Search results for: sensor voltage output

Authors: Van Chung Nguyen

Abstract:

The purpose of this research is to study the current status of the value chain for fish distribution at Quang Binh Fishing Port with 360 research samples, in which the research subjects are fishermen, traders, retailers, and businesses. The research uses the approach of applying the value chain theoretical framework of Kaplinsky and Morris to quantify and describe market channels and actors participating in the value chain and analyze the value-added process of these companies according to market channels. The analysis results show that fishermen directly catch fish with high economic efficiency, but processing enterprises and, especially retailers, are the agents to obtain higher added value. Processing enterprises play a role that is not really clear due to outdated processing technology; in contrast, retailers have the highest added value. This shows that the added value of the fish supply chain at Quang Binh fishing port is still limited, leading to low output quality. Therefore, the selling price of fish to the market is still high compared to the abundant fish resources, leading to low consumption and limiting exports due to the quality of processing enterprises. This reduces demand and fishing capacity, and productivity is lower than potential. To improve the fish value chain at fishing ports, it is necessary to focus on improving product quality, strengthening linkages between actors, building brands and product consumption markets at the same time, improving the capacity of export processing enterprises.

Keywords: Quang Binh fishing port, value chain, fish market, distributions channel.

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Authors: Adeniyi G. Adeogun, Bolaji F. Sule, Adebayo W. Salami, Michael O. Daramola

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Estimation of water yield and water balance in a river catchment is critical to the sustainable management of water resources at watershed level in any country. Therefore, in the present study, Soil and Water Assessment Tool (SWAT) interfaced with Geographical Information System (GIS) was applied as a tool to predict water balance and water yield of a catchment area in Nigeria. The catchment area, which was 12,992km², is located upstream Jebba hydropower dam in North central part of Nigeria. In this study, data on the observed flow were collected and compared with simulated flow using SWAT. The correlation between the two data sets was evaluated using statistical measures, such as, Nasch-Sucliffe Efficiency (NSE) and coefficient of determination (R²). The model output shows a good agreement between the observed flow and simulated flow as indicated by NSE and R², which were greater than 0.7 for both calibration and validation period. A total of 42,733 mm of water was predicted by the calibrated model as the water yield potential of the basin for a simulation period between 1985 to 2010. This interesting performance obtained with SWAT model suggests that SWAT model could be a promising tool to predict water balance and water yield in sustainable management of water resources. In addition, SWAT could be applied to other water resources in other basins in Nigeria as a decision support tool for sustainable water management in Nigeria.

Keywords: GIS, Modeling, Sensitivity Analysis, SWAT, Water Yield, Watershed level.

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: Computer-aided system, detection, image segmentation, morphology.

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Authors: José Alberto García Fernández, Zhimin Du, Xinqiao Jin

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Nowadays, data center industry faces strong challenges for increasing the speed and data processing capacities while at the same time is trying to keep their devices a suitable working temperature without penalizing that capacity. Consequently, the cooling systems of this kind of facilities use a large amount of energy to dissipate the heat generated inside the servers, and developing new cooling techniques or perfecting those already existing would be a great advance in this type of industry. The installation of a temperature sensor matrix distributed in the structure of each server would provide the necessary information for collecting the required data for obtaining a temperature profile instantly inside them. However, the number of temperature probes required to obtain the temperature profiles with sufficient accuracy is very high and expensive. Therefore, other less intrusive techniques are employed where each point that characterizes the server temperature profile is obtained by solving differential equations through simulation methods, simplifying data collection techniques but increasing the time to obtain results. In order to reduce these calculation times, complicated and slow computational fluid dynamics simulations are replaced by simpler and faster finite element method simulations which solve the Burgers‘ equations by backward, forward and central discretization techniques after simplifying the energy and enthalpy conservation differential equations. The discretization methods employed for solving the first and second order derivatives of the obtained Burgers‘ equation after these simplifications are the key for obtaining results with greater or lesser accuracy regardless of the characteristic truncation error.

Keywords: Burgers’ equations, CFD simulation, data center, discretization methods, FEM simulation, temperature profile.

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Authors: Meaghan Bowman

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Microblogging has become increasingly popular for commenting on current events, spreading gossip, and encouraging individualism--which favors its low-context communication channel. These social media (SM) platforms allow users to express opinions while interacting with a wide range of populations. Hashtags allow immediate identification of like-minded individuals worldwide on a vast array of topics. The output of the analytic tool, Linguistic Inquiry and Word Count (LIWC)--a program that associates psychological meaning with the frequency of use of specific words--may suggest the nature of individuals’ internal states and general sentiments. When applied to groupings of SM posts unified by a hashtag, such information can be helpful to community leaders during periods in which the forming of public opinion happens in parallel with the unfolding of political, economic, or social events. This is especially true when outcomes stand to impact the well-being of the group. Here, we applied the online tools, Google Translate and the University of Texas’s LIWC, to a 90-posting sample from a corpus of Colombian Spanish microblogs. On translated disjoint sets, identified by hashtag as being authored by advocates of voting “No,” advocates voting “Yes,” and entities refraining from hashtag use, we observed the value of LIWC’s Tone feature as distinguishing among the categories and the word “peace,” as carrying particular significance, due to its frequency of use in the data.

Keywords: Colombia peace referendum, FARC, hashtags, linguistics, microblogging, social media.

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Authors: Aini Hussain, M A Hannan, Azah Mohamed, Hilmi Sanusi, Burhanuddin Yeop Majlis

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Airbag deployment has been known to be responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decisions. Therefore, the authorities and industries have been looking for more innovative and intelligent products to be realized for future enhancements in the vehicle safety systems (VSSs). Although the VSSs technologies have advanced considerably, they still face challenges such as how to avoid unnecessary and untimely airbag deployments that can be hazardous and fatal. Currently, most of the existing airbag systems deploy without regard to occupant size and position. As such, this paper will focus on the occupant and crash sensing performances due to frontal collisions for the new breed of so called smart airbag systems. It intends to provide a thorough discussion relating to the occupancy detection, occupant size classification, occupant off-position detection to determine safe distance zone for airbag deployment, crash-severity analysis and airbag decision algorithms via a computer modeling. The proposed system model consists of three main modules namely, occupant sensing, crash severity analysis and decision fusion. The occupant sensing system module utilizes the weight sensor to determine occupancy, classify the occupant size, and determine occupant off-position condition to compute safe distance for airbag deployment. The crash severity analysis module is used to generate relevant information pertinent to airbag deployment decision. Outputs from these two modules are fused to the decision module for correct and efficient airbag deployment action. Computer modeling work is carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes.

Keywords: Crash severity analysis, occupant size classification, smart airbag, vehicle safety system.

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Authors: Roman Ružarovský, Radovan Holubek, Daynier Rolando Delgado Sobrino

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Currently is characterized production engineering together with the integration of industrial automation and robotics such very quick view of to manufacture the products. The production range is continuously changing, expanding and producers have to be flexible in this regard. It means that need to offer production possibilities, which can respond to the quick change. Engineering product development is focused on supporting CAD software, such systems are mainly used for product design. That manufacturers are competitive, it should be kept procured machines made available capable of responding to output flexibility. In response to that problem is the development of flexible manufacturing systems, consisting of various automated systems. The integration of flexible manufacturing systems and subunits together with product design and of engineering is a possible solution for this issue. Integration is possible through the implementation of CIM systems. Such a solution and finding a hyphen between CAD and procurement system ICIM 3000 from Festo Co. is engaged in the research project and this contribution. This can be designed the products in CAD systems and watch the manufacturing process from order to shipping by the development of methods and processes of integration, This can be modeled in CAD systems products and watch the manufacturing process from order to shipping to develop methods and processes of integration, which will improve support for product design parameters by monitoring of the production process, by creating of programs for production using the CAD and therefore accelerates the a total of process from design to implementation.

Keywords: CAD- Computer Aided Design, CAM- Computer Aided Manufacturing, CIM- Computer integrated manufacturing, iCIM 3000, integration, direct production from CAD.

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Authors: A. Rifa’i, Y. Takeshita, M. Komatsu

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After Yogyakarta earthquake in 2006, the main problem that occurred in the first yard of Prambanan Temple is ponding area that occurred after rainfall. Soil characterization needs to be determined by conducting several processes, especially permeability coefficient (k) in both saturated and unsaturated conditions to solve this problem. More accurate and efficient field testing procedure is required to obtain permeability data that present the field condition. One of the field permeability test equipment is Constant Discharge procedure to determine the permeability coefficient. Necessary adjustments of the Constant Discharge procedure are needed to be determined especially the value of geometric factor (F) to improve the corresponding value of permeability coefficient. The value of k will be correlated with the value of volumetric water content (θ) of an unsaturated condition until saturated condition. The principle procedure of Constant Discharge model provides a constant flow in permeameter tube that flows into the ground until the water level in the tube becomes constant. Constant water level in the tube is highly dependent on the tube dimension. Every tube dimension has a shape factor called the geometric factor that affects the result of the test. Geometric factor value is defined as the characteristic of shape and radius of the tube. This research has modified the geometric factor parameters by using empty material tube method so that the geometric factor will change. Saturation level is monitored by using soil moisture sensor. The field test results were compared with the results of laboratory tests to validate the results of the test. Field and laboratory test results of empty tube material method have an average difference of 3.33 x 10^-4 cm/sec. The test results showed that modified geometric factor provides more accurate data. The improved methods of constant discharge procedure provide more relevant results.

Keywords: Constant discharge, geometric factor, permeability coefficient, unsaturated soils.

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: Structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm.

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Authors: Nishi Bhuvandas, P. V. Timbadiya, P. L. Patel, P. D. Porey

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Recent perceived climate variability raises concerns with unprecedented hydrological phenomena and extremes. Distribution and circulation of the waters of the Earth become increasingly difficult to determine because of additional uncertainty related to anthropogenic emissions. The world wide observed changes in the large-scale hydrological cycle have been related to an increase in the observed temperature over several decades. Although the effect of change in climate on hydrology provides a general picture of possible hydrological global change, new tools and frameworks for modelling hydrological series with nonstationary characteristics at finer scales, are required for assessing climate change impacts. Of the downscaling techniques, dynamic downscaling is usually based on the use of Regional Climate Models (RCMs), which generate finer resolution output based on atmospheric physics over a region using General Circulation Model (GCM) fields as boundary conditions. However, RCMs are not expected to capture the observed spatial precipitation extremes at a fine cell scale or at a basin scale. Statistical downscaling derives a statistical or empirical relationship between the variables simulated by the GCMs, called predictors, and station-scale hydrologic variables, called predictands. The main focus of the paper is on the need for using statistical downscaling techniques for projection of local hydrometeorological variables under climate change scenarios. The projections can be then served as a means of input source to various hydrologic models to obtain streamflow, evapotranspiration, soil moisture and other hydrological variables of interest.

Keywords: Climate Change, Downscaling, GCM, RCM.

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Authors: Yuri Boiko, Ci Lin, Iluju Kiringa, Tet Yeap

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The performance of a permanent magnet brushless direct current (BLDC) motor controlled by the Kalman filter based position-sensorless drive is studied in terms of its dependence from the system’s parameters variations. The effects of the system’s parameters changes on the dynamic behavior of state variables are verified. Simulated is the closed loop control scheme with Kalman filter in the feedback line. Distinguished are two separate data sampling modes in analyzing feedback output from the BLDC motor: (1) equal angular separation and (2) equal time intervals. In case (1), the data are collected via equal intervals  of rotor’s angular position i, i.e. keeping  = const. In case (2), the data collection time points ti are separated by equal sampling time intervals t = const. Demonstrated are the effects of the parameters changes on the sensorless control flow, in particular, reduction of the instability torque ripples, switching spikes, and torque load balancing. It is specifically shown that an efficient suppression of commutation induced instability torque ripples is an achievable selection of the sampling rate in the Kalman filter settings above a certain critical value. The computational cost of such suppression is shown to be higher for the motors with lower induction values of the windings.

Keywords: BLDC motor, Kalman filter, sensorless drive, state variables, instability torque ripples reduction, sampling rate.

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Authors: Siqing Chen

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Megalopolis is a group of densely populated metropolitan areas that combine to form an urban complex. Since China introduced the economic reforms in late 1970s, the Chinese urban system has experienced unprecedented growth. The process of urbanisation prevailed in the 1980s, and the process of predominantly large city growth appeared to continue through 1990s and 2000s. In this study, the magnitude and pattern of urbanisation in China during 1990s were examined using remotely sensed imagery acquired by TM/ETM+ sensor onboard the Landsat satellites. The development of megalopolis areas in China was also studied based on the GIS analysis of the increases of urban and built-up area from 1990 to 2000. The analysis suggests that in the traditional agricultural zones in China, e.g., Huang-Huai-Hai Plains, Changjiang River Delta, Pearl River Delta and Sichuan Basin, the urban and built-up areas increased by 1.76 million hectares, of which 0.82 million hectares are expansion of urban areas, an increase of 24.78% compared with 1990 at the national scale. The Yellow River Delta, Changjiang River Delta and Pearl River Delta also saw an increase of urban and built-up area by 63.9%, 66.2% and 83.0% respectively. As a result, three major megalopolises were developed in China: the Guangzhou-Shenzhen-Hong Kong- Macau (Pearl River Delta: PRD) megalopolis area, the Shanghai- Nanjing-Hangzhou (Changjiang River Delta: CRD) megalopolis area and the Beijing-Tianjing-Tangshan-Qinhuangdao (Yellow River Delta-Bohai Sea Ring: YRD) megalopolis area. The relationship between the processed of megalopolisation and the inter-provincial population flow was also explored in the context of social-economic and transport infrastructure development in Post-reform China.

Keywords: Megalopolisation, Land use change, Spatial analysis, Post-reform China

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Authors: Amon Tunwannarux, Supanunt Tunwannarux

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This paper presents design features of a rescue robot, named CEO Mission II. Its body is designed to be the track wheel type with double front flippers for climbing over the collapse and the rough terrain. With 125 cm. long, 5-joint mechanical arm installed on the robot body, it is deployed not only for surveillance from the top view but also easier and faster access to the victims to get their vital signs. Two cameras and sensors for searching vital signs are set up at the tip of the multi-joint mechanical arm. The third camera is at the back of the robot for driving control. Hardware and software of the system, which controls and monitors the rescue robot, are explained. The control system is used for controlling the robot locomotion, the 5-joint mechanical arm, and for turning on/off devices. The monitoring system gathers all information from 7 distance sensors, IR temperature sensors, 3 CCD cameras, voice sensor, robot wheels encoders, yawn/pitch/roll angle sensors, laser range finder and 8 spare A/D inputs. All sensors and controlling data are communicated with a remote control station via IEEE 802.11b Wi-Fi. The audio and video data are compressed and sent via another IEEE 802.11g Wi-Fi transmitter for getting real-time response. At remote control station site, the robot locomotion and the mechanical arm are controlled by joystick. Moreover, the user-friendly GUI control program is developed based on the clicking and dragging method to easily control the movement of the arm. Robot traveling map is plotted from computing the information of wheel encoders and the yawn/pitch data. 2D Obstacle map is plotted from data of the laser range finder. The concept and design of this robot can be adapted to suit many other applications. As the Best Technique awardee from Thailand Rescue Robot Championship 2006, all testing results are satisfied.

Keywords: Controlling, monitoring, rescue robot, mechanicalarm.

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Authors: Yongquan Zhao, Bo Huang

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Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: Hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation.

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Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant Kumar Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986 and 0.9214 respectively at HHpolarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373 and 0.9428 respectively.

Keywords: Bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE.

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Authors: Y. V. Kim

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This article presents an approach with regards to the Functional Testing of Space System (SS) that could be a space vehicle (spacecraft-S/C) and/or its equipment and components – S/C subsystems. This test should finalize the Space Qualification Tests (SQT) campaign. It could be considered as a generic test and used for a wide class of SS that, from the point of view of System Dynamics and Control Theory, may be described by the ordinary differential equations. The suggested methodology is based on using semi-natural experiment laboratory stand that does not require complicated, precise and expensive technological control-verification equipment. However, it allows for testing totally assembled system during Assembling, Integration and Testing (AIT) activities at the final phase of SQT, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data are then inserted in a laboratory computer, where it is post-experiment processed by the MATLAB/Simulink Identification Toolbox. It allows for estimating the system dynamics in the form of estimation of its differential equation coefficients through the verification experimental test and comparing them with expected mathematical model, prematurely verified by mathematical simulation during the design process. Mathematical simulation results presented in the article show that this approach could be applicable and helpful in SQT practice. Further semi-natural experiments should specify detail requirements for the test laboratory equipment and test-procedures.

Keywords: system dynamics, space system ground tests, space qualification, system dynamics identification, satellite attitude control, assembling integration and testing

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Authors: Kamand Bagherian, Nariman Niknejad

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A vibration isolation technology for precise position control of a rotary system powered by two permanent magnet DC (PMDC) motors is proposed, where this system is mounted on an oscillatory frame. To achieve vibration isolation for this system, active damping and disturbance rejection (ADDR) technology is presented which introduces a cooperation of a main and an auxiliary PMDC, controlled by discrete-time sliding mode control (DTSMC) based schemes. The controller of the main actuator tracks a desired position and the auxiliary actuator simultaneously isolates the induced vibration, as its controller follows a torque trend. To determine this torque trend, a combination of two algorithms is introduced by the ADDR technology. The first torque-trend producing algorithm rejects the disturbance by counteracting the perturbation, estimated using a model-based observer. The second torque trend applies active variable damping to minimize the oscillation of the output shaft. In this practice, the presented technology is implemented on a rotary system with a pendulum attached, mounted on a linear actuator simulating an oscillation-transmitting structure. In addition, the obtained results illustrate the functionality of the proposed technology.

Keywords: Vibration isolation, position control, discrete-time nonlinear controller, active damping, disturbance tracking algorithm, oscillation transmitting support, stability robustness.

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Authors: Achela K. Fernando, Xiujuan Zhang, Peter F. Kinley

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A feed-forward, back-propagation Artificial Neural Network (ANN) model has been used to forecast the occurrences of wastewater overflows in a combined sewerage reticulation system. This approach was tested to evaluate its applicability as a method alternative to the common practice of developing a complete conceptual, mathematical hydrological-hydraulic model for the sewerage system to enable such forecasts. The ANN approach obviates the need for a-priori understanding and representation of the underlying hydrological hydraulic phenomena in mathematical terms but enables learning the characteristics of a sewer overflow from the historical data. The performance of the standard feed-forward, back-propagation of error algorithm was enhanced by a modified data normalizing technique that enabled the ANN model to extrapolate into the territory that was unseen by the training data. The algorithm and the data normalizing method are presented along with the ANN model output results that indicate a good accuracy in the forecasted sewer overflow rates. However, it was revealed that the accurate forecasting of the overflow rates are heavily dependent on the availability of a real-time flow monitoring at the overflow structure to provide antecedent flow rate data. The ability of the ANN to forecast the overflow rates without the antecedent flow rates (as is the case with traditional conceptual reticulation models) was found to be quite poor.

Keywords: Artificial Neural Networks, Back-propagationlearning, Combined sewer overflows, Forecasting.

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Authors: Meng Fanchao, Zhan Dechen, Xu Xiaofei

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Software reuse can be considered as the most realistic and promising way to improve software engineering productivity and quality. Automated assistance for software reuse involves the representation, classification, retrieval and adaptation of components. The representation and retrieval of components are important to software reuse in Component-Based on Software Development (CBSD). However, current industrial component models mainly focus on the implement techniques and ignore the semantic information about component, so it is difficult to retrieve the components that satisfy user-s requirements. This paper presents a method of business component retrieval based on specification matching to solve the software reuse of enterprise information system. First, a business component model oriented reuse is proposed. In our model, the business data type is represented as sign data type based on XML, which can express the variable business data type that can describe the variety of business operations. Based on this model, we propose specification match relationships in two levels: business operation level and business component level. In business operation level, we use input business data types, output business data types and the taxonomy of business operations evaluate the similarity between business operations. In the business component level, we propose five specification matches between business components. To retrieval reusable business components, we propose the measure of similarity degrees to calculate the similarities between business components. Finally, a business component retrieval command like SQL is proposed to help user to retrieve approximate business components from component repository.

Keywords: Business component, business operation, business data type, specification matching.

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Authors: M. L. Arias, J. D’Adamo, M. N. Novosad, P. A. Raffo, H. P. Burbridge, G. O. Artana

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Shale oils are highly paraffinic and, consequently, can create wax deposits that foul pipelines during transportation. Several factors must be considered when designing pipelines or treatment programs that prevent wax deposition: including chemical species in crude oils, flowrates, pipes diameters and temperature. This paper describes the wax deposition study carried out within the framework of YPF Tecnolgía S.A. (Y-TEC) flow assurance projects, as part of the process to achieve a better understanding on wax deposition issues. Laboratory experiments were performed on a medium size, 1 inch diameter, wax deposition loop of 15 meters long equipped with a solid detector system, online microscope to visualize crystals, temperature, and pressure sensors along the loop pipe. A baseline test was performed with diesel with no added paraffin or additive content. Tests were undertaken with different temperatures of circulating and cooling fluid at different flow conditions. Then, a solution formed with a paraffin incorporated to the diesel was considered. Tests varying flowrate and cooling rate were again run. Viscosity, density, WAT (Wax Appearance Temperature) with DSC (Differential Scanning Calorimetry), pour point and cold finger measurements were carried out to determine physical properties of the working fluids. The results obtained in the loop were analyzed through momentum balance and heat transfer models. To determine possible paraffin deposition scenarios temperature and pressure loop output signals were studied. They were compared with WAT static laboratory methods.

Keywords: Paraffin deposition, wax, oil pipelines, experimental pipe loop.

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the elearning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery.

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Authors: Roberto Sabatini, Terry Moore, Chris Hill

Abstract:

This paper presents a novel Global Navigation Satellite System (GNSS) Avionics Based Integrity Augmentation (ABIA) system architecture suitable for civil and military air platforms, including Unmanned Aircraft Systems (UAS). Taking the move from previous research on high-accuracy Differential GNSS (DGNSS) systems design, integration and experimental flight test activities conducted at the Italian Air Force Flight Test Centre (CSV-RSV), our research focused on the development of a novel approach to the problem of GNSS ABIA for mission- and safety-critical air vehicle applications and for multi-sensor avionics architectures based on GNSS. Detailed mathematical models were developed to describe the main causes of GNSS signal outages and degradation in flight, namely: antenna obscuration, multipath, fading due to adverse geometry and Doppler shift. Adopting these models in association with suitable integrity thresholds and guidance algorithms, the ABIA system is able to generate integrity cautions (predictive flags) and warnings (reactive flags), as well as providing steering information to the pilot and electronic commands to the aircraft/UAS flight control systems. These features allow real-time avoidance of safety-critical flight conditions and fast recovery of the required navigation performance in case of GNSS data losses. In other words, this novel ABIA system addresses all three cornerstones of GNSS integrity augmentation in mission- and safety-critical applications: prediction (caution flags), reaction (warning flags) and correction (alternate flight path computation).

Keywords: Global Navigation Satellite Systems (GNSS), Integrity Augmentation, Unmanned Aircraft Systems, Aircraft Based Augmentation, Avionics Based Integrity Augmentation, Safety-Critical Applications.

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Authors: Ogunduyile O. Oluwgbenga

Abstract:

Recent advancements in sensor technologies and Wireless Body Area Networks (WBANs) have led to the development of cost-effective healthcare devices which can be used to monitor and analyse a person-s physiological parameters from remote locations. These advancements provides a unique opportunity to overcome current healthcare challenges of low quality service provisioning, lack of easy accessibility to service varieties, high costs of services and increasing population of the elderly experienced globally. This paper reports on a prototype implementation of an architecture that seamlessly integrates Wireless Body Area Network (WBAN) with Web services (WS) to proactively collect physiological data of remote patients to recommend diagnostic services. Technologies based upon WBAN and WS can provide ubiquitous accessibility to a variety of services by allowing distributed healthcare resources to be massively reused to provide cost-effective services without individuals physically moving to the locations of those resources. In addition, these technologies can reduce costs of healthcare services by allowing individuals to access services to support their healthcare. The prototype uses WBAN body sensors implemented on arduino fio platforms to be worn by the patient and an android smart phone as a personal server. The physiological data are collected and uploaded through GPRS/internet to the Medical Health Server (MHS) to be analysed. The prototype monitors the activities, location and physiological parameters such as SpO2 and Heart Rate of the elderly and patients in rehabilitation. Medical practitioners would have real time access to the uploaded information through a web application.

Keywords: Android Smart phone, Arduino Fio, Web application server, Wireless Body Area Networks.

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Authors: Catherine A. Todd, Fazel Naghdy

Abstract:

In this work a surgical simulator is produced which enables a training otologist to conduct a virtual, real-time prosthetic insertion. The simulator provides the Ear, Nose and Throat surgeon with real-time visual and haptic responses during virtual cochlear implantation into a 3D model of the human Scala Tympani (ST). The parametric model is derived from measured data as published in the literature and accounts for human morphological variance, such as differences in cochlear shape, enabling patient-specific pre- operative assessment. Haptic modeling techniques use real physical data and insertion force measurements, to develop a force model which mimics the physical behavior of an implant as it collides with the ST walls during an insertion. Output force profiles are acquired from the insertion studies conducted in the work, to validate the haptic model. The simulator provides the user with real-time, quantitative insertion force information and associated electrode position as user inserts the virtual implant into the ST model. The information provided by this study may also be of use to implant manufacturers for design enhancements as well as for training specialists in optimal force administration, using the simulator. The paper reports on the methods for anatomical modeling and haptic algorithm development, with focus on simulator design, development, optimization and validation. The techniques may be transferrable to other medical applications that involve prosthetic device insertions where user vision is obstructed.

Keywords: Haptic modeling, medical device insertion, real-time visualization of prosthetic implantation, surgical simulation.

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Authors: Navdeep Goel, Salvador Gabarda

Abstract:

Digital images are widely used in computer applications. To store or transmit the uncompressed images requires considerable storage capacity and transmission bandwidth. Image compression is a means to perform transmission or storage of visual data in the most economical way. This paper explains about how images can be encoded to be transmitted in a multiplexing time-frequency domain channel. Multiplexing involves packing signals together whose representations are compact in the working domain. In order to optimize transmission resources each 4 × 4 pixel block of the image is transformed by a suitable polynomial approximation, into a minimal number of coefficients. Less than 4 × 4 coefficients in one block spares a significant amount of transmitted information, but some information is lost. Different approximations for image transformation have been evaluated as polynomial representation (Vandermonde matrix), least squares + gradient descent, 1-D Chebyshev polynomials, 2-D Chebyshev polynomials or singular value decomposition (SVD). Results have been compared in terms of nominal compression rate (NCR), compression ratio (CR) and peak signal-to-noise ratio (PSNR) in order to minimize the error function defined as the difference between the original pixel gray levels and the approximated polynomial output. Polynomial coefficients have been later encoded and handled for generating chirps in a target rate of about two chirps per 4 × 4 pixel block and then submitted to a transmission multiplexing operation in the time-frequency domain.

Keywords: Chirp signals, Image multiplexing, Image transformation, Linear canonical transform, Polynomial approximation.

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Authors: Chia-Chih Wei, Yun-Qi Li, Ssu-Ying Chen, Hsuan-Jung Chen, Hsi-Wen Yang, Chih-Yuan Chen, Chien-Chon Chen

Abstract:

In this paper, we used a high-quality anodization technique to make a colored wind chime with a nano-tube structure anodic film, which controls the length-to-diameter ratio of an aluminum rod and controls the oxide film structure on the surface of the aluminum rod by an anodizing method. The research experiment used hard anodization to grow a controllable thickness of anodic film on an aluminum alloy surface. The hard anodization film has high hardness, high insulation, high-temperature resistance, good corrosion resistance, colors, and mass production properties that can be further applied to transportation, electronic products, biomedical fields, or energy industry applications. This study also provides in-depth research and a detailed discussion of the related process of aluminum alloy surface hard anodizing, including pre-anodization, anodization, and post-anodization. The experiment parameters of anodization include using a mixed acid solution of sulfuric acid and oxalic acid as an anodization electrolyte and controlling the temperature, time, current density, and final voltage to obtain the anodic film. In the results of the experiments, the properties of the anodic film, including thickness, hardness, insulation, and corrosion characteristics, the microstructure of the anode film were measured, and the hard anodization efficiency was calculated. Thereby it can obtain different transmission speeds of sound in the aluminum rod. And, different audio sounds can present on the aluminum rod. Another feature of the present experiment result is the use of the anodizing method and dyeing method, laser engraving patterning and electrophoresis method to make good-quality colored aluminum wind chimes.

Keywords: Anodization, aluminum, wind chime, nano-tube.

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Authors: Muhammad Rehan Khalid, Muhammad Haroon Siddiqui, Danish Ilyas

Abstract:

This paper explores the implementation of adaptive coding and modulation schemes for Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) feedback systems. Adaptive coding and modulation enables robust and spectrally-efficient transmission over time-varying channels. The basic premise is to estimate the channel at the receiver and feed this estimate back to the transmitter, so that the transmission scheme can be adapted relative to the channel characteristics. Two types of codebook based channel feedback techniques are used in this work. The longterm and short-term CSI at the transmitter is used for efficient channel utilization. OFDM is a powerful technique employed in communication systems suffering from frequency selectivity. Combined with multiple antennas at the transmitter and receiver, OFDM proves to be robust against delay spread. Moreover, it leads to significant data rates with improved bit error performance over links having only a single antenna at both the transmitter and receiver. The coded modulation increases the effective transmit power relative to uncoded variablerate variable-power MQAM performance for MIMO-OFDM feedback system. Hence proposed arrangement becomes an attractive approach to achieve enhanced spectral efficiency and improved error rate performance for next generation high speed wireless communication systems.

Keywords: Adaptive Coded Modulation, MQAM, MIMO, OFDM, Codebooks, Feedback.

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Authors: Yanping Liao, Congcong He, Ruigang Zhao

Abstract:

The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: Constraint parameters, derivative matrix, magnetocardiography, regular term, total variation.

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Authors: Y. Abdelrazig, R. Moses

Abstract:

Roadway planning and design is a very complex process involving five key phases before a project is completed; planning, project development, final design, right-of-way, and construction. The planning phase for a new roadway transportation project is a very critical phase as it greatly affects all latter phases of the project. A location study is usually performed during the preliminary planning phase in a new roadway project. The objective of the location study is to develop alignment alternatives that are cost efficient considering land acquisition and construction costs. This paper describes a methodology to develop optimal preliminary roadway alignments utilizing spatial-data. Four optimization criteria are taken into consideration; roadway length, land cost, land slope, and environmental impacts. The basic concept of the methodology is to convert the proposed project area into a grid, which represents the search space for an optimal alignment. The aforementioned optimization criteria are represented in each of the grid’s cells. A spatial-data optimization technique is utilized to find the optimal alignment in the search space based on the four optimization criteria. Two case studies for new roadway projects in Duval County in the State of Florida are presented to illustrate the methodology. The optimization output alignments are compared to the proposed Florida Department of Transportation (FDOT) alignments. The comparison is based on right-of-way costs for the alignments. For both case studies, the right-of-way costs for the developed optimal alignments were found to be significantly lower than the FDOT alignments.

Keywords: Optimization, planning, roadway alignment, FDOT.

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Authors: Abdulaziz Alsadhan, Naveed Khan

Abstract:

In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).

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