Search results for: Statistical Analysis.

Authors: Sumiko Anno, Keiji Imaoka, Takeo Tadono, Tamotsu Igarashi, Subramaniam Sivaganesh, Selvam Kannathasan, Vaithehi Kumaran, Sinnathamby Noble Surendran

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Dengue outbreaks are affected by biological, ecological, socio-economic and demographic factors that vary over time and space. These factors have been examined separately and still require systematic clarification. The present study aimed to investigate the spatial-temporal clustering relationships between these factors and dengue outbreaks in the northern region of Sri Lanka. Remote sensing (RS) data gathered from a plurality of satellites were used to develop an index comprising rainfall, humidity and temperature data. RS data gathered by ALOS/AVNIR-2 were used to detect urbanization, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analyzed RS data and databases were integrated into geographic information systems, enabling temporal analysis, spatial statistical analysis and space-time clustering analysis. Our present results showed that increases in the number of the combination of ecological factor and socio-economic and demographic factors with above the average or the presence contribute to significantly high rates of space-time dengue clusters.

Keywords: ALOS/AVNIR-2, Dengue, Space-time clustering analysis, Sri Lanka.

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Authors: Satyendra Nath Mandal, J. Pal Choudhury, Dilip De, S. R. Bhadra Chaudhuri

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The production of a plant can be measured in terms of seeds. The generation of seeds plays a critical role in our social and daily life. The fruit production which generates seeds, depends on the various parameters of the plant, such as shoot length, leaf number, root length, root number, etc When the plant is growing, some leaves may be lost and some new leaves may appear. It is very difficult to use the number of leaves of the tree to calculate the growth of the plant.. It is also cumbersome to measure the number of roots and length of growth of root in several time instances continuously after certain initial period of time, because roots grow deeper and deeper under ground in course of time. On the contrary, the shoot length of the tree grows in course of time which can be measured in different time instances. So the growth of the plant can be measured using the data of shoot length which are measured at different time instances after plantation. The environmental parameters like temperature, rain fall, humidity and pollution are also play some role in production of yield. The soil, crop and distance management are taken care to produce maximum amount of yields of plant. The data of the growth of shoot length of some mustard plant at the initial stage (7,14,21 & 28 days after plantation) is available from the statistical survey by a group of scientists under the supervision of Prof. Dilip De. In this paper, initial shoot length of Ken( one type of mustard plant) has been used as an initial data. The statistical models, the methods of fuzzy logic and neural network have been tested on this mustard plant and based on error analysis (calculation of average error) that model with minimum error has been selected and can be used for the assessment of shoot length at maturity. Finally, all these methods have been tested with other type of mustard plants and the particular soft computing model with the minimum error of all types has been selected for calculating the predicted data of growth of shoot length. The shoot length at the stage of maturity of all types of mustard plants has been calculated using the statistical method on the predicted data of shoot length.

Keywords: Fuzzy time series, neural network, forecasting error, average error.

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Authors: S. Boria

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In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: Composite material, crashworthiness, finite element analysis, optimization.

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Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: Artificial neural networks, fuel consumption, machine learning, regression, statistical tests.

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Authors: Seyed Habib A. Rahmati, Mohsen Sadegh Amalnick

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Different terms of the Statistical Process Control (SPC) has sketch in the fuzzy environment. However, Measurement System Analysis (MSA), as a main branch of the SPC, is rarely investigated in fuzzy area. This procedure assesses the suitability of the data to be used in later stages or decisions of the SPC. Therefore, this research focuses on some important measures of MSA and through a new method introduces the measures in fuzzy environment. In this method, which works based on Buckley approach, imprecision and vagueness nature of the real world measurement are considered simultaneously. To do so, fuzzy version of the gauge capability (Cg and Cgk) are introduced. The method is also explained through example clearly.

Keywords: SPC, MSA, gauge capability, Cg, Cgk.

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Authors: Leslie J.C.Bluck, Sarah J.Jackson, Georgios Vlasakakis, Adrian Mander

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The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model's failures and data inconsistencies apparent in conventional analyses employing a Non-linear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag -lag phase, t1/ 2 -half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n = 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.

Keywords: Bayesian hierarchical analysis, 13COBT, Gastricemptying, WinBUGS.

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Authors: Chia-Hau Liu, Tai-Yue Wang

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Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.

Keywords: Multivariate control chart, statistical process control, one-class classification method.

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Authors: H. Starzyczna, M. Stoklasa, K. Matusinska

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This article deals with the benefits of regional brands for companies in the Czech Republic. Research was focused on finding out the expected and actual benefits of regional brands for companies. The data were obtained by questionnaire survey and analysed by IBM SPSS. Representative sample of 204 companies was created. The research analysis disclosed the expected benefits that the regional brand should bring to companies. But the actual benefits are much worse. The statistical testing of hypotheses revealed that the benefits depend on the region of origin, which surprised both us and the regional coordinators.

Keywords: Brand, regional brands, product protective branding programs, brand benefits.

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Authors: M. Boukhrouk, R. Ed-Dali

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Outbound tourism in Morocco, as in the majority of developing countries, reveals some of the aspects of inequality between the north and the south. Considered by some researchers as one of the facets of the development crisis, access to tourism and especially international tourism is a chance for a small minority with financial means, while the vast portions of the population dream rather of immigrating to a developed country for the sake of improving their standard of living. The right to travel is also limited by visa requirements, procedures in host countries, security and technical measures and creates discrimination in the practice of tourism. These conditions do not seem to be favorable to the democratization of the practice of international tourism for the populations of the southern countries. This paper is a contribution to the reading of the trends of outbound tourism in developing countries through the example of Morocco. It highlights the different aspects of Moroccan outbound tourism, destinations and the behavior of tourists through an analysis of the offer of a sample of 50 travel agencies. In the same vein, it offers a reading grid of the possibilities offered for the development of outbound tourism and the various existing obstacles to the democratization of international outbound tourism in the southern countries. This reading reveals the transformation in the behavior of Moroccan international tourists as well as the profound changes in Moroccan society, through a model of statistical analysis.

Keywords: Demand, Hajj, Morocco, outbound tourism, tendency, Umrah.

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Authors: T. G. L. J. Bikoko, J. C. Tchamba, S. Amziane

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This study focuses on the problem of collapsed buildings within the city of Douala over the past ten years, and more precisely within the period from 2011 to 2020. It was carried out in a bid to ascertain the real causes of this phenomenon, which has become recurrent in the leading economic city of Cameroon. To achieve this, it was first necessary to review some works dealing with construction materials and technology as well as some case histories of structural collapse within the city. Thereafter, a statistical study was carried out on the results obtained. It was found that the causes of building collapses in the city of Douala are: Neglect of administrative procedures, use of poor quality materials, poor composition and confectioning of concrete, lack of Geotechnical study, lack of structural analysis and design, corrosion of the reinforcement bars, poor maintenance in buildings, and other causes. Out of the 46 cases of failure and collapse of buildings within the city of Douala, 7 of these were identified to have had no geotechnical study carried out, giving a percentage of 15.22%. It was also observed that out of the 46 cases of structural failure, 6 were as a result of lack of proper structural analysis and design giving a percentage of 13.04%. Subsequently, recommendations and suggestions are made in a bid to placing particular emphasis on the choice of materials, the manufacture and casting of concrete as well as the placement of the required reinforcements. All this guarantees the stability of a building.

Keywords: collapse buildings, Douala, structural collapse, Cameroon

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Authors: Federico Pittino, Dominik Holzmann, Krithika Sayar-Chand, Stefan Moser, Sebastian Pliessnig, Thomas Arnold

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The shredding of waste materials is a key step in the recycling process towards circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need of frequent maintenance of critical components. The maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for several months and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring a very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

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Authors: N. Akhavan, Sh. Tavousi Tafreshi, A. Ghasemi

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Seismic behavior of irregular structures through the past decades indicate that the stated buildings do not have appropriate performance. Among these subjects, the current paper has investigated the behavior of special steel moment frame with different configuration of soft storey vertically. The analyzing procedure has been evaluated with respect to incremental dynamic analysis (IDA), and numeric process was carried out by OpenSees finite element analysis package. To this end, nine 2D steel frames, with different numbers of stories and irregularity positions, which were subjected to seven pairs of ground motion records orthogonally with respect to Ibarra-Krawinkler deterioration model, have been investigated. This paper aims at evaluating the response of two-dimensional buildings incorporating soft storey which subjected to bi-directional seismic excitation. The IDAs were implemented for different stages of PGA with various ground motion records, in order to determine maximum inter-storey drift ratio. According to statistical elements and fracture range (standard deviation), the vulnerability or exceedance from above-mentioned cases has been examined. For this reason, fragility curves for different placement of soft storey in the first, middle and the last floor for 4, 8, and 16 storey buildings have been generated and compared properly.

Keywords: Special steel moment frame, soft storey, incremental dynamic analysis, fragility curve.

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Authors: Leszek Chybowski, Artur Bejger, Katarzyna Gawdzińska

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Subversion analysis is a tool used in the TRIZ (Theory of Inventive Problem Solving) methodology. This article introduces the history and describes the process of subversion analysis, as well as function analysis and analysis of the resources, used at the design stage when generating possible undesirable situations. The article charts the course of subversion analysis when applied to a fuel injection nozzle of a marine engine. The work describes the fuel injector nozzle as a technological system and presents principles of analysis for the causes of a cracked tip of the nozzle body. The system is modelled with functional analysis. A search for potential causes of the damage is undertaken and a cause-and-effect analysis for various hypotheses concerning the damage is drawn up. The importance of particular hypotheses is evaluated and the most likely causes of damage identified.

Keywords: Complex technical system, fuel injector, function analysis, importance analysis, resource analysis, sabotage analysis, subversion analysis, TRIZ.

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Authors: Charawee Butbumrung

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This paper aimed to study the factors that relate to working behavior of employees at Pakkred Municipality, Nonthaburi Province. A questionnaire was utilized as the tool in collecting information. Descriptive statistics included frequency, percentage, mean and standard deviation. Independent- sample t- test, analysis of variance and Pearson Correlation were also used. The findings of this research revealed that the majority of the respondents were female, between 25- 35 years old, married, with a Bachelor degree. The average monthly salary of respondents was between 8,001- 12,000 Baht, and having about 4-7 years of working experience. Regarding the overall working motivation factors, the findings showed that interrelationship, respect, and acceptance were ranked as highly important factors, whereas motivation, remunerations & welfare, career growth, and working conditions were ranked as moderately important factors. Also, overall working behavior was ranked as high. The hypotheses testing revealed that different genders had a different working behavior and had a different way of working as a team, which was significant at the 0.05 confidence level, Moreover, there was a difference among employees with different monthly salary in working behavior, problem- solving and decision making, which all were significant at the 0.05 confidence level. Employees with different years of working experience were found to have work working behavior both individual and as a team at the statistical significance level of 0.01 and 0.05. The result of testing the relationship between motivation in overall working revealed that interrelationship, respect and acceptance from others, career growth, and working conditions related to working behavior at a moderate level, while motivation in performing duties and remunerations and welfares related to working behavior towards the same direction at a low level, with a statistical significance of 0.01.

Keywords: Employees of Pakkred Municipality, Factors, Nonthaburi Province, Working Behavior.

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Authors: Mohamed Hafid, Marcel Lacroix

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This study presents an inverse analysis for predicting the thermal conductivities and the heat flux of a high-temperature metallurgical reactor simultaneously. Once these thermal parameters are predicted, the time-varying thickness of the protective phase-change bank that covers the inside surface of the brick walls of a metallurgical reactor can be calculated. The enthalpy method is used to solve the melting/solidification process of the protective bank. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined with the Broyden method (BM). A statistical analysis for the thermal parameter estimation is carried out. The effect of the position of the temperature sensors, total number of measurements and measurement noise on the accuracy of inverse predictions is investigated. Recommendations are made concerning the location of temperature sensors.

Keywords: Inverse heat transfer, phase change, metallurgical reactor, Levenberg–Marquardt method, Broyden method, bank thickness.

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Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou

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There are multiple reasons to expect that detecting the word order errors in a text will be a difficult problem, and detection rates reported in the literature are in fact low. Although grammatical rules constructed by computer linguists improve the performance of grammar checker in word order diagnosis, the repairing task is still very difficult. This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The comparative advantage of this method is that works with a large set of words, and avoids the laborious and costly process of collecting word order errors for creating error patterns.

Keywords: Permutations filtering, Statistical languagemodel N-grams, Word order errors

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Authors: Ayodeji Adesina, Derek Molloy

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Traditional higher-education classrooms allow lecturers to observe students- behaviours and responses to a particular pedagogy during learning in a way that can influence changes to the pedagogical approach. Within current e-learning systems it is difficult to perform continuous analysis of the cohort-s behavioural tendency, making real-time pedagogical decisions difficult. This paper presents a Virtual Learning Process Environment (VLPE) based on the Business Process Management (BPM) conceptual framework. Within the VLPE, course designers can model various education pedagogies in the form of learning process workflows using an intuitive flow diagram interface. These diagrams are used to visually track the learning progresses of a cohort of students. This helps assess the effectiveness of the chosen pedagogy, providing the information required to improve course design. A case scenario of a cohort of students is presented and quantitative statistical analysis of their learning process performance is gathered and displayed in realtime using dashboards.

Keywords: Business process management, cohort analytics, learning processes, virtual learning environment.

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Authors: S. Raissi, R- Eslami Farsani

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In recent years, response surface methodology (RSM) has brought many attentions of many quality engineers in different industries. Most of the published literature on robust design methodology is basically concerned with optimization of a single response or quality characteristic which is often most critical to consumers. For most products, however, quality is multidimensional, so it is common to observe multiple responses in an experimental situation. Through this paper interested person will be familiarize with this methodology via surveying of the most cited technical papers. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with more than two responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.

Keywords: Multi-Response Surface Methodology (MRSM), Design of Experiments (DOE), Process modeling, Quality improvement; Robust Design.

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Authors: Nurfirdawati Muhamad Hanafi, Azmanirah Ab Rahman, Marina Ibrahim Mukhtar, Jamil Ahmad, Sarebah Warman

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This study was conducted to generate empirical evidence on validity and reliability of the item of Competency Assessment Implementation (CAI) Instrument using Rasch Model for polythomous data aided by Winstep software version 3.68. The construct validity was examined by analyzing the point-measure correlation index (PTMEA), infit and outfit MNSQ values; meanwhile the reliability was examined by analyzing item reliability index. A survey technique was used as the major method with the CAI instrument on 156 teachers from vocational schools. The results have shown that the reliability of CAI Instrument items were between 0.80 and 0.98. PTMEA Correlation is in positive values, in which the item is able to distinguish between the ability of the respondent. Statistical data obtained show that out of 154 items, 12 items from the instrument suggested to be omitted. This study is hoped could bring a new direction to the process of data analysis in educational research.

Keywords: Competency Assessment, Reliability, Validity, Item Analysis.

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Authors: S. Boonpoke, B. Marungsri

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This paper presents the effectiveness of artificial intelligent technique to apply for pattern recognition and classification of Partial Discharge (PD). Characteristics of PD signal for pattern recognition and classification are computed from the relation of the voltage phase angle, the discharge magnitude and the repeated existing of partial discharges by using statistical and fractal methods. The simplified fuzzy ARTMAP (SFAM) is used for pattern recognition and classification as artificial intelligent technique. PDs quantities, 13 parameters from statistical method and fractal method results, are inputted to Simplified Fuzzy ARTMAP to train system for pattern recognition and classification. The results confirm the effectiveness of purpose technique.

Keywords: Partial discharges, PD Pattern recognition, PDClassification, Artificial intelligent, Simplified Fuzzy ARTMAP

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Authors: Po-Wen Chen, Jin-Yu Wu, Md. Manirul Ali, Yang Peng, Chen-Te Chang, Der-Jun Jan

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Dynamics of cathode spot has become a major part of vacuum arc discharge with its high academic interest and wide application potential. In this article, using a three-dimensional statistical model, we simulate the distribution of the ignition probability of a new cathode spot occurring in different magnetic pressure on old cathode spot surface and at different arcing time. This model for the ignition probability of a new cathode spot was proposed in two typical situations, one by the pure isotropic random walk in the absence of an external magnetic field, other by the retrograde motion in external magnetic field, in parallel with the cathode surface. We mainly focus on developed relationship between the ignition probability density distribution of a new cathode spot and the external magnetic field.

Keywords: Cathode spot, vacuum arc discharge, transverse magnetic field, random walk.

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Authors: I-Huan Chiu, Kazuhiko Ninomiya, Shin’ichiro Takeda, Meito Kajino, Miho Katsuragawa, Shunsaku Nagasawa, Atsushi Shinohara, Tadayuki Takahashi, Ryota Tomaru, Shin Watanabe, Goro Yabu

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In recent years, a nondestructive elemental analysis method based on muonic X-ray measurements has been developed and applied for various samples. Muonic X-rays are emitted after the formation of a muonic atom, which occurs when a negatively charged muon is captured in a muon atomic orbit around the nucleus. Because muonic X-rays have a higher energy than electronic X-rays due to the muon mass, they can be measured without being absorbed by a material. Thus, estimating the two-dimensional (2D) elemental distribution of a sample became possible using an X-ray imaging detector. In this work, we report a non-destructive imaging experiment using muonic X-rays at Japan Proton Accelerator Research Complex. The irradiated target consisted of a polypropylene material, and a double-sided silicon strip detector, which was developed as an imaging detector for astronomical obervation, was employed. A peak corresponding to muonic X-rays from the carbon atoms in the target was clearly observed in the energy spectrum at an energy of 14 keV, and 2D visualizations were successfully reconstructed to reveal the projection image from the target. This result demonstrates the potential of the nondestructive elemental imaging method that is based on muonic X-ray measurement. To obtain a higher position resolution for imaging a smaller target, a new detector system will be developed to improve the statistical analysis in further research.

Keywords: DSSD, muon, muonic X-ray, imaging, non-destructive analysis

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Authors: Sadia Afroza, Rakiba Rouf

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Road safety and associated behaviors have received significant attention in recent years, reflecting general public concern. This paper portrays a statistical scenario of the young drivers in UAE with emphasis on various concern points of young driver’s behavior and license issuance. Although there are many factors contributing to road accidents, statistically it is evident that age plays a major role in road accidents. Despite ensuring strict road safety laws enforced by the UAE government, there is a staggering correlation among road accidents and young driver’s at UAE. However, private organizations like BMW and RoadSafetyUAE have extended its support on conducting surveys on driver’s behavior with an aim to ensure road safety. Various strategies such as road safety law enforcement, license issuance, adapting new technologies like safety cameras and raising awareness can be implemented to improve the road safety concerns among young drivers.

Keywords: Driving behavior, GLDS, road safety, UAE drivers, young drivers.

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Authors: Edward Guillen, Daniel Padilla, Adriana Hernandez, Kenneth Barner

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Biometrics methods include recognition techniques such as fingerprint, iris, hand geometry, voice, face, ears and gait. The gait recognition approach has some advantages, for example it does not need the prior concern of the observed subject and it can record many biometric features in order to make deeper analysis, but most of the research proposals use high computational cost. This paper shows a gait recognition system with feature subtraction on a bundle rectangle drawn over the observed person. Statistical results within a database of 500 videos are shown.

Keywords: Autentication, Biometrics, Gait Recognition, Human Identification, Security.

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Authors: M. Yaldagard, S.A. Mortazavi, F. Tabatabaie

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In the present study, the effects of ultrasound as emerging technology were investigated on germination stimulation, amount of alpha-amylase activity on dry barley seeds before steeping stage of malting process. All experiments were carried out at 20 KHz on the ultrasonic generator in 3 different ultrasonic intensities (20, 60 and 100% setting from total power of device) and time (5, 10 and 15 min) at constant temperature (30C). For determining the effects of these parameters on enzyme the Fuwa method assay based on the decreased staining value of blue starch–iodine complexes employed for measurement an activity. The results of these assays were analyzed by Qualitek4 software using the Taguchi statistical method to evaluate the factor-s effects on enzyme activity. It has been found that when malting barley is irradiated with an ultrasonic power, a stimulating effect occurs as to the enzyme activity.

Keywords: ultrasound, alpha-amylase activity, stimulationand Taguchi statistical method.

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Authors: M. Ilyas, M. W. Siddiqi

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This study employs auto-regressive distributed lag (ARDL) bounds approach to cointegration for long run and errorcorrection modeling (ECM) for short run analysis to examine the relationship between revenue gap and economic growth for Pakistan using annual time series data over the period 1980 to 2008. The short and long run results indicate that revenue gap is statistical significant and negatively effect economic growth. The significant and negative coefficient of error correction term in ECM indicates that after a shock, the long rum equilibrium will again converge towards equilibrium about 10.406 percent within a year.

Keywords: ARDL cointegration, Economic Growth, RevenueGap, Pakistan.

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Authors: Bülent Dilmaç, Didem Aydoğan

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The use of new technologies such internet (e-mail, chat rooms) and cell phones has steeply increased in recent years. Especially among children and young people, use of technological tools and equipments is widespread. Although many teachers and administrators now recognize the problem of school bullying, few are aware that students are being harassed through electronic communication. Referred to as electronic bullying, cyber bullying, or online social cruelty, this phenomenon includes bullying through email, instant messaging, in a chat room, on a website, or through digital messages or images sent to a cell phone. Cyber bullying is defined as causing deliberate/intentional harm to others using internet or other digital technologies. It has a quantitative research design nd uses relational survey as its method. The participants consisted of 300 secondary school students in the city of Konya, Turkey. 195 (64.8%) participants were female and 105 (35.2%) were male. 39 (13%) students were at grade 1, 187 (62.1%) were at grade 2 and 74 (24.6%) were at grade 3. The “Cyber Bullying Question List" developed by Ar─▒cak (2009) was given to students. Following questions about demographics, a functional definition of cyber bullying was provided. In order to specify students- human values, “Human Values Scale (HVS)" developed by Dilmaç (2007) for secondary school students was administered. The scale consists of 42 items in six dimensions. Data analysis was conducted by the primary investigator of the study using SPSS 14.00 statistical analysis software. Descriptive statistics were calculated for the analysis of students- cyber bullying behaviour and simple regression analysis was conducted in order to test whether each value in the scale could explain cyber bullying behaviour.

Keywords: Cyber bullying, Values, Secondary SchoolStudents

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Authors: Nishi Bhuvandas, P. V. Timbadiya, P. L. Patel, P. D. Porey

Abstract:

Recent perceived climate variability raises concerns with unprecedented hydrological phenomena and extremes. Distribution and circulation of the waters of the Earth become increasingly difficult to determine because of additional uncertainty related to anthropogenic emissions. The world wide observed changes in the large-scale hydrological cycle have been related to an increase in the observed temperature over several decades. Although the effect of change in climate on hydrology provides a general picture of possible hydrological global change, new tools and frameworks for modelling hydrological series with nonstationary characteristics at finer scales, are required for assessing climate change impacts. Of the downscaling techniques, dynamic downscaling is usually based on the use of Regional Climate Models (RCMs), which generate finer resolution output based on atmospheric physics over a region using General Circulation Model (GCM) fields as boundary conditions. However, RCMs are not expected to capture the observed spatial precipitation extremes at a fine cell scale or at a basin scale. Statistical downscaling derives a statistical or empirical relationship between the variables simulated by the GCMs, called predictors, and station-scale hydrologic variables, called predictands. The main focus of the paper is on the need for using statistical downscaling techniques for projection of local hydrometeorological variables under climate change scenarios. The projections can be then served as a means of input source to various hydrologic models to obtain streamflow, evapotranspiration, soil moisture and other hydrological variables of interest.

Keywords: Climate Change, Downscaling, GCM, RCM.

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Authors: Benedetto Manganelli, Beniamino Murgante

Abstract:

The use of statistical data and of the neural networks, capable of elaborate a series of data and territorial info, have allowed the making of a model useful in the subdivision of urban places into homogeneous zone under the profile of a social, real estate, environmental and urbanist background of a city. The development of homogeneous zone has fiscal and urbanist advantages. The tools in the model proposed, able to be adapted to the dynamic changes of the city, allow the application of the zoning fast and dynamic.

Keywords: Homogeneous Urban Areas, Multidimensional Scaling, Neural Network, Real Estate Market, Urban Planning.

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Authors: Sarah Motiee, Azadeh Nematzadeh, Mehrnoush Shamsfard

Abstract:

Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques to extract phrases from documents and the query and doing stemming on words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done flexible and in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.

Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.

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