Search results for: mobile database
244 A General Mandatory Access Control Framework in Distributed Environments
Authors: Feng Yang, Xuehai Zhou, Dalei Hu
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In this paper, we propose a general mandatory access framework for distributed systems. The framework can be applied into multiple operating systems and can handle multiple stakeholders. Despite considerable advancements in the area of mandatory access control, a certain approach to enforcing mandatory access control can only be applied in a specific operating system. Other than PC market in which windows captures the overwhelming shares, there are a number of popular operating systems in the emerging smart phone environment, i.e. Android, Windows mobile, Symbian, RIM. It should be noted that more and more stakeholders are involved in smartphone software, such as devices owners, service providers and application providers. Our framework includes three parts—local decision layer, the middle layer and the remote decision layer. The middle layer takes charge of managing security contexts, OS API, operations and policy combination. The design of the remote decision layer doesn’t depend on certain operating systems because of the middle layer’s existence. We implement the framework in windows, linux and other popular embedded systems.
Keywords: Mandatory Access Control, Distributed System, General Platform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2232243 High-Value Health System for All: Technologies for Promoting Health Education and Awareness
Authors: M. P. Sebastian
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Health for all is considered as a sign of well-being and inclusive growth. New healthcare technologies are contributing to the quality of human lives by promoting health education and awareness, leading to the prevention, early diagnosis and treatment of the symptoms of diseases. Healthcare technologies have now migrated from the medical and institutionalized settings to the home and everyday life. This paper explores these new technologies and investigates how they contribute to health education and awareness, promoting the objective of high-value health system for all. The methodology used for the research is literature review. The paper also discusses the opportunities and challenges with futuristic healthcare technologies. The combined advances in genomics medicine, wearables and the IoT with enhanced data collection in electronic health record (EHR) systems, environmental sensors, and mobile device applications can contribute in a big way to high-value health system for all. The promise by these technologies includes reduced total cost of healthcare, reduced incidence of medical diagnosis errors, and reduced treatment variability. The major barriers to adoption include concerns with security, privacy, and integrity of healthcare data, regulation and compliance issues, service reliability, interoperability and portability of data, and user friendliness and convenience of these technologies.
Keywords: Bigdata, education, healthcare, ICT, patients, technologies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1044242 Exploring the Potential of Chatbots in Higher Education: A Preliminary Study
Authors: S. Studente, S. Ellis, S. F. Garivaldis
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We report upon a study introducing a chatbot to develop learning communities at a London University, with a largely international student base. The focus of the chatbot was twofold; to ease the transition for students into their first year of university study, and to increase study engagement. Four learning communities were created using the chatbot; level 3 foundation, level 4 undergraduate, level 6 undergraduate and level 7 post-graduate. Students and programme leaders were provided with access to the chat bot via mobile app prior to their study induction and throughout the autumn term of 2019. At the end of the term, data were collected via questionnaires and focus groups with students and teaching staff to allow for identification of benefits and challenges. Findings indicated a positive correlation between study engagement and engagement with peers. Students reported that the chatbot enabled them to obtain support and connect to their programme leader. Both staff and students also made recommendation on how engagement could be further enhanced using the bot in terms of; clearly specified purpose, integration with existing university systems, leading by example and connectivity. Extending upon these recommendations, a second pilot study is planned for September 2020, for which the focus will be upon improving attendance rates, student satisfaction and module pass rates.
Keywords: Chatbot, e-learning, learning communities, student engagement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1716241 Biomass Gasification and Microcogeneration Unit – EZOB Technology
Authors: Martin Lisý, Marek Baláš, Michal Špiláček, Zdeněk Skála
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This paper deals with the issue of biomass and sorted municipal waste gasification and cogeneration using hot-air turbo-set. It brings description of designed pilot plant with electrical output 80 kWe. The generated gas is burned in secondary combustion chamber located beyond the gas generator. Flue gas flows through the heat exchanger where the compressed air is heated and consequently brought to a micro turbine. Except description, this paper brings our basic experiences from operating of pilot plant (operating parameters, contributions, problems during operating, etc.). The principal advantage of the given cycle is the fact that there is no contact between the generated gas and the turbine. So there is no need for costly and complicated gas cleaning which is the main source of operating problems in direct use in combustion engines because the content of impurities in the gas causes operation problems to the units due to clogging and tarring of working surfaces of engines and turbines, which may lead as far as serious damage to the equipment under operation. Another merit is the compact container package making installation of the facility easier or making it relatively more mobile. We imagine, this solution of cogeneration from biomass or waste can be suitable for small industrial or communal applications, for low output cogeneration.
Keywords: Biomass, combustion, gasification, microcogeneration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1886240 Employing QR Code as an Effective Educational Tool for Quick Access to Sources of Kindergarten Concepts
Authors: Ahmed Amin Mousa, M. Abd El-Salam
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This study discusses a simple solution for the problem of shortage in learning resources for kindergarten teachers. Occasionally, kindergarten teachers cannot access proper resources by usual search methods as libraries or search engines. Furthermore, these methods require a long time and efforts for preparing. The study is expected to facilitate accessing learning resources. Moreover, it suggests a potential direction for using QR code inside the classroom. The present work proposes that QR code can be used for digitizing kindergarten curriculums and accessing various learning resources. It investigates using QR code for saving information related to the concepts which kindergarten teachers use in the current educational situation. The researchers have established a guide for kindergarten teachers based on the Egyptian official curriculum. The guide provides different learning resources for each scientific and mathematical concept in the curriculum, and each learning resource is represented as a QR code image that contains its URL. Therefore, kindergarten teachers can use smartphone applications for reading QR codes and displaying the related learning resources for students immediately. The guide has been provided to a group of 108 teachers for using inside their classrooms. The results showed that the teachers approved the guide, and gave a good response.
Keywords: Kindergarten, child, learning resources, QR code, smart phone, mobile.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1555239 Application of RP Technology with Polycarbonate Material for Wind Tunnel Model Fabrication
Authors: A. Ahmadi Nadooshan, S. Daneshmand, C. Aghanajafi
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Traditionally, wind tunnel models are made of metal and are very expensive. In these years, everyone is looking for ways to do more with less. Under the right test conditions, a rapid prototype part could be tested in a wind tunnel. Using rapid prototype manufacturing techniques and materials in this way significantly reduces time and cost of production of wind tunnel models. This study was done of fused deposition modeling (FDM) and their ability to make components for wind tunnel models in a timely and cost effective manner. This paper discusses the application of wind tunnel model configuration constructed using FDM for transonic wind tunnel testing. A study was undertaken comparing a rapid prototyping model constructed of FDM Technologies using polycarbonate to that of a standard machined steel model. Testing covered the Mach range of Mach 0.3 to Mach 0.75 at an angle-ofattack range of - 2° to +12°. Results from this study show relatively good agreement between the two models and rapid prototyping Method reduces time and cost of production of wind tunnel models. It can be concluded from this study that wind tunnel models constructed using rapid prototyping method and materials can be used in wind tunnel testing for initial baseline aerodynamic database development.Keywords: Polycarbonate, Fabrication, FDM, Model, RapidPrototyping, Wind Tunnel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2446238 Attention Based Fully Convolutional Neural Network for Simultaneous Detection and Segmentation of Optic Disc in Retinal Fundus Images
Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara
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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.Keywords: Ocular diseases, retinal fundus image, optic disc detection and segmentation, fully convolutional network, overlap measure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 780237 Ubiquitous Life People Informatics Engine (U-Life PIE): Wearable Health Promotion System
Authors: Yi-Ping Lo, Shi-Yao Wei, Chih-Chun Ma
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Since Google launched Google Glass in 2012, numbers of commercial wearable devices were released, such as smart belt, smart band, smart shoes, smart clothes ... etc. However, most of these devices perform as sensors to show the readings of measurements and few of them provide the interactive feedback to the user. Furthermore, these devices are single task devices which are not able to communicate with each other. In this paper a new health promotion system, Ubiquitous Life People Informatics Engine (U-Life PIE), will be presented. This engine consists of People Informatics Engine (PIE) and the interactive user interface. PIE collects all the data from the compatible devices, analyzes this data comprehensively and communicates between devices via various application programming interfaces. All the data and informations are stored on the PIE unit, therefore, the user is able to view the instant and historical data on their mobile devices any time. It also provides the real-time hands-free feedback and instructions through the user interface visually, acoustically and tactilely. These feedback and instructions suggest the user to adjust their posture or habits in order to avoid the physical injuries and prevent illness.Keywords: Machine learning, user interface, user experience, Internet of things, health promotion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1432236 Tool Tracker: A Toolkit Ensembling Useful Online Networking Tools for Efficient Management and Operation of a Network
Authors: Onkar Bhat Kodical, Sridhar Srinivasan, N.K. Srinath
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Tool Tracker is a client-server based application. It is essentially a catalogue of various network monitoring and management tools that are available online. There is a database maintained on the server side that contains the information about various tools. Several clients can access this information simultaneously and utilize this information. The various categories of tools considered are packet sniffers, port mappers, port scanners, encryption tools, and vulnerability scanners etc for the development of this application. This application provides a front end through which the user can invoke any tool from a central repository for the purpose of packet sniffing, port scanning, network analysis etc. Apart from the tool, its description and the help files associated with it would also be stored in the central repository. This facility will enable the user to view the documentation pertaining to the tool without having to download and install the tool. The application would update the central repository with the latest versions of the tools. The application would inform the user about the availability of a newer version of the tool currently being used and give the choice of installing the newer version to the user. Thus ToolTracker provides any network administrator that much needed abstraction and ease-ofuse with respect to the tools that he can use to efficiently monitor a network.
Keywords: Network monitoring, single platform, client/server application, version management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1300235 An Empirical Assessment of Sustainability of an Urban Water Supply Service Delivery
Authors: Olayinka Gafar Okeola, Akinola Muyiwa Moore
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Urban population is rapidly increasing in Ilorin, (the capital of Kwara State of Nigeria) along with related increased water demand. The inadequacies of water supply services have forced the populace to depend on dug wells, boreholes, water tankers, street vendors etc. for their water needs. People spend hours daily carrying jerry can all around to collect and queue for water at the public water tap with high opportunity cost both in time and economic wastage. This situation motivated this study to assess the sustainability of an urban water supply services to unravel the factors undermining the effective delivery of services. Contingent Valuation Method was used to place value on water supply services using the Double Bounded Dichotomous Choice format for willingness to pay elicitation. A database was created with Microsoft Excel and Stata 12 Software to model and evaluate the variables that affect household willingness to pay. The results of the study reveal that about 92% of the total households surveyed were connected to the Government water supply out of which 87% reported that they were not satisfied with the existing services. The results furthered revealed that respondents are willing to pay ₦2500 monthly to enjoy sustainable water supply service delivery.
Keywords: Willingness-to-pay, contingent valuation method, Nigeria, service, delivery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 433234 Triangular Geometric Feature for Offline Signature Verification
Authors: Zuraidasahana Zulkarnain, Mohd Shafry Mohd Rahim, Nor Anita Fairos Ismail, Mohd Azhar M. Arsad
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Handwritten signature is accepted widely as a biometric characteristic for personal authentication. The use of appropriate features plays an important role in determining accuracy of signature verification; therefore, this paper presents a feature based on the geometrical concept. To achieve the aim, triangle attributes are exploited to design a new feature since the triangle possesses orientation, angle and transformation that would improve accuracy. The proposed feature uses triangulation geometric set comprising of sides, angles and perimeter of a triangle which is derived from the center of gravity of a signature image. For classification purpose, Euclidean classifier along with Voting-based classifier is used to verify the tendency of forgery signature. This classification process is experimented using triangular geometric feature and selected global features. Based on an experiment that was validated using Grupo de Senales 960 (GPDS-960) signature database, the proposed triangular geometric feature achieves a lower Average Error Rates (AER) value with a percentage of 34% as compared to 43% of the selected global feature. As a conclusion, the proposed triangular geometric feature proves to be a more reliable feature for accurate signature verification.
Keywords: biometrics, euclidean classifier, feature extraction, offline signature verification, VOTING-based classifier
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1978233 Multivariate Output-Associative RVM for Multi-Dimensional Affect Predictions
Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins
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The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.Keywords: Dimensional affect prediction, Output-associative RVM, Multivariate regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1668232 Random Subspace Neural Classifier for Meteor Recognition in the Night Sky
Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio
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This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.
Keywords: Contour orientation histogram, meteors, night sky, RSC neural classifier, stars.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 407231 The Application of Queuing Theory in Multi-Stage Production Lines
Authors: Hani Shafeek, Muhammed Marsudi
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The purpose of this work is examining the multiproduct multi-stage in a battery production line. To improve the performances of an assembly production line by determine the efficiency of each workstation. Data collected from every workstation. The data are throughput rate, number of operator, and number of parts that arrive and leaves during part processing. Data for the number of parts that arrives and leaves are collected at least at the amount of ten samples to make the data is possible to be analyzed by Chi-Squared Goodness Test and queuing theory. Measures of this model served as the comparison with the standard data available in the company. Validation of the task time value resulted by comparing it with the task time value based on the company database. Some performance factors for the multi-product multi-stage in a battery production line in this work are shown. The efficiency in each workstation was also shown. Total production time to produce each part can be determined by adding the total task time in each workstation. To reduce the queuing time and increase the efficiency based on the analysis any probably improvement should be done. One probably action is by increasing the number of operators how manually operate this workstation.
Keywords: Production line, manufacturing, performance measurement, queuing theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3147230 Interval Type-2 Fuzzy Vibration Control of an ERF Embedded Smart Structure
Authors: Chih-Jer Lin, Chun-Ying Lee, Ying Liu, Chiang-Ho Cheng
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The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.
Keywords: Electro-Rheological Fluid, Semi-active vibration control, shock absorber, type 2 fuzzy control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2123229 Robot Map Building from Sonar and Laser Information using DSmT with Discounting Theory
Authors: Xinde Li, Xinhan Huang, Min Wang
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In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together.
Keywords: Map building, DSmT, DST, uncertainty, information fusion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1940228 Cell Phone: A Vital Clue
Authors: Meenakshi Mahajan, Arun Sharma, Navendu Sharma
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Increasing use of cell phone as a medium of human interaction is playing a vital role in solving riddles of crime as well. A young girl went missing from her home late in the evening in the month of August, 2008 when her enraged relatives and villagers physically assaulted and chased her fiancée who often frequented her home. Two years later, her mother lodged a complaint against the relatives and the villagers alleging that after abduction her daughter was either sold or killed as she had failed to trace her. On investigation, a rusted cell phone with partial visible IMEI number, clothes, bangles, human skeleton etc. recovered from abandoned well in the month of May, 2011 were examined in the lab. All hopes pinned on identity of cell phone, for only linking evidence to fix the scene of occurrence supported by call detail record (CDR) and to dispel doubts about mode of sudden disappearance or death as DNA technology did not help in establishing identity of the deceased. The conventional scientific methods were used without success and international mobile equipment identification number of the cell phone could be generated by using statistical analysis followed by online verification.
Keywords: Call detail record, Luhn algorithm, stereomicroscope.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1981227 Comparison of Real-Time PCR and FTIR with Chemometrics Technique in Analysing Halal Supplement Capsules
Authors: Mohd Sukri Hassan, Ahlam Inayatullah Badrul Munir, M. Husaini A. Rahman
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Halal authentication and verification in supplement capsules are highly required as the gelatine available in the market can be from halal or non-halal sources. It is an obligation for Muslim to consume and use the halal consumer goods. At present, real-time polymerase chain reaction (RT-PCR) is the most common technique being used for the detection of porcine and bovine DNA in gelatine due to high sensitivity of the technique and higher stability of DNA compared to protein. In this study, twenty samples of supplements capsules from different products with different Halal logos were analyzed for porcine and bovine DNA using RT-PCR. Standard bovine and porcine gelatine from eurofins at a range of concentration from 10-1 to 10-5 ng/µl were used to determine the linearity range, limit of detection and specificity on RT-PCR (SYBR Green method). RT-PCR detected porcine (two samples), bovine (four samples) and mixture of porcine and bovine (six samples). The samples were also tested using FT-IR technique where normalized peak of IR spectra were pre-processed using Savitsky Golay method before Principal Components Analysis (PCA) was performed on the database. Scores plot of PCA shows three clusters of samples; bovine, porcine and mixture (bovine and porcine). The RT-PCR and FT-IR with chemometrics technique were found to give same results for porcine gelatine samples which can be used for Halal authentication.Keywords: Halal, real-time PCR, gelatin, FTIR and chemometrics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 920226 CFD Prediction of the Round Elbow Fitting Loss Coefficient
Authors: Ana Paula P. dos Santos, Claudia R. Andrade, Edson L. Zaparoli
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Pressure loss in ductworks is an important factor to be considered in design of engineering systems such as power-plants, refineries, HVAC systems to reduce energy costs. Ductwork can be composed by straight ducts and different types of fittings (elbows, transitions, converging and diverging tees and wyes). Duct fittings are significant sources of pressure loss in fluid distribution systems. Fitting losses can be even more significant than equipment components such as coils, filters, and dampers. At the present work, a conventional 90o round elbow under turbulent incompressible airflow is studied. Mass, momentum, and k-e turbulence model equations are solved employing the finite volume method. The SIMPLE algorithm is used for the pressure-velocity coupling. In order to validate the numerical tool, the elbow pressure loss coefficient is determined using the same conditions to compare with ASHRAE database. Furthermore, the effect of Reynolds number variation on the elbow pressure loss coefficient is investigated. These results can be useful to perform better preliminary design of air distribution ductworks in air conditioning systems.
Keywords: Duct fitting, Pressure loss, Elbow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4851225 Business Intelligence for N=1 Analytics using Hybrid Intelligent System Approach
Authors: Rajendra M Sonar
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The future of business intelligence (BI) is to integrate intelligence into operational systems that works in real-time analyzing small chunks of data based on requirements on continuous basis. This is moving away from traditional approach of doing analysis on ad-hoc basis or sporadically in passive and off-line mode analyzing huge amount data. Various AI techniques such as expert systems, case-based reasoning, neural-networks play important role in building business intelligent systems. Since BI involves various tasks and models various types of problems, hybrid intelligent techniques can be better choice. Intelligent systems accessible through web services make it easier to integrate them into existing operational systems to add intelligence in every business processes. These can be built to be invoked in modular and distributed way to work in real time. Functionality of such systems can be extended to get external inputs compatible with formats like RSS. In this paper, we describe a framework that use effective combinations of these techniques, accessible through web services and work in real-time. We have successfully developed various prototype systems and done few commercial deployments in the area of personalization and recommendation on mobile and websites.Keywords: Business Intelligence, Customer Relationship Management, Hybrid Intelligent Systems, Personalization and Recommendation (P&R), Recommender Systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2077224 Organization Model of Semantic Document Repository and Search Techniques for Studying Information Technology
Authors: Nhon Do, Thuong Huynh, An Pham
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Nowadays, organizing a repository of documents and resources for learning on a special field as Information Technology (IT), together with search techniques based on domain knowledge or document-s content is an urgent need in practice of teaching, learning and researching. There have been several works related to methods of organization and search by content. However, the results are still limited and insufficient to meet user-s demand for semantic document retrieval. This paper presents a solution for the organization of a repository that supports semantic representation and processing in search. The proposed solution is a model which integrates components such as an ontology describing domain knowledge, a database of document repository, semantic representation for documents and a file system; with problems, semantic processing techniques and advanced search techniques based on measuring semantic similarity. The solution is applied to build a IT learning materials management system of a university with semantic search function serving students, teachers, and manager as well. The application has been implemented, tested at the University of Information Technology, Ho Chi Minh City, Vietnam and has achieved good results.Keywords: document retrieval system, knowledgerepresentation, document representation, semantic search, ontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1710223 Digital Privacy Legislation Awareness
Authors: Henry Foulds, Magda Huisman, Gunther R. Drevin
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Privacy is regarded as a fundamental human right and it is clear that the study of digital privacy is an important field. Digital privacy is influenced by new and constantly evolving technologies and this continuous change makes it hard to create legislation to protect people’s privacy from being exploited by misuse of these technologies.
This study aims to benefit digital privacy legislation efforts by evaluating the awareness and perceived importance of digital privacy legislation among computer science students. The chosen fixed variables for the population are study year and gamer classification.
The use of location based services in mobile applications and games are a concern for digital privacy. For this reason the study focused on computer science students as they have a high likelihood to use and develop this type of software. Surveys were used to evaluate awareness and perceived importance of digital privacy legislation.
The results of the study show that privacy legislation and awareness of privacy legislation are important to people. The perception of the importance of privacy legislation increases with academic experience. Awareness of privacy legislation increases from non-gamers to pro gamers.
Keywords: Digital privacy, Legislation awareness, Gaming.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1995222 VoIP and Database Traffic Co-existence over IEEE 802.11b WLAN with Redundancy
Authors: Rizik Al-Sayyed, Colin Pattinson, Tony Dacre
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This paper presents the findings of two experiments that were performed on the Redundancy in Wireless Connection Model (RiWC) using the 802.11b standard. The experiments were simulated using OPNET 11.5 Modeler software. The first was aimed at finding the maximum number of simultaneous Voice over Internet Protocol (VoIP) users the model would support under the G.711 and G.729 codec standards when the packetization interval was 10 milliseconds (ms). The second experiment examined the model?s VoIP user capacity using the G.729 codec standard along with background traffic using the same packetization interval as in the first experiment. To determine the capacity of the model under various experiments, we checked three metrics: jitter, delay and data loss. When background traffic was added, we checked the response time in addition to the previous three metrics. The findings of the first experiment indicated that the maximum number of simultaneous VoIP users the model was able to support was 5, which is consistent with recent research findings. When using the G.729 codec, the model was able to support up to 16 VoIP users; similar experiments in current literature have indicated a maximum of 7 users. The finding of the second experiment demonstrated that the maximum number of VoIP users the model was able to support was 12, with the existence of background traffic.
Keywords: WLAN, IEEE 802.11b, Codec, VoIP, OPNET, Background traffic, and QoS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1694221 A Hybrid Feature Selection and Deep Learning Algorithm for Cancer Disease Classification
Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh
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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.
Keywords: Cancer classification, feature selection, deep learning, genetic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1272220 Dominating Set Algorithm and Trust Evaluation Scheme for Secured Cluster Formation and Data Transferring
Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji
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This paper describes the proficient way of choosing the cluster head based on dominating set algorithm in a wireless sensor network (WSN). The algorithm overcomes the energy deterioration problems by this selection process of cluster heads. Clustering algorithms such as LEACH, EEHC and HEED enhance scalability in WSNs. Dominating set algorithm keeps the first node alive longer than the other protocols previously used. As the dominating set of cluster heads are directly connected to each node, the energy of the network is saved by eliminating the intermediate nodes in WSN. Security and trust is pivotal in network messaging. Cluster head is secured with a unique key. The member can only connect with the cluster head if and only if they are secured too. The secured trust model provides security for data transmission in the dominated set network with the group key. The concept can be extended to add a mobile sink for each or for no of clusters to transmit data or messages between cluster heads and to base station. Data security id preferably high and data loss can be prevented. The simulation demonstrates the concept of choosing cluster heads by dominating set algorithm and trust evaluation using DSTE. The research done is rationalized.
Keywords: Wireless Sensor Networks, LEECH, EEHC, HEED, DSTE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1406219 Automatic Music Score Recognition System Using Digital Image Processing
Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng
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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.
Keywords: Connected component labeling, image processing, morphological processing, optical musical recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1931218 Using HMM-based Classifier Adapted to Background Noises with Improved Sounds Features for Audio Surveillance Application
Authors: Asma Rabaoui, Zied Lachiri, Noureddine Ellouze
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Discrimination between different classes of environmental sounds is the goal of our work. The use of a sound recognition system can offer concrete potentialities for surveillance and security applications. The first paper contribution to this research field is represented by a thorough investigation of the applicability of state-of-the-art audio features in the domain of environmental sound recognition. Additionally, a set of novel features obtained by combining the basic parameters is introduced. The quality of the features investigated is evaluated by a HMM-based classifier to which a great interest was done. In fact, we propose to use a Multi-Style training system based on HMMs: one recognizer is trained on a database including different levels of background noises and is used as a universal recognizer for every environment. In order to enhance the system robustness by reducing the environmental variability, we explore different adaptation algorithms including Maximum Likelihood Linear Regression (MLLR), Maximum A Posteriori (MAP) and the MAP/MLLR algorithm that combines MAP and MLLR. Experimental evaluation shows that a rather good recognition rate can be reached, even under important noise degradation conditions when the system is fed by the convenient set of features.Keywords: Sounds recognition, HMM classifier, Multi-style training, Environmental Adaptation, Feature combinations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1645217 Spatio-Temporal Data Mining with Association Rules for Lake Van
Authors: T. Aydin, M. F. Alaeddinoglu
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People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatiotemporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newlyformed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.Keywords: Apriori algorithm, association rules, data mining, spatio-temporal data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1405216 Speaker Independent Quranic Recognizer Basedon Maximum Likelihood Linear Regression
Authors: Ehab Mourtaga, Ahmad Sharieh, Mousa Abdallah
Abstract:
An automatic speech recognition system for the formal Arabic language is needed. The Quran is the most formal spoken book in Arabic, it is spoken all over the world. In this research, an automatic speech recognizer for Quranic based speakerindependent was developed and tested. The system was developed based on the tri-phone Hidden Markov Model and Maximum Likelihood Linear Regression (MLLR). The MLLR computes a set of transformations which reduces the mismatch between an initial model set and the adaptation data. It uses the regression class tree, as well as, estimates a set of linear transformations for the mean and variance parameters of a Gaussian mixture HMM system. The 30th Chapter of the Quran, with five of the most famous readers of the Quran, was used for the training and testing of the data. The chapter includes about 2000 distinct words. The advantages of using the Quranic verses as the database in this developed recognizer are the uniqueness of the words and the high level of orderliness between verses. The level of accuracy from the tested data ranged 68 to 85%.Keywords: Hidden Markov Model (HMM), MaximumLikelihood Linear Regression (MLLR), Quran, Regression ClassTree, Speech Recognition, Speaker-independent.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1915215 Interference Management in Long Term Evolution-Advanced System
Authors: Selma Sbit, Mohamed Bechir Dadi, Belgacem Chibani Rhaimi
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Incorporating Home eNodeB (HeNB) in cellular networks, e.g. Long Term Evolution Advanced (LTE-A), is beneficial for extending coverage and enhancing capacity at low price especially within the non-line-of sight (NLOS) environments such as homes. HeNB or femtocell is a small low powered base station which provides radio coverage to the mobile users in an indoor environment. This deployment results in a heterogeneous network where the available spectrum becomes shared between two layers. Therefore, a problem of Inter Cell Interference (ICI) appears. This issue is the main challenge in LTE-A. To deal with this challenge, various techniques based on frequency, time and power control are proposed. This paper deals with the impact of carrier aggregation and higher order MIMO (Multiple Input Multiple Output) schemes on the LTE-Advanced performance. Simulation results show the advantages of these schemes on the system capacity (4.109 b/s/Hz when bandwidth B=100 MHz and when applying MIMO 8x8 for SINR=30 dB), maximum theoretical peak data rate (more than 4 Gbps for B=100 MHz and when MIMO 8x8 is used) and spectral efficiency (15 b/s/Hz and 30b/s/Hz when MIMO 4x4 and MIMO 8x8 are applying respectively for SINR=30 dB).
Keywords: LTE-Advanced, carrier aggregation, MIMO, capacity, peak data rate, spectral efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 905