Hardware Prototyping of an Efficient Encryption Engine

An approach to develop the FPGA of a flexible key RSA encryption engine that can be used as a standard device in the secured communication system is presented. The VHDL modeling of this RSA encryption engine has the unique characteristics of supporting multiple key sizes, thus can easily be fit into the systems that require different levels of security. A simple nested loop addition and subtraction have been used in order to implement the RSA operation. This has made the processing time faster and used comparatively smaller amount of space in the FPGA. The hardware design is targeted on Altera STRATIX II device and determined that the flexible key RSA encryption engine can be best suited in the device named EP2S30F484C3. The RSA encryption implementation has made use of 13,779 units of logic elements and achieved a clock frequency of 17.77MHz. It has been verified that this RSA encryption engine can perform 32-bit, 256-bit and 1024-bit encryption operation in less than 41.585us, 531.515us and 790.61us respectively.

Performance Evaluation of a Limited Round-Robin System

Performance of a limited Round-Robin (RR) rule is studied in order to clarify the characteristics of a realistic sharing model of a processor. Under the limited RR rule, the processor allocates to each request a fixed amount of time, called a quantum, in a fixed order. The sum of the requests being allocated these quanta is kept below a fixed value. Arriving requests that cannot be allocated quanta because of such a restriction are queued or rejected. Practical performance measures, such as the relationship between the mean sojourn time, the mean number of requests, or the loss probability and the quantum size are evaluated via simulation. In the evaluation, the requested service time of an arriving request is converted into a quantum number. One of these quanta is included in an RR cycle, which means a series of quanta allocated to each request in a fixed order. The service time of the arriving request can be evaluated using the number of RR cycles required to complete the service, the number of requests receiving service, and the quantum size. Then an increase or decrease in the number of quanta that are necessary before service is completed is reevaluated at the arrival or departure of other requests. Tracking these events and calculations enables us to analyze the performance of our limited RR rule. In particular, we obtain the most suitable quantum size, which minimizes the mean sojourn time, for the case in which the switching time for each quantum is considered.

PUMA 560 Optimal Trajectory Control using Genetic Algorithm, Simulated Annealing and Generalized Pattern Search Techniques

Robot manipulators are highly coupled nonlinear systems, therefore real system and mathematical model of dynamics used for control system design are not same. Hence, fine-tuning of controller is always needed. For better tuning fast simulation speed is desired. Since, Matlab incorporates LAPACK to increase the speed and complexity of matrix computation, dynamics, forward and inverse kinematics of PUMA 560 is modeled on Matlab/Simulink in such a way that all operations are matrix based which give very less simulation time. This paper compares PID parameter tuning using Genetic Algorithm, Simulated Annealing, Generalized Pattern Search (GPS) and Hybrid Search techniques. Controller performances for all these methods are compared in terms of joint space ITSE and cartesian space ISE for tracking circular and butterfly trajectories. Disturbance signal is added to check robustness of controller. GAGPS hybrid search technique is showing best results for tuning PID controller parameters in terms of ITSE and robustness.

A Study of Touching Characters in Degraded Gurmukhi Text

Character segmentation is an important preprocessing step for text recognition. In degraded documents, existence of touching characters decreases recognition rate drastically, for any optical character recognition (OCR) system. In this paper a study of touching Gurmukhi characters is carried out and these characters have been divided into various categories after a careful analysis.Structural properties of the Gurmukhi characters are used for defining the categories. New algorithms have been proposed to segment the touching characters in middle zone. These algorithms have shown a reasonable improvement in segmenting the touching characters in degraded Gurmukhi script. The algorithms proposed in this paper are applicable only to machine printed text.

Using Submerge Fermentation Method to Production of Extracellular Lipase by Aspergillus niger

In this study, lipase production has been investigated using submerge fermentation by Aspergillus niger in Kilka fish oil as main substrate. The Taguchi method with an L9 orthogonal array design was used to investigate the effect of parameters and their levels on lipase productivity. The optimum conditions for Kilka fish oil concentration, incubation temperature and pH were obtained 3 gr./ml 35°C and 7, respectively. The amount of lipase activity in optimum condition was obtained 4.59IU/ml. By comparing this amount with the amount of productivity in the olive oil medium based on the cost of each medium, it was that using Kilka fish oil is 84% economical. Therefore Kilka fish oil can be used as an economical and suitable substrate in the lipase production and industrial usages.

Architecting a Knowledge Theatre

This paper describes the architectural design considerations for building a new class of application, a Personal Knowledge Integrator and a particular example a Knowledge Theatre. It then supports this description by describing a scenario of a child acquiring knowledge and how this process could be augmented by the proposed architecture and design of a Knowledge Theatre. David Merrill-s first “principles of instruction" are kept in focus to provide a background to view the learning potential.

Automated Stereophotogrammetry Data Cleansing

The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.

Motion Planning and Control of Autonomous Robots in a Two-dimensional Plane

This paper proposes a solution to the motion planning and control problem of a point-mass robot which is required to move safely to a designated target in a priori known workspace cluttered with fixed elliptical obstacles of arbitrary position and sizes. A tailored and unique algorithm for target convergence and obstacle avoidance is proposed that will work for any number of fixed obstacles. The control laws proposed in this paper also ensures that the equilibrium point of the given system is asymptotically stable. Computer simulations with the proposed technique and applications to a planar (RP) manipulator will be presented.

Application-Specific Instruction Sets Processor with Implicit Registers to Improve Register Bandwidth

Application-Specific Instruction (ASI ) set Processors (ASIP) have become an important design choice for embedded systems due to runtime flexibility, which cannot be provided by custom ASIC solutions. One major bottleneck in maximizing ASIP performance is the limitation on the data bandwidth between the General Purpose Register File (GPRF) and ASIs. This paper presents the Implicit Registers (IRs) to provide the desirable data bandwidth. An ASI Input/Output model is proposed to formulate the overheads of the additional data transfer between the GPRF and IRs, therefore, an IRs allocation algorithm is used to achieve the better performance by minimizing the number of extra data transfer instructions. The experiment results show an up to 3.33x speedup compared to the results without using IRs.

The Content Based Objective Metrics for Video Quality Evaluation

In this paper we proposed comparison of four content based objective metrics with results of subjective tests from 80 video sequences. We also include two objective metrics VQM and SSIM to our comparison to serve as “reference” objective metrics because their pros and cons have already been published. Each of the video sequence was preprocessed by the region recognition algorithm and then the particular objective video quality metric were calculated i.e. mutual information, angular distance, moment of angle and normalized cross-correlation measure. The Pearson coefficient was calculated to express metrics relationship to accuracy of the model and the Spearman rank order correlation coefficient to represent the metrics relationship to monotonicity. The results show that model with the mutual information as objective metric provides best result and it is suitable for evaluating quality of video sequences.

Detection and Classification of Faults on Parallel Transmission Lines Using Wavelet Transform and Neural Network

The protection of parallel transmission lines has been a challenging task due to mutual coupling between the adjacent circuits of the line. This paper presents a novel scheme for detection and classification of faults on parallel transmission lines. The proposed approach uses combination of wavelet transform and neural network, to solve the problem. While wavelet transform is a powerful mathematical tool which can be employed as a fast and very effective means of analyzing power system transient signals, artificial neural network has a ability to classify non-linear relationship between measured signals by identifying different patterns of the associated signals. The proposed algorithm consists of time-frequency analysis of fault generated transients using wavelet transform, followed by pattern recognition using artificial neural network to identify the type of the fault. MATLAB/Simulink is used to generate fault signals and verify the correctness of the algorithm. The adaptive discrimination scheme is tested by simulating different types of fault and varying fault resistance, fault location and fault inception time, on a given power system model. The simulation results show that the proposed scheme for fault diagnosis is able to classify all the faults on the parallel transmission line rapidly and correctly.

Endogenous Fantasy – Based Serious Games: Intrinsic Motivation and Learning

Current technological advances pale in comparison to the changes in social behaviors and 'sense of place' that is being empowered since the Internet made it on the scene. Today-s students view the Internet as both a source of entertainment and an educational tool. The development of virtual environments is a conceptual framework that needs to be addressed by educators and it is important that they become familiar with who these virtual learners are and how they are motivated to learn. Massively multiplayer online role playing games (MMORPGs), if well designed, could become the vehicle of choice to deliver learning content. We suggest that these games, in order to accomplish these goals, must begin with well-established instructional design principles that are co-aligned with established principles of video game design. And have the opportunity to provide an instructional model of significant prescriptive power. The authors believe that game designers need to take advantage of the natural motivation player-learners have for playing games by developing them in such a way so as to promote, intrinsic motivation, content learning, transfer of knowledge, and naturalization.

Legal Awareness of Surakarta Local Government Officer to Law Number 12 Year 2006 on Citizenship in Vanishing Civic Discrimination to Chinese Indonesians

The purposes of the paper are to know and improve the legal awareness of Surakarta local government officer to Law No.12/2006 on Citizenship in vanishing civic discrimination to Chinese Indonesians. Some issues of the Chinese Indonesian are the definitions of Indonesian citizens and native Indonesian people or “warga negara Indonesia (WNI) asli" and their obligation to show Indonesian Citizenship Certificate (SBKRI) in processing civil documents. Legal awareness of Surakarta local government officer can be categorized as “legal knowledge" only. They know the laws but they do not implement it yet. Nevertheless, at least this research has given the new awareness in citizenship law for the officers.

Bayes Net Classifiers for Prediction of Renal Graft Status and Survival Period

This paper presents the development of a Bayesian belief network classifier for prediction of graft status and survival period in renal transplantation using the patient profile information prior to the transplantation. The objective was to explore feasibility of developing a decision making tool for identifying the most suitable recipient among the candidate pool members. The dataset was compiled from the University of Toledo Medical Center Hospital patients as reported to the United Network Organ Sharing, and had 1228 patient records for the period covering 1987 through 2009. The Bayes net classifiers were developed using the Weka machine learning software workbench. Two separate classifiers were induced from the data set, one to predict the status of the graft as either failed or living, and a second classifier to predict the graft survival period. The classifier for graft status prediction performed very well with a prediction accuracy of 97.8% and true positive values of 0.967 and 0.988 for the living and failed classes, respectively. The second classifier to predict the graft survival period yielded a prediction accuracy of 68.2% and a true positive rate of 0.85 for the class representing those instances with kidneys failing during the first year following transplantation. Simulation results indicated that it is feasible to develop a successful Bayesian belief network classifier for prediction of graft status, but not the graft survival period, using the information in UNOS database.

The Effect of Ambient Occlusion Shading on Perception of Sign Language Animations

The goal of the study reported in the paper was to determine whether Ambient Occlusion Shading (AOS) has a significant effect on users' perception of American Sign Language (ASL) finger spelling animations. Seventy-one (71) subjects participated in the study; all subjects were fluent in ASL. The participants were asked to watch forty (40) sign language animation clips representing twenty (20) finger spelled words. Twenty (20) clips did not show ambient occlusion, whereas the other twenty (20) were rendered using ambient occlusion shading. After viewing each animation, subjects were asked to type the word being finger-spelled and rate its legibility. Findings show that the presence of AOS had a significant effect on the subjects perception of the signed words. Subjects were able to recognize the animated words rendered with AOS with higher level of accuracy, and the legibility ratings of the animations showing AOS were consistently higher across subjects.

Does Bio-Demographic Diversity Influence Team Innovation through Participation Safety Climate and Team Reflexivity?

Bio-demographic diversity which refers to age and gender of members in a team, has been frequently identified to influence team innovation directly. As the theories expanded, biodemographic diversity was suggested to influence team innovation via psychosocial trait and interaction process. This study examines those suggestions, in which psychosocial trait and interaction process were operationalized as 'participation safety climate' and 'team reflexivity' respectively. The role of team reflexivity as a mediator to participation safety climate and team innovation was also assessed. Due to a small number of teams involved in the study, data were analyzed by using a PLS-graph. While the results show only gender is significantly related to the participation safety climate, which in turn influences team reflexivity and team innovation, there is no statistical evidence that team reflexivity mediates the impact of participation safety climate on team innovation.

Information content of Islamic Private Debt Announcement: Evidence from Malaysia

Different types of Islamic debts have been increasingly utilized as preferred means of debt funding by Malaysian private firms in recent years. This study examines the impact of Islamic debts announcement on private firms- stock returns. Our sample includes forty five listed companies on Bursa Malaysia involved in issuing of Islamic debts during 2005 to 2008. The abnormal returns and cumulative average abnormal returns are calculated and tested using standard event study methodology. The results show that a significant, negative abnormal return occurs one day before announcement date. This negative abnormal return is representing market participant-s adverse attitude toward Islamic private debt announcement during the research period.

Effectiveness of ICT Training Workshop for Tutors of Allama Iqbal Open University, Pakistan

The purpose of the study was to investigate the effectiveness of ICT training workshop of tutors of Allama Iqbal Open University Pakistan. The study was delimited to tutors of Multan region. The total sample comprised of 100 tutors. All the tutors who participated in ICT training workshop in Multan region were taken as sample in the study. A questionnaire having two parts, based on five point rating scale was developed by the researcher. Part one was about the competency level of computer skills while Part two was based on items related to training delivery, structure and content. Part One of questionnaire had five levels of competency about computer skills. The questionnaire was personally administered and collected back by the researcher himself on the last day of workshop. The collected data were analyzed by using descriptive statistics. Through this study it was found that majority of the tutors strongly agreed that training enhanced their computer skills. Majority of the respondents consider themselves to be generally competent in the use of computer. They also agreed that there was appropriate infrastructure and technical support in lab during training workshop. Moreover, it was found that the training imparted the knowledge of pedagogy of using computers for distance education.

Advanced Geolocation of IP Addresses

Tracing and locating the geographical location of users (Geolocation) is used extensively in todays Internet. Whenever we, e.g., request a page from google we are - unless there was a specific configuration made - automatically forwarded to the page with the relevant language and amongst others, dependent on our location identified, specific commercials are presented. Especially within the area of Network Security, Geolocation has a significant impact. Because of the way the Internet works, attacks can be executed from almost everywhere. Therefore, for an attribution, knowledge of the origination of an attack - and thus Geolocation - is mandatory in order to be able to trace back an attacker. In addition, Geolocation can also be used very successfully to increase the security of a network during operation (i.e. before an intrusion actually has taken place). Similar to greylisting in emails, Geolocation allows to (i) correlate attacks detected with new connections and (ii) as a consequence to classify traffic a priori as more suspicious (thus particularly allowing to inspect this traffic in more detail). Although numerous techniques for Geolocation are existing, each strategy is subject to certain restrictions. Following the ideas of Endo et al., this publication tries to overcome these shortcomings with a combined solution of different methods to allow improved and optimized Geolocation. Thus, we present our architecture for improved Geolocation, by designing a new algorithm, which combines several Geolocation techniques to increase the accuracy.

A Multi-Phase Methodology for Investigating Localisation Policies within the GCC: The Hotel Industry in the KSA and the UAE

Due to a high unemployment rate among local people and a high reliance on expatriate workers, the governments in the Gulf Co-operation Council (GCC) countries have been implementing programmes of localisation (replacing foreign workers with GCC nationals). These programmes have been successful in the public sector but much less so in the private sector. However, there are now insufficient jobs for locals in the public sector and the onus to provide employment has fallen on the private sector. This paper is concerned with a study, which is a work in progress (certain elements are complete but not the whole study), investigating the effective implementation of localisation policies in four- and five-star hotels in the Kingdom of Saudi Arabia (KSA) and the United Arab Emirates (UAE). The purpose of the paper is to identify the research gap, and to present the need for the research. Further, it will explain how this research was conducted. Studies of localisation in the GCC countries are under-represented in scholarly literature. Currently, the hotel sectors in KSA and UAE play an important part in the countries’ economies. However, the total proportion of Saudis working in the hotel sector in KSA is slightly under 8%, and in the UAE, the hotel sector remains highly reliant on expatriates. There is therefore a need for research on strategies to enhance the implementation of the localisation policies in general and in the hotel sector in particular. Further, despite the importance of the hotel sector to their economies, there remains a dearth of research into the implementation of localisation policies in this sector. Indeed, as far as the researchers are aware, there is no study examining localisation in the hotel sector in KSA, and few in the UAE. This represents a considerable research gap. Regarding how the research was carried out, a multiple case study strategy was used. The four- and five-star hotel sector in KSA is one of the cases, while the four- and five-star hotel sector in the UAE is the other case. Four- and five-star hotels in KSA and the UAE were chosen as these countries have the longest established localisation policies of all the GCC states and there are more hotels of these classifications in these countries than in any of the other Gulf countries. A literature review was carried out to underpin the research. The empirical data were gathered in three phases. In order to gain a pre-understanding of the issues pertaining to the research context, Phase I involved eight unstructured interviews with officials from the Saudi Commission for Tourism and Antiquities (three interviewees); the Saudi Human Resources Development Fund (one); the Abu Dhabi Tourism and Culture Authority (three); and the Abu Dhabi Development Fund (one). In Phase II, a questionnaire was administered to 24 managers and 24 employees in four- and five-star hotels in each country to obtain their beliefs, attitudes, opinions, preferences and practices concerning localisation. Unstructured interviews were carried out in Phase III with six managers in each country in order to allow them to express opinions that may not have been explored in sufficient depth in the questionnaire. The interviews in Phases I and III were analysed using thematic analysis and SPSS will be used to analyse the questionnaire data. It is recommended that future research be undertaken on a larger scale, with a larger sample taken from all over KSA and the UAE rather than from only four cities (i.e., Riyadh and Jeddah in KSA and Abu Dhabi and Sharjah in the UAE), as was the case in this research.