Finding the convex hull of a point set has applications in research fields as well as industrial tools. This paper presents a pre-processing algorithm for computing convex hull vertices in a 2D spatial point set.Based on the position of extreme points we divide the exterior points into four groups bounded by rectangles(p-Rect). Then inside each p-Rect we recursively find and check the extreme points to verify if there are eligible to be convex hull points or not.The process gives a small set of candidates points for convex hull computation.Efficiency of the algorithm is evaluated with respect to time and space. Performance comparison with other classical algorithms shows that implementation of this pre-processing algorithm significantly improves their performance by reducing computational overhead and time.
This paper presents the mathematical morphological and rough set based approach in detection and classification of cancerous masses in MRI mammogram images. Breast cancer increases the mortality rate in India especially in women since it is considered to be the second largest form of disease which leads to death. Mammography is the best method of diagnosing early cancer. The Computer Aided Diagnosis lacks accuracy and it is time consuming. So we propose a hybrid mathematical approach for detection of cancerous masses in MRI mammogram. MRI Mammogram images are enhanced and the artifacts are removed using the Fuzzification technique. The ROI(Region of Interest) is extracted using Graph Cut method and the Four mathematical morphological features are calculated for the segmented contour . The features which play a vital role in classification of masses in mammogram into Normal, Benign and Malignant are extracted using ID3 algorithm. The sensitivity, the specificity, positive prediction value and negative prediction value of the proposed algorithm were determined and compared with the existing algorithms. Automatic classification of the mammogram MRI images is done through three layered Multilayered Perceptron .The weights are adjusted based the Artificial Bee Colony Optimization technique .Both qualitative and quantitative methods are used to detect the accuracy of the proposed system. The sensitivity, the specificity, positive prediction value and negative prediction value of the proposed algorithm accounts to 98.78%, 98.9%, 92% and 96.5% which rates very high when compared to the existing algorithms. The area under the ROC curve is 0.89. A GUI based tool was developed for the proposed methodology. An android application using simulator was developed to make the doctor and patient to view the image with appropriate information like Patient Name, age ,Size of tumor, Nature of tumor and type of treatment .
Social network sites (SNS) in recent times are focusing mainly on user interactions. These SNS are attracting the attention of academic and industry researchers who are intrigued by their accordance and reach rapidly. Mainly data mining techniques have been very effective in using the content and graph structure that was available to solve various problems such as friendship link prediction, estimating the percentage of their friendship…etc. Topic models are one among the most effective approaches to discover latent topic analysis and text data mining. One desirable feature of a social network is to be capable to suggest potential friends to its existing users and the approach must be proved to be effective in improving the predictions. Topic modeling approach provides an easy way to analyze large volume of data and the topic modeling techniques like Latent Dirichlet Allocation (LDA) to uncover latent structure in user interests which have to be explored is going to be implemented. By using LDA, the users are predicting their friends and with the how much amount of percentage ratio they are becoming friends. In this review paper, it has been identified that LDA has a limitation of topic correlation modeling which can be overcome by using CTM (correlated topic model) and it can work better than Arm (Association Rule Mining) for list of 4 or more communities while the tagging can be effectively done when both LDA and association rules are used together.
In process of knowledge discovery from any web-log dataset, most widely and extensively used clustering algorithm for this purpose is Fuzzy c-means (FCM) algorithm because the data of web-log is unsupervised dataset. Due to sensitivity of FCM, it can be easily trapped in a local optimum, and it is also depends on initialization. In this paper we present use of Genetic algorithm in Fuzzy c-means algorithm to select initial center point for clustering in FCM. The purpose of this paper is to provide optimum initial solution for FCM with the help of genetic algorithm to reduce the error rate in pattern creation.
Cybercrime has increased exponentially in conjunction with the introduction and widespread use of electronic medium. This is not just confined to one area, but rather is occurring worldwide. Some progress has been made to counter this type of crime, but criminal legislation which crosses international borders is severely lagging behind. Some sort of public policy must be adopted, according to individuals, educational institutions, organizations and corporations who are interested in combating this wave of crime.
Now a day's the broad casting of video place's a major role in wireless network. If we want to broadcast a video, it takes a time to transmit from source to destination, due to large size of video. In wireless network the packet must be lightweight, due to that it takes a large amount of time to transmit large file. We propose a technique to easily transmit or broadcast the data/video efficiently with short duration. If a node wants to do video broadcast it can select the video and transmit in the transmission our (data) video is divided (splitting) small packets these packets are less weight, due to that packets are easily move in the wireless network with less time when compare to previous one. Now a day's the broad casting of video place's a major role in wireless network. If we want to broadcast a video, it takes a time to transmit from source to destination, due to large size of video. In wireless network the packet must be lightweight, due to that it takes a large amount of time to transmit large file. We propose a technique to easily transmit or broadcast the data/video efficiently with short duration. If a node wants to do video broadcast it can select the video and transmit in the transmission our (data) video is divided (splitting) small packets these packets are less weight, due to that packets are easily move in the wireless network with less time when compare to previous one. After reaching all packets to the destination we are going to merge the packets according to the sequence number which is already allocated while doing the splitting with help of Selective repeat algorithm we can achieve it. Furthermore, we use low complexity algorithm's (approximation algorithm) for selecting the most energy efficient distribution for the entire set of directed acyclic graph (DAG). The flow selection and resource allocation process is adapted for each video frame. The flow selection and resource process is adapted in each video layer.
Due to the inherent property of mobile ad hoc network, nodes in this environment move arbitrarily or illogically.Due to the mobility of nodes the topology changes dynamically.As routing of data in such dynamic topology is an important issue in mobile ad hoc network, so the selection of suitable routing protocol is necessary which enables to route data between mobile nodes efficiently by using less bandwidth of the network.Each routing protocol has its own architecture and working.Routing protocols behave differently under different environments.Thus, it is necessary to analyze the behavior of different routing protocols under different environments.Many studies have been done on the performance evaluation of routing protocols of MANET, but most of these studies are based on IPv4.On the other hand, IPv6 gains popularity because it has some additional features over IPv4 as it supports multicasting, multi-homing, efficient routing.IPv6 is more secure as compared to IPv4 and has large address space to support.On account of these features of IPv6, many organizations are moving to use IPv6, and therefore, it is worthwhile to evaluate the performance of routing protocols under IPv6 environment.In this research performance of two ad hoc routing protocols OLSR and AODV evaluated under IPv6 environment on the basis of end-to-end delay, throughput, and network load.The objective of this research is to investigate how these routing protocols behave under IPv6 environment and identify which routing protocol performs better.OPNET Modeler 14.5 is used as simulation tool.On the basis of simulations we conclude that OLSR performs well which proves that it is suitable for efficient routing.
- Since the inception of elliptic curve cryptography by Koblitz [1] and Miller [2] for implementing public-key protocols as the Diffie-Hellman key agreement, elliptic curve cryptography has become one of the most researched area for providing one stop reliable and secure solution in the field of cryptography. The ECC covers all relevant asymmetric cryptographic primitives like digital signature (ECDSA), key exchange and agreement protocols. Point multiplication serves as the basic building block in all ECC primitives and is the computationally most expensive operation and our analysis revolves around this concept. This paper gives an introduction to Elliptic Curve Cryptography and deals with evaluation of fast scalar multiplication with parallelization of field operation and point addition/multiplication. Elliptic curve cryptography offers best optimized solution with minimum resources like Low memory, High Throughput, low power consumption and minimum key length for the same level of security as compared to its counterpart like RSA, DSA etc. in public key cryptography domain. The work is based on the extensive research work done by Julio Lopez, Ricardo Dahab, Montgomery and other pioneer scientists and academicians in the field of elliptic curve cryptography. Given the importance of Scalar multiplication , we focused ourselves on the Fast Multiplication on Elliptic Curves over finite Binary field GF(2m) without Pre-computation whose background is set by Julio Lopez et al. in [1], because the finite field operations can be implemented very efficiently in hardware and software.
In network based network mobility (N-NEMO), the automatic network selection during the mobility and handover scenarios are very challenging process. Most of the existing works concentrate only on selection of target network during handover execution. Also the user's Quality of Service (QoS) requirements are not taken into consideration. Approach: In this paper, we propose a QoS based handover technique for network-based network mobility (N-NEMO). The proposed architecture uses tunnel splitting scheme that establishes the global tunnel among local mobility anchor (LMA) and mobile access gateway (MAG) and local tunnel among mobile router (MR) and MAG respectively. Each mobile node estimates the QoS preferences such as bandwidth, battery power, received signal strength and link quality. Based on the estimated value, the priority list of MAG is build so that the best suitable MAG appears first in the list. The generated priority list is sent to the core network along with the handover request. Based on the handover scenario, core network executes either inter-domain or intra-domain handover technique. Results: By simulation results, we show that the proposed technique is efficient in terms of throughput, bandwidth usage, power conservation and delay.Conclusion: An effective QoS based handover technique is designed for N-NEMO.
Virtual reality has gained traction as a research, education and treatment tool. Virtual reality is a system that immerses people in virtual worlds and improves clinicians’ traditional treatments for addictive disorders, eating disorders, phobias, and stroke rehabilitation. Sex addiction is a dysregulation of sexual desire, characterized by excessive sexual behavior (between 5-15 sexual activities/day, for more than 6 months, after the age of 15). Hypersexuality highlights disturbances in human sexual desire, motivation, and behavior systems. Virtual reality worlds were initially designed to treat smokers and alcoholics, and are now programmed for drug users and other kind of addictions. In this article we present different characteristics of sex addiction and possible treatments, including the virtual exposure treatment.
Tree automata have been defined to accept trees. Different types of acceptance like bottom-up, top-down, tree walking have been considered in the literature. In this paper, we consider bottom-up tree automata and discuss the sequential distributed version of this model. Generally, this type of distribution is called cooperative distributed automata or the blackboard model. We define the traditional five modes of cooperation, viz. ∗-mode, t-mode, = k, ≥ k, ≤ k (k ≥ 1) modes on bottom-up tree automata. We discuss the accepting power of cooperative distributed tree automata under these modes of cooperation. We find that the ∗- mode does not increase the power, whereas the other modes increase the power. We discuss a few results comparing the acceptance power under different modes of cooperation.
Electrical current flow within populations of neurons is a fundamental constituent of brain function. The resulting fluctuating magnetic fields may be sampled noninvasively with an array of magnetic field detectors positioned outside a patient’s head. This is magnetoencephalography (MEG). Each source may be characterized by 5-6 parameters, the xyz location and the xyz direction. The magnetic field measurements are nonlinear in the location parameters; hence the source location is identifiable only via search of the brain volume. When there is one or a very few sources, this may be practical; solutions for the general problem are weak. Referee consensus is a new method which enables identification of one source at a time regardless of the number and location of others. This “independence” enables solution of the general problem and insures suitability to grid computing. The computation scales linearly with the number of nonlinear parameters. MEG recordings were obtained from volunteers while they performed a cognitive task The recordings were processed on the Open Science Grid (≈150 CPU hours/sec of data). On average 500-1500 sources were active throughout. Statistical analyses demonstrated < 2 mm resolving power [1] and very strong findings (p < 0.02 400 ) when testing for task specific information in the extracted virtual recordings from each individual. 3D maps of differential activation, neuroelectric tomography, provide a very high resolution functional imaging modality which compares favorably with functional MR imaging. Referee consensus is applicable widely to measurement systems including microwave telescope imaging, seismic tomography, and financial market linkage identification. Applicability requires: (1) The measurements are linear in at least one parameter of each “source.” (2) Each source is detectable at multiple sensors. (3) A sequence of measurements in time is available. [1] Linear dimensions are represented in this standard form. Volume dimensions are represented throughout in terms of the length of a side, e.g. 8mm 3 instead of ½ cc, ½ cm 3 or 512 mm 3 .
We introduce a new method for exploratory analysis of large data sets with time-varying features, where the aim is to automatically discover novel relationships between features (over some time period) that are predictive of any of a number of time-varying outcomes (over some other time period). Using a genetic algorithm, we co-evolve (i) a subset of predictive features, (ii) which attribute will be predicted (iii) the time period over which to assess the predictive features, and (iv) the time period over which to assess the predicted attribute. After validating the method on 15 synthetic test problems, we used the approach for exploratory analysis of a large healthcare network data set. We discovered a strong association, with 100% sensitivity, between hospital participation in multi-institutional quality improvement collaboratives during or before 2002, and changes in the risk-adjusted rates of mortality and morbidity observed after a 1-2 year lag. The proposed approach is a potentially powerful and general tool for exploratory analysis of a wide range of time-series data sets.
Programming teaching is a complex task, mainly because of the students’ difficulties on building structured solutions and also on problems interpretation. At introductory courses, we need to develop on students, programming skills to help them to apply their knowledge effectively on solving problems. This led us to use an approach that will be followed from the problem presentation until the development of a properly structured program. Its application in CS1/2, which we have taught in recent years, allowed an increase in approval rating and in the quality of the solutions presented, it also has proved to be adapted to the needs of teaching programming with different imperative programming languages. In this work we illustrate the approach with a simple example. We also present an evaluation of the methodology done with a population of 130 students at introductory courses using C and Java languages.
constructivist learning, connectivism, problem-based learning Abstract The contemporary era of social media and web 2.0 has enabled a bottom-up on-line collaborative approach with easy content creation and subsequent knowledge sharing. The technically literate students of today and the changes in pedagogy towards a user-centred approach, where learners engage in the learning process by constructing new ideas and concepts based on their current or past knowledge facilitate the use of social media in learning environments. This paper describes the combination of a wiki and screen capture videos as a complementary addition to conventional lectures in an information management and information systems development course. The basis for our approach was collaborative problem-based learning with concrete problems defined by students. In order to activate students they were asked to identify unclear concepts or issues from four not well-defined or clarified lecture themes. The students worked in small groups. After the groups selected the theme which was most unclear to them they created presentations associated with these issues. Our intention was to facilitate collaborative learning by using the principles of the Jigsaw method. The results from the experiment showed that videowiki-based coursework affects both external and internal motivation equally in most cases. This reflects that from the perspective of constructivism the videowiki-based assignment is equally effective compared to learning without this setting. However, the development of knowledge concerning different course themes was positive in groups of students who completed this videowiki assignment. 1
Abstract ¾ Recently, unstructured data on the World Wide Web has generated significant interest in the extraction of text, emails, web pages, reports and research papers in their raw form. Far more interestingly, extracting information from a specific domain using distributed corpora from the World Wide Web is a vital step towards creating corpus annotation. This paper describes a method of annotation, based on concepts from Information Science, to build a domain ontology, using Natural Language Programming (NLP) technology. We used Java Annotation Patterns Engine ( JAPE) grammars to support regular expression matching and thus annotate IS concepts using a GATE developer tool. This speeds up the time-consuming development of the ontology which is important for experts in the domain facing time constraints and high workloads. The rules provide significant results: the pattern matching of IS concepts based on the lookup list produced 403 correct concepts and the accuracy was generally higher, with 0 partially correct, missing and false positive results. Using NLP technique is good approaches to reduce the domain expert’s work and they can be evaluated the results
Interaction design, Security, Physical playing, Testing Abstract - This paper addresses the use of technology as a supplement to traditional and well-known dynamics of play. By examining the use of the Interactive Trampoline in the development process of play activities, this paper seeks to emphasise the relationship between physical activity, safety, enjoyment and sociality as factors that will be important to future development of interactive play design for play. The findings show us that, in order to design fun play activities that sustain children's interest over a prolonged period, we need to consider childrens play practices within their communities of play, and as part of the solution for a safer environment.
Cloud Computing has become most demanding utility or service for the current era, because of its high computing power, performance, cheapness, accessibility, scalability, and availability. But still it is in infancy stage, and has some pitfalls which are due to non-existence of standards. Interoperability and portability are the two among the major issues in Cloud Computing. Authors have pointed out these issues and how actually interoperability and portability issues would be encountered? Authors propose architecture to address these two issues with the collaboration of next emerging technology i.e., agents and XMPP protocol. As there is an architecture proposed before using agents but in this paper first time both features of an agent i.e. intelligence and mobility are used in some particular way. Mobility is for movement among different clouds, as agents are interoperable by default as per FIPA (Foundation of Intelligent Physical Agent), and intelligence is to take the wise decision by keeping number of attributes in the database i.e. workload per service on each machine, distance between the clouds and services available on each cloud to fix the above cited problems. Keywords– Interoperability, Portability, Open Clouds, FIPA Agents and XMPP
Tablets with touch-screens, multi-touch interfaces and various sensors are becoming increasingly common. More and more schools are testing them with their pupils in the hope of bringing pedagogic benefits. Thanks to this new type of device, new sets of interactions can be thought of. Many studies have tested user reception of innovative interactions. At the present time, pedagogic benefits can be evaluated to resolve 3D geometry problems. In this paper, we present a categorization of interactions in 3D geometry learning context. We present closer an already accepted set of interactions to manage rotation of solids and we evaluated its pedagogic benefit on a test group of learners aged 9 to 15. We propose a protocol based on mathematics didactic and pedagogy. We compared the set of interactions with classic sheets of paper and solids. Our results show that using our set of interactions increase significantly good answers.
Today’s Global era needs laws governing fast paced cyber crime. The popularity of on-line transaction is on the rise thereby having attempts made by unscrupulous entities to defraud internet users. The modus operandi may be in the form of Hacking, Spoofing, Pornography, Scanners, Device, Fake card and the like. The Educational sectors, Defense sector, Law Enforcement Bodies, Bank sectors are exposed to risk as the information sought usually includes data such as username, passwords, bank account and credit card number, revelation of which is huge loss for not only every individual but also the state at large. The paper is an analysis of the USA Laws for Cyber Crime with a comparative analysis with the Indian Laws. The aim is to analyze the conviction rate in cyber crime with comparison to both the countries and suggest various remedies.
