Reviewerly/exHarmony huggingface dataset:
INVESTIGATION OF MOBILE AUGMENTED REALITY APPLICATIONS USED IN THE INTERIOR DESIGN

Scientific developments have triggered bleeding-edge technologies that have positive effect on the life-quality of human-beings.One of these technologies is named as Augmented Reality (AR) which also the thesis has focused on.The AR technology is defined as the mixture of reality and virtuality.The AR technology that based on the combination of real space and/or object along with the virtual object within the same platform, has aimed at getting more information for the interactive users about the objects interacted with.AR applications can now experience a widespread deployment of mobile smart devices and a large kit kit.This study aims to discuss the use of a new technique, AR technology, as a tool in the representation and experience of interior space and the effects of user experience on the activities of mobile indoor AR applications.For this purpose, we reviewed Android and IOS-based seven mobile interiors AR applications by searching for 'augmented reality interior design' on Google Play and Apple Store mobile stores as of February 2018.Therefore, both design and designers and end users have tried to determine the use of these applications and their identified deficiencies.In the future, AR is considered to be a powerful influence on the interior designer and user axis, and is considered as a new technique and strategy that will contribute to the transformation of the space concept into technology coexistence.The AR technologies, to be deemed as having strong effect within the framework of interior designer and user, are evaluated as a new technique and strategy that will make a significant contribution to the transformation of space concept in line with the developing technologies.
Single Image Super Resolution Technique: An Extension to True Color Images

The super-resolution (SR) technique reconstructs a high-resolution image from single or multiple low-resolution images. SR has gained much attention over the past decade, as it has significant applications in our daily life. This paper provides a new technique of a single image super-resolution on true colored images. The key idea is to obtain the super-resolved image from observed low-resolution images. A proposed technique is based on both the wavelet and spatial domain-based algorithms by exploiting the advantages of both of the algorithms. A back projection with an iterative method is implemented to minimize the reconstruction error and for noise removal wavelet-based de-noising method is used. Previously, this technique has been followed for the grayscale images. In this proposed algorithm, the colored images are taken into account for super-resolution. The results of the proposed method have been examined both subjectively by observation of the results visually and objectively by considering the peak signal-to-noise ratio (PSNR) and mean squared error (MSE), which gives significant results and visually better in quality from the bi-cubic interpolation technique.
IMAGE PROCESSING MODELS AND METHODS RESEARCH AND WAYS OF IMPROVING MARKER RECOGNITION TECHNOLOGIES IN ADDED REALITY SYSTEMS

The subject matter of article is method of image processing, which identify and describe the local features of images. The aim of the article is the determination of ways for interconnection of the methods for processing the image and technologies creation in the development of markers in the systems of additional reality. The following tasks are solved in the article: to analyze the existing methods and algorithms for finding objects in two-dimensional images to determine the basic marker recognition technology in the complementary reality systems. Analyzed genetic, neural network, statistical and fractal methods, as well as approaches to the algorithms implementation of in the software construction for systems of complementary reality. The next results were obtained: a review and a comparative analysis of the main known algorithms for detecting key points in the images were conducted. It was suggested in the development of marker recognition methods it is necessary to develop a procedure of preliminary image processing for the formation algorithms of the front image for the marker under different conditions of obtaining images. At segmentation stages, it is expedient to use genetic algorithms based on the best indicators of proper segmentation and low processing time, but it is necessary to develop functions that are appropriate for the format of the markers. Improve existing methods for processing segmentation results based on a criterion base describing a visual model representing a marker. Conclusions: as a result of the analysis, the following conclusion can be drawn. The fastest and the most accurate algorithm for putting key points is the genetic algorithm (average time of the algorithm is 5.23 seconds, the number of correct answers is 84.25). The longest working time is the neural network method - 8.45 seconds, the accuracy of this algorithm is also the lowest - 52. Another advantage of the algorithm of point matching is that if the object goes beyond the frame and then returns again, the program will again continue to track this object. This is supported by algorithms of machine learning. You can also notice that the SIFT calculation works much faster than fractal texture analysis. These results suggest that there are currently no methods for recognizing markers, allowing high accuracy of less than one unit to recognize in a short time. In our opinion, one of the promising directions is the use of Royan methods, namely the development of target functions for accurate and fast recognition of the image by markers.
Efficiency of Phase Unwrapping and Image Filtering Algorithms Implemented in a Fpga Applied on Holographic Interferometry

The evaluation of efficiency of algorithms implemented in a FPGA, which are applied on phase unwrapping and image filtering for holographic interferometry performing, is here presented. A phase unwrapping linear algorithm was used in holograms obtained by holographic interferometry using the phase-shifting method; Fourier Transform and Bilateral filtering processes were also applied on 1024x1024 holographic images. Phase unwrapping operations combined with Bilateral image filtering implemented in the FPGA were 19 times faster than using an ARM processor, and 12 times faster when Fourier image filtering is used instead. Hardware capacities of FPGA as combined with high-level programming can be an alternative to improve heavy computing processes like those involved in digital holographic microscopy, for example.
Design of Building Environment Mobile Monitoring and Safety Early Warning Robot

In view of the characteristics of two-wheeled robots, such as the small size and flexible movement, and the increasing demand for environment and security, this design implements a building environment mobile monitoring and security early warning robot. On the basis of the self-balancing of two wheels, the robot can monitor the building environment and alert people with voice intelligently. The system combines automatic control technology, PWM DC motor control technology and sensor technology. It applies the STM32 as the controller and uses the PID control algorithm to meet the requirements of its characteristics, such as multiple variables, nonlinearity, strong coupling, parameter uncertainty, and others. The wireless sensing and control are also established. For this, people can use the mobile phone or PC terminal to realize the wireless mobile monitoring, early warning, and alarm of building environment including temperature, humidity, illumination, air pressure, altitude, air quality, fire source detection, etc., based on mobile machines.
Genetic Explorations for Feature Selection

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
A total variation-undecimated wavelet approach to chest radiograph image enhancement

Most often medical images such as X-Rays have a low dynamic range and many of their targeted features are difficult to identify. Intensity transformations that improve image quality usually rely onwavelet denoising and enhancement typically use the technique of thresholding to obtain better quality medical images. A disadvantage of wavelet thresholding is that even though it adequately removes noise in an image, it introduces unwanted artifacts into the image near discontinuities. We utilize a total variation method and an undecimated wavelet image enhancing algorithm for improving the image quality of chest radiographs. Our approach achieves a high level chest radiograph image deniosing in lung nodules detection while preserving the important features. Moreover, our method results in a high image sensitivity that reduces the average number of false positives on a test set of medical data.
Randomized Group Vs Heterogeneous Group in Developing EFL Argumentative Essay

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Study of Secured Full-Stack Web Development

In this paper, we reviewed the tiered architecture and MVC pattern for web development. We also discussed common vulnerabilities and threats in web applications. In order to better understand how to develop a secured web application, we furthermore examined best practices from Angular and ASP.NET core frameworks as well as sample codes for secured web apps.
Scrutiny of Steganalysis for Flipping Steganography Method

Steganography is the skill of hiding data inside other information in such a way that it is hard or even impossible to tell that it is there. There are many different carriers for steganography but the most popular is digital images. In recent times, there it has been supposed that terrorist cells are using steganography to hide their clandestine policies, and consequently it is fetching increasingly significant to notice the images that contain steganography such that we can decrease criminal action. This counter-technique is known as steganalysis. In comparison to the importance of papers that examine either steganography or steganalysis methods, this paper presents in-depth metaphors of steganalysis.
Modular exponential multivariate sequence and its application to lightweight security design

How to design an economic lightweight security scheme is emerging as a challenging issue since a larger number of private and confidential datum are generated every day in this big data era. As presented in this paper, dynamic systems generated using multivariate sequences constructed from residual rings of matrices have been proven to admit good randomness and non-singularity which can be used to solve the equivalent keys and factorization problems found in Multivariate Quadratic asymmetric systems. These properties are useful for constructing a practical economic cryptographic system for constraint devices and provide a potential balanced solution between cost and security.
Desarrollo de una aplicación para dispositivos móviles destinada a Geometría (Matemáticas II)

described and it will reflect how to use them and what solutions it provides.As a general idea the application will have a main menu with a series of buttons leading to the independently working tools.Each tool will have a group of input data according to the problem which it is designed for and a group of output data which will be the solution for the problem.Finally, a questionnaire was given to a group of students of 2nd of bachillerato and a second questionnaire was sent to some teachers from different secondary schools of the Valencian Community with the aim of obtaining information about the interface and the performance of the application.
Practical Applications of Cryptocurrency: <i>A New Investment Opportunity?</i>

<h3>Practical Applications Summary</h3> In <b>Cryptocurrency: <i>A New Investment Opportunity?</i></b> from the winter 2018 issue of <b><i>The Journal of Alternative Investments</i></b>, authors <b>David LEE Kuo Chuen</b>, <b>Yu Wang</b> (both of <b>Singapore Management University</b>) and <b>Li Guo</b> (of <b>Singapore Management University</b>) provide an in-depth introduction to Bitcoin and other cryptocurrencies, and explore their potential as an alternative investment class. Their results show that the return correlations between cryptocurrencies and traditional assets are low, and that adding the Cryptocurrency Index (CRIX) to a traditional asset portfolio helps diversify risk, and, under some circumstances, may improve overall performance. Given the difficulty of valuation in the cryptocurrency market, however, the authors explore the possibility of generating positive risk-adjusted profits with a “sentiment” strategy that evaluates each cryptocurrency individually. <b>TOPICS:</b>Currency, risk management, performance measurement, mutual funds/passive investing/indexing
Clinico-epidemiological profile of malaria cases admitted in a tertiary care hospital, in South India

Background: Malaria is a global health problem leading to huge morbidity and mortality. India accounts for 4% of global malaria cases and 52% of malaria deaths outside the African region. A disease that was relatively unknown in Mangaluru till 1990, has shown consistent rise till 2015 killing nearly 300 people. Though, declining trends are being observed since 2015, yet its incidence continues to be high. Present study was undertaken to study clinical as well as epidemiological factors associated with malaria transmission in Mangaluru.Methods: A record based retrospective study was conducted in A J Institute of Medical Sciences and Research Centre Mangaluru tertiary care hospital. The data was retrieved from the Medical Record Department of the hospital for three years i.e. 2015 to 2017 and analysed.Results: A total of 1779 confirmed cases of malaria were admitted during the study period. Out of these 1309 (73.58%) cases were due P. vivax, 73 (04.10%) cases due to P. falciparum 306 (17.20%) cases had mixed infections while species of remaining 91 (05.11%) cases remained unspecified. A peak in the number of inpatients was seen in June while mean duration of hospital stay was 5.17±3.31 days. A total of 252 (14.16%) patients had one or more severe manifestations of malaria as per WHO guidelines.Conclusions: The present study reveals that majority of admitted malaria cases were young adult males belonged to urban area. Majority of the cases were infected by Plasmodium vivax or had mixed infections.
Exploiting Unlabeled Ties for Link Prediction in Incomplete Signed Networks

Signed networks analysis has attracted increasing attention in the areas of friendship recommendation and trust relationship prediction. Existing methods for link prediction in signed networks tend to rely on the features only from labeled ties which are not ideal for handling incomplete networks. In order to solve this issue, in this paper, we present a novel model called UTLP (Unlabeled Ties based Link Prediction) for incomplete signed networks. Based on social awareness theories, UTLP can utilize the features of both labeled ties and unlabeled ties. We consider four types of features including node-based features, structural balance-based features, status-based features and latent features, which can provide abundant evidence to improve the accuracy of prediction. With the extracted features, we adopt transfer learning algorithm with instance weighting to utilize more useful training instances in the source network to train the model and predict the signs of links, which can effectively make up for the incompleteness of target samples. We conduct experimental studies based upon Epinions, Slashdot and Wikipeida. Experiments demonstrate the effectiveness and the efficiency of our proposed approach.
Online semi-supervised multi-person tracking with gaussian process regression

Most existing multi-person tracking approaches are affected by lighting condition, pedestrian pose change abruptly, scale changes, realtime processing to name a few, resulting in detection error, drift and other issues. To cope with this challenge, we propose an enhanced multi-person framework by introducing a new observation model, which adaptively updates fully online to avoid the loss of sample diversity and learning in a semi-supervised manner. We fuse prior information for tracking decision, meanwhile extracted knowledge from current frame is used to assist to make tracking decision, which can be viewed as a transfer learning strategy, and both aspects can ameliorate the tendency to drift. The new approach does not need any calibration or batch processing. Experimental results show that the approach yields comparable or better performance in comparison with the state-of-the-arts, which do calibration or batch processing.
Automatic Robotic ARM using Hand Gestures 

This system presents a model for gesture controlled user interface (GCUI), and identifies trends in technology, application and usability. We present an integrated approach is real time detections, gesture based data which control vehicle movement and manipulation on gesture of the user using hand movements. A three axis accelerometer is adaption. As the person moves their hand, the accelerometer also moves accordingly. The gesture is capture by accelerometer and processed by gesture
A Survey on Speaker Recognition with Various Feature Extraction Techniques

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
SISTEM PEMILIHAN LAPTOP TERBAIK DENGAN MENGGUNAKAN METODE WEIGHTED PRODUCT (WP)

The Weighted Product method requires a normalization process because this method assumes the results of evaluating each attribute. The results of these multiplications have not been meaningful if they have not been compared (divided) with standard values. The weight for the benefit attribute functions as a positive power in the multiplication process, while the weight of the cost functions as a negative rank. The Weighted Product method uses multiplication as a linking attribute rating, where the rating of each attribute must be raised first with the corresponding weight. Weighting Product Weighted method is calculated based on the level of importance. This system requires input weight values based on prospective buyers' needs in the form of prices, RAM capacity, processor type, Harddisk capacity, and VGA (Video Grapphics Array). The results of this study provide laptop recommendations according to specification requirements for prospective buyers with 100% calculation accuracy based on manual calculations and calculations on laptop selection decision support systems.
Penerapan Sistem Pakar Menggunakan Metode Nearest Neighbor Mendiagnosa Gangguan Kesehatan Pengguna Minuman Keras

Expert systems in general are systems that try to adopt human knowledge to computers so that computers can solve problems as is usually done by experts. Or in other words an expert system is a system that is designed and implemented with the help of certain programming languages to be able to solve problems as done by experts. It is expected that with this system, lay people can solve certain problems, either 'a little' complicated or even complicated 'without' the help of experts in the field. As for experts, this system can be used as an experienced assistant. This system diagnoses the types of health problems of liquor users based on the symptoms entered into the system. This developed application aims to determine which liquor users consume by only paying attention to the criteria experienced by liquor users. Using the Nearest Neighbor Method is able to show a measure of certainty about a fact from the existing criteria. System output in the form of search results for liquor users is used by users based on symptoms.
A note on joint mix random vectors

This note studies the dependence of joint mix random vectors from the perspective of covariance matrix. We first provide two useful methods in simulations to construct joint mix for Normal distribution. Then, we propose to characterize joint mix by covariance matrix for general marginal distribution. We present some examples showing that our methodology could provide supplementary results to relevant studies in literature.
Decentralized Artificial Intelligence on Blockchain

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Revisiting Cloud Security Threats Man-in-the-Middle Attack

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.