an ontology-based intelligent information systems needs to be developed. Domain knowledge unique and peculiar to Saudi Arabia needs to be formalized to develop an expert system that can detect abnormal activities and any intrusion.

Keywords: border security, sensors, abnormal activity detection, ontologies

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Authors: Jose Daniel Hoyos Giraldo, Jesus Hernan Jimenez Giraldo, Juan Pablo Alvarado Perilla

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Range and endurance are the main limitations of electric aircraft due to the nature of its source of power. The improvement of efficiency on this kind of systems is extremely meaningful to encourage the aircraft operation with less environmental impact. The propeller efficiency highly affects the overall efficiency of the propulsion system; hence its optimization can have an outstanding effect on the aircraft performance. An optimization method is applied to an aircraft propeller in order to maximize its range and endurance by estimating the best combination of geometrical parameters such as diameter and airfoil, chord and pitch distribution for a specific aircraft design at a certain cruise speed, then the rotational speed at which the propeller operates at minimum current consumption is estimated. The optimization is based on the Blade Element Momentum (BEM) method, additionally corrected to account for tip and hub losses, Mach number and rotational effects; furthermore an airfoil lift and drag coefficients approximation is implemented from Computational Fluid Dynamics (CFD) simulations supported by preliminary studies of grid independence and suitability of different turbulence models, to feed the BEM method, with the aim of achieve more reliable results. Additionally, Vortex Theory is employed to find the optimum pitch and chord distribution to achieve a minimum induced loss propeller design. Moreover, the optimization takes into account the well-known brushless motor model, thrust constraints for take-off runway limitations, maximum allowable propeller diameter due to aircraft height and maximum motor power. The BEM-CFD method is validated by comparing its predictions for a known APC propeller with both available experimental tests and APC reported performance curves which are based on Vortex Theory fed with the NASA Transonic Airfoil code, showing a adequate fitting with experimental data even more than reported APC data. Optimal propeller predictions are validated by wind tunnel tests, CFD propeller simulations and a study of how the propeller will perform if it replaces the one of on known aircraft. Some tendency charts relating a wide range of parameters such as diameter, voltage, pitch, rotational speed, current, propeller and electric efficiencies are obtained and discussed. The implementation of CFD tools shows an improvement in the accuracy of BEM predictions. Results also showed how a propeller has higher efficiency peaks when it operates at high rotational speed due to the higher Reynolds at which airfoils present lower drag. On the other hand, the behavior of the current consumption related to the propulsive efficiency shows counterintuitive results, the best range and endurance is not necessary achieved in an efficiency peak.

Keywords: BEM, blade design, CFD, electric aircraft, endurance, optimization, range

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Authors: B. E. Narkhede, S. K. Mahajan, B. T. Patil, R. D. Raut

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Information quality is a major performance measure for an Enterprise Resource Planning (ERP) system of any firm. This study identifies various critical success factors of information quality. The effect of various critical success factors like project management, reengineering efforts and interdepartmental communications on information quality is analyzed using a multiple regression model. Here quantitative data are collected from respondents from various firms through structured questionnaire for assessment of the information quality, project management, reengineering efforts and interdepartmental communications. The validity and reliability of the data are ensured using techniques like factor analysis, computing of Cronbach’s alpha. This study gives relative importance of each of the critical success factors. The findings suggest that among the various factors influencing information quality careful reengineering efforts are the most influencing factor. This paper gives clear insight to managers and practitioners regarding the relative importance of critical success factors influencing information quality so that they can formulate a strategy at the beginning of ERP system implementation.

Keywords: Enterprise Resource Planning (ERP), information systems (IS), multiple regression, information quality

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Authors: Amruta Rout, Golak Bihari Mahanta, Gunji Bala Murali, Bibhuti Bhusan Biswal, B. B. V. L. Deepak

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The use of industrial robots for performing welding operation is one of the chief sign of contemporary welding in these days. The weld joint parameter and weld process parameter modeling is one of the most crucial aspects of robotic welding. As weld process parameters affect the weld joint parameters differently, a multi-objective optimization technique has to be utilized to obtain optimal setting of weld process parameter. In this paper, a hybrid optimization technique, i.e., Principal Component Analysis (PCA) combined with fuzzy logic has been proposed to get optimal setting of weld process parameters like wire feed rate, welding current. Gas flow rate, welding speed and nozzle tip to plate distance. The weld joint parameters considered for optimization are the depth of penetration, yield strength, and ultimate strength. PCA is a very efficient multi-objective technique for converting the correlated and dependent parameters into uncorrelated and independent variables like the weld joint parameters. Also in this approach, no need for checking the correlation among responses as no individual weight has been assigned to responses. Fuzzy Inference Engine can efficiently consider these aspects into an internal hierarchy of it thereby overcoming various limitations of existing optimization approaches. At last Taguchi method is used to get the optimal setting of weld process parameters. Therefore, it has been concluded the hybrid technique has its own advantages which can be used for quality improvement in industrial applications.

Keywords: robotic arc welding, weld process parameters, weld joint parameters, principal component analysis, fuzzy logic, Taguchi method

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Authors: Wen-Bao Qiao, Jean-Charles Créput

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To accelerate the solution for large scale traveling salesman problems (TSP), a parallel 2-opt local search algorithm with simple implementation based on Graphics Processing Unit (GPU) is presented and tested in this paper. The parallel scheme is based on technique of data decomposition by dynamically assigning multiple K processors on the integral tour to treat K edges’ 2-opt local optimization simultaneously on independent sub-tours, where K can be user-defined or have a function relationship with input size N. We implement this algorithm with doubly linked list on GPU. The implementation only requires O(N) memory. We compare this parallel 2-opt local optimization against sequential exhaustive 2-opt search along integral tour on TSP instances from TSPLIB with more than 10000 cities.

Keywords: parallel 2-opt, double links, large scale TSP, GPU

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Authors: Anastasia Sorokina

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Self-reported language proficiency measures have been widely used by researchers and have been proven to be an accurate tool to assess actual language proficiency. L1 attrition researchers also rely on self-reported measures. More specifically, can-do-scales has gained popularity in the discipline of L1 attrition research. The can-do-scales usually contain statements about language (e.g., “I can write e-mails”); participants are asked to rate each statement on a scale from 1 (I cannot do it at all) to 5 (I can do it without any difficulties). Despite its popularity, no studies have examined can-do-scales’ reliability at measuring the actual level of L1 attrition. Do can-do-scales positively correlate with lexical diversity, syntactic complexity, and fluency? The present study analyzed speech samples of 35 Russian-English attriters to examine whether their self-reported proficiency correlates with their actual L1 proficiency. The results of Pearson correlation demonstrated that can-do-scales correlated with lexical diversity, syntactic complexity, and fluency. These findings provide a valuable contribution to the L1 attrition research by demonstrating that can-do-scales can be used as a reliable tool to measure L1 attrition.

Keywords: L1 attrition, can-do-scales, lexical diversity, syntactic complexity

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Authors: Pushpendra S. Bharti, S. Maheshwari

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Electric discharge machining (EDM) is one of the most widely used non-conventional manufacturing process to shape difficult-to-cut materials. The process yield, in terms of material removal rate, surface roughness and tool wear rate, of EDM may considerably be improved by selecting the optimal combination(s) of process parameters. This paper employs Multi-response signal-to-noise (MRSN) ratio technique to find the optimal combination(s) of the process parameters during EDM of Inconel 718. Three cases v.i.z. high cutting efficiency, high surface finish, and normal machining have been taken and the optimal combinations of input parameters have been obtained for each case. Analysis of variance (ANOVA) has been employed to find the dominant parameter(s) in all three cases. The experimental verification of the obtained results has also been made. MRSN ratio technique found to be a simple and effective multi-objective optimization technique.

Keywords: electric discharge machining, material removal rate, surface roughness, too wear rate, multi-response signal-to-noise ratio, multi response signal-to-noise ratio, optimization

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Authors: S. M. Javad Davoodi, Mojtaba Shourian

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Groundwater table close to the ground surface causes major problems in construction and mining operation. One of the methods to control groundwater in such cases is using pumping wells. These pumping wells remove excess water from the site project and lower the water table to a desirable value. Although the efficiency of this method is acceptable, it needs high expenses to apply. It means even small improvement in a design of pumping wells can lead to substantial cost savings. In order to minimize the total cost in the method of pumping wells, a simulation-optimization approach is applied. The proposed model integrates MODFLOW as the simulation model with Firefly as the optimization algorithm. In fact, MODFLOW computes the drawdown due to pumping in an aquifer and the Firefly algorithm defines the optimum value of design parameters which are numbers, pumping rates and layout of the designing wells. The developed Firefly-MODFLOW model is applied to minimize the cost of the dewatering project for the ancient mosque of Kerman city in Iran. Repetitive runs of the Firefly-MODFLOW model indicates that drilling two wells with the total rate of pumping 5503 m3/day is the result of the minimization problem. Results show that implementing the proposed solution leads to at least 1.5 m drawdown in the aquifer beneath mosque region. Also, the subsidence due to groundwater depletion is less than 80 mm. Sensitivity analyses indicate that desirable groundwater depletion has an enormous impact on total cost of the project. Besides, in a hypothetical aquifer decreasing the hydraulic conductivity contributes to decrease in total water extraction for dewatering.

Keywords: groundwater dewatering, pumping wells, simulation-optimization, MODFLOW, firefly algorithm

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Authors: Bingxi Huang, Yiqing Li, Marek Morzynski, Bernd R. Noack

Abstract:

We propose a Kriging-based global optimization method for active flow control with multiple actuation parameters. This method is designed to converge quickly and avoid getting trapped into local minima. We follow the model-free explorative gradient method (EGM) to alternate between explorative and exploitive steps. This facilitates a convergence similar to a gradient-based method and the parallel exploration of potentially better minima. In contrast to EGM, both kinds of steps are performed with Kriging surrogate model from the available data. The explorative step maximizes the expected improvement, i.e., favors regions of large uncertainty. The exploitive step identifies the best location of the cost function from the Kriging surrogate model for a subsequent weight-biased linear-gradient descent search method. To verify the effectiveness and robustness of the improved Kriging-based optimization method, we have examined several comparative test problems of varying dimensions with limited evaluation budgets. The results show that the proposed algorithm significantly outperforms some model-free optimization algorithms like genetic algorithm and differential evolution algorithm with a quicker convergence for a given budget. We have also performed direct numerical simulations of the fluidic pinball (N. Deng et al. 2020 J. Fluid Mech.) on three circular cylinders in equilateral-triangular arrangement immersed in an incoming flow at Re=100. The optimal cylinder rotations lead to 44.0% net drag power saving with 85.8% drag reduction and 41.8% actuation power. The optimal results for active flow control based on this configuration have achieved boat-tailing mechanism by employing Coanda forcing and wake stabilization by delaying separation and minimizing the wake region.

Keywords: direct numerical simulations, flow control, kriging, stochastic optimization, wake stabilization

Procedia PDF Downloads 106

Authors: Chua Bee Seok, Getrude Cosmas, Jasmine Adela Mutang, Shazia Iqbal Hashmi

Abstract:

The aims of this study were to determine the factor structure and psychometric properties (i.e., reliability and convergent validity) of the employees trust scale, a newly created instrument by the researchers. The employees trust scale initially contained 82 items to measure employee’s trust toward their supervisors. A sample of 818 (343 females, 449 males) employees were selected randomly from public and private organization sectors in Kota Kinabalu, Sabah, Malaysia. Their ages ranged from 19 to 67 years old with the mean of 34.55 years old. Their average tenure with their current employer was 11.2 years (s.d. = 7.5 years). The respondents were asked to complete the employees trust scale, as well as a managerial trust questionnaire from Mishra. The exploratory factor analysis on employee’s trust toward their supervisor’s extracted three factors, labeled 'trustworthiness' (32 items), 'position status' (11 items) and 'relationship' (6 items) which accounted for 62.49% of the total variance. Trustworthiness factors were re-categorized into three sub factors: competency (11 items), benevolence (8 items) and integrity (13 items). All factors and sub factors of the scales demonstrated clear reliability with internal consistency of Cronbach’s Alpha above 0.85. The convergent validity of the Scale was supported by an expected pattern of correlations (positive and significant correlation) between the score of all factors and sub factors of the scale and the score on the managerial trust questionnaire which measured the same construct. The convergent validity of employees trust scale was further supported by the significant and positive inter correlation between the factors and sub factors of the scale. The results suggest that the employees trust scale is a reliable and valid measure. However, further studies need to be carried out in other groups of sample as to further validate the Scale.

Keywords: employees trust scale, psychometric properties, trustworthiness, position status, relationship

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Authors: Dimeji Abe, Nonso Okoye, Gideon Ikpimi, Prince Idemudia

Abstract:

Multi-reservoir optimization operation has been a critical issue for river basin management. Water, as a scarce resource, is in high demand and the problems associated with the reservoir as its storage facility are enormous. The complexity in balancing the supply and demand of this prime resource has created the need to examine the best way to solve the problem using optimization techniques. The objective of this study is to evaluate the performance of the multi-objective meta-heuristic algorithm for the operation of Gariep Dam for satisfying ecological flow requirements. This study uses an evolutionary algorithm called backtrack search algorithm (BSA) to determine the best way to optimise the dam operations of hydropower production, flood control, and water supply without affecting the environmental flow requirement for the survival of aquatic bodies and sustain life downstream of the dam. To achieve this objective, the operations of the dam that corresponds to different tradeoffs between the objectives are optimized. The results indicate the best model from the algorithm that satisfies all the objectives without any constraint violation. It is expected that hydropower generation will be improved and more water will be available for ecological flow requirements with the use of the algorithm. This algorithm also provides farmers with more irrigation water as well to improve their business.

Keywords: BSA evolutionary algorithm, metaheuristics, optimization, river basin management

Procedia PDF Downloads 245

Authors: Parampal Kaur, Deepak Aggarwal

Abstract:

In the computational Grid, fault tolerance is an imperative issue to be considered during job scheduling. Due to the widespread use of resources, systems are highly prone to errors and failures. Hence, fault tolerance plays a key role in the grid to avoid the problem of unreliability. Scheduling the task to the appropriate resource is a vital requirement in computational Grid. The fittest resource scheduling algorithm searches for the appropriate resource based on the job requirements, in contrary to the general scheduling algorithms where jobs are scheduled to the resources with best performance factor. The proposed method is to improve the fault tolerance of the fittest resource scheduling algorithm by scheduling the job in coordination with job replication when the resource has low reliability. Based on the reliability index of the resource, the resource is identified as critical. The tasks are scheduled based on the criticality of the resources. Results show that the execution time of the tasks is comparatively reduced with the proposed algorithm using real-time approach rather than a simulator.

Keywords: computational grid, fault tolerance, task replication, job scheduling

Procedia PDF Downloads 436