Search results for: maintenance strategy selection multiple criteria decision-making analysis

Authors: Jia-Ru Li, Chih-Hung Wang, Ching-Wen Lin

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The association between emotional inhibition strategies linked to depression has been showed inconsistent among studies. Mild emotional inhibition maybe benefit for social interaction, especially for female among East Asian cultures. The present study aimed to examine whether the inhibition–depression relationship is dependent on level of emotion inhibition and gender context, given differing value of suppressing emotional displays. We hypothesized that the negative associations between inhibition and adolescent depression would not directly, in which affected by interaction between emotion inhibition and gender. To test this hypothesis, we asked 309 junior high school students which age range from 12 to14 years old to report on their use of emotion inhibition and depression syndrome. A multiple regressions analysis revealed that significant interaction that gender as a moderator to the relationships between emotion inhibition and adolescent depression. The group with the highest level of depression was girls with high levels of emotion inhibition, whose depression score was higher than that of boys with high levels of emotion inhibition. The result highlights that the importance of context in understanding the inhibition-depression relationship.

Keywords: Emotional inhibition strategies, gender, adolescent depression.

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Authors: Rajaram Kr. Gupta, Bhupendra Kumar, T. V. K. Gupta, D. S. Ramteke

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Machining of hard materials is a recent technology for direct production of work-pieces. The primary challenge in machining these materials is selection of cutting tool inserts which facilitates an extended tool life and high-precision machining of the component. These materials are widely for making precision parts for the aerospace industry. Nickel-based alloys are typically used in extreme environment applications where a combination of strength, corrosion resistance and oxidation resistance material characteristics are required. The present paper reports the theoretical and experimental investigations carried out to understand the influence of machining parameters on the response parameters. Considering the basic machining parameters (speed, feed and depth of cut) a study has been conducted to observe their influence on material removal rate, surface roughness, cutting forces and corresponding tool wear. Experiments are designed and conducted with the help of Central Composite Rotatable Design technique. The results reveals that for a given range of process parameters, material removal rate is favorable for higher depths of cut and low feed rate for cutting forces. Low feed rates and high values of rotational speeds are suitable for better finish and higher tool life.

Keywords: Speed, feed, depth of cut, roughness, cutting force, flank wear.

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Authors: Sanaeinejad, S. H.; A. Astaraei, . P. Mirhoseini.Mousavi, M. Ghaemi,

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One of the main environmental problems which affect extensive areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Neyshaboor area, North East of Iran was selected as a field study of this research. Landsat satellite images for this area were used in order to prepare suitable learning samples for processing and classifying the images. 300 locations were selected randomly in the area to collect soil samples and finally 273 locations were reselected for further laboratory works and image processing analysis. Electrical conductivity of all samples was measured. Six reflective bands of ETM+ satellite images taken from the study area in 2002 were used for soil salinity classification. The classification was carried out using common algorithms based on the best composition bands. The results showed that the reflective bands 7, 3, 4 and 1 are the best band composition for preparing the color composite images. We also found out, that hybrid classification is a suitable method for identifying and delineation of different salinity classes in the area.

Keywords: Soil salinity, Remote sensing, Image processing, ETM+, Nyshaboor

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Authors: Xiang Zhang, David Rey, S. Travis Waller

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Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model.

Keywords: Parameter calibration, sequential quadratic programming, Stochastic User Equilibrium, traffic assignment, transportation planning.

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Authors: Adnene Arbi, Chaouki Aouiti, Abderrahmane Touati

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In this paper, we consider the global exponential stability of the equilibrium point of Hopfield neural networks with delays and impulsive perturbation. Some new exponential stability criteria of the system are derived by using the Lyapunov functional method and the linear matrix inequality approach for estimating the upper bound of the derivative of Lyapunov functional. Finally, we illustrate two numerical examples showing the effectiveness of our theoretical results.

Keywords: Hopfield Neural Networks, Exponential stability.

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

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

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

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Authors: Archana S. Nanoty, A. R. Chudasama

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Three-phase induction machines are today a standard for industrial electrical drives. Cost, reliability, robustness and maintenance free operation are among the reasons these machines are replacing dc drive systems. The development of power electronics and signal processing systems has eliminated one of the greatest disadvantages of such ac systems, which is the issue of control. With modern techniques of field oriented vector control, the task of variable speed control of induction machines is no longer a disadvantage. The need to increase system performance, particularly when facing limits on the power ratings of power supplies and semiconductors, motivates the use of phase number other than three, In this paper a novel scheme of connecting two, three phase induction motors in parallel fed by two inverters; viz. VSI and CSI and their vector control is presented.

Keywords: Field oriented control, multiphase induction motor, power electronics converter.

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones are continually upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described more refined, complex and detailed. In this context, we analyzed a set of experimental data, obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model become extremely challenging. After a series of feature selection and parameters adjustments, a well-performed SVM classifier has been trained. 

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Hailu Dessalegn, T. Srinivas

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We propose new multiple-channel piezoelectric (PZT) actuated tunable optical filter based on racetrack multi-ring resonators for wavelength de-multiplexing network applications. We design tunable eight-channel wavelength de-multiplexer consisting of eight cascaded PZT actuated tunable multi-ring resonator filter with a channel spacing of 1.6nm. The filter for each channel is basically structured on a suspended beam, sandwiched with piezoelectric material and built in integrated ring resonators which are placed on the middle of the beam to gain uniform stress and linearly varying longitudinal strain. A reference single mode serially coupled multi stage racetrack ring resonator with the same radii and coupling length is designed with a line width of 0.8974nm with a flat top pass band at 1dB of 0.5205nm and free spectral range of about 14.9nm. In each channel, a small change in the perimeter of the rings is introduced to establish the shift in resonance wavelength as per the defined channel spacing. As a result, when a DC voltage is applied, the beams will elongate, which involves mechanical deformation of the ring resonators that induces a stress and a strain, which brings a change in refractive index and perimeter of the rings leading to change in the output spectrum shift providing the tunability of central wavelength in each channel. Simultaneous wave length shift as high as 45.54pm/

Keywords: Optical MEMS, piezoelectric (PZT) actuation, tunable optical filter, wavelength de-multiplexer.

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Authors: Ahmed F. Azmy , Amal E. Saafan, Tamer M. Essam, Magdy A. Amin, Shaban H. Ahmed

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Bacterial strains capable of degradation of malathion from the domestic sewage were isolated by an enrichment culture technique. Three bacterial strains were screened and identified as Acinetobacter baumannii (AFA), Pseudomonas aeruginosa (PS1), and Pseudomonas mendocina (PS2) based on morphological, biochemical identification and 16S rRNA sequence analysis. Acinetobacter baumannii AFA was the most efficient malathion degrading bacterium, so used for further biodegradation study. AFA was able to grow in mineral salt medium (MSM) supplemented with malathion (100 mg/l) as a sole carbon source, and within 14 days, 84% of the initial dose was degraded by the isolate measured by high performance liquid chromatography. Strain AFA could also degrade other organophosphorus compounds including diazinon, chlorpyrifos and fenitrothion. The effect of different culture conditions on the degradation of malathion like inoculum density, other carbon or nitrogen sources, temperature and shaking were examined. Degradation of malathion and bacterial cell growth were accelerated when culture media were supplemented with yeast extract, glucose and citrate. The optimum conditions for malathion degradation by strain AFA were; an inoculum density of 1.5x 10^12CFU/ml at 30°C with shaking. A specific polymerase chain reaction primers were designed manually using multiple sequence alignment of the corresponding carboxylesterase enzymes of Acinetobacter species. Sequencing result of amplified PCR product and phylogenetic analysis showed low degree of homology with the other carboxylesterase enzymes of Acinetobacter strains, so we suggested that this enzyme is a novel esterase enzyme. Isolated bacterial strains may have potential role for use in bioremediation of malathion contaminated.

Keywords: Acinetobacter baumannii, biodegradation, Malathion, organophosphate pesticides.

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Authors: Tawakal Hasnain Baluch, Adnan Masood, Javaid Iqbal, Umer Izhar, Umar Shahbaz Khan

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This paper will provide the kinematic and dynamic analysis of a lower limb exoskeleton. The forward and inverse kinematics of proposed exoskeleton is performed using Denevit and Hartenberg method. The torques required for the actuators will be calculated using Lagrangian formulation technique. This research can be used to design the control of the proposed exoskeleton.

Keywords: Dynamic Analysis, Exoskeleton, Kinematic Analysis, Lower Limb, Rehabilitation Robotics

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: Artificial Neural Network, Data Mining, Electroencephalogram, Epilepsy, Feature Extraction, Seizure Detection, Signal Processing.

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Authors: Elena C. Tamaş, Grațiela M. Țârlea, Gianni Flamaropol, Dragoș Hera

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This article is referring to a comparative study regarding the electrical energy consumption for lighting on diverse types of big sizes commercial buildings built in Romania after 2007, having 3, 4, 5 versus 8, 9, 10 operational years. Some buildings have installed building management systems (BMS) to monitor also the lighting performances starting with the opening days till the present days but some have chosen only local meters to implement. Firstly, for each analyzed building, the total required energy power and the energy power consumption for lighting were calculated depending on the lamps number, the unit power and the average daily running hours. All objects and installations were chosen depending on the destination/location of the lighting (exterior parking or access, interior or covering parking, building interior and building perimeter). Secondly, to all lighting objects and installations, mechanical counters were installed, and to the ones linked to BMS there were installed the digital meters as well for a better monitoring. Some efficient solutions are proposed to improve the power consumption, for example the 1/3 lighting functioning for the covered and exterior parking lighting to those buildings if can be done. This type of lighting share can be performed on each level, especially on the night shifts. Another example is to use the dimmers to reduce the light level, depending on the executed work in the respective area, and a 30% power energy saving can be achieved. Using the right BMS to monitor, the energy consumption depending on the average operational daily hours and changing the non-performant unit lights with the ones having LED technology or economical ones might increase significantly the energy performances and reduce the energy consumption of the buildings.

Keywords: Lighting consumption, commercial buildings, maintenance, energy performances.

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Authors: M. Stewart, Ameer Al-Khaykan, J. M. Counsell

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Emissions are a consequence of electricity generation. A major option for low carbon generation, local energy systems featuring Combined Heat and Power with solar PV (CHPV) has significant potential to increase energy performance, increase resilience, and offer greater control of local energy prices while complementing the UK’s emissions standards and targets. Recent advances in dynamic modelling and simulation of buildings and clusters of buildings using the IDEAS framework have successfully validated a novel multi-vector (simultaneous control of both heat and electricity) approach to integrating the wide range of primary and secondary plant typical of local energy systems designs including CHP, solar PV, gas boilers, absorption chillers and thermal energy storage, and associated electrical and hot water networks, all operating under a single unified control strategy. Results from this work indicate through simulation that integrated control of thermal storage can have a pivotal role in optimizing system performance well beyond the present expectations. Environmental impact analysis and reporting of all energy systems including CHPV LES presently employ a static annual average carbon emissions intensity for grid supplied electricity. This paper focuses on establishing and validating CHPV environmental performance against conventional emissions values and assessment benchmarks to analyze emissions performance without and with an active thermal store in a notional group of non-domestic buildings. Results of this analysis are presented and discussed in context of performance validation and quantifying the reduced environmental impact of CHPV systems with active energy storage in comparison with conventional LES designs.

Keywords: CHPV, thermal storage, control, dynamic simulation.

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Authors: Walid MOUDANI

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the Coronary Heart Disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts- knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: Multi-Classifier Decisions Tree, Features Reduction, Dynamic Programming, Rough Sets.

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Authors: Chethana K., Guru Prasad A. S., Vikranth H. N., Varun H., Omkar S. N., Asokan S.

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This paper describes a novel application of Fiber Braggs Grating (FBG) sensors in the assessment of human postural stability and balance on an unstable platform. In this work, FBG sensor Stability Analyzing Device (FBGSAD) is developed for measurement of plantar strain to assess the postural stability of subjects on unstable platforms during different stances in eyes open and eyes closed conditions on a rocker board. The studies are validated by comparing the Centre of Gravity (CG) variations measured on the lumbar vertebra of subjects using a commercial accelerometer. The results obtained from the developed FBGSAD depict qualitative similarities with the data recorded by commercial accelerometer. The advantage of the FBGSAD is that it measures simultaneously plantar strain distribution and postural stability of the subject along with its inherent benefits like non-requirement of energizing voltage to the sensor, electromagnetic immunity and simple design which suits its applicability in biomechanical applications. The developed FBGSAD can serve as a tool/yardstick to mitigate space motion sickness, identify individuals who are susceptible to falls and to qualify subjects for balance and stability, which are important factors in the selection of certain unique professionals such as aircraft pilots, astronauts, cosmonauts etc.

Keywords: Biomechanics, Fiber Bragg Gratings, Plantar Strain Measurement, Postural Stability Analysis.

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Authors: F. Gurkalo, K. Poutos

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Earthquakes produce some of the most violent loading situations that a structure can be subjected to and if a structure fails under these loads then inevitably human life is put at risk. One of the most common methods by which a structure fails under seismic loading is at the connection of structural elements. The research presented in this paper investigates the interlock systems as a novel method for building structures. The main objective of this experimental study wasto determine the dynamic characteristics and the seismic behaviour of the proposed structures compared to conventional structural systemsduring seismic motions. Results of this study indicate that the interlock mechanism of the panels influences the behaviour of lateral load-resisting systems of the structures during earthquakes, contributing to better structural flexibility and easier maintenance.

Keywords: Watertower, earthquake, seismic, interlocked panels

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Authors: A. Sohrabi

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The importance of local food products and their promotion are drivers for economic growth. Entrepreneurship is one of the most important tools for development, which puts its most important effect on the way of increasing business in society. The purpose of this paper is to assess the breadth of food strategies in Italy toward to promoting local Italian foods in order to present useful food policies for developing countries. The methodology of this paper is based on qualitative analysis. In order to achieve such objectives, a literature review is carried out by employing documenting study. In this research, at first, we seek to present compliance’s concepts and definitions. Then, after examining the dimensions of the three strategies, we access to the indicators and compare their effects in order to present some useful policies and guidelines for developing countries. Despite of the limitations like inaccessibility, performance of companies in exporting local foods and lacking perception of awareness and experience of people, the study offers possible ways for future, as an example for Middle East countries to promote Italian local foods. The finding of this paper evaluates the three strategies in order to promote local food entrepreneurship in Italy and developing countries.

Keywords: Local food, Italian food, Italian strategy, food policy.

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Authors: Hee Jae Shin, In Pyo Cha, Min Sang Lee, Hyun Kyung Yoon, Tae Ho Kim, Yoon Sun Lee, Lee Ku Kwac, Hong Gun Kim

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Non-destructive testing and evaluation techniques for assessing the integrity of composite structures are essential to both reduce manufacturing costs and out of service time of transport means due to maintenance. In this study, Analyze into non-destructive test characterization of carbon fiber reinforced plastics (CFRP) internal and external defects using thermo-graphic camera and transient thermography method. non-destructive testing were characterized by defect size (Ø8, Ø10, Ø12, Ø14) and depth (1.2mm, 2.4mm).

Keywords: Non Destructive test (NDT), Thermal characteristic, Thermo graphic Camera, Carbon Fiber Reinforced Plastics (CFRP).

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Authors: Aisha Tarek Noour, Nick Hubbard

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Learner motivation is considered to be an important component for the Blended e-Learning (BL) Method. BL is an effective learning method in multiple domains, which opens several opportunities for its participants to engage in the learning environment. This research explores the learners’ perspective of BL according to the Self-Determination Theory (SDT). It identifies the opportunities and challenges for using the BL in Logistics Education (LE) in Egyptian Higher Education (HE). SDT is approached from different perspectives within the relationship between Intrinsic Motivation (IM), Extrinsic Motivation (EM) and Amotivation (AM). A self-administered face-to-face questionnaire was used to collect data from learners who were geographically widely spread around three colleges of International Transport and Logistics (CILTs) at the Arab Academy for Science, Technology and Maritime Transport (AAST&MT) in Egypt. Six hundred and sixteen undergraduates responded to a questionnaire survey. Respondents were drawn from three branches in Greater Cairo, Alexandria, and Port Said. The data analysis used was SPSS 22 and AMOS 18.

Keywords: Intrinsic Motivation, Extrinsic Motivation, Amotivation, Blended e-Learning, Self Determination Theory.

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Authors: Favour Makuochukwu Orji, Yingkui Zhao

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A myriad of environmental issues face the Nigerian industrial region, resulting from; oil and gas production, mining, manufacturing and domestic wastes. Amidst these, much effort has been directed by stakeholders in the Nigerian oil producing regions, because of the impacts of the region on the wider Nigerian economy. Although collaborative environmental management has been noted as an effective approach in managing environmental issues, little attention has been given to the roles and practices of stakeholders in effecting a collaborative environmental management framework for the Nigerian oil-producing region. This paper produces a framework to expand and deepen knowledge relating to stakeholders aspects of collaborative roles in managing environmental issues in the Nigeria oil-producing region. The knowledge is derived from analysis of stakeholders’ practices – studied through multiple case studies using document analysis. Selected documents of key stakeholders – Nigerian government agencies, multi-national oil companies and host communities, were analyzed. Open and selective coding was employed manually during document analysis of data collected from the offices and websites of the stakeholders. The findings showed that the stakeholders have a range of roles, practices, interests, drivers and barriers regarding their collaborative roles in managing environmental issues. While they have interests for efficient resource use, compliance to standards, sharing of responsibilities, generating of new solutions, and shared objectives; there is evidence of major barriers and these include resource allocation, disjointed policy, ineffective monitoring, diverse socio- economic interests, lack of stakeholders’ commitment and limited knowledge sharing. However, host communities hold deep concerns over the collaborative roles of stakeholders for economic interests, particularly, where government agencies and multi-national oil companies are involved. With these barriers and concerns, a genuine stakeholders’ collaboration is found to be limited, and as a result, optimal environmental management practices and policies have not been successfully implemented in the Nigeria oil-producing region. A framework is produced that describes practices that characterize collaborative environmental management might be employed to satisfy the stakeholders’ interests. The framework recommends critical factors, based on the findings, which may guide a collaborative environmental management in the oil producing regions. The recommendations are designed to re-define the practices of stakeholders in managing environmental issues in the oil producing regions, not as something wholly new, but as an approach essential for implementing a sustainable environmental policy. This research outcome may clarify areas for future research as well as to contribute to industry guidance in the area of collaborative environmental management.

Keywords: Collaborative environmental management framework, document analysis, case studies, multinational oil companies, Nigerian oil-producing region, stakeholders analysis.

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Authors: Mohammad D. AL-Tahat, Shahnaz M. Alkhalil

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International markets driven forces are changing continuously, therefore companies need to gain a competitive edge in such markets. Improving the company's products, processes and practices is no longer auxiliary. Lean production is a production management philosophy that consolidates work tasks with minimum waste resulting in improved productivity. Lean production practices can be mapped into many production areas. One of these is Manufacturing Equipment and Technology (MET). Many lean production practices can be implemented in MET, namely, specific equipment configurations, total preventive maintenance, visual control, new equipment/ technologies, production process reengineering and shared vision of perfection.The purpose of this paper is to investigate the implementation level of these six practices in Jordanian industries. To achieve that a questionnaire survey has been designed according to five-point Likert scale. The questionnaire is validated through pilot study and through experts review. A sample of 350 Jordanian companies were surveyed, the response rate was 83%. The respondents were asked to rate the extent of implementation for each of practices. A relationship conceptual model is developed, hypotheses are proposed, and consequently the essential statistical analyses are then performed. An assessment tool that enables management to monitor the progress and the effectiveness of lean practices implementation is designed and presented. Consequently, the results show that the average implementation level of lean practices in MET is 77%, Jordanian companies are implementing successfully the considered lean production practices, and the presented model has Cronbach-s alpha value of 0.87 which is good evidence on model consistency and results validation.

Keywords: Lean Production, SME applications, Visual Control, New equipment/technologies, Specific equipment configurations, Jordan

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Authors: Mukesh Doble, Sunil K Narayan

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Diffuse viral encephalitis may lack fever and other cardinal signs of infection and hence its distinction from other acute encephalopathic illnesses is challenging. Often, the EEG changes seen routinely are nonspecific and reflect diffuse encephalopathic changes only. The aim of this study was to use nonlinear dynamic mathematical techniques for analyzing the EEG data in order to look for any characteristic diagnostic patterns in diffuse forms of encephalitis.It was diagnosed on clinical, imaging and cerebrospinal fluid criteria in three young male patients. Metabolic and toxic encephalopathies were ruled out through appropriate investigations. Digital EEGs were done on the 3rd to 5th day of onset. The digital EEGs of 5 male and 5 female age and sex matched healthy volunteers served as controls.Two sample t-test indicated that there was no statistically significant difference between the average values in amplitude between the two groups. However, the standard deviation (or variance) of the EEG signals at FP1-F7 and FP2-F8 are significantly higher for the patients than the normal subjects. The regularisation dimension is significantly less for the patients (average between 1.24-1.43) when compared to the normal persons (average between 1.41-1.63) for the EEG signals from all locations except for the Fz-Cz signal. Similarly the wavelet dimension is significantly less (P = 0.05*) for the patients (1.122) when compared to the normal person (1.458). EEGs are subdued in the case of the patients with presence of uniform patterns, manifested in the values of regularisation and wavelet dimensions, when compared to the normal person, indicating a decrease in chaotic nature.

Keywords: Chaos, Diffuse encephalitis, Electroencephalogram, Fractal dimension, Fourier spectrum.

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Authors: J. Grira, Y. Bédard, S. Roche

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The aim of this research is to design a collaborative framework that integrates risk analysis activities into the geospatial database design (GDD) process. Risk analysis is rarely undertaken iteratively as part of the present GDD methods in conformance to requirement engineering (RE) guidelines and risk standards. Accordingly, when risk analysis is performed during the GDD, some foreseeable risks may be overlooked and not reach the output specifications especially when user intentions are not systematically collected. This may lead to ill-defined requirements and ultimately in higher risks of geospatial data misuse. The adopted approach consists of 1) reviewing risk analysis process within the scope of RE and GDD, 2) analyzing the challenges of risk analysis within the context of GDD, and 3) presenting the components of a risk-based collaborative framework that improves the collection of the intended/forbidden usages of the data and helps geo-IT experts to discover implicit requirements and risks.

Keywords: Collaborative risk analysis, intention of use, Geospatial database design, Geospatial data misuse.

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Authors: M. Raciti Castelli, A. Fedrigo, E. Benini

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A multiple-option analytical model for the evaluation of the energy performance and distribution of aerodynamic forces acting on a vertical-axis Darrieus wind turbine depending on both rotor architecture and operating conditions is presented. For this purpose, a numerical algorithm, capable of generating the desired rotor conformation depending on design geometric parameters, is coupled to a Single/Double-Disk Multiple-Streamtube Blade Element – Momentum code. Both single and double-disk configurations are analyzed and model predictions are compared to literature experimental data in order to test the capability of the code for predicting rotor performance. Effective airfoil characteristics based on local blade Reynolds number are obtained through interpolation of literature low-Reynolds airfoil databases. Some corrections are introduced inside the original model with the aim of simulating also the effects of blade dynamic stall, rotor streamtube expansion and blade finite aspect ratio, for which a new empirical relationship to better fit the experimental data is proposed. In order to predict also open field rotor operation, a freestream wind shear profile is implemented, reproducing the effect of atmospheric boundary layer.

Keywords: Wind turbine, BE-M, dynamic stall, streamtube expansion, airfoil finite aspect ratio

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Authors: Jae-Neung Lee, Sung-Bum Pan, Keun-Chang Kwak

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This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. The results are summarized as follows. Attached to the cockpit are sensors that feed -back information on rudder angle, boat heel angle and mainsheet tension to the computer. Energy expenditure of the sailor measure indirectly using expired gas analysis for the measurement of VO2 and VCO2. At sea course configurations and wind conditions can be preset to suit any level of sailor from complete beginner to advanced sailor.

Keywords: Trends Analysis, Yacht Simulator, Sailing.

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Authors: Aimen Batool Bint-E-Rashid, Syed Muhammad Dawood Ali Shah, Muhammad Usman Farooq, Mahgul Anwar

Abstract:

As the world is progressing, the needs and demands of the consumer market are also changing. Nowadays the trends of consumer purchase decisions are dependent upon multiple factors. This study aims to identify the influential impact of country of origin over the perception and devotion towards daily personal care products specifically in reference to the knowledge and awareness regarding that particular brand in Pakistan. To corroborate this study, a 30-item brand origin questionnaire has been used with 300 purchase decision makers belonging to different age groups. To illustrate this study, a model has been developed based on brand origin, brand awareness and brand loyalty. Correlation and regression analysis have been used to find out the results which conclude the findings on the perspective of Pakistan’s consumer market as that brand origin has a direct relationship with brand loyalty provided that the consumer has a positive brand awareness. Support for the fact that brand origin impacts brand loyalty through brand awareness has been presented in this study.

Keywords: Brand awareness, brand loyalty, brand origin, personal care products, P&G, Unilever.

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Authors: Yen-Po Wang, Ming-Chih Huang, Ming-Lian Chang

Abstract:

A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.

Keywords: Damage locating vectors, deterministic-stochastic subspace system, shaking table tests, system identification.

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Authors: Shuki Dror

Abstract:

This work discusses an innovative methodology for deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational relationships. A House of Service Quality (HOSQ) matrix is built to extract the desired improvement in the service quality characteristics and to translate them into a hierarchy of important organizational features. The Mean Square Error (MSE) criterion enables the pinpointing of the few essential service quality characteristics to be improved as well as selection of the vital organizational features. The method was implemented in an engineering supply enterprise and provides useful information on its vital service dimensions.

Keywords: HOQ, organizational features, service quality.

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

Abstract:

Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: Predictive analysis, big data, predictive analysis algorithms. CART algorithm.

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