Reviewerly/exHarmony huggingface dataset:
EVALUASI MEDIA BERBASIS WEBSITE UNTUK MEMBANTU MENGIDENTIFIKASI KARIR SISWA DI MAN 2 BANTUL, D.I. YOGYAKARTA

This research was conducted to evaluate media with career assistance for class XII students at MAN 2 Bantul, D.I. Yogyakarta by using a qualitative descriptive approach. Media evaluation helps this career using the Context, Input Process and Product evaluation model or what is often called the CIPP Evaluation Model. The basis for selecting this evaluation is because it covers more as a whole than other evaluation models. As the name implies, the aspects in this evaluation are Context, Process Input and Product. Context evaluation which is intended to examine the background of media production, Evaluation of input or input reviews regarding materials and supporting resources both facilities and infrastructure, Process Evaluation is evaluating users and also product evaluation, namely studying media results, helping careers developed. The focus of research on evaluating media assistance in career selection for class XII students at MAN 2 Bantul is based on a website. The hope of evaluating the development of this media is that the media will have better product quality and be more useful.
A Gradient Boosting Approach for Training Convolutional and Deep Neural Networks

Deep learning has revolutionized computer vision and image classification domains. In this context Convolutional Neural Networks (CNNs) based architectures and Deep Neural Networks (DNNs) are the most widely applied models. In this article, we introduced two procedures for training CNNs and DNNs based on Gradient Boosting (GB), namely GB-CNN and GB-DNN. These models are trained to fit the gradient of the loss function or pseudo-residuals of previous models. At each iteration, the proposed method adds one dense layer to an exact copy of the previous deep NN model. The weights of the dense layers trained on previous iterations are frozen to prevent over-fitting, permitting the model to fit the new dense as well as to fine-tune the convolutional layers (for GB-CNN) while still utilizing the information already learned. Through extensive experimentation on different 2D-image classification and tabular datasets, the presented models show superior performance in terms of classification accuracy with respect to standard CNN and DNN with the same architectures.
The Impact of Contemplative Teaching on Fostering Iraqi (High) School Students Willingness to Communicate (WTC) and Speaking Fluency

This study investigates how contemplative education and teaching backs up Iraqi EFL learners to become more willing to speak in class. After data analysis and interpretation of the performance of 72 young Iraqi students in two language schools in Iraq, the researchers found how recruited participants responded to contemplative teaching strategies in their speaking class and developed a higher willingness to interact with their teacher and their cohort Based on the results, those students who received instruction through contemplative teaching did better than students who received the traditional speech program. Moreover, those students who had more communication skills proved to be more fluent than those who had less. Based on the results and the discussion of pre-test and post-test results, the willingness of students to communicate in questionnaires, analysis of student behavior and the classroom behavior of teachers, the researchers concluded that the reflective teaching strategies and techniques used in this study have a positive impact on student&amp;rsquo;s desire to communicate and speak fluent intermediate level language skills.
Effect Percentage of Seam Carving Implementation on Image Based on Texture Characteristics Using GLCM

flexibility of the appearance of electronic devices currently causes new demands on digital media, especially for the provision of content. Until now, images, although an important element in digital media, usually remain rigid in terms of size and cannot change size so that they cannot adjust to different layouts automatically. The solution to overcome this problem is by resizing the image. One method that works well for resizing images is seam carving. Seam carving aims to resize the image by not eliminating important content in the image. This study aims to see the effect of changing the texture of seam carving images to images that have different levels of complexity. The trial was conducted by comparing the original image and seam carving image. Seam carving image used is differentiated based on the ratio scale, which is 10%, 20%, 30%, 40%, 50%. Testing is done by processing 4 image samples using the Gray Level Co-Occurence Matrix (GLCM) method including Contrast, Correlation, Energy and Homogeneity. Then testing is done by comparing the original image with seam carving image using the features of GLCM. From the test results it can be concluded that seam carving as a method of resizing images can work well, with the comparison of textures using GLCM the highest level of similarity reaches 98% and the lowest is 86%.
Constructing “Electronic Liability” for International Crimes: Transcending the Individual in International Criminal Law

Abstract It is increasingly clear that autonomous agents can commit international crimes such as torture and genocide. This article aims to construct ‘electronic liability’ for such international crimes. It will argue that it is not sufficient to hold the persons or programmers behind the autonomous agents liable, but that it should be possible to hold the autonomous agents that commit international crimes liable. It will examine ways in which legal personality can be attributed to machines and argue that if there is a continuum of potential subjects of ICL, then the argument for electronic personhood and liability of machines is as compelling as for other non-humans such as corporate entities and animals. It will be argued that the ICC will potentially only be able to meaningfully prosecute international crimes committed by autonomous agents if it is willing to accommodate strict liability and other faultless models of liability that have so far been anathema to international criminal justice.
THE VULNERABILITY OF PROVING FRAUD AS THE BASIS FOR CANCELLING AGREEMENTS IN THE DIGITAL ERA

Civil Law grants freedom to everyone to agree on something as long as it fulfills the valid agreement requirements stated in Article 1320 of the Civil Code. The consent condition is mentioned in Article 1321 of the Civil Code. Consent is invalid if there is a mistake, coercion, or fraud. This writing discusses consent that is not valid due to fraud. Article 1328 of the Civil Code states that 'fraud is a reason for the cancellation of an agreement if the deception used by one of the parties is so obvious and clear that the other party would not have agreed if there was no deception.' It is not easy to prove fraud in an agreement that has been made, as the party that feels deceived is not in a position of 'being forced' and voluntarily signs or digitally approves the agreement with a submitted or accepted mark. More detailed regulations regarding canceling agreements due to fraud are needed to provide legal certainty and justice for the parties.
Computing Safety in Digital Watermarking: A Review Paper

Abstract: Digital data which is concealed in carrier signal is known as Watermarking. Digital data is embedded within another file is called Steganography, watermarking algorithms are used for keeping the watermark vigorous to attack and Steganography fortifiesthe information from impostors. Quality of the signal is tarnished when the impostor wants to infiltrate the signal and tries to remove the watermark and it becomes unusable. Information hiding is necessary in several area. Two type of outbreaks are there. Major one is active attack in which the attacker deviates the entire content. Second one is submissive attack in which the invader attempts to presume the secure data through eavesdropping. Dissimilar image data hiding attacks were presented in this paper
Weather Forecast with Map Using JavaScript

Weather Forecast Using JavaScript is the application of science and technology to predict the state of the atmosphere for a given location.
A Novel Global Calibration Approach for Multi-Viewpoint 3D Vision Measuring System

To unify the local 3D point clouds for the measured object with big size or complex structure to a global coordinate system, we usually need to adopt global calibration approach to calibrate the transformation relationship between the global binocular vision sensor (GBVS) and measuring binocular sensor (MBS) in different viewpoints in the 3D Vision Measuring System (VMS). The field of view (FOV) of the two global cameras in GBVS determines the measurement range of the 3D VMS in the global calibration process. In the traditional 3D VMS of single-station multi-viewpoint, the measurement range is limited because of the two global cameras in the GBVS are needed to have a public FOV. Then, the global calibration process is also limited. And the global calibration process is complex and easy to cause error accumulation when a laser tracker is used to replace the GBVS in the 3D VMS. In order to solve this problem, we proposed a novel global calibration approach based on multi-directional target (MDT) for a novel designed 3D VMS. It can achieve the function of global calibration for the designed 3D VMS once the MDT appears in the FOV of the global camera. Finally, we adopt two global cameras which don’t need to have a public FOV to form GBVS. It can further expand the measurement range of the 3D VMS. And the global calibration efficiency can also be improved at the same time. The feasibility and effectiveness of the proposed global calibration algorithm are verified through experiments. The experimental results show that the accuracy of the proposed global calibration algorithm can reach up to 0.08mm after optimizing. It has broad application prospects and practical theoretical research value.
Underwater Image Processing

This paper focuses its attention towards underwater image processing in order to improve the image quality.As most of the images of offshore installations, drinking water reservoir etc. are captured and inspected manually by divers.And manual intervention in this regard is dangerous, costly, time-consuming and yet does not often enable a full assessment.Hence camera based inspection is used to capture the images under water.Using cameras underwater poses major technological challenges.The objects in the underwater images are faint, difficult to view and analyze because the images of such environment loses the details of the object.The underwater images usually suffer from non-uniform lighting, low contrast, skew, blurs and diminished colors.And hence in this research work, a novel method has been proposed for handling underwater image skewing and blurring in case of unidirectional cyclic waves and circular ripples to enhance the visibility of underwater images.The geometric distortion such as skew is caused by the time variant refraction over the dynamic fluids.And this distortion is associated with motion blur depending on the exposure time of camera.The proposed work develops a mathematical model for image restoration from these distortions with good accuracy.
Emotion Detection From Text

Emotion can be expressed in different ways that can be seen such as facial expression and gestures, speech and by written text. Emotion Detection in text documents is necessarily a contentbased classification problem immediate concepts from the domains of Natural Language Processing as well as MachineLearning.In this paper emotion recognition based on textual data and the techniques used in emotion detection are discussed.
A systematic review of the quality and timeliness of public health data

The quality and timeliness of public health data is a topic of prime concern in this information age. Many epidemiologists, health scientists and researchers in the public health domain have consistently emphasized on the importance of the need for the right timely data for the right decision-making at the right time. In other words, there is an urgent need to ensure that the right data reaches the right people at the right time. However, this urgent need appears to be misleading and not achievable in the current public health practices and workflow processes. The workflow processes in the current healthcare environments enable data collection to be delayed and only to be captured when the events have already occurred. In this paper, a systematic review of relevant scientific literature was used to not only explore the complexity and uniqueness of public health data, but also explain why improving the quality and timeliness of public health data is a challenging endeavor for many epidemiologists, health scientists and researchers. Recommendations for streamlining the public health workflow processes to support the generation of high-quality and timely public health data were also discussed in the paper.
Review on Credit Card Fraud Detection System using Machine Learning

This review paper is discussing the use of machine learning in detecting cred-it card fraud.With the increasing number of online transactions, it is becoming more important to have accurate systems in place to identify fraudulent activity.The authors are proposing the use of machine learning algorithms to analyze and pre-process data sets in order to accurately detect fraudulent credit card transactions.The objective is to identify 100% of fraudulent transactions while minimizing false positive fraud classifications.The paper focuses on using machine learning techniques on transformed credit card transaction data to achieve this goal.
Influence of social networks on the students of Cardenal Maure school

This article took as its main objective to analyze the use of the internet by young students of 6th junior high education unit Cardenal Maurer, identify the types of social networks and influence in their lives, so knowing the consequences that affect in the teaching-learning process during training. To this end document review data and quantitative and qualitative techniques were used.
Hybrid Chaotic Keystream Generator Based on Dawson’s Summation Generator

The IoT consists of a vast number of interconnected sensors, and ensuring secure communications between these sensors is a crucial concern.In this study, we apply chaos theory to the security of real-time communications in the IoT.Chaos theory has been increasingly utilized in cryptography in recent years, with the proposal of numerous stream ciphers based on chaos.We merge different 1D chaotic maps and construct a hybrid keystream generator.To increase the randomness and linear complexity of the output sequence, we use a nonlinear Dawson's summation generator (DSG) to mix different chaotic outputs.The proposed keystream generator is suitable for real-time IoT communications as it features a low computational load and an improved throughput.Our analysis of the proposed keystream generator includes an evaluation of its resilience against known attacks, a measurement of its linear complexity, and statistical random number tests on the output keystream.The proposed keystream generator achieved a pass rate of 100% for the statistical test of the FIPS PUB 140-1 standard and a pass rate of at least 96% for that of the NIST SP800-22 standard.
A study on some relations on multi-fuzzy (left-right)ideals of rings

multi fuzzy set theory is an extension of fuzzy set theory, which deals with the multi dimensional fuzziness. In this paper, we introduce the concepts of multi-fuzzy rings, multi fuzzy ideal, image of multi- fuzzy ideal of a ring under homomorphism, Cartesian product of multi-fuzzy set, and some related properties and theorems are investigated. The purpose of this study is to implement the fuzzy set theory and rings theory in multi-fuzzy rings.
Development of Health Screening Information System for Elementary School Children at Dalam Kaum Sambas Public Health Center, Sambas Regency - West Kalimantan

Dalam Kaum Sambas Public Health Center is one of the public health centers that carry out the main activities of health improvement efforts in the form of promotive and preventive efforts, namely health screening for elementary school children, which are carried out manually, causing problems such as the length of recording, drawing conclusions based on examination results and recapitulation that are at risk of errors. This study aimed to develop an Information System for Primary School Children's Health Screening (SIPEKASDA) at Dalam Kaum Sambas Public Health Center. This research method is Research and Development (R&amp;D) with system design using the Waterfall model and system evaluation with the EUCS End User Computing Satisfaction (EUCS) model. The design of the Information System in this study includes a Data Flow Diagram, Flowchart, Entity Relationship Diagram and User Interface, which produces an Information System with several menus, namely processing student data, parents, student class mapping, health checks and recapitulation of school-based health check results. The results obtained from SIPEKASDA include; the presentation of examination results data and recapitulation of examination results per school, village and sub-district. SIPEKASDA is a website-based information system that can be accessed anywhere and anytime. The quality of the Primary School Children's Health Screening Information System assessed from the evaluation of information systems using the End User Computing Satisfaction (EUCS) model is very good, which reaches 83.58%, so the information system can be relied on if you need data at any time. One of the principles of using information systems is timelines or the speed of information systems in responding to what is done by its users, presenting data promptly and up to date so that the use of information systems can increase. Problems in recording inspection results, data processing, data recapitulation, report making, and ease of accessing the system can be adequately resolved after the system is made.
Modern Trends in Indian Education - Need of the Hour

India has been showing consistency in commercial growth patterns and pushing for an advanced share of Industries and service sectors of the economy.Still, the only area which needs reform is the "instruction system".In the development process, some investments are indeed taking place in the country's higher education system.Still, it is yet to establish world-class research facilities, employ profound academicians in universities/colleges/research institutions, etc., to achieve sustained economic development on par with Global standards.For that, we have already modernized; our curriculum and infrastructure facilities with both government and private participation.But, our methods of instruction at the Higher education level still cornered around that traditional and semimodernized methods and techniques, despite of the youth wanting latest technologies in teaching and learning.Hence, there is an urgent need to adopt modern practices and approaches in the system of Indian education.This particular paper analyses the possibilities in a concise manner.
Pengembangan Sistem Pendeteksi Gesture Angka pada Tangan secara Realtime Berbasis Android

&#x0D; &#x0D; &#x0D; &#x0D; The Image Processing technology growing very rapidly now days. Many research develop this system. Cause image processing system can help deaf communication. Communication is a very important basic in life. Based on health profile in 2005 from Indonesian Ministry of health, the Indonesian congenital deafness reached 214.100 people. The congenital deafness is a hearing loss since birth, which lack of nerve impulses in the ear to convert the mechanical energy of vibration into electrical energy. &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; With translator applications from sign languages to text, the deafness will be facilitated to interacting with other, despite the person canâ€™t understand sign languages. The pupose of Numbering Gesture Recognition Application exists is to be basic for the next research to built translator sign languages to text. Android platform choosen because this platform already spread and open source, so it will be easily to spread this application.
Performance Evaluation Of Supervised Machine Learning Classifiers For Mapping Natural Language Text To Entity Relationship Models

Transforming natural language requirements into entities involves a thorough study of natural language text. Sometimes mistakes are made by designers when manually performing this transformation. Often, the process is time-consuming and inaccurate. Hence, multiple research studies have been performed to assist inexperienced designers in mapping a natural language text into entities and reducing the time and error that such a method entails. This work is part of those studies. Human intervention is a significant constraint for prior studies. In this paper, machine learning classifiers are used to eliminate human intervention. The system performs well in predicting entities and has achieved 85%, 75% and 80% for recall, precision and the F-score, respectively. The system also performs well in predicting nouns which do not represent entities and has achieved 68%, 79% and 76% for recall, precision and the F-score, respectively. The performance level of the system is the same as other model generation tools found in the literature. The system is distinguished from these tools in using machine learning classifiers as a technique for establishing entities with no human intervention. Furthermore, the study finds that when distinguishing entities from other nouns, logic-based classifiers, perceptron-based classifiers and SVM classifiers perform better than statistical learning classifiers. The decision tree classifier, neural network classifier and SVM classifier all work well. The decision tree is the better because it can provide a decision tree that defines when a noun is an entity and when it is not based on given features; this is not the case with the neural network classifier and SVM classifier.
Pengembangan Game Math Story Problems Menggunakan RPG Maker MZ untuk Anak 4-7 Tahun

This study aims to produce and test the feasibility of an RPG (Role Playing Game) Math Story Problem created using the RPG Maker MZ software. The research method used is the Research and Development method using research stages (1) needs analysis, (2) design, (3) implementation, (4) validation, (5) revision and (6) product testing. The requirements analysis stage is used to analyze competency standards, hardware and software specifications. The design stage includes storyline design, display design, flowchart and character creation in the game. The implementation stage is the stage of realizing the design into an actual product. The validation stage is carried out to assess the feasibility of the game that has been designed and created which is then determined by the experts to get the criticism and suggestions needed for improvement so that the game becomes even better. The trial phase is carried out by direct application in children's learning. This test was conducted on respondents aged 4-7 years using a questionnaire. The data obtained were processed by descriptive analysis to determine the level of feasibility of the game. The results of data analysis showed that the feasibility level according to material experts was 96% which was included in the very feasible category and children as users was 83.75% which could be categorized as very feasible.