Search results for: real time data analysis

Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: Low density, optical flow, upward smoke motion, video based smoke detection.

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Authors: Yananda Siraphatthada

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The objectives of this research were to study the level of influencing factors, leadership, supply chain management, innovation, competitive advantages, business success, and affecting factors to the business success of the mobile phone system service providers in Bangkok Metropolitan. This research was done by the quantitative approach and the qualitative approach. The quantitative approach was used for questionnaires to collect data from the 331 mobile service shop managers franchised by AIS, Dtac and TrueMove. The mobile phone system service providers/shop managers were randomly stratified and proportionally allocated into subgroups exclusive to the number of the providers in each network. In terms of qualitative method, there were in-depth interviews of 6 mobile service providers/managers of Telewiz and Dtac and TrueMove shop to find the agreement or disagreement with the content analysis method. Descriptive Statistics, including Frequency, Percentage, Means and Standard Deviation were employed; also, the Structural Equation Model (SEM) was used as a tool for data analysis. The content analysis method was applied to identify key patterns emerging from the interview responses. The two data sets were brought together for comparing and contrasting to make the findings, providing triangulation to enrich result interpretation. It revealed that the level of the influencing factors – leadership, innovation management, supply chain management, and business competitiveness had an impact at a great level, but that the level of factors, innovation and the business, financial success and nonbusiness financial success of the mobile phone system service providers in Bangkok Metropolitan, is at the highest level. Moreover, the business influencing factors, competitive advantages in the business of mobile system service providers which were leadership, supply chain management, innovation management, business advantages, and business success, had statistical significance at .01 which corresponded to the data from the interviews.

Keywords: Business success, mobile service providers.

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Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

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Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: Cooperative networks, normalized capacity, sensing time.

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Authors: Ehab F. Badran, Guoxiang Gu

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We consider optimal channel equalization for MIMO (multi-input/multi-output) time-varying channels in the sense of MMSE (minimum mean-squared-error), where the observation noise can be non-stationary. We show that all ZF (zero-forcing) receivers can be parameterized in an affine form which eliminates completely the ISI (inter-symbol-interference), and optimal channel equalizers can be designed through minimization of the MSE (mean-squarederror) between the detected signals and the transmitted signals, among all ZF receivers. We demonstrate that the optimal channel equalizer is a modified Kalman filter, and show that under the AWGN (additive white Gaussian noise) assumption, the proposed optimal channel equalizer minimizes the BER (bit error rate) among all possible ZF receivers. Our results are applicable to optimal channel equalization for DWMT (discrete wavelet multitone), multirate transmultiplexers, OFDM (orthogonal frequency division multiplexing), and DS (direct sequence) CDMA (code division multiple access) wireless data communication systems. A design algorithm for optimal channel equalization is developed, and several simulation examples are worked out to illustrate the proposed design algorithm.

Keywords: Channel equalization, Kalman filtering, Time-varying systems.

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Authors: G. Theonas, D. Hobbs, D. Rigas

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The scope of this research was to study the relation between the facial expressions of three lecturers in a real academic lecture theatre and the reactions of the students to those expressions. The first experiment aimed to investigate the effectiveness of a virtual lecturer-s expressions on the students- learning outcome in a virtual pedagogical environment. The second experiment studied the effectiveness of a single facial expression, i.e. the smile, on the students- performance. Both experiments involved virtual lectures, with virtual lecturers teaching real students. The results suggest that the students performed better by 86%, in the lectures where the lecturer performed facial expressions compared to the results of the lectures that did not use facial expressions. However, when simple or basic information was used, the facial expressions of the virtual lecturer had no substantial effect on the students- learning outcome. Finally, the appropriate use of smiles increased the interest of the students and consequently their performance.

Keywords: emotion, facial expression, smile, virtual educational environment, virtual learning, virtual lecturer.

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Authors: Tshaudi Motsima

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Class attendance is key at all levels of education. At tertiary level many students develop a tendency of not attending all classes without being aware of the repercussions of not attending all classes. It is important for all students to attend all classes as they can receive first-hand information and they can benefit more. The student who attends classes is likely to perform better academically than the student who does not. The aim of this paper is to assess the relationship between class attendance and academic performance of industrial engineering students. The data for this study were collected through the attendance register of students and the other data were accessed from the Integrated Tertiary Software and the Higher Education Data Analyzer Portal. Data analysis was conducted on a sample of 93 students. The results revealed that students with medium predicate scores (OR = 3.8; p = 0.027) and students with low predicate scores (OR = 21.4, p < 0.001) were significantly likely to attend less than 80% of the classes as compared to students with high predicate scores. Students with examination performance of less than 50% were likely to attend less than 80% of classes than students with examination performance of 50% and above, but the differences were not statistically significant (OR = 1.3; p = 0.750).

Keywords: Class attendance, examination performance, final outcome, logistic regression.

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Authors: Hanaa E.Sayed, Hossam A. Gabbar, Shigeji Miyazaki

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This paper presents Faults Forecasting System (FFS) that utilizes statistical forecasting techniques in analyzing process variables data in order to forecast faults occurrences. FFS is proposing new idea in detecting faults. Current techniques used in faults detection are based on analyzing the current status of the system variables in order to check if the current status is fault or not. FFS is using forecasting techniques to predict future timing for faults before it happens. Proposed model is applying subset modeling strategy and Bayesian approach in order to decrease dimensionality of the process variables and improve faults forecasting accuracy. A practical experiment, designed and implemented in Okayama University, Japan, is implemented, and the comparison shows that our proposed model is showing high forecasting accuracy and BEFORE-TIME.

Keywords: Bayesian Techniques, Faults Detection, Forecasting techniques, Multivariate Analysis.

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Authors: Sellappan Narayanagounder, Karuppusami Gurusami

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The traditional Failure Mode and Effects Analysis (FMEA) uses Risk Priority Number (RPN) to evaluate the risk level of a component or process. The RPN index is determined by calculating the product of severity, occurrence and detection indexes. The most critically debated disadvantage of this approach is that various sets of these three indexes may produce an identical value of RPN. This research paper seeks to address the drawbacks in traditional FMEA and to propose a new approach to overcome these shortcomings. The Risk Priority Code (RPC) is used to prioritize failure modes, when two or more failure modes have the same RPN. A new method is proposed to prioritize failure modes, when there is a disagreement in ranking scale for severity, occurrence and detection. An Analysis of Variance (ANOVA) is used to compare means of RPN values. SPSS (Statistical Package for the Social Sciences) statistical analysis package is used to analyze the data. The results presented are based on two case studies. It is found that the proposed new methodology/approach resolves the limitations of traditional FMEA approach.

Keywords: Failure mode and effects analysis, Risk priority code, Critical failure mode, Analysis of variance.

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Authors: A. A. AlRasheed, A. Atkins, R. Campion

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This paper focuses on using knowledge management and visualisation concepts to improve the patients and hospitals employee’s workflow. Hospitals workflow is a complex and complicated process and poor patient flow can put both patients and a hospital’s reputation at risk, and can threaten the facility’s financial sustainability. Healthcare leaders are under increased pressure to reduce costs while maintaining or increasing patient care standards. In this paper, a framework is proposed to help improving patient experience, staff satisfaction, and operational efficiency across hospitals by using knowledge management based visualisation concepts. This framework is using real-time visibility to track and monitor location and status of patients, staff, rooms, and medical equipment.

Keywords: Knowledge management, visualisation, patients, hospitals, healthcare workers, workflow, improvements.

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Authors: Lidon Lashley

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This paper presents how the social model of disability can be used to reshape inclusive education practices in Guyana. Inclusive education in Guyana is metamorphosizing but still firmly held in the tenets of the Medical Model of Disability which influences the experiences of children with Special Education Needs and/or Disabilities (SEN/D). An ethnographic approach to data gathering was employed in this study. Qualitative data were gathered from the voices of children with and without SEN/D as well as their mainstream teachers to present the interplay of discourses and subjectivities in the situation. The data were analyzed using Adele Clarke's situational analysis. The data suggest that it is possible but will be challenging to fully contextualize and adopt Loreman's synthesis and Booths and Ainscow's Index in the two mainstream schools studied. In addition, the data paved the way for the presentation of the 'Southern Inclusive Education Framework for Guyana' and its support tool 'The Inclusive Checker created for Southern mainstream primary classrooms'.

Keywords: Social Model of Disability, Medical Model of Disability, subjectivities, metamorphosis, special education needs, postcolonial Guyana, Quasi-inclusion practices, Guyanese cultural challenges, mainstream primary schools, Loreman's Synthesis, Booths and Ainscow's Index.

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Authors: W. S. Hsu, S. W. Chen, Y. T. Ku, Y. Chiang, J. R. Wang , J. H. Yang, C. Shih

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ALOHA code was used to calculate the concentration under the CO₂ storage burst condition for Maanshan nuclear power plant (NPP) in this study. Five main data are input into ALOHA code including location, building, chemical, atmospheric, and source data. The data from Final Safety Analysis Report (FSAR) and some reports were used in this study. The ALOHA results are compared with the failure criteria of R.G. 1.78 to confirm the habitability of control room. The result of comparison presents that the ALOHA result is below the R.G. 1.78 criteria. This implies that the habitability of control room can be maintained in this case. The sensitivity study for atmospheric parameters was performed in this study. The results show that the wind speed has the larger effect in the concentration calculation.

Keywords: PWR, ALOHA, habitability, Maanshan.

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Authors: F. Sangiorgio, J. Silfwerbrand, G. Mancini

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Geometric and mechanical properties all influence the resistance of RC structures and may, in certain combination of property values, increase the risk of a brittle failure of the whole system. This paper presents a statistical and probabilistic investigation on the resistance of RC beams designed according to Eurocodes 2 and 8, and subjected to multiple failure modes, under both the natural variation of material properties and the uncertainty associated with cross-section and transverse reinforcement geometry. A full probabilistic model based on JCSS Probabilistic Model Code is derived. Different beams are studied through material nonlinear analysis via Monte Carlo simulations. The resistance model is consistent with Eurocode 2. Both a multivariate statistical evaluation and the data clustering analysis of outcomes are then performed. Results show that the ultimate load behaviour of RC beams subjected to flexural and shear failure modes seems to be mainly influenced by the combination of the mechanical properties of both longitudinal reinforcement and stirrups, and the tensile strength of concrete, of which the latter appears to affect the overall response of the system in a nonlinear way. The model uncertainty of the resistance model used in the analysis plays undoubtedly an important role in interpreting results.

Keywords: Modelling, Monte Carlo Simulations, Probabilistic Models, Data Clustering, Reinforced Concrete Members, Structural Design.

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Authors: MD Zaheer Ansari, A.K. Nirala

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In this study spatial-temporal speckle correlation techniques have been applied for the quality evaluation of three different Indian fruits namely apple, pear and tomato for the first time. The method is based on the analysis of variations of laser light scattered from biological samples. The results showed that crosscorrelation coefficients of biospeckle patterns change subject to their freshness and the storage conditions. The biospeckle activity was determined by means of the cross-correlation functions of the intensity fluctuations. Significant changes in biospeckle activity were observed during their shelf lives. From the study, it is found that the biospeckle activity decreases with the shelf-life storage time. Further it has been shown that biospeckle activity changes according to their respiration rates.

Keywords: Biospeckle, cross-correlation, respiration, shelf-life.

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Authors: R. F. B. Gonçalves, E. N. Iwama, J. A. F. F. Rocco, K. Iha

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Propellants based on Hydroxyl Terminated Polybutadiene/Ammonium Perchlorate (HTPB/AP) are the most commonly used in most of the rocket engines used by the Brazilian Armed Forces. This work aimed at the possibility of extending its useful life (currently in 10 years) by performing kinetic-chemical analyzes of its energetic material via Differential Scanning Calorimetry (DSC) and also performing computer simulation of aging process using the software Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). Thermal analysis via DSC was performed in triplicates and in three heating ratios (5 ºC, 10 ºC, and 15 ºC) of rocket motor with 11 years shelf-life, using the Arrhenius equation to obtain its activation energy, using Ozawa and Kissinger kinetic methods, allowing comparison with manufacturing period data (standard motor). In addition, the kinetic parameters of internal pressure of the combustion chamber in 08 rocket engines with 11 years of shelf-life were also acquired, for comparison purposes with the engine start-up data.

Keywords: Shelf-life, thermal analysis, Ozawa method, Kissinger method, LAMMPS software, thrust.

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Authors: Marilena Ianculescu, Adriana Alexandru

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Internet of Health Things (IoHT) has already proved to be a persuasive means to support a proper assessment of the living conditions by collecting a huge variety of data. For a customized health management of a senior patient, IoHT provides the capacity to build a dynamic solution for sustaining the shift inside the patient-physician relationship by allowing a real-time and continuous remote monitoring of the health status, well-being, safety and activities of the senior, especially in a non-clinical environment. Thus, is created a win-win solution in which both the patient and the physician enhance their involvement and shared decision-making, with significant outcomes. Health monitoring systems in smart environments are becoming a viable alternative to traditional healthcare solutions. The ongoing “Non-invasive monitoring and health assessment of the elderly in a smart environment (RO-SmartAgeing)” project aims to demonstrate that the existence of complete and accurate information is critical for assessing the health condition of the seniors, improving wellbeing and quality of life in relation to health. The researches performed inside the project aim to highlight how the management of IoHT devices connected to the RO-SmartAgeing platform in a secure way by using a role-based access control system, can allow the physicians to provide health services at a high level of efficiency and accessibility, which were previously only available in hospitals. The project aims to identify deficient aspects in the provision of health services tailored to a senior patient’s specificity and to offer a more comprehensive perspective of proactive and preventive medical acts.

Keywords: Health management, Internet of Health Things, remote monitoring, senior patient.

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Authors: Jianwei Wang, Timo Korhonen, Yuping Zhao

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Cross layer optimization based on utility functions has been recently studied extensively, meanwhile, numerous types of utility functions have been examined in the corresponding literature. However, a major drawback is that most utility functions take a fixed mathematical form or are based on simple combining, which can not fully exploit available information. In this paper, we formulate a framework of cross layer optimization based on Adaptively Weighted Utility Functions (AWUF) for fairness balancing in OFDMA networks. Under this framework, a two-step allocation algorithm is provided as a sub-optimal solution, whose control parameters can be updated in real-time to accommodate instantaneous QoS constrains. The simulation results show that the proposed algorithm achieves high throughput while balancing the fairness among multiple users.

Keywords: OFDMA, Fairness, AWUF, QoS.

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Authors: Haitham S. Hamza, Mohamed Maher, Shourok Alaa, Aya Khattab, Hadeal Ismail, Kamilia Hosny

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Radio Frequency Identification (RFID) has become a key technology in the emerging concept of Internet of Things (IoT). Naturally, business applications would require the deployment of various RFID systems developed by different vendors that use different data formats and structures. This heterogeneity poses a challenge in developing real-life IoT systems with RFID, as integration is becoming very complex and challenging. Semantic integration is a key approach to deal with this challenge. To do so, ontology for RFID systems need to be developed in order to annotated semantically RFID systems, and hence, facilitate their integration. Accordingly, in this paper, we propose ontology for RFID systems. The proposed ontology can be used to semantically enrich RFID systems, and hence, improve their usage and reasoning.

Keywords: IoT, RFID, Semantic, sparql, Ontology.

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Authors: Najmeh Bolbolamiri, Maryam Setayesh Sanai, Ahmad Mirabadi

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This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.

Keywords: stator currents monitoring, railway points, point failures, fault detection and diagnosis, Kolmogorov-Smirnov test, time-domain analysis.

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Authors: V. T. S. Dao, T. G. Etoh, C. Vo Le, H. D. Nguyen, K. Takehara, T. Akino, K. Nishi

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We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.

Keywords: Dimensional Analysis, Elmore model, RC network, Signal Attenuation, Ultra-High-Speed Image Sensor.

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Authors: Saeed Mohammed Baneamoon, Rosalina Abdul Salam, Abdullah Zawawi Hj. Talib

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Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real world. These problems are: time consuming, high cost, high errors percentage and low efficiency and accuracy of the system. The proposed system will investigate and improve the efficiency and accuracy of a simulated robot to choose correct behavior to perform its task. In this paper, machine learning, which uses genetic algorithm, is adopted. This type of machine learning is called genetic-based machine learning in which a distributed classifier system is used to improve the efficiency and accuracy of the robot. Consequently, it helps the robot to achieve optimal action.

Keywords: Machine Learning, Genetic-Based MachineLearning, Learning Classifier System, Behaviors.

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Authors: J. K. Visser, H. T. Malan

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A need exists to identify the sources of risks associated with the process automation systems within petrochemical companies or similar energy related industries. These companies use many different process automation technologies in its value chain. A crucial part of the process automation system is the information technology component featuring in the supervisory control layer. The ever-changing technology within the process automation layers and the rate at which it advances pose a risk to safe and predictable automation system performance. The age of the automation equipment also provides challenges to the operations and maintenance managers of the plant due to obsolescence and unavailability of spare parts. The main objective of this research was to determine the risk sources associated with the equipment that is part of the process automation systems. A secondary objective was to establish whether technology managers and technicians were aware of the risks and share the same viewpoint on the importance of the risks associated with automation systems. A conceptual model for risk sources of automation systems was formulated from models and frameworks in literature. This model comprised six categories of risk which forms the basis for identifying specific risks. This model was used to develop a questionnaire that was sent to 172 instrument technicians and technology managers in the company to obtain primary data. 75 completed and useful responses were received. These responses were analyzed statistically to determine the highest risk sources and to determine whether there was difference in opinion between technology managers and technicians. The most important risks that were revealed in this study are: 1) the lack of skilled technicians, 2) integration capability of third-party system software, 3) reliability of the process automation hardware, 4) excessive costs pertaining to performing maintenance and migrations on process automation systems, and 5) requirements of having third-party communication interfacing compatibility as well as real-time communication networks.

Keywords: Distributed control system, identification of risks, information technology, process automation system.

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Authors: Romeo A. Botes, Imelda Smit

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The demands of an ever changing and complex higher education environment, along with the profile of modern learners challenge current approaches to assessment and feedback. More learners enter the education system every year. The younger generation expects immediate feedback. At the same time, feedback should be meaningful. The assessment of practical activities in programming poses a particular problem, since both lecturers and learners in the information and computer science discipline acknowledge that paper-based assessment for programming subjects lacks meaningful real-life testing. At the same time, feedback lacks promptness, consistency, comprehensiveness and individualisation. Most of these aspects may be addressed by modern, technology-assisted assessment. The focus of this paper is the continuous development of an artefact that is used to assist the lecturer in the assessment and feedback of practical programming activities in a senior database programming class. The artefact was developed using three Design Science Research cycles. The first implementation allowed one programming activity submission per assessment intervention. This pilot provided valuable insight into the obstacles regarding the implementation of this type of assessment tool. A second implementation improved the initial version to allow multiple programming activity submissions per assessment. The focus of this version is on providing scaffold feedback to the learner – allowing improvement with each subsequent submission. It also has a built-in capability to provide the lecturer with information regarding the key problem areas of each assessment intervention.

Keywords: Programming, computer-aided assessment, technology-assisted assessment, programming assessment software, design science research, mixed-method.

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Authors: F. Rashno Seydari, M. Nikafrooz

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This paper intends to study needs analysis of hearing-impaired students’ teachers in elementary schools all over Iran. The subjects of this study were 275 teachers who were teaching hearing-impaired students in elementary schools. The participants were selected by a quota sampling method. To collect the data, questionnaires of training needs consisting of 41 knowledge items and 31 performance items were used. The collected data were analyzed by using SPSS software in the form of descriptive analyses (frequency and mean) and inferential analyses (one sample t-test, paired t-test, independent t-test, and Pearson correlation coefficient). The findings of the study indicated that teachers generally have considerable needs in knowledge and performance domains. In 32 items out of the total 41 knowledge domain items and in the 27 items out of the total 31 performance domain items, the teachers had considerable needs. From the quantitative point of view, the needs of the performance domain were more than those of the knowledge domain, so they have to be considered as the first priority in training these teachers. There was no difference between the level of the needs of male and female teachers. There was a significant difference between the knowledge and performance domain needs and the teachers’ teaching experience, 0.354 and 0.322 respectively. The teachers who had been trained in working with hearing-impaired students expressed more training needs (both knowledge and performance).

Keywords: Needs analysis, hearing impaired students, hearing impaired students’ teachers, knowledge domain, performance domain.

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Authors: Igor Astrov, Andrus Pedai

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This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory for a nontrivial mid-small size AUV “r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of noises, and also can be concluded that the proposed research technique will be useful for fast SA of similar AUV systems in real-time search-and-rescue operations.

Keywords: Autonomous underwater vehicles, multirate systems, neurocontrollers, situational awareness.

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Authors: Kumar Manoj, Ramesh Kumar, Kumari Arti

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A wireless Ad-hoc network consists of wireless nodes communicating without the need for a centralized administration, in which all nodes potentially contribute to the routing process.In this paper, we report the simulation results of four different scenarios for wireless ad hoc networks having thirty nodes. The performances of proposed networks are evaluated in terms of number of hops per route, delay and throughput with the help of OPNET simulator. Channel speed 1 Mbps and simulation time 600 sim-seconds were taken for all scenarios. For the above analysis DSR routing protocols has been used. The throughput obtained from the above analysis (four scenario) are compared as shown in Figure 3. The average media access delay at node_20 for two routes and at node_20 for four different scenario are compared as shown in Figures 4 and 5. It is observed that the throughput will degrade when it will follow different hops for same source to destination (i.e. it has dropped from 1.55 Mbps to 1.43 Mbps which is around 9.7%, and then dropped to 0.48Mbps which is around 35%).

Keywords: Throughput, Delay, DSR, OPNET, MANET, DSSS

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Authors: Tomoaki Hashimoto

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Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the effectiveness of the obtained stability condition.

Keywords: Computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems.

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Authors: Mahmoud A. El-Banna

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The need to increase the efficiency of health care systems is becoming an obligation, and one of area of improvement is the discharge process. The objective of this work is to minimize the patients discharge time (for insured patients) to be less than 50 minutes by using six sigma approach, this improvement will also: lead to an increase in customer satisfaction, increase the number of admissions and turnover on the rooms, increase hospital profitability.Three different departments were considered in this study: Female, Male, and Paediatrics. Six Sigma approach coupled with simulation has been applied to reduce the patients discharge time for pediatrics, female, and male departments at hospital. Upon applying these recommendations at hospital: 60%, 80%, and 22% of insured female, male, and pediatrics patients respectively will have discharge time less than the upper specification time i.e. 50 min.

Keywords: Discharge Time, Healthcare, Hospitals, Patients, Process Improvement, Six Sigma, Simulation

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Authors: Kejun Zhuang, Zhaohui Wen

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This paper deals with a delayed single population model on time scales. With the assistance of coincidence degree theory, sufficient conditions for existence of periodic solutions are obtained. Furthermore, the better estimations for bounds of periodic solutions are established.

Keywords: Coincidence degree, continuation theorem, periodic solutions, time scales

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Authors: H. C. Chang, J. R. Wang, A. L. Ho, S. W. Chen, J. H. Yang, C. Shih, L. C. Wang

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To confirm the reactor and containment integrity of the Advanced Boiling Water Reactor (ABWR), we perform the analysis of main steamline break (MSLB) transient by using the TRACE, PARCS, and SNAP codes. The process of the research has four steps. First, the ABWR nuclear power plant (NPP) model is developed by using the above codes. Second, the steady state analysis is performed by using this model. Third, the ABWR model is used to run the analysis of MSLB transient. Fourth, the predictions of TRACE and PARCS are compared with the data of FSAR. The results of TRACE/PARCS and FSAR are similar. According to the TRACE/PARCS results, the reactor and containment integrity of ABWR can be maintained in a safe condition for MSLB.

Keywords: ABWR, TRACE, PARCS, SNAP.

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Authors: Richard W. Longman

Abstract:

Iterative learning control aims to achieve zero tracking error of a specific command. This is accomplished by iteratively adjusting the command given to a feedback control system, based on the tracking error observed in the previous iteration. One would like the iterations to converge to zero tracking error in spite of any error present in the model used to design the learning law. First, this need for stability robustness is discussed, and then the need for robustness of the property that the transients are well behaved. Methods of producing the needed robustness to parameter variations and to singular perturbations are presented. Then a method involving reverse time runs is given that lets the world behavior produce the ILC gains in such a way as to eliminate the need for a mathematical model. Since the real world is producing the gains, there is no issue of model error. Provided the world behaves linearly, the approach gives an ILC law with both stability robustness and good transient robustness, without the need to generate a model.

Keywords: Iterative learning control, stability robustness, monotonic convergence.

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