Reviewerly/exHarmony huggingface dataset:
Various Implementation of Collaborative Filtering-Based Approach on Recommendation Systems using Similarity

The Recommendation System plays an increasingly important role in our daily lives. With the increasing amount of information on the internet, the recommendation system can also solve problems caused by increasing information quickly. Collaborative filtering is one method in the recommendation system that makes recommendations by analyzing correlations between users. Collaborative filtering accumulates customer item ratings, identifies customers with common ratings, and offers recommendations based on inter-customer comparisons. This study aims to build a system that can provide recommendations to users who want to order or choose fast food menus. This recommendation system provides recommendations based on item data calculations with customer review data using a collaborative filtering approach. The results of applying cosine similarity calculation to determine fast food menu recommendations obtained for the item-based recommendation is Pizza Frankfurter BBQ Large with a value of 1.0, item-based with genre recommendation is Calblend Float with value 1.0 and user-based recommendation is Pizza Black Pepper Beef / Chicken Large with mean score 2.5.
PENERAPAN MODEL PEMBELAJARAN QUANTUM LEARNING UNTUK MENINGKATKAN HASIL BELAJAR SISWA KELAS VII A MTs. ALKHAIRAAT BIROMARU PADA MATERI ARITMATIKA SOSIAL

The basic problem in this study is the low students learning outcomes in social arithmetic material regarding the profit, loss and percentage and discount in class VII A MTs Alkhairaat Biromaru 2017/2018 school year. There are several causes of the low students learning outcomes including teachers are still learning centers so students still tend to be passive in learning. This makes students become inactive, recultant, afraid and ashamend to ask. Therefore, to improve the learning outcomes of students of class VII A MTs Alkhairaat Biromaru and maximize learning, the researcher applied a quantum learning model, which is a learning model whose entire learning process can sharpen understanding and memory, and make learning a pleasant and useful process, so that learning becomes more motivated. The quantum learning model consists of 6 learning components, namely : 1. grow, 2. natural, 3. name, . demonstrate, 5. repeat, 6. Celebrate This research is a classroom action research using qualitative approachthat aims to improve the learning outcomes of class VII A MTs Alkhairaat Biromaru sudents. The subject of this study were all students of class VII A totaling 21 people. In the research tht has been carried out, the result of his study indicate that learning activities have been going well and have increased in each cycle. This can be seen from the percentage of completeness of classical learning. In the final test of the first cycle reached the average score of students that is 71,43% with the amount of absorption of 15 students. Then in the final test the second cycle increased to 85,71% in good qualifications. With the number of students who get individual absorption of 18 students.
Research on Network Public Opinion Analysis and Monitor Method Based on Big Data Technology

At present, the use of public opinion analysis method to explore the feelings of users in comments has become one of the hot research topics, and has been applied in many business and public management fields, such as movie box office, stock trend prediction, public opinion monitoring in power sector, etc. Data mining and analysis based on big data technology is increasingly demanding, and the logical relationship of data processing is increasingly complex. How to analyze and mine network public opinion information in heterogeneous data environment has become a big challenge in data management, application and value mining. This paper summarizes and compares several mainstream public opinion analysis methods and their applications, including unsupervised public opinion analysis method and supervised public opinion analysis method, and introduces the application scenarios related to public opinion analysis. A network public opinion analysis system model based on big data technology is designed to provide important data support for network public opinion monitoring.
Perancangan Aplikasi Web Penyewaan Lapangan Futsal (Studi Kasus :Sumber Jaya Futsal Tangerang)

Futsal sports have developed and are popular in Indonesia. Sumber Jaya Futsal is one of the providers of futsal field rental business in Tangerang. Sumber Jaya Futsal currently does not have a web-based system, the system for leasing futsal fields in Sumber Jaya Futsal is still conventional, where customers come directly or by calling to find out the schedule of available futsal fields. The rental transaction scheduling and report system is still using a notebook. Based on the problem, the purpose of this research is to produce a draft web application for futsal field rental at Sumber Jaya Futsal Tangerang. In this study to collect data the author uses case studies with methods of observation and literature. The design of this web application is made using the PHP programming language, assisted by xampp as a web server, MySQL for database management, ERD (Entity Relationship Diagram) and LRS (Logical Record Structure) to describe the data model. While the author's software development method uses the Waterfall Method.
Prediction of the Solar Radiation Map on Algeria by Latitude and Longitude Coordinates

Aims the study is how to create the model of the solar radiation as a function to coordinates of latitude and longitude of the location point for determined every points on the map of Algeria.This solar radiation varying according to type of the area, because the Algeria area changing from the rock, a vegetarian environment and desert area.Our model gives a good away for all area of the Algeria by average solar radiation with residual R² = 0.981 about latitude and 0.866 of longitude.The model it's good for help most researcher to calculate all points in the Algeria ground such as numerical study.
A 138 Mbps jitter based power efficient true random number generator

This paper introduces the design and implementation of True Random Number Generator (TRNG) based on clock jitter. The design extracts jitter from asynchronous type ring oscillator for enhanced randomness. The proposed design is implemented by considering 30 ring oscillators (RO) with a high-frequency divider block (designed by T-FF followed by DFF to address setup and hold time problem) and sampling block followed by a shifter. The design utilizes fewer resources yielding hardware redundancy and enhances the level of randomness. This TRNG has been designed and validated using Artix-7 FPGA. Power dissipation and speed have been obtained as 0.5mW and 138 Mbps respectively. The generated random bit stream has also been sampled and converted to a binary format in MATLAB and tested through the DIEHARD statistical test suite for validation. The obtained binary sequences passed all tests successfully.
A Serious Game for Evaluating the Competencies of Environmental Consultants

Having a competent workforce is one of the key elements that enable organizations to improve their global performance Thus, it is important for an organization to manage the competencies of its staff in the best possible way.In this paper, we present a serious game named EnviRun', that evaluates the acquired competencies of environmental consultants _ The environmental consultant advises and assists industries on projects related to the environment and sustainable development_ Indeed, Competency evaluation allows the organizations to define the potential of existing competencies and to specify competencies that need to be improved.To this end, the first step was competency identification.Indeed, we developed a competency framework that includes competencies required by an environmental consultant.Thereafter, the game elements were designed.To evaluate the environmental consultants' competencies, an approach based on the interval-valued 2-tuple linguistic representation model has been proposed, this approach is more flexible when dealing with qualitative information.
Technology Of Educational Process In School Technology Education

The article describes the essence of sending students to the profession through the technologicalization of the educational process in order to increase the effectiveness of the organization of "Technology" lessons in secondary schools.
Towards an objective comparison of feature extraction techniques for automatic speaker recognition systems

A common limitation of the previous comparative studies on speaker-features extraction techniques lies in the fact that the comparison is done independently of the used speaker modeling technique and its parameters. The aim of the present paper is twofold. Firstly, it aims to review the most significant advancements in feature extraction techniques used for automatic speaker recognition. Secondly, it seeks to evaluate and compare the currently dominant ones using an objective comparison methodology that overcomes the various limitations and drawbacks of the previous comparative studies. The results of the carried out experiments underlines the importance of the proposed comparison methodology.
Automatic Vehicles Detection, Classification and Counting Techniques / Survey

Vehicle detection (VD) plays a very essential role in Intelligent Transportation Systems (ITS) that have been intensively studied within the past years. The need for intelligent facilities expanded because the total number of vehicles is increasing rapidly in urban zones. Trafï¬c monitoring is an important element in the intelligent transportation system, which involves the detection, classification, tracking, and counting of vehicles. One of the key advantages of traffic video detection is that it provides traffic supervisors with the means to decrease congestion and improve highway planning. Vehicle detection in videos combines image processing in real-time with computerized pattern recognition in flexible stages. The real-time processing is very critical to keep the appropriate functionality of automated or continuously working systems. VD in road traffics has numerous applications in the transportation engineering field. In this review, different automated VD systems have been surveyed, with a focus on systems where the rectilinear stationary camera is positioned above intersections in the road rather than being mounted on the vehicle. Generally, three steps are utilized to acquire traffic condition information, including background subtraction (BS), vehicle detection and vehicle counting. First, we illustrate the concept of vehicle detection and discuss background subtraction for acquiring only moving objects. Then a variety of algorithms and techniques developed to detect vehicles are discussed beside illustrating their advantages and limitations. Finally, some limitations shared between the systems are demonstrated, such as the definition of ROI, focusing on only one aspect of detection, and the variation of accuracy with quality of videos. At the point when one can detect and classify vehicles, then it is probable to more improve the flow of the traffic and even give enormous information that can be valuable for many applications in the future.
Kinesics in EFL Language Teaching

This study was descriptive qualitative research to reveal the use of kinesics in EFL classrooms in STAHN Mpu Kuturan Singaraja. Specifically, the purposes of this study were: 1) to describe of how English lecturers perceive the kinesics in EFL communication; 2) to describe kinds of kinesics that the English lecturers use in their EFL classrooms; 3) to describe how the kinesics takes place in the EFL teaching and learning activities. The informants of the present study were three English lecturers in which the first informant was as the main informant and the two other informants were the secondary informants. The data were gathered through interviews using a validated interview guide. Data analysis was done by using Interactive Data Analysis Model proposed by Miles &amp;amp; Huberman (1984). From the data analysis conducted, this present study found out that kinesics was always be found in the communication process in EFL teaching and learning activities as it was very beneficial to help the students in acquiring the target language. There were four types of kinesics dealing with the EFL teaching and learning process found. Those were gestures, head movements, eye contact, and facial expressions. Those basic aspects of kinesics are very useful and considered as an easier way to help the EFL students to understand the meaning of utterances containing some difficult vocabularies as well helped them to acquire the target language.
State-of-the Art Optimal Multilevel Thresholding Methods for Brain MR Image Analysis

The brain MR image analysis is a primary non-invasive component to detect any abnormality in the brain.It is a very important application in the field of medical image processing.For analysing brain MR images, there is a strong need to develop efficient image segmentation methods.Over the years, many image segmentation techniques have been suggested and their real life applications have also been studied.Implementation of these segmentation techniques in biomedical engineering is a major breakthrough.Intensive research works have been carried out explicitly on the analysis of human brain images and their subsequent detection of lesion cells using different segmentation methods.One of the easiest and most generally used method of segmentation is multilevel thresholding due to its precision and robustness against the other methods.To solve the problem of computational complexity for increasing threshold levels, various optimization algorithms are used for optimal multilevel thresholding.In this paper, an attempt is made to present a comprehensive review on the recent advancements in the area of brain MR image segmentation using optimal multilevel thresholding.This review is unique of its kind due to its exclusive emphasis on segmentation of brain MR image using thresholding technique only, which may not be present in the existing literature reviews.Different validation measures used for the multilevel image thresholding are discussed.A detailed comparison of the results obtained over the years is done.The merits and demerits of the methods are highlighted.This compilation aims to aid and encourage researchers to further explore the research in this direction.
The Effect of Indonesian and Hokkien Mobile Learning Application Models

Tiongkok is a country with a large population and is in several states. In addition, Tiongkok has a variety of languages. Hokkien is the worldwide language of China and is widely known to many people. This is evidenced by the many China Town markets. In Indonesia there has been a lot of Hokkien language guidance. In almost every elementary school in the city, adding Hokkien language lessons is a must for elementary school students. Even starting from the playgroup has also been taught Hokkien. But still there are children who do not understand because of the different ways of writing by reading Hokkien. In this research, the writer makes an android-based hokkien language learning media which can be utilized by users with mobile technology, designed learning media adapted to the curriculum in elementary schools with 5 subject matter. From the results of testing designed learning media can help make it easier for students to better understand hokkien language.
Control of Electric Wheelchair Suspension System based on Biodynamic Response of Seated Human Body

Electric wheelchair is one of the equipment to be used by the incapacitated and disable people. Constant exposure to vibration affects human comfort and health. Reducing the vibrations transmitted to the human body is important in the electric wheelchair design and becomes a healthcare industry demand. This paper deals with the study on vibration control of the electric wheelchair suspension system. A generalized model of the electric wheelchair suspension, including the biodynamic model of seated human body is presented. In order to achieve optimal suspension performance, an active control for wheelchair suspension is designed based on H-infinity control criterion. Numerical simulations are carried out to demonstrate the effectiveness of the proposed wheelchair suspension system. The simulation results show that the proposed control system can effectively attenuate the vibration amplitude and improve the wheelchair suspension performance. This control system could be used for electric wheelchair design and assist with improving human comfort.
ENHANCEMENT OF DEPTH MAP BY FUSION USING ADAPTIVE AND SEMANTIC-GUIDED SPATIOTEMPORAL FILTERING

Abstract. Extracting detailed geometric information about a scene relies on the quality of the depth maps (e.g. Digital Elevation Surfaces, DSM) to enhance the performance of 3D model reconstruction. Elevation information from LiDAR is often expensive and hard to obtain. The most common approach to generate depth maps is through multi-view stereo (MVS) methods (e.g. dense stereo image matching). The quality of single depth maps, however, is often prone to noise, outliers, and missing data points due to the quality of the acquired image pairs. A reference multi-view image pair must be noise-free and clear to ensure high-quality depth maps. To avoid such a problem, current researches are headed toward fusing multiple depth maps to recover the shortcomings of single-depth maps resulted from a single pair of multi-view images. Several approaches tackled this problem by merging and fusing depth maps, using probabilistic and deterministic methods, but few discussed how these fused depth maps can be refined through adaptive spatiotemporal analysis algorithms (e.g. spatiotemporal filters). The motivation is to push towards preserving the high precision and detail level of depth maps while optimizing the performance, robustness, and efficiency of the algorithm.
LOCK-FREE MULTITHREADED SEMI-GLOBAL MATCHING WITH AN ARBITRARY NUMBER OF PATH DIRECTIONS

Abstract. This paper describes an efficient implementation of the semi-global matching (SGM) algorithm on multi-core processors that allows a nearly arbitrary number of path directions for the cost aggregation stage. The scanlines for each orientation are discretized iteratively once, and the regular substructures of the obtained template are reused and shifted to concurrently sum up the path cost in at most two sweeps per direction over the disparity space image. Since path overlaps do not occur at any time, no expensive thread synchronization will be needed. To further reduce the runtime on high counts of path directions, pixel-wise disparity gating is applied, and both the cost function and disparity loop of SGM are optimized using current single instruction multiple data (SIMD) intrinsics for two major CPU architectures. Performance evaluation of the proposed implementation on synthetic ground truth reveals a reduced height error if the number of aggregation directions is significantly increased or when the paths start with an angular offset. Overall runtime shows a speedup that is nearly linear to the number of available processors.
Look Ahead at the First-mile in Livecast with Crowdsourced Highlight Prediction

Recently, data-driven prediction strategies have shown the potential of shepherding the optimization strategies for end viewer's Quality-of-Experience in practical streaming applications. The current prediction-based designs have largely focused on optimizing the last-mile, i.e., viewer-side, which 1) need the real-time feedback from viewers to improve the prediction accuracy; and 2) need quick responses to guarantee the effectiveness of optimization strategies in the future. Thanks to the emerged crowdsourced livecast services, e.g., Twitch.tv, we for the first time exploit the opportunity to realize the long-term prediction and optimization with the assistance derived from the first-mile, i.e., source broadcasters.In this paper, we propose a novel framework CastFlag, which analyzes the broadcasters' operations and interactions, predicts the key events (i.e., highlights), and optimizes the transcoding stage in the corresponding live streams, even before the encoding stage. Taking the most popular eSports gamecast as an example, we illustrate the effectiveness of this framework in the game highlight prediction and transcoding workload allocation. The trace-driven evaluation shows the superiority of CastFlag as it: (1) improves the prediction accuracy over other learning-based approaches by up to 30%; (2) achieves an average of 10% saving of the transcoding latency at less cost.
Applying Aspect Oriented Programming in Distributed Application Engineering

Aspect-oriented programming is an emerging programming paradigm that stretches during the development phases in different domains.Many researchers have focused on the use of this paradigm in web service composition in different research axis.However, none of them use together aspectoriented programming and design by contract to deal with the adaptation of the parameters in the web service composition process.This paper proposes a web service composition algorithm based on the planning graph using both Aspectoriented programming and design by contract concept.The aspect-oriented Programming approach provides explicit support for separation of crosscutting concerns in web services composition whereas the design by contract approach allows the processing of parameters execution in pre-condition and postcondition mode by using contracts in order to ensure correct service execution with adaptation to external parameters without touching in properties which can be dealt with re-construction of the composite service.Future development of this planning graph will include the introduction of the dynamic way of aspect oriented programming and add comparison results.
A smart login system using face detection and recognition by ORB algorithm

&lt;p&gt;We can identify human faces using a web Camera which is known as Face Detection. This is a very effective technique in computer technology. There are used different types of attendance systems such as log in with the password, punch card, fingerprint, etc. In this research, we have introduced a facial recognition type of biometric system that can identify a specific face by analyzing and comparing patterns of a digital image. This system is the latest login system based on face detection. Primarily, the device captures the face images and stores the captured images into the specific path of the computer relating the information into a database. When any body tries to enter into any room or premises through this login system, the system captures the image of that particular person and matches the image with the stored image. If this image matches with the stored image then the system allows the person to enter the room or premises, otherwise the system denies entry. This face recognition login system is very effective, reliable and secured. This research has used the Viola and Jones algorithm for face detection and ORB for image matching in face recognition and Java, MySql, OpenCV, and iReport are used for implementation.&lt;/p&gt;