Reviewerly/exHarmony huggingface dataset:
Copyright Protection of Scientific Works using Digital Watermarking by Embedding DOI QR Code

Digital identifier is a technology used to prove ownership of a work. At this time, the Digital Object Identifier is a form of implementation of the digital identifier used in every scientific work. Not infrequently there are several cases of theft of ownership or copyright of a work, both scientific works, and certain other works. Watermarking is a technique created to protect the ownership of works. Watermarking techniques can be applied to several media such as audio, video, and also documents, one of which is the Portable Document Format document file. In this study, researchers want to build copyright protection for scientific works. Researchers offer research concepts using a Digital Object Identifier which is always installed on scientific papers to be published. The Digital Object Identifier will later become the basic data in building the Quick Response Code. The Digital Object Identifier of each scientific work will not be the same as each other, this will certainly make the Quick Response Code more unique. The results show that the watermarking process in building copyright protection of scientific works can be very successful Quick Response Code can be read and detected properly without experiencing lag time. Quick Response Code readings from several variations of motion are also not very influential, so it can be concluded that distance does not limit the detection of Quick Response Codes. From this research, researchers can deduce that the watermark is performed on the scientific work not only serves as the copyright protection of that scientific paper but can also be an alternative for other researchers to access the scientific work.
Gold price prediction using Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM)

Gold has an important role in worldwide economics. Gold is not only used in jewelry but also can be a good deal for investment however several factors can affect the fluctuation in gold which can make the risk of investing in gold is bigger for many people. Therefore, is very important to predict the gold price for people who invest in gold in order to help reduce the investment risk. This study will implement a hybrid method from Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). CNN can extract useful knowledge and learn the internal representation of time-series data, and LSTM networks will identify short-term and long-term dependencies effectively. This research will use daily time frame data and weekly time frame data. This research also tried some experiments to find the best hyperparameters of batch size and epochs in ratio data 60:40 and 80:20. The best result obtained in the daily time of ratio data 60:40 with RMSE 13.67953 and MAE 9,40998, while in ratio data 80:20 has RMSE 15,53199 and MAE 12,78120. In weekly time has obtained the RMSE 38,01949 and MAE 28,32035 for ratio data 60:40 while in ratio data 80:20 the result was RMSE 32,61283 and MAE 22,74638. Those results shows that CNN-LSTM model can predict the trend of daily time frame gold price.
Contact Tracing Apps in ASEAN: A Threat to Privacy and Personal Data

On March 11 2020, the World Health Organization (WHO) officially categorized the Coronavirus disease (COVID-19) as a global pandemic. The rapid spread of COVID-19 prompted governments all around the world to take steps toward controlling the pandemic and its significant socio-economic impacts. Digital technology has been relied upon to provide innovative solutions to aid efforts of stopping the spread of COVID-19. One such innovation is the development and implementation of contact tracing applications or apps. The use of these apps allows public health authorities to track confirmed cases of COVID-19 and mitigate its transmission. However, as useful as they may be, there exists a well-grounded fear that contact tracing apps may be used as a tool to broaden government surveillance powers. This is especially true among member nations of the Association of Southeast Asian Nations (ASEAN), where domestic regulations guaranteeing the right to privacy and protection of personal data are relatively weak. Additionally, ASEAN lacks a comprehensive and strong regional mechanism for the protection of human rights and personal data. This paper aims to analyze the implementation of contact tracing apps in ASEAN member states, whether its implementation fulfills the international standards of the protection of the right to privacy and personal data, as well as provide recommendations to ensure that countries do not spiral towards a state of unrestricted government surveillance.
General Cybersecurity Maturity Assessment Model: Best Practice to Achieve Payment Card Industry-Data Security Standard (PCI-DSS) Compliance

The use of technology in the era of the Industrial Revolution 4.0 is essential, marked by the use of technology in the economy and business. This situation makes many companies in the payment sector have to improve their information technology security systems. In Indonesia, Bank Indonesia and the Financial Services Authority (Otoritas Jasa Keuangan - OJK) are agencies that provide operational permits for companies by making Payment Card Industry-Data Security Standard (PCI-DSS) certification as one of the requirements for companies to obtain operating permits. However, not all companies can easily get PCI-DSS certification because many companies still do not meet the PCI-DSS requirements. The research offers a methodology for measuring the level of technology and information maturity using general cybersecurity requirements adopted from the cybersecurity frameworks of CIS, NIST, and Cobit. Then, the research also performs qualitative calculations based on interviews, observations, and data surveys conducted on switching companies that have been able to implement and obtain certification. PCI-DSS to produce practical cybersecurity measures, in general, can be used as a measure of the maturity of technology and information security. The results and discussion provide a model assessment tool on the procedures and requirements needed to obtain PCI-DSS certification. The maturity level value of PT XYZ is 4.0667 at maturity level 4, namely quantitatively managed, approaching level 5 as the highest level at maturity level.
Speech Emotion Recognition

Abstract: Speech Emotion Recognition, abbreviated as SER, the act of trying to identify a person's feelings and relationships. Affected situations from speech. This is because the truth often reflects the basic feelings of tone and tone of voice. Emotional awareness is a fast-growing field of research in recent years. Unlike humans, machines do not have the power to comprehend and express emotions. But human communication with the computer can be improved by using automatic sensory recognition, accordingly reducing the need for human intervention. In this project, basic emotions such as peace, happiness, fear, disgust, etc. are analyzed signs of emotional expression. We use machine learning techniques such as Multilayer perceptron Classifier (MLP Classifier) which is used to separate information provided by groups to be divided equally. Coefficients of Mel-frequency cepstrum (MFCC), chroma and mel features are extracted from speech signals and used to train MLP differentiation. By accomplishing this purpose, we use python libraries such as Librosa, sklearn, pyaudio, numpy and audio file to analyze speech patterns and see the feeling. Keywords: Speech emotion recognition, mel cepstral coefficient, neural artificial network, multilayer perceptrons, mlp classifier, python.
CODE MIXING IN NOVEL RANGE OF STORIES BY GITA SAVITRI DEVI AND ITS RELATION TO NOVEL TEXT

This research is motivated by the use of code-mixing in the novel Range of Stories by Gita Savitri Devi. This study aims to describe the form and function of code-mixing in the novel and to relate it to teaching materials in learning novel texts for class XII SMA. This type of research is descriptive qualitative. The research subject is the novel Range of Stories by Gita Savitri Devi and the object under study is code mixing in the novel. Data collection is done by using reading and note techniques. The main instrument determinant in this research is the researcher himself. The data analysis technique used is the referential equivalent method, while the data validity technique uses intrarater and interrater. This technique is done by intensifying observations, namely by reading the novel Range of Stories repeatedly. Meanwhile, the interrater technique was carried out by checking the validity of the data through supervisors and colleagues who carried out the same research. Then, data analysis using referential equivalent method. The results of this study are as follows: (1) code-mixing forms in the form of words, word groups, clauses, baster, abbreviations, and word repetitions; (2) the function of code mixing as repetition of words, display of learning, affirmation of the accuracy of meaning, and indication of uniqueness; and (3) the link between code mixing in novels and teaching materials in learning novel texts for class XII SMA based on KD 3.9 and 4.9.
Dimensão Ética da Mediação da Informação

Analytical study of literature that focuses on information as a social phenomenon, in comparison with others about mediation of information, socio-interactionist theories, social protagonism, education, culture and politics. Put in evidence the relevance of mediation of information when it reaches its dialogical, aesthetic, formative, ethical and political dimensions, having the ethical dimension as the ruler of the interference action, ensuring the exercise of problematization that contributes of the appropriation of information, and práxis for the awareness of those involved in the mediating action, favoring the development and strengthening of social protagonism as mediation intentionality, demanding the performance of the organic intelectual, under the conception of Gramsci.
DIGITAL SOCIETY: NEW CHALLENGES FOR EDUCATION

The world has entered a new phase of development – the era of digital society. Under the influence of a new round of technological progress, the mechanisms and practices of the world order, as well as equipment and technologies, are changing. The range of innovations today is not limited to one or two industries; changes cover almost everything – telecommunications, information and communication sectors, nanotechnology, space, bioengineering, robotics, etc. The research aims to study the processes of changing the paradigm of social development under the influence of the formation of a digital society. The article analyzes the concept of "digital society," shows how the tools of the digital economy are used to justify a paradigm shift in social development for the modern generation. The research methodology is based on a systematic and structural-functional approach. Also, methods of sociological survey and statistical processing of information were used. As a result of the analysis, plans to the definition of the digital economy are formulated, the stages of development of digital society are presented, the trajectories of technological changes in the digital era are identified, and problems that inhibit the digitalization process are formulated.
Optimization Inspired on Herd Immunity Applied to Non-Hierarchical Grouping of Objects

Characterized as one of the most important operations related to data analysis, one non-hierarchical grouping consists of, even without having any information about the elements to be classified, establish upon a finite collection of objects, the partitioning of the items that constitute it into subsets or groups without intersecting, so that the elements that are part of a certain group are more similar to each other than the items that belong to distinct group. In this context, this study proposes the application of a meta-heuristic inspired by herd immunity to the determination of the non-hierarchical grouping of objects, and compares the results obtained by this method with the answers provided by four other grouping strategies, described in the literature. In particular, the resulting arrangements of the classification of 33 benchmark collections, performed by the suggested algorithm, by the metaheuristic inspired by the particle swarm, by the genetic algorithm, by the K-means algorithm and by the meta-heuristic inspired by the thermal annealing process, were compared under the perspective of 10 different evaluation measures, indicating that the partitions established by the meta-heuristic inspired by the herd immunity may, in certain respects, be more favorable than the classifications obtained by the other clustering methods.
Key issues for a manufacturing data query system based on graph

Manufacturing industry data are distributed, heterogeneous and numerous, resulting in different challenges including fast, exhaustive and relevant querying of data. In order to provide an innovative answer to this challenge, the authors consider an information retrieval system based on a graph database. In this paper, the authors focus on determining the key issues to consider in this context. The authors define a three-step methodology using root causes analysis. This methodology is then applied to a data set and queries representative of an industrial use case. As a result, the authors list four main issues: (i) semantic extension of keyword search, (ii) the treatment of syntactic heterogeneity contained in unstructured data, (iii) the results treatment by relevance order and (iv) the detection of relationships between a priori unrelated data. The authors conclude by discussing potential resolutions of these four issues, suggest adapting the methodology used in the paper to evaluate a future proposal, and finally open the possibility of using the results beyond the manufacturing domain.
Computer Game-Based Learning Media as a Strategy to Increase Students' Motivation Learning

The success of teaching and learning activities is determined by one of the methods and media of learning. This study aims to determine the needs of learning media, develop learning media based on computer games, and determine the effectiveness of learning media based on computer games on students' motivation and interest in learning. This type of research is Research and Development (RD), referring to the ADDIE development model. Data collection techniques using observation and questionnaires. The data analysis technique is done by analyzing the questionnaire. The results showed that students needed new learning media with the criteria of using computer technology, game-based, having a colorful display, involving an active role in student participation, easy to operate, equipped with characters, login, and voice access rights. A computer game-based learning media application has been developed called "BEBEB" with a very proper assessment from Media Experts and Material Experts. The effectiveness of the "BEBEB" application as a learning media based on computer games increased learning motivation by 16.5% and interest in learning by 24.33%. The study results indicate that the development of computer-based learning media as a strategy to increase students' motivation and interest in learning at SMK Muhammadiyah 2 Andong Boyolali has been able to be implemented properly. This implies that teachers need to provide learning media that can arouse students' motivation and interest in learning, one of which is using computer game-based learning media.
HALO: Learning to Prune Neural Networks with Shrinkage

Deep neural networks achieve state-of-the-art performance in a variety of tasks by extracting a rich set of features from unstructured data, however this performance is closely tied to model size. Modern techniques for inducing sparsity and reducing model size are (1) network pruning, (2) training with a sparsity inducing penalty, and (3) training a binary mask jointly with the weights of the network. We study different sparsity inducing penalties from the perspective of Bayesian hierarchical models and present a novel penalty called Hierarchical Adaptive Lasso (HALO) which learns to adaptively sparsify weights of a given network via trainable parameters. When used to train over-parametrized networks, our penalty yields small subnetworks with high accuracy without fine-tuning. Empirically, on image recognition tasks, we find that HALO is able to learn highly sparse network (only 5% of the parameters) with significant gains in performance over state-of-the-art magnitude pruning methods at the same level of sparsity. Code is available at https://github.com/skyler120/sparsity-halo.
A Rapid Review of Image Captioning

Image captioning is an automatic process for generating text based on the content observed in an image. We do review, create framework, and build application model. We review image captioning into 4 categories based on input model, process model, output model, and lingual image caption. Input model is based on criteria caption, method, and dataset. Process model is based on type of learning, encoder-decoder, image extractor, and metric evaluation. Output model based on architecture, features extraction, feature aping, model, and number of caption. Lingual image caption based on language model with 2 groups: bilingual image caption and cross-language image caption. We also design framework with 3 framework model. Furthermore, we also build application with 3 application models. We also provide research opinions on trends and future research that can be developed with image caption generation. Image captioning can be further developed on computer vision versusÂ human vision.
Tree-classification Algorithm to Ease User Detection of Predatory Hijacked Journals: Empirical Analysis of Journal Metrics Rankings

A major challenge today in communication and over various communications medium is the wanton havoc wreaked by attackers as they continue to eavesdrop and intrude.Young and inexperienced academia are today faced with the challenge of journal houses to send cum have their articles published.The negative impact thus, of predatory and hijacked journals cannot be over-emphasized as adversaries use carefully crafted, social engineering (phishing attack) skillsto exploit unsuspecting and inexperienced academia usually for personals gains.These attacks re-direct victims to fake pages.The significance of the study is to advance a standard scheme/techniques employed by phished (predatory/hijacked) journals to scam young academia and inexperienced researchers in their quest for visibility in highly impactful indexed journals.Thus, our study advances a decision-tree algorithm that educates users by showing various indicators cum techniques advanced by predatory and hijacked journals.We explore journal phishing attacks employed by such journals, targeted at young academia to adequately differentiate also using web-page ranking.Results show the classification algorithm can effectively detect 95-percent accuracy of journal phishing based on journal metric indicators and website ranks.
What Constitutes Fairness in Games? A Case Study with Scrabble

The compensation system called komi has been used in scoring games such as Go. In Go, White (the second player) is at a disadvantage because Black gets to move first, giving that player an advantage; indeed, the winning percentage for Black is higher. The perceived value of komi has been re-evaluated over the years to maintain fairness. However, this implies that this static komi is not a sufficiently sophisticated solution. We leveraged existing komi methods in Go to study the evolution of fairness in board games and to generalize the concept of fairness in other contexts. This work revisits the notion of fairness and proposes the concept of dynamic komi Scrabble. We introduce two approaches, static and dynamic komi, in Scrabble to mitigate the advantage of initiative (AoI) issue and to improve fairness. We found that implementing the dynamic komi made the game attractive and provided direct real-time feedback, which is useful for the training of novice players and maintaining fairness for skilled players. A possible interpretation of physics-in-mind is also discussed for enhancing game refinement theory concerning fairness in games.
Model-Based Threat Modeling for Cyber-Physical Systems: A Computer-Aided Approach

Harming the security of a Cyber-Physical System (CPS) can lead to substantial damage and endanger for life because such a system includes many devices that interact with the physical world. Following the principle of security-by-design, the consideration of security should take place as early as possible during software development. However, the current state of the art often lacks systematic documentation of possible threats, and the identification of all relevant threats is not a trivial task. In previous work, we presented a taxonomy of relevant attack actions for CPSs. The distinguishing feature of the taxonomy is its two-dimensional structure. We map typical attack actions to the attack surface. The attack surface is described by the component’s interfaces which can be misused by attackers to gain access to a component, thus potentially harming the security of the system. On top of this taxonomy, we described an example of an attack action catalog. The application of our taxonomy and the attack action catalog still requires manual effort from practitioners, e.g. when looking up relevant attack actions. Therefore, we developed a tool based on our taxonomy which we present in the present paper. In a first step, we formalized our taxonomy in form of a metamodel. Each threat model is an instance of that metamodel. The metamodel reflects the way in which the taxonomy links attack actions with parts of the system. Furthermore, we created a graphical editor that assists practitioners in creating the threat model. Based on the taxonomy’s metamodel and attack action catalogs, the tool pre-filters relevant attack actions and allows to systematically document them in the threat model. Our tool provides different views on the threat model, thus helping to focus on the relevant aspects for a specific task.
LOGIC OF SCIENTIFIC RESEARCH

The article provides a general description of the features of scientific research. It is noted that the research process must obey certain construction rules, i.e. logic. The article reveals the features of the main stages that a researcher goes through in the process of cognizing a particular phenomenon, process. The author agrees with the opinion of scientists that there is no universal logic of research, since each field of study is unique. A list of those components is put forward, without which the logic of research cannot exist.