Search results for: employee periodical assessment system

Authors: Roshayani Arshad, Normah Omar, Siti Fatimah Awang

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The move from cash accounting to accrual accounting, or rule-based to principle-based accounting, by many governments is part of an ongoing efforts in promoting a more business-like and performance-focused public sector. Using questionnaire responses from preparers of financial statements of public universities in Malaysia, this study examines the implementation challenges and benefits of principle-based accounting. Results from these responses suggest that most respondents perceived significant costs would be incurred in relation to staff training and recruitment of staffs with relevant technical knowledge. In addition, most respondents also perceived that there will be significant changes in the current accounting system and structure in order to comply with the principle-based accounting requirements. However, most respondents perceived that these changes might not result in significant benefits for management purposes, for example, financial management, budgeting and allocation of resources. Nevertheless, most respondents perceived that principle-based accounting information would facilitate the monitoring function of the board. The general perception is that adoption of principle-based accounting information is not significantly useful than rule-based accounting information is expected to change over time as preparers of the financial statements gradually understand and appreciate the benefits of principle-based accounting information. This infers that the perceived usefulness of different accounting system is a function of familiarity by the preparers.

Keywords: Accrual accounting, principle-based accounting, public sector, rule-based accounting.

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Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

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The elastic period has a primary role in the seismic assessment of buildings. Reliable calculations and/or estimates of the fundamental frequency of a building and its site are essential during analysis and design process. Various code formulas based on empirical data are generally used to estimate the fundamental frequency of a structure. For existing structures, in addition to code formulas and available analytical tools such as modal analyses, various methods of testing including ambient and forced vibration testing procedures may be used to determine dynamic characteristics. In this study, the dynamic properties of the 32 buildings located in the Madinah of Saudi Arabia were identified using ambient motions recorded at several, spatially-distributed locations within each building. Ambient vibration measurements of buildings have been analyzed and the fundamental longitudinal and transverse periods for all tested buildings are presented. The fundamental mode of vibration has been compared in plots with codes formulae (Saudi Building Code, EC8, and UBC1997). The results indicate that measured periods of existing buildings are shorter than that given by most empirical code formulas. Recommendations are given based on the common design and construction practice in Madinah city.

Keywords: Ambient vibration, Fundamental period, RC buildings, Infill walls.

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Authors: B. Tah, P. Pal, M. Mahato, R. Sarkar, G. B. Talapatra

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Herein, we report the different types of surface morphology due to the interaction between the pure protein Insulin (INS) and catanionic surfactant mixture of Sodium Dodecyl Sulfate (SDS) and Cetyl Trimethyl Ammonium Bromide (CTAB) at air/water interface obtained by the Langmuir-Blodgett (LB) technique. We characterized the aggregations by Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) in LB films. We found that the INS adsorption increased in presence of catanionic surfactant at air/water interface. The presence of small amount of surfactant induces two-stage growth kinetics due to the pure protein absorption and protein-catanionic surface micelle interaction. The protein remains in native state in presence of small amount of surfactant mixture. Smaller amount of surfactant mixture with INS is producing surface micelle type structure. This may be considered for drug delivery system. On the other hand, INS becomes unfolded and fibrillated in presence of higher amount of surfactant mixture. In both the cases, the protein was successfully immobilized on a glass substrate by the LB technique. These results may find applications in the fundamental science of the physical chemistry of surfactant systems, as well as in the preparation of drug-delivery system.

Keywords: Air/water interface, Catanionic micelle, Insulin, Langmuir-Blodgett film

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Authors: Ahmed T. Alahmar

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There is an increasing trend toward student-centred interactive e-learning methods and students’ feedback is a valuable tool for improving learning methods. The aim of this study was to explore the attitude of second year pharmacy students at the University of Babylon, Iraq, towards lectures, exams and e-learning. Materials and methods: Ninety pharmacy students were surveyed by paper questionnaire about their preference for lecture format, use of e-files, theoretical lectures versus practical experiments, lecture and lab time. Students were also asked about their predilection for Moodle-based online exams, different types of exam questions, exam time and other extra academic activities. Results: Students prefer to read lectures on paper (73.3%), use of PowerPoint file (76.7%), short lectures of less than 10 pages (94.5%), practical experiments (66.7%), lectures and lab time of less than two hours (89.9% and 96.6 respectively) and intra-lecture discussions (68.9%). Students also like to have paper-based exam (73.3%), short essay (40%) or MCQ (34.4%) questions and also prefer to do extra activities like reports (22.2%), seminars (18.6%) and posters (10.8%). Conclusion: Second year pharmacy students have different attitudes toward traditional and electronic leaning and assessment methods. Using multimedia, e-learning and Moodle are increasingly preferred methods among some students.

Keywords: Pharmacy, students, lecture, exam, e-learning, Moodle.

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Authors: L. Parisi

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In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.

Keywords: Kinemic gait data, Neural networks, Hip joint implant, Hip arthroplasty, Rehabilitation Engineering.

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Authors: Hussein Alahmer, Amr Ahmed

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Liver cancer is one of the common diseases that cause the death. Early detection is important to diagnose and reduce the incidence of death. Improvements in medical imaging and image processing techniques have significantly enhanced interpretation of medical images. Computer-Aided Diagnosis (CAD) systems based on these techniques play a vital role in the early detection of liver disease and hence reduce liver cancer death rate.  This paper presents an automated CAD system consists of three stages; firstly, automatic liver segmentation and lesion’s detection. Secondly, extracting features. Finally, classifying liver lesions into benign and malignant by using the novel contrasting feature-difference approach. Several types of intensity, texture features are extracted from both; the lesion area and its surrounding normal liver tissue. The difference between the features of both areas is then used as the new lesion descriptors. Machine learning classifiers are then trained on the new descriptors to automatically classify liver lesions into benign or malignant. The experimental results show promising improvements. Moreover, the proposed approach can overcome the problems of varying ranges of intensity and textures between patients, demographics, and imaging devices and settings.

Keywords: CAD system, difference of feature, Fuzzy c means, Liver segmentation.

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Authors: Archana Panchapakesan Iyer, Taha Abdullah Kumosani

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Many high-risk pathogens that cause disease in humans are transmitted through various food items. Food-borne disease constitutes a major public health problem. Assessment of the quality and safety of foods is important in human health. Rapid and easy detection of pathogenic organisms will facilitate precautionary measures to maintain healthy food. The Polymerase Chain Reaction (PCR) is a handy tool for rapid detection of low numbers of bacteria. We have designed gene specific primers for most common food borne pathogens such as Staphylococci, Salmonella and E.coli. Bacteria were isolated from food samples of various food outlets and identified using gene specific PCRs. We identified Staphylococci, Salmonella and E.coli O157 using gene specific primers by rapid and direct PCR technique in various food samples. This study helps us in getting a complete picture of the various pathogens that threaten to cause and spread food borne diseases and it would also enable establishment of a routine procedure and methodology for rapid identification of food borne bacteria using the rapid technique of direct PCR. This study will also enable us to judge the efficiency of present food safety steps taken by food manufacturers and exporters.

Keywords: food borne pathogens, PCR, food safety, rapiddetection.

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Authors: Eisa Noveiri, Adel Taheri Nia

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The Non-Rotating Adjustable Stabilizer / Directional Solution (NAS/DS) is the imitation of a mechanical process or an object by a directional drilling operation that causes a respond mathematically and graphically to data and decision to choose the best conditions compared to the previous mode. The NAS/DS Auto Guide rotary steerable tool is undergoing final field trials. The point-the-bit tool can use any bit, work at any rotating speed, work with any MWD/LWD system, and there is no pressure drop through the tool. It is a fully closed-loop system that automatically maintains a specified curvature rate. The Non–Rotating Adjustable stabilizer (NAS) can be controls curvature rate by exactly positioning and run with the optimum bit, use the most effective weight (WOB) and rotary speed (RPM) and apply all of the available hydraulic energy to the bit. The directional simulator allowed to specify the size of the curvature rate performance errors of the NAS tool and the magnitude of the random errors in the survey measurements called the Directional Solution (DS). The combination of these technologies (NAS/DS) will provide smoother bore holes, reduced drilling time, reduced drilling cost and incredible targeting precision. This simulator controls curvature rate by precisely adjusting the radial extension of stabilizer blades on a near bit Non-Rotating Stabilizer and control process corrects for the secondary effects caused by formation characteristics, bit and tool wear, and manufacturing tolerances.

Keywords: non-rotating, Adjustable stabilizer, simulator, Directional Drilling, optimization, Oil Well Drilling

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Authors: Ekow A. Kwofie, Emmanuel K. Anto, Godfred Mensah

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In this paper, CYME Distribution software has been used to assess the impacts of solar Photovoltaic (PV) distributed generation (DG) plant on the Electricity Company of Ghana (ECG) 33 kV sub-transmission network at different PV penetration levels. As ECG begins to encourage DG PV interconnections within its network, there has been the need to assess the impacts on the sub-transmission losses and voltage contribution. In Tema, a city in Accra - Ghana, ECG has a 33 kV sub-transmission network made up of 20 No. 33 kV buses that was modeled. Three different locations were chosen: The source bus, a bus along the sub-transmission radial network and a bus at the tail end to determine the optimal location for DG PV interconnection. The optimal location was determined based on sub-transmission technical losses and voltage impact. PV capacities at different penetration levels were modeled at each location and simulations performed to determine the optimal PV penetration level. Interconnection at a bus along (or in the middle of) the sub-transmission network offered the highest benefits at an optimal PV penetration level of 80%. At that location, the maximum voltage improvement of 0.789% on the neighboring 33 kV buses and maximum loss reduction of 6.033% over the base case scenario were recorded. Hence, the optimal location for DG PV integration within the 33 kV sub-transmission utility network is at a bus along the sub-transmission radial network.

Keywords: Distributed generation photovoltaic, DG PV, optimal location, penetration level, sub-transmission network.

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Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka

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This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.

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Authors: Siham G. Farag

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The main objective of this paper is to provide a new methodology for road safety assessment in Oman through the development of suitable accident prediction models. GLM technique with Poisson or NBR using SAS package was carried out to develop these models. The paper utilized the accidents data of 31 un-signalized T-intersections during three years. Five goodness-of-fit measures were used to assess the overall quality of the developed models. Two types of models were developed separately; the flow-based models including only traffic exposure functions, and the full models containing both exposure functions and other significant geometry and traffic variables. The results show that, traffic exposure functions produced much better fit to the accident data. The most effective geometric variables were major-road mean speed, minor-road 85th percentile speed, major-road lane width, distance to the nearest junction, and right-turn curb radius. The developed models can be used for intersection treatment or upgrading and specify the appropriate design parameters of T-intersections. Finally, the models presented in this thesis reflect the intersection conditions in Oman and could represent the typical conditions in several countries in the middle east area, especially gulf countries.

Keywords: Accidents Prediction Models (APMs), Generalized Linear Model (GLM), T-intersections, Oman.

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Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

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This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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Authors: Mohammad Syuhaimi Ab-Rahman, Boonchuan Ng, Kasmiran Jumari

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This paper presented a MATLAB-based system named Smart Access Network Testing, Analyzing and Database (SANTAD), purposely for in-service transmission surveillance and self restoration against fiber fault in fiber-to-the-home (FTTH) access network. The developed program will be installed with optical line terminal (OLT) at central office (CO) to monitor the status and detect any fiber fault that occurs in FTTH downwardly from CO towards residential customer locations. SANTAD is interfaced with optical time domain reflectometer (OTDR) to accumulate every network testing result to be displayed on a single computer screen for further analysis. This program will identify and present the parameters of each optical fiber line such as the line's status either in working or nonworking condition, magnitude of decreasing at each point, failure location, and other details as shown in the OTDR's screen. The failure status will be delivered to field engineers for promptly actions, meanwhile the failure line will be diverted to protection line to ensure the traffic flow continuously. This approach has a bright prospect to improve the survivability and reliability as well as increase the efficiency and monitoring capabilities in FTTH.

Keywords: MATLAB, SANTAD, in-service transmission surveillance, self restoration, fiber fault, FTTH

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Authors: Mohamed Elshal, Hazim El-Mounayri, Omar El-Mounayri

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Emergency department (ED) is considered as a complex system of interacting entities: patients, human resources, software and hardware systems, interfaces, and other systems. This paper represents a research for implementing a detailed Systems Engineering (SE) approach in a mid-size hospital in central Indiana. This methodology will be applied by “The Initiative for Product Lifecycle Innovation (IPLI)” institution at Indiana University to study and solve the crowding problem with the aim of increasing throughput of patients and enhance their treatment experience; therefore, the nature of crowding problem needs to be investigated with all other problems that leads to it. The presented SE methods are workflow analysis and systems modeling where SE tools such as Microsoft Visio are used to construct a group of system-level diagrams that demonstrate: patient’s workflow, documentation and communication flow, data systems, human resources workflow and requirements, leadership involved, and integration between ER different systems. Finally, the ultimate goal will be managing the process through implementation of an executable model using commercialized software tools, which will identify bottlenecks, improve documentation flow, and help make the process faster.

Keywords: Systems modeling, ED operation, workflow modeling, systems analysis.

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Authors: Martin Doran, Roy Sterritt, George Wilkie

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NASA, ESA, and NSSC space agencies have plans to put planetary rovers on Mars in 2020. For these future planetary rovers to succeed, they will heavily depend on sensors to detect obstacles. This will also become of vital importance in the future, if rovers become less dependent on commands received from earth-based control and more dependent on self-configuration and self-decision making. These planetary rovers will face harsh environments and the possibility of hardware failure is high, as seen in missions from the past. In this paper, we focus on using Autonomic principles where self-healing, self-optimization, and self-adaption are explored using the MAPE-K model and expanding this model to encapsulate the attributes such as Awareness, Analysis, and Adjustment (AAA-3). In the experimentation, a Pioneer P3-DX research robot is used to simulate a planetary rover. The sonar sensors on the P3-DX robot are used to simulate the sensors on a planetary rover (even though in reality, sonar sensors cannot operate in a vacuum). Experiments using the P3-DX robot focus on how our software system can be adapted with the loss of sonar sensor functionality. The autonomic manager system is responsible for the decision making on how to make use of remaining ‘enabled’ sonars sensors to compensate for those sonar sensors that are ‘disabled’. The key to this research is that the robot can still detect objects even with reduced sonar sensor capability.

Keywords: Autonomic, self-adaption, self-healing, self-optimization.

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Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

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This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: Constructive alignment, constructivist theory, educational game, outcome-based education.

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Authors: Tarek M. Mahmoud

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Skin color can provide a useful and robust cue for human-related image analysis, such as face detection, pornographic image filtering, hand detection and tracking, people retrieval in databases and Internet, etc. The major problem of such kinds of skin color detection algorithms is that it is time consuming and hence cannot be applied to a real time system. To overcome this problem, we introduce a new fast technique for skin detection which can be applied in a real time system. In this technique, instead of testing each image pixel to label it as skin or non-skin (as in classic techniques), we skip a set of pixels. The reason of the skipping process is the high probability that neighbors of the skin color pixels are also skin pixels, especially in adult images and vise versa. The proposed method can rapidly detect skin and non-skin color pixels, which in turn dramatically reduce the CPU time required for the protection process. Since many fast detection techniques are based on image resizing, we apply our proposed pixel skipping technique with image resizing to obtain better results. The performance evaluation of the proposed skipping and hybrid techniques in terms of the measured CPU time is presented. Experimental results demonstrate that the proposed methods achieve better result than the relevant classic method.

Keywords: Adult images filtering, image resizing, skin color detection, YcbCr color space.

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Authors: Man Young Kim

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Catalytic combustion is generally accepted as an environmentally preferred alternative for the generation of heat and power from fossil fuels mainly due to its advantages related to the stable combustion under very lean conditions with low emissions of NOx, CO, and UHC at temperatures lower than those occurred in conventional flame combustion. Despite these advantages, the commercial application of catalytic combustion has been delayed because of complicated reaction processes and the difficulty in developing appropriate catalysts with the required stability and durability. To develop the catalytic combustors, detailed studies on the combustion characteristics of catalytic combustion should be conducted. To the end, in current research, quantitative studies on the combustion characteristics of the catalytic combustors, with a Pd-based catalyst for MCFC power generation systems, relying on numerical simulations have been conducted. In addition, data from experimental studies of variations in outlet temperatures and fuel conversion, taken after operating conditions have been used to validate the present numerical approach. After introducing the governing equations for mass, momentum, and energy equations as well as a description of catalytic combustion kinetics, the effects of the excess air ratio, space velocity, and inlet gas temperature on the catalytic combustion characteristics are extensively investigated. Quantitative comparisons are also conducted with previous experimental data. Finally, some concluding remarks are presented.

Keywords: Catalytic combustion, Methane, BOP, MCFC power generation system, Inlet temperature, Excess air ratio, Space velocity.

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Authors: Hyun-Koo Kim, Young-Nam Shin, Sa-gong Kuk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective traffic lights detection method at the night-time. First, candidate blobs of traffic lights are extracted from RGB color image. Input image is represented on the dominant color domain by using color transform proposed by Ruta, then red and green color dominant regions are selected as candidates. After candidate blob selection, we carry out shape filter for noise reduction using information of blobs such as length, area, area of boundary box, etc. A multi-class classifier based on SVM (Support Vector Machine) applies into the candidates. Three kinds of features are used. We use basic features such as blob width, height, center coordinate, area, area of blob. Bright based stochastic features are also used. In particular, geometric based moment-s values between candidate region and adjacent region are proposed and used to improve the detection performance. The proposed system is implemented on Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the urban and rural road videos. Through the test, we show that the proposed method using PF, BMF, and GMF reaches up to 93 % of detection rate with computation time of in average 15 ms/frame.

Keywords: Night-time traffic light detection, multi-class classification, driving assistance system.

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Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: Curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering.

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Authors: Xi Wang, Xiaoming Tao, Raymond C. H. So

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As one of the convenient and noninvasive sensing approaches, the automatic limb girth measurement has been applied to detect intention behind human motion from muscle deformation. The sensing validity has been elaborated by preliminary researches but still need more fundamental studies, especially on kinetic contraction modes. Based on the novel fabric strain sensors, a soft and smart limb girth measurement system was developed by the authors’ group, which can measure the limb girth in-motion. Experiments were carried out on elbow isometric flexion and elbow isokinetic flexion (biceps’ isokinetic contractions) of 90°/s, 60°/s, and 120°/s for 10 subjects (2 canoeists and 8 ordinary people). After removal of natural circumferential increments due to elbow position, the joint torque is found not uniformly sensitive to the limb circumferential strains, but declining as elbow joint angle rises, regardless of the angular speed. Moreover, the maximum joint torque was found as an exponential function of the joint’s angular speed. This research highly contributes to the application of the automatic limb girth measuring during kinetic contractions, and it is useful to predict the contraction level of voluntary skeletal muscles.

Keywords: Fabric strain sensor, muscle deformation, isokinetic contraction, joint torque, limb girth strain.

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Authors: P. S. Rajinikanth, Yeoh Suyu, Sanjay Garg

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The present study is aim to prepare and evaluate the selfnanoemulsifying drug delivery (SNEDDS) system of a poorly water soluble drug valsartan in order to achieve a better dissolution rate which would further help in enhancing oral bioavailability. The present research work describes a SNEDDS of valsartan using labrafil M 1944 CS, Tween 80 and Transcutol HP. The pseudoternary phase diagrams with presence and absence of drug were plotted to check for the emulsification range and also to evaluate the effect of valsartan on the emulsification behavior of the phases. The mixtures consisting of oil (labrafil M 1944 CS) with surfactant (tween 80), co-surfactant (Transcutol HP) were found to be optimum formulations. Prepared formulations were evaluated for its particle size distribution, nanoemulsifying properties, robustness to dilution, self emulsication time, turbidity measurement, drug content and invitro dissolution. The optimized formulations are further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential were carried out to confirm the stability of the formed SNEDDS formulations. The prepared formulation revealed t a significant improvement in terms of the drug solubility as compared with marketed tablet and pure drug.

Keywords: Self Emulsifying Drug Delivery System, Valsartan, Bioavailability, poorly soluble drug.

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Authors: Olayinka Gafar Okeola, Akinola Muyiwa Moore

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Urban population is rapidly increasing in Ilorin, (the capital of Kwara State of Nigeria) along with related increased water demand. The inadequacies of water supply services have forced the populace to depend on dug wells, boreholes, water tankers, street vendors etc. for their water needs. People spend hours daily carrying jerry can all around to collect and queue for water at the public water tap with high opportunity cost both in time and economic wastage. This situation motivated this study to assess the sustainability of an urban water supply services to unravel the factors undermining the effective delivery of services. Contingent Valuation Method was used to place value on water supply services using the Double Bounded Dichotomous Choice format for willingness to pay elicitation. A database was created with Microsoft Excel and Stata 12 Software to model and evaluate the variables that affect household willingness to pay. The results of the study reveal that about 92% of the total households surveyed were connected to the Government water supply out of which 87% reported that they were not satisfied with the existing services. The results furthered revealed that respondents are willing to pay ₦2500 monthly to enjoy sustainable water supply service delivery.

Keywords: Willingness-to-pay, contingent valuation method, Nigeria, service, delivery.

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Authors: Saeed Sedighizadeh, Abbas Mansoori, Mohammad Reza Pirestani, Davoud Sedighizadeh

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The usual method of river flow diversion involves construction of tunnels and cofferdams. Given the fact that the cost of diversion works could be as high as 10-20% of the total dam construction cost, due attention should be paid to optimum design of the diversion works. The cost of diversion works depends, on factors, such as: the tunnel dimensions and the intended tunneling support measures during and after excavation; quality and characterizes of the rock through which the tunnel should be excavated; the dimensions of the upstream (and downstream) cofferdams; and the magnitude of river flood the system is designed to divert. In this paper by use of the cost of unit prices for tunnel excavation, tunnel lining, tunnel support (rock bolt + shotcrete) and cofferdam fill the cost function was determined. The function is then minimized by the aid of PSO Algorithm (particle swarm optimization). It is found that the optimum diameter and the total diversion cost are directly related to the river flood discharge (Q). It has also shown that in addition to optimum diameter design discharge (Q), river length, tunnel length, is mainly a function of the ratios (not the absolute values) of the unit prices and does not depend on the overall price levels in the respective country. The results of optimization use in some of the case study lead us to significant changes in the cost.

Keywords: Diversion Tunnel, Optimization, PSO Algorithm

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Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji

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In wireless sensor networks, locality and positioning information can be captured using Global Positioning System (GPS). This message can be congregated initially from spot to identify the system. Users can retrieve information of interest from a wireless sensor network (WSN) by injecting queries and gathering results from the mobile sink nodes. Routing is the progression of choosing optimal path in a mobile network. Intermediate node employs permutation of device nodes into teams and generating cluster heads that gather the data from entity cluster’s node and encourage the collective data to base station. WSNs are widely used for gathering data. Since sensors are power-constrained devices, it is quite vital for them to reduce the power utilization. A tree-based data fusion clustering routing algorithm (TBDFC) is used to reduce energy consumption in wireless device networks. Here, the nodes in a tree use the cluster formation, whereas the elevation of the tree is decided based on the distance of the member nodes to the cluster-head. Network simulation shows that this scheme improves the power utilization by the nodes, and thus considerably improves the lifetime.

Keywords: WSN, TBDFC, LEACH, PEGASIS, TREEPSI.

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Authors: Sihao Lin, Bo Shen, Xuexiang Dai, Xuyan Xu, Zhenyi Wu, Xianzhe Zeng

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Infrared Thermography (IRT) has been little documented in the objective measurement of ergonomic exposure. We aimed to examine the association between different ergonomic exposures and low back skin temperature measured by IRT. A total of 114 subjects among sedentary students, sports students and cleaning workers were selected as different ergonomic exposure levels. Low back skin temperature was measured by IRT before and post ergonomic exposure. Ergonomic exposure was assessed by Quick Exposure Check (QEC) and quantitative scores were calculated on the low back. Multiple regressions were constructed to examine the possible associations between ergonomic risk exposures and the skin temperature over the low back. Compared to the two student groups, clean workers had significantly higher ergonomic exposure scores on the low back. The low back temperature variations were different among the three groups. The temperature decreased significantly among students with ergonomic exposure (P < 0.01), while it increased among cleaning workers. With adjustment of confounding, the post-exposure temperature and the temperature changes after exposure showed a significantly negative association with ergonomic exposure scores. For maximum temperature, one increasing ergonomic score decreased -0.23 °C (95% CI -0.37, -0.10) of temperature after ergonomic exposure over the low back. There was a significant association between ergonomic exposures and infrared thermal temperature over low back. IRT could be used as an objective assessment of ergonomic exposure on the low back.

Keywords: Ergonomic exposure, infrared thermography, musculoskeletal disorders, skin temperature, low back.

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Authors: Fouad Salha , X. Guillaud

Abstract:

Directional over current relays (DOCR) are commonly used in power system protection as a primary protection in distribution and sub-transmission electrical systems and as a secondary protection in transmission systems. Coordination of protective relays is necessary to obtain selective tripping. In this paper, an approach for efficiency reduction of DOCRs nonlinear optimum coordination (OC) is proposed. This was achieved by modifying the objective function and relaxing several constraints depending on the four constraints classification, non-valid, redundant, pre-obtained and valid constraints. According to this classification, the far end fault effect on the objective function and constraints, and in consequently on relay operating time, was studied. The study was carried out, firstly by taking into account the near-end and far-end faults in DOCRs coordination problem formulation; and then faults very close to the primary relays (nearend faults). The optimal coordination (OC) was achieved by simultaneously optimizing all variables (TDS and Ip) in nonlinear environment by using of Genetic algorithm nonlinear programming techniques. The results application of the above two approaches on 6-bus and 26-bus system verify that the far-end faults consideration on OC problem formulation don-t lose the optimality.

Keywords: Backup/Primary relay, Coordination time interval (CTI), directional over current relays, Genetic algorithm, time dial setting (TDS), pickup current setting (Ip), nonlinear programming.

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Authors: A. Tellaeche, X. P. Burgos-Artizzu, G. Pajares, A. Ribeiro

Abstract:

One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

Keywords: Fuzzy k-Means, Precision agriculture, SupportVectors Machines, Weed detection.

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Authors: Ashly Joseph, Jithu Paulose

Abstract:

The increased usage of cloud computing has revolutionized the IT landscape, but it has also raised new security concerns. DevSecOps emerged as a way for tackling these difficulties by integrating security into the software development process. However, the rising complexity and sophistication of cyber threats need more advanced solutions. This paper looks into the usage of artificial intelligence (AI) techniques in the DevSecOps framework to increase cloud security. This study uses quantitative and qualitative techniques to assess the usefulness of AI approaches such as machine learning, natural language processing, and deep learning in reducing security issues. This paper thoroughly examines the symbiotic relationship between AI and DevSecOps, concentrating on how AI may be seamlessly integrated into the continuous integration and continuous delivery (CI/CD) pipeline, automated security testing, and real-time monitoring methods. The findings emphasize AI's huge potential to improve threat detection, risk assessment, and incident response skills. Furthermore, the paper examines the implications and challenges of using AI in DevSecOps workflows, considering factors like as scalability, interpretability, and adaptability. This paper adds to a better understanding of AI's revolutionary role in cloud security and provides valuable insights for practitioners and scholars in the field.

Keywords: Cloud Security, DevSecOps, Artificial Intelligence, AI, Machine Learning, Natural Language Processing, NLP, cybersecurity, AI-driven Security.

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Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

Abstract:

In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: Prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy.

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