Search results for: topography. Subject classification: 86 A 05

Authors: R. K. Agrawal, Rajni Bala

Abstract:

Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.

Keywords: Gene selection, genetic algorithm, microarray datasets, multi-class SVM.

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Authors: Koray U. Erbas

Abstract:

Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: Convolutional Neural Network, Deep Learning, Deep Learning Based FER, Facial Emotion Recognition.

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Authors: E. Pikushchak, J. Dueck, L. Minkov

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In hydrocyclones, the particle separation efficiency is limited by the suspended fine particles, which are discharged with the coarse product in the underflow. It is well known that injecting water in the conical part of the cyclone reduces the fine particle fraction in the underflow. This paper presents a mathematical model that simulates the water injection in the conical component. The model accounts for the fluid flow and the particle motion. Particle interaction, due to hindered settling caused by increased density and viscosity of the suspension, and fine particle entrainment by settling coarse particles are included in the model. Water injection in the conical part of the hydrocyclone is performed to reduce fine particle discharge in the underflow. The model demonstrates the impact of the injection rate, injection velocity, and injection location on the shape of the partition curve. The simulations are compared with experimental data of a 50-mm cyclone.

Keywords: Classification, fine particle processing, hydrocyclone, water injection.

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Authors: A. Greco, N. Mammone, F.C. Morabito, M.Versaci

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This paper is mainly concerned with the application of a novel technique of data interpretation for classifying measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artificial Neural Networks and Multi-Class Support Vector Machines have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compared with earlier methods.

Keywords: Tokamak, Classification, Artificial Neural Network, Support Vector Machines.

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Authors: Farshideh Einsele, Hassan Foroosh

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In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using well-known geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: Camera-based OCR, Feature extraction, Document and image processing.

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Authors: Eleni Ioannou, Pascal Nucara, Keith Pullen

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The subject of this paper is the investigation of the best efficiency design of a compressor diffuser applied in new lightweight, ultra efficient micro-gas turbine engines for vehicles. The Computational Fluid Dynamics (CFD) results are obtained utilizing steady state simulations for a wedge and an ”oval” type pipe diffuser in an effort to identify the beneficial effects of the pipe diffuser design. The basic flow features are presented with particular focus on the optimization of the pipe diffuser leading to higher efficiencies for the compressor stage. The optimised pipe diffuser is designed to exploit the 3D freedom enabled by Selective Laser Melting, hence purposely involves an investigation of geometric characteristics that do not follow the traditional diffuser concept.

Keywords: CFD, centrifugal compressor, micro-gas turbine, pipe diffuser, SLM, wedge diffuser.

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Authors: Davoud Beheshtizadeh, Davood Jafari

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Concrete, with its unique properties and advantages, has gained widespread and increasing use in the construction industry, particularly in a country's infrastructure. However, concrete exhibits certain defects, most notably the presence of micro-cracks that occur after the setting process, leading to increased costs for infrastructure repair and maintenance. As a result, self-healing concretes have garnered attention in various countries in recent years. These concretes employ different mechanisms for repair, including physical, chemical, biological, and combined approaches, each with its own subsets and implementation methods. Certain mechanisms hold significant importance, leading to specialized production methods. Given the novelty of this subject in Iran, there is limited knowledge or, in some cases, a complete lack of understanding. This paper presents various self-healing concrete mechanisms and the advantages, disadvantages, and application scope of each method.

Keywords: Micro-cracks, self-healing concrete, microcapsules, concrete, cement, self-sensitive.

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Authors: Mario Kubek, Herwig Unger

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Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-ofthe- art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents.

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking.

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Authors: P. M. Arun Kumar, S. Chandramathi

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The proliferation of multimedia technology and services in today’s world provide ample research scope in the frontiers of visual signal processing. Wide spread usage of video based applications in heterogeneous environment needs viable methods of Video Quality Assessment (VQA). The evaluation of video quality not only depends on high QoS requirements but also emphasis the need of novel term ‘QoE’ (Quality of Experience) that perceive video quality as user centric. This paper discusses two vital video quality assessment methods namely, subjective and objective assessment methods. The evolution of various video quality metrics, their classification models and applications are reviewed in this work. The Mean Opinion Score (MOS) based subjective measurements and algorithm based objective metrics are discussed and their challenges are outlined. Further, this paper explores the recent progress of VQA in emerging technologies such as mobile video and 3D video.

Keywords: 3D-Video, no reference metric, quality of experience, video quality assessment, video quality metrics.

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Authors: Chyn Liaw, Chun-Wei Tung, Shinn-Jang Ho, Shinn-Ying Ho

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The γ-turns play important roles in protein folding and molecular recognition. The prediction and analysis of γ-turn types are important for both protein structure predictions and better understanding the characteristics of different γ-turn types. This study proposed a physicochemical property-based decision tree (PPDT) method to interpretably predict γ-turn types. In addition to the good prediction performance of PPDT, three simple and human interpretable IF-THEN rules are extracted from the decision tree constructed by PPDT. The identified informative physicochemical properties and concise rules provide a simple way for discriminating and understanding γ-turn types.

Keywords: Classification and regression tree (CART), γ-turn, Physicochemical properties, Protein secondary structure.

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Authors: Hanadi Mubarak AL-Mubaraki, Michael Busler

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In the context of business incubation (BI) as strategic enablers, this paper critically reviews the literature relating to the strategic benefits of BI in the Middle East. The taxonomy of BI benefits in the strategic elements on 1) type, 2) financial model, 3) services, 4) objectives, 5) number of clients, 6) number of graduates, and 7) jobs creation. Understanding the importance of BI benefits can be significant in the economic development although most incubators lead to diversify the economy. Thus, taxonomies of the benefits of BI are produced from both the academic literature and published case studies. In this way, a classification of strategic benefits elements as they relate to incubators has been developed to provide a greater understanding of the benefits needed to obtain a specific element. The result of this paper is Business incubators is aimed entrepreneurship, jobs creation, research commercialization and profitable enterprises in Middle Eastern countries.

Keywords: Economic Development, Incubators, Middle East, Strategic.

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Authors: Nikhil, Ari Visa, Chin-Chao Chen, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

Abstract:

A predictive clustering hybrid regression (pCHR) approach was developed and evaluated using dataset from H2- producing sucrose-based bioreactor operated for 15 months. The aim was to model and predict the H2-production rate using information available about envirome and metabolome of the bioprocess. Selforganizing maps (SOM) and Sammon map were used to visualize the dataset and to identify main metabolic patterns and clusters in bioprocess data. Three metabolic clusters: acetate coupled with other metabolites, butyrate only, and transition phases were detected. The developed pCHR model combines principles of k-means clustering, kNN classification and regression techniques. The model performed well in modeling and predicting the H2-production rate with mean square error values of 0.0014 and 0.0032, respectively.

Keywords: Biohydrogen, bioprocess modeling, clusteringhybrid regression.

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Authors: Marthese Azzopardi, Liberato Camilleri

Abstract:

This research was performed to investigate the study habits and level of difficulty perceived by post-secondary students in Biology at Advanced-level topics after completing their first year of study. At the end of a two-year ‘sixth form’ course, Maltese students sit for the Matriculation and Secondary Education Certificate (MATSEC) Advanced-level biology exam as a requirement to pursue science-related studies at the University of Malta. The sample was composed of 23 students (16 taking Chemistry and seven taking some ‘Other’ subject at the Advanced Level). The cohort comprised seven males and 16 females. A questionnaire constructed by the authors, was answered anonymously during the last lecture at the end of the first year of study, in May 2016. The Chi square test revealed that gender plays no effect on the various study habits (c² (6) = 5.873, p = 0.438). ‘Reading both notes and textbooks’ was the most common method adopted by males (71.4%), whereas ‘Writing notes on each topic’ was that mostly used by females (81.3%). The Mann-Whitney U test showed no significant difference in the study habits of students and the mean assessment mark obtained at the end of the first year course (p = 0.231). Statistical difference was found with the One-ANOVA test when comparing the mean assessment mark obtained at the end of the first year course when students are clustered by their Secondary Education Certificate (SEC) grade (p < 0.001). Those obtaining a SEC grade of 2 and 3 got the highest mean assessment of 68.33% and 66.9%, respectively [SEC grading is 1-7, where 1 is the highest]. The Friedman test was used to compare the mean difficulty rating scores provided for the difficulty of each topic. The mean difficulty rating score ranges from 1 to 4, where the larger the mean rating score, the higher the difficulty. When considering the whole group of students, nine topics out of 21 were perceived as significantly more difficult than the other topics. Protein synthesis, DNA Replication and Biomolecules were the most difficult, in that order. The Mann-Whitney U test revealed that the perceived level of difficulty in comprehending Biomolecules is significantly lower for students taking Chemistry compared to those not choosing the subject (p = 0.018). Protein Synthesis was claimed as the most difficult by Chemistry students and Biomolecules by those not studying Chemistry. DNA Replication was the second most difficult topic perceived by both groups. The Mann-Whitney U test was used to examine the effect of gender on the perceived level of difficulty in comprehending various topics. It was found that females have significantly more difficulty in comprehending Biomolecules than males (p=0.039). Protein synthesis was perceived as the most difficult topic by males (mean difficulty rating score = 3.14), while Biomolecules, DNA Replication and Protein synthesis were of equal difficulty for females (mean difficulty rating score = 3.00). Males and females perceived DNA Replication as equally difficult (mean difficulty rating score = 3.00). Discovering the students’ study habits and perceived level of difficulty of specific topics is vital for the lecturer to offer guidance that leads to higher academic achievement.

Keywords: Biology, Perceived difficulty, Post-secondary, Study habits.

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Authors: H. Baazaoui Zghal, S. Faiz, H. Ben Ghezala

Abstract:

Data mining is an extraordinarily demanding field referring to extraction of implicit knowledge and relationships, which are not explicitly stored in databases. A wide variety of methods of data mining have been introduced (classification, characterization, generalization...). Each one of these methods includes more than algorithm. A system of data mining implies different user categories,, which mean that the user-s behavior must be a component of the system. The problem at this level is to know which algorithm of which method to employ for an exploratory end, which one for a decisional end, and how can they collaborate and communicate. Agent paradigm presents a new way of conception and realizing of data mining system. The purpose is to combine different algorithms of data mining to prepare elements for decision-makers, benefiting from the possibilities offered by the multi-agent systems. In this paper the agent framework for data mining is introduced, and its overall architecture and functionality are presented. The validation is made on spatial data. Principal results will be presented.

Keywords: Databases, data mining, multi-agent, spatial datamart.

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Authors: Olatunde I. Sekunowo, Stephen I. Durowaye, Ganiyu I. Lawal

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Composites depending on the nature of their constituents and mode of production are regarded as one of the advanced materials that drive today’s technology. This paper attempts a short review of the subject matter with a general aim of pushing to the next level the frontier of knowledge as it impacts the technology of nano-particles manufacturing. The objectives entail an effort to; aggregate recent research efforts in this field, analyse research findings and observations, streamline research efforts and support industry in taking decision on areas of fund deployment. It is envisaged that this work will serve as a quick hand-on compendium material for researchers in this field and a guide to relevant government departments wishing to fund a research whose outcomes have the potential of improving the nation’s GDP.

Keywords: Advanced materials, Composites, Mechanical properties, Nano-particles.

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Authors: P. Ghann, J. Shiguang, C. Zhou

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Access control is one of the most challenging issues facing information security. Access control is defined as, the ability to permit or deny access to a particular computational resource or digital information by an unauthorized user or subject. The concept of usage control (UCON) has been introduced as a unified approach to capture a number of extensions for access control models and systems. In UCON, an access decision is determined by three factors: authorizations, obligations and conditions. Attribute mutability and decision continuity are two distinct characteristics introduced by UCON for the first time. An observation of UCON components indicates that, the components are predefined and static. In this paper, we propose a new and flexible model of usage control for the creation and elimination of some of these components; for example new objects, subjects, attributes and integrate these with the original UCON model. We also propose a model for concurrent usage scenarios in UCON.

Keywords: Access Control, Concurrency, Digital container, Usage control.

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Authors: Muñoz-Sanchez, Victor Manuel, Perez-Flores, Antonio Manuel

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The main objective of this paper is to establish the relationship between models of state organization and the various types of collective identity expressed by the Spanish. The question of nationalism and identity ascription in Spain has always been a topic of special importance due to the presence in that country of territories where the population emits very different opinions of nationalist sentiment than the rest of Spain. The current situation of sovereignty challenge of Catalonia to the central government exemplifies the importance of the subject matter. In order to analyze this process of interrelation, we use a secondary data mining by applying the multiple correspondence analysis technique (MCA). As a main result a typology of four types of expression of collective identity based on models of State organization are shown, which are connected with the party position on this issue.

Keywords: Models of organization of the state, nationalism, collective identity, Spain, political parties.

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Authors: Homayoon Zarshenas, Mahdi Bamdad, Hadi Grailu, Akbar A. Shakoori

Abstract:

In this study we focus on improvement performance of a cue based Motor Imagery Brain Computer Interface (BCI). For this purpose, data fusion approach is used on results of different classifiers to make the best decision. At first step Distinction Sensitive Learning Vector Quantization method is used as a feature selection method to determine most informative frequencies in recorded signals and its performance is evaluated by frequency search method. Then informative features are extracted by packet wavelet transform. In next step 5 different types of classification methods are applied. The methodologies are tested on BCI Competition II dataset III, the best obtained accuracy is 85% and the best kappa value is 0.8. At final step ordered weighted averaging (OWA) method is used to provide a proper aggregation classifiers outputs. Using OWA enhanced system accuracy to 95% and kappa value to 0.9. Applying OWA just uses 50 milliseconds for performing calculation.

Keywords: BCI, EEG, Classifier, Fuzzy operator, OWA.

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Authors: Dinh Ha, Tran, Chung - Ruey Yen

Abstract:

This study explored the morphological characteristics and effects of pollination methods on fruit set and characteristics in 4 red pitaya (Hylocereus spp.) clones. The distinctive morphological recognition and classification among pitaya clones were confirmed by the stem, flower and fruit features. The fruit production season was indicated from the beginning of May to the end of August – the beginning of September with 6-7 flowering cycles per year. The floral stage took from 15-19 days and fruit duration spent 30–32 days. VN White, fully self-compatible, obtained high fruit set rates (80.0–90.5%) in all pollination treatments and the maximum fruit weight (402.6g) in hand self- and (403.4g) in open-pollination. Chaozhou 5 was partially self-compatible while Orejona and F₁₁ were completely self-incompatible. Hand cross-pollination increased significantly fruit set (95.8; 88.4 and 90.2%) and fruit weight (374.2; 281.8 and 416.3 g) in Chaozhou 5, Orejona, and F₁₁, respectively. TSS contents were not much influenced by pollination methods.

Keywords: Hylocereus spp., morphology, floral phenology, pollination requirement.

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Authors: Dinh - Ha Tran, Chung - Ruey Yen

Abstract:

This study explored the morphological characteristics and effects of pollination methods on fruit set and characteristics in 4 red pitaya (Hylocereus spp.) clones. The distinctive morphological recognition and classification among pitaya clones were confirmed by the stem, flower and fruit features. The fruit production season was indicated from the beginning of May to the end of August – the beginning of September with 6-7 flowering cycles per year. The floral stage took from 15-19 days and fruit duration spent 30–32 days. VN White, fully self-compatible, obtained high fruit set rates (80.0–90.5%) in all pollination treatments and the maximum fruit weight (402.6g) in hand self- and (403.4g) in open-pollination. Chaozhou 5 was partially self-compatible while Orejona and F₁₁ were completely self-incompatible. Hand cross-pollination increased significantly fruit set (95.8; 88.4 and 90.2%) and fruit weight (374.2; 281.8 and 416.3g) in Chaozhou 5, Orejona and F₁₁, respectively. TSS contents were not much influcenced by pollination methods.

Keywords: Hylocereus spp., morphology, floral phenology, pollination requirement.

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Authors: O. Hasançebi, S. Kazemzadeh Azad

Abstract:

In the present study the efficiency of Big Bang-Big Crunch (BB-BC) algorithm is investigated in discrete structural design optimization. It is shown that a standard version of the BB-BC algorithm is sometimes unable to produce reasonable solutions to problems from discrete structural design optimization. Two reformulations of the algorithm, which are referred to as modified BB-BC (MBB-BC) and exponential BB-BC (EBB-BC), are introduced to enhance the capability of the standard algorithm in locating good solutions for steel truss and frame type structures, respectively. The performances of the proposed algorithms are experimented and compared to its standard version as well as some other algorithms over several practical design examples. In these examples, steel structures are sized for minimum weight subject to stress, stability and displacement limitations according to the provisions of AISC-ASD.

Keywords: Structural optimization, discrete optimization, metaheuristics, big bang-big crunch (BB-BC) algorithm, design optimization of steel trusses and frames.

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Authors: Hadi Farhadian, Homayoon Katibeh

Abstract:

In this paper, groundwater seepage into Amirkabir tunnel has been estimated using analytical and numerical methods for 14 different sections of the tunnel. Site Groundwater Rating (SGR) method also has been performed for qualitative and quantitative classification of the tunnel sections. The obtained results of above mentioned methods were compared together. The study shows reasonable accordance with results of the all methods unless for two sections of tunnel. In these two sections there are some significant discrepancies between numerical and analytical results mainly originated from model geometry and high overburden. SGR and the analytical and numerical calculations, confirm high concentration of seepage inflow in fault zones. Maximum seepage flow into tunnel has been estimated 0.425 lit/sec/m using analytical method and 0.628 lit/sec/m using numerical method occured in crashed zone. Based on SGR method, six sections of 14 sections in Amirkabir tunnel axis are found to be in "No Risk" class that is supported by the analytical and numerical seepage value of less than 0.04 lit/sec/m.

Keywords: Water Seepage, Amirkabir Tunnel, Analytical Method, DEM, SGR.

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Authors: Jan Sedlacek

Abstract:

The paper focuses on the implementation phase of the strategy of the European Union and the national strategy of the Czech Republic to promote academic and research staff with the potential to produce results that provide innovation useful for economic growth. It deals with the use of financial resources of the Operational Program Education for Competitiveness at the University of West Bohemia in Pilsen. The author presents an example of two strategic projects in the field of human resources – Excellence in Human Resources as a Source of Competitiveness and New Excellence of Human Resources. The subject of this paper is the potential contribution of newly recruited postdoctoral within these projects for the University of West Bohemia in Pilsen and its internal environment.

Keywords: EU funds, public universities, human resources, results of research, funding.

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Authors: Leila Torkaman, Nasser Ghassembaglou

Abstract:

Significant quota of Municipal Electrical Energy consumption is related to Decentralized Air Conditioning which is mostly provided by evaporative coolers. So the aim is to optimize design of air conditioners to increase their efficiencies. To achieve this goal, results of practical standardized tests for 40 evaporative coolers in different types collected and simultaneously results for same coolers based on one of EER (Energy Efficiency Ratio) modeling styles are figured out. By comparing experimental results of different coolers standardized tests with modeling results, preciseness of used model is assessed and after comparing gained preciseness with international standards based on EER for cooling capacity, aeration, and also electrical energy consumption, energy label from A (most effective) to G (less effective) is classified; finally needed methods to optimize energy consumption and coolers’ classification are provided.

Keywords: Cooler, EER, Energy Label, Optimization.

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Authors: Ying Zhao

Abstract:

Keystroke authentication is a new access control system to identify legitimate users via their typing behavior. In this paper, machine learning techniques are adapted for keystroke authentication. Seven learning methods are used to build models to differentiate user keystroke patterns. The selected classification methods are Decision Tree, Naive Bayesian, Instance Based Learning, Decision Table, One Rule, Random Tree and K-star. Among these methods, three of them are studied in more details. The results show that machine learning is a feasible alternative for keystroke authentication. Compared to the conventional Nearest Neighbour method in the recent research, learning methods especially Decision Tree can be more accurate. In addition, the experiment results reveal that 3-Grams is more accurate than 2-Grams and 4-Grams for feature extraction. Also, combination of attributes tend to result higher accuracy.

Keywords: Keystroke Authentication, Pattern recognition, MachineLearning, Instance-based Learning, Bayesian, Decision Tree.

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Authors: Hager Kammoun, Jean Charles Lamirel, Mohamed Ben Ahmed

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In this paper, a model for an information retrieval system is proposed which takes into account that knowledge about documents and information need of users are dynamic. Two methods are combined, one qualitative or symbolic and the other quantitative or numeric, which are deemed suitable for many clustering contexts, data analysis, concept exploring and knowledge discovery. These two methods may be classified as inductive learning techniques. In this model, they are introduced to build “long term" knowledge about past queries and concepts in a collection of documents. The “long term" knowledge can guide and assist the user to formulate an initial query and can be exploited in the process of retrieving relevant information. The different kinds of knowledge are organized in different points of view. This may be considered an enrichment of the exploration level which is coherent with the concept of document/query structure.

Keywords: Information Retrieval Systems, machine learning, classification, Galois lattices, Self Organizing Map.

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Authors: Jeffrey A. Dunne, Kevin Ligozio

Abstract:

In many applications there is a broad variety of information relevant to a focal “object" of interest, and the fusion of such heterogeneous data types is desirable for classification and categorization. While these various data types can sometimes be treated as orthogonal (such as the hull number, superstructure color, and speed of an oil tanker), there are instances where the inference and the correlation between quantities can provide improved fusion capabilities (such as the height, weight, and gender of a person). A service-oriented architecture has been designed and prototyped to support the fusion of information for such “object-centric" situations. It is modular, scalable, and flexible, and designed to support new data sources, fusion algorithms, and computational resources without affecting existing services. The architecture is designed to simplify the incorporation of legacy systems, support exact and probabilistic entity disambiguation, recognize and utilize multiple types of uncertainties, and minimize network bandwidth requirements.

Keywords: Data fusion, distributed computing, service-oriented architecture, SOA

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Authors: Karim Shiraazi, Mahyar Asheghi Milani, Alireza Sadeghi, Eram Azami, Ahadollah Azami

Abstract:

A passive system "Qanat" is collection of some underground wells. A mother-well was dug in a place far from the city where they could reach to the water table maybe 100 meters underground, they dug other wells to direct water toward the city, with minimum possible gradient. Using the slope of the earth they could bring water close to the surface in the city. The source of water or the appearance of Qanat, land slope and the ownership lines are the important and effective factors in the formation of routes and the segment division of lands to the extent that making use of Qanat as the techniques of extracting underground waters creates a channel of routes with an organic order and hierarchy coinciding the slope of land and it also guides the Qanat waters in the tradition texture of salt desert and border provinces of it. Qanats are excavated in a specified distinction from each other. The quantity of water provided by Qanats depends on the kind of land, distance from mountain, geographical situation of them and the rate of water supply from the underground land. The rate of underground waters, possibility of Qanat excavation, number of Qanats and rate of their water supply from one hand and the quantity of cultivable fertile lands from the other hand are the important natural factors making the size of cities. In the same manner the cities with several Qanats have multi central textures. The location of cities is in direct relation with land quality, soil fertility and possibility of using underground water by excavating Qanats. Observing the allowable distance for Qanat watering is a determining factor for distance between villages and cities. Topography, land slope, soil quality, watering system, ownership, kind of cultivation, etc. are the effective factors in directing Qanats for excavation and guiding water toward the cultivable lands and it also causes the formation of different textures in land division of farming provinces. Several divisions such as orderly and wide, inorderly, thin and long, comb like, etc. are the introduction to organic order. And at the same time they are complete coincidence with environmental conditions in the typical development of ecological architecture and planning in the traditional cities and settlements order.

Keywords: Qanat, Settlement Formation, Hot-Arid Region, Sustainable Development

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Authors: S. Kahvecioglu, A. Karamancioglu, A. Yazici

Abstract:

In this paper, a nonlinear model predictive swing-up and stabilizing sliding controller is proposed for an inverted pendulum-cart system. In the swing up phase, the nonlinear model predictive control is formulated as a nonlinear programming problem with energy based objective function. By solving this problem at each sampling instant, a sequence of control inputs that optimize the nonlinear objective function subject to various constraints over a finite horizon are obtained. Then, this control drives the pendulum to a predefined neighborhood of the upper equilibrium point, at where sliding mode based model predictive control is used to stabilize the systems with the specified constraints. It is shown by the simulations that, due to the way of formulating the problem, short horizon lengths are sufficient for attaining the swing up goal.

Keywords: Inverted pendulum, model predictive control, swingup, stabilization.

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Authors: Ali Nouri

Abstract:

Neuroeducation is one of the most exciting research fields which is continually evolving. However, there is a need to develop its theoretical bases in connection to practice. The present paper is a starting attempt in this regard to provide a space from which to think about neuroeducational theory and invoke more investigation in this area. Accordingly, a comprehensive theory of neuroeducation could be defined as grouping or clustering of concepts and propositions that describe and explain the nature of human learning to provide valid interpretations and implications useful for educational practice in relation to philosophical aspects or values. Whereas it should be originated from the philosophical foundations of the field and explain its normative significance, it needs to be testable in terms of rigorous evidence to fundamentally advance contemporary educational policy and practice. There is thus pragmatically a need to include a course on neuroeducational theory into the curriculum of the field. In addition, there is a need to articulate and disseminate considerable discussion over the subject within professional journals and academic societies.

Keywords: Neuroeducation studies, neuroeducational theory, theory building, neuroeducation research.

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