Search results for: Hospital Information System

Authors: Imran Usman, Asifullah Khan, Rafiullah Chamlawi, Abdul Majid

Abstract:

Information hiding for authenticating and verifying the content integrity of the multimedia has been exploited extensively in the last decade. We propose the idea of using genetic algorithm and non-deterministic dependence by involving the un-watermarkable coefficients for digital image authentication. Genetic algorithm is used to intelligently select coefficients for watermarking in a DCT based image authentication scheme, which implicitly watermark all the un-watermarkable coefficients also, in order to thwart different attacks. Experimental results show that such intelligent selection results in improvement of imperceptibility of the watermarked image, and implicit watermarking of all the coefficients improves security against attacks such as cover-up, vector quantization and transplantation.

Keywords: Digital watermarking, fragile watermarking, geneticalgorithm, Image authentication.

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Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices. 

Keywords: Industry 4.0., Mass Customization, Production networks, Virtual Process-Chain.

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Authors: Pavel Janak

Abstract:

This paper studies, maps and explains the interactions between downloaders and uploaders pertaining to the Internet film piracy. This study also covers several motivational factors that influence users to upload or download movies, and thus to engage in film piracy over the Internet. The essay also proposes a model that describes user behavior including their relationships and influences. Moreover, proposed theoretical interactions and motivational factors are applied to the real world scenario, using examples of a data storage webpage server Ulozto.net and webpage Piratebay.org gathering information about downloadable BitTorrents. Moreover, the theory is further supported by description of behavior of real Internet uploaders.

Keywords: Download, film piracy, internet, motivational factors for uploading.

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Authors: D. S. A. Nanayakkara, K. J. P. G. Perera

Abstract:

E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. TheAnalyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling TheAnalyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: Data clustering, data standardization, dimensionality reduction, human-computer interaction, user profiling.

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Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

Abstract:

Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: Artificial neural network, back-propagation, tide data, training algorithm.

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Authors: Sorin Soviany, Cristina Soviany, Mariana Jurian

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The paper presents a multimodal approach for biometric authentication, based on multiple classifiers. The proposed solution uses a post-classification biometric fusion method in which the biometric data classifiers outputs are combined in order to improve the overall biometric system performance by decreasing the classification error rates. The paper shows also the biometric recognition task improvement by means of a carefully feature selection, as much as not all of the feature vectors components support the accuracy improvement.

Keywords: biometric fusion, multiple classifiers

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Authors: M. Z. Othman

Abstract:

The aim of this study was to investigate the effectiveness of anaerobic digestion for the treatment of wool scouring wastes. The experiments design comprised three ratios of waste (W) to seed(S) (W:S) of 25:75, 50:50 and 75:25, corresponding to 1.9. 1.7 and 1.5g tCOD/g TS, respectively, with or without chemicals addition. NH4Cl was added to the reactors as a source for nitrogen to achieve C:N:P of 420:14:3. A cationic flocculent was added at 0.5 and 0.75% to enhance flocculation of sludge. The results showed that the reactors that received W:S at a ratio of 25:75 produced the largest volume of biogas. The final soluble COD (sCOD) was below the limits for discharge to the sewer system.

Keywords: Anaerobic digestion, wool processing waste, organicloading, biogas.

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Authors: Tawiwat V., Tosapolporn P., Kedit J.

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This research proposes the state of art on how to control or find the trajectory paths of the RRP robot when the prismatic joint is malfunction. According to this situation, the minimum energy of the dynamic optimization is applied. The RRP robot or similar systems have been used in many areas such as fire fighter truck, laboratory equipment and military truck for example a rocket launcher. In order to keep on task that assigned, the trajectory paths must be computed. Here, the open loop control is applied and the result of an example show the reasonable solution which can be applied to the controllable system.

Keywords: RRP robot, Optimal Control, Minimum Energy and Under Actuator.

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Authors: M. H. Chung, B. Y. Lee, Y. Kim, E. K. Rhee

Abstract:

With an increase in the interest in the energy conservation for buildings, and the emergence of many methods and easily-understandable approaches to it, energy conservation has now become the public’s main interest, as compared to in the past when it was only focused upon by experts. This study aims to help the occupants of a building to understand the energy efficiency and consumption of the building by providing them information on the building’s energy efficiency through a mobile application. The energy performance assessment models are proposed on the basis of the actual energy usage and building characteristics such as the architectural scheme and the building equipment. The university buildings in Korea are used as a case to demonstrate the mobile application.

Keywords: Energy consumption, energy performance assessment, mobile application, university buildings.

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Authors: Lianglin Xiong, Xiuyong Ding, Shouming Zhong

Abstract:

In this paper, the problem of asymptotical stability of neutral systems with nonlinear perturbations is investigated. Based on a class of novel augment Lyapunov functionals which contain freeweighting matrices, some new delay-dependent asymptotical stability criteria are formulated in terms of linear matrix inequalities (LMIs) by using new inequality analysis technique. Numerical examples are given to demonstrate the derived condition are much less conservative than those given in the literature.

Keywords: Asymptotical stability, neutral system, nonlinear perturbation, delay-dependent, linear matrix inequality (LMI).

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Authors: Suselo Thomas, Suyoto, Dwiandiyanta B. Yudi

Abstract:

This paper explain about analysis and design a business directory for micro-scale businesses, small and medium enterprises (SMEs). Business Directory, if implemented will facilitate and optimize the access of SMEs to ease suppliers access to marketing. Business Directory will be equipped with the power of geocoding, so each location can be easily viewed SMEs on the map. The map will be constructed by using the functionality of a webbased Google Maps API. The information presented in the form of multimedia that can be more interesting and interactive. The method used to achieve the goal are: observation; interviews; modeling and classifying business directory for SMEs.

Keywords: Business directories, SMEs, Google maps API, multimedia, geocoding ommas.

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Authors: Jalil Rashidinia, Reza Jalilian

Abstract:

In this paper we use quintic non-polynomial spline functions to develop numerical methods for approximation to the solution of a system of fourth-order boundaryvalue problems associated with obstacle, unilateral and contact problems. The convergence analysis of the methods has been discussed and shown that the given approximations are better than collocation and finite difference methods. Numerical examples are presented to illustrate the applications of these methods, and to compare the computed results with other known methods.

Keywords: Quintic non-polynomial spline, Boundary formula, Convergence, Obstacle problems.

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Authors: T. Anbu, K. Aravind Kumar

Abstract:

The road environment information is needed accurately for applications such as road maintenance and virtual 3D city modeling. Mobile laser scanning (MLS) produces dense point clouds from huge areas efficiently from which the road and its environment can be modeled in detail. Objects such as buildings, cars and trees are an important part of road environments. Different methods have been developed for detection of above such objects, but still there is a lack of accuracy due to the problems of illumination, environmental changes, and multiple objects with same features. In this work the comparison between different classifiers such as Multiclass SVM, kNN and Multiclass LDA for the road environment detection is analyzed. Finally the classification accuracy for kNN with LBP feature improved the classification accuracy as 93.3% than the other classifiers.

Keywords: Classifiers, feature extraction, mobile-based laser scanning, object location estimation.

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Authors: Arti Vaish, Harish Parthasarathy

Abstract:

This paper deals with the formulation of Maxwell-s equations in a cavity resonator in the presence of the gravitational field produced by a blackhole. The metric of space-time due to the blackhole is the Schwarzchild metric. Conventionally, this is expressed in spherical polar coordinates. In order to adapt this metric to our problem, we have considered this metric in a small region close to the blackhole and expressed this metric in a cartesian system locally.

Keywords: Method of moments, General theory of relativity, Electromagnetism, Metric tensor, schwarzchild metric, Wave Equation.

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Authors: Heung Seok Chae, Jaegeol Park

Abstract:

Recently, there have been an increasing interest in RFID system and RFID systems have been applied to various applications. Load balancing is a fundamental technique for providing scalability of systems by moving workload from overloaded nodes to under-loaded nodes. This paper presents an approach to adaptive load balancing for RFID middlewares. Workloads of RFID middlewares can have a considerable variation according to the location of the connected RFID readers and can abruptly change at a particular instance. The proposed approach considers those characteristics of RFID middle- wares to provide an efficient load balancing.

Keywords: RFID middleware, Adaptive load balancing.

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Authors: Adriano Bessa Albuquerque, Francisco Jose Barreto Nunes

Abstract:

Software vulnerabilities are increasing and not only impact services and processes availability as well as information confidentiality, integrity and privacy, but also cause changes that interfere in the development process. Security test could be a solution to reduce vulnerabilities. However, the variety of test techniques with the lack of real case studies of applying tests focusing on software development life cycle compromise its effective use. This paper offers an overview of how a Systematic Mapping Study (MS) about security verification, validation and test (VVT) was performed, besides presenting general results about this study.

Keywords: Software test, software security verification validation and test, security test institutionalization, systematic mapping study.

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Authors: L. Chen, X. P. Ouyang, Z. B. Zhang, J. F. Zhang, J. L. Liu

Abstract:

Ultrafast doped zinc oxide crystal promised us a good opportunity to build new instruments for ICF fusion neutron measurement. Two pulsed neutron detectors based on ZnO crystal wafer have been conceptually designed, the superfast ZnO timing detector and the scintillation recoil proton neutron detection system. The structure of these detectors was presented, and some characters were studied as well. The new detectors could be much faster than existing systems, and would be more competent for ICF neutron diagnostics.

Keywords: ICF fusion neutron detection, proton recoil telescope, superfast timing, ZnO crystal

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Authors: A. El Hamdouni, J. Zbitou, A. Tajmouati, L. El Abdellaoui, A. Errkik, A. Tribak, M. Latrach

Abstract:

This paper presents a novel fractal antenna structure proposed for UWB (Ultra – Wideband) applications. The frequency band 3.1-10.6GHz released by FCC (Federal Communication Commission) as the commercial operation of UWB has been chosen as frequency range for this antenna based on coplanar waveguide (CPW) feed and circular shapes fulfilled according to fractal geometry. The proposed antenna is validated and designed by using an FR4 substrate with overall area of 34x43 mm2. The simulated results performed by CST-Microwave Studio and compared by ADS (Advanced Design System) show good matching input impedance with return loss less than -10dB between 2.9 GHz and 11 GHz.

Keywords: Fractal antenna, Fractal Geometry, CPW Feed, UWB, FCC.

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Authors: Mohammad Rajabalinejad

Abstract:

Safety is often seen as a requirement or a performance indicator through the design process, and this does not always result in optimally safe products or systems. This paper suggests integrating the best safety practices with the design process to enrich the exploration experience for designers and add extra values for customers. For this purpose, the commonly practiced safety standards and design methods have been reviewed and their common blocks have been merged forming Safety Cube. Safety Cube combines common blocks for design, hazard identification, risk assessment and risk reduction through an integral approach. An example application presents the use of Safety Cube for design of machinery.

Keywords: Safety, safety cube, design, product, system, machinery.

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Authors: Siyamak Ziyaei, Siti Khalijah Mazlan, Petros Lappas

Abstract:

Compressed natural gas (CNG) is primarily composed of methane (CH4), and has a lower carbon to hydrogen ratio than other hydrocarbon fuels such as gasoline (C8H18) and diesel (C12H23). Consequently, it has the potential to reduce CO2 emissions compared to conventional fuels. Although Natural Gas (NG) has environmental advantages compared to other hydrocarbon fuels, its main component, CH4, burns at a slower rate compared to the conventional fuels. A higher pressure and leaner cylinder environment will unravel the slow burn characteristic of CH4. Lean combustion and high compression ratios are well-known methods for increasing the efficiency of internal combustion engines. In order to achieve successful a CNG lean combustion in Spark Ignition (SI) engines, a strong ignition system is essential to avoid engine misfires, especially in ultra-lean conditions. Turbulent Jet Ignition (TJI) is an ignition system that employs a pre-combustion chamber to ignite the lean fuel mixture in the main combustion chamber using a fraction of the total fuel per cycle. TJI enables ultra-lean combustion by providing distributed ignition sites through orifices. The fast burn rate provided by TJI enables the ordinary SI engine to be comparable to other combustion systems such as Homogeneous Charge Compression Ignition (HCCI) or Controlled Auto-Ignition (CAI) in terms of thermal efficiency, through the increased levels of dilution without the need of sophisticated control systems. Due to the physical geometry of TJI, which contains small orifices that connect the pre-chamber to the main chamber, providing the right mixture of fuel and air has been identified as a key challenge due to the insufficient amount of air that is pushed into the pre-chamber during each compression stroke. There is also the problem of scavenging which contributed to the factors that reduces the TJI performance. Combustion residual gases such as CO2, CO and NOx from the previous combustion cycle dilute the pre-chamber fuel-air mixture preventing rapid combustion in the pre-chamber. An air-controlled active TJI is presented in this paper in order to address these issues. By supplying air into the pre-chamber at a sufficient pressure, residual gases are exhausted, and the air-fuel ratio is controlled within the pre-chamber, thereby improving the quality of the combustion. An investigation of the 3D combustion characteristics of a CNG-fueled SI engine using a direct injection fuelling strategy employing an air channel in the prechamber is presented in this paper. Experiments and simulations were performed at the Worldwide Mapping Point (WWMP) at 1500 revolutions per minute (rpm), 3.3 bar Indicated Mean Effective Pressure (IMEP), using only conventional spark plugs as a baseline. With a validated baseline engine simulation, the settings were set for all simulation scenarios at λ=1. Following that, the pre-chambers with and without an auxiliary fuel supply were simulated. In the study of (DI-CNG) SI engine, active TJI was observed to perform better than passive TJI and conventional  spark plug ignition. In conclusion, the active pre-chamber with an air channel demonstrated an improved thermal efficiency (ηth) over other counterparts and conventional spark ignition systems.

Keywords: Turbulent Jet Ignition, Active Air Control Turbulent Jet Ignition, Pre-chamber ignition system, Active and Passive Pre-chamber, thermal efficiency, methane combustion, internal combustion engine combustion emissions.

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Authors: Marko Niinimaki

Abstract:

Cryptocurrencies are getting increasingly popular, but very few of them can be conveniently used in daily mobile phone purchases. To solve this problem, we demonstrate how to build a functional prototype of a mobile cryptocurrency-based e-commerce application the communicates with Near-Field Communication (NFC) tags. Using the system, users are able to purchase physical items with an NFC tag that contains an e-commerce URL. The payment is done simply by touching the tag with a mobile device and accepting the payment. Our method is constructive: we describe the design and technologies used in the implementation and evaluate the security and performance of the solution. Our main finding is that the analysis and measurements show that our solution is feasible for e-commerce.

Keywords: Cryptocurrency, e-commerce, NFC, mobile devices.

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Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

Abstract:

The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: Maintenance, complexity, simulation, multi-agent systems, AnyLogic platform.

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Authors: Adnene Arbi, Chaouki Aouiti, Abderrahmane Touati

Abstract:

In this paper, we consider the uniform asymptotic stability, global asymptotic stability and global exponential stability of the equilibrium point of discrete Hopfield neural networks with delays. Some new stability criteria for system are derived by using the Lyapunov functional method and the linear matrix inequality approach, for estimating the upper bound of Lyapunov functional derivative.

Keywords: Hopfield neural networks, uniform asymptotic stability, global asymptotic stability, exponential stability.

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Authors: S. H. Lee, M. J. Park, O. M. Kwon

Abstract:

In this paper, reliable consensus of multi-agent systems with sampled-data is investigated. By using a suitable Lyapunov-Krasovskii functional and some techniques such as Wirtinger Inequality, Schur Complement and Kronecker Product, the results of such system are obtained by solving a set of Linear Matrix Inequalities (LMIs). One numerical example is included to show the effectiveness of the proposed criteria.

Keywords: Multi-agent, Linear Matrix Inequalities (LMIs), Kronecker Product, Sampled-Data, Lyapunov method.

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Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

Abstract:

This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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Authors: F. Abdul Majeed, H. Karki, Y. Abdel Magid, M. Karkoub

Abstract:

This paper analyses the non linear properties exhibited by a drill string system under various un balanced mass conditions. The drill string is affected by continuous friction in the form of drill bit and well bore hole interactions. This paper proves the origin of limit cycling and increase of non linearity with increase in speed of the drilling in the presence of friction. The spectrum of the frequency response is also studied to detect the presence of vibration abnormalities arising during the drilling process.

Keywords: Drill strings, Nonlinear, Spectrum analysis, Unbalanced mass

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Authors: Keonwoo Kim, Dowon Hong

Abstract:

Electronic voting (E-voting) using an internet has been recently performed in some nations and regions. There is no spatial restriction which a voter directly has to visit the polling place, but an e-voting using an internet has to go together the computer in which the internet connection is possible. Also, this voting requires an access code for the e-voting through the beforehand report of a voter. To minimize these disadvantages, we propose a method in which a voter, who has the wireless certificate issued in advance, uses its own cellular phone for an e-voting without the special registration for a vote. Our proposal allows a voter to cast his vote in a simple and convenient way without the limit of time and location, thereby increasing the voting rate, and also ensuring confidentiality and anonymity.

Keywords: Voting, mobile terminal, confidentiality, anonymity.

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Authors: Xianqing Liu, Shouming Zhong, Lijiang Xiang

Abstract:

In this paper, a stochastic predator-prey system with Bedding-DeAngelis functional response is studied. By constructing a suitable Lyapunov founction, sufficient conditions for species to be stochastically permanent is established. Meanwhile, we show that the species will become extinct with probability one if the noise is sufficiently large.

Keywords: Stochastically permanent, extinct, white noise, Bedding-DeAngelis functional response.

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Authors: A. Ismail, M. S. Joy, J. E. Sinclair, M. I. Hamzah

Abstract:

This paper focuses on a novel method for semantic searching and retrieval of information about learning materials. Metametadata encapsulate metadata instances by using the properties and attributes provided by ontologies rather than describing learning objects. A novel metametadata taxonomy has been developed which provides the basis for a semantic search engine to extract, match and map queries to retrieve relevant results. The use of ontological views is a foundation for viewing the pedagogical content of metadata extracted from learning objects by using the pedagogical attributes from the metametadata taxonomy. Using the ontological approach and metametadata (based on the metametadata taxonomy) we present a novel semantic searching mechanism.These three strands – the taxonomy, the ontological views, and the search algorithm – are incorporated into a novel architecture (OMESCOD) which has been implemented.

Keywords: Metadata, metametadata, semantic, ontologies.

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Authors: Harsh Vikram Singh, S. P. Singh, Anand Mohan

Abstract:

This paper discusses a new heavy tailed distribution based data hiding into discrete cosine transform (DCT) coefficients of image, which provides statistical security as well as robustness against steganalysis attacks. Unlike other data hiding algorithms, the proposed technique does not introduce much effect in the stegoimage-s DCT coefficient probability plots, thus making the presence of hidden data statistically undetectable. In addition the proposed method does not compromise on hiding capacity. When compared to the generic block DCT based data-hiding scheme, our method found more robust against a variety of image manipulating attacks such as filtering, blurring, JPEG compression etc.

Keywords: Information Security, Robust Steganography, Steganalysis, Pareto Probability Distribution function.

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