Search results for: image subset selection

Authors: Vito M. Manghisi, Michele Gattullo, Alessandro Evangelista, Enricoandrea Laviola

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In this work, we compared two solutions for displaying a demo version of an Augmented Reality (AR) manual when the real product is not available, opting to replace it with its computer-aided design (CAD) model. AR has been proved to be effective in maintenance and assembly operations by many studies in the literature. However, most of them present solutions for existing products, usually converting old, printed manuals into AR manuals. In this case, authoring consists of defining how to convey existing instructions through AR. It is not a simple choice, and demo versions are created to test the design goodness. However, this becomes impossible when the product is not physically available, as for new products. A solution could be creating an entirely virtual environment with the product and the instructions. However, in this way, user interaction is completely different from that in the real application, then it would be hard testing the usability of the AR manual. This work aims to propose and compare two different solutions for the displaying of a demo version of an AR manual to support authoring in case of a product that is not physically available. We used as a case study that of an innovative semi-hermetic compressor that has not yet been produced. The applications were developed for a handheld device, using Unity 3D. The main issue was how to show the compressor and attach instructions on it. In one approach, we used Vuforia natural feature tracking to attach a CAD model of the compressor to a 2D image that is a drawing in scale 1:1 of the top-view of the CAD model. In this way, during the AR manual demonstration, the 3D model of the compressor is displayed on the user's device in place of the real compressor, and all the virtual instructions are attached to it. In the other approach, we first created a support application that shows the CAD model of the compressor on a marker. Then, we registered a video of this application, moving around the marker, obtaining a video that shows the CAD model from every point of view. For the AR manual, we used the Vuforia model target (360° option) to track the CAD model of the compressor, as it was the real compressor. Then, during the demonstration, the video is shown on a fixed large screen, and instructions are displayed attached to it in the AR manual. The first solution presents the main drawback to keeping the printed image with everyone working on the authoring of the AR manual, but allows to show the product in a real scale and interaction during the demonstration is very simple. The second one does not need a printed marker during the demonstration but a screen. Still, the compressor model is resized, and interaction is awkward since the user has to play the video on the screen to rotate the compressor. The two solutions were evaluated together with the company, and the preferred was the first one due to a more natural interaction.

Keywords: augmented reality, human computer interaction, operating instructions, maintenance, assembly

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

Procedia PDF Downloads 496

Authors: Ahmed Kayad Abdourazak, Abderafi Souad, Zejli Driss, Idriss Abdoulkader Ibrahim

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In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude and monthly solar irradiation. For this purpose the German Aerospace Centre (DLR) data of eight Djibouti sites were used as training and testing in a standard three layers network with the back propagation algorithm of Lavenber-Marquardt. Results have shown a very good agreement for the solar irradiation prediction in Djibouti and proves that the proposed approach can be well used as an efficient tool for prediction of solar irradiation by providing so helpful information concerning sites selection, design and planning of solar plants.

Keywords: artificial neural network, solar irradiation, concentrated solar power, Lavenberg-Marquardt

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: Jheanel E. Estrada, Larry A. Vea

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This study developed model to detect proper/improper sitting posture using the built in web camera which detects the upper body points’ location and distances (chin, manubrium and acromion process). It also established relationships of human body frames and proper sitting posture. The models were developed by training some well-known classifiers such as KNN, SVM, MLP, and Decision Tree using the data collected from 60 students of different body frames. Decision Tree classifier demonstrated the most promising model performance with an accuracy of 95.35% and a kappa of 0.907 for head and shoulder posture. Results also showed that there were relationships between body frame and posture through Body Mass Index.

Keywords: posture, spinal points, gyroscope, image processing, ergonomics

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Authors: M. Fozan Ur Rab, Mahrukh, M. Alam, N. Sheikh

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The purpose of this study is to analyze various high lift low Reynolds number airfoils using two-dimensional Computational Fluid Dynamics (CFD) code in the isolated flow field and select optimum airfoil to suit the motorsports application. The airfoil is selected after comparing the stall behavior, transition location, pressure recovery, pressure distribution and boundary layer characteristics of various airfoils. The prime consideration while selecting airfoil is highest Cl while achieving the sustainable performance over a range of Reynolds numbers encountered on the race track. The increase in Cl is always accompanied by the increase in Cd but this must be compromised since the main goal is to increase an aerodynamic grip. It is always desirable to increase the down-force in Formula One (F1)/Formula Student (FS) to gain reduction in lap time. This paper establishes the criteria for selection of high lift low Reynolds number airfoil while considering various parameters which affect the performance of airfoils.

Keywords: aerodynamics, airfoil, downforce, formula student, lap time

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Authors: Gaelle Candel, David Naccache

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t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embeddings. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n²) to O(n²=k), and the memory requirement from n² to 2(n=k)², which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution, and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning

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Authors: Brayan S. Pabón, R. Ricardo Moreno, Edith Gonzalez

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Inside the wide Colombian natural fiber set is the banana stem leaf, known as Calceta de Plátano, which is a material present in several regions of the country and is a fiber extracted from the pseudo stem of the banana plant (Musa paradisiaca) as a regular maintenance process. Colombia had a production of 2.8 million tons in 2007 and 2008 corresponding to 8.2% of the international production, number that is growing. This material was selected to be studied because it is not being used by farmers due to it being perceived as a waste from the banana harvest and a propagation pest agent inside the planting. In addition, the Calceta does not have industrial applications in Colombia since there is not enough concrete knowledge that informs us about the properties of the material and the possible applications it could have. Based on this situation the industrial design is used as a link between the properties of the material and the need to transform it into industrial products for the market. Therefore, the project identifies potential design attributes that the banana stem leaf can have for product development. The methodology was divided into 2 main chapters: Methodology for the material recognition: -Data Collection, inquiring the craftsmen experience and bibliography. -Knowledge in practice, with controlled experiments and validation tests. -Creation of design attributes and material profile according to the knowledge developed. Moreover, the Design methodology: -Application fields selection, exploring the use of the attributes and the relation with product functions. -Evaluating the possible fields and selection of the optimum application. -Design Process with sketching, ideation, and product development. Different protocols were elaborated to qualitatively determine some material properties of the Calceta, and if they could be designated as design attributes. Once defined, performed and analyzed the validation protocols, 25 design attributes were identified and classified into 4 attribute categories (Environmental, Functional, Aesthetics and Technical) forming the material profile. Then, 15 application fields were defined based on the relation between functions of product and the use of the Calceta attributes. Those fields were evaluated to measure how much are being used the functional attributes. After fields evaluation, a final field was defined , influenced by traditional use of the fiber for packing food. As final result, two products were designed for this application field. The first one is the Multiple Container, which works to contain small or large-thin pieces of food, like potatoes chips or small sausages; it allows the consumption of food with sauces or dressings. The second is the Chorizo container, specifically designed for this food due to the long shape and the consumption mode. Natural fiber research allows the generation of a solider and a more complete knowledge about natural fibers. In addition, the research is a way to strengthen the identity through the investigation of the proper and autochthonous, allowing the use of national resources in a sustainable and creative way. Using divergent thinking and the design as a tool, this investigation can achieve advances in the natural fiber handling.

Keywords: banana stem leaf, Calceta de Plátano, design attributes, natural fibers, product design

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Authors: Mustapha Benssalah, Mustapha Djeddou, Karim Drouiche

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The random number generation (RNG) presents a significant importance for the security and the privacy of numerous applications, such as RFID technology and smart cards. Since, the quality of the generated bit sequences is paramount that a weak internal generator for example, can directly cause the entire application to be insecure, and thus it makes no sense to employ strong algorithms for the application. In this paper, we propose a new pseudo random number generator (PRNG), suitable for cryptosystems ECC-based, constructed by randomly selecting points from several elliptic curves randomly selected. The main contribution of this work is the increasing of the generator internal states by extending the set of its output realizations to several curves auto-selected. The quality and the statistical characteristics of the proposed PRNG are validated using the Chi-square goodness of fit test and the empirical Special Publication 800-22 statistical test suite issued by NIST.

Keywords: PRNG, security, cryptosystem, ECC

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Authors: András Rövid, Takeshi Hashimoto

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The paper focuses on the problem of the point correspondence matching in stereo images. The proposed matching algorithm is based on the combination of simpler methods such as normalized sum of squared differences (NSSD) and a more complex phase correlation based approach, by considering the noise and other factors, as well. The speed of NSSD and the preciseness of the phase correlation together yield an efficient approach to find the best candidate point with sub-pixel accuracy in stereo image pairs. The task of the NSSD in this case is to approach the candidate pixel roughly. Afterwards the location of the candidate is refined by an enhanced phase correlation based method which in contrast to the NSSD has to run only once for each selected pixel.

Keywords: stereo matching, sub-pixel accuracy, phase correlation, SVD, NSSD

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Authors: Julio Vega

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Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

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Authors: Dinmukhamed T., Vassiliy S.

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This article suggests the idea of fitting clothes and accessories based on augmented reality. A logical data model has been developed, taking into account the decision-making module (colors, style, type, material, popularity, etc.) based on personal data (age, gender, weight, height, leg size, hoist length, geolocation, photogrammetry, number of purchases of certain types of clothing, etc.) and statistical data of the purchase history (number of items, price, size, color, style, etc.). Also, in order to provide information to the user, it is planned to develop an augmented reality system using a QR code. This system of selection and fitting of clothing and accessories based on augmented reality will be used in stores to reduce the time for the buyer to make a decision on the choice of clothes.

Keywords: augmented reality, online store, decision-making module, like QR code, clothing store, queue

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Authors: Marianna De Almeida

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Greek secondary education is a highly selective system with regard to the access of students to Greek universities. Since access from elementary to lower secondary education and afterward to upper secondary education is rather liberal and almost free of selective mechanisms, the basic selection process comes after graduating from upper secondary school into play when students go through a highly selective process for university entry. This structure is responsible for the experience of extreme stress on the part of the candidates during a period of at least two years before the entrance examination leading to a radical change in students' everyday life routines. Instead of the school being an important agent for academic and psychological support, it seems that other agents, such as the informal private preparatory school and the student's families, take on the supportive role.

Keywords: stress, entrance examinations, family support, secondary education

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Authors: Aliya Ashraf, Mehreen Sirshar, Fatima Akhtar, Farwa Kazmi, Jawaria Wazir

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Vision, the basis for performing navigational tasks, is absent or greatly reduced in visually impaired people due to which they face many hurdles. For increasing the navigational capabilities of visually impaired people a desktop application ODAPTA is presented in this paper. The application uses camera to capture video from surroundings, apply various image processing algorithms to get information about path and obstacles, tracks them and delivers that information to user through voice commands. Experimental results show that the application works effectively for straight paths in daylight.

Keywords: visually impaired, ODAPTA, Region of Interest (ROI), driver fatigue, face detection, expression recognition, CCD camera, artificial intelligence

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Authors: Malay Bhattacharyya, Saparya Suresh

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The Correlation Structure associated with a portfolio is subjected to vary across time. Studying the structural breaks in the time-dependent Correlation matrix associated with a collection had been a subject of interest for a better understanding of the market movements, portfolio selection, etc. The current paper proposes a methodology for testing the change in the time-dependent correlation structure of a portfolio in the high dimensional data using the techniques of generalized inverse, singular valued decomposition and multivariate distribution theory which has not been addressed so far. The asymptotic properties of the proposed test are derived. Also, the performance and the validity of the method is tested on a real data set. The proposed test performs well for detecting the change in the dependence of global markets in the context of high dimensional data.

Keywords: correlation structure, high dimensional data, multivariate distribution theory, singular valued decomposition

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Authors: G. B. Lim, C. H. Jeon, K. H. Jung

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General light metal alloys are often developed in the material of transportation equipment such as automobiles and aircraft. Among the light metal alloys, magnesium is the lightest structural material with superior specific strength and many attractive physical and mechanical properties. However, magnesium alloys were difficult to obtain the mechanical properties at warm temperature. The aims of present work were to establish an analytical relation between mechanical properties and plastic flow induced by local indentation. An experimental investigation of the local strain distribution was carried out using a specially designed local indentation equipment in conjunction with ARAMIS based on digital image correlation method.

Keywords: indentation, magnesium, mechanical property, lightweight material, ARAMIS

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Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi

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One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

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Authors: Selvakuma Kumaresh, Man Young Kim

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Combustion phenomenon will be accomplished effectively by the development of low emission combustor. One of the significant factors influencing the entire Combustion process is the mixing between a swirling angular jet (Primary Air) and the non-swirling inner jet (fuel). To study this fundamental flow, the chamber had to be designed in such a manner that the combustion process to sustain itself in a continuous manner and the temperature of the products is sufficiently below the maximum working temperature in the turbine. This study is used to develop the effective combustion with low unburned combustion products by adopting the concept of high swirl flow and motility of holes in the secondary chamber. The proper selection of a swirler is needed to reduce emission which can be concluded from the emission of Nox and CO2. The capture of CO2 is necessary to mitigate CO2 emissions from natural gas. Thus the suppression of unburned gases is a meaningful objective for the development of high performance combustor without affecting turbine blade temperature.

Keywords: combustion, emission, can-type combustion chamber, CFD, motility of holes, swirl flow

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Authors: Alice Sanwald, Thomas Schober

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We analyze mortality and follow-up costs of heart attack patients using administrative data from Austria (2002-2011). As treatment intensity in a hospital largely depends on whether it has a catheterization laboratory, we focus on the effects of patients' initial admission to these specialized hospitals. To account for the nonrandom selection of patients into hospitals, we exploit individuals' place of residence as a source of exogenous variation in an instrumental variable framework. We find that the initial admission to specialized hospitals increases patients' survival chances substantially. The effect on 3-year mortality is -9.5 percentage points. A separation of the sample into subgroups shows the strongest effects in relative terms for patients below the age of 65. We do not find significant effects on longterm inpatient costs and find only marginal increases in outpatient costs.

Keywords: acute myocardial infarction, mortality, costs, instrumental variables, heart attack

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Authors: Mohammed Mesrar, Hamza El Malki, Hamza Mesrar

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In this study, ceramics of (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3 were synthesized through a conventional calcination process (solid-state method) at 1000°C for 4 hours, with x(%) values ranging from 0.0 to 100. Room temperature XRD patterns confirmed the phase formation of the samples. The Rietveld refinement method was employed to verify the morphotropic phase boundary (MPB) at x(%)=16-20. We investigated the average crystallite size and lattice strain using Scherrer's formula and Williamson-Hall (W-H) analysis. SEM image analyses provided additional evidence of the impact of doping on structural growth under low temperatures. Relaxation time extracted from Z″(f) and M″(f) spectra for x(%) = 0.0, 12, 16, 20, and 30 followed the Arrhenius law, revealing the presence of three distinct relaxation mechanisms with varying activation energies. The shoulder response in M″(f) indirectly indicated the existence of highly polarizable entities in the samples, serving as a signature of polar nanoregions (PNRs) within the grains.In this study, ceramics of (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3 were synthesized through a conventional calcination process (solid-state method) at 1000°C for 4 hours, with x(%) values ranging from 0.0 to 100. Room temperature XRD patterns confirmed the phase formation of the samples. The Rietveld refinement method was employed to verify the morphotropic phase boundary (MPB) at x(%)=16-20. We investigated the average crystallite size and lattice strain using Scherrer's formula and Williamson-Hall (W-H) analysis. SEM image analyses provided additional evidence of the impact of doping on structural growth under low temperatures. Relaxation time extracted from Z″(f) and M″(f) spectra for x(%) = 0.0, 12, 16, 20, and 30 followed the Arrhenius law, revealing the presence of three distinct relaxation mechanisms with varying activation energies. The shoulder response in M″(f) indirectly indicated the existence of highly polarizable entities in the samples, serving as a signature of polar nanoregions (PNRs) within the grains.

Keywords: (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3, Rietveld refinement, Scanning electron microscopy (SEM), Williamson-Hall plots, charge density distribution, dielectric properties

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Authors: Narong Anurak

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This study aimed to find out the hair-care purchasing behavior at hypermarkets and to investigate two factors, package design and advertising channels, that influenced hair-care purchasing behavior. The subjects of the study consisted of 100 housewives aged between 20-60 who usually shopped at Big C Tiwanon. They were selected by accidental sampling, and were asked to complete a questionnaire. The main findings of the survey were that the majority of respondents regarding their brand selection of hair-care products, they gave priority to the product quality followed by a reasonable price, and fragrance, respectively. Besides, more than half of the respondents had brand loyalty while the rest were attracted by an attractive package design and advertising promotion campaigns. The respondents who were attracted by the package design said that the information on the labels influenced their purchasing decision the most, and television was a medium that best reached them as well.

Keywords: advertising channels, consumer purchasing decisions, hair-care market, package design

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Authors: Vahid Bayrami Rad

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Ever since humans developed a collective way of life to the development of urbanization, the concern of security has always been considered one of the most important challenges of life. To protect property, locks have always been a practical tool. With the advancement of technology, the form of locks has changed from mechanical to electric. One of the most widely used fields of using artificial intelligence is its application in the technology of surveillance security systems. Currently, the technologies used in smart anti-theft door handles are one of the most potential fields for using artificial intelligence. Artificial intelligence has the possibility to learn, calculate, interpret and process by analyzing data with the help of algorithms and mathematical models and make smart decisions. We will use Arduino board to process data.

Keywords: arduino board, artificial intelligence, image processing, solenoid lock

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Authors: Xiaoyan Dai, Hsieh Yisan

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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

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Authors: Spanova Yerkezhan, Amantay Ayan, Alimzhanova Laura

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This article discusses the concept of rebranding and its relationship to cybersecurity. Rebranding is the process of changing the appearance and image of a company or organization in order to appeal to new customers or change the perception of a company. It can be a powerful tool for businesses looking to renew their reputation or expand into new markets. In today's digital age, companies increasingly rely on technology and the internet to conduct business; rebranding can also present significant cybersecurity risks. This is because a rebranding effort can create new vulnerabilities for companies, particularly in terms of their online presence. This article explores the potential hazards associated with rebranding and provides recommendations for mitigating those risks. It also highlights the importance of considering cybersecurity in the rebranding process and how it can be integrated into the overall strategy for a successful and secure rebranding.

Keywords: rebranding, cybersecurity, cyberattack, logo, vulnerability

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Authors: M. Jebali, M. Jemni

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This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

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Authors: Bovornluck Kuosuwan, Kevin Wongleedee

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The purposes of this research was to study the level of satisfaction of international tourists in five important areas: satisfaction on visiting tourist destinations, satisfaction on tourist images, satisfaction on value for money, satisfaction on service quality, and satisfaction when compared with their expectation. A probability random sampling of 200 inbound tourists was utilized. A questionnaire was used to collect the data and small in-depth interviews were also used to get their opinions about their positive and negative evaluations of their experience travelling in Thailand. The findings revealed that the majority of respondents had a medium level of satisfaction. When examined in detail, the level of satisfaction can be ranked from highest to lowest according to the mean average as follows: visiting tourist destinations, expectations, service quality, tourist image, and value for money.

Keywords: inbound tourists, satisfaction, Thailand, international tourists

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Authors: Anuradha Banerjee

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Energy aware operation is one of the visionary goals in the area of robotics because operability of robots is greatly dependent upon their residual energy. Practically, the tasks allocated to robots carry different priority and often an upper limit of time stamp is imposed within which the task needs to be completed. If a robot is unable to complete one particular task given to it the task is reallocated to some other robot. The collection of robots is controlled by a Central Monitoring Unit (CMU). Selection of the new robot is performed by a fuzzy controller called Task Reallocator (TRAC). It accepts the parameters like residual energy of robots, possibility that the task will be successfully completed by the new robot within stipulated time, distance of the new robot (where the task is reallocated) from distance of the old one (where the task was going on) etc. The proposed methodology increases the probability of completing globally assigned tasks and saves huge amount of energy as far as the collection of robots is concerned.

Keywords: energy-efficiency, fuzzy-controller, priority, reallocation, task

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Authors: Tamphasana Wairokpam

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Inflammatory myopathies (IMs) have long been recognised as a heterogenous family of myopathies with acute, subacute, and sometimes chronic presentation and are potentially treatable. Necrotizing autoimmune myopathies (NAM) are a relatively new subset of myopathies. Patients generally present with subacute onset of proximal myopathy and significantly elevated creatinine kinase (CK) levels. It is being increasingly recognised that there are limitations to the independent diagnostic utility of muscle biopsy. Immunohistochemistry tests may reveal important information in these cases. The traditional classification of IMs failed to recognise NAM as a separate entity and did not adequately emphasize the diversity of IMs. This review and case report on NAM aims to highlight the heterogeneity of this entity and focus on the distinct clinical presentation, biopsy findings, specific auto-antibodies implicated, and available treatment options with prognosis. This article is a meta-analysis of literatures on NAM and a case report illustrating the clinical course, investigation and biopsy findings, antibodies implicated, and management of a patient with NAM. The main databases used for the search were Pubmed, Google Scholar, and Cochrane Library. Altogether, 67 publications have been taken as references. Two biomarkers, anti-signal recognition protein (SRP) and anti- hydroxyl methylglutaryl-coenzyme A reductase (HMGCR) Abs, have been found to have an association with NAM in about 2/3rd of cases. Interestingly, anti-SRP associated NAM appears to be more aggressive in its clinical course when compared to its anti-HMGCR associated counterpart. Biopsy shows muscle fibre necrosis without inflammation. There are reports of statin-induced NAM where progression of myopathy has been seen even after discontinuation of statins, pointing towards an underlying immune mechanism. Diagnosisng NAM is essential as it requires more aggressive immunotherapy than other types of IMs. Most cases are refractory to corticosteroid monotherapy. Immunosuppressive therapy with other immunotherapeutic agents such as IVIg, rituximab, mycophenolate mofetil, azathioprine has been explored and found to have a role in the treatment of NAM. In conclusion,given the heterogeneity of NAM, it appears that NAM is not just a single entity but consists of many different forms, despite the similarities in presentation and its classification remains an evolving field. A thorough understanding of underlying mechanism and the clinical correlation with antibodies associated with NAM is essential for efficacious management and disease prognostication.

Keywords: inflammatory myopathies, necrotising autoimmune myopathies, anti-SRP antibody, anti-HMGCR antibody, statin induced myopathy

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Authors: Mohammed A. A. Sarhan, Issam A. Al-Khatib

Abstract:

Complying with the technical specifications of compost production is of high importance not only for environmental protection but also for increasing the productivity and promotion of compost use by farmers in agriculture. This study focuses on the compost quality of the Palestinian market and farmers’ attitudes toward agricultural use of compost. The quality is assessed through selection of 20 compost samples of different suppliers and producers and lab testing for quality parameters, while the farmers’ attitudes to compost use for agriculture are evaluated through survey questionnaire of 321 farmers in the Hebron area. The results showed that the compost in the Palestinian markets is of medium quality due to partial or non-compliance with the quality standards and guidelines. The Palestinian farmers showed a positive attitude since 91.2% of them have the desire to use compost in agriculture. The results also showed that knowledge of difference between compost and chemical fertilizers, perception of compost benefits and previously experiencing problems in compost use, are significant factors affecting the farmers’ attitude toward the use of compost as an organic fertilizer.

Keywords: attitude, compost, compost quality, organic fertilizer, manure

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Authors: Doo Ki Lee, Kumaresh Selvakumar, Man Young Kim, In Jae Song

Abstract:

The widespread utilization of mixer in selective catalytic reduction (SCR) system marks a remarkable advantage in diesel engines. In the automotive selective catalytic reduction (SCR) system, the de-NOX efficiency can be improved by highly uniform flow with effective turbulent mixing. In this paper, the exhaust pipe is complemented with the swirling mixers of three different vane angles installed at the upstream of the SCR reactor. The attributes of the mixer are established by the variation in flow behavior followed by the drawback owing to the absence of mixer. In particular, the information pertaining to the selection of proper static mixer is provided based on the correlation between the uniformity index (UI) and the pressure drop. The uniform distribution of the flow at the entrance of the SCR reactor aids to determine the configuration which gives high mixing performance and comprehend the function of the mixer.

Keywords: pressure drop, selective catalytic reduction, static mixer, turbulent mixing, uniformity index

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