Segmentation of Breast Lesions in Ultrasound Images Using Spatial Fuzzy Clustering and Structure Tensors

Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.

Course Adoption of MS Technologies – Case Study

Motivated by Microsoft Co. Academic Program initiative, the department of Information Technology in King Saud University has adopted Microsoft products in three courses. The initiative aimed at enhancing the abilities of the university graduates and equipping them with skills that would help them in the job market. A number of methods of collecting assessment data were used to evaluate the course adoption initiative. Assessment data indicated that the goal of the course adoption is being achieved and that the students were much better prepared to design applications and administrate networks.

The Robust Clustering with Reduction Dimension

A clustering is process to identify a homogeneous groups of object called as cluster. Clustering is one interesting topic on data mining. A group or class behaves similarly characteristics. This paper discusses a robust clustering process for data images with two reduction dimension approaches; i.e. the two dimensional principal component analysis (2DPCA) and principal component analysis (PCA). A standard approach to overcome this problem is dimension reduction, which transforms a high-dimensional data into a lower-dimensional space with limited loss of information. One of the most common forms of dimensionality reduction is the principal components analysis (PCA). The 2DPCA is often called a variant of principal component (PCA), the image matrices were directly treated as 2D matrices; they do not need to be transformed into a vector so that the covariance matrix of image can be constructed directly using the original image matrices. The decomposed classical covariance matrix is very sensitive to outlying observations. The objective of paper is to compare the performance of robust minimizing vector variance (MVV) in the two dimensional projection PCA (2DPCA) and the PCA for clustering on an arbitrary data image when outliers are hiden in the data set. The simulation aspects of robustness and the illustration of clustering images are discussed in the end of paper

Automatic Camera Calibration for Images of Soccer Match

Camera calibration plays an important role in the domain of the analysis of sports video. Considering soccer video, in most cases, the cross-points can be used for calibration at the center of the soccer field are not sufficient, so this paper introduces a new automatic camera calibration algorithm focus on solving this problem by using the properties of images of the center circle, halfway line and a touch line. After the theoretical analysis, a practicable automatic algorithm is proposed. Very little information used though, results of experiments with both synthetic data and real data show that the algorithm is applicable.

A Review of Critical Success Factor in Building Maintenance Management Practice for University Sector

Building maintenance plays an important role among other activities in building operation. Building defect and damages are part of the building maintenance 'bread and butter' as their input indicated in the building inspection is very much justified, particularly as to determine the building performance. There will be no escape route or short cut from building maintenance work. This study attempts to identify a competitive performance that translates the Critical Success Factor achievements and satisfactorily meet the university-s expectation. The quality and efficiency of maintenance management operation of building depends, to some extent, on the building condition information, the expectation from the university sector and the works carried out for each maintenance activity. This paper reviews the critical success factor in building maintenance management practice for university sectors from four (4) perspectives which include (1) customer (2) internal processes (3) financial and (4) learning and growth perspective. The enhancement of these perspectives is capable to reach the maintenance management goal for a better living environment in university campus.

Real E-Government, Real Convenience

In this paper we have suggested a new system for egovernment. In this method a government can design a precise and perfect system to control people and organizations by using five major documents. These documents contain the important information of each member of a society and help all organizations to do their informatics tasks through them. This information would be available by only a national code and a secure program would support it. The suggested system can give a good awareness to the society and help it be managed correctly.

Trust Building Mechanisms for Electronic Business Networks and Their Relation to eSkills

Globalization, supported by information and communication technologies, changes the rules of competitiveness and increases the significance of information, knowledge and network cooperation. In line with this trend, the need for efficient trust-building tools has emerged. The absence of trust building mechanisms and strategies was identified within several studies. Through trust development, participation on e-business network and usage of network services will increase and provide to SMEs new economic benefits. This work is focused on effective trust building strategies development for electronic business network platforms. Based on trust building mechanism identification, the questionnairebased analysis of its significance and minimum level of requirements was conducted. In the paper, we are confirming the trust dependency on e-Skills which play crucial role in higher level of trust into the more sophisticated and complex trust building ICT solutions.

Detecting Abnormal ECG Signals Utilising Wavelet Transform and Standard Deviation

ECG contains very important clinical information about the cardiac activities of the heart. Often the ECG signal needs to be captured for a long period of time in order to identify abnormalities in certain situations. Such signal apart of a large volume often is characterised by low quality due to the noise and other influences. In order to extract features in the ECG signal with time-varying characteristics at first need to be preprocessed with the best parameters. Also, it is useful to identify specific parts of the long lasting signal which have certain abnormalities and to direct the practitioner to those parts of the signal. In this work we present a method based on wavelet transform, standard deviation and variable threshold which achieves 100% accuracy in identifying the ECG signal peaks and heartbeat as well as identifying the standard deviation, providing a quick reference to abnormalities.

A New Protocol for Concealed Data Aggregation in Wireless Sensor Networks

Wireless sensor networks (WSN) consists of many sensor nodes that are placed on unattended environments such as military sites in order to collect important information. Implementing a secure protocol that can prevent forwarding forged data and modifying content of aggregated data and has low delay and overhead of communication, computing and storage is very important. This paper presents a new protocol for concealed data aggregation (CDA). In this protocol, the network is divided to virtual cells, nodes within each cell produce a shared key to send and receive of concealed data with each other. Considering to data aggregation in each cell is locally and implementing a secure authentication mechanism, data aggregation delay is very low and producing false data in the network by malicious nodes is not possible. To evaluate the performance of our proposed protocol, we have presented computational models that show the performance and low overhead in our protocol.

Monte Carlo Analysis and Fuzzy Sets for Uncertainty Propagation in SIS Performance Assessment

The object of this work is the probabilistic performance evaluation of safety instrumented systems (SIS), i.e. the average probability of dangerous failure on demand (PFDavg) and the average frequency of failure (PFH), taking into account the uncertainties related to the different parameters that come into play: failure rate (λ), common cause failure proportion (β), diagnostic coverage (DC)... This leads to an accurate and safe assessment of the safety integrity level (SIL) inherent to the safety function performed by such systems. This aim is in keeping with the requirement of the IEC 61508 standard with respect to handling uncertainty. To do this, we propose an approach that combines (1) Monte Carlo simulation and (2) fuzzy sets. Indeed, the first method is appropriate where representative statistical data are available (using pdf of the relating parameters), while the latter applies in the case characterized by vague and subjective information (using membership function). The proposed approach is fully supported with a suitable computer code.

Enhancing Learning Experiences in Outcomebased Higher Education: A Step towards Student Centered Learning

Bologna process has influenced enhancing studentcentered learning in Estonian higher education since 2009, but there is no information about what helps or hinders students to achieve learning outcomes and how quality of student-centered learning might be improved. The purpose of this study is to analyze two questions from outcome-based course evaluation questionnaire which is used in Estonian Entrepreneurship University of Applied Sciences. In this qualitative research, 384 students from 22 different courses described what helped and hindered them to achieve learning outcomes. The analysis showed that the aspects that hinder students to achieve learning outcomes are mostly personal: time management, family and personal matters, motivation and non-academic activities. The results indicate that students- learning is commonly supported by school, where teacher, teaching and characteristics of teaching methods help mostly to achieve learning outcomes, also learning material, practical assignments and independent study was brought up as one of the key elements.

Cluster Algorithm for Genetic Diversity

With the hardware technology advancing, the cost of storing is decreasing. Thus there is an urgent need for new techniques and tools that can intelligently and automatically assist us in transferring this data into useful knowledge. Different techniques of data mining are developed which are helpful for handling these large size databases [7]. Data mining is also finding its role in the field of biotechnology. Pedigree means the associated ancestry of a crop variety. Genetic diversity is the variation in the genetic composition of individuals within or among species. Genetic diversity depends upon the pedigree information of the varieties. Parents at lower hierarchic levels have more weightage for predicting genetic diversity as compared to the upper hierarchic levels. The weightage decreases as the level increases. For crossbreeding, the two varieties should be more and more genetically diverse so as to incorporate the useful characters of the two varieties in the newly developed variety. This paper discusses the searching and analyzing of different possible pairs of varieties selected on the basis of morphological characters, Climatic conditions and Nutrients so as to obtain the most optimal pair that can produce the required crossbreed variety. An algorithm was developed to determine the genetic diversity between the selected wheat varieties. Cluster analysis technique is used for retrieving the results.

Classification of Soil Aptness to Establish of Panicum virgatum in Mississippi using Sensitivity Analysis and GIS

During the last decade Panicum virgatum, known as Switchgrass, has been broadly studied because of its remarkable attributes as a substitute pasture and as a functional biofuel source. The objective of this investigation was to establish soil suitability for Switchgrass in the State of Mississippi. A linear weighted additive model was developed to forecast soil suitability. Multicriteria analysis and Sensitivity analysis were utilized to adjust and optimize the model. The model was fit using seven years of field data associated with soils characteristics collected from Natural Resources Conservation System - United States Department of Agriculture (NRCS-USDA). The best model was selected by correlating calculated biomass yield with each model's soils-based output for Switchgrass suitability. Coefficient of determination (r2) was the decisive factor used to establish the 'best' soil suitability model. Coefficients associated with the 'best' model were implemented within a Geographic Information System (GIS) to create a map of relative soil suitability for Switchgrass in Mississippi. A Geodatabase associated with soil parameters was built and is available for future Geographic Information System use.

Role of GIS in Distribution Power Systems

With the prevalence of computer and development of information technology, Geographic Information Systems (GIS) have long used for a variety of applications in electrical engineering. GIS are designed to support the analysis, management, manipulation and mapping of spatial data. This paper presents several usages of GIS in power utilities such as automated route selection for the construction of new power lines which uses a dynamic programming model for route optimization, load forecasting and optimizing planning of substation-s location and capacity with comprehensive algorithm which involves an accurate small-area electric load forecasting procedure and simulates the different cost functions of substations.

Investigating the Individual Difference Antecedents of Perceived Enjoyment in the Acceptance of Blogging

With the proliferation of Weblogs (blogs) use in educational contexts, gaining a better understanding of why students are willing to utilize blog systems has become an important topic for practitioners and academics. While perceived enjoyment has been found to have a significant influence on behavioral intentions to use blogs or hedonic systems, few studies have investigated the antecedents of perceived enjoyment in the acceptance of blogging. The main purpose of the present study is to explore the individual difference antecedents of perceived enjoyment and examine how they influence behavioral intention to blog through the mediation of perceived enjoyment. Based on the previous literature, the Big Five personality traits (i.e., extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience), as well as computer self-efficacy and personal innovation in information technology (PIIT), are hypothesized as potential antecedents of perceived enjoyment in the acceptance of blogging. Data collected from 358 respondents in Taiwan are tested against the research model using the structural equation modeling approach. The results indicate that extraversion, agreeableness, conscientiousness, and PIIT have a significant influence on perceived enjoyment, which in turn significantly influences the behavioral intention to blog. These findings lead to several important implications for future research.

SIFT Accordion: A Space-Time Descriptor Applied to Human Action Recognition

Recognizing human action from videos is an active field of research in computer vision and pattern recognition. Human activity recognition has many potential applications such as video surveillance, human machine interaction, sport videos retrieval and robot navigation. Actually, local descriptors and bag of visuals words models achieve state-of-the-art performance for human action recognition. The main challenge in features description is how to represent efficiently the local motion information. Most of the previous works focus on the extension of 2D local descriptors on 3D ones to describe local information around every interest point. In this paper, we propose a new spatio-temporal descriptor based on a spacetime description of moving points. Our description is focused on an Accordion representation of video which is well-suited to recognize human action from 2D local descriptors without the need to 3D extensions. We use the bag of words approach to represent videos. We quantify 2D local descriptor describing both temporal and spatial features with a good compromise between computational complexity and action recognition rates. We have reached impressive results on publicly available action data set

Analysis and Comparison of Image Encryption Algorithms

With the fast progression of data exchange in electronic way, information security is becoming more important in data storage and transmission. Because of widely using images in industrial process, it is important to protect the confidential image data from unauthorized access. In this paper, we analyzed current image encryption algorithms and compression is added for two of them (Mirror-like image encryption and Visual Cryptography). Implementations of these two algorithms have been realized for experimental purposes. The results of analysis are given in this paper.

Satisfying and Frustrating Aspects of ICT Teaching: A Comparison Based On Self-Efficacy

The purpose of this study was to determine the most satisfying and frustrating aspects of ICT (Information and Communications Technologies) teaching in Turkish schools. Another aim was to compare these aspects based-on ICT teachers- selfefficacy. Participants were 119 ICT teachers from different geographical areas of Turkey. Participants were asked to list salient satisfying and frustrating aspects of ICT teaching, and to fill out the Self-Efficacy Scale for ICT Teachers. Results showed that the high self-efficacy teachers listed more positive and negative aspects of ICT teaching then did the low self-efficacy teachers. The satisfying aspects of ICT teaching were the dynamic nature of ICT subject, higher student interest, having opportunity to help other subject teachers, and lecturing in well-equipped labs, whereas the most frequently cited frustrating aspects of ICT teaching were ICT-related extra works of schools and colleagues, shortages of hardware and technical problems, indifferent students, insufficient teaching time, and the status of ICT subject in school curriculum. This information could be useful in redesigning ICT teachers- roles and responsibilities as well as job environment in schools.

Information and Communication Technologies in Collaboration Projects via the Internet

The aim of this study is to determine the basic information and communication technology (ICT) skills that may be needed by students studying in the 8th grade of the primary education in their cooperative project works implemented via the Internet. Within the scope of the study, the curriculum used for European Computer Driving License (ECDL) and the curriculum used in Turkey are also compared in terms of the ability to use ICT, which is aimed to be provided to the students. The research population of the study, during which the pre test – post test control group experimental model was used, consisted of 40 students from three different schools. In the first stage of the study, the skills that might be needed by students for their cooperative project works implemented via the Internet were determined through examination of the completed Comenious, e – twinning and WorldLinks projects. In the second stage of the study, the curriculums of the Turkish Ministry of National Education (MEB) and ECDL were evaluated by seven different teachers in line with these skills. Also in this study the ECDL and MEB curriculums were compared in terms of capability to provide the skills to implement cooperative projects via the Internet. In line with the findings of the study, the skills that might be needed by students to implement cooperative projects via the Internet were outlined, and existence of a significant difference was established in favor of the ECDL curriculum upon comparison of both curriculums in accordance with this outline (U = 50,500; p

Liquid-Liquid Equilibrium for the Binary Mixtures of α-Pinene + Water and α-Terpineol + Water

α-Pinene is the main component of the most turpentine oils. The hydration of α-pinene with acid catalysts leads to a complex mixture of monoterpenes. In order to obtain more valuable products, the α-pinene in the turpentine can be hydrated in dilute mineral acid solutions to produce α-terpineol. The design of separation processes requires information on phase equilibrium and related thermodynamic properties. This paper reports the results of study on liquid-liquid equilibrium (LLE) of system containing α- pinene + water and α-terpineol + water. Binary LLE for α-pinene + water system, and α-terpineol + water systems were determined by experiment at 301K and atmospheric pressure. The two component mixture was stirred for about 30min, then the mixture was left for about 2h for complete phase separation. The composition of both phases was analyzed by using a Gas Chromatograph. The experimental data were correlated by considering both NRTL and UNIQUAC activity coefficient models. The LLE data for the system of α-pinene + water and α-terpineol + water were correlated successfully by the NRTL model. The experimental data were not satisfactorily fitted by the UNIQUAC model. The NRTL model (α =0.3) correlates the LLE data for the system of α-pinene + water at 301K with RMSD of 0.0404%. And the NRTL model (α =0.61) at 301K with RMSD of 0.0058 %. The NRTL model (α =0.3) correlates the LLE data for the system of α- terpineol + water at 301K with RMSD of 0.1487% and the NRTL model (α =0.6) at 301K with RMSD of 0.0032%, between the experimental and calculated mole fractions.