Search results for: Analysis methods

Authors: Göksu Gözen Citak

Abstract:

The process of constructing a scale measuring the attitudes of youth toward violence on televisions is reported. A 30-item draft attitude scale was applied to a working group of 232 students attending the Faculty of Educational Sciences at Ankara University between the years 2005-2006. To introduce the construct validity and dimensionality of the scale, exploratory and confirmatory factor analysis was applied to the data. Results of the exploratory factor analysis showed that the scale had three factors that accounted for 58,44% (22,46% for the first, 22,15% for the second and 13,83% for the third factor) of the common variance. It is determined that the first factor considered issues related individual effects of violence on televisions, the second factor concerned issues related social effects of violence on televisions and the third factor concerned issues related violence on television programs. Results of the confirmatory factor analysis showed that all the items under each factor are fitting the concerning factors structure. An alpha reliability of 0,90 was estimated for the whole scale. It is concluded that the scale is valid and reliable.

Keywords: Attitudes toward violence, confirmatory factor analysis, constructing attitude scale, exploratory factor analysis, violence on televisions.

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Authors: Dušan Kravec, Ondrej Staš, Marián Tolnay, Michal Bachratý

Abstract:

This article gives a short preview of the new software created especially for palletizing process in automated production systems. Each chapter of this article is about problem solving in development of modules in Java programming language. First part describes structure of the software, its modules and data flow between them. Second part describes all deployment methods, which are implemented in the software. Next chapter is about twodimensional editor created for manipulation with objects in each layer of the load and gives calculations for collision control. Module of virtual reality used for three-dimensional preview and creation of the load is described in the fifth chapter. The last part of this article describes communication and data flow between control system of the robot, vision system and software.

Keywords: Palletizing, deployment methods, palletizing software, virtual reality in palletizing.

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Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

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Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: Average run length, Bernoulli CUSUM chart, beta binomial posterior predictive distribution, clinical indicator, health care organization, highest posterior density interval.

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Authors: Meryem Lamrani, Younès El Amrani, Aziz Ettouhami

Abstract:

The ability of UML to handle the modeling process of complex industrial software applications has increased its popularity to the extent of becoming the de-facto language in serving the design purpose. Although, its rich graphical notation naturally oriented towards the object-oriented concept, facilitates the understandability, it hardly successes to report all domainspecific aspects in a satisfactory way. OCL, as the standard language for expressing additional constraints on UML models, has great potential to help improve expressiveness. Unfortunately, it suffers from a weak formalism due to its poor semantic resulting in many obstacles towards the build of tools support and thus its application in the industry field. For this reason, many researches were established to formalize OCL expressions using a more rigorous approach. Our contribution join this work in a complementary way since it focuses specifically on OCL predefined properties which constitute an important part in the construction of OCL expressions. Using formal methods, we mainly succeed in expressing rigorously OCL predefined functions.

Keywords: Formal methods, Z, OCL, predefined properties, metamodel types.

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Authors: M. Michael Gromiha, Y. Yabuki, K. Imai, P. Horton, K. Fukui

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We have developed a database for membrane protein functions, which has more than 3000 experimental data on functionally important amino acid residues in membrane proteins along with sequence, structure and literature information. Further, we have proposed different methods for identifying membrane proteins based on their functions: (i) discrimination of membrane transport proteins from other globular and membrane proteins and classifying them into channels/pores, electrochemical and active transporters, and (ii) β-signal for the insertion of mitochondrial β-barrel outer membrane proteins and potential targets. Our method showed an accuracy of 82% in discriminating transport proteins and 68% to classify them into three different transporters. In addition, we have identified a motif for targeting β-signal and potential candidates for mitochondrial β-barrel membrane proteins. Our methods can be used as effective tools for genome-wide annotations.

Keywords: Membrane proteins, database, transporters, discrimination, β-signal.

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Authors: Ali Beydoun, Hamzé H. Alaeddine

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One of the main challenges in MIMO-OFDM system to achieve the expected performances in terms of data rate and robustness against multi-path fading channels is the channel estimation. Several methods were proposed in the literature based on either least square (LS) or minimum mean squared error (MMSE) estimators. These methods present high implementation complexity as they require the inversion of large matrices. In order to overcome this problem and to reduce the complexity, this paper presents a solution that benefits from the use of the STBC encoder and transforms the channel estimation process into a set of simple linear operations. The proposed method is evaluated via simulation in AWGN-Rayleigh fading channel. Simulation results show a maximum reduction of 6.85% of the bit error rate (BER) compared to the one obtained with the ideal case where the receiver has a perfect knowledge of the channel.

Keywords: Channel estimation, MIMO, OFDM, STBC, CAZAC sequence.

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Authors: S. W. Chen, W. K. Lin, J. R. Wang, C. Shih, H. T. Lin, H. C. Chang, W. Y. Li

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Kuosheng nuclear power plant (NPP) is a BWR/6 type NPP and located on the northern coast of Taiwan. First, Kuosheng NPP TRACE model were developed in this research. In order to assess the system response of Kuosheng NPP TRACE model, startup tests data were used to evaluate Kuosheng NPP TRACE model. Second, the overpressurization transient analysis of Kuosheng NPP TRACE model was performed. Besides, in order to confirm the mechanical property and integrity of fuel rods, FRAPTRAN analysis was also performed in this study.

Keywords: TRACE, Safety analysis, BWR/6, FRAPTRAN.

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Authors: P. C. Tewari, Rajiv Kumar, Dinesh Khanduja

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This paper discusses the performance modeling and availability analysis of Yarn Dyeing System of a Textile Industry. The Textile Industry is a complex and repairable engineering system. Yarn Dyeing System of Textile Industry consists of five subsystems arranged in series configuration. For performance modeling and analysis of availability, a performance evaluating model has been developed with the help of mathematical formulation based on Markov-Birth-Death Process. The differential equations have been developed on the basis of Probabilistic Approach using a Transition Diagram. These equations have further been solved using normalizing condition in order to develop the steady state availability, a performance measure of the system concerned. The system performance has been further analyzed with the help of decision matrices. These matrices provide various availability levels for different combinations of failure and repair rates for various subsystems. The findings of this paper are therefore, considered to be useful for the analysis of availability and determination of the best possible maintenance strategies which can be implemented in future to enhance the system performance.

Keywords: Availability Analysis, Markov Process, Performance Modeling, Steady State Availability.

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Authors: N. A. Samat, D. F. Percy

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The main aim of this study is to describe and introduce a method of numerical analysis in obtaining approximate solutions for the SIR-SI differential equations (susceptible-infectiverecovered for human populations; susceptible-infective for vector populations) that represent a model for dengue disease transmission. Firstly, we describe the ordinary differential equations for the SIR-SI disease transmission models. Then, we introduce the numerical analysis of solutions of this continuous time, discrete space SIR-SI model by simplifying the continuous time scale to a densely populated, discrete time scale. This is followed by the application of this numerical analysis of solutions of the SIR-SI differential equations to the estimation of relative risk using continuous time, discrete space dengue data of Kuala Lumpur, Malaysia. Finally, we present the results of the analysis, comparing and displaying the results in graphs, table and maps. Results of the numerical analysis of solutions that we implemented offers a useful and potentially superior model for estimating relative risks based on continuous time, discrete space data for vector borne infectious diseases specifically for dengue disease. 

Keywords: Dengue disease, disease mapping, numerical analysis, SIR-SI differential equations.

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Authors: Seksan Chunothaisawat, Pongchanun Luangpaiboon

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There are two common types of operational research techniques, optimisation and metaheuristic methods. The latter may be defined as a sequential process that intelligently performs the exploration and exploitation adopted by natural intelligence and strong inspiration to form several iterative searches. An aim is to effectively determine near optimal solutions in a solution space. In this work, a type of metaheuristics called Ant Colonies Optimisation, ACO, inspired by a foraging behaviour of ants was adapted to find optimal solutions of eight non-linear continuous mathematical models. Under a consideration of a solution space in a specified region on each model, sub-solutions may contain global or multiple local optimum. Moreover, the algorithm has several common parameters; number of ants, moves, and iterations, which act as the algorithm-s driver. A series of computational experiments for initialising parameters were conducted through methods of Rigid Simplex, RS, and Modified Simplex, MSM. Experimental results were analysed in terms of the best so far solutions, mean and standard deviation. Finally, they stated a recommendation of proper level settings of ACO parameters for all eight functions. These parameter settings can be applied as a guideline for future uses of ACO. This is to promote an ease of use of ACO in real industrial processes. It was found that the results obtained from MSM were pretty similar to those gained from RS. However, if these results with noise standard deviations of 1 and 3 are compared, MSM will reach optimal solutions more efficiently than RS, in terms of speed of convergence.

Keywords: Ant colony optimisation, metaheuristics, modified simplex, non-linear, rigid simplex.

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Authors: Florin Leon, Silvia Curteanu

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Developing complete mechanistic models for polymerization reactors is not easy, because complex reactions occur simultaneously; there is a large number of kinetic parameters involved and sometimes the chemical and physical phenomena for mixtures involving polymers are poorly understood. To overcome these difficulties, empirical models based on sampled data can be used instead, namely regression methods typical of machine learning field. They have the ability to learn the trends of a process without any knowledge about its particular physical and chemical laws. Therefore, they are useful for modeling complex processes, such as the free radical polymerization of methyl methacrylate achieved in a batch bulk process. The goal is to generate accurate predictions of monomer conversion, numerical average molecular weight and gravimetrical average molecular weight. This process is associated with non-linear gel and glass effects. For this purpose, an adaptive sampling technique is presented, which can select more samples around the regions where the values have a higher variation. Several machine learning methods are used for the modeling and their performance is compared: support vector machines, k-nearest neighbor, k-nearest neighbor and random forest, as well as an original algorithm, large margin nearest neighbor regression. The suggested method provides very good results compared to the other well-known regression algorithms.

Keywords: Adaptive sampling, batch bulk methyl methacrylate polymerization, large margin nearest neighbor regression, machine learning.

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Authors: Andrej Miklošík, Eva Hvizdová, Štefan Žák

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Many companies have switched their processes to project-oriented in the last years. This brings new possibilities and effectiveness not only in the field of external processes connected with the product delivery but also the internal processes as well. However centralized project organization which is based on the role of project manager in the team has proved insufficient in some cases. Agile methods of project organization are trying to solve this problem by bringing new view on the project organization, roles, processes and competences. Scrum is one of these methods which builds on the principles of knowledge management to drive the project to effectiveness from all view angles. Using this method to organize internal and delivery projects helps the organization to create and share knowledge throughout the company. It also supports forming unique competences of individuals and project teams and drives innovations in the company.

Keywords: agile software development, knowledge management, knowledge dissemination, project management, SCRUM

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Authors: Miloš Šeda

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Finding the minimal logical functions has important applications in the design of logical circuits. This task is solved by many different methods but, frequently, they are not suitable for a computer implementation. We briefly summarise the well-known Quine-McCluskey method, which gives a unique procedure of computing and thus can be simply implemented, but, even for simple examples, does not guarantee an optimal solution. Since the Petrick extension of the Quine-McCluskey method does not give a generally usable method for finding an optimum for logical functions with a high number of values, we focus on interpretation of the result of the Quine-McCluskey method and show that it represents a set covering problem that, unfortunately, is an NP-hard combinatorial problem. Therefore it must be solved by heuristic or approximation methods. We propose an approach based on genetic algorithms and show suitable parameter settings.

Keywords: Boolean algebra, Karnaugh map, Quine-McCluskey method, set covering problem, genetic algorithm.

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Authors: Virginia Bassily, Sherif Goubran

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In heritage conservation and revival, much of the focus is placed on the techniques and methods to preserve, restore, and revive heritage structures and locations. However, more attention needs to be drawn to how deterioration happens and its effect on the area’s character and socio-economic status. To this end, this research aims to examine the decline and its effect in the El Korba area in Heliopolis, Cairo, Egypt. El Korba was designed with a unique architectural character to stimulate social and economic life. However, the area has been on a path of physical deterioration that is corroding the social life on its streets. This research uses diachronic analysis in Ibrahim El-Lakkani Boulevard of El Korba based on a previously developed framework that connects buildings’ architectural features to the degree of social interaction in the street to document the changes that the building deterioration could have caused. Architectural features of the street level during both the original state (1906) and the current state (2021) are broken down and categorized in those six parameters to understand their decline or improvement over time. We find that the parameters that have decreased over the years and caused the deterioration are complexity and architectural character, permeability, territoriality and personalization, and physical comfort.  Based on these findings, revival projects can focus on physical parameters that create synergistic benefits by preserving and renewing heritage locations and revitalizing their socio-economic potential.

Keywords: Architectural character, heritage building conservation, enclosure, ground-floor use, El Korba, visual and physical permeability, personalization, physical comfort, social life, territoriality.

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Authors: M. V. G. Silva, J. Gazzola, I. M. Dal Fabbro, A. C. L. Lino

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Computer aided design accounts with the support of parametric software in the design of machine components as well as of any other pieces of interest. The complexities of the element under study sometimes offer certain difficulties to computer design, or ever might generate mistakes in the final body conception. Reverse engineering techniques are based on the transformation of already conceived body images into a matrix of points which can be visualized by the design software. The literature exhibits several techniques to obtain machine components dimensional fields, as contact instrument (MMC), calipers and optical methods as laser scanner, holograms as well as moiré methods. The objective of this research work was to analyze the moiré technique as instrument of reverse engineering, applied to bodies of nom complex geometry as simple solid figures, creating matrices of points. These matrices were forwarded to a parametric software named SolidWorks to generate the virtual object. Volume data obtained by mechanical means, i.e., by caliper, the volume obtained through the moiré method and the volume generated by the SolidWorks software were compared and found to be in close agreement. This research work suggests the application of phase shifting moiré methods as instrument of reverse engineering, serving also to support farm machinery element designs.

Keywords: Reverse engineering, Moiré technique, three dimensional image generation.

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Authors: Chien-Hua Wang, Wei-Hsuan Lee, Chin-Tzong Pang

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In data mining, the association rules are used to find for the associations between the different items of the transactions database. As the data collected and stored, rules of value can be found through association rules, which can be applied to help managers execute marketing strategies and establish sound market frameworks. This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth) to derive from fuzzy association rules. At first, we apply fuzzy partition methods and decide a membership function of quantitative value for each transaction item. Next, we implement FFP-growth to deal with the process of data mining. In addition, in order to understand the impact of Apriori algorithm and FFP-growth algorithm on the execution time and the number of generated association rules, the experiment will be performed by using different sizes of databases and thresholds. Lastly, the experiment results show FFPgrowth algorithm is more efficient than other existing methods.

Keywords: Data mining, association rule, fuzzy frequent patterngrowth.

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Authors: A. Mirrashid, M. Khoshbin, A. Atghaei, H. Shahbazi

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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: Attention, fire detection, smoke detection, spatiotemporal.

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Authors: Fahanim Abdul Rashid, Muhammad Azzam Ismail, Deo Prasad

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In order to encourage the construction of green homes (GH) in Malaysia, a simple and attainable framework for designing and building GHs is needed. This can be achieved by aligning GH principles against Cole-s 'Sustainable Building Criteria' (SBC). This set of considerations was used to categorize the GH features of three case studies from Malaysia. Although the categorization of building features is useful at exploring the presence of sustainability inclinations of each house, the overall impact of building features in each of the five SBCs are unknown. Therefore, this paper explored the possibility of quantifying the impact of building features categorized in SBC1 – “Buildings will have to adapt to the new environment and restore damaged ecology while mitigating resource use" based on existing GH assessment tools and methods and other literature. This process as reported in this paper could lead to a new dimension in green home rating and assessment methods.

Keywords: Green homes, Malaysia, Sustainable BuildingCriteria, Sustainable homes

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Authors: Alexander L. Pyayt, Ilya I. Mokhov, Bernhard Lang, Valeria V. Krzhizhanovskaya, Robert J. Meijer

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More and more natural disasters are happening every year: floods, earthquakes, volcanic eruptions, etc. In order to reduce the risk of possible damages, governments all around the world are investing into development of Early Warning Systems (EWS) for environmental applications. The most important task of the EWS is identification of the onset of critical situations affecting environment and population, early enough to inform the authorities and general public. This paper describes an approach for monitoring of flood protections systems based on machine learning methods. An Artificial Intelligence (AI) component has been developed for detection of abnormal dike behaviour. The AI module has been integrated into an EWS platform of the UrbanFlood project (EU Seventh Framework Programme) and validated on real-time measurements from the sensors installed in a dike.

Keywords: Early Warning System, intelligent environmentalmonitoring, machine learning, flood protection.

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Authors: K. Farhangdoost, H. Heirani

Abstract:

Contact stress is an important problem in industry. This is a problem that in the first attention may be don-t appears, but disregard of these stresses cause a lot of damages in machines. These stresses occur at locations such as gear teeth, bearings, cams and between a locomotive wheel and the railroad rail. These stresses cause failure by excessive elastic deformation, yielding and fracture. In this paper we intend show the effective parameters in contact stress and ponder effect of curvature. In this paper we study contact stresses on the surface of gear teeth and compare these stresses for four popular profiles of gear teeth (involute, cycloid, epicycloids, and hypocycloid). We study this problem with mathematical and finite element methods and compare these two methods on different profile surfaces.

Keywords: Contact stress, Cycloid, Epicycloids, Finite element, Gear, Hypocycloid, Involute, Radius of curvature.

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Authors: Mansoor Momeni, Mahmoud Dehghan Nayeri, Ali Faal Ghayoumi, Hoda Ghorbani

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This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.

Keywords: Financial data analysis, Influential data, Outliers, Robust regression.

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Authors: Ahmed Amine Hachicha, Chaouki Ghenai, Abdul Kadir Hamid

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Temperature effect on the performance of a photovoltaic module is one of the main concerns that face this renewable energy, especially in hot arid region, e.g. United Arab Emirates. Overheating of the PV modules reduces the open circuit voltage and the efficiency of the modules dramatically. In this work, water-cooling is developed to enhance the performance of PV modules. Different scenarios are tested under UAE weather conditions: front, back and double cooling. A spraying system is used for the front cooling whether a direct contact water system is used for the back cooling. The experimental results are compared to non-cooling module and the performance of the PV module is determined for different situations. The experimental results show that the front cooling is more effective than the back cooling and may decrease the temperature of the PV module significantly. 

Keywords: PV cooling, solar energy, cooling methods, electrical efficiency, temperature effect.

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Authors: Ilaria Lucrezia Amerise

Abstract:

Electricity markets throughout the world have undergone substantial changes. Accurate, reliable, clear and comprehensible modeling and forecasting of different variables (loads and prices in the first instance) have achieved increasing importance. In this paper, we describe the actual state of the art focusing on reg-SARMA methods, which have proven to be flexible enough to accommodate the electricity price/load behavior satisfactory. More specifically, we will discuss: 1) The dichotomy between point and interval forecasts; 2) The difficult choice between stochastic (e.g. climatic variation) and non-deterministic predictors (e.g. calendar variables); 3) The confrontation between modelling a single aggregate time series or creating separated and potentially different models of sub-series. The noteworthy point that we would like to make it emerge is that prices and loads require different approaches that appear irreconcilable even though must be made reconcilable for the interests and activities of energy companies.

Keywords: Forecasting problem, interval forecasts, time series, electricity prices, reg-plus-SARMA methods.

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Authors: Saman M. Abdulla, Najla B. Al-Dabagh, Omar Zakaria

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The aim of this article is to explain how features of attacks could be extracted from the packets. It also explains how vectors could be built and then applied to the input of any analysis stage. For analyzing, the work deploys the Feedforward-Back propagation neural network to act as misuse intrusion detection system. It uses ten types if attacks as example for training and testing the neural network. It explains how the packets are analyzed to extract features. The work shows how selecting the right features, building correct vectors and how correct identification of the training methods with nodes- number in hidden layer of any neural network affecting the accuracy of system. In addition, the work shows how to get values of optimal weights and use them to initialize the Artificial Neural Network.

Keywords: Artificial Neural Network, Attack Features, MisuseIntrusion Detection System, Training Parameters.

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Authors: Sergei Aleinik, Mikhail Stolbov

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In this work, a method of time delay estimation for  dual-channel acoustic signals (speech, music, etc.) recorded under  reverberant conditions is investigated. Standard methods based on  cross-correlation of the signals show poor results in cases involving  strong reverberation, large distances between microphones and  asynchronous recordings. Under similar conditions, a method based  on cross-correlation of temporal envelopes of the signals delivers a  delay estimation of acceptable quality. This method and its properties  are described and investigated in detail, including its limits of  applicability. The method’s optimal parameter estimation and a  comparison with other known methods of time delay estimation are  also provided.

 

Keywords: Cross-correlation, delay estimation, signal envelope, signal processing.

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Authors: Hossein Mirzaee, Farhad Besharati

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Solar sunspot rotation, latitudinal bands are studied based on intelligent computation methods. A combination of image fusion method with together tree decomposition is used to obtain quantitative values about the latitudes of trajectories on sun surface that sunspots rotate around them. Daily solar images taken with SOlar and Heliospheric (SOHO) satellite are fused for each month separately .The result of fused image is decomposed with Quad Tree decomposition method in order to achieve the precise information about latitudes of sunspot trajectories. Such analysis is useful for gathering information about the regions on sun surface and coordinates in space that is more expose to solar geomagnetic storms, tremendous flares and hot plasma gases permeate interplanetary space and help human to serve their technical systems. Here sunspot images in September, November and October in 2001 are used for studying the magnetic behavior of sun.

Keywords: Quad tree decomposition, sunspot image.

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Authors: Erika Martinez Ramirez, Rene V. Mayorga

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The internet is constantly expanding. Identifying web links of interest from web browsers requires users to visit each of the links listed, individually until a satisfactory link is found, therefore those users need to evaluate a considerable amount of links before finding their link of interest; this can be tedious and even unproductive. By incorporating web assistance, web users could be benefited from reduced time searching on relevant websites. In this paper, a rough set approach is presented, which facilitates classification of unlimited available e-vocabulary, to assist web users in reducing search times looking for relevant web sites. This approach includes two methods for identifying relevance data on web links based on the priority and percentage of relevance. As a result of these methods, a list of web sites is generated in priority sequence with an emphasis of the search criteria.

Keywords: Web search, Web Mining, Rough Sets, Web Intelligence, Intelligent Portals, Relevance.

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Authors: Djilani Kobibi Youcef Islam, Hadjeri Samir, Djehaf Mohamed Abdeldjalil

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The Flexible AC Transmission System (FACTS) technology is a new advanced solution that increases the reliability and provides more flexibility, controllability, and stability of a power system. The Unified Power Flow Controller (UPFC), as the most versatile FACTS device for regulating power flow, is able to control respectively transmission line real power, reactive power, and node voltage. The main purpose of this paper is to analyze the effect of the UPFC on the load flow, the power losses, and the voltage stability using NEPLAN software modules, Newton-Raphson load flow is used for the power flow analysis and the modal analysis is used for the study of the voltage stability. The simulation was carried out on the IEEE 14-bus test system.

Keywords: FACTS, load flow, modal analysis, UPFC, voltage stability.

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Authors: Saima Ali, Pathamanathan Rajeev, Imteaz A. Monzur

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In this paper, a brief review of the corrosion mechanism in buried pipe and modes of failure is provided together with the available corrosion models. Moreover, the sensitivity analysis is performed to understand the influence of corrosion model parameters on the remaining life estimation. Further, the probabilistic analysis is performed to propagate the uncertainty in the corrosion model on the estimation of the renaming life of the pipe. Finally, the comparison among the corrosion models on the basis of the remaining life estimation will be provided to improve the renewal plan.

Keywords: Corrosion, pit depth, sensitivity analysis, exposure period.

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Authors: Haleh Rezaei Zanjirabadi, Fatemeh Saberi, Bahman Rahimzadeh, Fariborz Masoudi, Mohammad Rahgosha

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In this study, apatite minerals from the iron-phosphate deposit of Yazd have been investigated within the microcontinent zone of Iran in the Zagros structural zone. The geological units in the Esfordi area belong to the pre-Cambrian to lower-Cambrian age, consisting of a succession of carbonate rocks (dolomite), shale, tuff, sandstone, and volcanic rocks. In addition to the mentioned sedimentary and volcanic rocks, the granitoid mass of Bahabad, which is the largest intrusive mass in the region, has intruded into the eastern part of this series and has caused its metamorphism and alteration. After collecting the available data, various samples of Esfordi’s apatite were prepared, and their mineralogy and crystallography were investigated using laboratory methods such as petrographic microscopy, Raman spectroscopy, EDS (Energy Dispersive Spectroscopy), and Scanning Electron Microscopy (SEM). In non-destructive Raman spectroscopy, the molecular structure of apatite minerals was revealed in four distinct spectral ranges. Initially, the spectra of phosphate and aluminum bonds with O2HO, OH, were observed, followed by the identification of Cl, OH, Al, Na, Ca and hydroxyl units depending on the type of apatite mineral family. In SEM analysis, based on various shapes and different phases of apatites, their constituent major elements were identified through EDS, indicating that the samples from the Esfordi mining area exhibit a dense and coherent texture with smooth surfaces. Based on the elemental analysis results by EDS, the apatites in the Esfordi area are classified into the calcic apatite group.

Keywords: Petrology, apatite, Esfordi, EDS, SEM, Scanning Electron Microscopy, Raman spectroscopy.

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