Search results for: online classes
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1011

Search results for: online classes

531 Identification of Vessel Class with LSTM using Kinematic Features in Maritime Traffic Control

Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

Abstract:

Prevent abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep Long Short-Term Memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviours far from the expected one, depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behaviour analysis, LSTM

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530 Using Self Organizing Feature Maps for Classification in RGB Images

Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

Abstract:

Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feedforward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on selforganizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: Classification, SOFM, neural network, RGB images.

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529 Multidimensional Data Mining by Means of Randomly Travelling Hyper-Ellipsoids

Authors: Pavel Y. Tabakov, Kevin Duffy

Abstract:

The present study presents a new approach to automatic data clustering and classification problems in large and complex databases and, at the same time, derives specific types of explicit rules describing each cluster. The method works well in both sparse and dense multidimensional data spaces. The members of the data space can be of the same nature or represent different classes. A number of N-dimensional ellipsoids are used for enclosing the data clouds. Due to the geometry of an ellipsoid and its free rotation in space the detection of clusters becomes very efficient. The method is based on genetic algorithms that are used for the optimization of location, orientation and geometric characteristics of the hyper-ellipsoids. The proposed approach can serve as a basis for the development of general knowledge systems for discovering hidden knowledge and unexpected patterns and rules in various large databases.

Keywords: Classification, clustering, data minig, genetic algorithms.

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528 Performance Analysis of Wireless Ad-Hoc Network Based on EDCA IEEE802.11e

Authors: Shah Ahsanuzzaman Md. Tariq, Fabrizio Granelli

Abstract:

IEEE 802.11e is the enhanced version of the IEEE 802.11 MAC dedicated to provide Quality of Service of wireless network. It supports QoS by the service differentiation and prioritization mechanism. Data traffic receives different priority based on QoS requirements. Fundamentally, applications are divided into four Access Categories (AC). Each AC has its own buffer queue and behaves as an independent backoff entity. Every frame with a specific priority of data traffic is assigned to one of these access categories. IEEE 802.11e EDCA (Enhanced Distributed Channel Access) is designed to enhance the IEEE 802.11 DCF (Distributed Coordination Function) mechanisms by providing a distributed access method that can support service differentiation among different classes of traffic. Performance of IEEE 802.11e MAC layer with different ACs is evaluated to understand the actual benefits deriving from the MAC enhancements.

Keywords: 802.11e, fairness, enhanced distributed channelaccess, access categories, quality of Service.

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527 An E-Coaching Methodology for Higher Education in Saudi Arabia

Authors: Essam Almuhsin, Ben Soh, Alice Li, Azmat Ullah

Abstract:

It is widely accepted that university students must acquire new knowledge, skills, awareness, and understanding to increase opportunities for professional and personal growth. The study reveals a significant increase in users engaging in e-coaching activities and a growing need for it during the COVID-19 pandemic. The paper proposes an e-coaching methodology for higher education in Saudi Arabia to address the need for effective coaching in the current online learning environment.

Keywords: Role of e-coaching, e-coaching in higher education, Saudi higher education environment, e-coaching methodology, importance of e-coaching.

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526 Adaptive MPC Using a Recursive Learning Technique

Authors: Ahmed Abbas Helmy, M. R. M. Rizk, Mohamed El-Sayed

Abstract:

A model predictive controller based on recursive learning is proposed. In this SISO adaptive controller, a model is automatically updated using simple recursive equations. The identified models are then stored in the memory to be re-used in the future. The decision for model update is taken based on a new control performance index. The new controller allows the use of simple linear model predictive controllers in the control of nonlinear time varying processes.

Keywords: Adaptive control, model predictive control, dynamic matrix control, online model identification

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525 An Adaptive Fuzzy Clustering Approach for the Network Management

Authors: Amal Elmzabi, Mostafa Bellafkih, Mohammed Ramdani

Abstract:

The Chiu-s method which generates a Takagi-Sugeno Fuzzy Inference System (FIS) is a method of fuzzy rules extraction. The rules output is a linear function of inputs. In addition, these rules are not explicit for the expert. In this paper, we develop a method which generates Mamdani FIS, where the rules output is fuzzy. The method proceeds in two steps: first, it uses the subtractive clustering principle to estimate both the number of clusters and the initial locations of a cluster centers. Each obtained cluster corresponds to a Mamdani fuzzy rule. Then, it optimizes the fuzzy model parameters by applying a genetic algorithm. This method is illustrated on a traffic network management application. We suggest also a Mamdani fuzzy rules generation method, where the expert wants to classify the output variables in some fuzzy predefined classes.

Keywords: Fuzzy entropy, fuzzy inference systems, genetic algorithms, network management, subtractive clustering.

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524 The Willingness of Business Students on T Innovative Behavior within the Theory of Planned Behavior

Authors: Mei L. Lin, Pi-Yueh Cheng

Abstract:

Classes on creativity, innovation, and entrepreneurship are becoming quite popular at universities throughout the world. However, it is not easy for business students to get involved to innovative activities, especially patent application. The present study investigated how to enhance business students- intention to participate in innovative activities and which incentives universities should consider. A 22-item research scale was used, and confirmatory factor analysis was conducted to verify its reliability and validity. Multiple regression and discriminant analyses were also conducted. The results demonstrate the effect of growth-need strength on innovative behavior and indicate that the theory of planned behavior can explain and predict business students- intention to participate in innovative activities. Additionally, the results suggest that applying our proposed model in practice would effectively strengthen business students- intentions to engage in innovative activities.

Keywords: discriminant analysis, growth need strength, innovative behavior, TPB model

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523 Vessel Inscribed Trigonometry to Measure the Vessel Progressive Orientations in the Digital Fundus Image

Authors: Pil Un Kim, Yunjung Lee, Gihyoun Lee, Jin Ho Cho, Myoung Nam Kim

Abstract:

In this paper, the vessel inscribed trigonometry (VITM) for the vessel progression orientation (VPO) is proposed in the two-dimensional fundus image. The VPO is a major factor in the optic disc (OD) detection which is a basic process in the retina analysis. To measure the VPO, skeletons of vessel are used. First, the vessels are classified into three classes as vessel end, vessel branch and vessel stem. And the chain code maps of VS are generated. Next, two farthest neighborhoods of each point on VS are searched by the proposed angle restriction. Lastly, a gradient of the straight line between two farthest neighborhoods is estimated to measure the VPO. VITM is validated by comparing with manual results and 2D Gaussian templates. It is confirmed that VPO of the proposed mensuration is correct enough to detect OD from the results of experiment which applied VITM to detect OD in fundus images.

Keywords: Angle measurement, Optic disc, Retina vessel, Vessel progression orientation.

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522 Statistical Wavelet Features, PCA, and SVM Based Approach for EEG Signals Classification

Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

Abstract:

The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the supportvectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: Discrete Wavelet Transform, Electroencephalogram, Pattern Recognition, Principal Component Analysis, Support Vector Machine.

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521 Applications of Rough Set Decompositions in Information Retrieval

Authors: Chen Wu, Xiaohua Hu

Abstract:

This paper proposes rough set models with three different level knowledge granules in incomplete information system under tolerance relation by similarity between objects according to their attribute values. Through introducing dominance relation on the discourse to decompose similarity classes into three subclasses: little better subclass, little worse subclass and vague subclass, it dismantles lower and upper approximations into three components. By using these components, retrieving information to find naturally hierarchical expansions to queries and constructing answers to elaborative queries can be effective. It illustrates the approach in applying rough set models in the design of information retrieval system to access different granular expanded documents. The proposed method enhances rough set model application in the flexibility of expansions and elaborative queries in information retrieval.

Keywords: Incomplete information system, Rough set model, tolerance relation, dominance relation, approximation, decomposition, elaborative query.

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520 A Hybrid Approach to Fault Detection and Diagnosis in a Diesel Fuel Hydrotreatment Process

Authors: Salvatore L., Pires B., Campos M. C. M., De Souza Jr M. B.

Abstract:

It is estimated that the total cost of abnormal conditions to US process industries is around $20 billion dollars in annual losses. The hydrotreatment (HDT) of diesel fuel in petroleum refineries is a conversion process that leads to high profitable economical returns. However, this is a difficult process to control because it is operated continuously, with high hydrogen pressures and it is also subject to disturbances in feed properties and catalyst performance. So, the automatic detection of fault and diagnosis plays an important role in this context. In this work, a hybrid approach based on neural networks together with a pos-processing classification algorithm is used to detect faults in a simulated HDT unit. Nine classes (8 faults and the normal operation) were correctly classified using the proposed approach in a maximum time of 5 minutes, based on on-line data process measurements.

Keywords: Fault detection, hydrotreatment, hybrid systems, neural networks.

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519 Mathematical Model for the Transmission of Leptospirosis in Juvennile and Adults Humans

Authors: P. Pongsumpun

Abstract:

Leptospirosis occurs worldwide (except the poles of the earth), urban and rural areas, developed and developing countries, especially in Thailand. It can be transmitted to the human by rats through direct and indirect ways. Human can be infected by either touching the infected rats or contacting with water, soil containing urine from the infected rats through skin, eyes and nose. The data of the people who are infected with this disease indicates that most of the patients are adults. The transmission of this disease is studied through mathematical model. The population is separated into human and rat. The human is divided into two classes, namely juvenile and adult. The model equation is constructed for each class. The standard dynamical modeling method is then used for analyzing the behaviours of solutions. In addition, the conditions of the parameters for the disease free and endemic states are obtained. Numerical solutions are shown to support the theoretical predictions. The results of this study guide the way to decrease the disease outbreak.

Keywords: Adult human, juvenile human, leptospirosis, mathematical model.

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518 A Taxonomy of Routing Protocols in Wireless Sensor Networks

Authors: A. Kardi, R. Zagrouba, M. Alqahtani

Abstract:

The Internet of Everything (IoE) presents today a very attractive and motivating field of research. It is basically based on Wireless Sensor Networks (WSNs) in which the routing task is the major analysis topic. In fact, it directly affects the effectiveness and the lifetime of the network. This paper, developed from recent works and based on extensive researches, proposes a taxonomy of routing protocols in WSNs. Our main contribution is that we propose a classification model based on nine classes namely application type, delivery mode, initiator of communication, network architecture, path establishment (route discovery), network topology (structure), protocol operation, next hop selection and latency-awareness and energy-efficient routing protocols. In order to provide a total classification pattern to serve as reference for network designers, each class is subdivided into possible subclasses, presented, and discussed using different parameters such as purposes and characteristics.

Keywords: WSNs, sensor, routing protocols, survey.

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517 Stability Analysis of a Human-Mosquito Model of Malaria with Infective Immigrants

Authors: Nisha Budhwar, Sunita Daniel

Abstract:

In this paper, we analyse the stability of the SEIR model of malaria with infective immigrants which was recently formulated by the authors. The model consists of an SEIR model for the human population and SI Model for the mosquitoes. Susceptible humans become infected after they are bitten by infectious mosquitoes and move on to the Exposed, Infected and Recovered classes respectively. The susceptible mosquito becomes infected after biting an infected person and remains infected till death. We calculate the reproduction number R0 using the next generation method and then discuss about the stability of the equilibrium points. We use the Lyapunov function to show the global stability of the equilibrium points.

Keywords: Susceptible, exposed, infective, recovered, infective immigrants, reproduction number, Lyapunov function, equilibrium points, global stability.

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516 A New Spectral-based Approach to Query-by-Humming for MP3 Songs Database

Authors: Leon Fu, Xiangyang Xue

Abstract:

In this paper, we propose a new approach to query-by-humming, focusing on MP3 songs database. Since MP3 songs are much more difficult in melody representation than symbolic performance data, we adopt to extract feature descriptors from the vocal sounds part of the songs. Our approach is based on signal filtering, sub-band spectral processing, MDCT coefficients analysis and peak energy detection by ignorance of the background music as much as possible. Finally, we apply dual dynamic programming algorithm for feature similarity matching. Experiments will show us its online performance in precision and efficiency.

Keywords: DP, MDCT, MP3, QBH.

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515 Opportunities of an Industrial City in the Leisure Tourism

Authors: E. Happ, A. Albert Tóth

Abstract:

The aim of the research is to investigate the forms of the demands of leisure tourism in a West-Hungarian industrial city, Győr. Today, Győr is still a traditional industrial city, its industry is mainly based on vehicle industry, but the role of tourism is increasing in the life of the city as well. Because of the industrial nature and the strong economy of the city, the ratio of business tourists is high. It can be stated that MICE tourism is dominating in Győr. Developments of the last decade can help the city with new tourism products to increase the leisure tourism. The new types of tourism – besides business tourism – can help the providers to increase the occupancy rates and the demand at the weekends. The research demonstrates the theoretical background of the topic, and it shows the present situation of the tourism in Győr with secondary data. The secondary research contains statistical data from the Hungarian Statistical Office and the city council, and it is based on the providers’ data. The next part of the paper shows the potential types of leisure tourism with the help of primary research. The primary research contains the results of an online questionnaire with a sample of 1000 potential customers. It is completed with 10 in-depth interviews with tourism experts, who explained their opinions about the opportunities of leisure tourism in Győr from the providers’ side. The online questionnaire was filled out in spring 2017 by customers, who have already stayed in Győr or plan to visit the city. At the same time in-depth interviews were made with hotel managers, head of touristic institutions and employees at the council. Based on the research it can be stated that the touristic supply of Győr allows the increase of the leisure tourism ratio in the city. Primarily, the cultural and health tourism show potential development, but the supply side of touristic services can be developed in order to increase the number of guest nights. The tourism marketing needs to be strengthened in the city, and a distinctive marketing activity - from other cities - is needed as well. To conclude, although Győr is an industrial city, it has a transforming industrial part, and tourism is also strongly present in its economy. Besides the leading role of business tourism, different types of leisure tourism have the opportunity to take place in the city.

Keywords: Business Tourism, Győr, industrial city, leisure tourism, touristic demand.

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514 Hybrid Reliability-Similarity-Based Approach for Supervised Machine Learning

Authors: Walid Cherif

Abstract:

Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: Data mining, knowledge discovery, machine learning, similarity measurement, supervised classification.

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513 Remote Sensing, GIS, and AHP for Assessing Physical Vulnerability to Tsunami Hazard

Authors: Abu Bakar Sambah, Fusanori Miura

Abstract:

Remote sensing image processing, spatial data analysis through GIS approach, and analytical hierarchy process were introduced in this study for assessing the vulnerability area and inundation area due to tsunami hazard in the area of Rikuzentakata, Iwate Prefecture, Japan. Appropriate input parameters were derived from GSI DEM data, ALOS AVNIR-2, and field data. We used the parameters of elevation, slope, shoreline distance, and vegetation density. Five classes of vulnerability were defined and weighted via pairwise comparison matrix. The assessment results described that 14.35km2 of the study area was under tsunami vulnerability zone. Inundation areas are those of high and slightly high vulnerability. The farthest area reached by a tsunami was about 7.50km from the shoreline and shows that rivers act as flooding strips that transport tsunami waves into the hinterland. This study can be used for determining a priority for land-use planning in the scope of tsunami hazard risk management.

Keywords: AHP, GIS, remote sensing, tsunami vulnerability.

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512 Orchestra Course Outcomes in Terms of Values Education

Authors: Z. Kurtaslan, H. Hakan Okay, E. Can Dönmez, I. Kuçukdoğan

Abstract:

Music education aims to bring up individuals most appropriately and to advanced levels as a balanced whole physically, cognitively, affectively, and kinesthetically while making a major contribution to the physical and spiritual development of the individual. The most crucial aim of music education, an influential education medium per se, is to make music be loved; yet, among its educational aims are concepts such as affinity, friendship, goodness, philanthropy, responsibility, and respect all extremely crucial bringing up individuals as a balanced whole. One of the most essential assets of the music education is the training of making music together, solidifying musical knowledge and enabling the acquisition of cooperation. This habit requires internalization of values like responsibility, patience, cooperativeness, respect, self-control, friendship, and fairness. If musicians lack these values, the ensemble will become after some certain time a cacophony. In this qualitative research, the attitudes of music teacher candidates in orchestra/chamber music classes will be examined in terms of values.

Keywords: Education, music, orchestra/chamber music, values.

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511 Teaching Turn-Taking Rules and Pragmatic Principles to Empower EFL Students and Enhance Their Learning in Speaking Modules

Authors: O. F. Elkommos

Abstract:

Teaching and learning EFL speaking modules is one of the most challenging productive modules for both instructors and learners. In a student-centered interactive communicative language teaching approach, learners and instructors should be aware of the fact that the target language must be taught as/for communication. The student must be empowered by tools that will work on more than one level of their communicative competence. Communicative learning will need a teaching and learning methodology that will address the goal. Teaching turn-taking rules, pragmatic principles and speech acts will enhance students' sociolinguistic competence, strategic competence together with discourse competence. Sociolinguistic competence entails the mastering of speech act conventions and illocutionary acts of refusing, agreeing/disagreeing; emotive acts like, thanking, apologizing, inviting, offering; directives like, ordering, requesting, advising, and hinting, among others. Strategic competence includes enlightening students’ consciousness of the various particular turn-taking systemic rules of organizing techniques of opening and closing conversation, adjacency pairs, interrupting, back-channeling, asking for/giving opinion, agreeing/disagreeing, using natural fillers for pauses, gaps, speaker select, self-select, and silence among others. Students will have the tools to manage a conversation. Students are engaged in opportunities of experiencing the natural language not as a mere extra student talking time but rather an empowerment of knowing and using the strategies. They will have the component items they need to use as well as the opportunity to communicate in the target language using topics of their interest and choice. This enhances students' communicative abilities. Available websites and textbooks now use one or more of these tools of turn-taking or pragmatics. These will be students' support in self-study in their independent learning study hours. This will be their reinforcement practice on e-Learning interactive activities. The students' target is to be able to communicate the intended meaning to an addressee that is in turn able to infer that intended meaning. The combination of these tools will be assertive and encouraging to the student to beat the struggle with what to say, how to say it, and when to say it. Teaching the rules, principles and techniques is an act of awareness raising method engaging students in activities that will lead to their pragmatic discourse competence. The aim of the paper is to show how the suggested pragmatic model will empower students with tools and systems that would support their learning. Supporting students with turn taking rules, speech act theory, applying both to texts and practical analysis and using it in speaking classes empowers students’ pragmatic discourse competence and assists them to understand language and its context. They become more spontaneous and ready to learn the discourse pragmatic dimension of the speaking techniques and suitable content. Students showed a better performance and a good motivation to learn. The model is therefore suggested for speaking modules in EFL classes.

Keywords: Communicative competence, EFL, empowering learners, enhance learning, speech acts, teaching speaking, turn-taking, learner centered, pragmatics.

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510 Online Web Service based Solution for Urban Traffic Management

Authors: A. Ionita, A. Zafiu, C. Ghita

Abstract:

In this article, we present a web server based solution for implementing a system for intelligent navigation. In this solution we use real time collected data and traffic history to establish the best route for navigation. This is a low cost solution that is easily to implement and extend. There is no need any infrastructure at road network level except only a device that collect data about traffic in key road crossing. The presented solution creates a strong base for traffic pursuit and offers an infrastructure for navigation applications.

Keywords: navigation, real time, route, traffic pursuit, webservice.

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509 An Effective Traffic Control for both Real-time Bursts and Reliable Bursts in OBS Networks

Authors: Yuki Kondo, Takanori Nagano, Yuki Takeda, Young-Bok Choi, Hiromi Okada

Abstract:

Optical burst switching(OBS) is considered as one of preferable network technologies for the next generation Internet. The Internet has two traffic classes, i.e. real-time bursts and reliable bursts. It is an important subject for OBS to achieve cooperated operation of real-time bursts and reliable bursts. In this paper, we proposes a new effective traffic control method named Separate TB+LB (Token Bucket + Leaky Bucket : TB+LB) method. The proposed method presents a new Token Bucket scheme for real-time bursts called as RBO-TB (Real-time Bursts Oriented Token Bucket). The method also applies the LB method to reliable bursts for obtaining better performance. This paper verifies the effectiveness of the Separate TB+LB method through the performance evaluation.

Keywords: leaky bucket, OBS, traffic control, token bucket.

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508 Blended Learning through Google Classroom

Authors: Lee Bih Ni

Abstract:

This paper discusses that good learning involves all academic groups in the school. Blended learning is learning outside the classroom. Google Classroom is a free service learning app for schools, non-profit organizations and anyone with a personal Google account. Facilities accessed through computers and mobile phones are very useful for school teachers and students. Blended learning classrooms using both traditional and technology-based methods for teaching have become the norm for many educators. Using Google Classroom gives students access to online learning. Even if the teacher is not in the classroom, the teacher can provide learning. This is the supervision of the form of the teacher when the student is outside the school.

Keywords: Blended learning, learning app, Google classroom, schools.

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507 Radar Hydrology: New Z/R Relationships for Klang River Basin Malaysia based on Rainfall Classification

Authors: R. Suzana, T. Wardah, A.B. Sahol Hamid

Abstract:

The use of radar in Quantitative Precipitation Estimation (QPE) for radar-rainfall measurement is significantly beneficial. Radar has advantages in terms of high spatial and temporal condition in rainfall measurement and also forecasting. In Malaysia, radar application in QPE is still new and needs to be explored. This paper focuses on the Z/R derivation works of radarrainfall estimation based on rainfall classification. The works developed new Z/R relationships for Klang River Basin in Selangor area for three different general classes of rain events, namely low (<10mm/hr), moderate (>10mm/hr, <30mm/hr) and heavy (>30mm/hr) and also on more specific rain types during monsoon seasons. Looking at the high potential of Doppler radar in QPE, the newly formulated Z/R equations will be useful in improving the measurement of rainfall for any hydrological application, especially for flood forecasting.

Keywords: Radar, Quantitative Precipitation Estimation, Z/R development, flood forecasting

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506 Wavelet - Based Classification of Outdoor Natural Scenes by Resilient Neural Network

Authors: Amitabh Wahi, Sundaramurthy S.

Abstract:

Natural outdoor scene classification is active and promising research area around the globe. In this study, the classification is carried out in two phases. In the first phase, the features are extracted from the images by wavelet decomposition method and stored in a database as feature vectors. In the second phase, the neural classifiers such as back-propagation neural network (BPNN) and resilient back-propagation neural network (RPNN) are employed for the classification of scenes. Four hundred color images are considered from MIT database of two classes as forest and street. A comparative study has been carried out on the performance of the two neural classifiers BPNN and RPNN on the increasing number of test samples. RPNN showed better classification results compared to BPNN on the large test samples.

Keywords: BPNN, Classification, Feature extraction, RPNN, Wavelet.

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505 The Masquerade of Life, Our Many Selves and Issues of Privacy

Authors: Karen Armstrong

Abstract:

This paper explores the importance of privacy in a contemporary online world. Crucial to the discussion is the idea of the Lacanian postmodern fragmented self and the problem of how to ensure that we have room to fully explore various aspects of our personalities in an environment which is–or at least feels--safe and free from observation by others. The paper begins with an exploration of the idea of the self with particular regard to the ways in which contemporary life and technology seems to have multiplied the various faces or masks which we present in different contexts. A brief history of privacy and surveillance follows. Finally, the paper ends with an affirmation of the importance of private space as an essential component of our spiritual and emotional well-being in today-s wired world.

Keywords: Lacan, panopticon, postmodern, privacy, surveillance.

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504 Automata Theory Approach for Solving Frequent Pattern Discovery Problems

Authors: Renáta Iváncsy, István Vajk

Abstract:

The various types of frequent pattern discovery problem, namely, the frequent itemset, sequence and graph mining problems are solved in different ways which are, however, in certain aspects similar. The main approach of discovering such patterns can be classified into two main classes, namely, in the class of the levelwise methods and in that of the database projection-based methods. The level-wise algorithms use in general clever indexing structures for discovering the patterns. In this paper a new approach is proposed for discovering frequent sequences and tree-like patterns efficiently that is based on the level-wise issue. Because the level-wise algorithms spend a lot of time for the subpattern testing problem, the new approach introduces the idea of using automaton theory to solve this problem.

Keywords: Frequent pattern discovery, graph mining, pushdownautomaton, sequence mining, state machine, tree mining.

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503 Virtual Reality Classrooms Strategies for Creating a Social Presence

Authors: Elizabeth M. Hodge, M.H.N. Tabrizi, Mary A. Farwell, Karl L. Wuensch

Abstract:

Delivering course material via a virtual environment is beneficial to today-s students because it offers the interactivity, real-time interaction and social presence that students of all ages have come to accept in our gaming rich community. It is essential that the Net Generation also known as Generation Why, have exposure to learning communities that encompass interactivity to form social and educational connections. As student and professor become interconnected through collaboration and interaction in a virtual learning space, relationships develop and students begin to take on an individual identity. With this in mind the research project was developed to investigate the use of virtual environments on student satisfaction and the effectiveness of course delivery. Furthermore, the project was designed to integrate both interactive (real-time) classes conducted in the Virtual Reality (VR) environment while also creating archived VR sessions for student use in retaining and reviewing course content.

Keywords: Virtual Reality, Social Presence, Virtual Environments, Course Delivery Methods.

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502 Verification and Validation for Java Classes using Design by Contract. The Modular External Approach

Authors: Dario Ramirez de Leon, Oscar Chavez Bosquez, Julian J. Francisco Leon

Abstract:

Since the conception of JML, many tools, applications and implementations have been done. In this context, the users or developers who want to use JML seem surounded by many of these tools, applications and so on. Looking for a common infrastructure and an independent language to provide a bridge between these tools and JML, we developed an approach to embedded contracts in XML for Java: XJML. This approach offer us the ability to separate preconditions, posconditions and class invariants using JML and XML, so we made a front-end which can process Runtime Assertion Checking, Extended Static Checking and Full Static Program Verification. Besides, the capabilities for this front-end can be extended and easily implemented thanks to XML. We believe that XJML is an easy way to start the building of a Graphic User Interface delivering in this way a friendly and IDE independency to developers community wich want to work with JML.

Keywords: Model checking, verification and validation, JML, XML, java, runtime assertion checking, extended static checking, full static program verification.

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