Search results for: career decision efficacy
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1779

Search results for: career decision efficacy

729 Risk Classification of SMEs by Early Warning Model Based on Data Mining

Authors: Nermin Ozgulbas, Ali Serhan Koyuncugil

Abstract:

One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an Early Warning System (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7,853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation.

Keywords: Early Warning Systems, Data Mining, Financial Risk, SMEs.

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728 A New Method for Detection of Artificial Objects and Materials from Long Distance Environmental Images

Authors: H. Dujmic, V. Papic, H. Turic

Abstract:

The article presents a new method for detection of artificial objects and materials from images of the environmental (non-urban) terrain. Our approach uses the hue and saturation (or Cb and Cr) components of the image as the input to the segmentation module that uses the mean shift method. The clusters obtained as the output of this stage have been processed by the decision-making module in order to find the regions of the image with the significant possibility of representing human. Although this method will detect various non-natural objects, it is primarily intended and optimized for detection of humans; i.e. for search and rescue purposes in non-urban terrain where, in normal circumstances, non-natural objects shouldn-t be present. Real world images are used for the evaluation of the method.

Keywords: Landscape surveillance, mean shift algorithm, image segmentation, target detection.

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727 Mind Your Product-Market Strategy on Selecting Marketing Inputs: An Uncertainty Approach in Indian Context

Authors: Susmita Ghosh, Bhaskar Bhowmick

Abstract:

Market is an important factor for start-ups to look into during decision-making in product development and related areas. Emerging country markets are more uncertain in terms of information availability and institutional supports. The literature review of market uncertainty reveals the need for identifying factors representing the market uncertainty. This paper identifies factors for market uncertainty using Exploratory Factor Analysis (EFA) and confirmed the number of factor retention using an alternative factor retention criterion ‘Parallel Analysis’. 500 entrepreneurs, engaged in start-ups from all over India participated in the study. This paper concludes with the factor structure of ‘market uncertainty’ having dimensions of uncertainty in industry orientation, uncertainty in customer orientation and uncertainty in marketing orientation.

Keywords: Uncertainty, market, orientation, competitor, demand.

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726 Optimal Resource Configuration and Allocation Planning Problem for Bottleneck Machines and Auxiliary Tools

Authors: Yin-Yann Chen, Tzu-Ling Chen

Abstract:

This study presents the case of an actual Taiwanese semiconductor assembly and testing manufacturer. Three major bottleneck manufacturing processes, namely, die bond, wire bond, and molding, are analyzed to determine how to use finite resources to achieve the optimal capacity allocation. A medium-term capacity allocation planning model is developed by considering the optimal total profit to satisfy the promised volume demanded by customers and to obtain the best migration decision among production lines for machines and tools. Finally, sensitivity analysis based on the actual case is provided to explore the effect of various parameter levels.

Keywords: Capacity planning, capacity allocation, machine migration, resource configuration.

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725 The Analysis of Different Classes of Weighted Fuzzy Petri Nets and Their Features

Authors: Yurii Bloshko, Oksana Olar

Abstract:

This paper presents the analysis of six different classes of Petri nets: fuzzy Petri nets (FPN), generalized fuzzy Petri nets (GFPN), parameterized fuzzy Petri nets (PFPN), T2GFPN, flexible generalized fuzzy Petri nets (FGFPN), binary Petri nets (BPN). These classes were simulated in the special software PNeS® for the analysis of its pros and cons on the example of models which are dedicated to the decision-making process of passenger transport logistics. The paper includes the analysis of two approaches: when input values are filled with the experts’ knowledge; when fuzzy expectations represented by output values are added to the point. These approaches fulfill the possibilities of triples of functions which are replaced with different combinations of t-/s-norms.

Keywords: Fuzzy petri net, intelligent computational techniques, knowledge representation, triangular norms.

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724 Meta Random Forests

Authors: Praveen Boinee, Alessandro De Angelis, Gian Luca Foresti

Abstract:

Leo Breimans Random Forests (RF) is a recent development in tree based classifiers and quickly proven to be one of the most important algorithms in the machine learning literature. It has shown robust and improved results of classifications on standard data sets. Ensemble learning algorithms such as AdaBoost and Bagging have been in active research and shown improvements in classification results for several benchmarking data sets with mainly decision trees as their base classifiers. In this paper we experiment to apply these Meta learning techniques to the random forests. We experiment the working of the ensembles of random forests on the standard data sets available in UCI data sets. We compare the original random forest algorithm with their ensemble counterparts and discuss the results.

Keywords: Random Forests [RF], ensembles, UCI.

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723 Forecasting Rainfall in Thailand: A Case Study of Nakhon Ratchasima Province

Authors: N. Sopipan

Abstract:

In this paper, we study the rainfall using a time series for weather stations in Nakhon Ratchasima province in Thailand by various statistical methods to enable us to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. The ARIMA and Holt-Winter models were built on the basis of exponential smoothing. All the models proved to be adequate. Therefore it is possible to give information that can help decision makers establish strategies for the proper planning of agriculture, drainage systems and other water resource applications in Nakhon Ratchasima province. We obtained the best performance from forecasting with the ARIMA Model(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, Exponential Smoothing, Holt- Winter model.

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722 Optimization Based Obstacle Avoidance

Authors: R. Dariani, S. Schmidt, R. Kasper

Abstract:

Based on a non-linear single track model which describes the dynamics of vehicle, an optimal path planning strategy is developed. Real time optimization is used to generate reference control values to allow leading the vehicle alongside a calculated lane which is optimal for different objectives such as energy consumption, run time, safety or comfort characteristics. Strict mathematic formulation of the autonomous driving allows taking decision on undefined situation such as lane change or obstacle avoidance. Based on position of the vehicle, lane situation and obstacle position, the optimization problem is reformulated in real-time to avoid the obstacle and any car crash.

Keywords: Autonomous driving, Obstacle avoidance, Optimal control, Path planning.

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721 Conceptual Design of a Wi-Fi and GPS Based Robotic Library Using an Intelligent System

Authors: M. S. Sreejith, Steffy Joy, Abhishesh Pal, Beom-Sahng Ryuh, V. R. Sanal Kumar

Abstract:

In this paper, an attempt has been made for the design of a robotic library using an intelligent system. The robot works on the ARM microprocessor, motor driver circuit with 5 degrees of freedom with Wi-Fi and GPS based communication protocol. The authenticity of the library books is controlled by RFID. The proposed robotic library system is facilitated with embedded system and ARM. In this library issuance system, the previous potential readers’ authentic review reports have been taken into consideration for recommending suitable books to the deserving new users and the issuance of books or periodicals is based on the users’ decision. We have conjectured that the Wi-Fi based robotic library management system would allow fast transaction of books issuance and it also produces quality readers.

Keywords: GPS based based robotic library, library management system, robotic library, Wi-Fi library.

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720 Explorations in the Role of Emotion in Moral Judgment

Authors: Arthur Yan

Abstract:

Recent theorizations on the cognitive process of moral judgment have focused on the role of intuitions and emotions, marking a departure from previous emphasis on conscious, step-by-step reasoning. My study investigated how being in a disgusted mood state affects moral judgment. Participants were induced to enter a disgusted mood state through listening to disgusting sounds and reading disgusting descriptions. Results shows that they, when compared to control who have not been induced to feel disgust, are more likely to endorse actions that are emotionally aversive but maximizes utilitarian return The result is analyzed using the 'emotion-as-information' approach to decision making. The result is consistent with the view that emotions play an important role in determining moral judgment.

Keywords: Disgust, mood induction, moral judgment, emotion-as-information.

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719 Continuous Fixed Bed Reactor Application for Decolourization of Textile Effluent by Adsorption on NaOH Treated Eggshell

Authors: M. Chafi, S. Akazdam, C. Asrir, L. Sebbahi, B. Gourich, N. Barka, M. Essahli

Abstract:

Fixed bed adsorption has become a frequently used industrial application in wastewater treatment processes. Various low cost adsorbents have been studied for their applicability in treatment of different types of effluents. In this work, the intention of the study was to explore the efficacy and feasibility for azo dye, Acid Orange 7 (AO7) adsorption onto fixed bed column of NaOH Treated eggshell (TES). The effect of various parameters like flow rate, initial dye concentration, and bed height were exploited in this study. The studies confirmed that the breakthrough curves were dependent on flow rate, initial dye concentration solution of AO7 and bed depth. The Thomas, Yoon–Nelson, and Adams and Bohart models were analysed to evaluate the column adsorption performance. The adsorption capacity, rate constant and correlation coefficient associated to each model for column adsorption was calculated and mentioned. The column experimental data were fitted well with Thomas model with coefficients of correlation R2 ≥0.93 at different conditions but the Yoon–Nelson, BDST and Bohart–Adams model (R2=0.911), predicted poor performance of fixed-bed column. The (TES) was shown to be suitable adsorbent for adsorption of AO7 using fixed-bed adsorption column.

Keywords: Adsorption models, acid orange 7, bed depth, breakthrough, dye adsorption, fixed-bed column, treated eggshell.

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718 Unified Structured Process for Health Analytics

Authors: Supunmali Ahangama, Danny Chiang Choon Poo

Abstract:

Health analytics (HA) is used in healthcare systems for effective decision making, management and planning of healthcare and related activities. However, user resistances, unique position of medical data content and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. Success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose a HA process model with features from rational unified process (RUP) model and agile methodology.

Keywords: Agile methodology, health analytics, unified process model, UML.

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717 Hepatoprotective Effect of Oleuropein against Cisplatin-Induced Liver Damage in Rat

Authors: Salim Cerig, Fatime Geyikoglu, Murat Bakir, Suat Colak, Merve Sonmez, Kubra Koc

Abstract:

Cisplatin (CIS) is one of the most effective an anticancer drug and also toxic to cells by activating oxidative stress. Oleuropein (OLE) has key role against oxidative stress in mammalian cells, but the role of this antioxidant in the toxicity of CIS remains unknown. The aim of the present study was to investigate the efficacy of OLE on CIS-induced liver damages in male rats. With this aim, male Sprague Dawley rats were randomly assigned to one of eight groups: Control group; the group treated with 7 mg/kg/day CIS; the groups treated with 50, 100 and 200 mg/kg/day OLE (i.p.); and the groups treated with OLE for three days starting at 24 h following CIS injection. After 4 days of injections, serum was provided to assess the blood AST, ALT and LDH values. The liver tissues were removed for histological, biochemical (TAC, TOS and MDA) and genotoxic evaluations. In the CIS treated group, the whole liver tissue showed significant histological changes. Also, CIS significantly increased both the incidence of oxidative stress and the induction of 8-hydroxy-deoxyguanosine (8-OH-dG). Moreover, the rats taking CIS have abnormal results on liver function tests. However, these parameters reached to the normal range after administration of OLE for 3 days. Finally, OLE demonstrated an acceptable high potential and was effective in attenuating CIS-induced liver injury. In this trial, the 200 mg/kg dose of OLE firstly appeared to induce the most optimal protective response.

Keywords: Antioxidant response, cisplatin, histology, liver, oleuropein, 8-OhdG.

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716 Survey on Arabic Sentiment Analysis in Twitter

Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

Abstract:

Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: Big Data, Social Networks, Sentiment Analysis.

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715 A Survey of Discrete Facility Location Problems

Authors: Z. Ulukan, E. Demircioğlu

Abstract:

Facility location is a complex real-world problem which needs a strategic management decision. This paper provides a general review on studies, efforts and developments in Facility Location Problems which are classical optimization problems having a wide-spread applications in various areas such as transportation, distribution, production, supply chain decisions and telecommunication. Our goal is not to review all variants of different studies in FLPs or to describe very detailed computational techniques and solution approaches, but rather to provide a broad overview of major location problems that have been studied, indicating how they are formulated and what are proposed by researchers to tackle the problem. A brief, elucidative table based on a grouping according to “General Problem Type” and “Methods Proposed” used in the studies is also presented at the end of the work.

Keywords: Discrete location problems, exact methods, heuristic algorithms, single source capacitated facility location problems.

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714 Application of Multi-objective Optimization Packages in Design of an Evaporator Coil

Authors: A.Mosavi

Abstract:

A novel methodology has been used to design an evaporator coil of a refrigerant. The methodology used is through a complete Computer Aided Design /Computer Aided Engineering approach, by means of a Computational Fluid Dynamic/Finite Element Analysis model which is executed many times for the thermal-fluid exploration of several designs' configuration by an commercial optimizer. Hence the design is carried out automatically by parallel computations, with an optimization package taking the decisions rather than the design engineer. The engineer instead takes decision regarding the physical settings and initializing of the computational models to employ, the number and the extension of the geometrical parameters of the coil fins and the optimization tools to be employed. The final design of the coil geometry found to be better than the initial design.

Keywords: Multi-objective shape optimization, Heat Transfer, multi-physics structures, modeFRONTIER

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713 Clinical Factors of Quality Switched Ruby Laser Therapy for Lentigo Depigmentation

Authors: SunWoo Lee, TaeBum Lee, YoonHwa Park, YooJeong Kim

Abstract:

Solar lentigines appear predominantly on chronically sun-exposed areas of skin, such as the face and the back of the hands. Among the several ways to lentigines treatment, quality-switched lasers are well-known effective treatment for removing solar lentigines. The present pilot study was therefore designed to assess the efficacy of quality-switched ruby laser treatment of such lentigines compare between pretreatment and posttreatment of skin brightness. Twenty-two adults with chronic sun-damaged skin (mean age 52.8 years, range 37–74 years) were treated at the Korean site. A 694 nm Q-switched ruby laser was used, with the energy density set from 1.4 to 12.5 J/cm2, to treat solar lentigines. Average brightness of skin color before ruby laser treatment was 137.3 and its skin color was brightened after ruby laser treatment by 150.5. Also, standard deviation of skin color was decreased from 17.8 to 16.4. Regarding the multivariate model, age and energy were identified as significant factors for skin color brightness change in lentigo depigmentation by ruby laser treatment. Their respective odds ratios were 1.082 (95% CI, 1.007–1.163), and 1.431 (95% CI, 1.051–1.946). Lentigo depigmentation treatment using ruby lasers resulted in a high performance in skin color brightness. Among the relative factors involve with ruby laser treatment, age and energy were the most effective factors which skin color change to brighter than pretreatment.

Keywords: Depigmentation, lentigo, quality switched ruby laser, skin color.

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712 Case Study Analysis of 2017 European Railway Traffic Management Incident: The Application of System for Investigation of Railway Interfaces Methodology

Authors: Sanjeev Kumar Appicharla

Abstract:

This paper presents the results of the modelling and analysis of the European Railway Traffic Management (ERTMS) safety critical incident to raise awareness of biases in systems engineering process on the Cambrian Railway in the UK using the RAIB 17/2019 as a primary input. The RAIB, the UK independent accident investigator, published the Report- RAIB 17/2019 giving the details of their investigation of the focal event in the form of immediate cause, causal factors and underlying factors and recommendations to prevent a repeat of the safety-critical incident on the Cambrian Line. The Systems for Investigation of Railway Interfaces (SIRI) is the Methodology used to model and analyse the safety-critical incident. The SIRI Methodology uses the Swiss Cheese Model to model the incident and identify latent failure conditions (potentially less than adequate conditions) by means of the Management Oversight and Risk Tree technique. The benefits of the SIRI Methodology are threefold: first is that it incorporates “Heuristics and Biases” approach, in the Management Oversight and Risk Tree technique to identify systematic errors. Civil engineering and programme management railway professionals are aware of role “optimism bias” plays in programme cost overruns and are aware of bow tie (fault and event tree) model-based safety risk modelling technique. However, the role of systematic errors due to “Heuristics and Biases” is not appreciated as yet. This overcomes the problems of omission of human and organisational factors from accident analysis. Second, the scope of the investigation includes all levels of the socio-technical system, including government, regulatory, railway safety bodies, duty holders, signalling firms and transport planners, and front-line staff such that lessons learned at the decision making and implementation level as well. Third, the author’s past accident case studies are supplemented with research pieces of evidence drawn from the practitioner’s and academic researchers’ publications as well. This is to discuss the role of system thinking to improve the decision making and risk management processes and practices in the IEC 15288 Systems Engineering standard, and in the industrial context such as the GB railways and Artificial Intelligence (AI) contexts as well.

Keywords: Accident analysis, AI algorithm internal audit, bounded rationality, Byzantine failures, heuristics and biases approach.

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711 Artificial Neural Networks for Cognitive Radio Network: A Survey

Authors: Vishnu Pratap Singh Kirar

Abstract:

The main aim of a communication system is to achieve maximum performance. In Cognitive Radio any user or transceiver has ability to sense best suitable channel, while channel is not in use. It means an unlicensed user can share the spectrum of a licensed user without any interference. Though, the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: Artificial Neural Network, Cognitive Radio, Cognitive Radio Networks, Back Propagation, Spectrum Sensing.

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710 Investment Prediction Using Simulation

Authors: Hussam Al-Shorman, Yosef Hasan Jbara

Abstract:

A business case is a proposal for an investment initiative to satisfy business and functional requirements. The business case provides the foundation for tactical decision making and technology risk management. It helps to clarify how the organization will use its resources in the best way by providing justification for investment of resources. This paper describes how simulation was used for business case benefits and return on investment for the procurement of 8 production machines. With investment costs of about 4.7 million dollars and annual operating costs of about 1.3 million, we needed to determine if the machines would provide enough cost savings and cost avoidance. We constructed a model of the existing factory environment consisting of 8 machines and subsequently, we conducted average day simulations with light and heavy volumes to facilitate planning decisions required to be documented and substantiated in the business case.

Keywords: Investment cost, business case, return on investment, simulation.

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709 Simulation of Activity Stream inside Energy Social Business Environment using Assemblage Theory and Simplicial Complex Tool

Authors: Eddie Soulier, Philippe Calvez, Florie Bugeaud, Francis Rousseaux, Jacky Legrand

Abstract:

Social, mobility and information aggregation inside business environment need to converge to reach the next step of collaboration to enhance interaction and innovation. The following article is based on the “Assemblage" concept seen as a framework to formalize new user interfaces and applications. The area of research is the Energy Social Business Environment, especially the Energy Smart Grids, which are considered as functional and technical foundations of the revolution of the Energy Sector of tomorrow. The assemblages are modelized by means of mereology and simplicial complexes. Its objective is to offer new central attention and decision-making tools to end-users.

Keywords: Activity Streams, Assemblage, Energy Social Business Environment, Simplicial Complex, Smart Grid

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708 Potential of Salvia sclarea L. for Phytoremediation of Soils Contaminated with Heavy Metals

Authors: Violina R. Angelova, Radka V. Ivanova, Givko M. Todorov, Krasimir I. Ivanov

Abstract:

A field study was conducted to evaluate the efficacy of Salvia sclarea L. for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. The content of heavy metals in different parts of Salvia sclarea L. (roots, stems, leaves and inflorescences) was determined by ICP. The essential oil of the Salvia sclarea L. was obtained by steam distillation in laboratory conditions and was analyzed for heavy metals and its chemical composition was determined. Salvia sclarea L. is a plant which is tolerant to heavy metals and can be grown on contaminated soils. Based on the obtained results and using the most common criteria, Salvia sclarea L. can be classified as Pb hyperaccumulator and Cd and Zn accumulators, therefore, this plant has suitable potential for the phytoremediation of heavy metal contaminated soils. Favorable is also the fact that heavy metals do not influence the development of the Salvia sclarea L., as well as on the quality and quantity of the essential oil. For clary sage oil obtained from the processing of clary sage grown on highly contaminated soils, its key odour-determining ingredients meet the quality requirements of the European Pharmacopoeia and BS ISO 7609 regarding Bulgarian clary sage oil and/or have values that are close to the limits of these standards. The possibility of further industrial processing will make Salvia sclarea L. an economically interesting crop for farmers of phytoextraction technology.

Keywords: Clary sage, heavy metals, phytoremediation, polluted soils.

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707 Modified Data Mining Approach for Defective Diagnosis in Hard Disk Drive Industry

Authors: S. Soommat, S. Patamatamkul, T. Prempridi, M. Sritulyachot, P. Ineure, S. Yimman

Abstract:

Currently, slider process of Hard Disk Drive Industry become more complex, defective diagnosis for yield improvement becomes more complicated and time-consumed. Manufacturing data analysis with data mining approach is widely used for solving that problem. The existing mining approach from combining of the KMean clustering, the machine oriented Kruskal-Wallis test and the multivariate chart were applied for defective diagnosis but it is still be a semiautomatic diagnosis system. This article aims to modify an algorithm to support an automatic decision for the existing approach. Based on the research framework, the new approach can do an automatic diagnosis and help engineer to find out the defective factors faster than the existing approach about 50%.

Keywords: Slider process, Defective diagnosis and Data mining.

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706 Environmental Issues Related to Nuclear Desalination

Authors: V. Anastasov, I.Khamis

Abstract:

The paper presents an overview of environmental issues that may be expected with nuclear desalination. The analysis of coupling nuclear power with desalination plants indicates that adverse marine impacts can be mitigated with alternative intake designs or cooling systems. The atmospheric impact of desalination may be greatly reduced through the coupling with nuclear power, while maximizing the socio-economic benefit for both processes. The potential for tritium contamination of the desalinated water was reviewed. Experience with the systems and practices related to the radiological quality of the product water, shows no examples of cross-contamination. Furthermore, the indicators for the public acceptance of nuclear desalination, as one of the most important sustainability aspects of any such large project, show a positive trend. From the data collected, a conclusion is made that nuclear desalination should be supported by decision-makers.

Keywords: Environmental impacts, nuclear desalination, publicacceptance, tritium.

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705 Fifth Order Variable Step Block Backward Differentiation Formulae for Solving Stiff ODEs

Authors: S.A.M. Yatim, Z.B. Ibrahim, K.I. Othman, F. Ismail

Abstract:

The implicit block methods based on the backward differentiation formulae (BDF) for the solution of stiff initial value problems (IVPs) using variable step size is derived. We construct a variable step size block methods which will store all the coefficients of the method with a simplified strategy in controlling the step size with the intention of optimizing the performance in terms of precision and computation time. The strategy involves constant, halving or increasing the step size by 1.9 times the previous step size. Decision of changing the step size is determined by the local truncation error (LTE). Numerical results are provided to support the enhancement of method applied.

Keywords: Backward differentiation formulae, block backwarddifferentiation formulae, stiff ordinary differential equation, variablestep size.

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704 Face Recognition Using Discrete Orthogonal Hahn Moments

Authors: Fatima Akhmedova, Simon Liao

Abstract:

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, nonredundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: Face Recognition, Hahn moments, Recognition-by-parts, Time-lapse.

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703 In Search of Bauman’s Moral Impulse in Shadow Factories of China

Authors: Akram Hatami, Naser Firoozi, Vesa Puhakka

Abstract:

Ethics and responsibility are rapidly becoming a distinguishing feature of organizations. In this paper, we analyze ethics and responsibility in shadow factories in China. We engage ourselves with Bauman’s moral impulse perspective because his idea can contextualize ethics and responsibility. Moral impulse is a feeling of a selfless, infinite and unconditional responsibility towards, and care for, Others. We analyze a case study from a secondary data source because, for such a critical phenomenon as business ethics in shadow factories, collecting primary data is difficult, since they are unregistered factories. We argue that there has not been enough attention given to the ethics and responsibility in shadow factories in China. Our main goal is to demonstrate that, considering the Other, more importantly the employees, in ethical decision-making is a simple instruction beyond the narrow version of ethics by ethical codes and rules.

Keywords: Moral impulse, responsibility, shadow factories, the other.

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702 Potential of Safflower (Carthamus tinctorius L.) for Phytoremedation of Soils Contaminated with Heavy Metals

Authors: Violina R. Angelova, Vanja I. Akova, Stefan V. Krustev, Krasimir I. Ivanov

Abstract:

A field study was conducted to evaluate the efficacy of safflower plant for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. Field experiments with randomized complete block design with five treatments (control, compost amendments added at 20 and 40 t/daa, and vermicompost amendments added at 20 and 40 t/daa) were carried out. The quality of safflower seeds and oil (heavy metals and fatty acid composition) were determined. Tested organic amendments significantly influenced the chemical composition of safflower seeds and oil. The compost and vermicompost treatments significantly reduced heavy metals concentration in safflower seeds and oils, but the effect differed among them. Addition of vermicompost and compost leads to an increase in the content of palmitic acid and linoleic acid, and a decrease in the stearic and oleic acids compared with the control. A significant increase in the quantity of saturated acids was observed in the variants with 20 t/daa of compost and 20 t/daa of vermicompost (9.1 and 8.9% relative to the control). Safflower is a plant which is tolerant to heavy metals and can be successfully used in the phytoremediation of heavy metal contaminated soils. The processing of seeds to oil and using the obtained oil for nutritional purposes will greatly reduce the cost of phytoremediation.

Keywords: Heavy metals, organic amendments, phytoremediation, safflower.

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701 An Optimal Bayesian Maintenance Policy for a Partially Observable System Subject to Two Failure Modes

Authors: Akram Khaleghei Ghosheh Balagh, Viliam Makis, Leila Jafari

Abstract:

In this paper, we present a new maintenance model for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model. A cost-optimal Bayesian control policy is developed for maintaining the system. The control problem is formulated in the semi-Markov decision process framework. An effective computational algorithm is developed, illustrated by a numerical example.

Keywords: Partially observable system, hidden Markov model, competing risks, multivariate Bayesian control.

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700 Coordination on Agrifood Supply Chain

Authors: Martha Liliana Reina Usuga, Wilson Adarme Jaimes, Oscar Eduardo Suarez

Abstract:

Coordinated supply chain represents major challenges for the different actors involved in it, because each agent responds to individual interests. The paper presents a framework with the reviewed literature regarding the system's decision structure and nature of demand. Later, it characterizes an agri food supply chain in the Central Region of Colombia, it responds to a decentralized distribution system and a stochastic demand. Finally, the paper recommends coordinating the chain based on shared information, and mechanisms for each agent, as VMI (vendor-managed inventory) strategy for farmer-buyer relationship, information system for farmers and contracts for transportation service providers.

Keywords: Agri-food supply chain, Coordination mechanisms, Decentralized distribution system, Supply chain coordination.

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