Search results for: Multi-criteria decision analysis

Authors: C. Nallusamy, A. Sabari, K. Suganya

Abstract:

Geographical routing protocol requires node physical location information to make forwarding decision. Geographical routing uses location service or position service to obtain the position of a node. The geographical information is a geographic coordinates or can be obtained through reference points on some fixed coordinate system. Link can be formed between two nodes. Link lifetime plays a crucial role in MANET. Link lifetime represent how long the link is stable without any failure between the nodes. Link failure may occur due to mobility and because of link failure energy of nodes can be drained. Thus this paper proposes survey about link lifetime prediction using geographical information.

Keywords: MANET, Geographical routing, Link lifetime, Link stability.

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Authors: Phanu Waraporn

Abstract:

This paper discusses the designing of knowledge integration of clinical information extracted from distributed medical ontologies in order to ameliorate a machine learning-based multilabel coding assignment system. The proposed approach is implemented using a decision tree technique of the machine learning on the university hospital data for patients with Coronary Heart Disease (CHD). The preliminary results obtained show a satisfactory finding that the use of medical ontologies improves the overall system performance.

Keywords: Medical Ontology, Knowledge Integration, Machine Learning, Medical Coding, Text Assignment.

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Authors: Valene J. Gresham, MA, Laura A. Brodie

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For the last decade, statistics show traumatic brain injury (TBI) is a growing concern in our legal system. In an effort to obtain data regarding the influence of neuropsychological expert witness testimony in a criminal case, this study tested three hypotheses. H1: The majority of jurors will vote not guilty, due to mild head injury. H2: The jurors will give more credence to the testimony of the neuropsychologist rather than the psychiatrist. H3: The jurors will be more lenient in their sentencing, given the testimony of the neuropsychologist-s testimony. The criterion for inclusion in the study as a participant is identical to those used for inclusion in the eligibility for jury duty in the United States. A chisquared test was performed to analyze the data for the three hypotheses. The results supported all of the hypotheses; however statistical significance was seen in H1 and H2 only.

Keywords: Expert witness, jury decision, neuropsychology, traumatic brain injury.

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Authors: A. Danbaba

Abstract:

Several experiments are conducted at different environments such as locations or periods (seasons) with identical treatments to each experiment purposely to study the interaction between the treatments and environments or between the treatments and periods (seasons). The commonly used designs of experiments for this purpose are randomized block design, Latin square design, balanced incomplete block design, Youden design, and one or more factor designs. The interest is to carry out a combined analysis of the data from these multi-environment experiments, instead of analyzing each experiment separately. This paper proposed combined analysis of experiments conducted via Sudoku square design of odd order with same experimental treatments.

Keywords: Sudoku designs, combined analysis, multi-environment experiments, common treatments.

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Authors: Ewa. M. Sztendur, Neil T. Diamond

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Random Forests are a powerful classification technique, consisting of a collection of decision trees. One useful feature of Random Forests is the ability to determine the importance of each variable in predicting the outcome. This is done by permuting each variable and computing the change in prediction accuracy before and after the permutation. This variable importance calculation is similar to a one-factor-at a time experiment and therefore is inefficient. In this paper, we use a regular fractional factorial design to determine which variables to permute. Based on the results of the trials in the experiment, we calculate the individual importance of the variables, with improved precision over the standard method. The method is illustrated with a study of student attrition at Monash University.

Keywords: Random Forests, Variable Importance, Fractional Factorial Designs, Student Attrition.

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Authors: Ki-Young Kim, Jae-Ho Lim, Deok-Min Kim, Seok-Yoon Kim

Abstract:

Average current analysis checking the impact of current flow is very important to guarantee the reliability of semiconductor systems. As semiconductor process technologies improve, the coupling capacitance often become bigger than self capacitances. In this paper, we propose an analytic technique for analyzing average current on interconnects in multi-conductor structures. The proposed technique has shown to yield the acceptable errors compared to HSPICE results while providing computational efficiency.

Keywords: current moment, interconnect modeling, reliability analysis, worst-case switching

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Authors: Abdel-Aziz M. Mohamed, Nermeen Coutry

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Lead time is a critical measure of a supply chain's performance. It impacts both the customer satisfactions as well as the total cost of inventory. This paper presents the result of a study on the analysis of the customer order lead-time for a multinational company. In the study, the lead time was divided into three stages respectively: order entry, order fulfillment, and order delivery. A sample of size 2,425 order lines was extracted from the company's records to use for this study. The sample data entails information regarding customer orders from the time of order entry until order delivery. Data regarding the lead time of each stage for different orders were also provided. Summary statistics on lead time data reveals that about 30% of the orders were delivered later than the scheduled due date. The result of the multiple linear regression analysis technique revealed that component type, logistics parameter, order size and the customer type have significant impacts on lead time. Data analysis on the stages of lead time indicates that stage 2 consumed over 50% of the lead time. Pareto analysis was made to study the reasons for the customer order delay in each stage. Recommendation was given to resolve the problem.

Keywords: Lead time reduction, customer satisfaction, service quality, statistical analysis.

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Authors: Burçe Boyraz

Abstract:

This study examines appearances of brand placement as an alternative communication strategy in television series by focusing on Yalan Dünya which is one of the most popular television series in Turkey. Consequently, this study has a descriptive research design and quantitative content analysis method is used in order to analyze frequency and time data of brand placement appearances in first 3 seasons of Yalan Dünya with 16 episodes. Analysis of brand placement practices in Yalan Dünya is dealt in three categories: episode-based analysis, season-based analysis and comparative analysis. At the end, brand placement practices in Yalan Dünya are evaluated in terms of type, form, duration and legal arrangements. As a result of this study, it is seen that brand placement plays a determinant role in Yalan Dünya content. Also, current legal arrangements make brand placement closer to other traditional communication strategies instead of differing brand placement from them distinctly.

Keywords: Advertising, Alternative communication strategy, Brand placement, Yalan Dünya.

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Authors: Campisi Domenico, Costa Roberta

Abstract:

Intellectual capital measurement is a central aspect of knowledge management. The measurement and the evaluation of intangible assets play a key role in allowing an effective management of these assets as sources of competitiveness. For these reasons, managers and practitioners need conceptual and analytical tools taking into account the unique characteristics and economic significance of Intellectual Capital. Following this lead, we propose an efficiency and productivity analysis of Intellectual Capital, as a determinant factor of the company competitive advantage. The analysis is carried out by means of Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI). These techniques identify Bests Practice companies that have accomplished competitive advantage implementing successful strategies of Intellectual Capital management, and offer to inefficient companies development paths by means of benchmarking. The proposed methodology is employed on the Biotechnology industry in the period 2007-2010.

Keywords: Data Envelopment Analysis, Innovation, Intangible assets, Intellectual Capital, Malmquist Productivity Index.

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Authors: Michael Harre, Terry Bossomaier, Ranqing Chu, Allan Snyder

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We introduce a novel approach to measuring how humans learn based on techniques from information theory and apply it to the oriental game of Go. We show that the total amount of information observable in human strategies, called the strategic information, remains constant for populations of players of differing skill levels for well studied patterns of play. This is despite the very large amount of knowledge required to progress from the recreational players at one end of our spectrum to the very best and most experienced players in the world at the other and is in contrast to the idea that having more knowledge might imply more 'certainty' in what move to play next. We show this is true for very local up to medium sized board patterns, across a variety of different moves using 80,000 game records. Consequences for theoretical and practical AI are outlined.

Keywords: Board Games, Cognitive Capacity, Decision Theory, Information Theory.

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Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto

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In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.

Keywords: Capacity-booking, SPA, monthly production planning, linear programming.

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Authors: Hyun-Kyu Kang

Abstract:

The Korean Government has applied the preliminary feasibility study to new government R&D program plans as a part of an evaluation system for R&D programs. The preliminary feasibility study for the R&D program is composed of 3 major criteria such as technological, policy and economic analysis. The program logic model approach is used as a part of the technological analysis in the preliminary feasibility study. We has developed and improved the R&D program logic model. The logic model is a very useful tool for evaluating R&D program plans. Using a logic model, we can generally identify important factors of the R&D program plan, analyze its logic flow and find the disconnection or jump in the logic flow among components of the logic model.

Keywords: Preliminary feasibility study, R&D program logic model, technological analysis.

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Authors: Alireza Abbasi Moshaii, Mehdi Tale Masouleh, Esmail Zarezadeh, Kamran Farajzadeh

Abstract:

The main purpose of this study is static analysis of two three-degree of freedom parallel mechanisms: 3-RCC and 3- RRS. Geometry of these mechanisms is expressed and static equilibrium equations are derived for the whole chains. For these mechanisms due to the equal number of equations and unknowns, the solution is as same as 3-RCC mechanism. A mathematical software is used to solve the equations. In order to prove the results obtained from solving the equations of mechanisms, the CAD model of these robots has been simulated and their static is analysed in ADAMS software. Due to symmetrical geometry of the mechanisms, the force and external torque acting on the end-effecter have been considered asymmetric to prove the generality of the solution method. Finally, the results of both softwares, for both mechanisms are extracted and compared as graphs. The good achieved comparison between the results indicates the accuracy of the analysis.

Keywords: Robotic, Static analysis, 3-RCC, 3-RRS.

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Authors: Mohsen Nikaein

Abstract:

Because of importance of energy, optimization of power generation systems is necessary. Gas turbine cycles are suitable manner for fast power generation, but their efficiency is partly low. In order to achieving higher efficiencies, some propositions are preferred such as recovery of heat from exhaust gases in a regenerator, utilization of intercooler in a multistage compressor, steam injection to combustion chamber and etc. However thermodynamic optimization of gas turbine cycle, even with above components, is necessary. In this article multi-objective genetic algorithms are employed for Pareto approach optimization of Regenerative-Intercooling-Gas Turbine (RIGT) cycle. In the multiobjective optimization a number of conflicting objective functions are to be optimized simultaneously. The important objective functions that have been considered for optimization are entropy generation of RIGT cycle (Ns) derives using Exergy Analysis and Gouy-Stodola theorem, thermal efficiency and the net output power of RIGT Cycle. These objectives are usually conflicting with each other. The design variables consist of thermodynamic parameters such as compressor pressure ratio (Rp), excess air in combustion (EA), turbine inlet temperature (TIT) and inlet air temperature (T0). At the first stage single objective optimization has been investigated and the method of Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used for multi-objective optimization. Optimization procedures are performed for two and three objective functions and the results are compared for RIGT Cycle. In order to investigate the optimal thermodynamic behavior of two objectives, different set, each including two objectives of output parameters, are considered individually. For each set Pareto front are depicted. The sets of selected decision variables based on this Pareto front, will cause the best possible combination of corresponding objective functions. There is no superiority for the points on the Pareto front figure, but they are superior to any other point. In the case of three objective optimization the results are given in tables.

Keywords: Exergy, Entropy Generation, Brayton Cycle, DesignParameters, Optimization, Genetic Algorithm, Multi-Objective.

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Authors: A. Arul Lawrence Selvakumar, C. Suresh Ganandhas

Abstract:

This paper describes the study of cryptographic hash functions, one of the most important classes of primitives used in recent techniques in cryptography. The main aim is the development of recent crypt analysis hash function. We present different approaches to defining security properties more formally and present basic attack on hash function. We recall Merkle-Damgard security properties of iterated hash function. The Main aim of this paper is the development of recent techniques applicable to crypt Analysis hash function, mainly from SHA family. Recent proposed attacks an MD5 & SHA motivate a new hash function design. It is designed not only to have higher security but also to be faster than SHA-256. The performance of the new hash function is at least 30% better than that of SHA-256 in software. And it is secure against any known cryptographic attacks on hash functions.

Keywords: Crypt Analysis, cryptographic.

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Authors: M. Byzedi, B. Saghafian

Abstract:

Droughts are complex, natural hazards that, to a varying degree, affect some parts of the world every year. The range of drought impacts is related to drought occurring in different stages of the hydrological cycle and usually different types of droughts, such as meteorological, agricultural, hydrological, and socioeconomical are distinguished. Streamflow drought was analyzed by the method of truncation level (at 70% level) on daily discharges measured in 54 hydrometric stations in southwestern Iran. Frequency analysis was carried out for annual maximum series (AMS) of drought deficit volume and duration series. Some factors including physiographic, climatic, geologic, and vegetation cover were studied as influential factors in the regional analysis. According to the results of factor analysis, six most effective factors were identified as area, rainfall from December to February, the percent of area with Normalized Difference Vegetation Index (NDVI) <0.1, the percent of convex area, drainage density and the minimum of watershed elevation that explained 90.9% of variance. The homogenous regions were determined by cluster analysis and discriminate function analysis. Suitable multivariate regression models were evaluated for streamflow drought deficit volume with 2 years return period. The significance level of regression models was 0.01. The results showed that the watershed area is the most effective factor with high correlation with deficit volume. Also, drought duration was not a suitable drought index for regional analysis.

Keywords: Iran, Streamflow drought, truncation level method, regional analysis.

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Authors: Guomin Luo, Daming Zhang, Yong Kwee Koh, Kim Teck Ng, Helmi Kurniawan, Weng Hoe Leong

Abstract:

Partial discharge (PD) detection is an important method to evaluate the insulation condition of metal-clad apparatus. Non-intrusive sensors which are easy to install and have no interruptions on operation are preferred in onsite PD detection. However, it often lacks of accuracy due to the interferences in PD signals. In this paper a novel PD extraction method that uses frequency analysis and entropy based time-frequency (TF) analysis is introduced. The repetitive pulses from convertor are first removed via frequency analysis. Then, the relative entropy and relative peak-frequency of each pulse (i.e. time-indexed vector TF spectrum) are calculated and all pulses with similar parameters are grouped. According to the characteristics of non-intrusive sensor and the frequency distribution of PDs, the pulses of PD and interferences are separated. Finally the PD signal and interferences are recovered via inverse TF transform. The de-noised result of noisy PD data demonstrates that the combination of frequency and time-frequency techniques can discriminate PDs from interferences with various frequency distributions.

Keywords: Entropy, Fourier analysis, non-intrusive measurement, time-frequency analysis, partial discharge

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Authors: Chulhyun Kim, Seungkyum Kim, Moon-soo Kim

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A variety of new technology-based services have emerged with the development of Information and Communication Technologies (ICTs). Since technology-based services have technology-driven characteristics, the identification of relationships between technology-based services and ICTs would give meaningful implications. Thus, this paper proposes an approach for identifying the relationships between technology-based services and ICTs by analyzing patent documents. First, business model (BM) patents are classified into relevant service categories. Second, patent citation analysis is conducted to investigate the technological linkage and impacts between technology-based services and ICTs at macro level. Third, as a micro level analysis, patent co-classification analysis is employed to identify the technological linkage and coverage. The proposed approach could guide and help managers and designers of technology-based services to discover the opportunity of the development of new technology-based services in emerging service sectors.

Keywords: Technology-based Services, Information and Communication Technology (ICT), Business Model (BM) Patent, Patent Analysis, Technological Relationship

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Authors: Nafaâ Nacereddine, Latifa Hamami, Djemel Ziou

Abstract:

In non destructive testing by radiography, a perfect knowledge of the weld defect shape is an essential step to appreciate the quality of the weld and make decision on its acceptability or rejection. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of thresholding methods must be done judiciously. In this paper, performance criteria are used to conduct a comparative study of thresholding methods based on gray level histogram, 2-D histogram and locally adaptive approach for weld defect extraction in radiographic images.

Keywords: 1D and 2D histogram, locally adaptive approach, performance criteria, radiographic image, thresholding, weld defect.

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Authors: Theodor D. Popescu

Abstract:

The paper presents a method for multivariate time series forecasting using Independent Component Analysis (ICA), as a preprocessing tool. The idea of this approach is to do the forecasting in the space of independent components (sources), and then to transform back the results to the original time series space. The forecasting can be done separately and with a different method for each component, depending on its time structure. The paper gives also a review of the main algorithms for independent component analysis in the case of instantaneous mixture models, using second and high-order statistics. The method has been applied in simulation to an artificial multivariate time series with five components, generated from three sources and a mixing matrix, randomly generated.

Keywords: Independent Component Analysis, second order statistics, simulation, time series forecasting

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Authors: Sudhir Jagtap, Kodge B. G., Shinde G. N., Devshette P. M

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Numerical analysis naturally finds applications in all fields of engineering and the physical sciences, but in the 21st century, the life sciences and even the arts have adopted elements of scientific computations. The numerical data analysis became key process in research and development of all the fields [6]. In this paper we have made an attempt to analyze the specified numerical patterns with reference to the association rule mining techniques with minimum confidence and minimum support mining criteria. The extracted rules and analyzed results are graphically demonstrated. Association rules are a simple but very useful form of data mining that describe the probabilistic co-occurrence of certain events within a database [7]. They were originally designed to analyze market-basket data, in which the likelihood of items being purchased together within the same transactions are analyzed.

Keywords: Numerical data analysis, Data Mining, Association Rule Mining

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Authors: José Antonio Esparza Isasa, Finn Overgaard Hansen, Peter Gorm Larsen

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This paper presents a new methodology to study power and energy consumption in mechatronic systems early in the development process. This new approach makes use of two modeling languages to represent and simulate embedded control software and electromechanical subsystems in the discrete event and continuous time domain respectively within a single co-model. This co-model enables an accurate representation of power and energy consumption and facilitates the analysis and development of both software and electro-mechanical subsystems in parallel. This makes the engineers aware of energy-wise implications of different design alternatives and enables early trade-off analysis from the beginning of the analysis and design activities.

Keywords: Energy consumption, embedded systems, modeldriven engineering, power awareness.

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Authors: Madina Hamiane, May Hashim Ali

Abstract:

This paper presents the processing and analysis of ECG signals. The study is based on wavelet transform and uses exclusively the MATLAB environment. This study includes removing Baseline wander and further de-noising through wavelet transform and metrics such as signal-to noise ratio (SNR), Peak signal-to-noise ratio (PSNR) and the mean squared error (MSE) are used to assess the efficiency of the de-noising techniques. Feature extraction is subsequently performed whereby signal features such as heart rate, rise and fall levels are extracted and the QRS complex was detected which helped in classifying the ECG signal. The classification is the last step in the analysis of the ECG signals and it is shown that these are successfully classified as Normal rhythm or Abnormal rhythm.  The final result proved the adequacy of using wavelet transform for the analysis of ECG signals.

Keywords: ECG Signal, QRS detection, thresholding, wavelet decomposition, feature extraction.

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Authors: C. Kumjeera, T. Unchim, B. Marungsri, A. Oonsivilai

Abstract:

The study of piezoelectric material in the past was in T-Domain form; however, no one has studied piezoelectric material in the S-Domain form. This paper will present the piezoelectric material in the transfer function or S-Domain model. S-Domain is a well known mathematical model, used for analyzing the stability of the material and determining the stability limits. By using S-Domain in testing stability of piezoelectric material, it will provide a new tool for the scientific world to study this material in various forms.

Keywords: Hard disk drive, failure analysis, tool, time

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Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

The UK has strong economic growth, which attracts other countries to invest there through globalization. This research process will be based on quantitative and qualitative descriptive analysis using interviews. The secondary analysis will involve a case study approach to understand the important aspects of leadership skills. The research outcomes will be identifying the strength and weakness of the leadership skills of UK automobile manufacturing enterprises and suggest the best practices adopted by the respective countries for better results.

Keywords: engineering management, leadership, industrial project management, project managers, automobile manufacturing

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Authors: Defu Zhang, Qingshan Jiang, Xin Li

Abstract:

This paper deals with the application of a well-known neural network technique, multilayer back-propagation (BP) neural network, in financial data mining. A modified neural network forecasting model is presented, and an intelligent mining system is developed. The system can forecast the buying and selling signs according to the prediction of future trends to stock market, and provide decision-making for stock investors. The simulation result of seven years to Shanghai Composite Index shows that the return achieved by this mining system is about three times as large as that achieved by the buy and hold strategy, so it is advantageous to apply neural networks to forecast financial time series, the different investors could benefit from it.

Keywords: Data mining, neural network, stock forecasting.

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Authors: M. Lloret-Climent, J. Nescolarde-Selva

Abstract:

The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Keywords: Attractor, invariant set, orbits, tourist variables.

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Authors: Mauro Giacomini, Stefania Bertone, Carlo Mansi, Pietro Dulbecco, Vincenzo Savarino

Abstract:

The prevalence of non organic constipation differs from country to country and the reliability of the estimate rates is uncertain. Moreover, the clinical relevance of subdividing the heterogeneous functional constipation disorders into pre-defined subgroups is largely unknown.. Aim: to estimate the prevalence of constipation in a population-based sample and determine whether clinical subgroups can be identified. An age and gender stratified sample population from 5 Italian cities was evaluated using a previously validated questionnaire. Data mining by cluster analysis was used to determine constipation subgroups. Results: 1,500 complete interviews were obtained from 2,083 contacted households (72%). Self-reported constipation correlated poorly with symptombased constipation found in 496 subjects (33.1%). Cluster analysis identified four constipation subgroups which correlated to subgroups identified according to pre-defined symptom criteria. Significant differences in socio-demographics and lifestyle were observed among subgroups.

Keywords: Cluster analysis, constipation, data mining, statistical analysis.

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Authors: A. Boudjemai , M.H. Bouanane, Mankour, R. Amri, H. Salem, B. Chouchaoui

Abstract:

The purpose of this paper is to perform a multidisciplinary design and analysis (MDA) of honeycomb panels used in the satellites structural design. All the analysis is based on clamped-free boundary conditions. In the present work, detailed finite element models for honeycomb panels are developed and analysed. Experimental tests were carried out on a honeycomb specimen of which the goal is to compare the previous modal analysis made by the finite element method as well as the existing equivalent approaches. The obtained results show a good agreement between the finite element analysis, equivalent and tests results; the difference in the first two frequencies is less than 4% and less than 10% for the third frequency. The results of the equivalent model presented in this analysis are obtained with a good accuracy. Moreover, investigations carried out in this research relate to the honeycomb plate modal analysis under several aspects including the structural geometrical variation by studying the various influences of the dimension parameters on the modal frequency, the variation of core and skin material of the honeycomb. The various results obtained in this paper are promising and show that the geometry parameters and the type of material have an effect on the value of the honeycomb plate modal frequency.

Keywords: Satellite, honeycomb, finite element method, modal frequency, dynamic.

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Authors: M. Arja, G. Sauce, B. Souyri

Abstract:

Overall cost is a significant consideration in any decision-making process. Although many studies were carried out on overall cost in construction, little has treated the uncertainties of real life cycle development. On the basis of several case studies, a feedback process was performed on the historical data of studied buildings. This process enabled to identify some factors causing uncertainty during the operational period. As a result, the research proposes a new method for assessing the overall cost during a part of the building-s life cycle taking account of the building actual value, its end-of-life value and the influence of the identified life cycle uncertainty factors. The findings are a step towards a higher level of reliability in overall cost evaluation taking account of some usually unexpected uncertainty factors.

Keywords: Asset management, building life cycle uncertainty, building value, overall cost.

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