Reviewerly/exHarmony huggingface dataset:
Pengembangan Mobile Learning Berbasis Client Server Pada Mata Pelajaran Simulasi Digital

This study aims to determine the level of Validity, Practicality and Effectiveness of Client Server-based Mobile Learning media in SMK Negeri 9 Padang. Because there are still limited learning resources and learning media in the form of interactive multimedia with mobile learning packaging at Padang Vocational High School 9. The study uses a development model (Four-D model). The development steps are (1) Define, (2) Design, (3) Development, and (4) Disseminate. The trial instrument was conducted on 31 students at Padang N 9 Vocational School. The sample in this study was 31 students. The results showed that the level of validity obtained was 82.17% with valid interpretations, the practicality level was 82.29%, which meant that it was practically used and for the effectiveness test level of 90.03, which meant that it was very effective to use the Learning Media Client Server Based Learning Media. Digital Simulation at SMKN 9 Padang
The use of information and communication technologies at the Higher educational system

Analyzed is, how widely and effectively information and communication technologies are used at the higher educational system. As a result of the study, it was found that in the process of distance learning students who belong to high and medium resource groups are more motivated, creative and efficient than students from families who belong to low resource groups. It has been determined that the main advantages of the distance learning format are the possibility of implementing individual educational trajectories of students, improving communication and the effectiveness of interaction between students and teachers, the ability to invite experts and practitioners to classes online, creating a more open and friendly educational environment. The study revealed the preferred forms of distance learning. Students from families who belong to highly resource groups, for the most part, believe that distance work of a teacher and student should be implemented mainly in the form of synchronous learning. Students from families who belong to medium resource and low resource groups generally prefer the format of asynchronous learning (recording lectures) and expanding students' independent work. Analyzed digital educational resources used by students of different groups. Regardless of gender, age, course of study and university, students widely use the digital educational resources of CyberLeninka. At the same time, it was found that students from families who belong to highly resource groups systematically turn to other digital educational resources: video lectures from Harvard and Stanford Universities. Based on the results of the study, measures are proposed to improve the effectiveness of distance learning at the university.
Hybrid Feature based Classification of Images using Supervised Methods for Tag Recommendation

Recent advancement in digital technology and vast use of social image sharing websites leads to a huge database of images. On social websites the images are associated with the tags or keywords which describe the visual content of the images and other information. Theses tags are used by social image sharing websites for retrieval of the images. Therefore, it is important to assign appropriate tags to the images. To assign related tags, it is necessary to choose appropriate classifier for automatic classification of images into various sematic categories with respect to the classification accuracy which is important step for image tag recommendation. In this paper, three supervised classifier algorithms are implemented for image classifications which are SVM, kNN and random forest and its performance is analyzed on Flickr images. For classification of images, the features are extracted using color moment and wavelet packet descriptor.
FACTORS MOTIVATING FOR INTERNET ADDICTIONS AMONG TEENAGERS

Objective To study the correlation of motivational factors with internet addiction.Methods A cross sectional study was conducted in 347 internet addicted teenagers with the help of semi-structured questionnaire consisting of questions related to motivational factors for internet use.Data were collected about variables and evaluated through multiple regression models. ResultsMotivational factors had high positive correlation with internet addiction at o.o5 level of significance.Motivational factors e.g.type of gadgets, location of internet use, availability of privacy and purpose of internet use (p = <0.001)are some of the factors highly associated with severity of internet addiction.Conclusions Motivational factors are highly associated with severity of internet addiction.Teenagers are vulnerable for internet addiction and efforts should be taken to modify the motivational factors.
MDC adaptive video streaming

Multiple Description Coding (MDC) is designed for multiple path video streaming with channel diversities. In this thesis, we investigate the performance of multi-path video streaming using the MDC technique. The MDC frame loss rate is one of the indicators of the real time video quality. A classification based framework for making mode decisions to minimize the MDC video frame transmission cost that may be defined in terms of the six parameters, number of sub-streams, number of transmission channels, GOP length, the I-frame positions, probability of network transmission states and probability of transmission changes. This thesis surveys the current status of horizontal decomposition into distributed computation, and vertical decomposition into functional modules such as congestion control, routing, scheduling, random access, and video coding. The focus of this thesis is on the video adaptive coding process to improve performance in terms of one or more of these factors. How to deliver a real-time MDC video from an end user over multi-channels is studied. The traffic is used to probe the network on determinig the network conditions and optimizing the coding algorithms appropriately. An efficient transmission statistical model Auto Regression (AR) to capture the properites of the region of interest is also introduced. Both the mode decisions and the error concealment require feedback from the network regarding the available bandwidth, loss probability, video coding methods and coding time spatial manners. The proposed algorithm works in a fully distributed environment, making it suitable for wireless ad hoc networks or other IP networks.
A Hybrid Method of Face Detection Based on Feature Optimization and Neural Network

The advancement of digital technology needs biometric security systems. Face detection plays an essential role in the security of digital devices. The detection of a face based on the lower content of the facial image for the processing of detection. In this paper modified the BP Neural Network Model for the detection of the human face. The modification of face detection algorithms incorporates feature optimization. The feature optimization process reduces the distorted features of the facial image. The optimized features of facial image enhance the performance of face detection for the optimization of features used glowworm optimization algorithms. The glowworm optimization algorithm is a dynamic population-based search technique. The concept of glowworm is a neighbor’s selection of worms based on the process of lubrification. For feature extraction we use discrete wavelet transform. The discrete wavelet transform function drives the features component in terms of low frequency and high frequency of facial image. The proposed algorithm simulated in MATLAB software and used a reputed facial image dataset from CSV300. Our experimental results show a better detection rate instead of the BP neural network model.
Defect Prediction and Dimension Reduction Methods for Achieving Better Software Quality

In quality of software, a fault discovery course is anticipated; intended to recover the taking up of various methods using cluster classifiers. Initially the classifiers are qualified on software record and then utilized to forecast if a forthcoming transformation originates a defect. Shortcomings of previous classifier based error prediction methods are inadequate presentation for realistic utilization and slow-moving forecast times due to a huge number of learned machine characteristics. Feature selection is a procedure in choosing a subset of pertinent characteristics so that the eminence of forecast replica can be enhanced. So that prediction recital of grouping techniques will be enhanced or sustained, whereas learning instance is considerably abridged. This effort commences by presenting a general idea of the datasets for error prediction, and then features a novel procedure for feature assortment by means of wrapper methods namely Fuzzy Neural Network (FNN) and Kernel Based Support Vector Machine (KSVM). The features chosen from FNN and KSVM are measured as significant characters. This effort examines numerous feature selection wrapper methods that are normally appropriate to grouping based error prediction. The system castoffs not as much of significant characters until optimal grouping recital are attained. The whole number of characters utilized for guidance is considerably reduced, frequently to lower than 15% of the unique. The general performance metrics is make used to estimate grouping systems such as accurateness, Recall, Precision, and F-Measure. It demonstrates that the anticipated Hybrid Hierarchical K-Centers (HHKC) grouping executes enhanced software quality compared to conventional grouping methods.
Pemilihan Media Promosi STMIK Pelita Nusantara Medan dengan Metode Analytic Network Process (ANP)

Analytic Network Process (ANP) algorithm is used to find optimal alternatives from a set of alternatives with certain criteria. Selection or process is carried out by evaluating promotional media by distributing questionnaires to students to find out the media to be evaluated next by selecting 4 promotional media, determining criteria and sub criteria by distributing questionnaires to the Chairperson of STMIK Pelita Nusantara, Puket III Student and Promotion Section, and The Chairperson of the Promotion, then processes the data using Super Decisions Software 2.4.0. The highest rating results obtained from the analysis and discussion show that the Internet (0.329). from the results of the distributed questionnaire data processing to the management of STMIK Pelita Nusantara Medan, namely the Chairperson, the Third Bouquet and Promotion Section, and the Chairperson of Pelita Nusantara STMIK Promotion, and the application of the Analyst Network Process (ANP) method with the Super Decisions 2.4.0 Application producing cracking the highest media is the Internet (0.329), followed by School Visits (0.274), Radio (0.213), and Banners / Billboards (0.185).
On or off the Slate: University Library E-Reserve Supports Web-Based Learning

Ryerson University Library in Toronto, Canada, embarked on an E-Reserve pilot project in 2004, providing electronic links to journal articles and scanned documents for course readings. Insufficient time allowed by faculty for copyright clearance, excessive copyright cost and the difficulty of achieving a single sign-on by users to access e-Reserve in Blackboard, the University’s courseware, were the major issues. Despite setbacks, E-Reserve continued to undertake innovative projects, using the new E-Reserve module in Blackboard to integrate course readings with faculty course pages, utilizing SFX open linking to connect citations to full-text articles, and experimenting with Web streaming of videos in Blackboard.
Indirect Estimation Of Distribution Algorithms For The Evolution Of Tree-Shaped Structures

This thesis explores indirect estimation of distribution algorithms (IEDAs) for the evolution of tree structured expressions. Unlike conventional estimation of distribution algorithms, IEDAs maintain a distribution of the genotype space and indirectly search the solution space by performing a genotype-to-phenotype mapping. In this work we introduce two IEDAs named PDPE and N-gram GEP. PDPE induces a population of programs, encoded as fixed-length gene expression programming (GEP) chromosomes, by iteratively refining and randomly sampling a probability distribution of program instructions. N-gram GEP attempts to capture regularities in GEP chromosomes by sampling the probability distribution of triplet of instructions (3-grams). We tested the performance of these systems using a variety of non-trivial test problems, such as symbolic regression and the lawn-mower problem. We compared PDPE and N-gram GEP with their predecessors, probabilistic incremental program evolution (PIPE) and N-gram GP, and the canonical GEP algorithm. The results proved that our methodology is more efficient than PIPE and the canonical GEP algorithm.
Persepsi dan Partisipasi Wisatawan terhadap Sampah di Pantai Pasir Padi Pulau Bangka

Background: The amount of rubbish in Pasir Padi Beach is about the assessment of public awareness, understanding of the assessment and participation of tourists visiting the beach about rubbish. Therefore, this study discusses the perception and participation of tourists related to trash cans in Pasir Padi Beach.Methods: The instrument used consisted of questionnaires with a Likert scale. The validity and reliability testing of each instrument uses the product valuation and Cronbach's alpha method, respectively and both were analyzed by Microsoft Excel.Result: The value of r count (1,688 – 14,099) &gt; r table value (1,661) on the validity test, while the Cronbach’s Alpha value on the reliability test (perception = 0,888; participation = 0,937) &gt; 0,66. The percentage who answered quite agree until agree on the instrument of perception and participation were 63% -100% and 55% -78%, respectivelyConclusion : The instrument proved to be valid and reliable so that it was good and feasible to be used in research. Related to the perception of Coastal waste as follows: the most distribution in Coastal and Coastal settlements, the largest source of food stalls, has no place to move garbage around the coast and there are no definite regulations which are the main causative factors, the main impact of waste is human health. The most important participation of the community in the action of reducing Coastal waste in Pasir Padi Beach is disposing of garbage in existing rubbish bins. All groups and levels of society have responsibility for beach cleanliness. In realizing the cleanliness of the Pangkal Pinang Coastal City, Bangka Island
Is it Still Worth Challenging the Status Quo? A Design Process Paper About the Involvement of Co-Dependent Users to Develop Safety Equipment for Horse Riders

Jockeys must wear safety vests as a piece of compulsory personal product equipment (PPE) due to the highly dangerous nature of horse racing. Notwithstanding that ‘design thinking’ became popular in various fields (e.g. business, education, health, IT), product innovation still not widely attract its application to the design of some PPE products. This article discusses a qualitative case study about the design of Australian safety vests for jockeys along with the application of user-centred design principles. This led to asking for a revision of this framework to accommodate design dependencies in terms of a suggested dependency-based user experience (D-UX) design framework along with further research in this field.
A framework for estimating relative depth in video

This dissertation proposes a novel framework for recovering relative depth maps from a video. The framework is composed of two parts: a depth estimator and a sparse label interpolator. These parts are completely separate from one another and can operate independently. Prior methods have tended to heavily couple the interpolation stage with the depth estimation, which can assist with automation at the expense of flexibility. The loss of this flexibility can in fact be worse than any advantage gained by coupling the two stages together. This dissertation shows how by treating the two stages separately, it is very easy to change the quality of the results with little effort. It also leaves room for other adjustments. The depth estimator is based upon well-established computer vision principles and only has the restriction that the camera must be moving in order to obtain depth estimates. By starting from first principles, this dissertation has developed a new approach for quickly estimating relative depth. That is, it is able to answer the question, “is this feature closer than another," with relatively little computational overhead. The estimator is designed using a pipeline-style approach so that it produces sparse depth estimates in an online fashion; i.e. a depth estimate is automatically available for each new frame presented to the estimator. Finally, the interpolator applies an existing method based upon edge-aware filtering to generate the final depth maps. When temporal filters are used, the interpolation stage is able to very easily handle frames without any depth information, such as when the camera was stationary. However, unlike the prior work, this dissertation establishes the theoretical background for this type of interpolation and addresses some of the associated numerical problems. Strategies for dealing with these issues have also been provided
Artificial Intelligence and Relativistic Computing

The article considers the fundamental question of the non-computable nature of algorithms that could serve as a basis for modeling brain consciousness and, therefore, for the develop-ment of artificial intelligence systems.The use of relativistic algorithms to overcome the Turing barrier is proposed.Quantum and relativistic algorithms are compared.The advantage of relativistic algorithms is shown
Manfred Horn biography

Manfred Horn, a German professor who has spent most of his life in Peru, is recognized by the Peruvian Physics community as one of the initiators of research activities in the country in the field of experimental physics, particularly in solid state physics and solar energy applications. The place where he developed his activities as researcher and teacher for more than 50 years is the National University of Engineering (UNI), Lima, but his experience and knowledge was spread out through all the country, particularly to rural areas, and he was particularly interested and very fond for young teacher qualification, especially of those from countryside universities. His personality, open mind and generosity, are particularly appreciated.
Evaluasi Sistem Informasi Admisi Terpadu Dengan Metode EUCS di RSUD Dr. Saiful Anwar Malang

Integrated Admision Information System (SISMIDU) is a system that serves to conduct bed managementdata in RSUD Dr. Saiful Anwar Malang. This system is a supporting facility to know the availability of bedinformation so that it can provide fast service in patients. The implementation of SISMIDU still has someobstacles that the system often encountered error in conducting patient data search, it takes a long time tosave data and system that is less update related to information availability of room in the inpatient area soas to cause inpatient buildup in the hospitalization of admission patient. The Purpose of this research is toevaluate the SISIMIDU based on user satisfaction. This type of research is qualitative research with datacollection through questionnaires. Method used is the End User Computing Satisfaction the methodconsisting aspects of content,aspects of accuracy, aspects of the format, aspects of timeliness and aspectof ease of use. Result of the research of the five aspects, among others, the aspect of content 67%respondents expressed satisfaction, aspect of accuracy 100% respondents expressed dissatisfied, aspectsof format 67% of respondents expressed dissatisfied, the aspect of timeliness 100% of respondentsexpressed dissatisfied and aspect of ease of use 100% expressed dissatisfied. It is hoped that hospitals canmake improvements and development against SISMIDU in order for SISMIDU to provide information thatsuits the needs of the user.
Quad-Copter (Pro-Q)

The unmanned Vehicles especially aerial are of great use and improved exponentially in last decade after development in the fields of AI and computer vision.(PRO-Q) is a specially designed vehicle which has the capability of a advanced quadcopter which is powered by a very powerful controller raspberry pi 3B+ . The flight controller (CC3D) fulfills the duty of keeping the quadcopter stable and performs the complex maneuver by using the 3-axis gyroscope and 3-axis accelerometer. This paper deals with using two controllers on a single quadcopter one to control maneuver and other to be programmed to do other various tasks that is user specific. The quadcopter is designed so that we have a advanced UAV which is able to record video and those videos can be used in further applications like computer vision.
Mereotopology for product modeling

Mereotopology is the branch of logic that treats the qualitative formalisation of parthood and connection relations between entities. Although it has apparently not yet found use in spatial reasoning for designed product modelling, the author proposes that it is well suited to the task. This paper introduces mereotopology and discusses some of the principles guiding the development of design mereotopology (DMT), a logic being developed by the author for product modelling. Typical MT logics cannot be applied directly to engineering applications because they assume a "common sense" approach, whereas design requires a more strict "engineering sense." DMT can provide a framework for improved understanding of product modelling knowledge and will lead to better computer-based aids to manipulate that knowledge.
Performance Research on Iterative Methods for Image Deblurring

This paper introduces the iterative image restoration algorithms for the elimination of linearly varying blurs from the images degraded by motion blur and additive noise. Iterative algorithms are very operative for this applications since they include different types of prior knowledge about the class of reasonable solutions. These algorithms are robust in nature to the errors in estimating the blurring operators and can be used to remove the non-stationary blurs. Performance analysis and limitations of traditional approaches such as Inverse, Wiener and Constrained Least Square filters (CLS) are discussed with respect to the iterations. Role and choice of imposing a constraint on the solutions of the algorithms which gives better restoration results are discussed. Regularization methods are debated to Minimis extreme noise amplifications due to ill-posed conditions in the inverse deblurring problems and it is shown that the reduction of noise effects can be achieved by terminating the algorithm after finite number of iterations. It is shown that restoration algorithms with constraints and spatially adaptability reduces the effects of ringing artifacts significantly. The rate of convergence of the algorithms based on the variations in the number of iterations are discussed and performance analysis, limitations and Comparison with the experimental results are presented.