Search results for: prophylactic of professional destruction techniques.

Authors: Abdallah A. Hlayel

Abstract:

Operations research science (OR) deals with good success in developing and applying scientific methods for problem solving and decision-making. However, by using OR techniques, we can enhance the use of computer decision support systems to achieve optimal management for institutions. OR applies comprehensive analysis including all factors that effect on it and builds mathematical modeling to solve business or organizational problems. In addition, it improves decision-making and uses available resources efficiently. The adoption of OR by universities would definitely contributes to the development and enhancement of the performance of OR techniques. This paper provides an understanding of the structures, approaches and models of OR in problem solving and decisionmaking.

Keywords: Best candidates' method, decision making, decision support system, operations research.

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Authors: Kunyanuth Kularbphettong, Phanu Waraporn, Cholticha Tongsiri

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This research aims to create a model for analysis of student motivation behavior on e-Learning based on association rule mining techniques in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The model was created under association rules, one of the data mining techniques with minimum confidence. The results showed that the student motivation behavior model by using association rule technique can indicate the important variables that influence the student motivation behavior on e-Learning.

Keywords: Motivation behavior, e-learning, moodle log, association rule mining.

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Authors: John Kabuba

Abstract:

The study investigated the implementation of the Neural Network (NN) techniques for prediction of the loading of Cu ions onto clinoptilolite. The experimental design using analysis of variance (ANOVA) was chosen for testing the adequacy of the Neural Network and for optimizing of the effective input parameters (pH, temperature and initial concentration). Feed forward, multi-layer perceptron (MLP) NN successfully tracked the non-linear behavior of the adsorption process versus the input parameters with mean squared error (MSE), correlation coefficient (R) and minimum squared error (MSRE) of 0.102, 0.998 and 0.004 respectively. The results showed that NN modeling techniques could effectively predict and simulate the highly complex system and non-linear process such as ionexchange.

Keywords: Clinoptilolite, loading, modeling, Neural network.

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: Semantic data integration, biological ontology, linked data, semantic web, OWL, RDF.

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

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This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: Simulation, visual navigation, mobile robot, data visualization.

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Authors: Rajendra M Sonar

Abstract:

The future of business intelligence (BI) is to integrate intelligence into operational systems that works in real-time analyzing small chunks of data based on requirements on continuous basis. This is moving away from traditional approach of doing analysis on ad-hoc basis or sporadically in passive and off-line mode analyzing huge amount data. Various AI techniques such as expert systems, case-based reasoning, neural-networks play important role in building business intelligent systems. Since BI involves various tasks and models various types of problems, hybrid intelligent techniques can be better choice. Intelligent systems accessible through web services make it easier to integrate them into existing operational systems to add intelligence in every business processes. These can be built to be invoked in modular and distributed way to work in real time. Functionality of such systems can be extended to get external inputs compatible with formats like RSS. In this paper, we describe a framework that use effective combinations of these techniques, accessible through web services and work in real-time. We have successfully developed various prototype systems and done few commercial deployments in the area of personalization and recommendation on mobile and websites.

Keywords: Business Intelligence, Customer Relationship Management, Hybrid Intelligent Systems, Personalization and Recommendation (P&R), Recommender Systems.

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Authors: P. V. V. Rama Rao, M. V. Srikanth, S. Dileep Kumar Varma

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With advances in solid-state power electronic devices and microprocessors, various pulse-width-modulation (PWM) techniques have been developed for industrial applications. This paper presents the comparison of two different PWM techniques, the sinusoidal PWM (SPWM) technique and the space-vector PWM (SVPWM) technique applied to two level VSI for micro grid applications. These two methods are compared by discussing their ease of implementation and by analyzing the output harmonic spectra of various output voltages (line-to-neutral voltages, and line-to-line voltages) and their total harmonic distortion (THD). The SVPWM technique in the under-modulation region can increase the fundamental output voltage by 15.5% over the SPWM technique.

Keywords: SPWM, SVPWM, VSI, Modulation Index.

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Authors: Ehsan Daryadel, Farhad Talaei

Abstract:

Wetlands are one of the most important ecosystems on Earth. Nevertheless, various challenges threaten these ecosystems and disrupt their ecological character. Among these, the effects of human-based threats are more devastating. Following mass degradation of wetlands during 1970s, the Ramsar Convention on Wetlands (Ramsar, Iran, 1971) was concluded to conserve wetlands of international importance and prevent destruction and degradation of such ecosystems through wise use of wetlands as a mean to achieve sustainable development in all over the world. Therefore, in this paper, efforts have been made to analyze threats to wetlands and then investigate solutions in the framework of the Ramsar Convention. Finally, in order to operate these mechanisms, this study concludes that all states should in turn make their best effort to improve and restore global wetlands through preservation of environmental standards and close contribution and also through taking joint measures with other states effectively.

Keywords: Ramsar Convention, Threats, Wetland Ecosystems, Wise Use.

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Authors: Fayez M. Idris, Nehal I. AlZubaidi

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Breast cancer detection techniques have been reported to aid radiologists in analyzing mammograms. We note that most techniques are performed on uncompressed digital mammograms. Mammogram images are huge in size necessitating the use of compression to reduce storage/transmission requirements. In this paper, we present an algorithm for the detection of microcalcifications in the JPEG2000 domain. The algorithm is based on the statistical properties of the wavelet transform that the JPEG2000 coder employs. Simulation results were carried out at different compression ratios. The sensitivity of this algorithm ranges from 92% with a false positive rate of 4.7 down to 66% with a false positive rate of 2.1 using lossless compression and lossy compression at a compression ratio of 100:1, respectively.

Keywords: Breast cancer, JPEG2000, mammography, microcalcifications.

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Authors: K. A. Sumitra Devi, N. P. Banashree, Annamma Abraham

Abstract:

Partitioning is a critical area of VLSI CAD. In order to build complex digital logic circuits its often essential to sub-divide multi -million transistor design into manageable Pieces. This paper looks at the various partitioning techniques aspects of VLSI CAD, targeted at various applications. We proposed an evolutionary time-series model and a statistical glitch prediction system using a neural network with selection of global feature by making use of clustering method model, for partitioning a circuit. For evolutionary time-series model, we made use of genetic, memetic & neuro-memetic techniques. Our work focused in use of clustering methods - K-means & EM methodology. A comparative study is provided for all techniques to solve the problem of circuit partitioning pertaining to VLSI design. The performance of all approaches is compared using benchmark data provided by MCNC standard cell placement benchmark net lists. Analysis of the investigational results proved that the Neuro-memetic model achieves greater performance then other model in recognizing sub-circuits with minimum amount of interconnections between them.

Keywords: VLSI, circuit partitioning, memetic algorithm, genetic algorithm.

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Authors: Shrey Sharma, Gunjan Kumar Verma

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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: Resistivity, inversion, optimization.

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Authors: Rizwan Moeen, Riaz Ahmad, Tanweer Ul Islam, Shahid Ikramullah, Muhammad Umer

Abstract:

Supplier appraisal fosters energy in Supply Chain Management and helps in best optimization of viable business partners for a company. Many Decision Making techniques have already been proposed by researchers for supplier-s appraisal. However, Analytic Hierarchy Process (AHP) is assumed to be the most structured technique to attain near-best solution of the problem. This paper focuses at implementation of AHP in the procurement processes. It also suggests that on what factors a Public Sector Enterprises must focus while dealing with their suppliers and what should the suppliers do to synchronize their activities with the strategic objectives of Organization. It also highlights the weak areas in supplier appraisal process with a view to suggest viable recommendations.

Keywords: AHP, MCDM techniques, Supply Chain Management (SCM), Supplier appraisal.

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Authors: Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

Abstract:

During the past decade, pond aeration systems have been developed which will sustain large quantities of fish and invertebrate biomass. Dissolved Oxygen (DO) is considered to be among the most important water quality parameters in fish culture. Fishponds in aquaculture farms are usually located in remote areas where grid lines are at far distance. Aeration of ponds is required to prevent mortality and to intensify production, especially when feeding is practical, and in warm regions. To increase pond production it is necessary to control dissolved oxygen. Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. This paper presents a new design of diffused aeration system using fuel cell as a power source. Also fuzzy logic control Technique (FLC) is used for controlling the speed of air flow rate from the blower to air piping connected to the pond by adjusting blower speed. MATLAB SIMULINK results show high performance of fuzzy logic control (FLC).

Keywords: aeration system, Fuel cell, Artificial intelligence (AI) techniques, fuzzy logic control

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Authors: Z. Pavlík, M. Čáchová, E. Vejmelková, T. Korecký, J. Fořt, M. Pavlíková, R. Černý

Abstract:

The effect of waste ceramic powder on the thermal properties of lime-pozzolana composites is investigated. At first, the measurements of effective thermal conductivity of lime-pozzolan composites are performed in dependence on moisture content from the dry state to fully water saturated state using a pulse method. Then, the obtained data are analyzed using two different homogenization techniques, namely the Lichtenecker’s and Dobson’s formulas, taking into account Wiener’s and Hashin/Shtrikman bounds. 

Keywords: Waste ceramic powder, lime-pozzolan plasters, effective thermal conductivity, homogenization techniques.

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Authors: Ritu Vijay, Rekha Govil

Abstract:

The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.

Keywords: ANN, RBF, Tidal Data.

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Authors: Lívia B. Meirelles, Erika C. A. N. Chrisman, Flávia B. de Andrade, Lilian C. M. de Oliveira

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True Boiling Point distillation (TBP) is one of the most common experimental techniques for the determination of petroleum properties. This curve provides information about the performance of petroleum in terms of its cuts. The experiment is performed in a few days. Techniques are used to determine the properties faster with a software that calculates the distillation curve when a little information about crude oil is known. In order to evaluate the accuracy of distillation curve prediction, eight points of the TBP curve and specific gravity curve (348 K and 523 K) were inserted into the HYSYS Oil Manager, and the extended curve was evaluated up to 748 K. The methods were able to predict the curve with the accuracy of 0.6%-9.2% error (Software X ASTM), 0.2%-5.1% error (Software X Spaltrohr).

Keywords: Distillation curve, petroleum distillation, simulation, true boiling point curve.

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Authors: N. Ahmed, A.J. Day, J.L. Victory L. Zeall, B. Young

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The manufacture of large-scale precision aerospace components using CNC requires a highly effective maintenance strategy to ensure that the required accuracy can be achieved over many hours of production. This paper reviews a strategy for a maintenance management system based on Failure Mode Avoidance, which uses advanced techniques and technologies to underpin a predictive maintenance strategy. It is shown how condition monitoring (CM) is important to predict potential failures in high precision machining facilities and achieve intelligent and integrated maintenance management. There are two distinct ways in which CM can be applied. One is to monitor key process parameters and observe trends which may indicate a gradual deterioration of accuracy in the product. The other is the use of CM techniques to monitor high status machine parameters enables trends to be observed which can be corrected before machine failure and downtime occurs. It is concluded that the key to developing a flexible and intelligent maintenance framework in any precision manufacturing operation is the ability to evaluate reliably and routinely machine tool condition using condition monitoring techniques within a framework of Failure Mode Avoidance.

Keywords: Maintenance, Condition Monitoring, CNC, Machining, Accuracy, Capability, Key Process Parameters, Critical Parameters

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Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

Abstract:

In this contribution a newly developed elearning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: E-learning environments, intelligent agents, user modeling, Bayesian Networks, computational intelligence.

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Authors: Hy Dang, Bo Mei

Abstract:

The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: Classification, machine learning, time representation, stock prediction.

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Authors: Parvinder S. Sandhu, Roma Jaswal, Sandeep Khimta, Shailendra Singh

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As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done in time especially for the critical applications. As, Neural networks, which have been already applied in software engineering applications to build reliability growth models predict the gross change or reusability metrics. Neural networks are non-linear sophisticated modeling techniques that are able to model complex functions. Neural network techniques are used when exact nature of input and outputs is not known. A key feature is that they learn the relationship between input and output through training. In this present work, various Neural Network Based techniques are explored and comparative analysis is performed for the prediction of level of need of maintenance by predicting level severity of faults present in NASA-s public domain defect dataset. The comparison of different algorithms is made on the basis of Mean Absolute Error, Root Mean Square Error and Accuracy Values. It is concluded that Generalized Regression Networks is the best algorithm for classification of the software components into different level of severity of impact of the faults. The algorithm can be used to develop model that can be used for identifying modules that are heavily affected by the faults.

Keywords: Neural Network, Software faults, Software Metric.

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Authors: Mansour Nikpour, Mohsen Ghasemi, Elahe Mosavi, Mohd Zin Kandar

Abstract:

lack of convenience condition is one of the problems in open spaces in hot and dry regions. Nowadays parks and green landscapes was designed and constructed without any attention to convenience condition. If this process continues, Citizens will encounter with some problems. Harsh climatic condition decreases the efficiency of people-s activities. However there is hard environment condition in hot and dry regions, Convenience condition has been provided in Iranian traditional architecture by using techniques and methods. In this research at the first step characteristics of Iranian garden that can effect on creating sustainable spaces were investigated through observation method. Pleasure space in cities will be created with using these methods and techniques in future cities. Furthermore the comparison between Iranian garden and landscape in today-s cities demonstrate the effectiveness of Iranian garden characteristics on sustainable spaces. Iranian architects used simple and available methods for creating open architectural spaces. In addition desirable conditions were provided with taking in to account both physically and spiritually. Parks and landscapes in future cities can be designed and constructed with respect to architectural techniques that used in Iranian gardens in hot and arid regions.

Keywords: Iranian garden, convenience condition, landscape, sustainable

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Authors: Saimir Heta, Kers Kapaj, Rialda Xhizdari, Ilma Robo

Abstract:

Dealing with emerging cases of dental malpractice with justifications that stem from the clear rules of dental ethics is a phenomenon with an increasing trend in today's dental practice. Dentists should clearly understand how far the limit of malpractice goes, with or without minimal or major consequences, for the affected patient, which can be justified as a complication of dental treatment, in support of the rules of dental ethics in the dental office. Indeed, malpractice can occur in cases of lack of professionalism, but it can also come as a consequence of anatomical and physiological limitations in the implementation of the dental protocols, predetermined and indicated by the patient in the paragraph of the treatment plan in his personal card. Let this article serve as a short communication between readers and interested parties about the problems that dental malpractice can bring to the community. Malpractice should not be seen only as a professional wrong approach, but also as a phenomenon that can occur during dental practice. The aim of this article is presentation of the latest data published in the literature about malpractice. The combination of keywords is done in such a way with the aim to give the necessary space for collecting the right information in the networks of publications about this field, always first from the point of view of the dentist and not from that of the lawyer or jurist. From the findings included in this article, it was noticed that the diversity of approaches towards the phenomenon depends on the different countries based on the legal basis that these countries have. There is a lack of or a small number of articles that touch on this topic, and these articles are presented with a limited amount of data on the same topic. Dental malpractice should not be hidden under the guise of various dental complications that we justify with the strict rules of ethics for patients treated in the dental chair. The individual experience of dental malpractice must be published with the aim of serving as a source of experience for future generations of dentists.

Keywords: Dental ethics, malpractice, professional protocol, random deviation, dental tourism.

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Authors: Kyoung Hoon Kim

Abstract:

This paper presents a comparative exergy analysis of ammonia-water Rankine cycles with and without regeneration and Kalina cycle for recovery of low-temperature heat source. Special attention is paid to the effect of system parameters such as ammonia mass fraction and turbine inlet pressure on the exergetical performance of the systems. Results show that maximum exergy efficiency can be obtained in the regenerative Rankine cycle for high turbine inlet pressures. However, Kalina cycle shows better exergy efficiency for low turbine inlet pressures, and the optimum ammonia mass fractions of Kalina cycle are lower than Rankine cycles.

Keywords: Ammonia-water, Rankine cycle, Kalina cycle, exergy, exergy destruction, low-temperature heat source.

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Authors: Kaumil B. Shah, Hina Chandwani

Abstract:

The modular multilevel converter (MMC) is one of the advanced topologies for medium and high-voltage applications. In high-power, high-voltage MMC, a large number of switching power devices are required. These switching power devices (IGBT) considerable switching losses. This paper analyzes the performance of different discontinuous pulse width modulation (DPWM) techniques and compares the results against a conventional carrier based pulse width modulation method, in order to reduce the switching losses of an MMC. The DPWM reference wave can be generated by adding the zero-sequence component to the original (sine) reference modulation signal. The result of the addition gives the reference signal of DPWM techniques. To minimize the switching losses of the MMC, the clamping period is controlled according to the absolute value of the output load current. No switching is generated in the clamping period so overall switching of the power device is reduced. The simulation result of the different DPWM techniques is compared with conventional carrier-based pulse-width modulation technique.

Keywords: Modular multilevel converter, discontinuous pulse width modulation, switching losses, zero-sequence voltage.

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Authors: Josefina Bengoechea, Alex Bell

Abstract:

Higher education, with its brick-and-mortar facilities and credits-based on hours of study, was developed to serve the needs of a national, industrial, analogue economy. However, the ongoing process of globalization on the one hand, and the emergence of ever-changing needs of employers on the other hand, make this type of process-based education obsolete, and exclusive to students who can afford to pay a full-time tuition and dedicate 4 years of their lives exclusively to study. The creative destruction brought about by new technologies in the 21st century will not only reconfigure the labour market, as millions of jobs will be lost to Artificial Intelligence. The purpose of this paper is to consider if the implementation of technology is the solution to the problems faced in higher education. The paper builds upon a constructivist approach, combining a literature review and research on key publications.

Keywords: Artificial intelligence, employability, labour market, new technology in higher education.

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Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

Abstract:

In this contribution a newly developed e-learning environment is presented, which incorporates Intelligent Agents and Computational Intelligence Techniques. The new e-learning environment is constituted by three parts, the E-learning platform Front-End, the Student Questioner Reasoning and the Student Model Agent. These parts are distributed geographically in dispersed computer servers, with main focus on the design and development of these subsystems through the use of new and emerging technologies. These parts are interconnected in an interoperable way, using web services for the integration of the subsystems, in order to enhance the user modelling procedure and achieve the goals of the learning process.

Keywords: Computational Intelligence, E-learning Environments, Intelligent Agents, User Modelling, Bayesian Networks.

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Authors: Miodrag T. Manić, Dejan I. Tanikić, Miloš S. Stojković, Dalibor M. ðenadić

Abstract:

The design of technological procedures for manufacturing certain products demands the definition and optimization of technological process parameters. Their determination depends on the model of the process itself and its complexity. Certain processes do not have an adequate mathematical model, thus they are modeled using heuristic methods. First part of this paper presents a state of the art of using soft computing techniques in manufacturing processes from the perspective of applicability in modern CAx systems. Methods of artificial intelligence which can be used for this purpose are analyzed. The second part of this paper shows some of the developed models of certain processes, as well as their applicability in the actual calculation of parameters of some technological processes within the design system from the viewpoint of productivity.

Keywords: fuzzy logic, manufacturing, neural networks

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Shailendra Singh

Abstract:

Biometric measures of one kind or another have been used to identify people since ancient times, with handwritten signatures, facial features, and fingerprints being the traditional methods. Of late, Systems have been built that automate the task of recognition, using these methods and newer ones, such as hand geometry, voiceprints and iris patterns. These systems have different strengths and weaknesses. This work is a two-section composition. In the starting section, we present an analytical and comparative study of common biometric techniques. The performance of each of them has been viewed and then tabularized as a result. The latter section involves the actual implementation of the techniques under consideration that has been done using a state of the art tool called, MATLAB. This tool aids to effectively portray the corresponding results and effects.

Keywords: Matlab, Recognition, Facial Vectors, Functions.

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Authors: Faruq A. Al-Omari, Nabeel I. Al-Fayoumi

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In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthesized image is then processed utilizing efficient image processing techniques to cluster the data in the dataset. Henceforth, the algorithm avoids exhaustive search to identify clusters. The algorithm considers only a small set of the data that contains critical boundary information sufficient to identify contained clusters. Compared to available data clustering techniques, the proposed algorithm produces similar quality results and outperforms them in execution time and storage requirements.

Keywords: Data clustering, Data mining, Image-mapping, Pattern discovery, Predictive analysis.

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Authors: B. Bergström, A. Ladd, A. Jones, L. Rosso, P. Michael

Abstract:

Attitudes toward treatment manuals serve as a meaningful predictor of general attitudes toward evidence-based practice. Despite demonstrating high effectiveness in treating many mental disorders, manualized treatments have been underutilized by practitioners. Thus, one can assess the state of the field regarding the adoption of evidence-based practices by surveying practitioner attitudes towards manualized treatments. This study is an adapted replication that assesses psychology graduate student attitudes towards manualized treatments, as a general marker for attitudes towards evidence-based practice. Training programs provide future clinicians with the foundation for critical skills in clinical practice. Research demonstrates that post-graduate continuing education has little to no effect on clinical practice; thus, graduate programs serve as the primary, and often final platform for all future practice. However, there are little empirical data identifying the attitudes and training of graduate students in utilizing manualized treatments. The empirical analysis of this study indicates an increase in positive attitudes among graduate student attitudes towards manualized treatments (within the United States), when compared to past surveys of professional psychologists. Findings from this study may inform graduate programs of barriers for students in developing positive attitudes toward manualized treatments and evidence-based practice. This study also serves as a preliminary predictor of the state-of-the field, in regards to professional psychologists attitudes towards evidence-based practice, if attitudes remain stable. This study indicates that the attitudes toward utilizing evidence-based practices, such as treatment manuals, has become more positive since year 2000.

Keywords: Evidence based treatment, Future of clinical science, Manualized treatment, Student attitudes towards evidence based treatments.

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