Reviewerly/exHarmony huggingface dataset:
Some Suggestions and Assignment for Protecting Children and Adolescents Victims of Sexual Exploitation Online

This article was conducted as part of a study to come up with measures to protect and support children and adolescents who do not experience criminal damage by communicating safely online. What especially thought about here is that unlike other problems, it is difficult for children and adolescents to ask their parents for help. Because children and adolescents are exposed to online sexual exploitation damage when chatting and photo transmission, which are mainly online activities in the context of children and adolescents'' play culture, are combined with inappropriate sexual conversation or economic consideration. In the case of minor victims, it may be ideal to proceed with the case with the help of a legal representative, but in the process of collecting evidence from the Sunflower Center, which integrates sexual violence, children and adolescents give up or refuse to report the damage. However, if children and adolescents give up reporting and support due to parental reprimand, disappointment, and fear of anger, the perpetrator is likely to try the next crime more boldly without punishment, and the victim will not receive timely and appropriate help, so the pain and damage will continue. It is necessary to discuss ways to prevent such a situation and supplement a gap if not notified to a legal representative, as it may infringe on the rights of child and youth victims by unconditionally notifying the legal representative or requiring parental consent. The guardian agent system examines remedies for infringement of the rights of victims and adolescents, and should not conflict with the rights of victims to be protected in the sexual violence reporting process, and measures to guarantee the rights of victims and adolescents should be widely discussed through discussions on revision of related laws. One of them is the improvement of Article 13 of the National Police Agency''s Criminal Investigation Rules, which requires notification of the progress of the investigation to legal representatives or counselors at victim support institutions, in consideration of decision-making ability. In addition, those in charge of the case, including front-line judicial police officers, need to understand and recognize that informing parents of their reports of sexual violence without the consent of the victim children and adolescents can violate the rights of the victim. Under this awareness, this article first examined the route and damage patterns of children and adolescents induced by online sexual exploitation, and sought ways to improve related laws and systems by pointing out factors that are difficult to respond to and recover from damage, but in particular, it was overlooked in previous studies. In addition, the article was concluded with suggestions on the assignment of coping with and preventing online sexual exploitation of children and adolescents.
Pengaruh Pembelajaran/Pengetahuan dan Efisiensi terhadap Modal Manusia, Modal Struktural, Modal Relasional dan Daya Tarik

Human knowledge is the priority because humans need knowledge in carrying out all activities. This knowledge possessed by humans is one of the capitals they have to manage various activities, especially in an organization or company that has an environment of work needs. Knowledge is intellectual capital and knowledge management is the process of understanding that knowledge. This research method uses a quantitative approach by testing the relationship between each variable. Tests using statistical tests and concluded. The results showed that knowledge and efficiency had a positive effect on human capital, capital structure, relational capital and attractiveness.
Password Generation Based on Song Lyrics and Its Management

This paper focuses on creating a Password Manager which is secure and easy-to-remember. Password managers prove efficient in generating and storing passwords but they were never able to generate passwords that people could remember easily. Our password manager solves this by creating passwords using song lyrics. Instead of generating passwords randomly, our tool will create passwords from the lyrics of the song selected by the user. The passwords generated are checked thoroughly for validity, by using the haveibeenpwned API(data breach checks) and are made secure by making combinations of letters, numbers special characters of the password and suggesting the best secure password from the list.
Using KullBack-Liebler Divergence Based Meta-learning Algorithm for Few-Shot Skin Cancer Image Classification: Literature Review and a Conceptual Framework

Meta-learning often termed “learning to learn,” seeks to construct models that can swiftly learn new information or adapt to new situations using only a few training data samples. Meta-learning is distinct from traditional supervised learning. The model is required to recognise training data before generalising to unknown test data in traditional supervised learning. Meta-learning, on the other hand, has only one goal: to learn. Few-shot makes predictions based on a limited amount of data using a prototypical network that it learns using a metric space in which classification is done by computing distances between prototype representations of each class. The Kullback-Leibler Divergence (KLD) a non-symmetric distance measure between two probability distributions, p(x) and q(x) is used in the meta-learning process of few-shot leaning to compute the distance between the prototype class to query cancerous image. This study seeks to investigate the usefulness of KLD in cancer image classification to assist medical practitioner in early diagnosis of the dreadful disease.
A Novel Multimodal Fusion Technique for Text Based Hate Speech Classification

Hate speech is when someone or a group of people is insulted or stigmatized based on their background, colour, gender, religion, or other traits. Additionally, social media generates massive amounts of data every day. However, due to data peculiarities, a single classifier cannot deliver the heterogeneous feature for text classification. As a result, a novel fusion RNN (BiLSTM-BiGRU)-Multichannel CNN-Capsule Network-Attention (RMCCA) is presented in this research. The proposed approach improves in classification improvement. By eliminating ambiguity and text granularities, the suggested method facilitates in strengthening classification accuracy and ground truth evidence. Separate data sets are used to validate the suggested models. The empirical results show that the offered methods produce sufficient hate speech classification results.
On Two Approaches to Clustering of Cross-Sections of Rotationally Symmetric Objects

Abstract We analyze two approaches to clustering 2D shapes representing cross-sections of rotationally symmetrical objects. These approaches are based on two ways of shape representation - contours and silhouettes - and a number of similarity measures which are based on a combination of Procrustes analysis (PA) and Dynamic Time Warping (DTW) as well as on binary matrix analysis. The comparison of efficiency of the proposed approaches is performed on datasets of archaeological ceramic vessels.
Tuning Proximal Policy Optimization Algorithm in Maze Solving with ML-Agents

The proximal Policy Optimization algorithm is the ML-Agents toolkit’s default reinforcement algorithm. This algorithm can alternate between sampling data via environmental interaction and applying stochastic gradient descent to optimize a “surrogate” cost function. Although when creating a new machine learning model, it is tough to know the optimal model architecture for a given project immediately. In most cases, we can use the default given values from the algorithm’s creator or use the machine to carry out this evaluation and choose the best model architecture automatically. Hyperparameters define the model architecture; thus, searching for the best model is called hyperparameter tuning. We focus on comparing four hyperparameters: Beta, Epsilon, Lambd, Num_epoch of PPO algorithm in solving a maze. The results obtained in the training process show the difference in the selection of hyperparameters. The modification of hyperparameters will depend on the maze’s complexity and the complexity of the Agent’s actions. This paper will help to make appropriate choices at hyperparameters in concrete and practical projects.
Case Selection

This chapter elaborates Bayesian information-theoretic principles for optimal case selection and practical rules of thumb for real-world contexts.
Comparative Analysis of Object Detection Algorithms

Artificial Neural Networks can be considered to be one of the greatest inventions because the way they are making the machines intelligent is phenomenal. One of the biggest accomplishments of ANNs is in the field of computer vision as they have given computers the ability to see and distinguish between different types of objects. Although Convolutional Neural Networks, are able to successfully learn robust and high-level feature representations of images, Object Detection still remains one of the most complex domains and highly evolving domains. Every year, scientists come up with a new algorithm that tries to outperform previous ones. Advancement in GPU technology and deep learning has allowed researchers to create models for processing complex images. This paper discusses the difference between the popular object detection models including Fast-RCNN, Faster-RCNN, YOLO, and SSD and compared them on the basis of their performance in detecting objects belonging to the PASCAL VOC 2007 dataset.
Video Tutorial Kaligrafi Blackletter

The purpose of designing this BlackLetter Calligraphy video tutorial is to provide communicative and informative teaching to the target audience, namely Minang Typers as a community that houses letter artists. Video media was chosen in order to convey information through audio-visual to be effective because it can stimulate two senses simultaneously in conveying information, namely audio (hearing) and audio visual (sight).The method used in designing this video tutorial is a combination of the glass box and black box methods. The glass box and black box methods are inseparable methods because these two methods have their respective portion shapes to form balanced elements in creating or creating a work. The analytical approach uses 5W + 1H. This video tutorial creative design program goes through three stages, namely pre-production, production, and post-production. Keywords: Video, Calligraphy, Blacklette
THE IMPACT OF QUANTUM TECHNOLOGIES ON WARSHIP DESIGN

New advancements in quantum technologies look to provide significant improvements in capability for combat platforms in navies across the world. From communications systems to weapon targeting and navigation, there are countless possibilities for enhancements and augmentation of current systems.
The Expandability of Posthuman Body Art Challenging a New Paradigm : Focusing on the Work of ORLAN and Marina Abramović

This essay is a study on the expandability of the body art and the posthuman body in the paradigm of a cultural art world that is changed by science and technology, and examines it through the new work of ORLAN and Marina Abramović. ORLAN created 〈ORLAN-OÏDE〉(2018) using biotechnology and cloning technology, creating a robot that replicates her voice and shares her biometric data. Abramovic’s mixed reality performance titled 〈The Life〉(2019), experiments the de-materialized posthuman body beyond traditions of time and space. Both these works offer a private and intimate performance realized virtually, and the concept of a typical performance with spatiality, presence, in real-time was challenged.BR The two women artists used their bodies as an important medium of art, challenging the gender and social norms imposed on women, and in doing so revealed the artist’s subjectivity. The artists also modify, expand, and change their bodies using network environments and digital devices, crossing physical distance, space and time, they show that they have a fluent identity which is not fixed by society and culture. The posthuman body they pursue is de-constructed from socio-cultural, racial and gendered existence. And breaks down the boundaries between men and women, humans and machines, natural and artificial, organic and inorganic, and material and immaterial, to challenge the perspective of human beings.BR In the works of Orlan and Abramović, they transcend the physical body, time and space through the entire process: constructing new art forms, challenging specific cultures, races, and sexual traditions, as well as challenging the concepts of existing body art. Therefore, in body art, the body is practicing not a biological body, but a body created by android or mixed reality, transcending the limits of human beings and practicing in a posthuman world that breaks the boundaries between the outside and the inside, technology and humans, and the real and virtual.
Item Based Collaborative Filtering Based on Highest Item Similarity

The popularity of movies has increased in recent years. There are thousands of films produced each year. These films make it challenging for movie lovers to pick the ideal film to see. We propose a recommendation system that strives to offer guidance in selecting films. Depending on the method employed, recommendation systems can be categorized into three groups: collaborative filtering, content-based filtering, and hybrid filtering. In this work, collaborative filtering, one of the methods frequently used in recommendation systems was used. There are two ways to the Collaborative Filtering approach: User-Based Collaborative Filtering (UBCF) and Item-Based Collaborative Filtering (IBCF). There are two methods for finding similar items or users: Cosine and Pearson similarities. The Cosine similarity approach is one way to determine how similar two items are. Additionally, the Pearson Correlation Coefficient approach, which determines similarities between objects by calculating linear correlations between two sets, is the most widely employed. This study aims to determine which system produces the highest item similarity in IBCF and predicted ratings to actual ratings using 90% training and 10% testing data. The data set taken from MovieLens.org consists of 943 users from 1664 movies with 99392 ratings. The MovieLens data collection will be analyzed with the RStudio and the R package recommenderlab. The results reveal that the IBCF with Cosine similarities shows the number of items recommended n top-rated movies to each user for 10 movies. The IBCF can identify the most recommended films and creates a frequency distribution of items.
INTEGRATED ACADEMIC SERVICE INFORMATION SYSTEM (SIPAKATAU): STUDY OF EDUCATION SERVICE POLICY AT IAIN PALOPO

This study aims to 1) determine the service quality of the integrated academic service information system (SIPAKATAU) at IAIN Palopo. 2) Describe the implementation of the education service policy of IAIN Palopo. This research uses mixed methods, with an approach to academic and managerial information system research using explanatory sequential design. Data collection techniques are observation, interviews, questionnaires, and documentation. Data analysis consists of data reduction, condensation, presentation, and conclusion drawing.The results showed that: 1) The service quality of the SIPAKATAU was categorized as good by looking at the results of descriptive statistical tests on lecturer responses with an average value of 0.57 and a standard deviation of 0.502, students with an average score of 0.62 and a standard deviation of 0.493 and education staff with an average value of 0.69 and a standard deviation of 0.467 because more than half the number of respondents who chose to agree with the SIPAKATAU. 2) Education policy services at IAIN Palopo through the SIPAKATAU application service greatly facilitate users in all academic aspects, both administratively and in the teaching and learning process, which is currently in the online learning category. In this case, service users are helped by an integrated academic service information system service because the teaching and learning process can occur when students are in their respective areas. Therefore, SIPAKATAU is very useful. It helps users provide services because some of the services can already be done in the SIPAKATAU application so that academic services at IAIN Palopo are better and on target when learning demands increasingly sophisticated technology and technological developments are also increasingly modern. IAIN Palopo's policy challenges implementing educational services, such as the uneven access to the information contained in the SIPAKATAU service to service users in the era of the industrial revolution 4.0.Research Implications: 1) IAIN Palopo's educational services should be evaluated every semester by evaluating the performance between students, lecturers, and education staff. 2) Education policy services at IAIN Palopo require developing the SIPAKATA application to refine further the features contained in the application to support the quality of education in the face of the industrial revolution era with increasingly sophisticated educational technology. 3) The SIPAKATAU still requires socialization on services. 4) SIPAKATAU has a vision and mission at the beginning of the manufacturing process so that it is carried out in its development to achieve the goals in its use according to the needs of service users.
A Deep-Fracture Approach to Embedded Multilayer Neural Networks for Handwritten Character Recognition

Low-cost microcontrollers, but also with reduced processing and memory capabilities, are highly appreciated devices for the development of specific tasks as embedded systems. The devices found in the market today provide dedicated 32-bit architectures with communication capabilities ideal for IoT applications. Some of these tasks would highly benefit from the generalization and approximation capabilities of a neural network, but current convolutional networks prove to be too complex for microcontrollers. An alternative for some cases is the use of Multilayer Neural Networks (MNNs), which, thanks to a shallower depth, reach sizes suitable for use in small embedded systems. An MNN can accommodate a complex decision surface capable of being used in high dimensionality pattern classification problems, such as handwritten character recognition. Given the lack of an explicit strategy to define the architecture of these networks in coherence with the problem to be solved, this paper conducts a performance analysis of these networks in terms of their depth, to establish criteria to determine their size in a specific application. For the evaluation, the public database MNIST has been used in conjunction with classical metrics to evaluate the performance of a classification model. The results show that the depth of the network determines to a high degree the performance of the model, and guides the appropriate selection of the architecture.
Stability Investigation of Ensemble Feature Selection for High Dimensional Data Analytics

In the selection of feature subsets, stability is an important factor. In literature, however, stability receives less emphasis. Stability analysis of an algorithm is used to determine the reproducibility of algorithm findings. Ensemble approaches are becoming increasingly prominent in predictive analytics due to their accuracy and stability. The accuracy and stability dilemma for high-dimensional data is a significant research topic. The purpose of this research is to investigate the stability of ensemble feature selection and utilize that information to improve system accuracy in high-dimensional datasets. We conducted a stability analysis of the ensemble feature selection approaches ChS-R and SU-R using the jaccard similarity index. Ensemble approaches have been found to be more stable than previous feature selection methods such as SU and ChS for high-dimensional datasets. The average stability of the SU-R and ChS-R ensemble approaches is 56.03 and 50.71%, respectively. Accuracy improvement achieved is 4 to 5%.
Smart Farming Using Data Science Approach

Smart Farming is a new trend that stresses the use of internet in agricultural production cycle. New technologies like the Internet of Things and Cloud Computing are projected to accelerate this trend by allowing farmers to use more robots and artificial intelligence. This is encapsulated by the Big Data phenomena, which refers to large amounts of data of varying types that may be acquired, evaluated, and used for judgement. The goal of this review is to get an understanding of the current state of Big Data applications in Smart Farming and to identify the corresponding socio-economic concerns that must be solved. A conceptual model for analysis was constructed using a structured approach which can also be used for further studies on this issue. The analysis reveals that Big Data applications in Smart Farming have an impact on the entire food supply chain, in addition to primary production. Big data is being used in farming operations to give predictive insights, drive real-time operational choices, and rethink business processes in order to create game-changing business models. As a result, several experts believe that Big Data will result in significant adjustments in the roles and power relationships among various players in today’s food supply chain operations. The stakeholder landscape reveals an intriguing interplay between large digital corporations, venture capitalists, and often small start-ups and newcomers. Several public entities, on the other hand, disseminate open data under the condition that individuals’ privacy be protected.
Review of Bayesian books in Bayesian statistics

"Review of Bayesian books in Bayesian statistics." Journal of Statistical Computation and Simulation, ahead-of-print(ahead-of-print), pp. 1–2
Приобщаващото образование в началната образователна степен за ученици с нарушения от аутистичния спектър

This article focuses on inclusive education and integration of students with autism spectrum disorder in general education schools. Psychometric tools for assessment of intellectual and adaptive capacity of autistic students are represented. A review was made on expected social stereotypes of behavior and skills in primary school stage (I – IV grade), methods and techniques for education, ways of communication with autistic children and accessory tools of teaching. The research aims to describe the specifications of categorizing and teaching students with autism spectrum disorder in primary school stage which will help future development of methods and approaches for assisting their education with the application of ICT (information-communication technologies).
Модел на образованието на бъдещето [Model of the Future of the Education

This article attempts to build a hypothetical, theoretical model of the education of the future, based on the current state of education and the tendencies for its development in the future. In the context of the unpredictable and unpredictable future, in this model, probability theory is of prime importance, ie. the model is relatively volatile and volatile, variable not only with respect to its basic constants, but also with respect to the details that make it up. The model of education of the future is deductive-inductive, it is complex, multidimensional.
A Hybrid Approach to Facial Recognition for Online Shopping Using PCA and Haar Cascade

This paper proposes a model, designed to add an extra layer of security using facial recognition to make the payment method more secure. In this facial recognition, the algorithm used is the combination of both Principal Components Analysis (PCA) and Haar Cascade algorithms, so that the face recognition will be more accurate and faster. The Haar cascade algorithm is used in the detection of faces and PCA is used to analyse the face and match with the existing data stored in pixel format, so that it can be matched at the time checkout and proceed to the payment page.