Search results for: Multiple input multiple output

Authors: Jagadish H. Pujar, Pallavi S. Gurjal, Shambhavi D. S, Kiran S. Kunnur

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Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.

Keywords: Image Segmentation, Image smoothing, Edge Detection, Impulsive noise, Gaussian noise, Median filter, Canny edge, Eigen values, Eigen vector.

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Authors: D. Jayalakshmi, S. Bhosale

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This paper, in its first part, presents the state-of-the-art literature of design approaches for geosynthetic reinforced unpaved roads. The literature starting since 1970 and the critical appraisal of flexible pavement design by Giroud and Han (2004) and Jonathan Fannin (2006) is presented. The design example is illustrated for Indian conditions. The example emphasizes the results computed by Giroud and Han's (2004) design method with the Indian road congress guidelines by IRC SP 72 -2015. The input data considered are related to the subgrade soil condition of Maharashtra State in India. The unified soil classification of the subgrade soil is inorganic clay with high plasticity (CH), which is expansive with a California bearing ratio (CBR) of 2% to 3%. The example exhibits the unreinforced case and geotextile as reinforcement by varying the rut depth from 25 mm to 100 mm. The present result reveals the base thickness for the unreinforced case from the IRC design catalogs is in good agreement with Giroud and Han (2004) approach for a range of 75 mm to 100 mm rut depth. Since Giroud and Han (2004) method is applicable for both reinforced and unreinforced cases, for the same data with appropriate Nc factor, for the same rut depth, the base thickness for the reinforced case has arrived for the Indian condition. From this trial, for the CBR of 2%, the base thickness reduction due to geotextile inclusion is 35%. For the CBR range of 2% to 5% with different stiffness in geosynthetics, the reduction in base course thickness will be evaluated, and the validation will be executed by the full-scale accelerated pavement testing set up at the College of Engineering Pune (COE), India.

Keywords: Base thickness, design approach, equation, full scale accelerated pavement set up, Indian condition.

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Authors: Jeong-Woo Seo, Jin-Seung Choi, Dong-Won Kang, Jae-Hyuk Bae, Gye-Rae Tack

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To achieve accurate and precise results of finite element analysis (FEA) of bones, it is important to represent the load/boundary conditions as identical as possible to the human body such as the bone properties, the type and force of the muscles, the contact force of the joints, and the location of the muscle attachment. In this study, the difference in the Von-Mises stress and the total deformation was compared by classifying them into Case 1, which shows the actual anatomical form of the muscle attached to the femur when the same muscle force was applied, and Case 2, which gives a simplified representation of the attached location. An inverse dynamical musculoskeletal model was simulated using data from an actual walking experiment to complement the accuracy of the muscular force, the input value of FEA. The FEA method using the results of the muscular force that were calculated through the simulation showed that the maximum Von-Mises stress and the maximum total deformation in Case 2 were underestimated by 8.42% and 6.29%, respectively, compared to Case 1. The torsion energy and bending moment at each location of the femur occurred via the stress ingredient. Due to the geometrical/morphological feature of the femur of having a long bone shape when the stress distribution is wide, as shown in Case 1, a greater Von-Mises stress and total deformation are expected from the sum of the stress ingredients. More accurate results can be achieved only when the muscular strength and the attachment location in the FEA of the bones and the attachment form are the same as those in the actual anatomical condition under the various moving conditions of the human body.

Keywords: Musculoskeletal modeling, Finite element analysis, Von-Mises stress, Deformation, Muscle attachment.

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Authors: Gesine Hellwig

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Functional imaging procedures for the non-invasive assessment of tissue microcirculation are highly requested, but require a mathematical approach describing the trans- and intercapillary passage of tracer particles. Up to now, two theoretical, for the moment different concepts have been established for tracer kinetic modeling of contrast agent transport in tissues: pharmacokinetic compartment models, which are usually written as coupled differential equations, and the indicator dilution theory, which can be generalized in accordance with the theory of lineartime- invariant (LTI) systems by using a convolution approach. Based on mathematical considerations, it can be shown that also in the case of an open two-compartment model well-known from functional imaging, the concentration-time course in tissue is given by a convolution, which allows a separation of the arterial input function from a system function being the impulse response function, summarizing the available information on tissue microcirculation. Due to this reason, it is possible to integrate the open two-compartment model into the system-theoretic concept of indicator dilution theory (IDT) and thus results known from IDT remain valid for the compartment approach. According to the long number of applications of compartmental analysis, even for a more general context similar solutions of the so-called forward problem can already be found in the extensively available appropriate literature of the seventies and early eighties. Nevertheless, to this day, within the field of biomedical imaging – not from the mathematical point of view – there seems to be a trench between both approaches, which the author would like to get over by exemplary analysis of the well-known model.

Keywords: Functional imaging, Tracer kinetic modeling, LTIsystem, Indicator dilution theory / convolution approach, Two-Compartment model.

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed length window in the past as an explicit input. In this paper, we study how the performance of predictive models change as a function of different look-back window sizes and different amounts of time to predict into the future. We also consider the performance of the recent attention-based transformer models, which had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), Gated Recurrent Units (GRU), and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the website of University of California, Irvine (UCI), which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean   Absolute Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: Air quality prediction, deep learning algorithms, time series forecasting, look-back window.

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Authors: Anjan Kumar Kakati, M. Chandrasekaran, Amitava Mandal, Amit Kumar Singh

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End milling process is one of the common metal cutting operations used for machining parts in manufacturing industry. It is usually performed at the final stage in manufacturing a product and surface roughness of the produced job plays an important role. In general, the surface roughness affects wear resistance, ductility, tensile, fatigue strength, etc., for machined parts and cannot be neglected in design. In the present work an experimental investigation of end milling of aluminium alloy with carbide tool is carried out and the effect of different cutting parameters on the response are studied with three-dimensional surface plots. An artificial neural network (ANN) is used to establish the relationship between the surface roughness and the input cutting parameters (i.e., spindle speed, feed, and depth of cut). The Matlab ANN toolbox works on feed forward back propagation algorithm is used for modeling purpose. 3-12-1 network structure having minimum average prediction error found as best network architecture for predicting surface roughness value. The network predicts surface roughness for unseen data and found that the result/prediction is better. For desired surface finish of the component to be produced there are many different combination of cutting parameters are available. The optimum cutting parameter for obtaining desired surface finish, to maximize tool life is predicted. The methodology is demonstrated, number of problems are solved and algorithm is coded in Matlab®.

Keywords: End milling, Surface roughness, Neural networks.

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Authors: Himanshu V. Gajjar, Anish H. Gandhi, Tanvir A Jafri, Harit K. Raval

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Bendability is constrained by maximum top roller load imparting capacity of the machine. Maximum load is encountered during the edge pre-bending stage of roller bending. Capacity of 3-roller plate bending machine is specified by maximum thickness and minimum shell diameter combinations that can be pre-bend for given plate material of maximum width. Commercially available plate width or width of the plate that can be accommodated on machine decides the maximum rolling width. Original equipment manufacturers (OEM) provide the machine capacity chart based on reference material considering perfectly plastic material model. Reported work shows the bendability analysis of heavy duty 3-roller plate bending machine. The input variables for the industry are plate thickness, shell diameter and material property parameters, as it is fixed by the design. Analytical models of equivalent thickness, equivalent width and maximum width based on power law material model were derived to study the bendability. Equation of maximum width provides bendability for designed configuration i.e. material property, shell diameter and thickness combinations within the machine limitations. Equivalent thicknesses based on perfectly plastic and power law material model were compared for four different materials grades of C-Mn steel in order to predict the bend-ability. Effect of top roller offset on the bendability at maximum top roller load imparting capacity is reported.

Keywords: 3-Roller bending, Bendability, Equivalent thickness, Equivalent width, Maximum width.

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Authors: R. Hocine, A. Boudjemai, A. Amrani, K. Belkacemi

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Temperature rising is a negative factor in almost all systems. It could cause by self heating or ambient temperature. In solar photovoltaic cells this temperature rising affects on the behavior of cells. The ability of a PV module to withstand the effects of periodic hot-spot heating that occurs when cells are operated under reverse biased conditions is closely related to the properties of the cell semi-conductor material.

In addition, the thermal effect also influences the estimation of the maximum power point (MPP) and electrical parameters for the PV modules, such as maximum output power, maximum conversion efficiency, internal efficiency, reliability, and lifetime. The cells junction temperature is a critical parameter that significantly affects the electrical characteristics of PV modules. For practical applications of PV modules, it is very important to accurately estimate the junction temperature of PV modules and analyze the thermal characteristics of the PV modules. Once the temperature variation is taken into account, we can then acquire a more accurate MPP for the PV modules, and the maximum utilization efficiency of the PV modules can also be further achieved.

In this paper, the three-Dimensional Transmission Line Matrix (3D-TLM) method was used to map the surface temperature distribution of solar cells while in the reverse bias mode. It was observed that some cells exhibited an inhomogeneity of the surface temperature resulting in localized heating (hot-spot). This hot-spot heating causes irreversible destruction of the solar cell structure. Hot spots can have a deleterious impact on the total solar modules if individual solar cells are heated. So, the results show clearly that the solar cells are capable of self-generating considerable amounts of heat that should be dissipated very quickly to increase PV module's lifetime.

Keywords: Thermal effect, Conduction, Heat dissipation, Thermal conductivity, Solar cell, PV module, Nodes, 3D-TLM.

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Authors: Ah-young Jeon, In-cheol Kim, Jae-hee Jung, Soo-young Ye, Jae-hyung Kim, Ki-gon Nam, Seoung-wan Baik, Jung-hoon Ro, Gye-rok Jeon

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The aged are faced with increasing risk for falls. The aged have the easily fragile bones than others. When falls have occurred, it is important to detect this emergency state because such events often lead to more serious illness or even death. A implementation of PDA system, for detection of emergency situation, was developed using 3-axis accelerometer in this paper as follows. The signals were acquired from the 3-axis accelerometer, and then transmitted to the PDA through Bluetooth module. This system can classify the human activity, and also detect the emergency state like falls. When the fall occurs, the system generates the alarm on the PDA. If a subject does not respond to the alarm, the system determines whether the current situation is an emergency state or not, and then sends some information to the emergency center in the case of urgent situation. Three different studies were conducted on 12 experimental subjects, with results indicating a good accuracy. The first study was performed to detect the posture change of human daily activity. The second study was performed to detect the correct direction of fall. The third study was conducted to check the classification of the daily physical activity. Each test was lasted at least 1 min. in third study. The output of acceleration signal was compared and evaluated by changing a various posture after attaching a 3-axis accelerometer module on the chest. The newly developed system has some important features such as portability, convenience and low cost. One of the main advantages of this system is that it is available at home healthcare environment. Another important feature lies in low cost to manufacture device. The implemented system can detect the fall accurately, so will be widely used in emergency situation.

Keywords: Alarm System, Ambulatory monitoring, Emergency detection, Classification of activity, and 3-axis accelerometer.

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Authors: Haydar Kepekçi, Baha Zafer, Hasan Rıza Güven

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Noise disturbance is one of the major factors considered in the fast development of aircraft technology. This paper reviews the flow field, which is examined on the 2D NACA0015 and 3D NACA0012 blade profile using SST k-ω turbulence model to compute the unsteady flow field. We inserted the time-dependent flow area variables in Ffowcs-Williams and Hawkings (FW-H) equations as an input and Sound Pressure Level (SPL) values will be computed for different angles of attack (AoA) from the microphone which is positioned in the computational domain to investigate effect of augmentation of unsteady 2D and 3D airfoil region noise level. The computed results will be compared with experimental data which are available in the open literature. As results; one of the calculated Cp is slightly lower than the experimental value. This difference could be due to the higher Reynolds number of the experimental data. The ANSYS Fluent software was used in this study. Fluent includes well-validated physical modeling capabilities to deliver fast, accurate results across the widest range of CFD and multiphysics applications. This paper includes a study which is on external flow over an airfoil. The case of 2D NACA0015 has approximately 7 million elements and solves compressible fluid flow with heat transfer using the SST turbulence model. The other case of 3D NACA0012 has approximately 3 million elements.

Keywords: Aeroacoustics, Ffowcs-Williams and Hawkings equations, SST k-ω turbulence model, Noise Disturbance, 3D Blade Profile, 2D Blade Profile.

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Authors: T. Yamaguchi, Y. Kurosawa, S. Maruyama, K. Tobita, Y. Hirano, K. Yokouchi, K. Kihara, T. Sunaga

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This paper describes dynamic analysis using proposed fast finite element method for a shock absorbing structure including a sponge. The structure is supported by nonlinear concentrated springs. The restoring force of the spring has cubic nonlinearity and linear hysteresis damping. To calculate damping properties for the structures including elastic body and porous body, displacement vectors as common unknown variable are solved under coupled condition. Under small amplitude, we apply asymptotic method to complex eigenvalue problem of this system to obtain modal parameters. And then expressions of modal loss factor are derived approximately. This approach was proposed by one of the authors previously. We call this method as Modal Strain and Kinetic Energy Method (MSKE method). Further, using the modal loss factors, the discretized equations in physical coordinate are transformed into the nonlinear ordinary coupled equations using normal coordinate corresponding to linear natural modes. This transformation yields computation efficiency. As a numerical example of a shock absorbing structures, we adopt double skins with a sponge. The double skins are supported by nonlinear concentrated springs. We clarify influences of amplitude of the input force on nonlinear and chaotic responses.

Keywords: Dynamic response, Nonlinear and chaotic motions, Finite Element analysis, Numerical analysis.

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Authors: M. G. Papoutsidakis, G. Chamilothoris, F. Dailami, N. Larsen, A Pipe

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Due to their high power-to-weight ratio and low cost, pneumatic actuators are attractive for robotics and automation applications; however, achieving fast and accurate control of their position have been known as a complex control problem. A methodology for obtaining high position accuracy with a linear pneumatic actuator is presented. During experimentation with a number of PID classical control approaches over many operations of the pneumatic system, the need for frequent manual re-tuning of the controller could not be eliminated. The reason for this problem is thermal and energy losses inside the cylinder body due to the complex friction forces developed by the piston displacements. Although PD controllers performed very well over short periods, it was necessary in our research project to introduce some form of automatic gain-scheduling to achieve good long-term performance. We chose a fuzzy logic system to do this, which proved to be an easily designed and robust approach. Since the PD approach showed very good behaviour in terms of position accuracy and settling time, it was incorporated into a modified form of the 1st order Tagaki- Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler uses an input variable which automatically changes the PD gain values of the controller according to the frequency of repeated system operations. Performance of the new controller was significantly improved and the need for manual re-tuning was eliminated without a decrease in performance. The performance of the controller operating with the above method is going to be tested through a high-speed web network (GRID) for research purposes.

Keywords: Fuzzy logic, gain scheduling, leaky integrator, pneumatic actuator.

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Authors: A. Esmaili Torshabi, A. Terakawa, K. Ishii, H. Yamazaki, S. Matsuyama, Y. Kikuchi, M. Nakhostin, H. Sabet, A. Ishizaki, W. Yamashita, T. Togashi, J. Arikawa, H. Akiyama, K. Koyata

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The purpose of this study is to introduce a new interface program to calculate a dose distribution with Monte Carlo method in complex heterogeneous systems such as organs or tissues in proton therapy. This interface program was developed under MATLAB software and includes a friendly graphical user interface with several tools such as image properties adjustment or results display. Quadtree decomposition technique was used as an image segmentation algorithm to create optimum geometries from Computed Tomography (CT) images for dose calculations of proton beam. The result of the mentioned technique is a number of nonoverlapped squares with different sizes in every image. By this way the resolution of image segmentation is high enough in and near heterogeneous areas to preserve the precision of dose calculations and is low enough in homogeneous areas to reduce the number of cells directly. Furthermore a cell reduction algorithm can be used to combine neighboring cells with the same material. The validation of this method has been done in two ways; first, in comparison with experimental data obtained with 80 MeV proton beam in Cyclotron and Radioisotope Center (CYRIC) in Tohoku University and second, in comparison with data based on polybinary tissue calibration method, performed in CYRIC. These results are presented in this paper. This program can read the output file of Monte Carlo code while region of interest is selected manually, and give a plot of dose distribution of proton beam superimposed onto the CT images.

Keywords: Monte Carlo, CT images, Quadtree decomposition, Interface program, Proton beam

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Authors: Jozef Mindas, Jaroslav Skvarenina, Jana Skvareninova

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Study of the effects of climate change on Norway Spruce (Picea abies) forests has mainly focused on the diversity of tree species diversity of tree species as a result of the ability of species to tolerate temperature and moisture changes as well as some effects of disturbance regime changes. The tree species’ diversity changes in spruce forests due to climate change have been analyzed via gap model. Forest gap model is a dynamic model for calculation basic characteristics of individual forest trees. Input ecological data for model calculations have been taken from the permanent research plots located in primeval forests in mountainous regions in Slovakia. The results of regional scenarios of the climatic change for the territory of Slovakia have been used, from which the values are according to the CGCM3.1 (global) model, KNMI and MPI (regional) models. Model results for conditions of the climate change scenarios suggest a shift of the upper forest limit to the region of the present subalpine zone, in supramontane zone. N. spruce representation will decrease at the expense of beech and precious broadleaved species (Acer sp., Sorbus sp., Fraxinus sp.). The most significant tree species diversity changes have been identified for the upper tree line and current belt of dwarf pine (Pinus mugo) occurrence. The results have been also discussed in relation to most important disturbances (wind storms, snow and ice storms) and phenological changes which consequences are little known. Special discussion is focused on biomass production changes in relation to carbon storage diversity in different carbon pools.

Keywords: Biodiversity, climate change, Norway spruce forests, gap model.

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Authors: F. Amin Salehi, L. Sharp, M. A. Abdoli, D.E.Cotton, K.Rezapour

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The daily increase of organic waste materials resulting from different activities in the country is one of the main factors for the pollution of environment. Today, with regard to the low level of the output of using traditional methods, the high cost of disposal waste materials and environmental pollutions, the use of modern methods such as anaerobic digestion for the production of biogas has been prevailing. The collected biogas from the process of anaerobic digestion, as a renewable energy source similar to natural gas but with a less methane and heating value is usable. Today, with the help of technologies of filtration and proper preparation, access to biogas with features fully similar to natural gas has become possible. At present biogas is one of the main sources of supplying electrical and thermal energy and also an appropriate option to be used in four stroke engine, diesel engine, sterling engine, gas turbine, gas micro turbine and fuel cell to produce electricity. The use of biogas for different reasons which returns to socio-economic and environmental advantages has been noticed in CHP for the production of energy in the world. The production of biogas from the technology of anaerobic digestion and its application in CHP power plants in Iran can not only supply part of the energy demands in the country, but it can materialize moving in line with the sustainable development. In this article, the necessity of the development of CHP plants with biogas fuels in the country will be dealt based on studies performed from the economic, environmental and social aspects. Also to prove the importance of the establishment of these kinds of power plants from the economic point of view, necessary calculations has been done as a case study for a CHP power plant with a biogas fuel.

Keywords: Anaerobic Digestion, Biogas, CHP, Organic Wastes

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Authors: Mohammad T. Uddin, Aurup R. Dhar

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The study was conducted to assess the impact of conservation agriculture practice on farmers’ socioeconomic condition and soil environmental quality in Bangladesh. A total of 450 (i.e., 50 focal, 150 proximal and 250 control) farmers from five districts were selected for this study. Descriptive statistics like sum, averages, percentages, etc. were calculated to evaluate the socioeconomic data. Using Enyedi’s crop productivity index, it was found that the crop productivity of focal, proximal and control farmers was increased by 0.9, 1.2 and 1.3 percent, respectively. The result of DID (Difference-in-difference) analysis indicated that the impact of conservation agriculture practice on farmers’ average annual income was significant. Multidimensional poverty index (MPI) indicates that poverty in terms of deprivation of health, education and living standards was decreased; and a remarkable improvement in farmers’ socioeconomic status was found after adopting conservation agriculture practice. Most of the focal and proximal farmers stated about increased soil environmental condition where majority of control farmers stated about constant environmental condition in this regard. The Probit model reveals that minimum tillage operation, permanent organic soil cover, and application of compost and vermicompost were found significant factors affecting soil environmental quality under conservation agriculture. Input support, motivation, training programmes and extension services are recommended to implement in order to raise the awareness and enrich the knowledge of the farmers on conservation agriculture practice.

Keywords: Conservation agriculture, crop productivity, socioeconomic status, soil environment quality.

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Authors: Steve Fish, Chris Lambert

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Cumbria is a geo-political county in Northwest England within which the Lake District National Park, a UNESCO World Heritage site is located. Whilst the area has a formidable reputation for natural beauty and historic assets, the innovation ecosystem is described as ‘patchy’ for a number of reasons. The county is one of the largest in England by area and is sparsely populated. This paper describes the needs, development and delivery of an SME business-support programme funded by the European Regional Development Fund, Lancaster University and the University of Cumbria. The Cumbria Innovations Platform (CUSP) Project has been designed to respond to the nuanced needs of SMEs in this locale, whilst promoting the adoption of research and innovation. CUSP utilizes a funnel method to support rural businesses with access to university innovation intervention. CUSP has been built on a three-tier model: Communicate, Collaborate and Create. The paper describes this project in detail and presents results in terms of output indicators achieved, a beneficiary telephone survey and wider economic forecasts. From a pragmatic point-of-view, the paper provides experiences and reflections of those people who are delivering and evaluating knowledge exchange. The authors discuss some of the benefits, challenges and implications for both policy makers and practitioners. Finally, the paper aims to serve as an invitation to others who may consider adopting a similar method of university-industry collaboration in their own region.

Keywords: Regional business support, rural business support, university-industry collaboration, collaborative R&D, SMEs, knowledge exchange.

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Authors: Luciana C. Ramos, Leandro J. Sousa, Antônio Ferreira da Silva, Valéria Gomes Oliveira Falcão, Suzana T. Cunha Lima

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The commercial production of biodiesel using microalgae demands a high-energy input for harvesting biomass, making production economically unfeasible. Methods currently used involve mechanical, chemical, and biological procedures. In this work, a flocculation system is presented as a cost and energy effective process to increase biomass production of Phaeodactylum tricornutum. This diatom is the only species of the genus that present fast growth and lipid accumulation ability that are of great interest for biofuel production. The algae, selected from the Bank of Microalgae, Institute of Biology, Federal University of Bahia (Brazil), have been bred in tubular reactor with photoperiod of 12 h (clear/dark), providing luminance of about 35 μmol photons m^-2s^-1, and temperature of 22 °C. The medium used for growing cells was the Conway medium, with addition of silica. The seaweed growth curve was accompanied by cell count in Neubauer camera and by optical density in spectrophotometer, at 680 nm. The precipitation occurred at the end of the stationary phase of growth, 21 days after inoculation, using two methods: centrifugation at 5000 rpm for 5 min, and electro-flocculation at 19 EPD and 95 W. After precipitation, cells were frozen at -20 °C and, subsequently, lyophilized. Biomass obtained by electro-flocculation was approximately four times greater than the one achieved by centrifugation. The benefits of this method are that no addition of chemical flocculants is necessary and similar cultivation conditions can be used for the biodiesel production and pharmacological purposes. The results may contribute to improve biodiesel production costs using marine microalgae.

Keywords: Biomass, diatom, flocculation, microalgae.

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Authors: Mohammed A. Elhaj, Jamal S. Yassin

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In the present time, energy crises is considered a severe problem across the world. For the protection of global environment and maintain ecological balance, energy saving is considered one of the most vital issues from the view point of fuel consumption. As the industrial sectors everywhere continue efforts to improve their energy efficiency, recovering waste heat losses provides an attractive opportunity for an emission free and less costly energy resource. In the other hand the using of solar energy has become more insistent particularly after the high gross of prices and running off the conventional energy sources. Therefore, it is essential that we should endeavor for waste heat recovery as well as solar energy by making significant and concrete efforts. For these reasons this investigation is carried out to study and analyze the performance of a power plant working by a combined cycle in which heat recovery system generator (HRSG) gets its energy from the waste heat of a gas turbine unit. Evaluation of the performance of the plant is based on different thermal efficiencies of the main components in addition to the second law analysis considering the exergy destructions for the whole components. The contribution factors including the solar as well as the wasted energy are considered in the calculations. The final results have shown that there is significant exergy destruction in solar concentrator and the combustion chamber of the gas turbine unit. Other components such as compressor, gas turbine, steam turbine and heat exchangers having insignificant exergy destruction. Also, solar energy can contribute by about 27% of the input energy to the plant while the energy lost with exhaust gases can contribute by about 64% at maximum cases.

Keywords: Solar energy, environment, efficiency, waste heat, steam generator, performance, exergy destruction.

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores, Valentin Soloiu

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This work describes a system that uses electromyography (EMG) signals obtained from muscle sensors and an Artificial Neural Network (ANN) for signal classification and pattern recognition that is used to control a small unmanned aerial vehicle using specific arm movements. The main objective of this endeavor is the development of an intelligent interface that allows the user to control the flight of a drone beyond direct manual control. The sensor used were the MyoWare Muscle sensor which contains two EMG electrodes used to collect signals from the posterior (extensor) and anterior (flexor) forearm, and the bicep. The collection of the raw signals from each sensor was performed using an Arduino Uno. Data processing algorithms were developed with the purpose of classifying the signals generated by the arm’s muscles when performing specific movements, namely: flexing, resting, and motion of the arm. With these arm motions roll control of the drone was achieved. MATLAB software was utilized to condition the signals and prepare them for the classification. To generate the input vector for the ANN and perform the classification, the root mean square and the standard deviation were processed for the signals from each electrode. The neuromuscular information was trained using an ANN with a single 10 neurons hidden layer to categorize the four targets. The result of the classification shows that an accuracy of 97.5% was obtained. Afterwards, classification results are used to generate the appropriate control signals from the computer to the drone through a Wi-Fi network connection. These procedures were successfully tested, where the drone responded successfully in real time to the commanded inputs.

Keywords: Biosensors, electromyography, Artificial Neural Network, Arduino, drone flight control, machine learning.

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Authors: Cigdem Safak Saglam

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Most thermal power plants use steam as working fluid in their power cycle. Therefore, in addition to fuel, water is the other main input for thermal plants. Water and steam must be highly pure in order to protect the systems from corrosion, scaling and biofouling. Pure process water is produced in water treatment plants having many several treatment methods. Treatment plant design is selected depending on raw water source and required water quality. Although working principle of fossil-fuel fired thermal power plants are same, there is no standard design and equipment arrangement valid for all thermal power plant utility systems. Besides that, there are many other technology evaluation and selection criteria for designing the most optimal water systems meeting the requirements such as local conditions, environmental restrictions, electricity and other consumables availability and transport, process water sources and scarcity, land use constraints etc. Aim of this study is explaining the adopted methodology for technology selection for process water preparation and industrial waste water treatment plant in a thermal power plant project located in Tufanbeyli, Adana Province in Turkey. Thermal power plant is fired with indigenous lignite coal extracted from adjacent lignite reserves. This paper addresses all above-mentioned factors affecting the thermal power plant water treatment facilities (demineralization + waste water treatment) design and describes the ultimate design of Tufanbeyli Thermal Power Plant Water Treatment Plant.

Keywords: Thermal power plant, lignite coal, pre-treatment, demineralization, electrodialysis, recycling, waste water, process water.

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Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao

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Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.

Keywords: Neural Network, Fuzzy, River, Forecasting

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Authors: O. Abramova, L. Abukova, A. Goreva, G. Isaeva

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The present work was made for the purpose of evaluating the interstitial water’s role in the mobilization of metal elements of clay deposits and occurrences in sedimentary formation in the hydro-geological basins. The experiments were performed by using a special facility, which allows adjusting the pressure, temperature, and the frequency of the acoustic vibrations. The dates for study were samples of the oil shales (Baltic career, O₂kk) and clay rocks, mainly montmorillonite composition (Borehole SG-12000, the depth of selection 1000–3600 m, the Azov-Kuban trough, N₁). After interstitial water squeezing from the rock samples, decrease in the original content of the rock forming components including trace metals V, Cr, Co, Ni, Cu, Zn, Zr, Mo, Pb, W, Ti, and others was recorded. The experiments made it possible to evaluate the ore elements output and organic matters with the interstitial waters. Calculations have shown that, in standard conditions, from each ton of the oil shales, 5-6 kg of ore elements and 9-10 kg of organic matter can be escaped. A quantity of matter, migrating from clays in the process of solidification, is changed depending on the lithogenesis stage: more recent unrealized deposits lose more ore and organic materials than the clay rocks, selected from depth over 3000 m. Each ton of clays in the depth interval 1000-1500 m is able to generate 3-5 kg of the ore elements and 6-8 kg of the organic matters. The interstitial waters are a freight forwarder over transferring these matters in the reservoir beds. It was concluded that the interstitial waters which escaped from the study samples are solutions with abnormal high concentrations of the metals and organic matters. In the discharge zones of the sediment basins, such fluids can create paragenetic associations of the sedimentary-catagenetic ore and hydrocarbon mineral resources accumulations.

Keywords: Hydrocarbons, ore genesis, paragenesis, interstitial waters.

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Authors: Mohammed W. Abdulrahman

Abstract:

In the thermochemical water splitting process by Cu-Cl cycle, oxygen gas is produced by an endothermic thermolysis process at a temperature of 530^oC. Oxygen production reactor is a three-phase reactor involving cuprous chloride molten salt, copper oxychloride solid reactant and oxygen gas. To perform optimal performance, the oxygen reactor requires accurate control of heat transfer to the molten salt and decomposing solid particles within the thermolysis reactor. In this paper, the scale up analysis of the oxygen reactor that is heated by an internal helical tube is performed from the perspective of heat transfer. A heat balance of the oxygen reactor is investigated to analyze the size of the reactor that provides the required heat input for different rates of hydrogen production. It is found that the helical tube wall and the service side constitute the largest thermal resistances of the oxygen reactor system. In the analysis of this paper, the Cu-Cl cycle is assumed to be heated by two types of nuclear reactor, which are HTGR and CANDU SCWR. It is concluded that using CANDU SCWR requires more heat transfer rate by 3-4 times than that when using HTGR. The effect of the reactor aspect ratio is also studied and it is found that increasing the aspect ratio decreases the number of reactors and the rate of decrease in the number of reactors decreases by increasing the aspect ratio. Comparisons between the results of this study and pervious results of material balances in the oxygen reactor show that the size of the oxygen reactor is dominated by the heat balance rather than the material balance.

Keywords: Heat transfer, Cu-Cl cycle, hydrogen production, oxygen, clean energy.

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Authors: Farnaz Amin Salehi, David Edward.Cotton, Mohammad Ali Abdoli, Kambiz Rezapour

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The daily increase of organic waste materials resulting from different activities in the country is one of the main factors for the pollution of environment. Today, with regard to the low level of the output of using traditional methods, the high cost of disposal waste materials and environmental pollutions, the use of modern methods such as anaerobic digestion for the production of biogas has been prevailing. The collected biogas from the process of anaerobic digestion, as a renewable energy source similar to natural gas but with a less methane and heating value is usable. Today, with the help of technologies of filtration and proper preparation, access to biogas with features fully similar to natural gas has become possible. At present biogas is one of the main sources of supplying electrical and thermal energy and also an appropriate option to be used in four stroke engine, diesel engine, sterling engine, gas turbine, gas micro turbine and fuel cell to produce electricity. The use of biogas for different reasons which returns to socio-economic and environmental advantages has been noticed in CHP for the production of energy in the world. The production of biogas from the technology of anaerobic digestion and its application in CHP power plants in Iran can not only supply part of the energy demands in the country, but it can materialize moving in line with the sustainable development. In this article, the necessity of the development of CHP plants with biogas fuels in the country will be dealt based on studies performed from the economic, environmental and social aspects. Also to prove the importance of the establishment of these kinds of power plants from the economic point of view, necessary calculations has been done as a case study for a CHP power plant with a biogas fuel.

Keywords: Anaerobic Digestion, Biogas, CHP, Organic Wastes

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: Autonomous vehicles, deformable part model, dpm, pedestrian recognition.

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Authors: M.C. Zaghdoudi, S. Maalej, J. Mansouri, M.B.H. Sassi

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An experimental study is realized in order to verify the Mini Heat Pipe (MHP) concept for cooling high power dissipation electronic components and determines the potential advantages of constructing mini channels as an integrated part of a flat heat pipe. A Flat Mini Heat Pipe (FMHP) prototype including a capillary structure composed of parallel rectangular microchannels is manufactured and a filling apparatus is developed in order to charge the FMHP. The heat transfer improvement obtained by comparing the heat pipe thermal resistance to the heat conduction thermal resistance of a copper plate having the same dimensions as the tested FMHP is demonstrated for different heat input flux rates. Moreover, the heat transfer in the evaporator and condenser sections are analyzed, and heat transfer laws are proposed. In the theoretical part of this work, a detailed mathematical model of a FMHP with axial microchannels is developed in which the fluid flow is considered along with the heat and mass transfer processes during evaporation and condensation. The model is based on the equations for the mass, momentum and energy conservation, which are written for the evaporator, adiabatic, and condenser zones. The model, which permits to simulate several shapes of microchannels, can predict the maximum heat transfer capacity of FMHP, the optimal fluid mass, and the flow and thermal parameters along the FMHP. The comparison between experimental and model results shows the good ability of the numerical model to predict the axial temperature distribution along the FMHP.

Keywords: Electronics Cooling, Micro Heat Pipe, Mini Heat Pipe, Mini Heat Spreader, Capillary grooves.

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Authors: Eid Alotaibi

Abstract:

The purpose of this study is to investigate the impact of tourists’ culture on perception and evaluation of hotel service experience and behavioral intentions. Drawing on Hofested’s cultural dimensions, this study seeks to further contribute towards understanding the effect of culture on perception and evaluation of hotels’ services, and whether there are differences between Saudi and European tourists’ perceptions of hotel services evaluation. A descriptive cross-sectional design was used in this study. Data were collected from tourists staying in five-star hotels in Saudi Arabia using the self-completion technique. The findings show that evaluations of hotel services differ from one culture to another. T-test results reveal that Saudis were more tolerant and reported significantly higher levels of satisfaction, were more likely to return and recommend the hotel, and perceived the price for the hotel stay as being good value for money as compared to their European counterparts. The sample was relatively small and specific to only five-star hotel evaluations. As a result, findings cannot be generalized to the wider tourist population. The results of this research have important implications for management within the Saudi hospitality industry. The study contributes to the tourist cultural theory by emphasizing the relative importance of cultural dimensions in-service evaluation. The author argues that no studies could be identified that compare Saudis and Europeans in their evaluations of their experiences staying at hotels. Therefore, the current study would enhance understanding of the effects of cultural factors on service evaluations and provide valuable input for international market segmentation and resource allocation in the Saudi hotel industry.

Keywords: Culture, tourist, service experience, hotel industry, Hofested’s cultural dimensions.

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Authors: A. Arockia Selvakumar, R. Sivaramakrishnan, Srinivasa Karthik.T.V, Valluri Siva Ramakrishna, B.Vinodh.

Abstract:

Industrial robots play a vital role in automation however only little effort are taken for the application of robots in machining work such as Grinding, Cutting, Milling, Drilling, Polishing etc. Robot parallel manipulators have high stiffness, rigidity and accuracy, which cannot be provided by conventional serial robot manipulators. The aim of this paper is to perform the modeling and the workspace analysis of a 3 DOF Parallel Manipulator (3 DOF PM). The 3 DOF PM was modeled and simulated using 'ADAMS'. The concept involved is based on the transformation of motion from a screw joint to a spherical joint through a connecting link. This paper work has been planned to model the Parallel Manipulator (PM) using screw joints for very accurate positioning. A workspace analysis has been done for the determination of work volume of the 3 DOF PM. The position of the spherical joints connected to the moving platform and the circumferential points of the moving platform were considered for finding the workspace. After the simulation, the position of the joints of the moving platform was noted with respect to simulation time and these points were given as input to the 'MATLAB' for getting the work envelope. Then 'AUTOCAD' is used for determining the work volume. The obtained values were compared with analytical approach by using Pappus-Guldinus Theorem. The analysis had been dealt by considering the parameters, link length and radius of the moving platform. From the results it is found that the radius of moving platform is directly proportional to the work volume for a constant link length and the link length is also directly proportional to the work volume, at a constant radius of the moving platform.

Keywords: Three Degrees of freedom Parallel Manipulator (3DOF PM), ADAMS, Work volume, MATLAB, AUTOCAD, Pappus- Guldinus Theorem.

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Authors: Md. Shafiqul Islam, Abdullah Khan, Sharon Kao-Walter, Li Jian

Abstract:

Shear testing is one of the most complex testing areas where available methods and specimen geometries are different from each other. Therefore, a modified shear test specimen (MSTS) combining the simple uniaxial test with a zone of interest (ZOI) is tested which gives almost the pure shear. In this study, material parameters of polypropylene (PP) and high density polyethylene (HDPE) are first measured by tensile tests with a dogbone shaped specimen. These parameters are then used as an input for the finite element analysis. Secondly, a specially designed specimen (MSTS) is used to perform the shear stress tests in a tensile testing machine to get the results in terms of forces and extension, crack initiation etc. Scanning Electron Microscopy (SEM) is also performed on the shear fracture surface to find material behavior. These experiments are then simulated by finite element method and compared with the experimental results in order to confirm the simulation model. Shear stress state is inspected to find the usability of the proposed shear specimen. Finally, a geometry correction factor can be established for these two materials in this specific loading and geometry with notch using Linear Elastic Fracture Mechanics (LEFM). By these results, strain energy of shear failure and stress intensity factor (SIF) of shear of these two polymers are discussed in the special application of the screw cap opening of the medical or food packages with a temper evidence safety solution.

Keywords: Shear test specimen, Stress intensity factor, Finite Element simulation, Scanning electron microscopy, Screw cap opening.

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