Reviewerly/exHarmony huggingface dataset:
COLABORATIVE BADAN PENAGGULANGAN BENCANA DAERAH KOTA DUMAI DALAM MENAGGULANGI KEBAKARAN LAHAN DI KOTA DUMAI

Forest and land fire control is generally carried out through efforts to prevent, extinguish, and handle post-fire carried out at the national level to the level of forest management unit. Fire prevention efforts are carried out through public awareness campaigns; improvement of prevention technology, such as warning and prevention of forest fires, such as reservoirs, green belts, control towers, and others; and software stabilization. The handling of land fire disasters is of particular concern by the central government and regional governments. According to the Ministry of Environment and Forestry (KLHK), based on Landsat satellite imagery up to September 2019, forest and land fires reached 857,755 hectares. For mineral land 630,451 hectares, and 227,304 hectares of peatland. Dumai in 2019 experienced a land deed with a land area of ​​about 192.25 hectares with coverage of the nine river districts, West Dumai, south Dumai, Medangkampai, East Dumai and Bukir Kapur. report from the Dumai City Environment Agency Air Quality Index, Wednesday (18/9) at 07.00 at the level of 500 PSI (695 Pm10 / 698 Pm2.5), dangerous status. Dumai currently has 10 hotspots detected at the 70 percent confidence level, while at the 75 percent confidence level. In accordance with the mayor's regulation number 71 of 2016 concerning the position, organizational structure, duties and functions as well as the work procedures of the Dumai City Regional Disaster Management Agency article 7 point 2, the task of carrying out integrated disaster management includes: 1. Pre-disaster, 2. Emergency response, 3. Post-disaster has not been optimally carried out by disaster management agencies. In order to optimize the handling of land fires in the Dumai City area, the Government of the City of Dumai in particular the Regional Disaster Management Agency seeks in the form of socialization of prevention and suppression of land fires. To realize the handling of land fires, there needs to be collaborative among related institutions, namely the regional government, military, police and other agencies. In the opinion of Ansell and Gash collaborative governance is a process of collaborative activities by regulating a decision in the policy process carried out by several public institutions with other parties involved and directly or indirectly involved with the aim of resolving public problems.
Internet Traffic Prediction in SDN Using RF and XGB

Internet traffic prediction is required for the allocation of bandwidth dynamically to provide continuous services to the users and to improve the QoS (Quality of Service). Internet traffic prediction makes a significant contribution to network operations and management. The consummation of the network can be further improved by studying the measurements of network traffic and predicting them to take early measures accordingly and to yield the internet traffic to effectively utilize the resources of the network, and to improve the QoS (Quality of Service). In this paper, we applied two machine learning models i.e. Random forest (RF) and eXtreme Gradient Boosting (XGB) for SDN traffic prediction and showed that XGB performs better than RF.
Pengujian Aplikasi Reservasi Hotel di LeGreen Hotel &amp; Suite dengan Metode Black Box Testing Boundary Value Analysis

In this test we will use software that has been made, namely the desktop-based LeGreen Hotel Reservation Application. In testing this hotel room reservation application, the writer uses the black box testing method. Black Box Testing is suitable in testing hotel booking applications because this test aims to ensure the functionality of the LeGreen Hotel Reservation application. This study has several stages that must be done, including the identification of experimental problems, input data samples into the process system, then testing to evaluate the output and finally the documentation of test results. Based on the analysis of the results of the application of methods to solve the problem shows that the level of application that runs reaches 70%, able to run and process employee data, rooms, visitors and payments used for hotel reservations. In the admin login form of 30%, only 20% succeeded, and in the Print Report Form, repairs are needed in order to improve the quality of the application in processing report print data as it functions.
The Curious Case of Modified Merge Sort

We propose an O(N logN) sorting method by Modified Merge Sort Method, which shows huge potential to sort big data sets, and even better potential to sort big data sets with a smaller range. Six sorting algorithms: Selection Sort, Insertion sort, Merge sort, Quick sort, Bubble Sort and Modified Merge Sort were implemented in C++ programming languages and tested for the random sequence input of length 100, 1000, 4000, 9000 on random numbers and the IPL Dataset.
PELATIHAN LAS LISTRIK DASAR UNTUK MASYARAKAT USIA PRODUKTIF LINGKUNGAN RW 10 DESA SIDANEGARA KECAMATAN CILACAP TENGAH KABUPATEN CILACAP

Community service is an obligation which must be formed for lecturers in higher education. Training of electrical welding that had been conducted as a form of dedication to society aims to provide the understanding of the importance of skill in conducting the training of basic electrical welding. The objective of the community service was productive men surrounding RW 10 Sidanegara, Cilacap subdistrict. To choose the objective was based on some reason, i.e.,there were many productive men that could cause the effect of the number of unemployed increased. This actvity used two methods. The first method was giving te understanding of basic electrical welding theory. In this case, preaching and discussing method were conducted. The second method was practice in laboratory in order that they obtained skill of welding. The result of this activity was the increase of knowledge and skill about techniques of basic electrical welding. With the skill they obtained, it can give positive impacts for people in economy and social sector.
Automation of mind maps

The mind maps that students compile are subject to verification. To compare graphs, you need to develop an application that connects to the control system training on the server. To reduce the complexity of application development, you need to limit the choice of texts added by students to the knowledge map, the choice of terms from the thesaurus subject area. Automatic assessment of the quality of intelligence maps created by students when mastering the topics of the course can be performed in this way. The restrictions imposed to solve this problem are the prohibition of entering texts from the keyboard. Signatures to card nodes must be selected from a list prepared in advance — from terminological dictionary of the subject area. The need to limit text input requires abandoning the use of common programs and online services for building smart maps. In fact, it is necessary develop new software or modify one of the existing software packages available under an open source license. Perhaps, for the first iterations it is necessary to be limited only to text representation of a card in the outline mode as it is implemented in text2mindmap service.
Mixed Reality: A Known Unknown

Mixed reality (MR) is an area of computer research dealing with the combination of real-world and computer-generated data (virtual reality), where computer-generated graphical objects are visually mixed into the real environment and vice versa in real time.This chapter contains an introduction to this modern technology.Mixed reality combines real and virtual and is interactive, real-time processed, and registered in three dimensions.We can create mixed reality by using at least one of the following technologies: augmented reality and augmented virtuality.The mixed reality system can be considered as the ultimate immersive system.MR systems are usually constructed as optical see-through systems (usually by using transparent displays) or video see-through.Implementation of MR systems is as marker systems (real scene will be added with special markers.These will be recognized during runtime and replaced with virtual objects) or (semi) markerless systems (processing and inserting of virtual objects is without exact markers.Additional information is usually needed, for example, image and face recognition, GPS coordinates, etc.).The chapter contains also a description of mixed reality as an advanced computer user interface and the newest collaborative mixed reality.
Enhancing the Association in Multi-Object Tracking via Neighbor Graph

Most modern multi-object tracking (MOT) systems follow the tracking-by-detection paradigm. It first localizes the objects of interest, then extracting their individual appearance features to make data association. The individual features, however, are susceptible to the negative effects as occlusions, illumination variations and inaccurate detections, thus resulting in the mismatch in the association inference. In this work, we propose to handle this problem via making full use of the neighboring information. Our motivations derive from the observations that people tend to move in a group. As such, when an individual target's appearance is seriously changed, we can still identify it with the help of its neighbors. To this end, we first utilize the spatio-temporal relations produced by the tracking self to efficiently select suitable neighbors for the targets. Subsequently, we construct neighbor graph of the target and neighbors then employ the graph convolution networks (GCN) to learn the graph features. To the best of our knowledge, it is the first time to exploit neighbor cues via GCN in MOT. Finally, we test our approach on the MOT benchmarks and achieve state-of-the-art performance in online tracking.
SPECIFICS OF LEGAL REGULATION IN GENOMIC RESEARCHES AT THE INTERNATIONAL AND EUROPEAN LEVEL

This article is devoted to the analysis of diff erences in approaches and in choice of tools at the international (universal) and European (regional) levels of interaction between states in the regulation of relations in the fi eld of genomic research and the implementation of their results. The article analyzes specifi cs of approaches at the universal and regional level, including activities of the UN family bodies, the Council of Europe, the European Union in the fi eld of protecting human rights and human genomics. Special attention is paid to the role of international soft law in the development of legal regulation (self-regulation) in the mentioned fi eld. The materials of the article can be useful both in theoretical and practical jurisprudence, and may also be of interest for other areas of the human genome research (bioinformatics, medicine, human reproduction, etc.).
Quotients of Bounded Natural Functors

The functorial structure of type constructors is the foundation for many definition and proof principles in higher-order logic (HOL). For example, inductive and coinductive datatypes can be built modularly from bounded natural functors (BNFs), a class of well-behaved type constructors. Composition, fixpoints, and—under certain conditions—subtypes are known to preserve the BNF structure. In this paper, we tackle the preservation question for quotients, the last important principle for introducing new types in HOL. We identify sufficient conditions under which a quotient inherits the BNF structure from its underlying type. We extend the Isabelle proof assistant with a command that automates the registration of a quotient type as a BNF by lifting the underlying type’s BNF structure. We demonstrate the command’s usefulness through several case studies.
Information Needs of Women Subsistence Farmers in a Village in KwaZulu-Natal Province, South Africa

This article reports on findings of a study that was conducted to establish the information needs of women subsistence or smallholder farmers and the various information sources they consulted to resolve their information needs. The study was qualitative, and a grounded theory design was used. Focus group interviews and observation were used to collect data from 14 women crop farmers and three women livestock keepers. The farmer-to-farmer extension (FFE) model was adopted to understand the information-seeking behaviours of women farmers and how they can be improved, if need be. The findings revealed that while the women crop farmers needed help with seeds, soil treatment and the protection of crops from pests and stray animals, they needed more information on drought preparedness and management, and, on how to transform from subsistence to commercial farming. Women livestock keepers needed information on livestock feeds, the treatment of various ailments, and disaster preparedness and management. In addition, they needed the reintegration of the extension officer. It also transpired that local libraries were not responding to the information needs of farmers. The main source of information was oral communication. The use of radio, television, cell phones and extension officers was limited. This study echoes other studies which propose it is important that libraries, non-government organisations (NGOs) and extension officers respond to the information needs of smallholder farmers, especially women.
Personal Data Privacy Semantics in Multi-Agent Systems Interactions

In recent years, we have witnessed the growth of applications relying on the use and processing of personal data, especially in the health and well-being domains. Users themselves produce these data (e.g., through self-reported data acquisition, or personal devices such as smartphones, smartwatches or other wearables). A key challenge in this context is to guarantee the protection of personal data privacy, respecting the rights of users for deciding about data reuse, consent to data processing and storage, anonymity conditions, or the right to withhold or delete personal data. With the enforcement of recent regulations in this domain, such as the GDPR, applications are required to guarantee compliance, challenging current practices for personal data management. In this paper, we address this problem in the context of decentralized personal data applications, which may need to interact and negotiate conditions of data processing and reuse. Following a distributed paradigm without a top-down organization, we propose an agent-based model in which personal data providers and data consumers are embedded into privacy-aware agents capable of negotiating and coordinating data reuse, consent, and policies, using semantic vocabularies for privacy and provenance.
Visual aid presentation as a learning method: a case study in learning English of management students in Binus University

Abstract Schools, colleges and universities are now embracing the use of visual aid presentation (e.g., PowerPoint) in the classroom. Studies have consistently indicated that students generally believed that the use of technology for oral presentation would facilitate their learning. Students in such condition believed that the class was more organized, clear and interesting. Students also liked the teacher/lecturer more and indicated that they would like to take another class from the teacher/lecturer when the he or she used technology means of presentation. This research was focusing on the perspective of students in Binus University regarding the advantages or disadvantages of this model of learning process in regard of interesting or boring and long or short endurance of understanding. The visual aid presentation here meant that the students were the ones who were performing the presentation, instead of the teacher/lecturer. The research method used was descriptive qualitative based on the survey and interview of some sample students who were chosen randomly, who were taking English course in first/second semester.Based on some researches, the visual aid presentation in learning process was showing positive impact for teachers and students. Therefore, the hypothesis on this research was that the visual aid presentation on learning process would bring an interesting environment, long endurance of understanding and improving students’ behavior. It was expected that the result of this research could be used to improve the learning method of English learning in Binus University in order to support Binus Vision to be a global university and to enrich graduates with the skill of oral presentation.The respondents were selected from management students in Binus, Alam Sutera Campus, and randomly chosen. All of the respondents replied that learning by doing presentations was giving more understanding on topics, boosting up self-confident, teaching public speaking, handling nervous and creating a dynamic class environment to avoid boredom. From the students’ point of view, this learning method was giving advantage for students and long endurance of understanding.
Unbiased Loss Functions for Extreme Classification With Missing Labels.

The goal in extreme multi-label classification (XMC) is to tag an instance with a small subset of relevant labels from an extremely large set of possible labels. In addition to the computational burden arising from large number of training instances, features and labels, problems in XMC are faced with two statistical challenges, (i) large number of 'tail-labels' -- those which occur very infrequently, and (ii) missing labels as it is virtually impossible to manually assign every relevant label to an instance. In this work, we derive an unbiased estimator for general formulation of loss functions which decompose over labels, and then infer the forms for commonly used loss functions such as hinge- and squared-hinge-loss and binary cross-entropy loss. We show that the derived unbiased estimators, in the form of appropriate weighting factors, can be easily incorporated in state-of-the-art algorithms for extreme classification, thereby scaling to datasets with hundreds of thousand labels. However, empirically, we find a slightly altered version that gives more relative weight to tail labels to perform even better. We suspect is due to the label imbalance in the dataset, which is not explicitly addressed by our theoretically derived estimator. Minimizing the proposed loss functions leads to significant improvement over existing methods (up to 20% in some cases) on benchmark datasets in XMC.
On the Privacy-Utility Tradeoff in Peer-Review Data Analysis

A major impediment to research on improving peer review is the unavailability of peer-review data, since any release of such data must grapple with the sensitivity of the peer review data in terms of protecting identities of reviewers from authors. We posit the need to develop techniques to release peer-review data in a privacy-preserving manner. Identifying this problem, in this paper we propose a framework for privacy-preserving release of certain conference peer-review data -- distributions of ratings, miscalibration, and subjectivity -- with an emphasis on the accuracy (or utility) of the released data. The crux of the framework lies in recognizing that a part of the data pertaining to the reviews is already available in public, and we use this information to post-process the data released by any privacy mechanism in a manner that improves the accuracy (utility) of the data while retaining the privacy guarantees. Our framework works with any privacy-preserving mechanism that operates via releasing perturbed data. We present several positive and negative theoretical results, including a polynomial-time algorithm for improving on the privacy-utility tradeoff.
A Latent Semantic Analysis Method for Automatic Scoring System at Essay Test

Abstract An essay test is the type of test that requires students’ skills to propose, arrange, and combine the ideas they have from the teaching-learning process conducted. The essay answers in the form of description cause the examination becomes more complicated compared to an objective multiple-choice test. Therefore, in this research, the scoring system is built for an essay test by Using Latent Semantic Analysis that can pay attention to the word synonym of the key answer on the students’ answer. The highest accuracy from the test that had been conducted at the essay scoring system by Using Latent Semantic Analysis was 84.35%, categorized into good.
J. Ladyman and E. J. Lowe: Patterns, Essence, and Truthmaking

The paper aims to look for an adequate ontological explanation of the «second pattern» existence within Ladyman’s ITSR, the existence of which is a necessary condition that the analyzed pattern is a real pattern indeed. From Ladyman’s point of view, the ontological truthmaker for the epistemic fact is thus that it is a real pattern. As the core interpretation of truthmaking within Ladyman’s concept, we will take the interpretation of truthmaking as essential dependence proposed by E.J. Lowe: an object is a truthmaker for the proposition when part of the essence of the proposition is that the proposition is true if the object exists. Taking into account a number of limitations of Lowe’s concept (essence precedes existence, essence is not an object, etc.), the existence of a “second pattern” within Ladyman’s conception should be understood via defining its essence, regardless of whether its very existence is ever confirmed.
New Developer Metrics for Open Source Software Development Challenges: An Empirical Study of Project Recommendation Systems

Open-source code development has become widespread in recent years. As a result, open-source software platforms have also become popular, and millions of developers from diverse locations are able to contribute to the same projects. On these platforms, various knowledge about them is obtained from user activity. This information is used in the form of developer metrics to solve a variety of challenges. In this study, we proposed new developer metrics, including commenting and issue-related activity, that require less information. We concluded that commenting on any feature of a project can be equally as valuable as code contribution. In addition, besides the quantitative ones, metrics based on only the existence of the activity have been shown to offer also considerable results. We saw that issues were crucial in identifying user contributions. Even if a developer makes a contribution to only one issue on a project, the relation between the developer and the project is tight. The hit scores are relatively lower because of the sparsity problem of our dataset; even so, we believe that we have presented improvable and remarkable new developer metrics.
Sampling the Riemann-Theta Boltzmann machine

We show that the visible sector probability density function of the Riemann-Theta Boltzmann machine corresponds to a Gaussian mixture model consisting of an infinite number of component multi-variate Gaussians. The weights of the mixture are given by a discrete multi-variate Gaussian over the hidden state space. This allows us to sample the visible sector density function in a straightforward manner. Furthermore, we show that the visible sector probability density function possesses an affine transform property, similar to the multi-variate Gaussian density.
The key concepts of forming sociolinguistic competence of future english language specialists

This article aims at examining how cultural norms, rules, shared knowledge and practices build a sociolinguistic competence in successful communication and the crucial needs of forming sociolinguistic competence of future English teachers in EFL classroom as it serves a certain function in social settings.