Search results for: nugget making

Authors: Javid Iqbal, Zhu Shifan

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The development in the construction of unconventional ships and the implementation of lightweight materials have shown a large impulse towards finite element (FE) method, making it a general tool for ship design. This paper briefly presents the modeling and analysis techniques of ship structures using FE method for complex boundary conditions which are difficult to analyze by existing Ship Classification Societies rules. During operation, all ships experience complex loading conditions. These loads are general categories into thermal loads, linear static, dynamic and non-linear loads. General strength of the ship structure is analyzed using static FE analysis. FE method is also suitable to consider the local loads generated by ballast tanks and cargo in addition to hydrostatic and hydrodynamic loads. Vibration analysis of a ship structure and its components can be performed using FE method which helps in obtaining the dynamic stability of the ship. FE method has developed better techniques for calculation of natural frequencies and different mode shapes of ship structure to avoid resonance both globally and locally. There is a lot of development towards the ideal design in ship industry over the past few years for solving complex engineering problems by employing the data stored in the FE model. This paper provides an overview of ship modeling methodology for FE analysis and its general application. Historical background, the basic concept of FE, advantages, and disadvantages of FE analysis are also reported along with examples related to hull strength and structural components.

Keywords: Dynamic analysis, finite element methods, ship structure, vibration analysis.

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Authors: Matheus Borges Carneiro, Fabiane Letícia Lizarelli, José Carlos de Toledo

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The evolution of quality management by companies was strongly enabled by, among others, ISO 9001 certification, which is considered a crucial requirement for several customers. Likewise, performance measurement provides useful insights for companies to identify the reflection of their decision-making process on their improvement. One of the most used performance measurement models is the balanced scorecard (BSC), which uses four perspectives to address a firm’s performance: financial, internal process, customer satisfaction, and learning and growth. Since ISO 9001 certified firms are likely to measure their performance through BSC approach, it is important to verify whether the certificate influences the firm performance or not. Therefore, this paper aims to verify the impact of ISO 9001:2015 on Brazilian firms’ performance based on the BSC perspective. Hence, nine certified companies located in the Southeast region of Brazil were studied through a multiple case study approach. Within this study, it was possible to identify the positive impact of ISO 9001 on firms’ overall performance, and four Critical Success Factors (CSFs) were identified as relevant on the linkage among ISO 9001 and firms’ performance: employee involvement, top management, process management, and customer focus. Due to the COVID-19 pandemic, the number of interviews was limited to the quality manager specialist, and the sample was limited since several companies were closed during the period of the study. This study presents an in-depth analysis of how the relationship between ISO 9001 certification and firms’ performance in a developing country is.

Keywords: Balanced scorecard, Brazilian firms’ performance, critical success factors, ISO 9001 certification, performance measurement.

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Authors: A. Idawaty, O. Mohamed, A. Z. Zuriati

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This paper presents the development of an event based Discrete Event Simulation (DES) for a recovery algorithm known Backward Recovery Global Preemptive Utility Accrual Scheduling (BR_GPUAS). This algorithm implements the Backward Recovery (BR) mechanism as a fault recovery solution under the existing Time/Utility Function/ Utility Accrual (TUF/UA) scheduling domain for multiprocessor environment. The BR mechanism attempts to take the faulty tasks back to its initial safe state and then proceeds to re-execute the affected section of the faulty tasks to enable recovery. Considering that faults may occur in the components of any system; a fault tolerance system that can nullify the erroneous effect is necessary to be developed. Current TUF/UA scheduling algorithm uses the abortion recovery mechanism and it simply aborts the erroneous task as their fault recovery solution. None of the existing algorithm in TUF/UA scheduling domain in multiprocessor scheduling environment have considered the transient fault and implement the BR mechanism as a fault recovery mechanism to nullify the erroneous effect and solve the recovery problem in this domain. The developed BR_GPUAS simulator has derived the set of parameter, events and performance metrics according to a detailed analysis of the base model. Simulation results revealed that BR_GPUAS algorithm can saved almost 20-30% of the accumulated utilities making it reliable and efficient for the real-time application in the multiprocessor scheduling environment.

Keywords: Time Utility Function/ Utility Accrual (TUF/UA) scheduling, Real-time system (RTS), Backward Recovery, Multiprocessor, Discrete Event Simulation (DES).

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Authors: Yi-Feng Su, Chia-Tseng Chen, Hsueh-Lung Liao

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The objective of this research is to develop an advanced driver assistance system characterized with the functions of lane departure warning (LDW), forward collision warning (FCW) and adaptive front-lighting system (AFS). The system is mainly configured a CCD/CMOS camera to acquire the images of roadway ahead in association with the analysis made by an image-processing unit concerning the lane ahead and the preceding vehicles. The input image captured by a camera is used to recognize the lane and the preceding vehicle positions by image detection and DROI (Dynamic Range of Interesting) algorithms. Therefore, the system is able to issue real-time auditory and visual outputs of warning when a driver is departing the lane or driving too close to approach the preceding vehicle unwittingly so that the danger could be prevented from occurring. During the nighttime, in addition to the foregoing warning functions, the system is able to control the bending light of headlamp to provide an immediate light illumination when making a turn at a curved lane and adjust the level automatically to reduce the lighting interference against the oncoming vehicles driving in the opposite direction by the curvature of lane and the vanishing point estimations. The experimental results show that the integrated vehicle image system is robust to most environments such as the lane detection and preceding vehicle detection average accuracy performances are both above 90 %.

Keywords: Lane mark detection, lane departure warning (LDW), dynamic range of interesting (DROI), forward collision warning (FCW), adaptive front-lighting system (AFS).

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Authors: Phusit Phukamchanoad

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This study aimed to analyse the application of sufficiency economy in students’ ways of life on campus at Suan Sunandha Rajabhat University. Data was gathered through 394 questionnaires. The study results found that the majority of students were confident that “where there’s a will, there’s a way.” Overall, the students applied the sufficiency economy at a great level, along with being persons who do not exploit others, were satisfied with living their lives moderately, according to the sufficiency economy. Importance was also given to kindness and generosity. Importantly, students were happy with living according to their individual circumstances and status at the present. They saw the importance of joint life planning, self-development, and self-dependence, always learning to be satisfied with “adequate”. As for their practices and ways of life, socially relational activities rated highly, especially initiation activities for underclassmen at the university and the seniority system, which are suitable for activities on campus. Furthermore, the students knew how to build a career and find supplemental income, knew how to earnestly work according to convention to finish work, and preferred to study elective subjects which directly benefit career-wise. The students’ application of sufficiency economy philosophy principles depended on their lives in their hometowns. The students from the provinces regularly applied sufficiency economy philosophy to their lives, for example, by being frugal, steadfast, determined, avoiding negligence, and making economical spending plans; more so than the students from the capital.

Keywords: Application of Sufficiency Economy Philosophy, Way of Living, Undergraduate Students.

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Authors: Chee-Ming Chan

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In spite of the advent of new materials, clay bricks remain, arguably, the most popular construction materials today. Nevertheless the low cost and versatility of clay bricks cannot always be associated with high environmental and sustainable values, especially in terms of raw material sources and manufacturing processes. At the same time, the worldwide agricultural footprint is fast growing, with vast agricultural land cultivation and active expansion of the agro-based industry. The resulting large quantities of agricultural wastes, unfortunately, are not always well managed or utilised. These wastes can be recycled, such as by retrieving fibres from disposed leaves and fruit bunches, and then incorporated in brick-making. This way the clay bricks are made a 'greener' building material and the discarded natural wastes can be reutilised, avoiding otherwise wasteful landfill and harmful open incineration. This study examined the physical and mechanical properties of clay bricks made by adding two natural fibres to a clay-water mixture, with baked and non-baked conditions. The fibres were sourced from pineapple leaves (PF) and oil palm fruit bunch (OF), and added within the range of 0.25-0.75 %. Cement was added as a binder to the mixture at 5-15 %. Although the two fibres had different effects on the bricks produced, cement appeared to dominate the compressive strength. The non-baked bricks disintegrated when submerged in water, while the baked ones displayed cement-dependent characteristics in water-absorption and density changes. Interestingly, further increase in fibre content did not cause significant density decrease in both the baked and non-baked bricks.

Keywords: natural fibres, clay bricks, strength, water absorption, density.

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Authors: Ibrahim A. Al-Sulaihi, Khalid S. Al-Gahtani, Abdullah M. Al-Sugair, Aref A. Abadel

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Achieving environmental sustainability is one of the important issues considered in many countries’ vision. Green/Sustainable building is widely used terminology for describing a friendly environmental construction. Applying sustainable practices has a significant importance in various fields, including construction field that consumes an enormous amount of resource and causes a considerable amount of waste. The need for sustainability is increased in the regions that suffering from the limitation of natural resource and extreme weather conditions such as Saudi Arabia. Since buildings designs are getting sophisticated, the need for tools, which support decision-making for sustainability issues, is increasing, especially in the design and preconstruction stages. In this context, Building Information Modeling (BIM) can aid in performing complex building performance analyses to ensure an optimized sustainable building design. Accordingly, this paper introduces a roadmap towards developing a systematic approach for presenting the sustainability of buildings using BIM. The approach includes set of main processes including; identifying the sustainability parameters that can be used for sustainability assessment in Saudi Arabia, developing sustainability assessment method that fits the special circumstances in the Kingdom, identifying the sustainability requirements and BIM functions that can be used for satisfying these requirements, and integrating these requirements with identified functions. As a result, the sustainability-BIM approach can be developed which helps designers in assessing the sustainability and exploring different design alternatives at the early stage of the construction project.

Keywords: Green buildings, sustainability, BIM, rating systems, environment, Saudi Arabia.

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Authors: Angela–M. Paleologou, Aphrodite Dellaporta

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Erroneous computer entry problems [here: 'e'errors] in hospital labs threaten the patients-–health carers- relationship, undermining the health system credibility. Are e-errors random, and do lab professionals make them accidentally, or may they be traced through meaningful determinants? Theories on internal causality of mistakes compel to seek specific causal ascriptions of hospital lab eerrors instead of accepting some inescapability. Undeniably, 'To Err is Human'. But in view of rapid global health organizational changes, e-errors are too expensive to lack in-depth considerations. Yet, that efunction might supposedly be entrenched in the health carers- job description remains under dispute – at least for Hellenic labs, where e-use falls behind generalized(able) appreciation and application. In this study: i) an empirical basis of a truly high annual cost of e-errors at about €498,000.00 per rural Hellenic hospital was established, hence interest in exploring the issue was sufficiently substantiated; ii) a sample of 270 lab-expert nurses, technicians and doctors were assessed on several personality, burnout and e-error measures, and iii) the hypothesis that the Hardiness vs Alienation personality construct disposition explains resistance vs proclivity to e-errors was tested and verified: Hardiness operates as a resilience source in the encounter of high pressures experienced in the hospital lab, whereas its 'opposite', i.e., Alienation, functions as a predictor, not only of making e-errors, but also of leading to burn-out. Implications for apt interventions are discussed.

Keywords: Hospital lab, personality hardiness/alienation, e-errors' cost, burnout.

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Authors: Mojisola F. Oyewole, Franscisca T. Adetoro, Nkiru T. Meludu

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Moringa oleifera is a nutritious vegetable tree with varieties of potential uses, as almost every part of the Moringa oleifera tree can be used for food. This study was conducted in Oyo State, Nigeria, to find out the level of acceptability of Moringa oleifera diversified products among rural and urban dwellers. Purposive sampling was used to select two local governments’ areas. Stratified sampling technique was also used to select one community each from rural and urban areas while snowball sampling technique was used to select ten respondents each from the two communities, making a total number of forty respondents. Data were analyzed using frequencies, percentages, Chi-square, Pearson Product Moment Correlation and regression analysis. Result from the study revealed that majority of the respondents (80%) fell within the age range of 20-49 years and 55% of them were male, 55% were married, 70% of them were Christians, 80% of them had tertiary education. The result also showed that 85% were aware of the Moringa plant and (65%) of them have consumed Moringa oleifera and the perception statements on the benefits of Moringa oleifera indicated that (52.5%) of the respondents rated Moringa oleifera to be favorable, most of them had high acceptability for Moringa egusi soup, Moringa tea, Moringa pap and yam pottage with Moringa. The result of the hypotheses testing showed that there is a significant relationship between sex of the respondents and acceptability of the diversified Moringa oleifera products (x2=6.465, p = 0.011). There is also a significant relationship between family size of the respondents level of acceptability of the Moringa oleifera products (r = 0.327, p = 0.040). Based on the level of acceptability of Moringa oleifera diversified products; the plant is of great economic importance to the populace. Therefore, there should be more public awareness through the media to enlighten people on the beneficial effects of Moringa oleifera.

Keywords: Acceptability, Moringa oleifera, Diversified, Product, Dwellers.

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Authors: Wafa Ghonaim

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Though quite fast on growth, Islamic financing at large, and its diverse instruments, is a controversial matter among scholars. This is evident from the ongoing debates on its Shariah compliance. Arguments, however, are inciting doubts and concerns among clients about its credibility, which is harming this lucrative sector. The work here investigates, particularly, some issues related to the Tawarruq instrument. The work examines the issues of linking Murabaha and Wakala contracts, the reselling of commodities to same traders, and the transfer of ownerships. The work affirms that a multi-agent smart electronic market design would facilitate Shariah compliance. The smart market exploits the rational decision-making capabilities of autonomous proxy agents that enable the clients, traders, brokers, and the bank buy and sell commodities, and manage transactions and cash flow. The smart electronic market design delivers desirable qualities that terminate the need for Wakala contracts and the reselling of commodities to the same traders. It also resolves the ownership transfer issues by allowing stakeholders to trade independently. The bank administers the smart electronic market and assures reliability of trades, transactions and cash flow. A multi-agent simulation is presented to validate the concept and processes. We anticipate that the multi-agent smart electronic market design would deliver Shariah compliance of personal financing to the aspiration of scholars, banks, traders and potential clients.

Keywords: Islamic finance, Shariah compliance, smart electronic markets design, multi-agent systems.

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Authors: Suttipong Boonphadung

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The research on ARCS for critical information retrieval development aimed to (1) investigate conditions of critical information retrieval skill of the Mathematics pre-service teachers before applying ARCS model in learning activities, (2) study and analyze the development of critical information retrieval skill of the Mathematics pre-service teachers after utilizing ARCS model in learning activities, and (3) evaluate the Mathematics pre-service teachers’ satisfaction on using ARCS model in learning activities as a tool to development critical information retrieval skill. Forty-one of 4th year Mathematics pre-service teachers who have enrolled in the subject of Research for Learning Development of semester 2 in 2012 were purposively selected as the research cohort. The research tools were self-report and interview questionnaire that was approved as content validity and reliability (IOC=.66-1.00, α =.834). The research found that critical information retrieval skill of the research samples before using ARCS model in learning activities was in the normal high level. According to the in-depth interview and focus group, the result however showed that the pre-service teachers still lack inadequate and effective knowledge in information retrieval. Additionally, critical information retrieval skill of the research cohort after applying ARCS model in learning activities appeared to be high level. The result revealed that the pre-service teachers are able to explain the method of searching, extraction, and selecting information as well as evaluating quality of information, and effectively making decision in accepting information. Moreover, the research discovered that the pre-service teachers showed normal high to highest level of satisfaction on using ARCS model in learning activities as a tool to development their critical information retrieval skill.

Keywords: Critical information retrieval skill, ARCS model, Satisfaction.

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Authors: Ichiro Mukai

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The purpose of this study is to investigate whether firms applying International Financial Reporting Standards (IFRS), provide high-quality and comparable earnings information that is useful for decision making of information users relative to firms applying local Generally Accepted Accounting Principles (GAAP). Focus is placed on the earnings quality of listed firms in several developed countries: Australia, Canada, France, Germany, Japan, the United Kingdom (UK), and the United States (US). Except for Japan and the US, the adoption of IFRS is mandatory for listed firms in these countries. In Japan, the application of IFRS is allowed for specific listed firms. In the US, the foreign firms listed on the US securities market are permitted to apply IFRS but the listed domestic firms are prohibited from doing so. In this paper, the differences in earnings quality are compared between firms applying local GAAP and those applying IFRS in each country and industry category, and the reasons of differences in earnings quality are analyzed using various factors. The results show that, although the earnings quality of firms applying IFRS is higher than that of firms applying local GAAP, this varies with country and industry category. Thus, even if a single set of global accounting standards is used for all listed firms worldwide, it is difficult to establish comparability of financial information among global firms. These findings imply that various circumstances surrounding firms, industries, and countries etc. influence business operations and affect the differences in earnings quality.

Keywords: Accruals, earnings quality, IFRS, information comparability.

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Authors: E. Soboleva, E. Sergachyova, S. G. Davydenko, T. V. Meledina

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Problem of food preservation is extremely important for mankind. Viscous damage ("illness") of bread results from development of Bacillus spp. bacteria. High temperature resistant spores of this microorganism are steady against 120°C) and remain in bread during pastries, potentially causing spoilage of the final product. Scientists are interested in further characterization of bread spoiling Bacillus spp. species. Our aim was to find weather yeast Saccharomyces cerevisiae strains that are able to produce natural antimicrobial killer factor can preserve bread illness. By diffusion method, we showed yeast antagonistic activity against spore-forming bacteria. Experimental technological parameters were the same as for bakers' yeasts production on the industrial scale. Risograph test during dough fermentation demonstrated gas production. The major finding of the study was a clear indication of the presence of killer yeast strain antagonistic activity against rope in bread causing bacteria. After demonstrating antagonistic effect of S. cerevisiae on bacteria using solid nutrient medium, we tested baked bread under provocative conditions. We also measured formation of carbon dioxide in the dough, dough-making duration and quality of the final products, when using different strains of S. cerevisiae. It is determined that the use of yeast S. cerevisiae RCAM 01730 killer strain inhibits appearance of rope in bread. Thus, natural yeast antimicrobial killer toxin, produced by some S. cerevisiae strains is an anti-rope in bread protector.

Keywords: Bakers' yeasts, rope in bread, Saccharomyces cerevisiae.

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

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As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling. The research proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling. The paper concludes the challenges and improvement directions for Deep Reinforcement Learning-based resource scheduling algorithms.

Keywords: Resource scheduling, deep reinforcement learning, distributed system, artificial intelligence.

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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: Othman Maklouf, Abdurazag Ghila, Ahmed Abdulla, Ameer Yousef

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Land vehicle navigation system technology is a subject of great interest today. Global Positioning System (GPS) is a common choice for positioning in such systems. However, GPS alone is incapable of providing continuous and reliable positioning, because of its inherent dependency on external electromagnetic signals. Inertial Navigation is the implementation of inertial sensors to determine the position and orientation of a vehicle. As such, inertial navigation has unbounded error growth since the error accumulates at each step. Thus in order to contain these errors some form of external aiding is required. The availability of low cost Micro-Electro-Mechanical-System (MEMS) inertial sensors is now making it feasible to develop Inertial Navigation System (INS) using an inertial measurement unit (IMU), in conjunction with GPS to fulfill the demands of such systems. Typically IMU’s are very expensive systems; however this INS will use “low cost” components. Unfortunately with low cost also comes low performance and is the main reason for the inclusion of GPS and Kalman filtering into the system. The aim of this paper is to develop a GPS/MEMS INS integrated system, which is able to provide a navigation solution with accuracy levels appropriate for land vehicle navigation. The primary piece of equipment used was a MEMS-based Crista IMU (from Cloud Cap Technology Inc.) and a Garmin GPS 18 PC (which is both a receiver and antenna). The integration of GPS with INS can be implemented using a Kalman filter in loosely coupled mode. In this integration mode the INS error states, together with any navigation state (position, velocity, and attitude) and other unknown parameters of interest, are estimated using GPS measurements. All important equations regarding navigation are presented along with discussion.

Keywords: GPS, IMU, Kalman Filter.

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Authors: A. Badoud, M. Khemliche, S. Latreche

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The main objective developed in this paper is to find a graphic technique for modeling, simulation and diagnosis of the industrial systems. This importance is much apparent when it is about a complex system such as the nuclear reactor with pressurized water of several form with various several non-linearity and time scales. In this case the analytical approach is heavy and does not give a fast idea on the evolution of the system. The tool Bond Graph enabled us to transform the analytical model into graphic model and the software of simulation SYMBOLS 2000 specific to the Bond Graphs made it possible to validate and have the results given by the technical specifications. We introduce the analysis of the problem involved in the faults localization and identification in the complex industrial processes. We propose a method of fault detection applied to the diagnosis and to determine the gravity of a detected fault. We show the possibilities of application of the new diagnosis approaches to the complex system control. The industrial systems became increasingly complex with the faults diagnosis procedures in the physical systems prove to become very complex as soon as the systems considered are not elementary any more. Indeed, in front of this complexity, we chose to make recourse to Fault Detection and Isolation method (FDI) by the analysis of the problem of its control and to conceive a reliable system of diagnosis making it possible to apprehend the complex dynamic systems spatially distributed applied to the standard pressurized water nuclear reactor.

Keywords: Bond Graph, Modeling, Simulation, Monitoring, Analytical Redundancy Relations, Pressurized Water Reactor, Directed Graph.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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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: Sahar S. Tabrizi, Dogan Ibrahim

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Cloud Computing is a convenient model for on-demand networks that uses shared pools of virtual configurable computing resources, such as servers, networks, storage devices, applications, etc. The cloud serves as an environment for companies and organizations to use infrastructure resources without making any purchases and they can access such resources wherever and whenever they need. Cloud computing is useful to overcome a number of problems in various Information Technology (IT) domains such as Geographical Information Systems (GIS), Scientific Research, e-Governance Systems, Decision Support Systems, ERP, Web Application Development, Mobile Technology, etc. Companies can use Cloud Computing services to store large amounts of data that can be accessed from anywhere on Earth and also at any time. Such services are rented by the client companies where the actual rent depends upon the amount of data stored on the cloud and also the amount of processing power used in a given time period. The resources offered by the cloud service companies are flexible in the sense that the user companies can increase or decrease their storage requirements or the processing power requirements at any time, thus minimizing the overall rental cost of the service they receive. In addition, the Cloud Computing service providers offer fast processors and applications software that can be shared by their clients. This is especially important for small companies with limited budgets which cannot afford to purchase their own expensive hardware and software. This paper is an overview of the Cloud Computing, giving its types, principles, advantages, and disadvantages. In addition, the paper gives some example engineering applications of Cloud Computing and makes suggestions for possible future applications in the field of engineering.

Keywords: Cloud computing, cloud services, IaaS, PaaS, SaaS, IoT.

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Authors: Toshifumi Hiramatsu, Satoshi Morita, Manuel Pencelli, Marta Niccolini, Matteo Ragaglia, Alfredo Argiolas

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Automation technologies for agriculture field are needed to promote labor-saving. One of the most relevant problems in automated agriculture is represented by controlling the robot along a predetermined path in presence of rough terrain or incline ground. Unfortunately, disturbances originating from interaction with the ground, such as slipping, make it quite difficult to achieve the required accuracy. In general, it is required to move within 5-10 cm accuracy with respect to the predetermined path. Moreover, lateral velocity caused by gravity on the incline field also affects slipping. In this paper, a path-tracking controller for tracked mobile robots moving on rough terrains of incline field such as vineyard is presented. The controller is composed of a disturbance observer and an adaptive controller based on the kinematic model of the robot. The disturbance observer measures the difference between the measured and the reference yaw rate and linear velocity in order to estimate slip. Then, the adaptive controller adapts “virtual” parameter of the kinematics model: Instantaneous Centers of Rotation (ICRs). Finally, target angular velocity reference is computed according to the adapted parameter. This solution allows estimating the effects of slip without making the model too complex. Finally, the effectiveness of the proposed solution is tested in a simulation environment.

Keywords: Agricultural robot, autonomous control, path-tracking control, tracked mobile robot.

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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: M. Aghili, S. Tabarestani, C. Freytes, M. Shojaie, M. Cabrerizo, A. Barreto, N. Rishe, R. E. Curiel, D. Loewenstein, R. Duara, M. Adjouadi

Abstract:

A major challenge in medical studies, especially those that are longitudinal, is the problem of missing measurements which hinders the effective application of many machine learning algorithms. Furthermore, recent Alzheimer's Disease studies have focused on the delineation of Early Mild Cognitive Impairment (EMCI) and Late Mild Cognitive Impairment (LMCI) from cognitively normal controls (CN) which is essential for developing effective and early treatment methods. To address the aforementioned challenges, this paper explores the potential of using the eXtreme Gradient Boosting (XGBoost) algorithm in handling missing values in multiclass classification. We seek a generalized classification scheme where all prodromal stages of the disease are considered simultaneously in the classification and decision-making processes. Given the large number of subjects (1631) included in this study and in the presence of almost 28% missing values, we investigated the performance of XGBoost on the classification of the four classes of AD, NC, EMCI, and LMCI. Using 10-fold cross validation technique, XGBoost is shown to outperform other state-of-the-art classification algorithms by 3% in terms of accuracy and F-score. Our model achieved an accuracy of 80.52%, a precision of 80.62% and recall of 80.51%, supporting the more natural and promising multiclass classification.

Keywords: eXtreme Gradient Boosting, missing data, Alzheimer disease, early mild cognitive impairment, late mild cognitive impairment, multiclass classification, ADNI, support vector machine, random forest.

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Authors: D. Nouri, M.R. Sabour, M. Ghanbarzadeh Lak

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Proper management of residues originated from industrial activities is considered as one of the serious challenges faced by industrial societies due to their potential hazards to the environment. Common disposal methods for industrial solid wastes (ISWs) encompass various combinations of solely management options, i.e. recycling, incineration, composting, and sanitary landfilling. Indeed, the procedure used to evaluate and nominate the best practical methods should be based on environmental, technical, economical, and social assessments. In this paper an environmentaltechnical assessment model is developed using analytical network process (ANP) to facilitate the decision making practice for ISWs generated at Gilan province, Iran. Using the results of performed surveys on industrial units located at Gilan, the various groups of solid wastes in the research area were characterized, and four different ISW management scenarios were studied. The evaluation process was conducted using the above-mentioned model in the Super Decisions software (version 2.0.8) environment. The results indicates that the best ISW management scenario for Gilan province is consist of recycling the metal industries residues, composting the putrescible portion of ISWs, combustion of paper, wood, fabric and polymeric wastes as well as energy extraction in the incineration plant, and finally landfilling the rest of the waste stream in addition with rejected materials from recycling and compost production plants and ashes from the incineration unit.

Keywords: Analytical Network Process, Disposal Scenario, Gilan Province, Industrial Waste.

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Authors: Charawee Butbumrung

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This paper aimed to study the factors that relate to working behavior of employees at Pakkred Municipality, Nonthaburi Province. A questionnaire was utilized as the tool in collecting information. Descriptive statistics included frequency, percentage, mean and standard deviation. Independent- sample t- test, analysis of variance and Pearson Correlation were also used. The findings of this research revealed that the majority of the respondents were female, between 25- 35 years old, married, with a Bachelor degree. The average monthly salary of respondents was between 8,001- 12,000 Baht, and having about 4-7 years of working experience. Regarding the overall working motivation factors, the findings showed that interrelationship, respect, and acceptance were ranked as highly important factors, whereas motivation, remunerations & welfare, career growth, and working conditions were ranked as moderately important factors. Also, overall working behavior was ranked as high. The hypotheses testing revealed that different genders had a different working behavior and had a different way of working as a team, which was significant at the 0.05 confidence level, Moreover, there was a difference among employees with different monthly salary in working behavior, problem- solving and decision making, which all were significant at the 0.05 confidence level. Employees with different years of working experience were found to have work working behavior both individual and as a team at the statistical significance level of 0.01 and 0.05. The result of testing the relationship between motivation in overall working revealed that interrelationship, respect and acceptance from others, career growth, and working conditions related to working behavior at a moderate level, while motivation in performing duties and remunerations and welfares related to working behavior towards the same direction at a low level, with a statistical significance of 0.01.

Keywords: Employees of Pakkred Municipality, Factors, Nonthaburi Province, Working Behavior.

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Authors: V Krishnaveni, S Jayaraman, A Gunasekaran, K Ramadoss

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The ElectroEncephaloGram (EEG) is useful for clinical diagnosis and biomedical research. EEG signals often contain strong ElectroOculoGram (EOG) artifacts produced by eye movements and eye blinks especially in EEG recorded from frontal channels. These artifacts obscure the underlying brain activity, making its visual or automated inspection difficult. The goal of ocular artifact removal is to remove ocular artifacts from the recorded EEG, leaving the underlying background signals due to brain activity. In recent times, Independent Component Analysis (ICA) algorithms have demonstrated superior potential in obtaining the least dependent source components. In this paper, the independent components are obtained by using the JADE algorithm (best separating algorithm) and are classified into either artifact component or neural component. Neural Network is used for the classification of the obtained independent components. Neural Network requires input features that exactly represent the true character of the input signals so that the neural network could classify the signals based on those key characters that differentiate between various signals. In this work, Auto Regressive (AR) coefficients are used as the input features for classification. Two neural network approaches are used to learn classification rules from EEG data. First, a Polynomial Neural Network (PNN) trained by GMDH (Group Method of Data Handling) algorithm is used and secondly, feed-forward neural network classifier trained by a standard back-propagation algorithm is used for classification and the results show that JADE-FNN performs better than JADEPNN.

Keywords: Auto Regressive (AR) Coefficients, Feed Forward Neural Network (FNN), Joint Approximation Diagonalisation of Eigen matrices (JADE) Algorithm, Polynomial Neural Network (PNN).

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Authors: P. Luangpaiboon, P. Aungkulanon

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This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.

Keywords: Aggregate Production Planning, Desirability Function Approach, Improved Harmony Search Algorithm, Hunting Search Algorithm and Firefly Algorithm.

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Authors: Ana Paula Esteves, Diego S. Caetano, Louise L. B. Lomardo

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This paper presents an approach to the performance of the natural lighting, when the use of appropriated solar lighting systems on the roof is applied in cultural buildings such as museums and foundations. The roofs, as a part of contact between the building and the external environment, require special attention in projects that aim at energy efficiency, being an important element for the capture of natural light in greater quantity, but also for being the most important point of generation of photovoltaic solar energy, even semitransparent, allowing the partial passage of light. Transparent elements in roofs, as well as superior protection of the building, can also play other roles, such as: meeting the needs of natural light for the accomplishment of the internal tasks, attending to the visual comfort; to bring benefits to the human perception and about the interior experience in a building. When these resources are well dimensioned, they also contribute to the energy efficiency and consequent character of sustainability of the building. Therefore, when properly designed and executed, a roof light system can bring higher quality natural light to the interior of the building, which is related to the human health and well-being dimension. Furthermore, it can meet the technologic, economic and environmental yearnings, making possible the more efficient use of that primordial resource, which is the light of the Sun. The article presents the analysis of buildings that used zenith light systems in search of better lighting performance in museums and foundations: the Solomon R. Guggenheim Museum in the United States, the Iberê Camargo Foundation in Brazil, the Museum of Fine Arts in Castellón in Spain and the Pinacoteca of São Paulo.

Keywords: Natural lighting, roof lighting systems, natural lighting in museums, comfort lighting.

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Authors: Essa Alenazi, Zulfikar Adamu

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The Kingdom of Saudi Arabia (KSA) is not an exception in relying on the growth of its construction industry to support rapid population growth. However, its need for infrastructure development is constrained by low productivity levels and cost overruns caused by factors such as delays to project completion. Delays in delivering a construction project are a global issue and while theories such as Optimism Bias have been used to explain such delays, in KSA, client-related causes of delays are also significant. The objective of this paper is to develop a framework-based approach to explore how the country’s construction industry can manage and reduce delays in construction projects through building information modelling (BIM) in order to mitigate the cost consequences of such delays.  It comprehensively and systematically reviewed the global literature on the subject and identified gaps, critical delay factors and the specific benefits that BIM can deliver for the delay management.  A case study comprising of nine hospital projects that have experienced delay and cost overruns was also carried out. Five critical delay factors related to the clients were identified as candidates that can be mitigated through BIM’s benefits. These factors are: Ineffective planning and scheduling of the project; changes during construction by the client; delay in progress payment; slowness in decision making by the client; and poor communication between clients and other stakeholders. In addition, data from the case study projects strongly suggest that optimism bias is present in many of the hospital projects. Further validation via key stakeholder interviews and documentations are planned.

Keywords: BIM, client perspective, delay management, optimism bias, public sector projects.

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Authors: Luciana C. Ramos, Leandro J. Sousa, Antônio Ferreira da Silva, Valéria Gomes Oliveira Falcão, Suzana T. Cunha Lima

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The commercial production of biodiesel using microalgae demands a high-energy input for harvesting biomass, making production economically unfeasible. Methods currently used involve mechanical, chemical, and biological procedures. In this work, a flocculation system is presented as a cost and energy effective process to increase biomass production of Phaeodactylum tricornutum. This diatom is the only species of the genus that present fast growth and lipid accumulation ability that are of great interest for biofuel production. The algae, selected from the Bank of Microalgae, Institute of Biology, Federal University of Bahia (Brazil), have been bred in tubular reactor with photoperiod of 12 h (clear/dark), providing luminance of about 35 μmol photons m^-2s^-1, and temperature of 22 °C. The medium used for growing cells was the Conway medium, with addition of silica. The seaweed growth curve was accompanied by cell count in Neubauer camera and by optical density in spectrophotometer, at 680 nm. The precipitation occurred at the end of the stationary phase of growth, 21 days after inoculation, using two methods: centrifugation at 5000 rpm for 5 min, and electro-flocculation at 19 EPD and 95 W. After precipitation, cells were frozen at -20 °C and, subsequently, lyophilized. Biomass obtained by electro-flocculation was approximately four times greater than the one achieved by centrifugation. The benefits of this method are that no addition of chemical flocculants is necessary and similar cultivation conditions can be used for the biodiesel production and pharmacological purposes. The results may contribute to improve biodiesel production costs using marine microalgae.

Keywords: Biomass, diatom, flocculation, microalgae.

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