Search results for: Optical flow estimation

Authors: Ali Serhan Koyuncugil, Nermin Ozgulbas

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In this paper, a data mining model to SMEs for detecting financial and operational risk indicators by data mining is presenting. The identification of the risk factors by clarifying the relationship between the variables defines the discovery of knowledge from the financial and operational variables. Automatic and estimation oriented information discovery process coincides the definition of data mining. During the formation of model; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. In addition, this paper is based on a project which was funded by The Scientific and Technological Research Council of Turkey (TUBITAK).

Keywords: Risk Management, Financial Risk, Operational Risk, Financial Early Warning System, Data Mining, CHAID Decision Tree Algorithm, SMEs.

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Authors: Burcu Kaya, Jan-Martin Kaiser, Karl-Friedrich Becker, Tanja Braun, Klaus-Dieter Lang

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Quality of the molded packages is strongly influenced by the process parameters of the transfer molding. To achieve a better package quality and a stable transfer molding process, it is necessary to understand the influence of the process parameters on the package quality. This work aims to comprehend the relationship between the process parameters, and to identify the optimum process parameters for the transfer molding process in order to achieve less voids and wire sweep. To achieve this, a DoE is executed for process optimization and a regression analysis is carried out. A systematic approach is represented to generate models which enable an estimation of the number of voids and wire sweep. Validation experiments are conducted to verify the model and the results are presented.

Keywords: Epoxy molding compounds, optimization, regression analysis, transfer molding process, voids, wire sweep.

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Authors: Zhizhong Jiang, Peter Naudé

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Effective evaluation of software development effort is an important aspect of successful project management. Based on a large database with 4106 projects ever developed, this study statistically examines the factors that influence development effort. The factors found to be significant for effort are project size, average number of developers that worked on the project, type of development, development language, development platform, and the use of rapid application development. Among these factors, project size is the most critical cost driver. Unsurprisingly, this study found that the use of CASE tools does not necessarily reduce development effort, which adds support to the claim that the use of tools is subtle. As many of the current estimation models are rarely or unsuccessfully used, this study proposes a parsimonious parametric model for the prediction of effort which is both simple and more accurate than previous models.

Keywords: Development effort, function points, team size, development language, CASE tool, rapid application development.

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Authors: Bianca A. Szasz, Keiichi Okuyama

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As the human race will continue to explore the space by creating new space transportation means and sending them to other planets, the enhance of atmospheric reentry study is crucial. In this context, an analysis of mass recession rate of ablative materials for thermal shields of reentry spacecrafts is important to be carried out. The paper describes a new estimation method for calculating the mass recession of an ablator system made of carbon fiber reinforced plastic materials. This method is based on Arrhenius equation for low temperatures and, for high temperatures, on a theory applied for the recession phenomenon of carbon fiber reinforced plastic materials, theory which takes into account the presence of the resin inside the materials. The space mission of USERS spacecraft is considered as a case study.

Keywords: Ablator system, mass recession, spacecraft, atmospheric reentry.

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Authors: S. Safi, M. Frikel, M. M'Saad, A. Zeroual

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This paper describes a blind algorithm for estimating a time varying and frequency selective fading channel. In order to identify blindly the impulse response of these channels, we have used Higher Order Statistics (HOS) to build our algorithm. In this paper, we have selected two theoretical frequency selective channels as the Proakis-s 'B' channel and the Macchi-s channel, and one practical frequency selective fading channel called Broadband Radio Access Network (BRAN A). The simulation results in noisy environment and for different data input channel, demonstrate that the proposed method could estimate the phase and magnitude of these channels blindly and without any information about the input, except that the input excitation is i.i.d (Identically and Independent Distributed) and non-Gaussian.

Keywords: Frequency response, system identification, higher order statistics, communication channels, phase estimation.

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Authors: Marian Dragomir, Alin Dragomir

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In the paper, two fault location algorithms are presented for transmission lines which use the line parameters to estimate the distance to the fault. The first algorithm uses only the measurements from one end of the line and the positive and zero sequence parameters of the line, while the second one uses the measurements from both ends of the line and only the positive sequence parameters of the line. The algorithms were tested using a transmission grid transposed in MATLAB. In a first stage it was established a fault location base line, where the algorithms mentioned above estimate the fault locations using the exact line parameters. After that, the positive and zero sequence resistance and reactance of the line were calculated again for different ground resistivity values and then the fault locations were estimated again in order to compare the results with the base line results. The results show that the algorithm which uses the zero sequence impedance of the line is the most sensitive to the line parameters modifications. The other algorithm is less sensitive to the line parameters modification.

Keywords: Estimation algorithms, fault location, line parameters, simulation tool.

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Authors: Gül Çevik

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This paper summarizes the work conducted to assess the root cause of the failure of a medium commercial vehicle leaf spring failed in service. Macro- and micro-fractographic analyses by scanning electron microscope as well as material verification tests were conducted in order to understand the failure mechanisms and root cause of the failure. Findings from the fractographic analyses indicated that failure mechanism is fatigue. Crack initiation was identified to have occurred from a point on the top surface near to the front face and to the left side. Two other crack initiation points were also observed, however, these cracks did not propagate. The propagation mode of the fatigue crack revealed that the cyclic loads resulting in crack initiation and propagation were unidirectional bending. Fractographic analyses have also showed that the root cause of the fatigue crack initiation and propagation was loading the part above design stress. Material properties of the part were also verified by chemical composition analysis, microstructural analysis by optical microscopy and hardness tests.

Keywords: Leaf spring, failure analysis, fatigue, fractography.

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Authors: Xiang Zhang, Daohong Yang, Ziyuan Wu, Lei Li, Wanting Zhou

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Visual Simultaneous Localization and Mapping (VSLAM) uses cameras to gather information in unknown environments to achieve simultaneous localization and mapping of the environment. This technology has a wide range of applications in autonomous driving, virtual reality, and other related fields. Currently, the research advancements related to VSLAM can maintain high accuracy in static environments. But in dynamic environments, the presence of moving objects in the scene can reduce the stability of the VSLAM system, leading to inaccurate localization and mapping, or even system failure. In this paper, a robust VSLAM method was proposed to effectively address the challenges in dynamic environments. We proposed a dynamic region removal scheme based on a semantic segmentation neural network and geometric constraints. Firstly, a semantic segmentation neural network is used to extract the prior active motion region, prior static region, and prior passive motion region in the environment. Then, the lightweight frame tracking module initializes the transform pose between the previous frame and the current frame on the prior static region. A motion consistency detection module based on multi-view geometry and scene flow is used to divide the environment into static regions and dynamic regions. Thus, the dynamic object region was successfully eliminated. Finally, only the static region is used for tracking thread. Our research is based on the ORBSLAM3 system, which is one of the most effective VSLAM systems available. We evaluated our method on the TUM RGB-D benchmark and the results demonstrate that the proposed VSLAM method improves the accuracy of the original ORBSLAM3 by 70%˜98.5% under a high dynamic environment.

Keywords: Dynamic scene, dynamic visual SLAM, semantic segmentation, scene flow, VSLAM.

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Authors: Evans Belly, Imdad Rizvi, M. M. Kadam

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Satellite imagery is one of the emerging technologies which are extensively utilized in various applications such as detection/extraction of man-made structures, monitoring of sensitive areas, creating graphic maps etc. The main approach here is the automated detection of buildings from very high resolution (VHR) optical satellite images. Initially, the shadow, the building and the non-building regions (roads, vegetation etc.) are investigated wherein building extraction is mainly focused. Once all the landscape is collected a trimming process is done so as to eliminate the landscapes that may occur due to non-building objects. Finally the label method is used to extract the building regions. The label method may be altered for efficient building extraction. The images used for the analysis are the ones which are extracted from the sensors having resolution less than 1 meter (VHR). This method provides an efficient way to produce good results. The additional overhead of mid processing is eliminated without compromising the quality of the output to ease the processing steps required and time consumed.

Keywords: Building detection, shadow detection, landscape generation, label, partitioning, very high resolution satellite imagery.

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Authors: Marwa I. Shabayek, Ola A. Said, Hanan A. Attaia, Heba A. Awida

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Bladder carcinoma is an important worldwide health problem. Both cystoscopy and urine cytology used in detecting bladder cancer suffer from drawbacks where cystoscopy is an invasive method and urine cytology shows low sensitivity in low grade tumors. This study validates easier and less time-consuming techniques to evaluate the value of combined use of angiogenin and clusterin in comparison and combination with voided urine cytology in the detection of bladder cancer patients. This study includes malignant (bladder cancer patients, n= 50), benign (n=20) and healthy (n=20) groups. The studied groups were subjected to cystoscopic examination, detection of bilharzial antibodies, urine cytology, and estimation of urinary angiogenin and clusterin by ELISA. The overall sensitivity and specificity were 66% and 75% for angiogenin, 70% and 82.5% for clusterin and 46% and 80% for voided urine cytology. Combined sensitivity of angiogenin and clusterin with urine cytology increased from 82 to 88%. 

Keywords: Angiogenin, Bladder Cancer, Clusterin, Cytology.

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Authors: Salim Ouchtati, Bedda Mouldi, Abderrazak Lachouri

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In this paper we present an off line system for the recognition of the handwritten numeric chains. Our work is divided in two big parts. The first part is the realization of a recognition system of the isolated handwritten digits. In this case the study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the digits by several methods: the distribution sequence, the Barr features and the centred moments of the different projections and profiles. The second part is the extension of our system for the reading of the handwritten numeric chains constituted of a variable number of digits. The vertical projection is used to segment the numeric chain at isolated digits and every digit (or segment) will be presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits). The result of the recognition of the numeric chain will be displayed at the exit of the global system.

Keywords: Optical Characters Recognition, Neural networks, Barr features, Image processing, Pattern Recognition, Featuresextraction.

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Authors: Dimitrios Koukopoulos

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In this work, we study the impact of dynamically changing link slowdowns on the stability properties of packetswitched networks under the Adversarial Queueing Theory framework. Especially, we consider the Adversarial, Quasi-Static Slowdown Queueing Theory model, where each link slowdown may take on values in the two-valued set of integers {1, D} with D > 1 which remain fixed for a long time, under a (w, p)-adversary. In this framework, we present an innovative systematic construction for the estimation of adversarial injection rate lower bounds, which, if exceeded, cause instability in networks that use the LIS (Longest-in- System) protocol for contention-resolution. In addition, we show that a network that uses the LIS protocol for contention-resolution may result in dropping its instability bound at injection rates p > 0 when the network size and the high slowdown D take large values. This is the best ever known instability lower bound for LIS networks.

Keywords: Parallel computing, network stability, adversarial queuing theory, greedy scheduling protocols.

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Authors: Saleh Mesbah Elkaffas, Ahmed A. Toony

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This paper details the application of a genetic programming framework for induction of useful classification rules from a database of income statements, balance sheets, and cash flow statements for North American public companies. Potentially interesting classification rules are discovered. Anomalies in the discovery process merit further investigation of the application of genetic programming to the dataset for the problem domain.

Keywords: Genetic programming, data mining classification rule.

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Authors: D. Erdenechimeg, T. Bujinlkham, N. Erdenepurev

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The anti-corrosion performance of fatty acid coated mild steel samples is studied. Samples of structural steel coated with collector reagents deposited from surfactant in ethanol solution and overcoated with an epoxy barrier paint. A quantitative corrosion rate was determined by linear polarization resistance method using biopotentiostat/galvanostat 400. Coating morphology was determined by scanning electronic microscopy. A test for hydrophobic surface of steel by surfactant was done. From the samples, the main component or high content iron was determined by chemical method and other metal contents were determined by Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) method. Prior to measuring the corrosion rate, mechanical and chemical treatments were performed to prepare the test specimens. Overcoating the metal samples with epoxy barrier paint after exposing them with surfactant the corrosion rate can be inhibited by 34-35 µm/year.

Keywords: Corrosion, linear polarization resistance, coating, surfactant.

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Authors: Taimur Qureshi, Djamel A Zighed

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Many supervised induction algorithms require discrete data, even while real data often comes in a discrete and continuous formats. Quality discretization of continuous attributes is an important problem that has effects on speed, accuracy and understandability of the induction models. Usually, discretization and other types of statistical processes are applied to subsets of the population as the entire population is practically inaccessible. For this reason we argue that the discretization performed on a sample of the population is only an estimate of the entire population. Most of the existing discretization methods, partition the attribute range into two or several intervals using a single or a set of cut points. In this paper, we introduce a technique by using resampling (such as bootstrap) to generate a set of candidate discretization points and thus, improving the discretization quality by providing a better estimation towards the entire population. Thus, the goal of this paper is to observe whether the resampling technique can lead to better discretization points, which opens up a new paradigm to construction of soft decision trees.

Keywords: Bootstrap, discretization, resampling, soft decision trees.

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

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 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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Authors: Chun-Ying Lee, Mei-Wen Wu, Li-Yi Cheng, Chiang-Ho Cheng

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This research studies the electroplating of zinc coating in the zinc chloride bath mixed with supercritical CO2. The sodium fluoride (NaF) was used as the bath additive to change the structure and property of the coating, and therefore the roughness and corrosion resistance of the zinc coating was investigated. The surface characterization was performed using optical microscope (OM), X-ray diffractometer (XRD), and α-step profilometer. Moreover, the potentiodynamic polarization measurement in 3% NaCl solution was employed in the corrosion resistance evaluation. Because of the emulsification of the electrolyte mixed in Sc-CO2, the electroplated zinc produced the coating with smoother surface, smaller grain, better throwing power and higher corrosion resistance. The main role played by the NaF was to reduce the coating’s roughness and grain size. In other words, the CO2 mixed with the electrolyte under the supercritical condition performed the similar function as brighter and leveler in zinc electroplating to enhance the throwing power and corrosion resistance of the coating.

Keywords: Supercritical CO2, zinc-electroplating, sodium fluoride.

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Authors: Aka S. Koffi, N’Goran Yao, Philippe Bastide, Denis Bruneau, Diby Kadjo

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Cocoa beans (Theobroma cocoa L.) are the main components for chocolate manufacturing. The beans must be correctly fermented at first. Traditional process to perform the first fermentation (lactic fermentation) often consists in confining cacao beans using banana leaves or a fermentation basket, both of them leading to a poor product thermal insulation and to an inability to mix the product. Box fermenter reduces this loss by using a wood with large thickness (e>3cm), but mixing to homogenize the product is still hard to perform. Automatic fermenters are not rentable for most of producers. Heat (T>45°C) and acidity produced during the fermentation by microbiology activity of yeasts and bacteria are enabling the emergence of potential flavor and taste of future chocolate. In this study, a cylindro-rotative fermenter (FCR-V1) has been built and coconut fibers were used in its structure to confine heat. An axis of rotation (360°) has been integrated to facilitate the turning and homogenization of beans in the fermenter. This axis permits to put fermenter in a vertical position during the anaerobic alcoholic phase of fermentation, and horizontally during acetic phase to take advantage of the mid height filling. For circulation of air flow during turning in acetic phase, two woven rattan with grid have been made, one for the top and second for the bottom of the fermenter. In order to reduce air flow during acetic phase, two airtight covers are put on each grid cover. The efficiency of the turning by this kind of rotation, coupled with homogenization of the temperature, caused by the horizontal position in the acetic phase of the fermenter, contribute to having a good proportion of well-fermented beans (83.23%). In addition, beans’pH values ranged between 4.5 and 5.5. These values are ideal for enzymatic activity in the production of the aromatic compounds inside beans. The regularity of mass loss during all fermentation makes it possible to predict the drying surface corresponding to the amount being fermented.

Keywords: Cocoa fermentation, fermenter, microbial activity, temperature, turning.

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Authors: Vahid Khorramshahi, Alireza Behrad, Neeraj K. Kanhere

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In this paper we present a new method for over-height vehicle detection in low headroom streets and highways using digital video possessing. The accuracy and the lower price comparing to present detectors like laser radars and the capability of providing extra information like speed and height measurement make this method more reliable and efficient. In this algorithm the features are selected and tracked using KLT algorithm. A blob extraction algorithm is also applied using background estimation and subtraction. Then the world coordinates of features that are inside the blobs are estimated using a noble calibration method. As, the heights of the features are calculated, we apply a threshold to select overheight features and eliminate others. The over-height features are segmented using some association criteria and grouped using an undirected graph. Then they are tracked through sequential frames. The obtained groups refer to over-height vehicles in a scene.

Keywords: Feature extraction, over-height vehicle detection, traffic monitoring, vehicle tracking.

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Authors: Le Xuan Cau

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Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.

Keywords: ArcObjects SDK for .NET, Basin average value of FFPI, Gridded basin flash flood potential index, GBFFPI map.

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Authors: Swetha Priya Darshini Thammadi, Sateesh Kumar Pisini, Sanjay Kumar Shukla

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Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM_2.5, while the AERMOD dispersion model has been used to account for missing sources of PM_2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM_2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.

Keywords: CMB, GIS, AERMOD, PM2.5, fugitive, emission inventory.

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Authors: A. Talapatra, N. R. Bandhyopadhyay, J. Datta

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In the present study, two TRIP-assisted steels were designated as A (having no Cr and Cu content) and B (having higher Ni, Cr and Cu content) heat treated under different conditions, and the correlation between its heat treatment, microstructure and properties were investigated. Micro structural examination was carried out by optical microscope and scanning electron microscope after electrolytic etching. Non-destructive electrochemical and ultrasonic testing on two TRIP-assisted steels was used to find out corrosion and mechanical properties of different alter microstructure phase’s steels. Furthermore, micro structural studies accompanied by the evaluation of mechanical properties revealed that steels having martensite phases with higher corrosive and hardness value were less sound velocity and also steel’s microstructure having finer grains that was more grain boundary was less corrosion resistance. Steel containing more Cu, Ni and Cr was less corrosive compared to other steels having same processing or microstructure.

Keywords: TRIP-assisted steels, heat treatment, corrosion, electrochemical techniques, micro-structural characterization, non-destructive (ultrasonic) technique.

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Authors: Khin Thandar Lwin, Than Htike, Zaw Min Naing

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This paper introduces an intelligent system, which can be applied in the monitoring of vehicle speed using a single camera. The ability of motion tracking is extremely useful in many automation problems and the solution to this problem will open up many future applications. One of the most common problems in our daily life is the speed detection of vehicles on a highway. In this paper, a novel technique is developed to track multiple moving objects with their speeds being estimated using a sequence of video frames. Field test has been conducted to capture real-life data and the processed results were presented. Multiple object problems and noisy in data are also considered. Implementing this system in real-time is straightforward. The proposal can accurately evaluate the position and the orientation of moving objects in real-time. The transformations and calibration between the 2D image and the actual road are also considered.

Keywords: Motion Estimation, Image Analyses, Speed Detection

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Authors: S. A. Nta, M. J. Ayotamuno, A. H. Igoni, R. N. Okparanma

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The work sought to understand the pattern of movement of contaminant from a continuous point source through soil. The soil used was sandy-loam in texture. The contaminant used was municipal solid waste landfill leachate, introduced as a point source through an entry point located at the center of top layer of the soil tank. Analyses were conducted after maturity periods of 50 and 80 days. The maximum change in chemical concentration was observed on soil samples at a radial distance of 0.25 m. Finite element approximation based model was used to assess the future prediction, management and remediation in the polluted area. The actual field data collected for the case study were used to calibrate the modeling and thus simulated the flow pattern of the pollutants through soil. MATLAB R2015a was used to visualize the flow of pollutant through the soil. Dispersion coefficient at 0.25 and 0.50 m radial distance from the point of application of leachate shows a measure of the spreading of a flowing leachate due to the nature of the soil medium, with its interconnected channels distributed at random in all directions. Surface plots of metals on soil after maturity period of 80 days shows a functional relationship between a designated dependent variable (Y), and two independent variables (X and Z). Comparison of measured and predicted profile transport along the depth after 50 and 80 days of leachate application and end of the experiment shows that there were no much difference between the predicted and measured concentrations as they were all lying close to each other. For the analysis of contaminant transport, finite difference approximation based model was very effective in assessing the future prediction, management and remediation in the polluted area. The experiment gave insight into the most likely pattern of movement of contaminant as a result of continuous percolations of the leachate on soil. This is important for contaminant movement prediction and subsequent remediation of such soils.

Keywords: Contaminant, dispersion, point or leaky source, surface plot, soil.

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Authors: Florian Kleber, Martin Kampel

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The increasing demand of gallium, indium and rare-earth elements for the production of electronics, e.g. solid state-lighting, photovoltaics, integrated circuits, and liquid crystal displays, will exceed the world-wide supply according to current forecasts. Recycling systems to reclaim these materials are not yet in place, which challenges the sustainability of these technologies. This paper proposes a multispectral imaging system as a basis for a vision based recognition system for valuable components of electronics waste. Multispectral images intend to enhance the contrast of images of printed circuit boards (single components, as well as labels) for further analysis, such as optical character recognition and entire printed circuit board recognition. The results show, that a higher contrast is achieved in the near infrared compared to ultraviolett and visible light.

Keywords: Electronic Waste, Recycling, Multispectral Imaging, Printed Circuit Boards, Rare-Earth Elements.

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Authors: E. Fehling, P. Capewell

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In recent years, the importance of masonry glued by polyurethane adhesive has increased. In 2021, the Institute of Structural Engineering of the University of Kassel was commissioned to carry out quasi-static in-plane shear tests on prefabricated brick masonry panel systems with 2K PUR adhesive in order to investigate the load-bearing behavior during earthquakes. In addition to the usual measurement of deformations using displacement transducers, all tests were documented using an optical measuring system, which was used to determine the surface strains and deformations of the test walls. To compare the results with conventional mortar walls, additional reference tests were carried out on test specimens with thin-bed mortar joints. This article summarizes the results of the test program and provides a comparison between the load-bearing behavior of masonry bonded with polyurethane adhesive and thin-bed mortar in order to enable realistic non-linear modeling.

Keywords: Glued Masonry, in-plane tests, shear resistance, polyurethane adhesive.

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Authors: Toshinori Takabatake, Yoshikazu Komano

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Recently, the improvements in processing performance of a computer and in high speed communication of an optical fiber have been achieved, so that the amount of data which are processed by a computer and flowed on a network has been increasing greatly. However, in a client-server system, since the server receives and processes the amount of data from the clients through the network, a load on the server is increasing. Thus, there are needed to introduce a server with high processing ability and to have a line with high bandwidth. In this paper, concerning to P2P networks to resolve the load on a specific server, a criterion called an Indexed-Priority Metric is proposed and its performance is evaluated. The proposed metric is to allocate some files to each node. As a result, the load on a specific server can distribute them to each node equally well. A P2P file sharing system using the proposed metric is implemented. Simulation results show that the proposed metric can make it distribute files on the specific server.

Keywords: peer-to-peer, file-sharing system, load-balancing, dependability

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Authors: Anushree, Chhaya Sharma, Satish Kumar

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Catalytic wet air oxidation (CWAO) is normally carried out at elevated temperature and pressure. This work investigates the potential of NiO-CeO₂ nano-catalyst in CWAO of paper industry wastewater under milder operating conditions of 90 °C and 1 atm. The NiO-CeO₂ nano-catalysts were synthesized by a simple co-precipitation method and characterized by X-ray diffraction (XRD), before and after use, in order to study any crystallographic change during experiment. The extent of metal-leaching from the catalyst was determined using the inductively coupled plasma optical emission spectrometry (ICP-OES). The catalytic activity of nano-catalysts was studied in terms of total organic carbon (TOC), adsorbable organic halides (AOX) and chlorophenolics (CHPs) removal. Interestingly, mixed oxide catalysts exhibited higher activity than the corresponding single-metal oxides. The maximum removal efficiency was achieved with Ce₄₀Ni₆₀ catalyst. The results indicate that the CWAO process is efficient in removing the priority organic pollutants from wastewater, as it exhibited up to 59% TOC, 55% AOX, and 54 % CHPs removal.

Keywords: Nano-materials, NiO-CeO2, wastewater, wet air oxidation.

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Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

Abstract:

The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: CNC milling, CNC turning, surface roughness, Taguchi analysis.

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Authors: Banashree N. P., R. Vasanta

Abstract:

Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.

Keywords: OCR, Global Feature, End-Points, Neuro-Memetic model.

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