Search results for: Decision Making for cultural tourism

Authors: Z. Tasir, S. N. Kew, D. West, Z. Abdullah, D. Toohey

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Research on Learning Analytics is progressively developing in the higher education field by concentrating on the process of students' learning. Therefore, a research project between Malaysian and Australian Universities was initiated in 2015 to look at the use of Learning Analytics to support the development of teaching practice. The focal point of this article is to discuss and share the experiences of Malaysian and Australian universities in the process of developing the collaborative research on Learning Analytics. Three aspects of this will be discussed: 1) Establishing an international research project and team members, 2) cross-cultural understandings, and 3) ways of working in relation to the practicalities of the project. This article is intended to benefit other researchers by highlighting the challenges as well as the strategies used in this project to ensure such collaborative research succeeds.

Keywords: Academic research project, collaborative research, cross-cultural understanding, international research project.

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Authors: G. Kumaravelan, R. Sivakumar

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Modeling the behavior of the dialogue management in the design of a spoken dialogue system using statistical methodologies is currently a growing research area. This paper presents a work on developing an adaptive learning approach to optimize dialogue strategy. At the core of our system is a method formalizing dialogue management as a sequential decision making under uncertainty whose underlying probabilistic structure has a Markov Chain. Researchers have mostly focused on model-free algorithms for automating the design of dialogue management using machine learning techniques such as reinforcement learning. But in model-free algorithms there exist a dilemma in engaging the type of exploration versus exploitation. Hence we present a model-based online policy learning algorithm using interconnected learning automata for optimizing dialogue strategy. The proposed algorithm is capable of deriving an optimal policy that prescribes what action should be taken in various states of conversation so as to maximize the expected total reward to attain the goal and incorporates good exploration and exploitation in its updates to improve the naturalness of humancomputer interaction. We test the proposed approach using the most sophisticated evaluation framework PARADISE for accessing to the railway information system.

Keywords: Dialogue management, Learning automata, Reinforcement learning, Spoken dialogue system

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Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

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In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: Equivalent Martingale Measure, European Put Option, Girsanov Theorem, Martingales, Monte Carlo method, option price valuation, option price valuation formula.

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Authors: Pardeep Singh, Sanjay Sharma

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Content-Based Image Retrieval (CBIR) has been one on the most vivid research areas in the field of computer vision over the last 10 years. Many programs and tools have been developed to formulate and execute queries based on the visual or audio content and to help browsing large multimedia repositories. Still, no general breakthrough has been achieved with respect to large varied databases with documents of difering sorts and with varying characteristics. Answers to many questions with respect to speed, semantic descriptors or objective image interpretations are still unanswered. In the medical field, images, and especially digital images, are produced in ever increasing quantities and used for diagnostics and therapy. In several articles, content based access to medical images for supporting clinical decision making has been proposed that would ease the management of clinical data and scenarios for the integration of content-based access methods into Picture Archiving and Communication Systems (PACS) have been created. This paper gives an overview of soft computing techniques. New research directions are being defined that can prove to be useful. Still, there are very few systems that seem to be used in clinical practice. It needs to be stated as well that the goal is not, in general, to replace text based retrieval methods as they exist at the moment.

Keywords: CBIR, GA, Rough sets, CBMIR

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Authors: Jaouad Oukrich, Belaid Bouikhalene, Noureddine Askour

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This paper deals with the problem of management of information resources in libraries of the public institution Sultan Moulay Slimane University (SMSU) in order to analyze the satisfaction of the readers, and allow university leaders to make better strategic and instant decisions. For this, the integration of an integrated management decision library system is a priority program of higher education, as part of the Digital Morocco, which has a proactive policy to develop the use of new technologies information and communication in higher institutions. This operational information system can provide better services to the students and for the leaders. Our approach is to integrate the tools of business intelligence (BI) in the library management by using power BI.

Keywords: PMB, integrated library management system, ILMS, document, SMSU, power BI, satisfaction.

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Authors: Khondokar Farid Ahmmed, Robin Bown

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It is widely recognized that the formal financing of Small and Medium Size Enterprises (SMEs) by Private Commercial Banks (PCBs) is restricted. Due to changing financial market competition, SMEs are now important customers to PCBs in the member countries of the Asian Development Bank (ADB). Various initiatives in enhancing the efficiency of risk assessment of PCBs have failed in increasing financing accessibility in the traditional financing system where information asymmetry is a key constraint. In this circumstance, PCBs need to undertake a holistic approach. Holistic approach refers to methods that attempt to fundamentally change established traditions. To undertake holistic approach, this study intends to find the entire established financing culture between PCBs and SMEs in a new lens beyond the tradition on the basis of two basic questions: “What is the traditional lending culture between PCBs and SMEs” and “What could be potential role of PCBs to develop that culture where focusing on SME financing to PCBs". This study considered formal SME financing in Bangladesh by focusing on SMEs applying for their first loan. Bangladesh is a member country of ADB. The data collection method is semi-structured and we utilized face-to-face interviews with in-depth branch managers, higher officials and owner-managers of SME customers of PCBs and higher officials of SME Foundation and the Bangladesh central bank. Discourse analysis method was used for data analysis on the frame of thematic discussion fully based on participants’ views. The research found that branch managers and loan officers have a high level of power in assessing and financing decision-making. There is a changing attitude in PCB sector in requiring flexible collateral assets. Branch managers (Loan Officers) consider value of business prospect of owner-mangers as complementary of collateral assets. However, the study found the assessment process of business prospect is entirely unstructured and linked with socio-cultural settings that does not support PCBs’ changing manner in terms of collateral requirement. The study redefined and classified collateral assets to include all financing constructs in a structure. The degree of value of the collateral assets determines the degree of business prospects. This study suggested applying an outside classroom-learning paradigm such as “knowledge tour” to enhance the value of the kinds of collateral assets. This is the scope of PCBs in increasing SMEs’ financing eligibility in win-win basis. The findings and proposition could be effective in other ADB member countries and audiences in the field.

Keywords: CCA, financing, information asymmetry, PCA, PCB, financing.

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Authors: Vichai Rungreunganaun, Chirawat Woarawichai

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The objective of this research is to calculate the optimal inventory lot-sizing for each supplier and minimize the total inventory cost which includes joint purchase cost of the products, transaction cost for the suppliers, and holding cost for remaining inventory. Genetic algorithms (GAs) are applied to the multi-product and multi-period inventory lot-sizing problems with supplier selection under storage space. Also a maximum storage space for the decision maker in each period is considered. The decision maker needs to determine what products to order in what quantities with which suppliers in which periods. It is assumed that demand of multiple products is known over a planning horizon. The problem is formulated as a mixed integer programming and is solved with the GAs. The detailed computation results are presented.

Keywords: Genetic Algorithms, Inventory lot-sizing, Supplier selection, Storage space.

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Authors: F. Niazkar, N. Arab-Moghaddam

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In this research, effort was made to identify and evaluate barriers to the development of entrepreneurship among Iranian entrepreneur women who were graduated from universities. In this study, perspectives of thirty-seven available entrepreneur women were examined. In order to prepare questionnaires and receive knowledge about barriers among these women, seven cases of entrepreneur women took part in in-depth interviews. Then, to evaluate the importance of barriers, the researchers made a questionnaire with closed questions in which the barriers were classified into the following categories: personal-familial barriers; socio-cultural barriers; economic-financial-commercial barriers; and structural barriers. Entrepreneur women were requested to rate the importance of each item. The results indicated that there were different obstacles among entrepreneur women. The order of the important barriers was as fallow: economic-financial-commercial, structural, socio-cultural, and personal-familial.

Keywords: Barriers to Entrepreneurship, Entrepreneur Women

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Authors: Namal A. Senanayake, A. Beg, Withana C. Prasad

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This paper analyzes the patterns of the Monte Carlo data for a large number of variables and minterms, in order to characterize the circuit path length behavior. We propose models that are determined by training process of shortest path length derived from a wide range of binary decision diagram (BDD) simulations. The creation of the model was done use of feed forward neural network (NN) modeling methodology. Experimental results for ISCAS benchmark circuits show an RMS error of 0.102 for the shortest path length complexity estimation predicted by the NN model (NNM). Use of such a model can help reduce the time complexity of very large scale integrated (VLSI) circuitries and related computer-aided design (CAD) tools that use BDDs.

Keywords: Monte Carlo data, Binary decision diagrams, Neural network modeling, Shortest path length estimation.

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Authors: Karina Zaccari, Ernesto Cordeiro Marujo

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This paper presents a Machine Learning (ML) approach to support Meningitis diagnosis in patients at a children’s hospital in Sao Paulo, Brazil. The aim is to use ML techniques to reduce the use of invasive procedures, such as cerebrospinal fluid (CSF) collection, as much as possible. In this study, we focus on predicting the probability of Meningitis given the results of a blood and urine laboratory tests, together with the analysis of pain or other complaints from the patient. We tested a number of different ML algorithms, including: Adaptative Boosting (AdaBoost), Decision Tree, Gradient Boosting, K-Nearest Neighbors (KNN), Logistic Regression, Random Forest and Support Vector Machines (SVM). Decision Tree algorithm performed best, with 94.56% and 96.18% accuracy for training and testing data, respectively. These results represent a significant aid to doctors in diagnosing Meningitis as early as possible and in preventing expensive and painful procedures on some children.

Keywords: Machine learning, medical diagnosis, meningitis detection, gradient boosting.

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Authors: Mohsen Pirdashti, Masoomeh Omidi, Hemmatollah Pidashti

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Today, advantage of biotechnology especially in environmental issues compared to other technologies is irrefragable. Kimia Gharb Gostar Industries Company, as a largest producer of citric acid in Middle East, applies biotechnology for this goal. Citrogypsum is a by–product of citric acid production and it considered as a valid residuum of this company. At this paper summary of acid citric production and condition of Citrogypsum production in company were introduced in addition to defmition of Citrogypsum production and its applications in world. According to these information and evaluation of present conditions about Iran needing to Citrogypsum, the best priority was introduced and emphasized on strategy selection and proper programming for self-sufficiency. The Delphi technique was used to elicit expert opinions about criteria for evaluating the usages. The criteria identified by the experts were profitability, capacity of production, the degree of investment, marketable, production ease and time production. The Analytical Hierarchy Process (ARP) and Expert Choice software were used to compare the alternatives on the criteria derived from the Delphi process.

Keywords: Analytical Hierarchy Process, ARP, Delphi, Multi- criteria decision making, Citrogypsum

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Authors: Eman Mohamed Ali Elalwani, Salah Haj Ismail

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The Libyan heritage buildings are currently facing a number of crises that pose a threat to their structural integrity, functionality, and overall performance. One of the challenges pertains to the loss of community identity, which has arisen due to the lack of awareness and unconscious behavior of the residents. An additional issue arises from inadequate site management practices, including the implementation of modern techniques and innovative building materials that are incompatible with structural elements, resulting in the deformation of certain sections of the buildings. The security concerns of the city, along with the ongoing civil conflict, fostered a conducive environment for violations, resulting in the vandalism of certain monuments in the city. However, the degradation of this valuable heritage is mainly attributed to the city's neglect and pollution. The elevated groundwater level resulting from pollution has led to erosion in the building's foundations. Mitigating these negative consequences through strategic interventions and rehabilitation is required to preserve this treasure. In order to assist the local community in recovering from those crises, this paper stated a viable strategy for promoting preservation efforts that aimed at safeguarding the heritage sites while also providing guidance to decision-makers and the local community on how to avoid these crises, preserve, enhance, and recognize the significance of the Libyan heritage.

Keywords: Cultural heritage, historical buildings, Tripoli’s Old City, Red Castle, crises, preservation.

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Authors: Shahzadah Fahad Qureshi, Jianqing Zhang

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The wisest economic decision of United States in the 20th century was establishing the favorable international monetary system, and capturing the leadership position in it. This decision gave economic hegemony to the US for the next more than 7 decades. The continuation of this hegemony till the next decade seems difficult as the US economy is under continuous streams of recessions since 2007. On the other hand, Chinese economy is progressing with a very fast speed and is estimated to pass the US economy till 2025, in various aspects. Will the US be able to continue its leadership in the IMS? Will China replace US in the international monetary system? The answers to these questions have been explored by comparing the economic competitiveness of US and China, with respect to each other. The paper concludes that the change in global economic environment will compel US to share the leadership of international monetary system with China. This sharing will solve most problems of the current IMS, but will also birth some new problems.

Keywords: Economic competitiveness, Global economic environment (GEE), International monetary fund (IMF), International monetary system (IMS)

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Authors: K. Aravindhan, Trishit Bandyopadhyay, Mahesh Mehendale, Supriya Kumar De

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The inherent iterative nature of product design and development poses significant challenge to reduce the product design and development time (PD). In order to shorten the time to market, organizations have adopted concurrent development where multiple specialized tasks and design activities are carried out in parallel. Iterative nature of work coupled with the overlap of activities can result in unpredictable time to completion and significant rework. Many of the products have missed the time to market window due to unanticipated or rather unplanned iteration and rework. The iterative and often overlapped processes introduce greater amounts of ambiguity in design and development, where the traditional methods and tools of project management provide less value. In this context, identifying critical metrics to understand the iteration probability is an open research area where significant contribution can be made given that iteration has been the key driver of cost and schedule risk in PD projects. Two important questions that the proposed study attempts to address are: Can we predict and identify the number of iterations in a product development flow? Can we provide managerial insights for a better control over iteration? The proposal introduces the concept of decision points and using this concept intends to develop metrics that can provide managerial insights into iteration predictability. By characterizing the product development flow as a network of decision points, the proposed research intends to delve further into iteration probability and attempts to provide more clarity.

Keywords: Decision Points, Iteration, Product Design, Rework.

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Authors: M. Csete, G. Szendrö

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The last Assessment Report of the Intergovernmental Panel on Climate Change, stating that the greatest risk in climate change affects sustainability is now widely known and accepted. However, it has not provoked substantial reaction and attention in Hungary, while international and national efforts have also not achieved expected results so far. Still, there are numerous examples on different levels (national, regional, local, household) making considerable progress in limiting their own emissions and making steps toward mitigation of and adaptation to climate change. The local level is exceptionally important in sustainability adaptation, as local communities are often able to adapt more flexibly to changes in the natural environment.The aim of this paper is to attempt a review of the national climate policy and the local climate change strategies in Hungary considering sustainable development.

Keywords: adaptation, climate policy, mitigation, localsustainability.

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Authors: S. Chabrier, G. Molle, E. Conte, C. Carlier

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Fishing has always been an essential component of the Polynesians- life. Fishhooks, mostly in pearl shell, found during archaeological excavations are the artifacts related to this activity the most numerous. Thanks to them, we try to reconstruct the ancient techniques of resources exploitation, inside the lagoons and offshore. They can also be used as chronological and cultural indicators. The shapes and dimensions of these artifacts allow comparisons and classifications used in both functional approach and chrono-cultural perspective. Hence it is very important for the ethno-archaeologists to dispose of reliable methods and standardized measurement of these artifacts. Such a reliable objective and standardized method have been previously proposed. But this method cannot be envisaged manually because of the very important time required to measure each fishhook manually and the quantity of fishhooks to measure (many hundreds). We propose in this paper a detailed acquisition protocol of fishhooks and an automation of every step of this method. We also provide some experimental results obtained on the fishhooks coming from three archaeological excavations sites.

Keywords: Automated measures, extraction, fishhook, segmentation.

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Authors: Chen Wu, Lijuan Wang

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Relation between tolerance class and indispensable attribute and knowledge dependency in rough set model with tolerance relation is explored. After giving definitions and concepts of knowledge dependency and knowledge dependency degree for incomplete information system in tolerance rough set model by distinguishing decision attribute containing missing attribute value or not, the result of maintaining reflectivity, transitivity, augmentation, decomposition law and merge law for complete knowledge dependency is proved. Knowledge dependency degrees (not complete knowledge dependency degrees) only satisfy some laws after transitivity, augmentation and decomposition operations. An algorithm to solve attribute reduction in an incomplete decision table is designed. The correctness is checked by an example.

Keywords: Incomplete information system, rough set, tolerance relation, knowledge dependence, attribute reduction.

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Authors: Indradip Banerjee, Souvik Bhattacharyya, Gautam Sanyal

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‘Steganalysis’ is one of the challenging and attractive interests for the researchers with the development of information hiding techniques. It is the procedure to detect the hidden information from the stego created by known steganographic algorithm. In this paper, a novel feature based image steganalysis technique is proposed. Various statistical moments have been used along with some similarity metric. The proposed steganalysis technique has been designed based on transformation in four wavelet domains, which include Haar, Daubechies, Symlets and Biorthogonal. Each domain is being subjected to various classifiers, namely K-nearest-neighbor, K* Classifier, Locally weighted learning, Naive Bayes classifier, Neural networks, Decision trees and Support vector machines. The experiments are performed on a large set of pictures which are available freely in image database. The system also predicts the different message length definitions.

Keywords: Steganalysis, Moments, Wavelet Domain, KNN, K*, LWL, Naive Bayes Classifier, Neural networks, Decision trees, SVM.

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Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: Behavior, big data, hierarchical Hidden Markov Model, intelligent object.

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

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The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: EIoT, machine learning, anomaly detection, environment monitoring.

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Authors: Qasim Kriri, Harsh B. Desai

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Water supply and sanitation in Saudi Arabia is portrayed by difficulties and accomplishments. One of the fundamental difficulties is water shortage. With a specific end goal to beat water shortage, significant ventures have been attempted in sea water desalination, water circulation, sewerage, and wastewater treatment. The motivation behind Statistical Process Control (SPC) is to decide whether the execution of a procedure is keeping up an acceptable quality level [AQL]. SPC is an analytical decision-making method. A fundamental apparatus in the SPC is the Control Charts, which follow the inconstancy in the estimations of the item quality attributes. By utilizing the suitable outline, administration can decide whether changes should be made with a specific end goal to keep the procedure in charge. The two most important quality factors in the distilled water which were taken into consideration were pH (Potential of Hydrogen) and TDS (Total Dissolved Solids). There were three stages at which the quality checks were done. The stages were as follows: (1) Water at the source, (2) water after chemical treatment & (3) water which is sent for packing. The upper specification limit, central limit and lower specification limit are taken as per Saudi water standards. The procedure capacity to accomplish the particulars set for the quality attributes of Berain water Factory chose to be focused by the proposed SPC system.

Keywords: Acceptable quality level, statistical quality control, control charts, process charts.

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Authors: Ruedee Niyomrath

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Ranong province has the best kaolin, and it is the most useful of all the clay types used in ceramic making. Until recently, there has been only one community business making ceramics in Ranong province. And this business could not build the mix of body and glaze from their raw material without assistance. Considering these problems, this research is aimed to test the composition of ceramic body and glaze which suit. Kaolin from Ranong is the raw material which these search focuses on. All other raw materials use in the investigation will come from southern Thailand, kaolin and limestone from Ranong province, ball clay from Surat Thani province, white sand from Songkhla province, and feldspar from Nakhon Si Thammarat province. Results can be used to develop the efficiency of industrial production which in return will enhance the business process.

Keywords: Ceramic body and glaze, Ceramic material, Ceramic production from kaolin, Ceramic souvenirs.

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Authors: Hassan Haleh, Amin Ghaffari, Parisa Farahpour

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Need for an appropriate system of evaluating students- educational developments is a key problem to achieve the predefined educational goals. Intensity of the related papers in the last years; that tries to proof or disproof the necessity and adequacy of the students assessment; is the corroborator of this matter. Some of these studies tried to increase the precision of determining question weights in scientific examinations. But in all of them there has been an attempt to adjust the initial question weights while the accuracy and precision of those initial question weights are still under question. Thus In order to increase the precision of the assessment process of students- educational development, the present study tries to propose a new method for determining the initial question weights by considering the factors of questions like: difficulty, importance and complexity; and implementing a combined method of PROMETHEE and fuzzy analytic network process using a data mining approach to improve the model-s inputs. The result of the implemented case study proves the development of performance and precision of the proposed model.

Keywords: Assessing students, Analytic network process, Clustering, Data mining, Fuzzy sets, Multi-criteria decision making, and Preference function.

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Authors: M. Orefice, V. Di Vito

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This paper provides a description of a Collision Avoidance algorithm that has been developed starting from the mathematical modeling of the flight of insects, in terms of spirals and conchospirals geometric paths. It is able to calculate a proper avoidance manoeuver aimed to prevent the infringement of a predefined distance threshold between ownship and the considered intruder, while minimizing the ownship trajectory deviation from the original path and in compliance with the aircraft performance limitations and dynamic constraints. The algorithm is designed in order to be suitable for real-time applications, so that it can be considered for the implementation in the most recent airborne automatic collision avoidance systems using the traffic data received through an ADS-B IN device. The presented approach is able to take into account the rules-of-the-air, due to the possibility to select, through specifically designed decision making logic based on the consideration of the encounter geometry, the direction of the calculated collision avoidance manoeuver that allows complying with the rules-of-the-air, as for instance the fundamental right of way rule. In the paper, the proposed collision avoidance algorithm is presented and its preliminary design and software implementation is described. The applicability of this method has been proved through preliminary simulation tests performed in a 2D environment considering single intruder encounter geometries, as reported and discussed in the paper.

Keywords: collision avoidance, RPAS, spiral geometry, ADS-B based application

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Authors: Violeta Damjanovic-Behrendt

Abstract:

This paper presents an approach for optimal cyber security decisions to protect instances of a federated Internet of Things (IoT) platform in the cloud. The presented solution implements the repeated Stackelberg Security Game (SSG) and a model called Stochastic Human behaviour model with AttRactiveness and Probability weighting (SHARP). SHARP employs the Subjective Utility Quantal Response (SUQR) for formulating a subjective utility function, which is based on the evaluations of alternative solutions during decision-making. We augment the repeated SSG (including SHARP and SUQR) with a reinforced learning algorithm called Naïve Q-Learning. Naïve Q-Learning belongs to the category of active and model-free Machine Learning (ML) techniques in which the agent (either the defender or the attacker) attempts to find an optimal security solution. In this way, we combine GT and ML algorithms for discovering optimal cyber security policies. The proposed security optimization components will be validated in a collaborative cloud platform that is based on the Industrial Internet Reference Architecture (IIRA) and its recently published security model.

Keywords: Security, internet of things, cloud computing, Stackelberg security game, machine learning, Naïve Q-learning.

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Authors: S. Kotsiantis, E. Koumanakos, D. Tzelepis, V. Tampakas

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This paper explores the effectiveness of machine learning techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. To this end, a number of experiments have been conducted using representative learning algorithms, which were trained using a data set of 164 fraud and non-fraud Greek firms in the recent period 2001-2002. The decision of which particular method to choose is a complicated problem. A good alternative to choosing only one method is to create a hybrid forecasting system incorporating a number of possible solution methods as components (an ensemble of classifiers). For this purpose, we have implemented a hybrid decision support system that combines the representative algorithms using a stacking variant methodology and achieves better performance than any examined simple and ensemble method. To sum up, this study indicates that the investigation of financial information can be used in the identification of FFS and underline the importance of financial ratios.

Keywords: Machine learning, stacking, classifier.

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Authors: Wu Defu, Kiefer Chiam, Yang Kin Seng

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The planning of geological survey works is an iterative process which involves planner, geologist, civil engineer and other stakeholders, who perform different roles and have different points of view. Traditionally, the team used paper maps or CAD drawings to present the proposal which is not an efficient way to present and share idea on the site investigation proposal such as sitting of borehole location or seismic survey lines. This paper focuses on how a GIS approach can be utilised to develop a webbased system to support decision making process in the planning of geological survey works and also to plan site activities carried out by Singapore Geological Office (SGO). The authors design a framework of building an interactive web-based GIS system, and develop a prototype, which enables the users to obtain rapidly existing geological information and also to plan interactively borehole locations and seismic survey lines via a web browser. This prototype system is used daily by SGO and has shown to be effective in increasing efficiency and productivity as the time taken in the planning of geological survey works is shortened. The prototype system has been developed using the ESRI ArcGIS API 3.7 for Flex which is based on the ArcGIS 10.2.1 platform.

Keywords: Engineering geology, Flex, Geological survey planning, Geoscience, GIS, Site investigation, WebGIS.

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Authors: K. Krishna Milan Rao, Nelvin Joseph, Praveen Dwarakanath

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Augmented and Virtual Realties is quickly becoming a hotbed of activity with millions of dollars being spent on R & D and companies such as Google and Microsoft rushing to stake their claim. Augmented reality (AR) is however marching ahead due to the spread of the ideal AR device – the smartphone. Despite its potential, there remains a deep digital divide between the Developed and Developing Countries. The Technological Acceptance Model (TAM) and Hofstede cultural dimensions also predict the behaviour intention to uptake AR in India will be large. This paper takes a quantified approach by collecting 340 survey responses to AR scenarios and analyzing them through statistics. The Survey responses show that the Intention to Use, Perceived Usefulness and Perceived Enjoyment dimensions are high among the urban population in India. This along with the exponential smartphone indicates that India is on the cusp of a boom in the AR sector.

Keywords: Mobile augmented reality, technology acceptance model, Hofstede, cultural dimensions, India.

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Authors: Yusuff Idowu Moshood, Sanni Mohammed

Abstract:

Natural radiations such as ultraviolet (UV) radiation sourced from sun are known to be the main causes of skin cancer, sunburn, eye damage, premature aging of skin and other skin related diseases. Its percentage of radiation reaching the earth populace and its impacts are not well known. Its variability in near-surface relating to its impacts on populace depends on some atmospheric parameters. Hence, this work was embarked on to determine the variability in near-surface UV radiation and its dependency on some atmospheric parameters at different time of the day in Offa, Nigeria. The variability was determined using the data obtained from meteorological garden, Science Laboratory Technology Department, Federal Polytechnic Offa, Nigeria. The data obtained were solar UV radiation, solar radiation, temperature, humidity and pressure at 30 minutes interval. Relationships were determined and correlations were derived using SPSS Pearson Correlation tool. The results showed a significant level of correlation with p-value of 0.01 and 0.05 levels. Thus, the results revealed some good relationships between the solar UV radiation and other atmospheric parameters with significance level less than p-value obtained. Inferentially, interdependent relationships were found to exist. Therefore, the nature of relationship obtained could be a yardstick for decision making in short term environmental planning on solar UV radiation depending of some atmospheric parameters within Offa locality.

Keywords: Correlation, inferential, radiation, yardstick.

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Authors: P.Cordero, R.Poler, R.Sanchis

Abstract:

The environmental impacts caused by the current production and consumption models, together with the impact that the current economic crisis, bring necessary changes in the European industry toward new business models based on sustainability issues that could allow them to innovate and improve their competitiveness. This paper analyzes the key environmental issues and the current and future market trends in one of the most important industrial sectors in Spain, the furniture sector. It also proposes new decision support tools -diagnostic kit, roadmap and guidelines- to guide companies to implement sustainability criteria into their organizations, including eco-design strategies and other economical and social strategies in accordance with the sustainability definition, and other available tools such as eco-labels, environmental management systems, etc., and to use and combine them to obtain the results the company expects to help improve its competitiveness.

Keywords: Furniture sector, eco-design, sustainability, economical crisis, market trends, roadmap

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