Reviewerly/exHarmony huggingface dataset:
Searching for high-fidelity builds using active learning

Modern software is incredibly complex. A typical application may comprise hundreds or thousands of reusable components. Automated package managers can help to maintain a consistent set of dependency versions, but ultimately the solvers in these systems rely on constraints generated by humans. At scale, small errors add up, and it becomes increasingly difficult to find high-fidelity configurations. We cannot test all configurations, because the space is combinatorial, so exhaustive exploration is infeasible.
Penggunaan Kartu Peta dalam Peningkatan Motivasi dan Hasil Belajar IPS

Social studies learning with broad material tends to be boring. The use of map cards is expected to increase motivation and social studies learning outcomes. This study aims to determine the increase in motivation and social studies learning outcomes in fourth grade students at SDN Ketangi. This research is a classroom action research, data collected through tests and observations. The subjects of this study were elementary school students grade IV SDN Ketangi as many as 22 students. The research instrument was a test sheet and an observation sheet. The results showed that the use of map cards increased students' learning motivation in participating in social studies lessons, it was seen that the high category was achieved by 20 students (90%) and the medium category was only 2 students (10%). The average student motivation in social studies learning reached 82%. Learning outcomes or student achievement have increased from the average class 53 to 80.
Monochromatic Image Colorization using Machine Learning

The introduction of Artificial intelligence has opened doors to many automatic, unsupervised learning trends, which help to translate and acknowledge data. During the past years, the procedure of colorization of monochrome images has been greater or greater in several application fields, like restoration of old images or degraded images, and also, storage of monochrome images is more efficient when compared to colored images. This issue is not excessively presented because of an extremely high likelihood of conceivable outcomes during the designation of varied subtleties to the picture. A considerable lot of the new advancements in colorization have pictures with a normal format or exceptionally refined information, like semantic guides as the info. In the proposed system we are making use of Generative Adversarial Network (GAN). The final outcome is compared between the traditional deep neural network and the generative Model
Towards reconstructing HDR light fields by combining 2D and 3D CNN architectures

High dynamic range imaging has become a technological trend in the past couple of decades, particularly through its integration into many applications. Numerous attempts were made to reconstruct HDR images from lowdynamic-range data. Such reconstruction techniques can be classified into single-camera and multi-camera approaches. Single-camera setups are less expensive, yet multi-camera setups are more efficient. At the time of this paper, there is already a great number of algorithms for single-camera HDR image reconstruction, but there are only a few for HDR video reconstruction. The latter takes into account the temporal coherence between consecutive video frames, leading to better results. For light field images, this remains a challenging open issue, as the HDR video reconstruction methods do not work as efficiently for light field images as HDR image reconstruction algorithms do. However, analogously to 2D videos, where consecutive frames have temporal coherence, many similarities can be found between the adjacent views of light field contents. In this paper, we investigate the theoretical possibilities of combining CNN architectures utilized for HDR images and videos, in order to enhance the outputs of HDR light field image reconstruction. The concept of our work is to exploit the similarities between light field images since they all visualize the same scene from different angular perspectives.
FORMATION OF COGNITIVE INDEPENDENCE OF STUDENTS OF ECONOMIC DIRECTION OF TRAINING IN THE PROCESS OF STUDYING PROFESSIONAL DISCIPLINES

The article deals with some actual problems concerning the formation o f students’ (are being trained to be economists) cognitive self directed activities in the process o f special disciplines studies.
CODE OF COMMUNICATION OF MODERNITY AND RESOURCES OF HAPPINESS

The development of new information technologies involves revolutionary social change. Digital technologies universalize the former variety of available means (language, audiovisual instruments), and therefore allow to construct a parallel real digital (virtual) space. A matrix of coexistence in a new bipolar world is being developed. Digital technologies are new values, principles of ethics and aesthetics, behavioral practices. Mankind has been given superpowers that allow us to communicate anytime, anywhere. However, information technology has not brought us closer to each other. The digitalization of socio-economic relations is a global world process that requires a deep awareness of contradictory changes. Any changes taking place in society must have, above all, a human dimension. And happiness is one of the important parameters of these dimensions. Key words: digitization, bipolar world, network communication, conscious loneliness, programmability of relationships, matching applications
Investigating Lexical Replacements for Arabic-English Code-Switched Data Augmentation

Data sparsity is a main problem hindering the development of code-switching (CS) NLP systems. In this paper, we investigate data augmentation techniques for synthesizing dialectal Arabic-English CS text. We perform lexical replacements using word-aligned parallel corpora where CS points are either randomly chosen or learnt using a sequence-to-sequence model. We compare these approaches against dictionary-based replacements. We assess the quality of the generated sentences through human evaluation and evaluate the effectiveness of data augmentation on machine translation (MT), automatic speech recognition (ASR), and speech translation (ST) tasks. Results show that using a predictive model results in more natural CS sentences compared to the random approach, as reported in human judgements. In the downstream tasks, despite the random approach generating more data, both approaches perform equally (outperforming dictionary-based replacements). Overall, data augmentation achieves 34% improvement in perplexity, 5.2% relative improvement on WER for ASR task, +4.0-5.1 BLEU points on MT task, and +2.1-2.2 BLEU points on ST over a baseline trained on available data without augmentation.
Trends of English Language Teacher Education in Nepal

This paper envisages the history and the trend of English language teacher education in Nepal. It reflects the outcome of the content analysis available on teacher education in the context of Nepal in printed materials and through online archives chosen purposively. For this, themes like teacher education in the past, teacher education in the ICT era and opportunities of continuous professional development in the context of Nepal were developed and authentic materials and documents relevant to the English language teacher education were analyzed, organized and reflection was written based on subjective interpretation. Analysis led to the conclusion that English language teacher education has a short history with remarkable achievements through continuous improvement. The provision of teacher education made by government and other organizations are found to have helped to maintain equalities and uniformities among teachers and professionals developing their career and imparting knowledge living in sophisticated area of the city center and the remote and rural areas of the multi-topographies of the country Nepal. However, the exposure the professionals have received in the comfortable zone has boosted the potentiality of them more in comparison to the ones who have been imparting knowledge, educating poor and marginalized people and earning livelihood in the remote areas.
QUALITY OF SELF-ORGANIZATION AS DETERMINING CONSTITUENT OF MAN OF MODEM SOCIAL STRUCTURE

In the article attention is accented to that modem social structure of active transformations requires certain organizational qualities from the actors of different social roles. Existence of such qualities is the condition of support by personality of itself in a viable form in the negative terms of social cha nges and, in addition are realization of the abilities in new social projects. An author briefly opens up essence of these organizational qualities of personality and the necessity of their forming already today at teenagers by the changes in general middle and in out-of-school education becomes firmly established.
Heavy metals risk assessment of commercial boreholes water within Wukari Town of Taraba State Nigeria

Background: Water is an essential and the most important element of life with several biochemical relevancies in the body. It is an important solvent for most macro molecules in the body and is regarded as a universal solvent. The increase in the contamination of water with different sources such as pesticides, oil spillages, industrial wastes, and other pollutants has become an alarming issue in the environment. This study determined the concentration of some heavy metals (Mn, Cr, Cd, Pb and Fe) in water samples from Avyi, Puje and Hospital in Wukari local government area (LGA) of Taraba state. Methods: Five samples were collected from each point and assayed for heavy metals using atomic absorption spectroscopy (AAS). Result: The results obtained showed that Mn and Cr were higher in concentrations in the samples from the three locations with values ranging from 0.01 to 0.2 ppm. However, these values were below the permissible risk limit of W.H.O. Lead was the least in risk estimation calculation with values ranging from 0.003 to 0.009 HQ while cadmium was the highest in risk estimation with values ranging from 0.02 to 0.03 HQ which is closer to the limit of 1 that indicates toxicity. The result of cancer estimation showed that Cr has a high risk of carcinogenesis with value of 1.2x10-6 in hospital water, 4.8x10-7 in Puje and 6.3x10-7 in Avyi all with values higher than the other heavy metals. Conclusion: This research is of public importance as individuals who consume water from these locations of Wukari LGA are at the risk of heavy metal toxicity such as renal, neural and respiratory disorders among others.
Overcoming camera instability problem for detecting and tracking moving objects in video using reduced data

Moving &lt;span&gt;objects detection is a vital field of study in various applications. Many of such applications may have to capture and process a lot of data, then such these data need to be reduced as much as possible in order to have a reasonable and suitable system for achieving the desired aims efficiently. The proposed algorithm utilizes singular value decomposition (SVD) and Bayer pattern filter for their good properties in producing very representative reduced data. This data is then handled by frame difference objects detection, which in turn is an approach that doesn’t need to handle much data. The camera shaking which can be caused by a windy weather in the case of the outdoor static camera may introduce a frame difference with imprecise moving objects detection, hence frames compensation is conducted utilizing a transformation based on speed up robust feature transform (SURF) detected key points.&lt;/span&gt;
Q-LIC: Quantizing Learned Image Compression with Channel Splitting

Learned image compression (LIC) has reached a comparable coding gain with traditional hand-crafted methods such as VVC intra. However, the large network complexity prohibits the usage of LIC on resource-limited embedded systems. Network quantization is an efficient way to reduce the network burden. This paper presents a quantized LIC (QLIC) by channel splitting. First, we explore that the influence of quantization error to the reconstruction error is different for various channels. Second, we split the channels whose quantization has larger influence to the reconstruction error. After the splitting, the dynamic range of channels is reduced so that the quantization error can be reduced. Finally, we prune several channels to keep the number of overall channels as origin. By using the proposal, in the case of 8-bit quantization for weight and activation of both main and hyper path, we can reduce the BD-rate by 0.61%-4.74% compared with the previous QLIC. Besides, we can reach better coding gain compared with the state-of-the-art network quantization method when quantizing MS-SSIM models. Moreover, our proposal can be combined with other network quantization methods to further improve the coding gain. The moderate coding loss caused by the quantization validates the feasibility of the hardware implementation for QLIC in the future.
Review of factors affecting facial recognition algorithms performance

The face is a significant part of the human body, recognizing people in large groups of individuals. Thus, because of its uniqueness and universality, it has turned into the most generally utilized and acknowledged biometric technique. Many algorithms have been used by various researchers for face detection and recognition. Research, innovation progression, and applications consolidating face recognition in the last twenty years have grown massively. In this paper, some essential existing approaches which are adjusted with dealing with the issues of face recognition have been presented close by their Face recognition accuracy and the variables capable of debasing the performance of the review. In the first section, various factors that decrease facial detection and recognition accuracy have been researched like posture variety, illumination, aging, facial expressions, etc. While in the second section of the paper, various methods have been examined that attempt to relieve the impact of discussed factors. Various algorithms give various exhibitions in various conditions like enlightenment, noise, posture, and mask change. All the previously mentioned methods are represented briefly to give an overall idea. The motive of the paper is to carry all the various methods to a similar spot and simplify it to review the paper.
Analysis of implementation : the payroll accounting system and employee wages

The accounting system, especially the payroll accounting system, and employee wages will assist the company in managing the payment of wages and salary, thereby preventing fraud. Internal control will be influenced by a solid accounting system. The goal of this research is to determine the company's internal control effectiveness by examining how well payroll accounting information systems are applied. The research method used is a literature study. In the organizational structure, there is a lack of task separation and division. The authorization system and recording procedures and healthy practices have not been implemented properly. In conclusion, internal control aspects in the payroll and salary accounting systems have not been fully fulfilled in several companies.
How to respond to emerging threats of cyberspace security via social engineering? A novel paradigm to solve cyberspace security issues

Cybersecurity researchers always ignore the “people” behind the issues when dealing with cyberspace security issues. The human and technological aspects of cyberspace security must be simultaneously addressed to enable a secure cyber environment. Social engineering is a discipline whose research object is people, and the combination of social engineering and cyberspace security can provide new solution ideas for lots of cyberspace security issues. This paper attempts to answer the question —— “How to solve cyberspace security issues via social engineering?” We briefly review existing frameworks for social engineering attacks and pro?pose a novel, recursive, and iterative framework for social engineering attacks in cyberspace. The existing research achievements of combination of social engineering and cyberspace security were reviewed in the order of cyber personality, hacker psychology, human flesh search, and social engineering defense. To answer this question, we summarized four “guidelines” for using social engineering. Finally, we look ahead, give our thoughts, and discuss answers of the question and future research. It is aimed at getting more researchers of cyberspace security and social science to pay attention to this field.
Byzantine Fault-Tolerant Min-Max Optimization

In this paper, we consider a min-max optimization problem under adversarial manipulation, where there are $n$ cost functions, up to $f$ of which may be replaced by arbitrary faulty functions by an adversary. The goal is to minimize the maximum cost over $x$ among the $n$ functions despite the faulty functions. The problem formulation could naturally extend to Byzantine fault-tolerant distributed min-max optimization. We present a simple algorithm for Byzantine min-max optimization, and provide bounds on the output of the algorithm. We also present an approximate algorithm for this problem. We then extend the problem to a distributed setting and present a distributed algorithm. To the best of our knowledge, we are the first to consider this problem.
O Microagulhamento no Tratamento de Estrias em Mulheres no Puerpério / The Use of Ultrasound in Lipodystrophy: A Bibliographic Study

A estética corporal, ganhou visibilidade nas últimas décadas com ênfase nas questões relativas tanto a vaidade, como à saúde mental e bem-estar geral. No passado mulheres na faixa dos 30-40 anos tinham enormes preocupações ao começarem a depararem-se com as primeiras marcas do tempo como rugas e flacidez cutânea, sem contarem com tratamentos eficazes. A pele, maior órgão do corpo humano, é o principal objeto de estudo na área da estética e este artigo consiste em revisão bibliográfica com o fim de analisar o microagulhamento no tratamento de estrias em mulheres no puerpério. Para tal, levantou-se um total de 44 artigos, sendo destes excluídos 28 com base em títulos e resumos, restando 16 para leitura completa, dos quais apenas 5 foram funcionais para responder às hipóteses desta pesquisa que conclui que o microagulhamento é um procedimento efetivamente seguro no tratamento das estrias, desde que realizado por um profissional habilitado. Abstract: Body aesthetics has gained visibility in recent decades with an emphasis on issues related to vanity, mental health and general well-being. In the past, women in their 30s and 40s had enormous concerns when they began to face the first marks of time such as wrinkles and sagging skin, without having effective treatments. The skin, the largest organ of the human body, is the main object of study in the area of aesthetics and this article consists of a literature review in order to analyze micro needling in the treatment of stretch marks in women in the puerperium. To this end, a total of 44 articles were raised, of which 28 were excluded based on titles and abstracts, leaving 16 for full reading, of which only 5 were functional to answer the hypotheses of this research that concludes that micro needling is an effectively safe in the treatment of stretch marks, as long as it is performed by a qualified professional.
CULTURAL APPROACH TO THE FORMATION OF PERSONALITY FUTURE LABOR TEACHER

The article deals with the ways of realization of cultural method in order to form the future teachers personality. The author of this article accents on the necessity of using of the system of artistic and creative exercises, which promotes the actualization of this process.
The Development of Monitoring Java Web Application Server Resource Usage using JavaMelody Promotheus Grafana for Sever Maintenance

Abstract The goal of this study is to create a web monitoring application that can retrieve and save data from java application server resources. This study's research methodology consists of two phases: data collecting and software development. The data gathering phase includes a review of the literature, a survey, the distribution of questionnaires, and an analysis of similar apps. The waterfall method is used during the development phase. The ultimate result of this research is a web application that can monitor resource utilization on the java application server and send email notifications if it becomes excessive. Finally, web application server monitoring can be used to make the developer's job easier.
MASTER-D W-MOOC PLATFORM BASED MEDIA AS AN ONLINE LEARNING SOLUTION FOR DYSLEXIC ACCOUNTING STUDENTS

Health protocol rules during the New Normal period due to the COVID-19 virus pandemic in Indonesia are serious obstacle, especially the online learning process in universities. Accounting students are required to excel in attending lectures and online practice, including accounting students with dyslexia. This study uses a qualitative descriptive method with naturalistic and interpretive paradigms that describe solutions for dyslexic students in adjusting to being able to complete their education and can be realized at the time of graduation. Subjects consisted of senior professional educators from Dyslexia Center Indonesia (DCI). The Open Online Course (W-MOOC) is needed for people with dyslexia as a learning solution to improve the innovation ability of applied accounting skills, and prepare graduates' competencies according to their field of study.
A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning

The generalization of model-based reinforcement learning (MBRL) methods to environments with unseen transition dynamics is an important yet challenging problem. Existing methods try to extract environment-specified information $Z$ from past transition segments to make the dynamics prediction model generalizable to different dynamics. However, because environments are not labelled, the extracted information inevitably contains redundant information unrelated to the dynamics in transition segments and thus fails to maintain a crucial property of $Z$: $Z$ should be similar in the same environment and dissimilar in different ones. As a result, the learned dynamics prediction function will deviate from the true one, which undermines the generalization ability. To tackle this problem, we introduce an interventional prediction module to estimate the probability of two estimated $\hat{z}_i, \hat{z}_j$ belonging to the same environment. Furthermore, by utilizing the $Z$'s invariance within a single environment, a relational head is proposed to enforce the similarity between $\hat{{Z}}$ from the same environment. As a result, the redundant information will be reduced in $\hat{Z}$. We empirically show that $\hat{{Z}}$ estimated by our method enjoy less redundant information than previous methods, and such $\hat{{Z}}$ can significantly reduce dynamics prediction errors and improve the performance of model-based RL methods on zero-shot new environments with unseen dynamics. The codes of this method are available at \url{https://github.com/CR-Gjx/RIA}.