Search results for: multivariate exponentially weighted moving average

Authors: Belaynesh Chekol, Numan Çelebi

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The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

Procedia PDF Downloads 277

Authors: Naydelis Brito Suárez, Deni Librado Torres Román, Fernando Hermosillo Reynoso

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Automatic detection and generation of a dynamic ROI (Region of Interest) in vehicle traffic surveillance videos based on a static camera in Intelligent Transportation Systems is challenging for computer vision-based systems. The dynamic ROI, being a changing ROI, should capture any other moving object located outside of a static ROI. In this work, the video is represented by a Tensor model composed of a Background and a Foreground Tensor, which contains all moving vehicles or objects. The values of each pixel over a time interval are represented by time series, and some pixel rows were selected. This paper proposes a pixel entropy-based algorithm for automatic detection and generation of a dynamic ROI in traffic videos under the assumption of two types of theoretical pixel entropy behaviors: (1) a pixel located at the road shows a high entropy value due to disturbances in this zone by vehicle traffic, (2) a pixel located outside the road shows a relatively low entropy value. To study the statistical behavior of the selected pixels, detecting the entropy changes and consequently moving objects, Shannon, Tsallis, and Approximate entropies were employed. Although Tsallis entropy achieved very high results in real-time, Approximate entropy showed results slightly better but in greater time.

Keywords: convex hull, dynamic ROI detection, pixel entropy, time series, moving objects

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Authors: Guoyu Wang, Meilian Zhang, Chunhui LI, Bing Ren

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In recent decades, a variety of floating structures have played a crucial role in ocean and marine engineering, such as ships, offshore platforms, floating breakwaters, fish farms, floating airports, etc. It is common for floating structures to suffer from loadings under waves, and the responses of the structures mounted in marine environments have a significant relation to the wave impacts. The interaction between surface waves and floating structures is one of the important issues in ship or marine structure design to increase performance and efficiency. With the progress of computational fluid dynamics, a number of numerical models based on the NS equations in the time domain have been developed to explore the above problem, such as the finite difference method or the finite volume method. Those traditional numerical simulation techniques for moving bodies are grid-based, which may encounter some difficulties when treating a large free surface deformation and a moving boundary. In these models, the moving structures in a Lagrangian formulation need to be appropriately described in grids, and the special treatment of the moving boundary is inevitable. Nevertheless, in the mesh-based models, the movement of the grid near the structure or the communication between the moving Lagrangian structure and Eulerian meshes will increase the algorithm complexity. Fortunately, these challenges can be avoided by the meshless particle methods. In the present study, a moving particle semi-implicit model is explored for the numerical simulation of fluid–structure interaction with surface flows, especially for coupling of fluid and moving rigid body. The equivalent momentum transfer method is proposed and derived for the coupling of fluid and rigid moving body. The structure is discretized into a group of solid particles, which are assumed as fluid particles involved in solving the NS equation altogether with the surrounding fluid particles. The momentum conservation is ensured by the transfer from those fluid particles to the corresponding solid particles. Then, the position of the solid particles is updated to keep the initial shape of the structure. Using the proposed method, the motions of a free-floating body in regular waves are numerically studied. The wave surface evaluation and the dynamic response of the floating body are presented. There is good agreement when the numerical results, such as the sway, heave, and roll of the floating body, are compared with the experimental and other numerical data. It is demonstrated that the presented MPS model is effective for the numerical simulation of fluid-structure interaction.

Keywords: floating body, fluid structure interaction, MPS, particle method, waves

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Authors: T. Francis Thamburaj, A. Aloysius

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Polymorphism is one of the main pillars of the object-oriented paradigm. It induces hidden forms of class dependencies which may impact software quality, resulting in higher cost factor for comprehending, debugging, testing, and maintaining the software. In this paper, a new cognitive complexity metric called Cognitive Weighted Polymorphism Factor (CWPF) is proposed. Apart from the software structural complexity, it includes the cognitive complexity on the basis of type. The cognitive weights are calibrated based on 27 empirical studies with 120 persons. A case study and experimentation of the new software metric shows positive results. Further, a comparative study is made and the correlation test has proved that CWPF complexity metric is a better, more comprehensive, and more realistic indicator of the software complexity than Abreu’s Polymorphism Factor (PF) complexity metric.

Keywords: cognitive complexity metric, object-oriented metrics, polymorphism factor, software metrics

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Authors: Sajith Sajeev, Brenton McLaury, Siamack Shirazi

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In the petroleum industry, solid particles are often present along with the produced fluids. It is imperative to keep particles from accumulating in flow lines. In this study, various experiments are conducted to study sand particle transport, where critical velocity is defined as the average fluid velocity to keep particles continuously moving. Many parameters related to the fluid, particles and pipe affect the transport process. Experimental results are presented varying the particle concentration. Additionally, CFD simulations using a discrete element modeling (DEM) approach are presented to compare with experimental result.

Keywords: particle transport, critical velocity, CFD, DEM

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Authors: Sara ElElimy, Samir Moustafa

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Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

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Authors: Oğuzhan Urhan

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In this paper, an improved motion estimation (ME) approach based on weighted constrained one-bit transform is proposed for block-based ME employed in video encoders. Binary ME approaches utilize low bit-depth representation of the original image frames with a Boolean exclusive-OR based hardware efficient matching criterion to decrease computational burden of the ME stage. Weighted constrained one-bit transform (WC‑1BT) based approach improves the performance of conventional C-1BT based ME employing 2-bit depth constraint mask instead of a 1-bit depth mask. In this work, the range of constraint mask is further extended to increase ME performance of WC-1BT approach. Experiments reveal that the proposed method provides better ME accuracy compared existing similar ME methods in the literature.

Keywords: fast motion estimation; low-complexity motion estimation, video coding

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Authors: C. Annapurna, Rao M. Srinivasa, Bhanu C. H. Vijaya, M. Sivalakshmi, Rao P. V. Surya

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A study on the community structure of meiobenthic fauna was undertaken during three cruises (June 2008, October 2008 and March 2009). Ten stations at depth between 10 and 40 m off Pudimadaka in Visakhapatnam (Lat.17º29′12″N and Long. 83º00′09″), East coast of India were investigated. Ninety species representing 3 major (meiofaunal) taxa namely foraminifera (2), copepoda (9), nematoda (58) and polychaeta (21) were encountered. Overall, meiofaunal (mean) abundance ranged from 2 individuals to 63 ind. 10cm-² with an average of 24.3 ind.10cm-2. The meiobenthic biomass varied between 0.135 to 0.48 mg.10cm-2 with an average 0.27 ± 0.12. On the whole, nematodes constituted 73.62% of the meiofauna in terms of numerical abundance. Shannon –Wiener index values were 2.053 ± 0.64 (June, 2008), 2.477 ± 0.177 (October 2008) and 2.2815±0.24 (March 2009). Multivariate analyses were used to define the most important taxon in nematode assemblages. Three nematode associations could be recognized off Pudimadaka coast, namely Laimella longicaudata, Euchromodora vulgaris and Sabatieria elongata assemblage (June, 2008); Catanema sp. and Leptosomatum sp. assemblage (October 2008) assemblage; Sabatieria sp. and Setosabatieria sp. assemblage (March 2009). Canonical correspondence analysis showed that temperature, organic matter, silt and mean particle diameter were important in controlling nematode community structure.

Keywords: meiofauna, marine nematode, biodiversity, community structure, India

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Authors: M. Reni Sagayaraj, S. Anand Gnana Selvam, R. Reynald Susainathan

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This study analyzed a queueing system with blocking and no waiting line. The customers arrive according to a Poisson process and the service times follow exponential distribution. There are two non-identical servers in the system. The queue discipline is FCFS, and the customers select the servers on fastest server first (FSF) basis. The service times are exponentially distributed with parameters μ1 and μ2 at servers I and II, respectively. Besides, the catastrophes occur in a Poisson manner with rate γ in the system. When server I is busy or blocked, the customer who arrives in the system leaves the system without being served. Such customers are called lost customers. The probability of losing a customer was computed for the system. The explicit time dependent probabilities of system size are obtained and a numerical example is presented in order to show the managerial insights of the model. Finally, the probability that arriving customer finds system busy and average number of server busy in steady state are obtained numerically.

Keywords: queueing system, blocking, poisson process, heterogeneous servers, queue discipline FCFS, busy period

Procedia PDF Downloads 499

Authors: Vishal D. Bharud, B. J. Patil, S. S. Dahiwale, V. N. Bhoraskar, S. D. Dhole

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Photon induced average reaction cross section of ¹¹¹Cd (γ, γ`) ¹¹¹ᵐCd reaction was experimentally determined for the bremsstrahlung energy spectrum of 6 MeV by utilizing the activation and offline γ-ray spectrometric techniques. The 6 MeV electron accelerator Racetrack Microtron of Savitribai Phule Pune University, Pune was used for the experimental work. The bremsstrahlung spectrum generated by bombarding 6 MeV electrons on lead target was theoretically estimated by FLUKA code. Bremsstrahlung radiation can have energies exceeding the threshold of the particle emission, which is normally above 6 MeV. Photons of energies below the particle emission threshold undergo absorption into discrete energy levels, with possibility of exciting nuclei to excited state including metastable state. The ¹¹¹Cd (γ, γ`) ¹¹¹ᵐCd reaction cross sections were calculated at different energies of bombarding Photon by using the TALYS 1.8 computer code with a default parameter. The focus of the present work was to study the (γ,γ’) reaction for exciting ¹¹¹Cd nuclei to metastable states which have threshold energy below 3 MeV. The flux weighted average cross section was obtained from the theoretical values of TALYS 1.8 and TENDL 2017 and is found to be in good agreement with the present experimental cross section.

Keywords: bremsstrahlung, cross section, FLUKA, TALYS-1.8

Procedia PDF Downloads 166

Authors: K. A. Bindu, T. V. Raja, P. M. Rojan, A. Siby

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The multivariate path coefficient approach was employed to study the effects of various production and reproduction traits on the slaughter body weight of rabbits. Information on 562 rabbits maintained at the university rabbit farm attached to the Centre for Advanced Studies in Animal Genetics, and Breeding, Kerala Veterinary and Animal Sciences University, Kerala State, India was utilized. The manifest variables used in the study were age and weight of dam, birth weight, litter size at birth and weaning, weight at first, second and third months. The linear multiple regression analysis was performed by keeping the slaughter weight as the dependent variable and the remaining as independent variables. The model explained 48.60 percentage of the total variation present in the market weight of the rabbits. Even though the model used was significant, the standardized beta coefficients for the independent variables viz., age and weight of the dam, birth weight and litter sizes at birth and weaning were less than one indicating their negligible influence on the slaughter weight. However, the standardized beta coefficient of the second-month body weight was maximum followed by the first-month weight indicating their major role on the market weight. All the other factors influence indirectly only through these two variables. Hence it was concluded that the slaughter body weight can be predicted using the first and second-month body weights. The principal components were also developed so as to achieve more accuracy in the prediction of market weight of rabbits.

Keywords: component analysis, multivariate, slaughter, regression

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Authors: Debjani Chakraborty, Abhijit Chatterjee, Aishwaryaprajna

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Posynomials, a special type of polynomials, having singularities, pose difficulties while solving geometric programming problems. In this paper, a methodology has been proposed and used to obtain extreme values for geometric programming problems by nth degree polynomial interpolation technique. Here the main idea to optimise the posynomial is to fit a best polynomial which has continuous gradient values throughout the range of the function. The approximating polynomial is smoothened to remove the discontinuities present in the feasible region and the objective function. This spatial interpolation method is capable to optimise univariate and multivariate geometric programming problems. An example is solved to explain the robustness of the methodology by considering a bivariate nonlinear geometric programming problem. This method is also applicable for signomial programming problem.

Keywords: geometric programming problem, multivariate optimisation technique, posynomial, spatial interpolation

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Authors: Ijaz Ahmed, Anwar Zada, Muhammad Waqas, M. U. Ashraf

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We demonstrate the performance of a very efficient tagger applies on hadronically decaying top quark pairs as signal based on deep neural network algorithms and compares with the QCD multi-jet background events. A significant enhancement of performance in boosted top quark events is observed with our limited computing resources. We also compare modern machine learning approaches and perform a multivariate analysis of boosted top-pair as well as single top quark production through weak interaction at √s = 14 TeV proton-proton Collider. The most relevant known background processes are incorporated. Through the techniques of Boosted Decision Tree (BDT), likelihood and Multlayer Perceptron (MLP) the analysis is trained to observe the performance in comparison with the conventional cut based and count approach

Keywords: top tagger, multivariate, deep learning, LHC, single top

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Authors: S. Turkan

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In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.

Keywords: data envelopment analysis, super efficiency, logistic regression, financial ratios

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Authors: Punitha Periyasamy, Mahalingam Sudalaimuthu, Sachikanta Nanda, Arasu Sundaram

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India holds 17.5% of the world’s population but has only 2% of the total geographical area of the world where 27.35% of the area is categorized as wasteland due to lack of or less groundwater. So there is a demand for excessive groundwater for agricultural and non agricultural activities to balance its growth rate. With this in mind, an attempt is made to find the groundwater potential zone in Gomukhi river sub basin of Vellar River basin, TamilNadu, India covering an area of 1146.6 Sq.Km consists of 9 blocks from Peddanaickanpalayam to Villupuram fall in the sub basin. The thematic maps such as Geology, Geomorphology, Lineament, Landuse, and Landcover and Drainage are prepared for the study area using IRS P6 data. The collateral data includes rainfall, water level, soil map are collected for analysis and inference. The digital elevation model (DEM) is generated using Shuttle Radar Topographic Mission (SRTM) and the slope of the study area is obtained. ArcGIS 10.1 acts as a powerful spatial analysis tool to find out the ground water potential zones in the study area by means of weighted overlay analysis. Each individual parameter of the thematic maps are ranked and weighted in accordance with their influence to increase the water level in the ground. The potential zones in the study area are classified viz., Very Good, Good, Moderate, Poor with its aerial extent of 15.67, 381.06, 575.38, 174.49 Sq.Km respectively.

Keywords: ArcGIS, DEM, groundwater, recharge, weighted overlay

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Authors: H. İmrek, O. Corumluoglu, B. Akdemir, I. Sanlioglu

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It is important to be able to determine the heading direction of a moving vehicle with respect to a distant location. Additionally, it is important to be able to direct a rotating platform on a moving vehicle towards a distant position or location on the earth surface, especially for applications such as determination of the Kaaba direction for daily Muslim prayers. GNNS offers some reasonable solutions. In this study, a functional model of such a directing system supported by GNNS is discussed, and an appropriate system is designed for these purposes. An application for directing system is done by using RTK and DGNSS. Accuracy estimations are given for this system.

Keywords: GNNS, orientation of rotating platform, vehicle orientation, prayer aid device

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Authors: Vitas Valinčius, Rolandas Uscila, Viktorija Grigaitienė, Žydrūnas Kavaliauskas, Romualdas Kėželis

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Determination of integral dynamical and energy characteristics of high-temperature gas flows is a very important task of gas-dynamic for hazardous substances destruction systems. They are also always necessary for the investigation of high-temperature turbulent flow dynamics, heat and mass transfer. It is well known that distribution of dynamical and thermal characteristics of high-temperature flows and jets is strongly related to heat flux variation over an imposed area of heating. As is visible from numerous experiments and theoretical considerations, the fundamental properties of an isothermal jet are well investigated. However, the establishment of regularities in high-temperature conditions meets certain specific behavior comparing with moderate-temperature jets and flows. Their structures have not been thoroughly studied yet, especially in the cases of plasma ambient. It is well known that the distribution of local plasma jet parameters in high temperature and isothermal jets and flows may significantly differ. High temperature axisymmetric air jet generated by atmospheric pressure DC arc plasma torch was investigated employing enthalpy probe 3.8∙10-3 m of diameter. Distribution of velocities and temperatures were established in different cross-sections of the plasma jet outflowing from 42∙10-3 m diameter pipe at the average mean velocity of 700 m∙s-1, and averaged temperature of 4000 K. It has been found that gas heating fractionally influences shape and values of a dimensionless profile of velocity and temperature in the main zone of plasma jet and has a significant influence in the initial zone of the plasma jet. The width of the initial zone of the plasma jet has been found to be lesser than in the case of isothermal flow. The relation between dynamical thickness and turbulent number of Prandtl has been established along jet axis. Experimental results were generalized in dimensionless form. The presence of convective heating shows that heat transfer in a moving high-temperature jet also occurs due to heat transfer by moving particles of the jet. In this case, the intensity of convective heat transfer is proportional to the instantaneous value of the flow velocity at a given point in space. Consequently, the configuration of the temperature field in moving jets and flows essentially depends on the configuration of the velocity field.

Keywords: plasma jet, plasma torch, heat transfer, enthalpy probe, turbulent number of Prandtl

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Authors: Elvira Mustikawati P.H., Iis Dewi Ratih, Dita Amelia

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Bojonegoro has proclaimed a policy of zero malnutrition. Therefore, as an effort to solve the cases of malnutrition children in Bojonegoro, this study used the approach geographically Mixed Weighted Regression (MGWR) to determine the factors that influence the percentage of malnourished children under five in which factors can be divided into locally influential factor in each district and global factors that influence throughout the district. Based on the test of goodness of fit models, R2 and AIC values in GWR models are better than MGWR models. R2 and AIC values in MGWR models are 84.37% and 14.28, while the GWR models respectively are 91.04% and -62.04. Based on the analysis with GWR models, District Sekar, Bubulan, Gondang, and Dander is a district with three predictor variables (percentage of vitamin A, the percentage of births assisted health personnel, and the percentage of clean water) that significantly influence the percentage of malnourished children under five.

Keywords: GWR, MGWR, R2, AIC

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Authors: Samuele Ghignoli, Valentina de Lorenzi, Gianmarco Ferri, Stefano Luin, Francesco Cardarelli

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Insulin and glucagon are the two essential hormones for maintaining proper blood glucose homeostasis, which is disrupted in Diabetes. A constantly growing research interest has been focused on the study of the subcellular structures involved in hormone secretion, namely insulin- and glucagon-containing granules, and on the mechanisms regulating their behaviour. Yet, while several successful attempts were reported describing the dynamic properties of insulin granules, little is known about their counterparts in α cells, the glucagon-containing granules. To fill this gap, we used αTC1 clone 9 cells as a model of α cells and ZIGIR as a fluorescent Zinc chelator for granule labelling. We started by using spatiotemporal fluorescence correlation spectroscopy in the form of imaging-derived mean square displacement (iMSD) analysis. This afforded quantitative information on the average dynamical and structural properties of glucagon granules having insulin granules as a benchmark. Interestingly, the iMSD sensitivity to average granule size allowed us to confirm that glucagon granules are smaller than insulin ones (~1.4 folds, further validated by STORM imaging). To investigate possible heterogeneities in granule dynamic properties, we moved from correlation spectroscopy to single particle tracking (SPT). We developed a MATLAB script to localize and track single granules with high spatial resolution. This enabled us to classify the glucagon granules, based on their dynamic properties, as ‘blocked’ (i.e., trajectories corresponding to immobile granules), ‘confined/diffusive’ (i.e., trajectories corresponding to slowly moving granules in a defined region of the cell), or ‘drifted’ (i.e., trajectories corresponding to fast-moving granules). In cell-culturing control conditions, results show this average distribution: 32.9 ± 9.3% blocked, 59.6 ± 9.3% conf/diff, and 7.4 ± 3.2% drifted. This benchmarking provided us with a foundation for investigating selected experimental conditions of interest, such as the glucagon-granule relationship with the cytoskeleton. For instance, if Nocodazole (10 μM) is used for microtubule depolymerization, the percentage of drifted motion collapses to 3.5 ± 1.7% while immobile granules increase to 56.0 ± 10.7% (remaining 40.4 ± 10.2% of conf/diff). This result confirms the clear link between glucagon-granule motion and cytoskeleton structures, a first step towards understanding the intracellular behaviour of this subcellular compartment. The information collected might now serve to support future investigations on glucagon granules in physiology and disease. Acknowledgment: This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 866127, project CAPTUR3D).

Keywords: glucagon granules, single particle tracking, correlation spectroscopy, ZIGIR

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Authors: Insaf Bellamine, Hamid Tairi

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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

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Authors: Aymen Rhouma, Khaled Hcheichi, Sami Hafsi

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The article presents an application of Fractional Model Predictive Control (FMPC) to a fractional order thermal system using Controlled Auto Regressive Integrated Moving Average (CARIMA) model obtained by discretization of a continuous fractional differential equation. Moreover, the output deviation approach is exploited to design the K -step ahead output predictor, and the corresponding control law is obtained by solving a quadratic cost function. Experiment results onto a thermal system are presented to emphasize the performances and the effectiveness of the proposed predictive controller.

Keywords: fractional model predictive control, fractional order systems, thermal system, predictive control

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Authors: Suleh Yusufu Godi, Ado Makama Adamu

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Marketing involves all the legal, physical, and economic services which are necessary in moving products from producer to consumers. The more efficient the marketing functions are performed the better the marketing system for the farmers, marketing agents, and the society at large. Rice marketing ensures the flow of product from producers to consumers in the form, time and place of need. Therefore, this study examined profitability of milled rice marketing in Gombe metropolis, Gombe State. Data were collected using structured questionnaires from ninety randomly selected rice marketers in Gombe metropolis. The data were analyzed using descriptive statistics, farm budget technique and regression analysis. The study revealed the total rice marketing cost incurred by rice marketers to be N6, 610,214.70. This gave an average of N73, 446.83 per marketer and N37.30 per Kilogram of rice. The Gross Income for rice marketers in Gombe metropolis was N15, 064,600.00. This value gave an average of N167, 384.44 per rice marketer or N85.00 per kilogram of rice. The study also revealed net income for all rice marketers to be N8, 454,385.30. This gave an average of N93, 937.61 per rice marketer or N47.70 per Kilogram of rice. The study further revealed a marketing margin, marketing efficiency and return per naira invested on rice marketing to be 39.30%, 150.16% and N0.56, respectively. The result of regression analysis shows that age, sex and cost of transportation are positive and significantly affect marketing margin of rice marketers in Gombe Metropolis. However, the main constraints to rice marketing in Gombe metropolis include inadequate electricity, capital, high transportation cost, instability of prices and low patronage among others. The study recommends provision of adequate electrical power supply in the State especially the State capital and also encouraging rice marketers in Gombe metropolis to form cooperative societies so as to have easy access to credit facilities especially from the formal sources.

Keywords: rice marketers, milled rice, cost and return, marketing margin, efficiency, profitability

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Authors: Kanayo Kenneth Asogwa

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The influence of the flow of nanoparticles in nanofluids across a vertical surface is significant, and its application in medical sciences, engineering, pharmaceutical, and food industries is enormous & widely published. However, the comparative examination of alumina nanoparticles with cupric nanoparticles past a rapid progressive Riga plate remains unknown. Thus, this report investigates water-based alumina and cupric nanoparticles passing through an exponentially accelerated Riga plate. Nanofluids containing copper (II) oxide (CuO) and aluminum oxide (Al2O3) nanoparticles are considered. The Laplace transform technique is used to solve the partial differential equations guiding the flow. The effect of various factors on skin friction coefficient, Nusselt number, velocity and temperature profiles is investigated and reported in tabular and graphical form. The upsurge of Modified Hartmann number and radiative impact improves copper (II) oxide nanofluid compared to aluminum oxide nanofluid due to Lorentz force and since CuO is a better heat conductor. At the same time, heat absorption and reactive species favor a slight decline in Alumina nanofluid than Cupric nanofluid in the thermal and velocity fields. The higher density of Cupric nanofluid is enhanced by increasing nanoparticle volume fraction over Alumina nanofluid with a decline in velocity distribution.

Keywords: alumina, cupric, nanoparticles, water-based

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Authors: Sofia Papadimitriou

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INTRODUCTION: The differential diagnosis between acute viral and bacterial infections is an important cost-effectiveness parameter at the stage of the treatment process in order to achieve the maximum benefits in therapeutic intervention by combining the minimum cost to ensure the proper use of antibiotics.The discovery of sensitive and robust molecular diagnostic tests in response to the role of the host in infections has enhanced the accurate diagnosis and differentiation of infections. METHOD: The study used a sample of six independent blood samples (total=756) which are associated with human proteins-proteins, each of which at the transcription stage expresses a different response in the host network between viral and bacterial infections.Τhe individual blood samples are subjected to a sequence of computer filters that identify a gene panel corresponding to an autonomous diagnostic score. The data set and the correspondence of the gene panel to the diagnostic patents a new Bangalore -Viral Bacterial (BL-VB). FINDING: We use a biomarker based on the blood of 10 genes(Panel-VB) that are an important prognostic value for the detection of viruses from bacterial infections with a weighted average AUROC of 0.97(95% CL:0.96-0.99) in eleven independent samples (sets n=898). We discovered a base with a patient score (VB 10 ) according to the table, which is a significant diagnostic value with a weighted average of AUROC 0.94(95% CL: 0.91-0.98) in 2996 patient samples from 56 public sets of data from 19 different countries. We also studied VB 10 in a new cohort of South India (BL-VB,n=56) and found 97% accuracy in confirmed cases of viral and bacterial infections. We found that VB 10 (a)accurately identifies the type of infection even in unspecified cases negative to the culture (b) shows its clinical condition recovery and (c) applies to all age groups, covering a wide range of acute bacterial and viral infectious, including non-specific pathogens. We applied our VB 10 rating to publicly available COVID 19 data and found that our rating diagnosed viral infection in patient samples. RESULTS: Τhe results of the study showed the diagnostic power of the biomarker VB 10 as a diagnostic test for the accurate diagnosis of acute infections in recovery conditions. We look forward to helping you make clinical decisions about prescribing antibiotics and integrating them into your policies management of antibiotic stewardship efforts. CONCLUSIONS: Overall, we are developing a new property of the RNA-based biomarker and a new blood test to differentiate between viral and bacterial infections to assist a physician in designing the optimal treatment regimen to contribute to the proper use of antibiotics and reduce the burden on antimicrobial resistance, AMR.

Keywords: acute infections, antimicrobial resistance, biomarker, blood transcriptome, systems biology, classifier diagnostic score

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Authors: Yung-Chung Chuang

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The cultural layers of archaeological sites are mainly affected by surface land use, land cover, and root system of surface vegetation. For this reason, continuous monitoring of land use and land cover change is important for archaeological sites protection and management. However, in actual operation, on-site investigation and orthogonal photograph interpretation require a lot of time and manpower. For this reason, it is necessary to perform a good alternative for surface vegetation survey in an automated or semi-automated manner. In this study, we applied semi-automatic digital aerial survey technology and canopy characters classification with very high-resolution aerial photographs for surface vegetation interpretation of archaeological sites. The main idea is based on different landscape or forest type can easily be distinguished with canopy characters (e.g., specific texture distribution, shadow effects and gap characters) extracted by semi-automatic image classification. A novel methodology to classify the shape of canopy characters using landscape indices and multivariate statistics was also proposed. Non-hierarchical cluster analysis was used to assess the optimal number of canopy character clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy character classification (seven categories). Therefore, people could easily predict the forest type and vegetation land cover by corresponding to the specific canopy character category. The results showed that the semi-automatic classification could effectively extract the canopy characters of forest and vegetation land cover. As for forest type and vegetation type prediction, the average prediction accuracy reached 80.3%~91.7% with different sizes of test frame. It represented this technology is useful for archaeological site survey, and can improve the classification efficiency and data update rate.

Keywords: digital aerial survey, canopy characters classification, archaeological sites, multivariate statistics

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Authors: Hyun-Woo Cho

Abstract:

The detection and identification of multivariate manufacturing processes are quite important in order to maintain good product quality. Unusual behaviors or events encountered during its operation can have a serious impact on the process and product quality. Thus they should be detected and identified as soon as possible. This paper focused on the efficient representation of process measurement data in detecting and identifying abnormalities. This qualitative method is effective in representing fault patterns of process data. In addition, it is quite sensitive to measurement noise so that reliable outcomes can be obtained. To evaluate its performance a simulation process was utilized, and the effect of adopting linear and nonlinear methods in the detection and identification was tested with different simulation data. It has shown that the use of a nonlinear technique produced more satisfactory and more robust results for the simulation data sets. This monitoring framework can help operating personnel to detect the occurrence of process abnormalities and identify their assignable causes in an on-line or real-time basis.

Keywords: detection, monitoring, identification, measurement data, multivariate techniques

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Authors: Jeh-Nan Pan, Chung-I Li

Abstract:

Measurement system analysis (MSA) plays an important role in helping organizations to improve their product quality. Generally speaking, the gauge repeatability and reproducibility (GRR) study is performed according to the MSA handbook stated in QS9000 standards. Usually, GRR study for assessing the adequacy of gauge variation needs to be conducted prior to the process capability analysis. Traditional MSA only considers a single quality characteristic. With the advent of modern technology, industrial products have become very sophisticated with more than one quality characteristic. Thus, it becomes necessary to perform multivariate GRR analysis for a measurement system when collecting data with multiple responses. In this paper, we take the correlation coefficients among tolerances into account to revise the multivariate precision-to-tolerance (P/T) ratio as proposed by Majeske (2008). We then compare the performance of our revised P/T ratio with that of the existing ratios. The simulation results show that our revised P/T ratio outperforms others in terms of robustness and proximity to the actual value. Moreover, the optimal allocation of several parameters such as the number of quality characteristics (v), sample size of parts (p), number of operators (o) and replicate measurements (r) is discussed using the confidence interval of the revised P/T ratio. Finally, a standard operating procedure (S.O.P.) to perform the GRR study for multivariate measurement systems is proposed based on the research results. Hopefully, it can be served as a useful reference for quality practitioners when conducting such study in industries. Measurement system analysis (MSA) plays an important role in helping organizations to improve their product quality. Generally speaking, the gauge repeatability and reproducibility (GRR) study is performed according to the MSA handbook stated in QS9000 standards. Usually, GRR study for assessing the adequacy of gauge variation needs to be conducted prior to the process capability analysis. Traditional MSA only considers a single quality characteristic. With the advent of modern technology, industrial products have become very sophisticated with more than one quality characteristic. Thus, it becomes necessary to perform multivariate GRR analysis for a measurement system when collecting data with multiple responses. In this paper, we take the correlation coefficients among tolerances into account to revise the multivariate precision-to-tolerance (P/T) ratio as proposed by Majeske (2008). We then compare the performance of our revised P/T ratio with that of the existing ratios. The simulation results show that our revised P/T ratio outperforms others in terms of robustness and proximity to the actual value. Moreover, the optimal allocation of several parameters such as the number of quality characteristics (v), sample size of parts (p), number of operators (o) and replicate measurements (r) is discussed using the confidence interval of the revised P/T ratio. Finally, a standard operating procedure (S.O.P.) to perform the GRR study for multivariate measurement systems is proposed based on the research results. Hopefully, it can be served as a useful reference for quality practitioners when conducting such study in industries.

Keywords: gauge repeatability and reproducibility, multivariate measurement system analysis, precision-to-tolerance ratio, Gauge repeatability

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Authors: A. Harras, A. Tsuji, K. Terada

Abstract:

Tracking of moving people has gained a matter of great importance due to rapid technological advancements in the field of computer vision. The objective of this study is to design a motion based detection and tracking multiple walking pedestrians randomly in different directions. In our proposed method, Gaussian mixture model (GMM) is used to determine moving persons in image sequences. It reacts to changes that take place in the scene like different illumination; moving objects start and stop often, etc. Background noise in the scene is eliminated through applying morphological operations and the motions of tracked people which is determined by using the Kalman filter. The Kalman filter is applied to predict the tracked location in each frame and to determine the likelihood of each detection. We used a benchmark data set for the evaluation based on a side wall stationary camera. The actual scenes from the data set are taken on a street including up to eight people in front of the camera in different two scenes, the duration is 53 and 35 seconds, respectively. In the case of walking pedestrians in close proximity, the proposed method has achieved the detection ratio of 87%, and the tracking ratio is 77 % successfully. When they are deferred from each other, the detection ratio is increased to 90% and the tracking ratio is also increased to 79%.

Keywords: automatic detection, tracking, pedestrians, counting

Procedia PDF Downloads 254

Authors: Wedad Albalawi

Abstract:

The mathematical inequalities have been the core of mathematical study and used in almost all branches of mathematics as well in various areas of science and engineering. The inequalities by Hardy, Littlewood and Polya were the first significant composition of several science. This work presents fundamental ideas, results and techniques and it has had much influence on research in various branches of analysis. Since 1934, various inequalities have been produced and studied in the literature. Furthermore, some inequalities have been formulated by some operators; in 1989, weighted Hardy inequalities have been obtained for integration operators. Then, they obtained weighted estimates for Steklov operators that were used in the solution of the Cauchy problem for the wave equation. They were improved upon in 2011 to include the boundedness of integral operators from the weighted Sobolev space to the weighted Lebesgue space. Some inequalities have been demonstrated and improved using the Hardy–Steklov operator. Recently, a lot of integral inequalities have been improved by differential operators. Hardy inequality has been one of the tools that is used to consider integrity solutions of differential equations. Then dynamic inequalities of Hardy and Coposon have been extended and improved by various integral operators. These inequalities would be interesting to apply in different fields of mathematics (functional spaces, partial differential equations, mathematical modeling). Some inequalities have been appeared involving Copson and Hardy inequalities on time scales to obtain new special version of them. A time scale is defined as a closed subset contains real numbers. Then the inequalities of time scales version have received a lot of attention and has had a major field in both pure and applied mathematics. There are many applications of dynamic equations on time scales to quantum mechanics, electrical engineering, neural networks, heat transfer, combinatorics, and population dynamics. This study focuses on double integrals to obtain new time-scale inequalities of Copson driven by Steklov operator. They will be applied in the solution of the Cauchy problem for the wave equation. The proof can be done by introducing restriction on the operator in several cases. In addition, the obtained inequalities done by using some concepts in time scale version such as time scales calculus, theorem of Fubini and the inequality of H¨older.

Keywords: time scales, inequality of Hardy, inequality of Coposon, Steklov operator

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Authors: Walid Chkili

Abstract:

This paper investigates the dynamic relationship between gold and stock markets using data for BRICS counties. For this purpose, we estimate three multivariate GARCH models (namely CCC, DCC and BEKK) for weekly stock and gold data. Our main objective is to examine time variations in conditional correlations between the two assets and to check the effectiveness use of gold as a hedge for equity markets. Empirical results reveal that dynamic conditional correlations switch between positive and negative values over the period under study. This correlation is negative during the major financial crises suggesting that gold can act as a safe haven during the major stress period of stock markets. We also evaluate the implications for portfolio diversification and hedging effectiveness for the pair gold/stock. Our findings suggest that adding gold in the stock portfolio enhance its risk-adjusted return.

Keywords: gold, financial markets, hedge, multivariate GARCH

Procedia PDF Downloads 468