Reviewerly/exHarmony huggingface dataset:
Upaya Meningkatkan Motivasi Belajar Siswa dalam Pembelajaran IPS melalui Metode Outdoor Study

Instilling social values in students is a very urgent concept, because the social studies concept examines how social attitudes, social relationships and social behavior must be carried out by students in their lives. In social studies learning, learning tools and learning elements are needed, for example teacher elements, objectives, materials and facilities as well as methods which are not an easy task to be able to transform social studies values in students. All existing elements must be packaged and arranged completely so that the learning process is interesting for students, is of higher quality and learning objectives can be achieved. In reality the teacher's role and students' enthusiasm for social studies learning, there are still many problems, including 1) teachers carry out more teaching and learning activities in the form of lectures, 2) the dominance of the expository method, 3) the growth of a Verbalistic Learning Culture, 4) Teaching Centered on Textbooks (Textbook Centered), 5) Teachers who are still transferring of Knowledge. Conditions like this cause social studies to be a boring, boring subject (low student motivation) so that social studies subjects are underestimated by students which in the end mastery of subject matter by students, the percentage is small and the value of social studies lessons is low. Based on this background, it is important to study why social studies teachers need to innovate learning by applying learning methods outside the classroom (outdoor study)? how do social studies teachers apply learning methods outside the classroom (outdoor study) so as to increase students' learning motivation?. This study is a literature study. This study was conducted by analyzing the literature related to social studies learning problems and learning methods that are able to activate students in learning. The data analyzed are articles from accredited national journals, books and other relevant sources. learning activities outside the classroom (outdoor study) can be one solution to improve student learning in social studies learning by looking directly at phenomena which of course must be related to the topics the teacher teaches. The outdoor study method is a learning activity outside the classroom or school that aims to concretize and at the same time link all students' conceptual understanding of the subject matter with the natural environment and actual phenomena.
Multi-agent Databases via Independent Learning

Machine learning is rapidly being used in database research to improve the effectiveness of numerous tasks included but not limited to query optimization, workload scheduling, physical design, etc. Currently, the research focus has been on replacing a single database component responsible for one task by its learning-based counterpart. However, query performance is not simply determined by the performance of a single component, but by the cooperation of multiple ones. As such, learning based database components need to collaborate during both training and execution in order to develop policies that meet end performance goals. Thus, the paper attempts to address the question "Is it possible to design a database consisting of various learned components that cooperatively work to improve end-to-end query latency?". To answer this question, we introduce MADB (Multi-Agent DB), a proof-of-concept system that incorporates a learned query scheduler and a learned query optimizer. MADB leverages a cooperative multi-agent reinforcement learning approach that allows the two components to exchange the context of their decisions with each other and collaboratively work towards reducing the query latency. Preliminary results demonstrate that MADB can outperform the non-cooperative integration of learned components.
Distance learning experiences at the University of Guadalajara, Mexico. Towards a hybrid model

The recent health crisis caused by the SARS-CoV-2 virus, known as the COVID-19 virus, disrupted essential areas of the economy and led to the implementation of new forms of teaching and learning in education. At the University of Guadalajara (UDG), Jalisco, Mexico, practical distance learning tools were adapted, and teaching staff was trained to use them; however, areas of opportunity were left visible beyond the work of universities. With the data resulting from a survey of students at the University Center for Economic and Administrative Sciences (CUCEA), we concluded that the strategy implemented by the university was successful; however, the outcome of the learning process was not wholly successful there were significant shortcomings.
Sentiment Analysis for Board Game Review using Deep Learning and Sentiment Lexicon

Sentiment Analysis is a field of study of obtaining the sentiment of a writer through a written text about a particular subject. This study proposes a modified method in performing sentiment analysis using deep learning. The proposed method uses a sentiment lexicon to precalculate the estimated dataset sentiment score and adding it as a new attribute to the dataset, which is then used in training the deep learning models. This study uses user board game review dataset taken from the BoardGameGeek website and a Long Short-Term Memory Network (LSTM) model is used for performing a three-class sentiment analysis. The proposed method managed to improve the accuracy of the model from 45.17% to 54.67%. Keywords— Board game, Deep Learning, Long Short-term Memory Network, Sentiment Analysis, Sentiment Lexicon, User review
Plant Lead Disease Detection and Smart Spraying Robot using Artificial Intelligence for Precision Agriculture

Abstract: As we all know that India is the biggest agricultural country variety of crops are grown here and many a times these crops are destroyed by the diseases that are settled on the plants leaves so to overcome this we have proposed a model that will detect the diseases in the plant leaves and spray the required medicine for the same. Keywords: Species detection, Disease Detection, CNN Algorithm, Image Pre-processing, Medicine spraying.
Upaya Peningkatan Kemampuan Penggunaan Microsoft Access Programming Bagi Pegawai Unit Usaha Bank Sumut Syariah

This training aims to improve the ability to use microsoft access programming for employees of the Bank Sumut Syariah business unit. This training was attended by all employees because this training is considered very important to support the performance of the employees. Currently, the Bank Sumut Syariah business unit has implemented technology based on Microsoft Access Programming in the context of carrying out all office activities. This training is carried out by means of socialization to employees, discussions, training and also direct practice of its use. The service activities for the Microsoft Access Programming Training have been carried out well. The service activity for the Microsoft Access Programming Training received an enthusiastic response from the participants of the Bank Sumut Syariah unit employees. Microsoft Access Programming training is carried out in stages and distributed in 14 meetings with a student center learning system and project based learning model so that employees can solve work problems with the skills that have been taught. Microsoft Access is a relational computer database application program that is used to design, create and process various types of data with large capacities. Database is a collection of related tables. Between tables with one another are related to each other, so it is often called a relational database. The relations between tables are connected by a key, namely the primary key and foreign key
Security and international crime drops

While security devices are sometimes maligned, they offer the most efficient means of reducing crime and criminality. The best security measures activate powerful crime prevention mechanisms and are also elegant, that is, ethical and unobtrusive. A strong body of evidence shows how security measures were responsible for the major and prolonged declines in many crime types internationally. Security improvements that remove crime opportunities offer the best hope for reducing crime, cybercrime, future crime and criminality.
ДОСВІД ОРГАНІЗАЦІЇ ТА ПРОВЕДЕННЯ ЛАБОРАТОРНИХ РОБІТ НА БАЗІ ДЕМОНСТРАЦІЙНОЇ ЗАЛИ НАТУРНИХ ЗРАЗКІВ РАКЕТНО-КОСМІЧНОЇ ТЕХНІКИ

Special importance of laboratory works in educational process of students of the physics-technical faculty of Dniprovskyi national university is emphasized. The laboratory rocket-space specimens for study are showed. A number of recommendations to improve of laboratory work effectiveness are formulated.
Perbandingan Pemeriksaan Trombosit Cara Rees Ecker dan Amonium Oxalate dengan Gold Standard Hematology Analyzer

In some clinical laboratories, especially in laboratories at health center and in small clinics outside big cities, the manual method of counting platelets is still widely used, in medium to major laboratories, manual methods have been abandoned and have changed to automatic methods, this is due to patients in the laboratory. Medium-sized hospitals tend to be more than health center laboratories so that health center laboratory workers prefer to use the manual platelet count method. The purpose of this study was to find out how far the results of the rees ecker and amonium oxalate examination of platelets differ from the gold standard hematology analyzer, which of the two methods is closest to the hematology analyzer. So that it can be a reference for health workers and the health center themselves to choose which manual examination method is better, i.e. the results are closer to the results of the gold standard hematology analyzer. The type of research conducted is comparative research, which is comparing the differences in the value or data of one variable with another. Based on the results of manual platelet examination using amonium oxalate, the results are closer to the results of automatic platelet examination, namely the gold standard hematology analyzer, thus manual platelet examination with amonium oxalate can be an option for smallclinics.
Seven Segment Display Circuit Simulation using Electronics Workbench

A seven segment display, or in Indonesian it is called a seven segment display, is an electronic device consisting of segments that are used to display decimal numbers or numbers. This journal will explain how to simulate a seven segment display circuit using computer software called Electronics Workbench. This simulation is done to help understand how a seven segment display circuit can work, and because this is a simulation, there is no need to be afraid of failure, or making mistakes. This simulation is done by connecting a seven segment display with a 74 series Digital IC, you can use a 7447 or 7448 IC, because the function is still the same, and the IC formation is still the same, and is suitable for connecting seven segment displays. Then the IC is controlled via a switch / button that is connected directly to the IC, and the switch and IC are also connected to a power source, so that the circuit simulation can run. The results of this simulation show that the simulation can be done well in the Electronics Workbench software, can be a medium of learning about how seven segment displays work, and so that we can more easily understand how electronic devices work.
HetGraph: A High Performance CPU-CGRA Architecture for Matrix-based Graph Analytics

In this paper, we explore graph analytics on a heterogeneous platform named HetGraph integrating with CPU and a flexible CGRA accelerator called RFU for matrix-based paradigm in this paper. RFU utilizes the lightweight pipeline without data hazards to support various generalized Sparse Matrix-Vector multiplications (SpMVs) of matrix-based graph analytics effectively. HetGraph utilizes the degree-aware workload distribution with vector-scanning sparsity removing scheme to alleviate the impact of highly sparse graph. Furthermore, we propose a heterogeneous work-stealing strategy to balance the workloads between CPU and RFU for HetGraph. To the best of our knowledge, HetGraph is the first heterogeneous CPU-CGRA architecture for matrix-based graph analytics. Overall, HetGraph achieves 9.42x, 2.45x speedup, and 9.80x, 7.70x energy savings on average compared to state-of-the-art (SOTA) CPU-based and GPGPU-based solutions respectively. Compared to the SOTA graph analytics accelerator, HetGraph also achieves 1.42x speedup and 1.06x less energy.
Penerapan Metode RUP Untuk Sistem Pengajuan Cuti Pegawai Di SMA AZ-Zahra Palembang Berbasis Web Mobile

There are still a lot of even almost all types of companies that still use conventional methods in recording or calculating leave manually, one of them is SMA Az-zahra Palembang, Seeing with increasingly sophisticated technological advances, the author wants to help the problem of recording employee leave. Create a computerized leave application information system. The benefits include facilitating the recording process, both submitting leave for each employee and setting up leave confirmation so that each workforce can be properly distributed. The development is carried out using the RUP (Rational Unified Process) method and making designs using the Unified Modeling Language (UML) visual modeling. The application used in making this application is PHP, and MYSQL database. The hope of the information system created is that it can help accurately record employee leave and make the company better at managing its workforce.
Neural Reflex Networks for Automating Quadcopter Drone Obstacle Avoidance

The physically modelled neural and nervous networks pioneered more than two decades ago by Mark Tilden, E. A. Rietman and collaborators, M. Ashkenazi et al. have proven to be a robust and interesting way to obtain powerful emergent behavior by utilizing neuromimetic circuitry. Using a physical representation of biologic neurons, both motor (NU) and cortical (NV) these structures mimic simple reflex arcs present in a large number of evolved organisms. The simple circuits using logic gate oscillators wired as integrators or pulse delay loops with sensors coupled as current injectors or variable resistors of different types demonstrated unexpected emergent „survival” behaviors when connected in chains or loops of several neurons. Mark Tilden calls the simplest functional unit of such looped structures „bicores”-as two neurons linked together in a loop already generate meaningful behavior when their inputs are linked to appropriate sensors. These powerful neuromimetic machines allow for a robust implementation of automated responses in autonomous or semi-autonomous robots. Quadcopters are a very good target for neural network control/stabilization because of their unique flight dynamics and normal control procedures. Obstacle avoidance and stabilization are simple tasks for a well-tuned physical neural network.
Developing and Deploying Artificial Intelligence Systems

This special issue of Computer addresses lessons learned and best practices for developing and deploying artificial intelligence systems.
SHORTSTACK: Distributed, Fault-tolerant, Oblivious Data Access

Many applications that benefit from data offload to cloud services operate on private data. A now-long line of work has shown that, even when data is offloaded in an encrypted form, an adversary can learn sensitive information by analyzing data access patterns. Existing techniques for oblivious data access-that protect against access pattern attacks-require a centralized and stateful trusted proxy to orchestrate data accesses from applications to cloud services. We show that, in failure-prone deployments, such a centralized and stateful proxy results in violation of oblivious data access security guarantees and/or system unavailability. We thus initiate the study of distributed, fault-tolerant, oblivious data access. We present SHORTSTACK, a distributed proxy architecture for oblivious data access in failure-prone deployments. SHORTSTACK achieves the classical obliviousness guarantee--access patterns observed by the adversary being independent of the input--even under a powerful passive persistent adversary that can force failure of arbitrary (bounded-sized) subset of proxy servers at arbitrary times. We also introduce a security model that enables studying oblivious data access with distributed, failure-prone, servers. We provide a formal proof that SHORTSTACK enables oblivious data access under this model, and show empirically that SHORTSTACK performance scales near-linearly with number of distributed proxy servers.
Analisis Open Journal System Lembaga Ilmu Pengetahuan Indonesia

An analysis of the Open Journal System (OJS) published by the Indonesian Institute of Sciences 2016-2020 was carried out, against the background of the growing development of OJS. The analysis aims to determine: a) The number of OJS issued by LIPI; b) Number of OJS that have received SINTA accreditation from the Ministry of Research and Technology/BRIN; c) Frequency of issue of OJS; d) Most publishers; e) Number of articles published 2016-2020. The data source is a journal located on the https://ejournal.lipi.go.id/ site. The study used a descriptive method, and data collection was carried out by noting the title of the journal, frequency of publication, description of the contents of the journal, the first year it was published, the level of accreditation of the SINTA journal, and the number of articles. The results showed that 25 OJS titles had been published, and the most were in the social and humanities field (9 journals). OJS is at least an engineering field (4 titles). The Sinta 2 accreditation is in the top position, but there is no SINTA 1 accreditation. The highest frequency of publication is twice a year, the number of articles is 1,631 titles, namely the field of biology, 447 titles, social humanities 773 titles, engineering 191 titles, and earthly 220 titles. It is concluded that OJS LIPI has 25 titles, with the number of social and humanities journals occupying the first place, it is necessary to improve the quality of journals from SINTA 2 to SINTA 1.
Peningkatan Kemenangan Non-Playable Character dalam Permainan Triple Triad Menggunakan Alpha-Beta Pruning

Non-Playable Character (NPC) is one of the essential elements in video games. Generally, NPCs provide challenges for players in completing missions in the game, where NPCs mean acting as enemies. The role of the enemy causes the victory rate to be one of the main goals of artificial intelligence applied to NPCs. The challenges that these NPCs provide are significant to keep players going. NPCs must be able to provide a balanced challenge like humans to have an experience that is as enjoyable as when playing with other people. The problem is the low win rate achieved by NPCs so that players can feel bored. The alpha-beta pruning algorithm is one of the decision-making algorithms that is often applied to games that require more than or equal two players. Therefore, this algorithm is suitable for applying to the object of research, namely the Triple Triad game. The Triple Triad game is a board game played by two players. The Triple Triad game was first introduced as a mini-game in the Final Fantasy VIII game. This game is a combination of card games and board games. In this study, the alpha-beta pruning algorithm was proven to increase the win rate of NPCs. It is indicated by comparing the win rate of NPCs who choose a random step, which is 17.5%, with an NPC that has applied the alpha-beta pruning algorithm, which is 55%. Therefore, there is a significant increase in the win rate. Keywords: Alpha-beta pruning; artificial intelligence; card; game; Non-Playable Character.
Saúde mental dos estudantes de medicina durante a pandemia de Covid-19 em uma instituição do interior de Minas Gerais / Mental health of medicine students during the Covid-19 pandemic in an institution in the inside of Minas Gerais

uma instituição do interior de Minas Gerais Mental health of medicine students during the Covid-19 pandemic in an institution in the inside of Minas Gerais
How to Utilize E-EWS as a Tool in Healthcare

ECHO (the European network of Cybersecurity centres and competence Hub for innovation and Operations) is one of the four pilot projects under the European Commission’s H2020 Program. This work-in-progress paper relates to the project’s task “ECHO Early-Warning Systems (E-EWS) / ECHO Federated Cyber Range (E-FCR) Demonstration Workshops” that will be implemented during 2021 and 2022. As the healthcare industry becomes more connected to the Internet, the possibilities for disastrous cyber-attacks rise accordingly. Well-performing warning systems and robust information sharing between different parties are essential tools to help prevent these attacks. The aim of this paper is to find out how to utilize E-EWS as a tool in the healthcare sector. We started by mapping out the existing Early Warning Systems related to healthcare. At the same time, we researched the different implementations of E-EWS into already existing national systems and how possible information sharing could be done. As a result, we found that there does not seem to be any widely used international Early Warning Systems in use in the healthcare field and can conclude that implementing E-EWS could have significant benefits for the whole industry. A working Early Warning System can help to prevent cyber threats and save lives. However, there are many challenges involved in the implementation. First, the healthcare field is very fragmented with many different private and national actors, and second, the structural differences between different EU countries bring their own problems. Thus, the successful implementation of E-EWS in healthcare depends mainly on how all the different actors can cooperate.
Peningkatan Hasil Belajar IPS melalui Pembelajaran Kooperatif Tipe Think Paire Share di SMPN 2 Saptosari Gunungkidul

This study aims to improve social studies learning outcomes through cooperative learning of the Think Pair Share type for class VIIIC students of SMPN 2 Saptosari, Gunungkidul Regency, in the 2021/2022 academic year. The subjects of this study were 24 students consisting of 10 males and 14 females. This type of research is classroom action research (CAR) with two cycles. Each cycle consists of three meetings, and each session has four stages, namely (1) planning, (2) implementation, (3) observation, and (4) reflection. Data collection techniques used are tests and observations. The data analysis technique used is a quantitative descriptive technique with a percentage. The results showed that the Think-Pair-Share type of cooperative learning improves social studies learning outcomes. Its show: 1) the number of students who completed the pre-cycle of as many as 13 students (54.16%), 2) at the end of the first cycle of students who reached the KKM as many as 17 students (70.83%), and 3) at the end of the second cycle as many as 20 students (83.33%) managed to reach the KKM. Based on the results of data analysis and discussion, it can be concluded that Think Pair Share cooperative learning can improve social studies learning outcomes for class VIIIC SMPN 2 Saptosari, Gunungkidul Regency for the 2021/2022 academic year.