Search results for: linear trend flow

Authors: Ilya Kavalchuk, Mehdi Seyedmahmoudian, Ben Horan, Aman Than Oo, Alex Stojcevski

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The power electronic components within Electric Vehicles (EV) need to operate in several important modes. Some modes directly influence safety, while others influence vehicle performance. Given the variety of functions and operational modes required of the power electronics, it needs to meet efficiency requirements to minimize power losses. Another challenge in the control and construction of such systems is the ability to support bidirectional power flow. This paper considers the construction, operation, and feasibility of available converters for electric vehicles with feasible configurations of electrical buses and loads. This paper describes logic and control signals for the converters for different operations conditions based on the efficiency and energy usage bases.

Keywords: electric vehicles, electrical machines control, power electronics, powerflow regulations

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Authors: Anas H. Aljemely, Jianping Xuan

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Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

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Authors: Hefzollah Mohammadian, Mohammad Bagher Heidari

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This paper deals with the technical and economic effects of various parameters on the performance of heat recovery system on gas complex turbo generator. Given the importance of this issue, that is the main goal of economic efficiency and reduces costs; this project has been implemented similar plans in which the target is the implementation of specific patterns. The project will also help us in the process of gas refineries and the actual efficiency of the process after adding a system to analyze the turbine and predict potential problems and fix them and take appropriate measures according to the results of simulation analysis and results of the process gain. The results of modeling and the effect of different parameters on this line, have been done using Thermo Flow.

Keywords: turbo compressor, turbo generator, heat recovery boiler, gas turbines

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Authors: O. S. Adeyemi, C. G. Whiteley

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The present study determined the toxic potential of metal nanoparticles in cell culture system. Silver and gold nanoparticles were synthesized and characterized following established "green" protocols. The synthesized nanoparticles, in varying concentrations ranging from 0.1–100 µM were evaluated for toxicity in metastatic MDA-MB-231 cells. The nanoparticles promoted a generation of reactive oxygen species and reduced cell viability to less than 50% in the demonstration of cellular toxicity. The nanoparticles; gold and the silver-gold mixture had IC50 values of 56.65 and 18.44 µM respectively. The IC50 concentration for silver nanoparticles could not be determined. Furthermore, the probe of the cell death using flow cytometry and confocal microscopy revealed the partial involvement of apoptosis as well as necrosis. Our results revealed cellular toxicity caused by the nanoparticles but the mechanism remains yet undefined.

Keywords: cell death, nanomedicine, nanotoxicology, toxicity

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Authors: B. T. Naveen Kumar, Anuj Tyagi, Niraj Kumar Singh, Visanu Boonyawiwat, A. H. Shanthanagouda, Orawan Boodde, K. M. Shankar, Prakash Patil, Shubhkaramjeet Kaur

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Early mortality syndrome (EMS)/Acute Hepatopancreatic Necrosis Disease (AHPND) has emerged as a major obstacle for the shrimp farming around the world. It is caused by a strain of Vibrio parahaemolyticus. The possible preventive and control measure is, early and rapid detection of the pathogen in the broodstock, post-larvae and monitoring the shrimp during the culture period. Polymerase chain reaction (PCR) based early detection methods are good, but they are costly, time taking and requires a sophisticated laboratory. The present study was conducted to develop a simple, sensitive and rapid diagnostic farmer level kit for the reliable detection of AHPND in shrimp. A panel of monoclonal antibodies (MAbs) were raised against the recombinant Pir B protein (rPirB). First, an immunodot was developed by using MAbs G3B8 and Mab G3H2 which showed specific reactivity to purified r-PirB protein with no cross-reactivity to other shrimp bacterial pathogens (AHPND free Vibrio parahaemolyticus (Indian strains), V. anguillarum, WSSV, Aeromonas hydrophila, and Aphanomyces invadans). Immunodot developed using Mab G3B8 is more sensitive than that with the Mab G3H2. However, immunodot takes almost 2.5 hours to complete with several hands-on steps. Therefore, the flow-through assay (FTA) was developed by using a plastic cassette containing the nitrocellulose membrane with absorbing pads below. The sample was dotted in the test zone on the nitrocellulose membrane followed by continuos addition of five solutions in the order of i) blocking buffer (BSA) ii) primary antibody (MAb) iii) washing Solution iv) secondary antibody and v) chromogen substrate (TMB) clear purple dots against a white background were considered as positive reactions. The FTA developed using MAbG3B8 is more sensitive than that with MAb G3H2. In FTA the two MAbs showed specific reactivity to purified r-PirB protein and not to other shrimp bacterial pathogens. The FTA is simple to farmer/field level, sensitive and rapid requiring only 8-10 min for completion. Tests can be developed to kits, which will be ideal for use in biosecurity, for the first line of screening (at the port or pond site) and during monitoring and surveillance programmes overall for the good management practices to reduce the risk of the disease.

Keywords: acute hepatopancreatic necrosis disease, AHPND, flow-through assay, FTA, farmer level, immunodot, pond site, shrimp

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Authors: Abdullah Bajelan, Adel Akbarimajd

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Object manipulation techniques in robotics can be categorized in two major groups including manipulation with grasp and manipulation without grasp. The original aim of this paper is to develop an object manipulation method where in addition to being grasp-less, the manipulation task is done in a passive approach. In this method, linear and angular positions of the object are changed and its manipulation path is controlled. The manipulation path is a helix track with constant radius and incline. The method presented in this paper proposes a system which has not the actuator and the active controller. So this system requires a passive mechanical intelligence to convey the object from the status of the source along the specified path to the goal state. This intelligent is created based on utilizing the geometry of the system components. A general set up for the components of the system is considered to satisfy the required conditions. Then after kinematical analysis, detailed dimensions and geometry of the mechanism is obtained. The kinematical results are verified by simulation in ADAMS.

Keywords: mechanical intelligence, object manipulation, passive mechanism, passive non-prehensile manipulation

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Authors: Pratiksha Saxena, Dipti Singh, Neha Khanna

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A self-organizing migrating genetic algorithm(C-SOMGA) is developed for animal diet formulation. This paper presents animal diet formulation using stochastic and genetic algorithm. Tri-objective models for cost minimization and shelf life maximization are developed. These objectives are achieved by combination of stochastic programming and C-SOMGA. Stochastic programming is used to introduce nutrient variability for animal diet. Self-organizing migrating genetic algorithm provides exact and quick solution and presents an innovative approach towards successful application of soft computing technique in the area of animal diet formulation.

Keywords: animal feed ration, feed formulation, linear programming, stochastic programming, self-migrating genetic algorithm, C-SOMGA technique, shelf life maximization, cost minimization, nutrient maximization

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Authors: Mostafa Ghasemi, Andrew Urquhart

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In this study, fluorescent carbon dots (CDs) were synthesized in a green way using a one-step hydrothermal method. Carbon dots are carbon-based nanomaterials with a size of less than 10 nm, unique structure, and excellent properties such as low toxicity, good biocompatibility, tunable fluorescence, excellent photostability, and easy functionalization. These properties make them a good candidate to use in different fields such as biological sensing, photocatalysis, photodynamic, and drug delivery. Fourier transformed infrared (FTIR) spectra approved OH/NH groups on the surface of the as-synthesized CDs, and UV-vis spectra showed excellent fluorescence quenching effect of Fe (III) ion on the as-synthesized CDs with high selectivity detection compared with other metal ions. The probe showed a linear response concentration range (0–2.0 mM) to Fe (III) ion, and the limit of detection was calculated to be about 0.50 μM. In addition, CDs also showed good sensitivity to the pH value in the range from 2 to 14, indicating great potential as a pH sensor.

Keywords: carbon dots, fluorescence, pH sensing, metal ions sensor

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Novawiguna Kemalasari, Ahmad Badawi Saluy

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This research is a planned activity to find an objective answer to PT XYZ problem through scientific procedure. In this study, It was used quantitative research methods by using samples taken from a department selected by researchers. This study aims to analyze the influence of organizational culture, work discipline and work motivation on employee performance of Personal Care & Cosmetic Department (PCC) Flammable PT XYZ. This research was conducted at PT XYZ Personal Care & Cosmetic Department (PCC) Flammable involving 82 employees as respondents, the data were obtained by using questionnaires filled in self-rating by respondents. The data were analyzed by multiple linear regression model processed by using SPSS version 22. The result of research showed that organizational culture variable, work discipline and work motivation had significant effect to employee performance.

Keywords: organizational culture, work discipline, employee motivation, employees performance

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Authors: Bukola Solomon

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In counterterrorism, policymakers typically design a confined role for women as family members and nurturers. In recent years, they have embraced the idea of mothers as the missing link to preventing and countering violent extremism. This ‘programmed’ role of women is derived from the convictions that women’s central roles in the family and community afford them the ‘unique set of skills’ to detect early signs of radicalization and extremism. This paper attempts to focus on the ‘mother’ narrative that frames women’s agency as mothers of ‘terrorists’ and ‘potential’ terrorists. The general underlying assumption of the ‘mother’ narrative is that naturally, every ‘terrorist’ has or once had a mother, and their radicalization is a maternal ‘oversight.’ By deconstructing the notion of motherhood as a social construct instead of an inherent female desire and ability, this paper argues that the assumption of ‘mothers know best’ is invalid. Also, this paper suggests that the ‘mother’ narrative is a deliberate effort to restrict women’s participation in counterterrorism as ‘preventers.’ Finally, this paper notes a global trend in which mothers are contesting the dominant view of women empowerment that restricts their agency by seeking alternative versions in terrorist organizations. And as such, they create parallel terror cells. Thus, the overemphasis on the role women plays as mothers in counterterrorism limits the scope and potential of counterterrorism programs by marginalizing gender issues and reinforcing gender disparities to the extent that the programs become counterproductive.

Keywords: countering violent extremism, counterterrorism, gender, gender roles, terrorism, women

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Authors: Arash Mirabdolah Lavasani, Taher Maarefdoost

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Effect of blockage ratio on heat transfer from non-circular tube is studied experimentally. For doing this experiment a suction type low speed wind tunnel with test section dimension of 14×14×40 and velocity in rage of 7-20 m/s was designed. The blockage ratios varied between 1.5 to 7 and Reynolds number based on equivalent diameter varies in range of 7.5×103 to 17.5×103. The results show that by increasing blockage ratio from 1.5 to 7, drag coefficient of the cam shaped tube decreased about 55 percent. By increasing Reynolds number, Nusselt number of the cam shaped tube increases about 40 to 48 percent in all ranges of blockage ratios.

Keywords: wind tunnel, non-circular tube, blockage ratio, experimental heat transfer, cross-flow

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: F. Louati, H. Trabelsi, M. Jamei

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Desiccation cracks following drainage-humidification cycles. With water loss, mainly due to evaporation, suction in the soil increases, producing volumetric shrinkage and tensile stress. When the tensile stress reaches tensile strength, the soil cracks. Desiccation cracks networks can directly control soil hydraulic properties. The aim of this study was for quantifying the hydraulic properties for examples the water retention curve, the saturated hydraulic conductivity, the unsaturated hydraulic conductivity function, the shrinkage dynamics in Tibar soil- clay soil in the Northern of Tunisia. Then a numerical simulation of unsaturated hydraulic properties for a crack network has been attempted. The finite elements code ‘CODE_BRIGHT’ can be used to follow the hydraulic distribution in cracked porous media.

Keywords: desiccation, cracks, permeability, unsaturated hydraulic flow, simulation

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Authors: Najmehossadat Enjoo

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Beautification means all mindfully measurements to improve quality of urban environment which makes the city more suitable for its inhabitants' life. Purpose of beautification is to provide an environment in which all citizens take pleasure. Beautification aims at urban environment's quality improvement. In space among buildings and constructions some supplementary elements are required to furnish urban life; equipment like house furniture makes life possible in a space surrounded with stones, concrete, and glass. Such elements regulate the flow of movement, rest, recreation and stress in a city and exhilarate it. Urban furniture is the common term used for such facilities and capabilities. Nowadays, experience and application of urban elements have proved that to what extent using proper equipment and furniture can positively affect the citizens and users of urban environments.

Keywords: urban servitudes, urban design, urban furniture, visage of city

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Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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Authors: Hyun-Woo Cho

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Unexpected operational events or abnormalities of industrial processes have a serious impact on the quality of final product of interest. In terms of statistical process control, fault detection and diagnosis of processes is one of the essential tasks needed to run the process safely. In this work, nonlinear representation of process measurement data is presented and evaluated using a simulation process. The effect of using different representation methods on the diagnosis performance is tested in terms of computational efficiency and data handling. The results have shown that the nonlinear representation technique produced more reliable diagnosis results and outperforms linear methods. The use of data filtering step improved computational speed and diagnosis performance for test data sets. The presented scheme is different from existing ones in that it attempts to extract the fault pattern in the reduced space, not in the original process variable space. Thus this scheme helps to reduce the sensitivity of empirical models to noise.

Keywords: fault diagnosis, nonlinear technique, process data, reduced spaces

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Authors: Reda Mankbadi

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In this paper we explore the use of a second-order unstructured-grid, finite-volume code for direct noise prediction. We consider a Mach 1.5 jet impinging on a perpendicular flat plate. Hybrid LES-RANS simulations are used to calculate directly both the flow field and the radiated sound. The ANSYS Fluent commercial code is utilized for the calculations. The acoustic field is obtained directly from the simulations and is compared with the integral approach of Ffowcs Williams-Hawkings (FWH). Results indicate the existence of a preferred radiation angle. The spectrum obtained is in good agreement with observations. This points out to the possibility of handling the effects of complicated geometries on noise radiation by using unstructured second-orders codes.

Keywords: CFD, Ffowcs Williams-Hawkings (FWH), imping jet, ANSYS fluent commercial code, hybrid LES-RANS simulations

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Authors: Jung-Ho Moon, Myung-Gon Yoon, Tae Kwon Ha

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This paper presents a wireless sensor network protocol for a car parking monitoring system. A wireless sensor network for the purpose is composed of multiple sensor nodes, a sink node, a gateway, and a server. Each of the sensor nodes is equipped with a 3-axis AMR sensor and deployed in the center of a parking space. The sensor node reads its sensor values periodically and transmits the data to the sink node if the current and immediate past sensor values show a difference exceeding a threshold value. The operations of the sink and sensor nodes are described in detail along with flow diagrams. The protocol allows a low-duty cycle operation of the sensor nodes and a flexible adjustment of the threshold value used by the sensor nodes.

Keywords: car parking monitoring, sensor node, wireless sensor network, network protocol

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Authors: Eric Huang, Coleman DeLude, Justin Romberg, Saibal Mukhopadhyay, Madhavan Swaminathan

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High performance computing (HPC) based emulators can be used to model the scattering from multiple stationary and moving targets for RADAR applications. These emulators rely on the RADAR Cross Section (RCS) of the targets being available in complex scenarios. Representing the RCS using tables generated from electromagnetic (EM) simulations is often times cumbersome leading to large storage requirement. This paper proposed a spherical harmonic based anisotropic scatterer model to represent the RCS of complex targets. The problem of finding the locations and reflection profiles of all scatterers can be formulated as a linear least square problem with a special sparsity constraint. This paper solves this problem using a modified Orthogonal Matching Pursuit algorithm. The results show that the spherical harmonic based scatterer model can effectively represent the RCS data of complex targets.

Keywords: RADAR, RCS, high performance computing, point scatterer model

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Authors: Wennan Long, Yuhao Nie, Yunan Li, Adam Brandt

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To fight against climate change, California government issued the Senate Bill No. 100 (SB-100) in 2018 September, which aims at achieving a target of 100% renewable electricity by the end of 2045. A capacity expansion problem is solved in this case study using a binary quadratic programming model. The optimal locations and capacities of the potential renewable power plants (i.e., solar, wind, biomass, geothermal and hydropower), the phase-out schedule of existing fossil-based (nature gas) power plants and the transmission of electricity across the entire network are determined with the minimal total annualized cost measured by net present value (NPV). The results show that the renewable electricity contribution could increase to 85.9% by 2030 and reach 100% by 2035. Fossil-based power plants will be totally phased out around 2035 and solar and wind will finally become the most dominant renewable energy resource in California electricity mix.

Keywords: 100% renewable electricity, California, capacity expansion, mixed integer non-linear programming

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Authors: Ghada S. Moussa

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Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

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Authors: Yussif Tawfiq, Stephen Omari, Kwaku Poku Asante

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The abundance of malaria vectors is influenced by micro-ecology, rainfall, and temperature patterns. The main objective of the study was to identify mosquito larval sites for future larval surveys and possible intervention programs. The study was conducted in Kintampo in central Ghana. Twenty larval sites were surveyed. Larval density was determined per cm² of water from each of the various sites. The dipper was used to fetch larvae from the larval sites, and a global positioning system (GPS) was used to identify larvae locations. There was a negative linear relationship between humidity, temperature, pH, and mosquito larval density. GPS of larval sites was taken for easy larval identification. There was the presence of Anopheles mosquito larvae in all polluted waters with Culex larval presence. This shows that Anopheles mosquito larvae are beginning to adapt to survival in polluted waters. The identified breeding sites are going to be useful for future larval surveys and will also help in intervention programs.

Keywords: larvae, GPS, dipper, larval density

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Authors: Faten Hatem

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This paper promotes the importance of focusing on spatial aspects and affective factors that impact smart urbanism. This helps to better inform city governance, spatial planning, and policymaking to focus on what Smart does and what it can achieve for cities in terms of performance rather than on using the notion for prestige in a worldwide trend towards becoming a smart city. By illustrating how this style of practice compromises the social aspects and related elements of space making through an interdisciplinary comparative approach, the paper clarifies the impact of this compromise on the overall smart city performance. In response, this paper recognizes the importance of establishing a new meaning for urban progress by moving beyond improving basic services of the city to enhance the actual human experience which is essential for the development of authentic smart cities. The topic is presented under five overlooked areas that discuss the relation between smart cities’ potential and efficiency paradox, the social aspect, connectedness with nature, the human factor, and untapped resources. However, these themes are not meant to be discussed in silos, instead, they are presented to collectively examine smart cities in performance, arguing there is more to the practical life of smart cities than software and hardware inventions. The study is based on a case study approach, presenting Milton Keynes as a living example to learn from while engaging with various methods for data collection including multi-disciplinary semi-structured interviews, field observations, and data mining.

Keywords: smart design, the human in the city, human needs and urban planning, sustainability, smart cities, smart

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Authors: O. Behar, A. Khellaf, K. Mohammedi, S. Ait Kaci

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Up to now, most validation studies have been based on the MBE and RMSE, and therefore, focused only on long and short terms performance to test and classify solar radiation models. This traditional analysis does not take into account the quality of modeling and linearity. In our analysis we have tested 22 solar radiation models that are capable to provide instantaneous direct and global radiation at any given location Worldwide. We introduce a new indicator, which we named Global Accuracy Indicator (GAI) to examine the linear relationship between the measured and predicted values and the quality of modeling in addition to long and short terms performance. Note that the quality of model has been represented by the T-Statistical test, the model linearity has been given by the correlation coefficient and the long and short term performance have been respectively known by the MBE and RMSE. An important founding of this research is that the use GAI allows avoiding default validation when using traditional methodology that might results in erroneous prediction of solar power conversion systems performances.

Keywords: solar radiation model, parametric model, performance analysis, Global Accuracy Indicator (GAI)

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Authors: Guillaume Craveur

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The evaluation of the passenger exchange time is necessary for railway operators in order to optimize and dimension rail traffic. Several influential parameters are identified and studied. Each parameter leads to a modeling completed with the buildingEXODUS software. The objective is the modelling of passenger exchanges measured by passenger counting. Population size is dimensioned using passenger counting files which are a report of the train service and contain following useful informations: number of passengers who get on and leave the train, exchange time. These information are collected by sensors placed at the top of each train door. With passenger counting files it is possible to know how many people are engaged in the exchange and how long is the exchange, but it is not possible to know passenger flow of the door. All the information about observed exchanges are thus not available. For this reason and in order to minimize inaccuracies, only short exchanges (less than 30 seconds) with a maximum of people are performed.

Keywords: passengers exchange, numerical tools, rolling stock, platforms

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Authors: Samuel I. Becher, Tal Z. Zarsky

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The digital world becomes part of our DNA now. The way e-commerce, human behavior, and law interact and affect one another is rapidly and significantly changing. Among others things, the internet equips consumers with a variety of platforms to share information in a volume we could not imagine before. As part of this development, online information flows allow consumers to learn about businesses and their contracts in an efficient and quick manner. Consumers can become informed by the impressions that other, experienced consumers share and spread. In other words, consumers may familiarize themselves with the contents of contracts through the experiences that other consumers had. Online and offline, the relationship between consumers and businesses are most frequently governed by consumer standard form contracts. For decades, such contracts are assumed to be one-sided and biased against consumers. Consumer Law seeks to alleviate this bias and empower consumers. Legislatures, consumer organizations, scholars, and judges are constantly looking for clever ways to protect consumers from unscrupulous firms and unfair behaviors. While consumers-businesses relationships are theoretically administered by standardized contracts, firms do not always follow these contracts in practice. At times, there is a significant disparity between what the written contract stipulates and what consumers experience de facto. That is, there is a crucial gap (“the Gap”) between how firms draft their contracts on the one hand, and how firms actually treat consumers on the other. Interestingly, the Gap is frequently manifested by deviation from the written contract in favor of consumers. In other words, firms often exercise lenient approach in spite of the stringent written contracts they draft. This essay examines whether, counter-intuitively, policy makers should add firms’ leniency to the growing list of firms suspicious behaviors. At first glance, firms should be allowed, if not encouraged, to exercise leniency. Many legal regimes are looking for ways to cope with unfair contract terms in consumer contracts. Naturally, therefore, consumer law should enable, if not encourage, firms’ lenient practices. Firms’ willingness to deviate from their strict contracts in order to benefit consumers seems like a sensible approach. Apparently, such behavior should not be second guessed. However, at times online tools, firm’s behaviors and human psychology result in a toxic mix. Beneficial and helpful online information should be treated with due respect as it may occasionally have surprising and harmful qualities. In this essay, we illustrate that technological changes turn the Gap into a key component in consumers' understanding, or misunderstanding, of consumer contracts. In short, a Gap may distort consumers’ perception and undermine rational decision-making. Consequently, this essay explores whether, counter-intuitively, consumer law should sanction firms that create a Gap and use it. It examines when firms’ leniency should be considered as manipulative or exercised in bad faith. It then investigates whether firms should be allowed to enforce the written contract even if the firms deliberately and consistently deviated from it.

Keywords: consumer contracts, consumer protection, information flow, law and economics, law and technology, paper deal v firms' behavior

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Authors: Yun-Xuan Tang, Pei-Yuan Liu, Kun-Mu Lu, Min-Tsung Tseng, Liang-Kuang Chen, Yuh-Feng Tsai, Ching-Wen Lee, Jay Wu

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Breast cancer is predominant of malignant tumors in females. The increase in the glandular density increases the risk of breast cancer. BI-RADS is a frequently used density indicator in mammography; however, it significantly overestimates the glandularity. Therefore, it is very important to accurately and quantitatively assess the glandularity by mammography. In this study, 20%, 30% and 50% glandularity phantoms were exposed using a mammography machine at 28, 30 and 31 kVp, and 30, 55, 80 and 105 mAs, respectively. The regions of interest (ROIs) were drawn to assess the gray level. The relationship between the glandularity and gray level under various compression thicknesses, kVp, and mAs was established by the multivariable linear regression. A phantom verification was performed with automatic exposure control (AEC). The regression equation was obtained with an R-square value of 0.928. The average gray levels of the verification phantom were 8708, 8660 and 8434 for 0.952, 0.963 and 0.985 g/cm3, respectively. The percent differences of glandularity to the regression equation were 3.24%, 2.75% and 13.7%. We concluded that the proposed method could be clinically applied in mammography to improve the glandularity estimation and further increase the importance of breast cancer screening.

Keywords: mammography, glandularity, gray value, BI-RADS

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Authors: A. M. Sultana, Norhirdawati Binti Mhd Zahir, Norzalan Hadi Yaacob

Abstract:

Recently in Malaysia, women's participation in teaching profession has increased. The increasing trend of women’s participation in the teaching profession poses challenges in families, especially in the developing countries like Malaysia. One of these challenges, concerns in balancing their role between family and job responsibility that faced by many women teachers. The purpose of this study is to discover how women teachers' impact on family happiness and the challenges faced by them in balancing their role between family and job responsibility. The findings presented in this study are based on survey research in a secondary school Dato’ Bijaya Setia in the district of Gugusan Manjoi which is located in Kedah, Malaysia. The study found that employment of women in economic activity has several beneficial impacts of improving the economic condition of the family. The results also revealed that in low income earning families, both husbands and wives’ employment contribute to the family income that less likely to experience of family poverty. The study also showed despite women's teachers’ significant role towards the overall development of the family, the majority of women teachers encountered a number of difficulties in balancing their role between family and job responsibility especially when they need to work more than the normal working time. Therefore, it is common for the majority of women suffering from psychological stress when they are unable to complete the task at a fixed time. The present study also suggests implication of family friendly policy and its appropriate practice to support the women teachers who are significantly contributing to family, community and the country.

Keywords: emotional exhaustion, family friendly policy, work family conflict, women teacher

Procedia PDF Downloads 413

Authors: Ramutė Miseikienė, Saulius Tusas

Abstract:

Somatic cell count and bacteria count are the main indicators of cow milk quality. The aim of this study was to analyze and compare parameters of milk quality in different-sized cows herds. Milk quality of ten dairy cows farms during one year period was analyzed. Dairy farms were divided into five groups according to number of cows in the farm (under 50 cows, 51–100 cows, 101–200 cows, 201–400 cows and more than 400 cows). The averages of somatic cells bacteria count in milk and milk freezing temperature were analyzed. Also, these parameters of milk quality were compared during outdoor (from May to September) and indoor (from October to April) periods. The largest number of SCC was established in the smallest farms, i.e., in farms under 50 cows and 51-100 cows (respectively 264±9,19 and 300±10,24 thousand/ml). Reliable link between the smallest and largest dairy farms and farms with 101-200 and 201-400 cows and count of somatic cells in milk has not been established (P > 0.05). Bacteria count had a low tendency to decrease when the number of cows in farms increased. The highest bacteria number was determined in the farms with 51-100 cows and the the lowest bacteria count was in milk when 201-400 and more than 401 cows were kept. With increasing the number of cows milk maximal freezing temperature decreases (significant negative trend), i. e, indicator is improving. It should be noted that in all farms milk freezing point never exceeded requirements (-0.515 °C). The highest difference between SCC in milk during the indoor and outdoor periods was established in farms with 201-400 cows (respectively 218.49 thousand/ml and 268.84 thousand/ml). However, the count of SC was significantly higher (P < 0.05) during outdoor period in large farms (201-400 and more cows). There was no significant difference between bacteria count in milk during both – outdoor and indoor – periods (P > 0.05).

Keywords: bacteria, cow, farm size, somatic cell count

Procedia PDF Downloads 251