Search results for: User Modelling

Authors: Hongyuan Li, Guang Liu, Yuewei Dai, Zhiquan Wang

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Digital watermarking is the process of embedding information into a digital signal which can be used in DRM (digital rights managements) system. The visible watermark (often called logo) can indicate the owner of the copyright which can often be seen in the TV program and protects the copyright in an active way. However, most of the schemes do not consider the visible watermark removing process. To solve this problem, a visible watermarking scheme with embedding and removing process is proposed under the control of a secure template. The template generates different version of watermarks which can be seen visually the same for different users. Users with the right key can completely remove the watermark and recover the original image while the unauthorized user is prevented to remove the watermark. Experiment results show that our watermarking algorithm obtains a good visual quality and is hard to be removed by the illegally users. Additionally, the authorized users can completely remove the visible watermark and recover the original image with a good quality.

Keywords: digital watermarking, visible and removablewatermark, secure template, JPEG compression

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Authors: Phumelele P. Kubheka, Pius A. Owolawi, Gbolahan Aiyetoro

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Twitter is one of the most popular social media platforms where users share their opinions on different subjects. Twitter can be considered a great source for mining text due to the high volumes of data generated through the platform daily. Many industries such as telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model in this experiment. A higher topic coherence score indicates better performance of the model.

Keywords: Big data, latent Dirichlet allocation, latent semantic indexing, Telco, topic modeling, Twitter.

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Authors: Clemens Pizzinini, Philipp Rosner, David Ziegler, Markus Lienkamp

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Transportation is a constitutional part of most supply and value chains in modern economies. Smallholder farmers in rural Ethiopia face severe challenges along their supply and value chains. In particular, suitable, affordable, and available transport services are in high demand. To develop context-specific technical solutions, a problem-to-solution methodology based on the interaction with technology is developed. With this approach, we fill the gap between proven transportation assessment frameworks and general user-centered techniques. Central to our approach is an electric test vehicle that is implemented in rural supply and value chains for research, development, and testing. Based on our objective and the derived methodological requirements, a set of existing methods is  selected. Local partners are integrated in an organizational framework that executes major parts of this research endeavour in Arsi Zone, Oromia Region, Ethiopia.

Keywords: Agricultural value chain, participatory methods, agile methods, sub-Saharan Africa, Ethiopia, electric vehicle, transport service.

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Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Ismail Saritas, Sadiye Didem Boztepe Erkis, Selma Tasdemir

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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modelled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the developed system, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), and fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: Artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

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Authors: Zoran Jovanovic, Zoran Masonicic, S. Dragutinovic, Z. Sakota

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In this paper, results concerning flame propagation of various fuels in a particular combustion chamber with four tilted valves were elucidated. Flame propagation was represented by the evolution of spatial distribution of temperature in various cut-planes within combustion chamber while the flame front location was determined by dint of zones with maximum temperature gradient. The results presented are only a small part of broader on-going scrutinizing activity in the field of multidimensional modeling of reactive flows in combustion chambers with complicated geometries encompassing various models of turbulence, different fuels and combustion models. In the case of turbulence two different models were applied i.e. standard k-ε model of turbulence and k-ξ-f model of turbulence. In this paper flame propagation results were analyzed and presented for two different hydrocarbon fuels, such as CH4 and C8H18. In the case of combustion all differences ensuing from different turbulence models, obvious for non-reactive flows are annihilated entirely. Namely the interplay between fluid flow pattern and flame propagation is invariant as regards turbulence models and fuels applied. Namely the interplay between fluid flow pattern and flame propagation is entirely invariant as regards fuel variation indicating that the flame propagation through unburned mixture of CH4 and C8H18 fuels is not chemically controlled.

Keywords: Automotive flows, flame propagation, combustion modelling.

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Authors: Razieh Arian, Hadi Adibi-Asl

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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine.

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Authors: Abdul Hadi Abdul Razak, Mohd Hairy Manap

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The focus of this paper is to highlight the design and development of an educational game prototype as an evaluation instrument for the Malaysia driving license static test. This educational game brings gaming technology into the conventional objective static test to make it more effective, real and interesting. From the feeling of realistic, the future driver can learn something, memorized and use it in the real life. The current online objective static test only make the user memorized the answer without knowing and understand the true purpose of the question. Therefore, in real life, they will not behave as expected due to behavior and moral lacking. This prototype has been developed inform of multiple-choice questions integrated with 3D gaming environment to make it simulate the real environment and scenarios. Based on the testing conducted, the respondent agrees with the use of this game prototype it can increase understanding and promote obligation towards traffic rules.

Keywords: Educational game, evaluation instrument, game, game prototype.

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Authors: Tao Shun, Xiao Xiangning, HadjSaid, N.

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In a liberalized electricity market, it is not surprising that different customers require different power quality (PQ) levels at different price. Power quality related to several power disturbances is described by many parameters, so how to define a comprehensive hierarchy evaluation system of power quality (PQCHES) has become a concerned issue. In this paper, based on four electromagnetic compatibility (EMC) levels, the numerical range of each power disturbance is divided into five grades (Grade I –Grade V), and the “barrel principle" of power quality is used for the assessment of overall PQ performance with only one grade indicator. A case study based on actual monitored data of PQ shows that the site PQ grade indicates the electromagnetic environment level and also expresses the characteristics of loads served by the site. The shortest plank principle of PQ barrel is an incentive mechanism, which can combine with the rewards/penalty mechanism (RPM) of consumed energy “on quality demand", to stimulate utilities to improve the overall PQ level and also stimulate end-user more “smart" under the infrastructure of future SmartGrid..

Keywords: Power quality, electromagnetic compatibility, SmartGrid, comprehensive evaluation, barrel principle, electricitymarket

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Authors: Muhibul H. Bhuyan, Md. T. Hasan, Hasan Iskander

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Electrocardiographic (ECG) machine is an important equipment to diagnose heart problems. Besides, the ECG signals are used to detect many other features of human body and behavior. But it is not so cheap and simple in operation to be used in the countries like Bangladesh, where most of the people are very low income earners. Therefore, in this paper, we have tried to implement a simple and portable ECG machine. Since Arduino Uno microcontroller is very cheap, we have used it in our system to minimize the cost. Our designed system is powered by a 2-voltage level DC power supply. It provides wireless connectivity to have ECG data either in smartphone having android operating system or a PC/laptop having Windows operating system. To get the data, a graphic user interface has been designed. Android application has also been made using IDE for Android 2.3 and API 10. Since it requires no USB host API, almost 98% Android smartphones, available in the country, will be able to use it. We have calculated the heart rate from the measured ECG by our designed machine and by an ECG machine of a reputed diagnostic center in Dhaka city for the same people at the same time on same day. Then we calculated the percentage of errors between the readings of two machines and computed its average. From this computation, we have found out that the average percentage of error is within an acceptable limit.

Keywords: Low cost ECG machine, heart diseases, remote monitoring, Arduino microcontroller.

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Authors: Ming Wen, Nasim Nezamoddini

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Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.

Keywords: FEA, random vibration fatigue, process automation, AHP, TOPSIS, multiple-criteria decision-making, MCDM.

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Authors: Weifeng Wang, Xianwei Zeng, Jianping Ding

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Nanomaterials have attracted considerable attention during the last two decades, due to their unusual electrical, mechanical and other physical properties as compared with their bulky counterparts. The mechanical properties of nanostructured materials show strong size dependency, which has been explained within the framework of continuum mechanics by including the effects of surface stress. The size-dependent deformations of two-dimensional nanosized structures with surface effects are investigated in the paper by the finite element method. Truss element is used to evaluate the contribution of surface stress to the total potential energy and the Gurtin and Murdoch surface stress model is implemented with ANSYS through its user programmable features. The proposed approach is used to investigate size-dependent stress concentration around a nanosized circular hole and the size-dependent effective moduli of nanoporous materials. Numerical results are compared with available analytical results to validate the proposed modeling approach.

Keywords: Nanomaterials, finite element method, sizedependency, surface stress

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Authors: M. Bodner, M. Scampicchio

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Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm^–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R² = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R² = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.

Keywords: Adulterated butter, margarine, PCA, PLS-DA, PLS-R, SIMCA.

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Authors: H. Soleimanjahi, M. J. Nategh, S. Falahi

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Deciding the numerous parameters involved in designing a competent artificial neural network is a complicated task. The existence of several options for selecting an appropriate architecture for neural network adds to this complexity, especially when different applications of heterogeneous natures are concerned. Two completely different applications in engineering and medical science were selected in the present study including prediction of workpiece's surface roughness in ultrasonic-vibration assisted turning and papilloma viruses oncogenicity. Several neural network architectures with different parameters were developed for each application and the results were compared. It was illustrated in this paper that some applications such as the first one mentioned above are apt to be modeled by a single network with sufficient accuracy, whereas others such as the second application can be best modeled by different expert networks for different ranges of output. Development of knowledge about the essentials of neural networks for different applications is regarded as the cornerstone of multidisciplinary network design programs to be developed as a means of reducing inconsistencies and the burden of the user intervention.

Keywords: Artificial Neural Network, Malignancy Diagnosis, Papilloma Viruses Oncogenicity, Surface Roughness, UltrasonicVibration-Assisted Turning.

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Authors: Joseph Maloba Makokha

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Idea generation is an important part of the design process, and many strategies to support this stage have been developed. As artificial intelligence (AI) gains adoption in many domains, we need to understand its role, if any, in the design process. This paper introduces the concept of a “Disruptive Interjector”, an AI system that frequently interjects with suggestions based on observing what a user does. The concept emanates from a study that was conducted with pairs of humans on one hand, and human-AI pairs on the other collaborating on idea generation by sketching. Results from a study show that participants who collaborated with, and took cues from the AI sketch suggestions generated more ideas; and also had more ideas ranked by experts as “creative” compared to two humans working together on the same tasks. It is notable that while researchers from diverse fields of engineering, psychology, art and others have explored conditions and environments that enhance people's creativity - and have provided insights on creativity in general - there still exists a gap on the role that AI can play on creativity. We attempt to narrow this gap.

Keywords: Artificial intelligence, design collaboration, creativity, human-machine collaboration, machine learning.

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Authors: Ali Ghaffari, A. Hosein Shamekhi, Akbar Saki, Ehsan Kamrani

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In order to meet the limits imposed on automotive emissions, engine control systems are required to constrain air/fuel ratio (AFR) in a narrow band around the stoichiometric value, due to the strong decay of catalyst efficiency in case of rich or lean mixture. This paper presents a model of a sample spark ignition engine and demonstrates Simulink-s capabilities to model an internal combustion engine from the throttle to the crankshaft output. We used welldefined physical principles supplemented, where appropriate, with empirical relationships that describe the system-s dynamic behavior without introducing unnecessary complexity. We also presents a PID tuning method that uses an adaptive fuzzy system to model the relationship between the controller gains and the target output response, with the response specification set by desired percent overshoot and settling time. The adaptive fuzzy based input-output model is then used to tune on-line the PID gains for different response specifications. Experimental results demonstrate that better performance can be achieved with adaptive fuzzy tuning relative to similar alternative control strategies. The actual response specifications with adaptive fuzzy matched the desired response specifications.

Keywords: Modelling, Air–fuel ratio control, SI engine, Adaptive fuzzy Control.

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Authors: Simon E. Uguru, Victor E. Idigo, Obinna S. Oguejiofor, Naveed Nawaz

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As the deployment of the Fifth Generation (5G) mobile communication networks take shape all over the world, achieving spectral efficiency, energy efficiency, and dealing with interference are among the greatest challenges encountered so far. The aim of this study is to mitigate inter-cell interference (ICI) in a multi-cell multi-antenna system while maximizing the spectral efficiency of the system. In this study, a system model was devised that showed a miniature representation of a multi-cell multi-antenna system. Based on this system model, a convex optimization problem was formulated to maximize the spectral efficiency of the system while mitigating the ICI. This optimization problem was solved using CVX, which is a modeling system for constructing and solving discipline convex programs. The solutions to the optimization problem are sub-optimal coordinated beamformers. These coordinated beamformers direct each data to the served user equipments (UEs) in each cell without interference during downlink transmission, thereby maximizing the system-wide spectral efficiency.

Keywords: coordinated beamforming, convex optimization, inter-cell interference, multi-antenna, multi-cell, spectral efficiency

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Authors: Stephen Akuma, Isaac Terngu Adom, Evelyn Doofan Akuma

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Generation after generation of humans has experienced conflicts leading to needless deaths. Usually, it begins as a minor argument that occasionally escalates into a full-fledged conflict. There has been a lingering crisis in the Lake Chad Basin (LCB) of Africa for over a decade leading to bloodshed that has claimed thousands of lives. The terrorist group, Boko Haram has claimed responsibility for these deaths. Efforts have been made by the governments in the LCB region to end the crisis through kinetic approaches, but the conflict persists. In this work, we explored non-kinetic methods used by social scientists in resolving conflicts, with a focus on computational approaches due to the increasing processing power of the computer. Firstly, we reviewed the innovative computational methods available for researchers working on conflict, violence, and peace. Secondly, we described how an Agent-Based Model (ABM) can be linked with a Geographic Information System (GIS) to model the LCB. Finally, this research discusses the challenges and opportunities in constructing a Geographic Information System linked Agent-Based Model of the LCB region.

Keywords: Agent-based modelling, conflict, Geographical Information Systems, Lake Chad Basin, simulation.

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Authors: Faheem Ahmed, Piers Campbell, Ahmad Jaffar, Luiz Capretz

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Free and open source software is gaining popularity at an unprecedented rate of growth. Organizations despite some concerns about the quality have been using them for various purposes. One of the biggest concerns about free and open source software is post release software defects and their fixing. Many believe that there is no appropriate support available to fix the bugs. On the contrary some believe that due to the active involvement of internet user in online forums, they become a major source of communicating the identification and fixing of defects in open source software. The research model of this empirical investigation establishes and studies the relationship between open source software defects and online public forums. The results of this empirical study provide evidence about the realities of software defects myths of open source software. We used a dataset consist of 616 open source software projects covering a broad range of categories to study the research model of this investigation. The results of this investigation show that online forums play a significant role identifying and fixing the defects in open source software.

Keywords: About Open source software, software engineering, software defect management, empirical software engineering.

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Authors: K. Nirmala Devi, V. Murali Bhaskaran

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The exponential growth of social media arouses much attention on public opinion information. The online forums, blogs, micro blogs are proving to be extremely valuable resources and are having bulk volume of information. However, most of the social media data is unstructured and semi structured form. So that it is more difficult to decipher automatically. Therefore, it is very much essential to understand and analyze those data for making a right decision. The online forums hotspot detection is a promising research field in the web mining and it guides to motivate the user to take right decision in right time. The proposed system consist of a novel approach to detect a hotspot forum for any given time period. It uses aging theory to find the hot terms and E-K-means for detecting the hotspot forum. Experimental results demonstrate that the proposed approach outperforms k-means for detecting the hotspot forums with the improved accuracy.

Keywords: Hotspot forums, Micro blog, Blog, Sentiment Analysis, Opinion Mining, Social media, Twitter, Web mining.

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Authors: S. Nandagopalan, Dr. B. S. Adiga, N. Deepak

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In this paper a novel approach for generalized image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. This is provided through User Interface (UI) in the form of relevance feedback. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture cooccurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, a novel idea is developed based on greedy strategy to reduce the computational complexity. The entire system was developed using AForge.Imaging (an open source product), MATLAB .NET Builder, C#, and Oracle 10g. The system was tested with Coral Image database containing 1000 natural images and achieved better results.

Keywords: Content Based Image Retrieval (CBIR), Cooccurrencematrix, Feature vector, Edge Histogram Descriptor(EHD), Greedy strategy.

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Authors: Abdunaser Abduelmula, Maria Luisa M. Bastos, José A. Gonçalves

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Modelling of the earth's surface and evaluation of urban environment, with 3D models, is an important research topic. New stereo capabilities of high resolution optical satellites images, such as the tri-stereo mode of Pleiades, combined with new image matching algorithms, are now available and can be applied in urban area analysis. In addition, photogrammetry software packages gained new, more efficient matching algorithms, such as SGM, as well as improved filters to deal with shadow areas, can achieve more dense and more precise results. This paper describes a comparison between 3D data extracted from tri-stereo and dual stereo satellite images, combined with pixel based matching and Wallis filter. The aim was to improve the accuracy of 3D models especially in urban areas, in order to assess if satellite images are appropriate for a rapid evaluation of urban environments. The results showed that 3D models achieved by Pleiades tri-stereo outperformed, both in terms of accuracy and detail, the result obtained from a Geo-eye pair. The assessment was made with reference digital surface models derived from high resolution aerial photography. This could mean that tri-stereo images can be successfully used for the proposed urban change analyses.

Keywords: 3D Models, Environment, Matching, Pleiades.

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Authors: Shivakumar Krishnamurti, Ruchi Agarwal

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The study examines the influence of marital status on consumers of products and services using blogs as a source of information. A pre-designed questionnaire was used to collect the primary data from the respondents (experiences). Data were collected from one hundred and eighty seven respondents residing in and around the Emirates of Sharjah and Dubai of the United Arab Emirates. The collected data was analyzed with the help of statistical tools such as averages, percentages, factor analysis, Student’s t-test and Structural Equation Modelling Technique. Objectives of the study are to know the reasons how married and unmarried or single consumers of products and services are motivated to use blogs as a source of information, to know whether the consumers of products and services irrespective of their marital status share their views and experiences with other bloggers and to know the respondents’ future intentions towards blogging. The study revealed the following: Majority of the respondents have the motivation to blog because they are willing to receive comments on what they post about services, convenience of blogs to search for information about services and products, by blogging respondents share information on the symptoms of a disease/ disorder that may be experienced by someone, helps to share information about ready to cook mix products and are keen to spend more time blogging in the future.

Keywords: Blog, consumer, information, marital status.

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Authors: Pramod Goyal, S. K. Saxena

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The convergence of heterogeneous wireless access technologies characterizes the 4G wireless networks. In such converged systems, the seamless and efficient handoff between different access technologies (vertical handoff) is essential and remains a challenging problem. The heterogeneous co-existence of access technologies with largely different characteristics creates a decision problem of determining the “best" available network at “best" time to reduce the unnecessary handoffs. This paper proposes a dynamic decision model to decide the “best" network at “best" time moment to handoffs. The proposed dynamic decision model make the right vertical handoff decisions by determining the “best" network at “best" time among available networks based on, dynamic factors such as “Received Signal Strength(RSS)" of network and “velocity" of mobile station simultaneously with static factors like Usage Expense, Link capacity(offered bandwidth) and power consumption. This model not only meets the individual user needs but also improve the whole system performance by reducing the unnecessary handoffs.

Keywords: Dynamic decision model, Seamless handoff, Vertical handoff, Wireless networks

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Authors: Stephen Akuma, Timothy Ndera

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Information seekers get “lost in hyperspace” due to the voluminous documents updated daily on the internet. Adaptive Hypermedia Systems (AHS) are used to direct learners to their target goals. One of the most common AHS designed to help information seekers to overcome the problem of information overload is the Adaptive Education Hypermedia System (AEHS). However, this paper focuses on AEHS that adopts the learning preference of high school students and deliver learning content according to this preference throughout their learning experience. The research developed a prototype system for predicting students’ learning preference from the Visual, Aural, Read-Write and Kinesthetic (VARK) learning style model and adopting the learning content suitable to their preference. The predicting strength of several classifiers was compared and we found Support Vector Machine (SVM) to be more accurate in predicting learning style based on users’ preferences.

Keywords: Hypermedia, adaptive education, learning style, lesson content, user profile, prediction, feedback, adaptive hypermedia, learning style.

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Authors: Krishnamoorthi R., Sheba Kezia Malarchelvi P. D.

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In this paper, an image adaptive, invisible digital watermarking algorithm with Orthogonal Polynomials based Transformation (OPT) is proposed, for copyright protection of digital images. The proposed algorithm utilizes a visual model to determine the watermarking strength necessary to invisibly embed the watermark in the mid frequency AC coefficients of the cover image, chosen with a secret key. The visual model is designed to generate a Just Noticeable Distortion mask (JND) by analyzing the low level image characteristics such as textures, edges and luminance of the cover image in the orthogonal polynomials based transformation domain. Since the secret key is required for both embedding and extraction of watermark, it is not possible for an unauthorized user to extract the embedded watermark. The proposed scheme is robust to common image processing distortions like filtering, JPEG compression and additive noise. Experimental results show that the quality of OPT domain watermarked images is better than its DCT counterpart.

Keywords: Orthogonal Polynomials based Transformation, Digital Watermarking, Copyright Protection, Visual model.

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Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

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Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness.

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Authors: Sundus Ayyaz, Saad Rehman

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In the recent years, a fundamental revolution in the Mobile Phone technology from just being able to provide voice and short message services to becoming the most essential part of our lives by connecting to network and various app stores for downloading software apps of almost every activity related to our life from finding location to banking from getting news updates to downloading HD videos and so on. This progress in Smart Phone industry has modernized and transformed our way of living into a trouble-free world. The smart phone has become our personal computers with the addition of significant features such as multi core processors, multi-tasking, large storage space, bluetooth, WiFi, including large screen and cameras. With this evolution, the rise in the security threats have also been amplified. In Literature, different threats related to smart phones have been highlighted and various precautions and solutions have been proposed to keep the smart phone safe which carries all the private data of a user. In this paper, a survey has been carried out to find out the most secure and the most unsecure smart phone operating system among the most popular smart phones in use today.

Keywords: Smart phone, operating system, security threats, Android, iOS, Balckberry, Windows.

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Authors: I. A Tijani, Y. F Wu, C.W. Lim

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Concrete Damaged Plasticity Model (CDPM) is capable of modeling the stress-strain behavior of confined concrete. Nevertheless, the accuracy of the model largely depends on its parameters. To date, most research works mainly focus on the identification and modification of the parameters for fiber reinforced polymer (FRP) confined concrete prior to damage. And, it has been established that the FRP-strengthened concrete behaves differently to FRP-repaired concrete. This paper presents a modified plastic damage model within the context of the CDPM in ABAQUS for modelling of a uniformly FRP-confined repaired concrete under monotonic loading. The proposed model includes infliction damage, elastic stiffness, yield criterion and strain hardening rule. The distinct feature of damaged concrete is elastic stiffness reduction; this is included in the model. Meanwhile, the test results were obtained from a physical testing of repaired concrete. The dilation model is expressed as a function of the lateral stiffness of the FRP-jacket. The finite element predictions are shown to be in close agreement with the obtained test results of the repaired concrete. It was observed from the study that with necessary modifications, finite element method is capable of modeling FRP-repaired concrete structures.

Keywords: Concrete, FRP, damage, repairing, plasticity, and finite element method.

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

Abstract:

In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: Anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines.

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Authors: N. Mamode Khan, V. Jowaheer

Abstract:

In this paper, we apply and compare two generalized estimating equation approaches to the analysis of car breakdowns data in Mauritius. Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observation as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use the two types of quasi-likelihood estimation approaches to estimate the parameters of the model: marginal and joint generalized quasi-likelihood estimating equation approaches. Under-dispersion parameter is estimated to be around 2.14 justifying the appropriateness of Com-Poisson distribution in modelling underdispersed count responses recorded in this study.

Keywords: Breakdowns, under-dispersion, com-poisson, generalized linear model, marginal quasi-likelihood estimation, joint quasi-likelihood estimation.

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