Reviewerly/exHarmony huggingface dataset:
Anti- Forensics: The Tampering of Videos

In the context of forensic investigations, the traditional understanding of evidence is changing nowadays where most prosecutors, lawyers and judges heavily rely on multimedia substantiations.However, the evolution of easy-to-use media manipulating tools, made it very easy for almost any (technical) person to alter the content of a digital media (e.g.digital image, audio or video) without leaving any traces that can be detectable by human's basic perceptions.Therefore, the validity of the digital media can no longer be guaranteed which in turn leads to a serious problem regarding digital crime investigation.As there are tools which can tamper media, there are also ones that can do the reverse: detect the tampering.This paper sheds the light on the available anti-forensics tools.Experiments were done using some of these tools to detect tampered mediamore specifically video tampering.Our experiments showed the efficiency of these tools by differentiating between original and altered evidences.
Optimizing data augmentation policies for convolutional neural networks based on classification of sickle cells

Data augmentation is a key procedure in many image classification tasks, mainly to overcome the problem of small datasets. In this work, we exploit the data augmentation as a hyperparameter optimization approach. We tested our methods to classify erythrocytes to assist the diagnosis of sickle cell anemia. In this study, we proposed a data augmentation approach based on hyperparameter optimization to find the best augmentation policies through the Bayesian optimization algorithm. We also developed a convolutional neural network architecture from scratch and compared it with two classic architectures to classify sickle cell images. Our approach defines the best data augmentation solutions and sends those solutions to be carried out by CNN in the final training. All experiments were validated using a stratified five-fold cross-validation procedure, and our best result achieves 92.54% of accuracy. The results suggest the best augmentation policies defined with optimization allow us to obtain superior results than other strategies such as without data augmentation, several randomly defined image transformations, and only random rotations. As far as we know, our paper is the first to propose optimizing data augmentation policies in biomedical images leading to a better exploration of these strategies in several fields.
Frontiers in the emerging development of blockchain and Bitcoin: visual research based on big data analysis

In the era of the rapid development of information technology, the innovation of Fintech continues to send emerging research hotspots to the financial market. Based on the analysis of documents retrieved from the Web of Science database, this article provides a comprehensive data analysis and visualization of keywords such as “blockchain”, “bitcoin”, and “business and economic”. Using big data analysis technology and visual presentation, the author analyzed the details of the author’s keywords, popular organizations, countries, sources, and other key points of the correlation and external development status. Show the researchers the influence of the intersection of keywords, and point out the leading status of the organizations or countries with large resource occupancy in the research progress; at the same time, provide the researchers with an accurate grasp of the direction of the field and provide a reliable basis.
Analysis of feasibility and advantages of multi‐source image registration using regional features

Automatic registration of multi-source remote sensing data is a challenging task due to the high non-linearity of radiometric differences among various data. Feature extraction is a key enabling technique in registration algorithm design. In this letter, we prove the feasibility of using extracted regional features for multi-source image registration. In particular, regional features can be extracted through pixel-level image classification, and existing off-the-shelf algorithms can be directly adopted. Experiment results demonstrate the robustness of the regional-feature-based registration method.
MODEL OF TEACHER-LEADER DEVELOPMENT IN STEAM-ORIENTED EDUCATIONAL ENVIRONMENT OF GENERAL EDUCATION INSTITUTION

Тhe article is devoted to the analysis of the phenomenon of teacher leadership in the STEAM-oriented educational environment of a general education institution and the creation of a model of teacher-leader development in the STEAM-oriented educational environment. The model of teacher-leader development in the STEAM-oriented educational environ It is concluded that for the successful implementation of STEAM-education in the school it is important to develop a teacher-leader, whose roles include not only the participation of teachers as leaders in the classroom, school, pedagogical council, but also the functions of facilitator for students and teachers, teacher-innovator for ensuring the introduction of new pedagogical approaches, ICT, strategies, etc. in the school, a student who masters new knowledge, technologies, approaches and implements them in their pedagogical activities and consults and trains their colleagues. Ment of a general education institution is substantiated and designed.
Intelligence Quotient (IQ) Berpengaruh terhadap Perilaku Seksual Berisiko pada Remaja di Jakarta Pusat

The problem of risky sexual behavior among adolescents from year to year is reported to have increased significantly, this can be seen from the dating age which is still adolescents. Intelligence status which is still relatively low in adolescents can cause health problems, especially deviant behavior in adolescents This study aims to determine the relationship between Intelligence Quotient (IQ) and risky sexual behavior among adolescents in Central Jakarta. This research used quantitative analytic with cross sectional design. Sampling using purposive sampling technique in order to obtain a sample of 147 respondents. Research respondents were adolescents aged 17-19 years in Central Jakarta. The instruments used were primary data (questionnaires) and secondary data (IQ test results psychological test agency). The data analysis used was the bivariate statistical test using chi square and the multivariate statistical test using logistic regression. The results showed that there was a significant relationship between Intelligence Quotient (IQ) and risky sexual behavior among adolescents in Central Jakarta (p = 0.000, OR 22, 95% CI 0.561-0.801). Researchers recommend the role of educational institutions in developing adolescent creativity by using cognitive abilities to increase intellectual intelligence to avoid risky sexual behavior.
Research on Block Chain Product Evaluation System

Block chain technology has occupied a very important position in today's society.This emerging technology has been successfully explored and developed in many fields and scenarios.However, due to the fact that block chain technology is still in the exploratory stage, there is no rigid specification and index for block chain products, Integrating the research results of block chain technology architecture and security risk assessment, this paper designs a set of evaluation indicators for block chain products.The indicators are divided into six aspects, including P2P network technology evaluation index, distributed ledger technology evaluation index, asymmetric encryption technology evaluation index, smart contract evaluation index, consensus mechanism evaluation index and other security technologies Evaluation indicators, each big evaluation index is subdivided into several more in-depth evaluation indicators, and each of the specific analysis and explanation.Finally, based on the previous analysis and design work, a block chain product evaluation software is developed, which provides users with the function of comprehensive evaluation of block chain products.The design and software implementation of the block chain product evaluation system can effectively improve the efficiency in the development of block chain products and the quality of the products themselves, which is conducive to the further development of the block chain field.
Arsitektur Sistem Informasi Akademik Perguruan Tinggi Swasta Menggunakan EAP

Universities in Indonesia already have academic information systems. This university in developing its academic information system is carried out individually according to conditions and needs. Currently there are no guidelines in providing direction for the planning, development, implementation and service of academic information systems based on information and communication technology in universities. In addition to this, it is based on the planning and development of an academic information system which is what will be planned and developed and how its development guidelines are not yet available. The purpose of this study is to provide guidance in building academic information systems at private universities that can be applied in South Sumatra Province. This goal needs to be done because in general the academic information system business processes and services as well as the need for information in each university have in common namely the acceptance of new students, academic management and academic release. The result of the research is an academic information system architecture as a guideline in planning the development of an academic information system according to the conditions of private universities in South Sumatra Province. This study uses the EAP method with the steps of activities including planning initiation, business modeling and survey of current institutions, systems and technologies, data architecture and application architecture. The results of this study are a guide in building a system in the form of an academic information system architecture that can be applied to private universities in Indonesia especially South Sumatra Province.This study uses the EAP / Enterprise Architecture Planning method with activity steps including planning initiation, business modeling and institutional surveys, current systems and technology, data architecture and application architecture.
Hate Speech in Online Polylogues

This research is the first attempt in Georgia to analyse hate speech emerging in Computer-Meditated Communication. Particular attention is paid to the polylogal, asynchronic remarks made by members of the public reacting to online newspaper articles or press releases concerning the LGPT pride event planned for 18 - 23 June 2019, in Tbilisi, Georgia. The methodology is based on combining methods utilized in CDA and Genre Approach to (im)politeness which is in accord with the general approach to CMDA . At the first stage of the analysis, the examples of hate-speech acts were analysed according to the following criteria: identification of linguistic means and strategies employed while expressing impoliteness and specificity of identity construction (self-asserted versus others -asserted, positive versus negative, roles of participants and strategies of conflict generation or management). Next, linguistic peculiarities of hate speech (for instance, linguistic triggers [threats, insults, sarcasm incitements], wordplay, taboo, swear and derogatory words, metaphors, allusions and similes) were identified and analysed. Quantitative methodology was employed while stating the number of proponents and opponents of the event as well as statistical data referring to the number of linguistic and politeness strategies employed while expressing an opinion. This research shows particular tendencies of how impoliteness can be realised and how social identities can be construed using the example of hate discourse concerning LGBT pride in Georgia. However, to fully explore the genre properties of hate discourse in Georgia further research based on examples of hate-discourse strategies applied when discussing ethnic minorities and gender roles, is needed.
Cybersecurity: A Key Challenge to the Information Age in Sierra Leone

Humans' growing desire to continuously interact with each other through the internet has both negative and positive consequences, especially if users tend to use it maliciously. The advent of social networking sites has broken the traditional barriers to communication. It is a cost-effective way of communicating using text-messages, video-messages, and voice-notes as it happens from a source (sender) to the audience (receivers). Anyone can participate if they have a mobile phone with internet facilities, and now, everyone is an online journalist and a reporter. Unfortunately, although social media platforms have numerous merits, these platforms still face critical challenges, especially in controlling and policing content post by users. The revolution in information technology and social networking platforms have provided a NEW NORMAL for online fraudsters and criminals. Fake news, hate speech, and political propaganda/rhetoric has created a confusing world, especially during the Covid-19 pandemic situation. Therefore, our paper presented some of the challenges and solutions to cybercrime.
Deep Active Learning for Object Detection with Mixture Density Networks

Active learning aims to reduce the labeling costs by selecting only samples that are informative to improve the accuracy of the network. Few existing works have addressed the problem of active learning for object detection, and most of them estimate the informativeness of an image based only on the classification head, neglecting the influence of the localization head. In this paper, we propose a novel deep active learning approach for object detection. Our approach relies on mixture density networks to provide a mixture distribution for every output parameter. Based on these distributions, our approach is able to compute, separately and in a single forward pass of a single model, the epistemic and aleatoric uncertainty. We further propose a more efficient approach to reduce the computational cost of the mixture model. For active learning, we propose a scoring function that aggregates uncertainties from both the classification and the localization outputs of the network. Our extensive set of experiments on PASCAL VOC and COCO demonstrates that our modification to the object detection network yields better accuracy compared to the original one and, for active learning, our approach outperforms single-model based methods and performs on par when compared to methods using multiple models while requiring significantly lower computational cost. In addition, we show that our approach scales to different object detection networks and datasets acquired actively using our approach to transfer to different networks.
Deep Learning Identifikasi Tanaman Obat Menggunakan Konsep Siamese Neural Network

One of the roles of humans in community empowerment activities is in the health sector. Community empowerment in this field can be carried out through efforts to improve community health by utilizing family medicinal plants. The purpose of using family medicinal plants is so that the community can preserve these plants, reduce hospital costs, and serve as access to first aid for health if health services are difficult to reach. Based on this explanation, to increase public knowledge and understanding of the types of Toga and its benefits as a medicinal ingredient, it can be done several ways. One of them is through an in-depth learning approach. The deep learning approach with Siamese Neural Network is by comparing two patterns and producing an appropriate output based on the similarity of the two patterns. The application of Siamese Neural Network with an Android Smartphone is the right choice because it can facilitate the community in terms of usage. Based on these problems, the writer wants to build an application that can identify plants based on Android-based leaf images by applying the Siamese Neural Network approach. In this study, the results achieved were that the Siamese Neural Network could be implemented on Android-based smartphones. The application was able to identify family medicinal plants based on leaves.
PENERAPAN MODEL PEMBELAJARAN SELF ORGANIZING LEARNING ENVIRONMENT (SOLE) TERHADAP KEMAMPUAN LITERASI GURU PAUD

This study aims to verify the effect of the SOLE learning model on the literacy skills of Early Childhood Education Teachers in Banten Province. This research is quantitative research with a quasi-experimental type. The subjects of this study were Early Childhood Education Teachers Teachers in Banten Province. The research data collection technique was in the form of a test instrument. The data validity used content and construct validity. The data analysis technique used variance analysis. The results showed that there was an effect of the SOLE learning model on the literacy skills of Early Childhood Education Teachers teachers in Banten Province. The descriptive analysis of teacher activity shows that the experimental class (SOLE learning model) is better than the control class (conventional model). The conclusion of this study is that the SOLE learning model has an effect on improving the literacy skills of Early Childhood Education Teachers teachers.AbstrakPenelitian ini bertujuan untuk menguji pengaruh model pembelajaran SOLE terhadap kemampuan literasi guru PAUD di Provinsi Banten. Penelitian ini merupakan penelitian kuantitatif dengan jenis kuasi eksperimen. Subjek penelitian ini yaitu guru PAUD di Provinsi Banten. Teknik pengumpulan data penelitian ini berupa instrument tes. Validitas data menggunakan validitas isi dan konstruk. Teknik analisis data menggunakan analisis variansi. Hasil penelitian menunjukkan bahwa ada pengaruh model pembelajaran SOLE terhadap kemampuan literasi guru PAUD di Provinsi Banten. Analisis aktivitas guru secara deskriptif memperlihatkan bahwa kelas eksperimen (model pembelajaran SOLE) lebih baik daripada kelas control (model konvensional). Simpulan penelitian ini yaitu model pembelajaran SOLE berpengaruh meningkatkan kemampuan literasi guru PAUD.
Implementasi Kartu Uno dan Pengaruhnya terhadap Motivasi Dan Hasil Belajar Peserta Didik

This study aims to find out the implementation of uno card games on motivation and learning outcomes in motion system materials in class XI MAN Tasikmalaya Regency. This research was conducted from November to January 2020 in MAN Tasikmalaya Regency. Sample research as many as 2 classes, with sampling using cluster random sampling techniques. The instruments used in this study were test results of learning on motion system materials as many as 32 items of questions and motivational questionnaires learned as many as 22 items of statement. Data analysis techniques using U Mann Whitney. Based on the results of the study, it was concluded that there is a positive influence of uno card games on the motivation and learning outcomes of learners on motion system materials in class XI MAN Tasikmalaya Regency.
Penerapan Algoritma Naive Bayes Untuk Klasifikasi Penerima Bantuan Surat Keterangan Tidak Mampu

Rukun Warga 002 Kelurahan Meruya Selatan runs a government program, namely assistance for recipients of a certificate of being unable to meet the community's needs and aims to improve the community's welfare. Rukun Warga 002 has community services, namely death certificate services, making ID cards, disability certificates (SKTM), birth certificates, and many more. In carrying out assistance, most of the community complained that they did not get help, while some people were considered capable of getting this assistance. The researcher carried out data processing techniques with observation, literature study, and questionnaires based on this background. In contrast, the data processing used data mining to determine the incapable recipient's proper or inappropriate status, namely by using the Naïve Bayes algorithm while using the Rapidminer application, aiming to test the dataset's accuracy. In the dataset of incapacitated recipients used in this study, there are 35 records with eight attributes: name, occupation, age, status, income, vehicle, ownership, and roof of the building, while this research aims to predict and produce level values. Accuracy in providing assistance letters of incapacity to the people of 002 sub-district of Meruya Selatan using the naïve Bayes method. The trial results show that the system accuracy rate is 62.86%, a recall of 78.57%, and 52.38% precision.
Predicting Team Project Score: It’s More about Team Harmony and Less about Individual Performance

She enjoys serving as a "communication coach" to students throughout the curriculum, and she's especially
Robust Model-Based Clustering

We propose a class of Fisher-consistent robust estimators for mixture models. These estimators are then used to build a robust model-based clustering procedure. We study in detail the case of multivariate Gaussian mixtures and propose an algorithm, similar to the EM algorithm, to compute the proposed estimators and build the robust clusters. An extensive Monte Carlo simulation study shows that our proposal outperforms other robust and non robust, state of the art, model-based clustering procedures. We apply our proposal to a real data set and show that again it outperforms alternative procedures.
Perawatan dan Perbaikan Sistem Pendingin Mesin Induk Pada Kapal Perikanan

Diesel engine is one type of piston motor fuel, whose fuel combustion occurs due to high air pressure in the combustion chamber. The combustion process diesel engine generates heat energy and raises the high pressure in the cylinder, the pressure is comverted to mechanical energy on the crankshaft. Then the cooling system is needed on the main engine. The cooling system is one system that functions to maintain the engine temperature at a certain temperature in accordance with the design specified so that the diesel engine can operate sustainably. This research work aims to find out how to work the ship’s cooling system, to find out how to maintain the ship’s cooling system, to find out the interference that occurs in the cooling system and to make repairs. The working of the cooling system at KM Sumber Fortuna use a cooling system indirectly / closed by using a heat excanger as a place to heat the heat excanger media by circulating fresh water to the entire machine to remove heat arising from combustion and friction in the engine. The method of maintenance is carried out with the duty service for 4 hours, the service carried ou is to check all the engine components in KM Sumber fortuna. While the damage occurred in the seawater suction pipe which had leaked in the pipe binder and replaced the leaked pipe by cutting the new pipe or hose and clamping the pipe / hose on the suction side of the heat exchanger.
System Architecture of a Proactive Intelligent System to Monitor Health of Older Adults Living Alone

Worldwide improvements in the quality of life highlight immense need to have a remote health monitoring system that can provide critical biomedical data.This paper presents a low-cost health monitoring system, forming part of the Internet of Things (IoT), which aims at continuous, 24/7 monitoring of elderly people and disabled people.The system is implemented with a variety of sensors, for example, temperature, heart rate, and movement measurements, to observe a person's status.Doctors may also prescribe this system with a specific number and type of sensor, depending on a patient's condition.In a case study, three sensors measured the status of a person during the day.The measurements reflected the actions of the person as he/she relaxed or was active, in addition to monitoring his/her state of health.The observed data were recorded in a database that can be displayed by authorized caregivers.Results witnessed the efficacy of the proposed system.The proposed system finds enormous potential in giving remote healthcare facilities, especially to unaccompanied older adults.
SELF-EDUCATION IN DIGITAL SOCIETY

Татаринов Константин Анатольевич