IJACSA Volume 2 Issue 10 - thesai.org

IJACSA Volume 2 Issue 10

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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Paper 1: Data Mining for Engineering Schools

Abstract: the supervision of the academic performance of engineering students is vital during an early stage of their curricula. Indeed, their grades in specific core/major courses as well as their cumulative General Point Average (GPA) are decisive when pertaining to their ability/condition to pursue Masters’ studies or graduate from a five-year Bachelor-of-Engineering program. Furthermore, these compelling strict requirements not only significantly affect the attrition rates in engineering studies (on top of probation and suspension) but also decide of grant management, developing courseware, and scheduling of programs. In this paper, we present a study that has a twofold objective. First, it attempts at correlating the aforementioned issues with the engineering students’ performance in some key courses taken at early stages of their curricula, then, a predictive model is presented and refined in order to endow advisors and administrators with a powerful decision-making tool when tackling such highly important issues. Matlab Neural Networks Pattern Recognition tool as well as Classification and Regression Trees (CART) are fully deployed with important cross validation and testing. Simulation and prediction results demonstrated a high level of accuracy and offered efficient analysis and information pertinent to the management of engineering schools and programs in the frame of the aforementioned perspective.

Author 1: Chady EI Moucary

Keywords: component; Educational Data Mining; Classification and Regression Trees (CART); Relieff tool; Neural Networks; Prediction; Engineering Students’ Performance; Engineering Students’ Enrollment in Masters’ Studies.

Paper 2: Model of Temperature Dependence Shape of Ytterbium -doped Fiber Amplifier Operating at 915 nm Pumping Configuration

Abstract: We numerically analyze the temperature dependence of an ytterbium-doped fiber amplifier (YDFA) operating at 915 nm, investigating its gain and Noise Figure properties variation with temperature. The temperature-dependent gain and noise figure variation with YDFA length are numerically obtained for the temperature range of +20 0C to +70 0C. The results show that good intrinsic output stability against temperature change can be achieved in ytterbium doped fiber amplifiers even when operating at high gain regime with small signal input. This result demonstrates the great potential for stable high power laser communication systems based on ytterbium system.

Author 1: Abdel Hakeim M

Author 2: Fady I. EL-Nahal

Keywords: YDFA; Gain; Noise Figure.

Paper 3: Healthcare Providers’ Perceptions towards Health Information Applications at King Abdul-Aziz Medical City, Saudi Arabia

Abstract: The purpose of this study was to assess the perceptions of healthcare providers towards health information technology applications in King Abdul-Aziz Medical City (KAMC) in terms of benefits, barriers, and motivation to use these applications. Data Collection: The study population consists of all healthcare providers working at KAMC. A sample size of 623 was drawn from a population of 7493 healthcare providers using convenience random sampling method. Of 623 questionnaires distributed, 377 were returned, giving a response rate of 60.5 percent. Measurement A self-administered questionnaire was developed based on extended literature review. The questionnaire comprised 25 statements measuring benefits, barriers, and motivation to use health information applications to be responded on a five-point Likert-scale. In addition, the questionnaire included questions on demographic and organizational variables. Results: The results show that the majority of healthcare providers had good knowledge and skills in information technology, as most of them use KAMC health information applications regularly and/or had training courses in the field. The results indicated that training has a significant positive effect on health providers' IT knowledge and skills. The majority of healthcare providers perceived that the information technology applications in KAMC are valuable and beneficial to both patients and KAMC. However, the healthcare providers were split over the barriers to HIT use in KAMC. As for drivers, the results showed that healthcare providers generally would be motivated to use IT applications in KAMC by provision of new applications and training, contribution in change hospital's work procedures, and provision of technical support. Finally, the results showed the perceptions of healthcare providers on benefits, barriers and motives were influenced by gender, occupation and training. However, the effect of these variables on healthcare providers towards benefits, barriers and motives of IT use were inconsistent. Conclusion: Despite the perceived benefits and motives of health information applications, there were many barriers identified by healthcare providers. These were insufficient number of computers, frequent system down, and the use of computerized systems is time consuming. Furthermore, there were significant differences in the perceptions of healthcare providers towards benefits, barriers, and motives to health information technology with respect gender, occupation, and training.

Author 1: Abeer Al-Harbi

Keywords: Healthcare providers, Health Information Technology, Computerized Patient Record, King Abdul-Aziz Medical City.

Paper 4: Route Maintenance Approach For Link Breakage Prediction In Mobile Ad Hoc Networks

Abstract: Mobile Ad hoc Network (MANET) consists of a group of mobile nodes that can communicate with each other without the need of infrastructure. The movement of nodes in MANET is random; therefore MANETs have a dynamic topology. Because of this dynamic topology, the link breakages in these networks are something common. This problem causes high data loss and delay. In order to decrease these problems, the idea of link breakage prediction has appeared. In link breakage prediction, the availability of a link is evaluated, and a warning is issued if there is a possibility of soon link breakage. In this paper a new approach of link breakage prediction in MANETs is proposed. This approach has been implemented on the well known Dynamic Source Routing protocol (DSR). This new mechanism was able to decrease the packet loss and delay that occur in the original protocol.

Author 1: Khalid Zahedi

Author 2: Abdul Samad Ismail

Keywords: MANET; link breakage prediction; DSR

Paper 5: Web Service Architecture for a Meta Search Engine

Abstract: With the rapid advancements in Information Technology, Information Retrieval on Internet is gaining its importance day by day. Nowadays there are millions of Websites and billions of homepages available on the Internet. Search Engines are the essential tools for the purpose of retrieving the required information from the Web. But the existing search engines have many problems such as not having wide scope, imbalance in accessing the sites etc. So, the effectiveness of a search engine plays a vital role. Meta search engines are such systems that can provide effective information by accessing multiple existing search engines such as Dog Pile, Meta Crawler etc, but most of them cannot successfully operate on heterogeneous and fully dynamic web environment. In this paper we propose a Web Service Architecture for Meta Search Engine to cater the need of heterogeneous and dynamic web environment. The objective of our proposal is to exploit most of the features offered by Web Services through the implementation of a Web Service Meta Search Engine .

Author 1: K Srinivas

Author 2: P.V.S. Srinivas

Author 3: A.Govardhan

Keywords: Meta Search Engine; Search engine; Web Services.

Paper 6: A Statistical Approach For Latin Handwritten Digit Recognition

Abstract: A simple method based on some statistical measurements for Latin handwritten digit recognition is proposed in this paper. Firstly, a preprocess step is started with thresholding the gray-scale digit image into a binary image, and then noise removal, spurring and thinning are performed. Secondly, by reducing the search space, the region-of-interest (ROI) is cropped from the preprocessed image, then a freeman chain code template is applied and five feature sets are extracted from each digit image. Counting the number of termination points, their coordinates with relation to the center of the ROI, Euclidian distances, orientations in terms of angles, and other statistical properties such as minor-to-major axis length ratio, area and others. Finally, six categories are created based on the relation between number of termination points and possible digits. The present method is applied and tested on training set (60,000 images) and test set (10,000 images) of MNIST handwritten digit database. Our experiments report a correct classification of 92.9041% for the testing set and 95.0953% for the training set.

Author 1: Ihab Zaqout

Keywords: Digit recognition; freeman chain coding; feature extraction; classification.

Paper 7: Plant Leaf Recognition using Shape based Features and Neural Network classifiers

Abstract: This paper proposes an automated system for recognizing plant species based on leaf images. Plant leaf images corresponding to three plant types, are analyzed using two different shape modeling techniques, the first based on the Moments-Invariant (M-I) model and the second on the Centroid-Radii (C-R) model. For the M-I model the first four normalized central moments have been considered and studied in various combinations viz. individually, in joint 2-D and 3-D feature spaces for producing optimum results. For the C-R model an edge detector has been used to identify the boundary of the leaf shape and 36 radii at 10 degree angular separation have been used to build the feature vector. To further improve the accuracy, a hybrid set of features involving both the M-I and C-R models has been generated and explored to find whether the combination feature vector can lead to better performance. Neural networks are used as classifiers for discrimination. The data set consists of 180 images divided into three classes with 60 images each. Accuracies ranging from 90%-100% are obtained which are comparable to the best figures reported in extant literature.

Author 1: Jyotismita Chaki

Author 2: Ranjan Parekh

Keywords: plant recognition; moment invariants; centroid-radii model; neural network; computer vision.

Paper 8: Integrated Information System for reserving rooms in Hotels

Abstract: It is very important to build new and modern flexible dynamic effective compatible reusable information systems including database to help manipulate different processes and deal with many parts around it. One of these is managing the room reservations for groups and individual, to focus necessary needs in hotels and to be integrated with accounting system. This system provides many tools can be used in taking decision.

Author 1: Safarini Osama

Keywords: IS - Information System-, MIS -Management Information System, DFD - Data Flow Diagram, ER- Entity Relationship, and DBMS - Database Management system.

Paper 9: Automatic Classification and Segmentation of Brain Tumor in CT Images using Optimal Dominant Gray level Run length Texture Features

Abstract: Tumor classification and segmentation from brain computed tomography image data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in appearance of tumor tissue among different patients and in many cases, similarity between tumor and normal tissue. This paper deals with an efficient segmentation algorithm for extracting the brain tumors in computed tomography images using Support Vector Machine classifier. The objective of this work is to compare the dominant grey level run length feature extraction method with wavelet based texture feature extraction method and SGLDM method. A dominant gray level run length texture feature set is derived from the region of interest (ROI) of the image to be selected. The optimal texture features are selected using Genetic Algorithm. The selected optimal run length texture features are fed to the Support Vector Machine classifier (SVM) to classify and segment the tumor from brain CT images. The method is applied on real data of CT images of 120 images with normal and abnormal tumor images. The results are compared with radiologist labeled ground truth. Quantitative analysis between ground truth and segmented tumor is presented in terms of classification accuracy. From the analysis and performance measures like classification accuracy, it is inferred that the brain tumor classification and segmentation is best done using SVM with dominant run length feature extraction method than SVM with wavelet based texture feature extraction method and SVM with SGLDM method. In this work,we have attempted to improve the computing efficiency as it selects the most suitable feature extration method that can used for classification and segmentation of brain tumor in CT images efficiently and accurately. An avearage accuracy rate of above 97% was obtained usinh this classification and segmentation algorithm.

Author 1: A PADMA

Author 2: R.Sukanesh

Keywords: Dominant Gray Level Run Length Matrix method (DGLRLM), Support Vector Machine (SVM), Spatial Gray Level Dependence Matrix method (SGLDM), Genetic Algorithm(GA).

Paper 10: An Ontology- and Constraint-based Approach for Dynamic Personalized Planning in Renal Disease Management

Abstract: Healthcare service providers, including those involved in renal disease management, are concerned about the planning of their patients’ treatments. With efforts to automate the planning process, shortcomings are apparent due to the following reasons: (1) current plan representations or ontologies are too fine grained, and (2) current planning systems are often static. To address these issues, we introduce a planning system called Dynamic Personalized Planner (DP Planner) which consists of: (1) a suitably light-weight and generic plan representation, and (2) a constraint-based dynamic planning engine. The plan representation is based on existing plan ontologies, and developed in XML. With the available plans, the planning engine focuses on personalizing pre-existing (or generic) plans that can be dynamically changed as the condition of the patient changes over time. To illustrate our dynamic personalized planning approach, we present an example in renal disease management. In a comparative study, we observed that the resulting DP Planner possesses features that rival that of other planning systems, in particular that of Asgaard and O-Plan.

Author 1: Normadiah Mahiddin,

Author 2: Yu-N Cheah

Author 3: Fazilah Haron

Keywords: patient care planning; treatment protocols; dynamic treatment planning; personal health services.

Paper 11: Asynchronous Checkpointing And Optimistic Message Logging For Mobile Ad Hoc Networks

Abstract: In recent years the advancements in wireless communication technology and mobile computing fueled a steady increase in both number and types of applications for wireless networks. Wireless networks can roughly be classified into cellular networks which use dedicated infrastructure (like base stations) and ad hoc networks without infrastructure. A Mobile Ad Hoc Network (MANET) is a collection of mobile nodes that can communicate with each other using Multihop wireless links without using any fixed infrastructure and centralized controller. Since this type of networks exhibits a dynamic topology, that is, the nodes move very frequently, it is hard to establish some intermittent connectivity in this scenario. Fault tolerance is one of the key issues for MANETs. In a cluster federation, clusters are gathered to provide huge computing power. Clustering methods allow fast connection and also better routing and topology management of mobile ad hoc networks (MANET). To work efficiently on such systems, networks characteristics have to be taken into account, for e.g. the latency between two nodes of different clusters is much higher than the latency between two nodes of the same cluster. In this paper, we present a message logging protocol well-suited to provide fault tolerance for cluster federations in mobile ad hoc networks. The proposed scheme is based on optimistic message logging.

Author 1: Ruchi Tuli

Author 2: Parveen Kumar

Keywords: MANETs, clusterhead, checkpointing, pessimistic logging, fault tolerance, Mobile Host.

Paper 12: An Experimental Improvement Analysis of Loss Tolerant TCP (LT-TCP) For Wireless Network

Abstract: Now-a-days TCP is a famous protocol used in Internet but the main problem is packet losses due to congestion. In this thesis we proposed a new Loss Tolerant TCP (LT-TCP), an enhancement of TCP which makes it robust and applicable for extreme wireless environment. In the proposed LT-TCP two additional term, data and data header compression are added in existing LT-TCP. We reduce the total volume of data and packet size in our adaptive method which is able to minimize the congestion and increase the reliability of wireless communication. The ECN respond about random data packet loss and disruption process. The overhead of Forward Error Control FEC is imposed just-in-time process and target to maximize the performance even if the path characteristics are uncertain. This proposal show that it will perform better over regular TCP and it is possible to reduce packet losses up to 40-50%.

Author 1: Abdullah Al Mamun

Author 2: Sumaya kazary

Author 3: Momotaz Begum

Author 4: Md. Rubel

Keywords: LT-TCP, Mix reliability, Timeouts, Congestion avoidance, end-to-end Algorithms, Compression technique, Packet erasure rate, TCP SACK, RFEC, PFEC, RAR, ECN, throughput, RTT, Goodput.

Paper 13: Comparison of Workflow Scheduling Algorithms in Cloud Computing

Abstract: Cloud computing has gained popularity in recent times. Cloud computing is internet based computing, whereby shared resources, software and information are provided to computers and other devices on demand, like a public utility. Cloud computing is technology that uses the internet and central remote servers to maintain data and applications. This technology allows consumers and businesses to use application without installation and access their personal files at any computer with internet access. The main aim of my work is to study various problems, issues and types of scheduling algorithms for cloud workflows as well as on designing new workflow algorithms for cloud Workflow management system. The proposed algorithms are implemented on real time cloud which is developed using Microsoft .Net Technologies. The algorithms are compared with each other on the basis of parameters like Total execution time, Execution time for algorithm, Estimated execution time. Experimental results generated via simulation shown that Algorithm 2 is much better than Algorithm 1, as it reduced makespan time.

Author 1: Navjot Kaur

Author 2: Taranjit Singh Aulakh

Author 3: Rajbir Singh Cheema

Keywords: Cloud Computing, Workflows, Scheduling, Makespan, Task ordering, Resource Allocation.

Paper 14: Study Of Indian Banks Websites For Cyber Crime Safety Mechansim

Abstract: The human society has undergone tremendous changes from time to time with rapid pace at social level from the beginning and technological level ever since the rise of technologies. This technology word changes the human life in every manner and every sector. Banking field is one of them. Banking in India originated in the last decades of the 18th century. Since that time the banking sector applying different ways to provide facilities and securities to a common man regarding to money. Security issues play extremely important role in the implementation of technologies specially in banking sector. Further on it becomes more critical when it comes to the cyber security which is at the core of banking sector. After the arrival of Internet and WWW this banking sector is totally change specially in terms of security because now money is in your hand on a single click. Now user has number of choices to manage his money with different kind of methods. In this paper an attempt has been made to put forward various issues of Indian banks websites for cyber crime safety mechanism.

Author 1: Susheel Chandra Bhatt

Author 2: Durgesh Pant

Keywords: Cyber, Encryption, Phishing, Secure Socket Layer.

Paper 15: An Empirical Study of the Applications of Web Mining Techniques in Health Care

Abstract: Few years ago, the information flow in health care field was relatively simple and the application of technology was limited. However, as we progress into a more integrated world where technology has become an integral part of the business processes, the process of transfer of information has become more complicated. There has already been a long standing tradition for computer-based decision support, dealing with complex problems in medicine such as diagnosing disease, managerial decisions and assisting in the prescription of appropriate treatment. Today, one of the biggest challenges that health care system, face is the explosive growth of data, use this data to improve the quality of managerial decisions. Web mining and Data mining techniques are analytical tools that can be used to extract meaningful knowledge from large data sets. This paper addresses the applications of web mining and data mining in health care management system to extract useful information from the huge data sets and providing analytical tool to view and use this information for decision making processes by taking real life examples. Further we propose the IDSS model for the health care so that exact and accurate decision can be taken for the removal of a particular disease.

Author 1: Varun Kumar

Author 2: MD. Ezaz Ahmed

Keywords: Web mining; Health care management system; Data mining; Knowledge discovery; Classification; Association rules; Prediction; Outlier analysis, IDSS.

Paper 16: Quality EContent Design using Reusability approach

Abstract: Technology is the one changing ever, and major technological innovations can make a paradigm shifts. The computer network known as the Internet is one such innovation. After affecting sweeping changes in the way people communicate and do business, the Internet is perched to bring about a paradigm shift in the way people learn. Consequently, a major change may also be coming in the way educational materials are designed, developed, and delivered to the learner. An instructional technology called “learning objects” currently leads other candidates for the position of technology of choice in the next generation of instructional design, development, and delivery. This paper aims to address the reusability, generativity, adaptability, and scalability of the content designed using the learning objects. Object-orientation highly values the creation of components (called “objects”) that can be reused in multiple contexts. This is the fundamental idea behind learning objects.

Author 1: Senthil Kumar J

Author 2: Dr S.K.Srivatsa, Ph.D

Keywords: Technology, paradigm, network, learning objects.

Paper 17: Retrieval of Images Using DCT and DCT Wavelet Over Image Blocks

Abstract: This paper introduces a new CBIR system based on two different approaches in order to achieve the retrieval efficiency and accuracy. Color and texture information is extracted and used in this work to form the feature vector. To do the texture feature extraction this system uses DCT and DCT Wavelet transform to generate the feature vectors of the query and database images. Color information extraction process includes separation of image into R, G and B planes. Further each plane is divided into 4 blocks and for each block row mean vectors are calculated. DCT and DCT wavelet is applied over row mean vector of each block separately and 4 sets of DCT and DCT wavelet coefficients are obtained respectively. Out of these few coefficients are selected from each block and arranged in consecutive order to form the feature vector of the image. Variable size feature vectors are formed by changing the no of coefficients selected from each row vector. Total 18 different sets are obtained by changing the no of coefficients selected from each block. These two different feature databases obtained using DCT and DCT wavelet are then tested using 100 query images from 10 different categories. Euclidean distance is used as similarity measure to compare the image features. Euclidean distance calculated is sorted into ascending order and cluster of first 100 images is selected to count the images which are relevant to the query image. Results are further refined using second level thresholding which uses three criteria which can be applied to first level results. Results obtained are showing the better performance by DCT wavelet as compare to DCT transform.

Author 1: H B Kekre

Author 2: Kavita Sonawane

Keywords: component; DCT, DCT wavelet, Eucidean distance.

Paper 18: Cryptanalysis of An Advanced Authentication Scheme

Abstract: In this paper we study a scheme for making cryptanalysis and security improvement. This protocol by Song, is a password authentication protocol using smart card. We note that this protocol has been shown to be prone to the offline password guessing attack. We perform an additional cryptanalysis on this scheme and detect that it is vulnerable to the clogging attack, a type of denial-of-service attack. We notice that all smart card typed authentication schemes which lead the scheme by Song, and need the server to find the computationally exhaustive modular exponentiation, similar to the scheme by Xu et al., and it is vulnerable to the clogging attack. Then we propose an enhancement in the scheme to avoid the clogging attack.

Author 1: Sattar J Aboud

Author 2: Abid T. Al Ajeeli

Keywords: authentication protocol, offline password guessing attack, clogging attack.

Paper 19: Conceptual Level Design of Semi-structured Database System: Graph-semantic Based Approach

Abstract: This paper has proposed a Graph – semantic based conceptual model for semi-structured database system, called GOOSSDM, to conceptualize the different facets of such system in object oriented paradigm. The model defines a set of graph based formal constructs, variety of relationship types with participation constraints and rich set of graphical notations to specify the conceptual level design of semi-structured database system. The proposed design approach facilitates modeling of irregular, heterogeneous, hierarchical and non-hierarchical semi-structured data at the conceptual level. Moreover, the proposed GOOSSDM is capable to model XML document at conceptual level with the facility of document-centric design, ordering and disjunction characteristic. A rule based transformation mechanism of GOOSSDM schema into the equivalent XML Schema Definition (XSD) also has been proposed in this paper. The concepts of the proposed conceptual model have been implemented using Generic Modeling Environment (GME).

Author 1: Anirban Sarkar

Keywords: Semi-structured Data; XML; XSD; Conceptual Modeling; Semi-structured Data Modeling; XML Modeling.