Search results for: innovations management systems

Authors: Raksha Sharma, Vishnu Kant Soni, Manoj Kumar Mishra, Prachet Bhuyan

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Grid computing is a form of distributed computing that involves coordinating and sharing computational power, data storage and network resources across dynamic and geographically dispersed organizations. Scheduling onto the Grid is NP-complete, so there is no best scheduling algorithm for all grid computing systems. An alternative is to select an appropriate scheduling algorithm to use in a given grid environment because of the characteristics of the tasks, machines and network connectivity. Job and resource scheduling is one of the key research area in grid computing. The goal of scheduling is to achieve highest possible system throughput and to match the application need with the available computing resources. Motivation of the survey is to encourage the amateur researcher in the field of grid computing, so that they can understand easily the concept of scheduling and can contribute in developing more efficient scheduling algorithm. This will benefit interested researchers to carry out further work in this thrust area of research.

Keywords: Grid Computing, Job Scheduling, ResourceScheduling.

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Authors: Rajesh Kumar, Puneet Aggarwal

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In context of understanding problems faced by undergraduate students while carrying out laboratory experiments dealing with high voltages, it was found that most of the students are hesitant to work directly on machine. The reason is that error in the circuitry might lead to deterioration of machine and laboratory instruments. So, it has become inevitable to include modern pedagogic techniques for undergraduate students, which would help them to first carry out experiment in virtual system and then to work on live circuit. Further advantages include that students can try out their intuitive ideas and perform in virtual environment, hence leading to new research and innovations. In this paper, virtual environment used is of MATLAB/Simulink for three-phase induction machines. The performance analysis of three-phase induction machine is carried out using virtual environment which includes Direct Current (DC) Test, No-Load Test, and Block Rotor Test along with speed torque characteristics for different rotor resistances and input voltage, respectively. Further, this paper carries out computer aided teaching of basic Voltage Source Inverter (VSI) drive circuitry. Hence, this paper gave undergraduates a clearer view of experiments performed on virtual machine (No-Load test, Block Rotor test and DC test, respectively). After successful implementation of basic tests, VSI circuitry is implemented, and related harmonic distortion (THD) and Fast Fourier Transform (FFT) of current and voltage waveform are studied.

Keywords: Block rotor test, DC test, no-load test, virtual environment, VSI.

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Authors: Youngpo Lee, Seokho Yoon

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In this paper, we propose a distance estimation scheme for radar systems using direct sequence ultra wideband (DS-UWB) signals. The proposed distance estimation scheme averages out the noise by accumulating the correlator outputs of the radar, and thus, helps the radar to employ a short-length DS-UWB signal reducing the correlation processing time. Numerical results confirm that the proposed distance estimation scheme provides a better estimation performance and a reduced correlation processing time compared with those of the conventional DS-UWB radars.

Keywords: Radar, DS-UWB, distance estimation, correlation accumulation.

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Authors: Muhammad N. Khan, Syed O. Gillani, Mohsin Jamil, Tarbia Iftikhar

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With the increasing demand of bandwidth and data rate, there is a dire need to implement antenna systems in mobile phones which are able to fulfill user requirements. A monopole antenna system with multi-antennas configurations is proposed considering the feasibility and user demand. The multi-antenna structure is referred to as multi-input multi-output (MIMO) antenna system. The multi-antenna system comprises of 4 antennas operating below 6 GHz frequency bands for 4G/LTE and 4 antenna for 5G applications at 28 GHz and the dimension of board is 120 × 70 × 0.8mm3. The suggested designs is feasible with a structure of low-profile planar-antenna and is adaptable to smart cell phones and handheld devices. To the best of our knowledge, this is the first design compared to the literature by having integrated antenna system for two standards, i.e., 4G and 5G. All MIMO antenna systems are simulated on commercially available software, which is high frequency structures simulator (HFSS).

Keywords: High frequency structures simulator (HFSS), mutli-input multi-output (MIMO), monopole antenna, slot antenna.

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Authors: Nurazean Maarop, Noorjan Mohd Mustapha, Rasimah Yusoff, Roslina Ibrahim, Norziha Megat Mohd Zainuddin

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The goal of this study is to identify success factors that could influence the ISMS self-implementation in government sector from qualitative perspective. This study is based on a case study in one of the Malaysian government agency. Semi-structured interviews involving five key informants were conducted to examine factors addressed in the conceptual framework. Subsequently, thematic analysis was executed to describe the influence of each factor on the success implementation of ISMS. The result of this study indicates that management commitment, implementer commitment and implementer competency are part of the success factors for ISMS self-implementation in Malaysian Government Sector.

Keywords: ISMS Success Factors, IT Project Management, IS Success, Information Security.

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Authors: G. Lindemann, D. Schmidt, T. Schrader, M. Beil, T. Schaaf, H.-D. Burkhard

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The amount and heterogeneity of data in biomedical research, notably in interdisciplinary research, requires new methods for the collection, presentation and analysis of information. Important data from laboratory experiments as well as patient trials are available but come out of distributed resources. The Charite Medical School in Berlin has established together with the German Research Foundation (DFG) a new information service center for kidney diseases and transplantation (Open European Nephrology Science Centre - OpEN.SC). The system is based on a service-oriented architecture (SOA) with main and auxiliary modules arranged in four layers. To improve the reuse and efficient arrangement of the services the functionalities are described as business processes using the standardised Business Process Execution Language (BPEL).

Keywords: Software development management, Business dataprocessing, Knowledge based systems in medicine

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.

Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.

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Authors: Namchul Do, Jihun Cho

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Modeling product configurations needs large amounts of knowledge about technical and marketing restrictions on the product. Previous attempts to automate product configurations concentrate on representations and management of the knowledge for specific domains in fixed and isolated computing environments. Since the knowledge about product configurations is subject to continuous change and hard to express, these attempts often failed to efficiently manage and exchange the knowledge in collaborative product development. In this paper, XML Topic Map (XTM) is introduced to represent and exchange the knowledge about product configurations in collaborative product development. A product configuration model based on XTM along with its merger and inference facilities enables configuration engineers in collaborative product development to manage and exchange their knowledge efficiently. A prototype implementation is also presented to demonstrate the proposed model can be applied to engineering information systems to exchange the product configuration knowledge.

Keywords: Knowledge exchange, product configurations, XML topic map.

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Authors: Woo Young Jung, Min Ho Kwon, Bu Seog Ju

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A failure of the non-structural component can cause  significant damages in critical facilities such as nuclear power plants  and hospitals. Historically, it was reported that the damage from the  leakage of sprinkler systems, resulted in the shutdown of hospitals for  several weeks by the 1971 San Fernando and 1994 North Ridge  earthquakes. In most cases, water leakages were observed at the cross  joints, sprinkler heads, and T-joint connections in piping systems  during and after the seismic events. Hence, the primary objective of  this study was to understand the seismic performance of T-joint  connections and to develop an analytical Finite Element (FE) model  for the T-joint systems of 2-inch fire protection piping system in  hospitals subjected to seismic ground motions. In order to evaluate the  FE models of the piping systems using OpenSees, two types of  materials were used: 1) Steel02 materials and 2) Pinching4 materials.  Results of the current study revealed that the nonlinear  moment-rotation FE models for the threaded T-joint reconciled well  with the experimental results in both FE material models. However,  the system-level fragility determined from multiple nonlinear time  history analyses at the threaded T-joint was slightly different. The  system-level fragility at the T-joint, determined by Pinching4 material  was more conservative than that of using Steel02 material in the piping  system.

Keywords: Fragility, T-joint, Piping, Leakage, Sprinkler.

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Authors: Alireza Sadrmomtaz

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Positron emission particle tracking (PEPT) is a technique in which a single radioactive tracer particle can be accurately tracked as it moves. A limitation of PET is that in order to reconstruct a tomographic image it is necessary to acquire a large volume of data (millions of events), so it is difficult to study rapidly changing systems. By considering this fact, PEPT is a very fast process compared with PET. In PEPT detecting both photons defines a line and the annihilation is assumed to have occurred somewhere along this line. The location of the tracer can be determined to within a few mm from coincident detection of a small number of pairs of back-to-back gamma rays and using triangulation. This can be achieved many times per second and the track of a moving particle can be reliably followed. This technique was invented at the University of Birmingham [1]. The attempt in PEPT is not to form an image of the tracer particle but simply to determine its location with time. If this tracer is followed for a long enough period within a closed, circulating system it explores all possible types of motion. The application of PEPT to industrial process systems carried out at the University of Birmingham is categorized in two subjects: the behaviour of granular materials and viscous fluids. Granular materials are processed in industry for example in the manufacture of pharmaceuticals, ceramics, food, polymers and PEPT has been used in a number of ways to study the behaviour of these systems [2]. PEPT allows the possibility of tracking a single particle within the bed [3]. Also PEPT has been used for studying systems such as: fluid flow, viscous fluids in mixers [4], using a neutrally-buoyant tracer particle [5].

Keywords: PET, BGO, Particle Tracking, ECAT 931, List mode, PEPT.

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Authors: Eileen M. J. Knight

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This study examines the structural and systematic processes of the Human Resources Division at The University of the West Indies, St. Augustine, Trinidad and Tobago for evidence of incorporation of the University's 2012- 2017 Strategic Plan. In conducting the study the structure of the Human Resources Management Division and its functions were carefully reviewed and measured against the strategic direction of the organisation. Findings indicate disconnect between these areas as there is apparent failure of the Human Resources Division to totally align its mandate with that of the organisation-s strategic direction. This action serves to threaten the viability of the organisation and its efficiency and effectiveness as an institution. The recommendations being put forward are for the realignment of the Human Resources Management Division and for its focus to mirror that of the organisation and the organisation-s goals and objectives. This may entail a restructuring of the Division.

Keywords: Commonwealth Caribbean, Realignment, Region, Strategic Plan.

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Authors: Fu Shiming, Pei Yifei

Abstract:

To study the impact of the inter-module ventilation (IMV) on the space station, the Computational Fluid Dynamic (CFD) model under the influence of IMV, the mathematical model, boundary conditions and calculation method are established and determined to analyze the influence of IMV on cabin air flow characteristics and velocity distribution firstly; and then an integrated overall thermal mathematical model of the space station is used to consider the impact of IMV on thermal management. The results show that: the IMV has a significant influence on the cabin air flow, the flowrate of IMV within a certain range can effectively improve the air velocity distribution in cabin, if too much may lead to its deterioration; IMV can affect the heat deployment of the different modules in space station, thus affecting its thermal management, the use of IMV can effectively maintain the temperature levels of the different modules and help the space station to dissipate the waste heat.

Keywords: CFD, Environment control and life support, Space station, Thermal management, Thermal mathematical model.

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Authors: S. Anbu, N. Jaya

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Nonlinearity is the inherent characteristics of all the industrial processes. The Classical control approach used for a generation often fails to show better results particularly for non-linear systems and in the systems, whose parameters changes over a period of time for a variety of reasons. Alternatively, adaptive control strategies provide very good performance. The Model Reference Adaptive Control based on Lyapunov stability analysis and classical PI control strategies are designed and evaluated for Continuous Stirred Tank Reactor, which shows appreciable dynamic nonlinear characteristics.

Keywords: Adaptive Control, CSTR, Lyapunov stability, MRAS, PID.

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Authors: M. Hajduk-Stelmachowicz

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This paper shows the results of empirical research. It presents experiences of Polish companies from the Podkarpackie voivodeship connected with implementing EMS according to the requirements of the ISO 14001 international standard. The incentives to introduce and certify organizational eco-innovation, which formal EMSs are treated as, are presented in this paper.

Keywords: Environmental Management System (EMS), ISO 14001, Podkarpackie voivodeship (Poland)

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Authors: C. S. Mammas, A. Lazaris, A. S. Mamma-Graham, G. Kostopanagiotou, C. Lemonidou, J. Mantas, E. Patsouris

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Introduction: The process to build a better safety culture, methods of error analysis, and preventive measures, starts with an understanding of the effects when human factors engineering refer to remote microscopic diagnosis in surgery and specially in organ transplantation for the remote evaluation of the grafts. It has been estimated that even in well-organized transplant systems an average of 8% to 14% of the grafts (G) that arrive at the recipient hospitals may be considered as diseased, injured, damaged or improper for transplantation. Digital microscopy adds information on a microscopic level about the grafts in Organ Transplant (OT), and may lead to a change in their management. Such a method will reduce the possibility that a diseased G, will arrive at the recipient hospital for implantation. Aim: Ergonomics of Digital Microscopy (DM) based on virtual slides, on Telemedicine Systems (TS) for Tele-Pathological (TPE) evaluation of the grafts (G) in organ transplantation (OT). Material and Methods: By experimental simulation, the ergonomics of DM for microscopic TPE of Renal Graft (RG), Liver Graft (LG) and Pancreatic Graft (PG) tissues is analyzed. In fact, this corresponded to the ergonomics of digital microscopy for TPE in OT by applying Virtual Slide (VS) system for graft tissue image capture, for remote diagnoses of possible microscopic inflammatory and/or neoplastic lesions. Experimentation included: a. Development of an OTE-TS similar Experimental Telemedicine System (Exp.-TS), b. Simulation of the integration of TS with the VS based microscopic TPE of RG, LG and PG applying DM. Simulation of the DM based TPE was performed by 2 specialists on a total of 238 human Renal Graft (RG), 172 Liver Graft (LG) and 108 Pancreatic Graft (PG) tissues digital microscopic images for inflammatory and neoplastic lesions on four electronic spaces of the four used TS. Results: Statistical analysis of specialist‘s answers about the ability to diagnose accurately the diseased RG, LG and PG tissues on the electronic space among four TS (A,B,C,D) showed that DM on TS for TPE in OT is elaborated perfectly on the ES of a Desktop, followed by the ES of the applied Exp.-TS. Tablet and Mobile-Phone ES seem significantly risky for the application of DM in OT (p<.001). Conclusion: To make the largest reduction in errors and adverse events referring to the quality of the grafts, it will take application of human factors engineering to procurement, design, audit, and aware ness-raising activities. Consequently, it will take an investment in new training, people, and other changes to management activities for DM in OT. The simulating VS based TPE with DM of RG, LG and PG tissues after retrieval; seem feasible and reliable and dependable on the size of the electronic space of the applied TS, for remote prevention of diseased grafts from being retrieved and/or sent to the recipient hospital and for post-grafting and pre-transplant planning.

Keywords: Organ Transplantation, Tele-Pathology, Digital Microscopy, Virtual Slides.

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Authors: Amogh Katti, J. Sai Asritha, D. Nivedh, M. Kalyan Srinivas, B. Somnath Chakravarthi

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Today's modern education system uses Learning Management System (LMS) portals for the scoring and grading of student performances, to maintain student records, and teachers are instructed to accept assignments through online submissions of .pdf, .doc, .ppt, etc. There is a risk of data tampering in the traditional portals; we will apply the Blockchain model instead of this traditional model to avoid data tampering and also provide a decentralized mechanism for overall fairness. Blockchain technology is a better and also recommended model because of the following features: consensus mechanism, decentralized system, cryptographic encryption, smart contracts, Ethereum blockchain. The proposed system ensures data integrity and tamper-proof assignment submission and grading, which will be helpful for both students and also educators.

Keywords: Education technology, learning management system, decentralized applications, blockchain.

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Authors: Aspasia Koutsokosta, Stefanos Katsavounis

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This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of the CSC modeling research accommodates conceptual or process models which present general management frameworks and do not relate to acknowledged soft Operations Research methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, objectives, modeling approach, solution methods and software used. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop optimization models for integrated CSCM. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without translating the generic concepts to the context of construction industry.

Keywords: Construction supply chain management, modeling, operations research, optimization and simulation.

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Authors: Rotchanakitumnuai, Siriluck

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The objectives of the study are to examine the determinants of ERP implementation success factors of ERP implementation. The result indicates that large scale ERP implementation success consist of eight factors: project management competence, knowledge sharing, ERP system quality , understanding, user involvement, business process re-engineering, top management support, organization readiness.

Keywords: large scale ERP, implementation success factors, Thailand

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Authors: Keunhong Chae, Seokho Yoon

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We address a new integer frequency offset (IFO) estimation scheme with an aid of a pilot for orthogonal frequency division multiplexing systems. After correlating each continual pilot with a predetermined scattered pilot, the correlation value is again correlated to alleviate the influence of the timing offset. From numerical results, it is demonstrated that the influence of the timing offset on the IFO estimation is significantly decreased.

Keywords: Estimation, integer frequency offset, OFDM, timing offset.

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Authors: Amaral, António, Araújo, Madalena

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This paper seeks to give a general idea of the universe of project portfolio management, from its multidisciplinary nature, to the many challenges it raises, passing through the different techniques, models and tools used to solve the multiple problems known. It is intended to contribute to the clarification, with great depth, of the impacts and relationships involved in managing the projects- portfolio. It aims at proposing a technique for the project alignment with the organisational strategy, in order to select projects that later on will be considered in the analysis and selection of the portfolio. We consider the development of a methodology for assessing the project alignment index very relevant in the global market scenario. It can help organisations to gain a greater awareness of market dynamics, speed up the decision process and increase its consistency, thus enabling the strategic alignment and the improvement of the organisational performance.

Keywords: Project Portfolio Management Cycle, Project Portfolio Selection, Resource Assignment, Strategy Alignment technique

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Authors: M.G.A. Nassef, Linghan Li, C. Schenck, B. Kuhfuss

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Design and modeling of nonlinear systems require the knowledge of all inside acting parameters and effects. An empirical alternative is to identify the system-s transfer function from input and output data as a black box model. This paper presents a procedure using least squares algorithm for the identification of a feed drive system coefficients in time domain using a reduced model based on windowed input and output data. The command and response of the axis are first measured in the first 4 ms, and then least squares are applied to predict the transfer function coefficients for this displacement segment. From the identified coefficients, the next command response segments are estimated. The obtained results reveal a considerable potential of least squares method to identify the system-s time-based coefficients and predict accurately the command response as compared to measurements.

Keywords: feed drive systems, least squares algorithm, onlineparameter identification, short time window

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Authors: Ammar Mahjoubi, Ridha Fethi Mechlouch, Belgacem Mahdhaoui, Ammar Ben Brahim

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This purpose of this paper is to develop and validate a model to accurately predict the cell temperature of a PV module that adapts to various mounting configurations, mounting locations, and climates while only requiring readily available data from the module manufacturer. Results from this model are also compared to results from published cell temperature models. The models were used to predict real-time performance from a PV water pumping systems in the desert of Medenine, south of Tunisia using 60-min intervals of measured performance data during one complete year. Statistical analysis of the predicted results and measured data highlight possible sources of errors and the limitations and/or adequacy of existing models, to describe the temperature and efficiency of PV-cells and consequently, the accuracy of performance of PV water pumping systems prediction models.

Keywords: Temperature of a photovoltaic module, Predicted models, PV water pumping systems efficiency, Simulation, Desert of southern Tunisia.

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Authors: K. Schmidt, Z. Miodrag, C. Geiger

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Performance Measurement is still a difficult task for forwarding companies. This is caused on the one hand by missing resources and on the other hand by missing tools. The research project “Management Information System for Logistics Service Providers" aims for closing the gap between needed and disposable solutions. Core of the project is the development

Keywords: Forwarder, Logistics, Management Information, Performance Measurement.

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Authors: Mert Bal, Hayri Sever, Oya Kalıpsız

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Medical Decision Support Systems (MDSSs) are sophisticated, intelligent systems that can provide inference due to lack of information and uncertainty. In such systems, to model the uncertainty various soft computing methods such as Bayesian networks, rough sets, artificial neural networks, fuzzy logic, inductive logic programming and genetic algorithms and hybrid methods that formed from the combination of the few mentioned methods are used. In this study, symptom-disease relationships are presented by a framework which is modeled with a formal concept analysis and theory, as diseases, objects and attributes of symptoms. After a concept lattice is formed, Bayes theorem can be used to determine the relationships between attributes and objects. A discernibility relation that forms the base of the rough sets can be applied to attribute data sets in order to reduce attributes and decrease the complexity of computation.

Keywords: Formal Concept Analysis, Rough Set Theory, Granular Computing, Medical Decision Support System.

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Authors: Daniella Kucsma

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The examination of the Public Service Organization’s performance evaluation includes several steps that help public organizations to develop a more efficient system. Public sector organizations have different characteristics than the competitive sector, so it can be stated that other/new elements become more important in their performance processes. The literature in this area is diverse, so highlighting an indicator system can be useful for introducing a system, but it is also worthwhile to measure the specific elements of the organization. In the case of a public service organization, due to the service obligation, it is usually possible to talk about a high number of users, so compliance is more difficult. For the organization, it is an important target to place great emphasis on the increase of service standards and the development of related processes. In this research, the health sector is given a prominent role, as it is a sensitive area where both organizational and individual performance is important for all participants. As a primary step, the content of the strategy is decisive, as this is important for the efficient structure of the process. When designing any system, it is important to review the expectations of the stakeholders, as this is primary when considering the design. The goal of this paper is to build the foundations of a performance management and indexing framework that can help a hospital to provide effective feedback and a direction that is important in assessing and developing a service and can become a management philosophy.

Keywords: health sector, public sector, performance management, strategy

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Authors: Samah Jawad Jabari

Abstract:

Water is the most important and valuable resource not only for human life but also for all living things on the planet. The water supply utilities should fulfill the water requirement quantitatively and qualitatively. Drinking water systems are exposed to both natural (hurricanes and flood) and manmade hazards (risks) that are common in Palestine. Non-Revenue Water (NRW) is a manmade risk which remains a major concern in Palestine, as the NRW levels are estimated to be at a high level. In this research, Hebron city water distribution network was taken as a case study to estimate and audit the NRW levels. The research also investigated the state of the existing water distribution system in the study area by investigating the water losses and obtained more information on NRW prevention and management practices. Data and information have been collected from the Palestinian Water Authority (PWA) and Hebron Municipality (HM) archive. In addition to that, a questionnaire has been designed and administered by the researcher in order to collect the necessary data for water auditing. The questionnaire also assessed the views of stakeholder in PWA and HM (staff) on the current status of the NRW in the Hebron water distribution system. The important result obtained by this research shows that NRW in Hebron city was high and in excess of 30%. The main factors that contribute to NRW were the inaccuracies in billing volumes, unauthorized consumption, and the method of estimating consumptions through faulty meters. Policy for NRW reduction is available in Palestine; however, it is clear that the number of qualified staff available to carry out the activities related to leak detection is low, and that there is a lack of appropriate technologies to reduce water losses and undertake sufficient system maintenance, which needs to be improved to enhance the performance of the network and decrease the level of NRW losses.

Keywords: Non-revenue water, water auditing, leak detection, water meters.

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Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

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The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

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Authors: Daniela Grădinaru, Iuliana Georgescu, Loredana Huţanu (Toma), Mihai-Bogdan Afrăsinei

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This article aims to analyze the situation of Romanian companies from an environmental point of view. Environmental issues are addressed very often nowadays, and they reach and affect every domain, including the economical one. Implementing an environmental management system will not only help the companies to comply with laws and regulations, but, above all, will offer them an important competitive advantage.

Keywords: Environmental management system, environmental reporting, environmental expenses, sustainable development.

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Authors: Nevine M. Labib, Michael N. Malek

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Data Mining aims at discovering knowledge out of data and presenting it in a form that is easily comprehensible to humans. One of the useful applications in Egypt is the Cancer management, especially the management of Acute Lymphoblastic Leukemia or ALL, which is the most common type of cancer in children. This paper discusses the process of designing a prototype that can help in the management of childhood ALL, which has a great significance in the health care field. Besides, it has a social impact on decreasing the rate of infection in children in Egypt. It also provides valubale information about the distribution and segmentation of ALL in Egypt, which may be linked to the possible risk factors. Undirected Knowledge Discovery is used since, in the case of this research project, there is no target field as the data provided is mainly subjective. This is done in order to quantify the subjective variables. Therefore, the computer will be asked to identify significant patterns in the provided medical data about ALL. This may be achieved through collecting the data necessary for the system, determimng the data mining technique to be used for the system, and choosing the most suitable implementation tool for the domain. The research makes use of a data mining tool, Clementine, so as to apply Decision Trees technique. We feed it with data extracted from real-life cases taken from specialized Cancer Institutes. Relevant medical cases details such as patient medical history and diagnosis are analyzed, classified, and clustered in order to improve the disease management.

Keywords: Data Mining, Decision Trees, Knowledge Discovery, Leukemia.

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Authors: Ashkan Ebadi, Adam Krzyzak

Abstract:

Recommender systems, also known as recommender engines, have become an important research area and are now being applied in various fields. In addition, the techniques behind the recommender systems have been improved over the time. In general, such systems help users to find their required products or services (e.g. books, music) through analyzing and aggregating other users’ activities and behavior, mainly in form of reviews, and making the best recommendations. The recommendations can facilitate user’s decision making process. Despite the wide literature on the topic, using multiple data sources of different types as the input has not been widely studied. Recommender systems can benefit from the high availability of digital data to collect the input data of different types which implicitly or explicitly help the system to improve its accuracy. Moreover, most of the existing research in this area is based on single rating measures in which a single rating is used to link users to items. This paper proposes a highly accurate hotel recommender system, implemented in various layers. Using multi-aspect rating system and benefitting from large-scale data of different types, the recommender system suggests hotels that are personalized and tailored for the given user. The system employs natural language processing and topic modelling techniques to assess the sentiment of the users’ reviews and extract implicit features. The entire recommender engine contains multiple sub-systems, namely users clustering, matrix factorization module, and hybrid recommender system. Each sub-system contributes to the final composite set of recommendations through covering a specific aspect of the problem. The accuracy of the proposed recommender system has been tested intensively where the results confirm the high performance of the system.

Keywords: Tourism, hotel recommender system, hybrid, implicit features.

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