Reviewerly/exHarmony huggingface dataset:
PENERAPAN MODEL PEMBELAJARAN PETA PIKIRAN UNTUK MENINGKATKAN BERPIKIR KRITIS DAN KETERAMPILAN MENULIS KARANGAN NARASI

This study aims to describe the application of the mind map learning model in improving students' critical thinking, improving the writing skills of narrative essays in Indonesian students of grade VII SMPN 3 Kikim Timur, describing how the effectiveness of the application of the mind map learning model in improving the writing skills of narrative essays in the eyes. Indonesian language lessons. The research design used was classroom action research (PTK) and quasi-experimental. The research subjects were students of class VII.A for the PTK class, class VII.B students for the experimental class and class VII.C students for the control class even semester of the 2020/2021 school year. The research instrument used observation sheets and tests. The research data were analyzed using descriptive statistics, mean, percentage, and t-test. The results of the study concluded that the mind map learning model could improve students' critical thinking and narrative essay writing skills in Indonesian class VII SMPN 3 Kikim Timur subjects
Detection of Abnormal Human Behavior in Video Images based on a Hybrid Approach

The analysis of human movement has attracted the attention of many scholars of various disciplines today.The purpose of such systems is to perceive human behavior from a sequence of video images.They monitor the population to find common properties among pedestrians on the scene.In video surveillance, the main purpose of detecting specific or malicious events is to help security personnel.Different methods have been used to detect human behavior from images.This paper has used an efficient computational algorithm for detecting anomalies in video images based on the combined approach of the differential evolution algorithm and cellular neural network.In this method, the input image's gray-level image is first generated.Because it may be possible to identify several large areas in the image after the threshold, the largest white area is selected as the target area.The images are then used to remove noise, smooth the image, and fade the morphology.The results showed that the proposed method has higher speed and accuracy than other methods.The advantage of the algorithm is that it has a runtime of three seconds on a home computer, and the average sensitivity criterion is 98.6% (97.2%).
The Research on Controlling Virtual Reality by EEG Sensor

In this paper, the research on the EEG sensor, which provides data sensing the human visual cortex is presented. We focused on various influences such as materials of objects, size of objects, etc. mainly from a time point of view. Thus, the reaction time of a person to process the visual object when he is focused on it. For these experiments, a virtual environment with a measurement system was created. It has several simple applications for controlling virtual reality objects by thought. For the experiments, the combination of Oculus Quest 2 and NextMind was used.
Learning Management Systems as Anti-Convivial Tools

The last two decades have seen an increase in the number of online university classes operating under any of several commercial Learning Management Systems (LMS). Online classes expanded dramatically in the US during 2020 as a response to the COVID-19 pandemic. Students, faculty, and administrators frequently assume that LMSs are epistemologically neutral. These LMSs are designed to do exactly what they say on the tin: they are systems for managing learning. At the same time, they function based on implicit understandings of “learning,” “management,” and “systems” that privilege some knowledges, interactions, and discourses while de-emphasizing others. In this paper I argue that the LMS as a tool is not—in the terms of Ivan Illich—convivial. Rather, LMSs as designed enforce a technocratic perspective based on efficiency and replicability, making them actively anti-convivial. At the same time, problems with LMS-hosted classes are defined in technological terms, with additional improved software being seen as the main solution. I argue that employing a critical participatory pedagogy can begin to address these concerns.
Magmatic Ni–Cu–Fe sulphide mineralization from the Halaguru area, Eastern Dharwar Craton, southern India

Here we report sulphide mineralization in a spinel-bearing orthopyroxene hornblendite from the Halaguru area, Eastern Dharwar Craton (EDC), southern India.The hornblendite contains approximately 3% olivine, 38% orthopyroxene, 56% amphibole and 2% oxide/ sulphide phases.Petrographic and mineral chemistry studies show its formation as a result of the reaction between early formed olivine and hydrous silicate melt without any metamorphic imprint, despite its proximity to amphibolites-granulite isograd in the EDC.The sulphides comprise the disseminated form of pyrrhotite-pentlandite-chalcopyrite assemblage, which is well crystallized and the primary magmatic features are preserved as contact and granular textures.Absence of crustal xenoliths and lower SiO 2 (48 wt%), Sr (35 ppm), Pb (<5 ppm), U (<0.1 ppm) and Th (0.10 ppm) content coupled with higher Mg# (~82), Ni (700 ppm), Cr (2500 ppm) concentration in the bulk sample rules out the possibility of sulphide saturation by the addition of crustal-derived sulphur.Based on the combined textural and compositional criteria, the pyrrhotitepentlandite-chalcopyrite assemblage is a product of the cooling and crystallization of immiscible sulphide globules.The initial high monosulphide solution, upon cooling, exsolves to pyrrhotite and pentlandite and later, at lower temperature, intermediate sulphide solid solution gives rise to chalcopyrite which is dominantly present around the edges of the pyrrhotite-pentlandite assemblage.
Penerapan Metode Median Filtering untuk Optimasi Deteksi Wajah pada Foto Digital

Face detection in digital photos aims to get the face area in the photo. Problems often occur when detecting faces, namely there is a lot of noise in digital photos so that it affects the detection process. Therefore, in this study apply the median filtering method to improve digital photos by reducing noise in the photos to be tested. The advantage of using this filter is to keep the edges smooth while reducing noise which aims to improve image quality. The ability of this method is measured using the parameters of Mean Square Error (MSE) and Peak Noise to Signal Ratio (PNSR). When the MSE value obtained is low and the PNSR value obtained is high, the results can be said to be good. The method used to detect faces in this research, viola-jones, was chosen because it is one of the face detection procedures with a high level of accuracy and good computational ability. The sample used in this study consisted of 10 digital photos taken using a Samsung A11 smartphone camera with a resolution of 13 mega pixels and 8 mega pixels in JPEG format. The results obtained in this study are the best error values in MSE 0.9517 and PSNR 24.2804. Based on these results, it can be concluded that the mean filtering method is feasible to be used in the case of face detection in this digital photo
Design of Accounting Information System in Data Processing: Case Study in Indonesia Company

This study aims to determine the implementation of System Application and Product in Data Processing (SAP) in a company to provide solutions for companies to obtain reliable reports and improve performance in a company.This study uses the mixed method through interviews with resource persons who have work in well-known company.The data obtained were analyzed by the method of literature study from data on the internet.The results of this study indicate that many companies still apply manual systems in reporting, one of them is the lack of adequate technological facilities within the company so that companies cannot fulfill their business processes optimally due to not using integrated system that connected with each other.
Deep Static and Dynamic Level Analysis: A Study on Infinite Mario

Automatic analysis of game levels can provide as- sistance to game designers and procedural content generation. We introduce a static-dynamic scale to categorize level analysis strategies, which captures the extent that the analysis depends on player simulation. Due to its ability to automatically learn intermediate representations for the task, a convolutional neural network (CNN) provides a general tool for both types of analysis. In this paper, we explore the use of CNN to analyze 1,437 Infinite Mario levels. We further propose a deep reinforcement learning technique for dynamic analysis, which allows the simulated player to pay a penalty to reduce error in its control. We empirically demonstrate the effectiveness of our techniques and complementarity of dynamic and static analysis.
Augmented Reality – Industrial use case

SGS-2021-028 ‘Developmental and training tools for the interaction of man and the cyber– physical production system’ carried out with the support of the Internal Grant Agency of the University of West Bohemia
Blind Image Deblurring Using Laplacian of Gaussian (LoG) Based Image Prior

Blind image deconvolution, a technique for obtaining restored image as well as the blur kernel from an inexact image. This research uses spatial characteristics to tackle the problem of blind image deconvolution. To work, the proposed method does not necessitate prior information about the blur kernel. Many applications, such as remote sensing, astronomy, and medical X-ray imaging, necessitate blind image deconvolution algorithms. This study used the maximum a posteriori (MAP) paradigm to create a new blind deblurring approach for removing blur from images. In beginning, we employed a Laplacian of Gaussian (LoG)-based image before regularising the gradients of an image. In the second phase, we used an operator known as the Iterative Shrinkage Thresholding Algorithm (ISTA) to cope with the non-convex challenge that develops during the entire deblurring procedure. Finally, we compared our method to several well-known methods in terms of quantitative and qualitative qualities, and we were able to determine which strategy was the most effective. Our findings show that the strategy we propose outperforms the others by a large margin.
Supply chain transparency, ethical sourcing, and synthetic diamond alternatives: exploring the perspectives of diamond retailers

Supply chain transparency is central to sustainable business operations, and consumers are more proactively seeking out socially responsible goods and services. At the same time, the diamond industry has traditionally been 'opaque'. The perception of 'blood diamonds' continues to be a challenge to the industry. The purpose of this paper is to explore the importance and perspectives of supply chain transparency of diamond retailers in the UAE and their perceptions of the importance of transparency and ethical sourcing for consumer diamond purchasing decisions. The research findings suggest that retailers currently perceive the consumers to be indifferent or unaware of the complexity of transparency in the diamond supply chain. However, some consumers did inquire about the origin. Additionally, as they are at the end of the supply chain, retailers do not have the means to guarantee that diamonds are ethically sourced.
A Mediated Model of Employee commitment: The Impact of Knowledge Management Practices on Organizational Outcomes

In this modern and competitive day, firms rely on innovative ideas to sustain and succeed. For today's management, it is critical to look for ways and means to knowledge management, and this study greatly emphasizes this aspect. This study investigates and investigates the impact of a knowledge management on organizational outcome as well as the role of employee commitment as a mediator. Essentially, it provides a framework via which a high-commitment work environment supports innovative work behavior in Kurdistan region of Iraq SMEs. Using the findings of this study, SMEs firms, particularly mobile network operators, can alter and innovate their services in order to thrive in a competitive market. All proven correlations are conceptually explained, practically tested, and supported by a survey of the literature. The findings revealed that all three variables in the study have a favorable association. All three hypotheses are accepted, and the association between knowledge management and organizational outcome is mediated by employee commitment.
Comparison of Deep Learning Approaches for Lithuanian Sentiment Analysis

Sentiment analysis is one of the oldest Natural Language Processing problems, still relevant and challenging today.It is usually formulated and solved as a supervised machine learning problem.In this research, we are solving the three-class sentiment analysis problem for the non-normative Lithuanian language.The contribution of our research is related to applying the innovative BERT-based multilingual sentence transformer models to the Lithuanian sentiment analysis problem.For comparison purposes, we have also investigated traditional Deep Learning approaches, such as fastText or BERT word embeddings with the Convolutional Neural Network as the classifier.The best accuracy ∼0.788 was achieved with the purely monolingual model, i.e., fastText (trained on the very large and diverse Lithuanian corpus) and the Convolutional Neural Network (refined in various text classification tasks).The backbone of the second-best approach (reaching ∼0.762) is the multilingual sentence-transformer-based model, which is the trend in text classification tasks, especially for the English language.
A Transfer-Learning-Based Approach for Emergency Vehicle Detection

The paper presents a computer-vision based approach for real-time detection of different types of emergency vehicles under heavy traffic conditions.This enables preferential path clearance for emergency vehicles by the traffic controller which has the potential of saving lives, properties and increasing the ability to prevent crimes and drastically reducing the total time required by an emergency vehicle to reach its target destination.The main challenge emergency vehicles faced in and around the cities is heavy traffic jams, which significantly hampers their operations resulting in a disastrous outcome.In most of the cities, emergency vehicles are equipped with unique colors and sound system which enable the traffic police to identify them.As our cities become smarter and transition into an era of artificial intelligence, the old system may not be sustainable due to that fact that it needs humans to constantly monitor emergency vehicle arrival at the intersections and also the sound produces by such vehicles may be nuisance and discomforting to the general public.This paper proposed a method of automatic detection of four different categories of emergency vehicle irrespective of the vehicle's shapes, models or manufacturers' using modified version of YOLOv5 object detection algorithm.YOLO is an acronym for (You Only Look Once) and it is an object detection algorithm that divides images into a grid system.Each cell within the grid is responsible for detecting objects within itself.YOLO is one of the most famous object detection algorithms due to its speed and accuracy.YOLO models are used for object detection with high performance which consists of 84 classes to detect and differentiate between 84 different objects.The proposed model developed here is based on 4 classes which are (Firetrucks, Ambulance, Police Car, and Normal Cars) classes.The top layers (fully connected layers) of the YOLO algorithm were re-designed and retrained to get new learned weights while freezing the bottom layers (convolutional layers) and retaining the pre-trained YOLOv5 weights.After retraining with the proposed modified YOLOv5, the model has shown promising results and quite impressive metrics in detecting and classifying emergency vehicles and normal vehicles.Using Mean Average Precision (mAP) metric, for police cars we achieved 98%, 96% for fire trucks, 89% for ambulances and 97% for normal cars.
ERROR ANALYSIS ON THE USE SIMPLE PAST TENSE IN NARRATIVE TEXT

The purpose of this research is to analyze of student’s errors on the use of past tense in Narrative text based on the problem that students felt confused about using past tense in their writing especially Narrative text. The method of research is qualitative descriptive. The subject of study researcher choose eight grade (2016/2017) in MTs Darussalam, Cepu. The result show that the researcher found four types of errors : omission, addition, misformation, misodering. Then, the researcher found the highest error made by students is misformation with 52% percentages. This problem influenced by student felt confused to understand simple past because they did not know the meaning and differences between regular verb and irregular verb. Therefore, students claimed if they seldom to practice writing paragraph.
Pengembangan Sistem Informasi Kawasan Agrowisata Menggunakan Konsep Model View Control berbasis Web

The business process of selling products from the Cimanggis Village community is still conventionally with a marketing strategy of offering words of mouth through business partners such as the community, retail, and markets, and the lack of access to information about product sales can hinder the product marketing process. This study aims to create a web-based agro-tourism area information system to help BUMDes and village UMKM overcome problems in ongoing business processes. Observation and interviews are methods used to collect data (needs analysis). Meanwhile, the MVC concept and the agile software development method were used to build an information system for agro-tourism areas in Cimanggis Village. This agro-tourism area information system is tested using black-box testing. The results of this study are data on UMKM activities and business processes in Cimanggis Village, design of information systems for agro-tourism areas, and evaluation of information systems. Data on business activities and processes are displayed in the current system analysis. The design of the information system is displayed in business processes, UML diagrams, and user interface views of the information system. The evaluation results show that the agro-tourism area information system can manage transaction data and information on UMKM products and tourism services with good results.
Text encryption for lower bandwidth channels: Design and implementation

Data security is critical for businesses of all sizes and types in the IT industry. Data security refers to the provision of secure data privacy protections to databases and websites, as well as the prevention of unwanted data access. Encryption is a critical data security approach in which unauthorized people or hackers gain access to unreadable material by encrypting digital data, software/hardware, and hard drives. Computing processes generate data, which is then encrypted and sent into the network using the key. In this work, an encryption approach has been proposed for low bandwidth channels. The proposed approach is compared with various other approaches like DES, 3DES, AES, blowfish, and RSA in terms of execution time and file size. It is observed that the proposed approach has a faster execution time than existing algorithms for data sizes less than 1 MB. However, once the data size exceeds 1 MB, the proposed approach takes longer to execute than previous algorithms. This implementation focuses on shortening the encrypted message in this proposed technique, increasing the complexity of the attacker's decryption. The key is generated by the message and sent together with the encrypted message. The key is the same length as the cipher text, and the cipher text is then reduced to the original message. Finally, the encrypted text and key are the same size as the original message.
Development of Android-Based Interactive Multimedia on Odd Semester Chemistry Materials for Class X SMA/MA

This study aims to develop android-based interactive multimedia for chemistry subjects for class X odd semesters that are valid, practical and effective.This research is a development research.The data analysis technique used is quantitative descriptive analysis technique and qualitative descriptive analysis technique.The results of this study are android-based interactive multimedia that has been developed based on the design (storyboard) that was designed, according to a review by two material experts, the average value of the three aspects considered to be in the valid category (93%), according to a review by a media expert , indicates a valid category (88%), and according to a review of two chemistry teachers showed the average value of the three aspects that were assessed in the good category (86.67%).Thus this interactive multimedia is said to be valid, practical and effective and can be implemented for the learning process.
Education of the future: an analysis of definitions (literary review)

The education of the future requires new approaches to the implementation of the target principles of this sphere of social activity. The reason for the transformation of educational principles and ideas is a cardinal change in the format of educational space associated with the active introduction of globalization factors and elements of information and digital technologies. The purpose of scientific exploration is to systematize the definitions of future education in the context of the content and format of educational activity. The objectives of the article are to identify the main priorities for the development of education in the short and long term. Methodology, which is able to ensure the implementation of goals and objectives of scientific research, is based on general scientific (analysis, forecasting, systematization), philosophical-scientific (synergetic), and prospective scientific and pedagogical (developmental pedagogy, digital pedagogy, pedagogical modeling) elements. A promising direction of research is structuring the definitions of future education in accordance with the actualization of certain clusters of the educational activity (socialization, digitalization, humanization). So, 4 clusters of definitions of future education perspectives are proposed: existential educational dimension, long-term educational strategies, short-term educational planning, futuristic projects in the educational space. The fundamental principle of planning of prospective models of education development will be the concept of education quality, which will include aspects of the purpose of education as a socio-cultural phenomenon and elements of the format of educational space.