Reviewerly/exHarmony huggingface dataset:
Pelatihan Bagi Guru Dan Siswa –Siswi Ma Ishlahul Amanah untuk Mengetahui Proteksi Sistem PLTS Sederhana

Maximum utilization of solar energy requires the active role of the community. Several things can be done, namely by providing information related to solar energy with the large potential that can be obtained in its utilization. In addition, coaching to the community by providing basic knowledge about energy conversion from solar to electricity as well as practicing in proving the basic knowledge provided in the form of simple practice. Thus, the public can understand this solar energy as a whole, both with basic knowledge, conversion techniques, and practice. In Community Service activities by providing training related to the protection of the Solar Power Generation system or usually called PLTS. With the target participants, namely teachers and students of MA Ishlahul Amanah in Pengalengan District, Bandung Regency. The main activity is providing protection training and a set of PLTS as a learning medium for the use of new and renewable energy in the form of solar energy. Students today are required to be more creative and innovative in utilizing all the potential of nature, especially the use of alternative technologies, one of which is solar energy. The canning area is also a challenge in itself in the use of electricity technology for the need for support by using solar energy for electricity use. The results of this activity provide a positive appreciation. This can be seen from the evaluation of the activities carried out that participants, both students and teachers, chose to agree and strongly agree with the items in the written statement
Musicians (Don't) Play Algorithms. Or: What makes a musical performance

Abstract Our private perception of listening to an individualized playlist during a jog is very different from the interaction we might experience at a live concert. We do realize that music is not necessarily a performing art, such as dancing or theater, while our demands regarding musical performances are conflicting: We expect perfect sound quality and the thrill of the immediate. We want the artist to overwhelm us with her virtuosity and we want her to struggle, just like a human. We want to engage with the musical expression and rely on visual and physical cues. Considering that the ears of today's listeners are used to technologically mediated music, in this paper I explore the unique qualities of musical live performances and examine if our conception allows for new mechatronic inventions, in particular robotic musicians, to participate in this art form. Some of Godlovitch's main thoughts expounded in his work on "musical performance" [11] serve as a reference and starting point for this investigation. His concept of `personalism', which deprives computer-/program-based musical performances from expressive potential and creative accomplishment is an issue that I want to challenge by pointing out new approaches arising from a reective discourse on technology, embodiment and expression. The enquiry conducted illustrates, how in reasoning about machine performers and algorithmic realization of music, we also examine the perceptual, physical and social aspects of human musicianship, reconceptualizing our understanding of a musical live performance.
Assessment of the Impact of Environmental Scanning Intensity on Innovation among SMEs Owners in Oyo State Nigeria

The study investigated the effect of environmental scanning intensity on innovation among SMEs in Oyo State Nigeria. A sample of 400 SME owners was taken using the multistage sampling technique. The questionnaire was used to collect information from the respondents and the data were analyzed using descriptive and quantitative analysis. The result from the study shows that environmental scanning intensity on the part of SME owners is very crucial to innovation. The study further underscores the importance of resources, organizational structure, and technology in the promotion of innovation while the study also concludes that government policy has not been encouraging innovation among SMEs. The study recommends more involvement of government in the promotion of innovation and the SMEs owners on their part should embark on efficient environmental scanning in other to improve their innovative ideas that can make their businesses excel or stand out in the ever-rising competitive world.
360° Laparoscopic Imaging System to Facilitate Camera Control and Orientation in Minimally Invasive Surgery

Abstract During laparoscopic procedures, the surgeon's view of the situs, and thus her or his performance, is dependent on the skills of the camera assistant. The surgeon lacks control over his own field of view and there is a high potential for reducing mental load and workflow issues. In this paper, a research setup of a 360° laparoscopic imaging system is presented and evaluated. The system consists of a 360° camera and a head-mounted display, through which the surgeon can inspect the situs. In a user test, the system showed advantages over a conventional laparoscope regarding orientation in the situs, intuitiveness of operation, and faster task completion.
Robust Colon Tissue Cartography with Semi-Supervision

Abstract We explore the task of tissue classification for colon cancer histology in a low label regime comparing a semi-supervised and a supervised learning strategy in a series of experiments. Further, we investigate the model robustness w.r.t. distribution shifts in the unlabeled data and domain shifts across different scanners to prove their practicality in a histology context. By utilizing unlabeled data in addition to nl = 1000 labeled tiles per class, we yield a substantial increase in accuracy from 89.9% to 91.4%.
Application to monitoring a SNes control with Ruby in Windows, Linux Ubuntu, OS X El Capitan, and Raspbian GNU/Linux 10

This paper shows the development of a Ruby application to detect the actions carried out on an USB control, with the goal of achieving the coding of multiplatform application that can be used as a basis for the creation of projects with larger scope and impact in this fiel, such as videogame development, and device control systems. The ‘prototype models’ methodology was the approach for this project. In the first prototype a CLI program was written that prints out messages in the terminal depending on the buttons that are simulated based on the keys pressed on the keyboard, and so on until the end of the project, in which a final application is delivered, in compliance with the necessary tests. This application code was published in a GITLAB repository for reference and future use. The application was developed to be compatible with Windows, Linux, macOS, and Raspbian operating systems to test Ruby portability.
Block programming to develop interactive activities in the analysis of passive filters using an RC circuit for distance classes

Block programming was developed for interactive activities in the analysis of a passive low pass filter using a RC circuit for distance classes. On a breadboard, was integrated an Arduino development board, a potentiometer and a visual indicator (a light emitting diode LED). The development of the programming was carried out using the software LabVIEW to generate an interactive front panel that allows us to manipulate and visualize the calculations, the graphic expressions and at the same time vary at least one passive element. A graphical interface was obtained that allows iterations and immediate calculations for the missing parameters to see the behavior of the filter and also generates a display for the mathematical expression and its Bode plot, the resistance allows us vary the values and make a sweep to locate the angular frequency and activate the light emitting diode connected on the development board. In the programming a web camera was implemented to visualize the circuit in real time at the moment of manipulating a graphical interface.
Optimized YOLOv4 Algorithm for Car Detection in Traffic Flow

The vehicle detection accuracy and actual in images and videos appear to be very tough and critical duties in a key technology traffic system. Specifically, under convoluted traffic conditions. As a result, the presented study proposes single-stage deep neural networks YOLOv4-3L, YOLOv4-2L, YOLOv4-GB, and YOLOv3-GB. After optimizing the network structure by adding more layers in the right positions with the right amount of filters, the dataset will be repaired and the noise reduced before being sent to the mentoring. This research will be applied to YOLOv3 and YOLOv4. In this study the OA-Dataset is collect and used, the data set is manually labeled with the care of different weathers and scenarios, as well as for end-to-end training of the network. Around the same time, optimized YOLOv4 and YOLOv3 demonstrate a significant degree of accuracy with 99.68 % and precision of 91 %. The speed and detection accuracy of this algorithm are found to be higher than that of previous algorithms.
Cryptocurrencies and the State: Can They Become Disruptive Enough to Overthrow the Status-Quo?

Cryptocurrencies have grown to be very significant during the past two decades. Starting off at the way cryptocurrencies, specifically Bitcoin, operate, we move forward towards the discussion on their nature as currency and their disruptiveness. We navigate through the political character of Bitcoin over the years, the potential of Bitcoin and other cryptocurrencies to threaten a state’s sovereignty and an overview of state responses to cryptocurrency. Finally, there is a number of speculations and suggestions on how Bitcoin could grow and gain a less controversial position in the global economy.
Pelatihan dan Pendapingan jurusan Otomatisasi Tata Kelola Perkantoran (OTKP) SMK Bina Cipta Palembang

Abstract: Purpose: From this community service activity is to increase the application of science and technology in the SMK Bina Cipta Community, especially the Office Governance Authority (OTKP) department using Microsoft Office and Publisher applications. Method: One of the methods used for this PKM activity is training and mentoring. Media used office applications (Ms Office and Publisher), typing manuscripts, making correspondence, making tables, graphs, using formulas and making brochures. This office application application is also used to facilitate work in office administration related to information and aminstaration. The method of service activities is carried out using teaching media and the practice of using Office Applications, namely Ms. Office and Publisher. Results: Students understand how it works and its benefits, understand how to work with office applications, by applying training and mentoring, understanding various types of needs and how they work, recognizing features / menus in office applications, utilizing applications in office administration activities, understanding how to type scripts well, making easy tables, presenting reports, making brochures quickly and neatly, file (saving, importing, printing). Conclusion: Based on the results of the questionnaire graph that participants are in the interval of 65-78%, it means that this service activity has a positive impact on increasing the application of science and technology to students. Keywords: 1. Education 2. Innovation 3. Technology
Perceptions and Key Attributes of Exercise Among Korean Men and Women During the COVID-19 Pandemic: A Comparative Study Using Big Data Analysis

Background:The COVID-19 pandemic has increased risks to people's health due to restrictions on movement and access to exercise facilities.This study compares and analyzes perceptions and key attributes of exercise among Korean men and women in the context of the COVID-19 pandemic by using data collected from social media.Methods: Data were collected from January 2020 to June 2021.The search keywords were classified into "COVID-19, men, and exercise" and "COVID-19, women, and exercise", and data were collected through Textom (The Imc Inc., Daegu, Republic of Korea), a big data collection and analysis platform.Frequency analysis, TF-IDF analysis, and degree centrality analysis were performed using Textom.In addition, a CONCOR (CONvergent and CORrelation) analysis was performed using UCINET 6 (Analytic Technologies Corp., Lexington, KY, USA) to visualize related words and analyze clusters.Results: In total, 10,703 data points of 5.935 MB were collected and analyzed.The top 50 words related to men's and women's exercises of COVID-19 were derived through frequency analysis, TF-IDF analysis, and degree centrality analysis.We also derived four common clusters (exercise method, COVID-19 situation, friends, and sports).In addition, three clusters (women's fitness, children and hashtags) for men's exercise and two clusters (weight loss and Olympics) for women's exercise were derived separately.Conclusions: The study results show that it is possible to provide suggestions and health improvement plans for exercise based on gender.In addition, our findings can serve as an academic basis for developing health promotion programs related to exercise during the COVID-19 pandemic, which can contribute to reducing the economic costs and health risks associated with the pandemic.
Digital Democracy and Disinformation: The European Approach to Disinformation on Social Media in the Case of 2019 European Parliament Elections

This policy paper offers a brief overview of the hazards for digital democracy stemming from AI and digital tools and how the EU tackled online disinformation social media ahead of the 2019 European Parliament elections. The advent and introduction of social media into the political sphere has had a profound and substantial effect on Europe’s electoral processes affecting both voting behavior and the underlying factors that influence it. Whereas malicious actors often participating in disinformation have led to growing calls for reforms, this phenomenon has been most pronounced in the 2019 European parliament elections which saw an unprecedented reliance on digital media within the political process. Specifically, the European actors faced negative stemming from the scale of the vote and the algorithms and the attention-based business models used by the social media platforms. To meet these challenges, the EU not only employed legal and social means (e.g., the 2019 Action Plan Against Disinformation) but also created new initiatives focused on tackling disinformation (e.g., the Rapid Alert System). Notably, in an unprecedented manner, the EU also included the private sector in the process. As the paper argues, although its limitations, AI is an important tool for aiding the democratic process and tackling disinformation; however, a self-regulating approach favors the success of these endeavors.
Reading psychology and news communication strategies for affective computing

Reading psychology is an important basis for formulating news strategies. The purpose of this paper is to study how to analyze and study the psychological mechanism of reading and news communication strategies based on affective computing. It described the conditional random field. This paper put forward the problem of affective computing, which is based on affective computing technology. Then it expounded the concept of conditional random fields and related algorithms, and designed and analyzed cases of news communication strategies. Through the period from April 1, 2022 to June 1, 2022, the 300 short videos of news and information with the highest playback volume respectively released by Z software were used as research samples, and a multi-angle analysis was carried out. Among the 300 selected news information videos, 252 videos are original content, accounting for 84.00%, and the other short videos are from the self-media of the platform. At present, it is necessary to continuously develop intelligent products that meet the needs of users at different stages, and carry out personalized design in strict accordance with the living habits and natural conditions of different groups of people. Then continuously improving the experience of different groups of people using new media products, so that their reading interest can be more effectively stimulated.
Free and Open-Source Software: Freedom, Transparency and Efficiency in the Digitalization Era

Free and Open-Source Software (FOSS) has grown substantially over the past decades, becoming an essential part of the modern world. FOSS refers to software that preserves the user’s freedom to read the program’s source code, make modifications and redistribute it. Since the source code is open and accessible to everyone, the user is not only permitted, but also encouraged to make modifications to the software to fill specific needs. Corporations utilize that capability to get access to specifically tailored software for their needs, while proprietary software fails to meet that promise due to providing a standardized package of the software, adopting a one-size-fits-all approach. Therefore, FOSS allows for a more efficient fulfillment of software needs. Additionally, FOSS can play an important role in the protection of human rights in the digital realm, particularly in the case of the right to privacy. Because of its transparent nature, FOSS is more respectful towards the user’s privacy, compared to proprietary software, since the latter restricts the user from knowing the program’s under the hood functionality. With closed source software, arises a problem of asymmetric information between the software company and the consumer. FOSS offers a solution to this information asymmetry, by allowing users to obtain information about the inner workings of the program they rely upon. Through FOSS, the imbalance of power between the developer and the user disintegrates.
Query Indexing and Cluster-based Indexing Model for the Document Retrieval

In the research community field, query optimization plays an important role to retrieve the important and the appropriate documents on the basis of query indexing.In the documents, using the query retrieval process the information is retrieved on the basis of the distance measured.Although several methods are present in the query processing scheme as well as indexing, extracting the matched as well as appropriate documents still outcomes in numerous confronts in the research community.Hence, to retrieve the appropriate documents competently an effective cluster-based inverted indexing model is adopted.By exploiting stop word removal and stemming approaches, unnecessary and redundant words are removed.By cluster-based inverted indexing approach, document indexing is carried out that is the integration of Possibilistic fuzzy c-means (PFCM) clustering approach to index the documents.For user queries, such as multigram queries or semantic queries, on basis of Bhattacharyya distance to generate an enhanced query outcome, query matching is processed.By exploiting the Pearson correlation coefficient, the query optimization is carried out and the appropriate documents are retrieved efficiently.The achievement of a developed cluster-based indexing approach is carried out in this paper.The developed cluster-based indexing approach performance is calculated by exploiting measures, namely precision, recall, as well as F-measure.
Hybrid Flower Pollination Algorithm and Binary Particle Swarm Optimization Algorithm for Osteosarcoma Detection

Generally, Osteosarcoma is represented as malignant bone sarcoma which is typified by an extensive genomic disruption and a proclivity for metastatic extend.Due to the early recognition, Osteosarcoma raises the human beings' survival rate.During the early phase, several Osteosarcoma recognition approaches are developed in order to recognize the Osteosarcoma, however, evaluating the slides in the microscope to identify the tumor necrosis degree and tumor outcome is an important challenge in the medical segment.Therefore, an effectual recognition approach is modeled by exploiting the adopted Hybrid Flower Pollination algorithm with the Binary Particle Swarm Optimization algorithm based Generative Adversarial Network (FPO-BPSO based GAN) to detect the osteosarcoma during the initial phase.Moreover, the adopted FPO-BPSO is modeled using the combination of FPA and BPSO, correspondingly.As a result, the classification of the important tumor, non-tumor, as well as necrotic tumor is performed using GAN by exploiting the histology image slides.GAN is exploited to carry out the osteosarcoma recognition based on features extracted from the image via the cell segmentation process.The GAN training process is performed by exploiting the adopted Hybrid FPO-BPSO approach.Nevertheless, the adopted FPO-BPSO attained superior performance by exploiting the measures, like accuracy, sensitivity, and specificity.
Chaotic Butterfly Optimization Algorithm for Resource Allocation in Cloud Gaming

One of the dangerous death-causing diseases called cancer can be cured by exploiting a renowned technique called chemotherapy.In cloud platforms, cloud gaming is a new technique that assembles video games and transmits aiding the game streams to the users via the network.In addition, the users might possess diverse requirements on Quality-of-Experience (QoE), like the prominent quality of the video, minimum delay, etc.In this situation, in order to assure the basic fulfillment for all users with restricted cloud resources is an important problem in the cloud.The main aim of this work is to acclimatize game theory to formulate a new technique to meet the basic requirements of users with minimum cost.Therefore, in order to discover the optimum solutions the cloud gaming approach with resource optimization is formulated to solve the resource allocation problem.In this paper, resource allocation is carried out with an optimization approach as the optimal option of task presents improved effectuality in cloud computing.To improve the effectiveness of cloud computing systems for resource allocation Chaotic Butterfly Optimization Algorithm (BOA) is presented for optimal resource allocation.Here, the objective function is highly formulated by considering the definite QoS parameters that include the Quantified experience of players (QE), fairness index, and Mean Opinion Score (MOS).
Hybrid Moth Flame Optimization and Teachers Learning based Optimization Algorithm based Artificial Neural Network Model for Speaker Diarization

Speaker diarization or indexing is the procedure of automatically dividing conversation including numerous speakers into homogeneous segments and clustering together all segments, which symbolize a similar speaker.Till now, numerous researches are carried out in this field, but the requirement of precise partitioning procedure gates lagged in particular conditions.However, this work aspires to develop a novel speaker diarization or indexing technique (Telugu language) which at first includes the Mel Frequency Cepstral coefficient (MFCC) based feature extraction.Then, for the process of clustering, a novel optimized Artificial Neural Network (ANN) is developed.The main aim of the process of clustering is to train the ANN and it is performed using the optimization algorithm which updates the ANN weight by exploiting a hybrid Moth Flame Optimization (MFO) and Teaching learning-based Optimization Algorithm (TLBO).Thus, the adopted technique is called Hybrid MFO-TLBO and the overall performance is evaluated with the conventional models regarding diverse performance metrics.
PROFESSIONAL CHOICE AS A SOCIAL AND PSYCHOLOGICAL PHENOMENON

The problem of professional self-determination has been and remains one of the urgent problems of both education and society as a whole. Readiness for professional selfdetermination is formed at the senior school age. It is youth (senior school age) that is the "age" of professional self-determination. High school students are faced with questions: Whom to be? What to be? Where am I most needed? In the process of professional selfdetermination, a person takes an active position: he chooses a profession and builds his professional career, realizing his personal and intellectual potential, becoming a potential subject of future professional activity.