Reviewerly/exHarmony huggingface dataset:
Proposal for a software development framework based on the ISO/IEC 29110 standard: Public organizations

In Software Engineering there are several methods, methodologies, standards or frameworks, which allow the development of better quality software or with less expenditure of resources. However, the context of each organization must be taken into account in order to make the correct choice of any of them. In the case of very small entities (less than 25 people), they also face other problems, such as the limited amount of resources available. In public sector organizations that are in charge of software development or operation and services the same problems are identified. In addition, there are a number of laws or regulations that they must comply with, such as MAAGTICSI. Therefore, this article shows the proposal of a framework for software development based on the ISO/IEC 29110 standard for public sector organizations that aims to help improve their processes for software management and development. In order to establish this proposal, the main standards and methodologies that are applied in public organizations in Mexico were identified, as well as, some related works that show how some standards and methodologies are implemented in small organizations.
Implementation of K-Modes Algorithm for Clustering of Stress Causes in University Students

Stress is an inevitable part of life in a college environment. The variety of factors that cause stress in students, it is necessary to cluster the factors that cause stress in students to see the description of the characteristics of each cluster of students. The clustering process is carried out to identify the causes of stress in student groups and their relationship to these internal and external factors. Cluster analysis can be used as a reference to decide on efforts to handle and prevent increased stress in students.&#x0D; The clustering process is carried out using the Python programming language. The algorithm used is the k-modes clustering algorithm. This algorithm is suitable for clustering categorical data. The optimal number of clusters obtained from the implementation of the elbow method is three clusters. Cluster 1 is a cluster with a mild stress level, the main cause of stress is academic issues. Cluster 1 is the only group where the majority of the cause of stress is not financial. Cluster 2 is a cluster with a high stress level which causes various stressors. However, cluster 2 is the only cluster where the cause of stress is on careers and on involvement in hostels, clubs, and society. Cluster 3 is a cluster with a medium stress level. This cluster is the only cluster dominated by male gender. The main cause of stress in this cluster is academic and financial.
Pemilihan Kualitas Gambir dengan Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA)

Gambier (gambir plantae) is an half of perdu plantation which in separated in several regions of Indonesia. It is especially live in Sumatra, Java, Maluku, and Burneo. In West Sumatra province, gambir is used to component for menyirih (betle) and also the farmer of gambir asproduction as. It is reserving from hot water. Extraction come from the leaves and twigs of gambir in depositor forms, then printed and then turned into dried forms. The gambir farmers usually sell their productions to the collectors with a certaibty prices. Gambir has many qualities based from it processing, catechin contains, colors, ash contains, water contains, and also its density. Some its barries often occurs from the gambir processing being into product, which a minusly quality suffers, that cause gambir price in decrease or not to expensive conditions in the market by using support decision by Multi-Objective Optimization by Ratio Analysis (MOORA) methode is a multi objektives system from which can be optimated some atributes whom contradicting each other in simultaneously, either lost profit (cost) or getting profit (benefit), the system using these methode used to choose some gambir qualified form for determine its price. These data of sample taken form Pesisir Selatan gambir, which the research result farmed that gambier ranked can be as support as some decisions to make the best gambir as price decision as. Form theseresearch could be conclude that the best gambir have an higher catechin contains, low water contains, a slightly ash contains, with a yellowish skin, and have as highest as density. Based on the data of sample of research, the best gambier in qualified in getting from Siam and pian with the grade in 0.163 with the good one criteria condition. From gambier standardization, all of gambier which have upper grade standars, qualified into good gambier quality, gambier with high quality or good can give an expensive price that encourages some gambir farmers in motivation to process gambir product being increase gambier quality that can be improve the price selling gambir as well as the purchase of gambier products.
TEACHING NEW METHODS OF INTERCULTURAL COMMUNICATION IN THE AREA OF LIBRARY AND INFORMATION SERVICES

The relevance of the problem under study is that the article examines the formation of modern teaching methods of intercultural communication in an area of library and information services on the background of the integration of libraries into the developing information society. Important characteristics of a modern area of library and information services are open access to funds, remote consultation of a bibliographer and access to network resources from home computers, tablets and mobile devices.The purpose of the study is to design teaching methods of intercultural communication in an area of modern library and information services. Research objectives: to define the concept of an area of library and information services; to determine the main pedagogical methods of updating the linguistic and cultural knowledge of students in the area of library and information services; define the basic methods of information technology. Object of research: the area of modern library and information services, which is formed in the context of the integration of libraries into the developing information society. The area of library and information services allows creating a more open atmosphere for mutual communication and training of ethnocultural users and foreign language speakers, when it is recognized that each person has his own specific knowledge and experience that can enrich others. In this regard, a special environment of all kinds of symbolic forms is created in the library, the purpose of which is to gradually immerse the reader in an atmosphere of polysemy, multilingualism, the coexistence of various cultural meanings so that he gets used to the possibility of such a world order and does not experience a cultural shock when meeting it in reality. Research methods: observation, study, generalization of advanced pedagogical experience on this topic. The results of the research are: teaching methods of intercultural communication in the area of library and information services have been developed; the linguistic environment in the area of library and information services by comparing languages and cultures in the learning process has been explored; integration of IT disciplines and foreign languages has been proved to be effective. The results of the research can contribute to the development of practice of intercultural communication and be used for further scientific research on this and related topics.
Artificial Emotions in Intelligent machines

The article presents the results of research devoted to identifying and clarifying the causes of the existing methodological difficulties and shortcomings inherent in the modeling of emotions in artificial agents.The arguments that the neurobiological data obtained in recent studies should be necessarily taken into account in the development of artificial emotions are presented, and a set of methodological recommendations for future research in the field of artificial emotions and intelligent machines in general is proposed.
Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolution

Masked language models (MLMs) have contributed to drastic performance improvements with regard to zero anaphora resolution (ZAR). To further improve this approach, in this study, we made two proposals. The first is a new pretraining task that trains MLMs on anaphoric relations with explicit supervision, and the second proposal is a new finetuning method that remedies a notorious issue, the pretrain-finetune discrepancy. Our experiments on Japanese ZAR demonstrated that our two proposals boost the state-of-the-art performance, and our detailed analysis provides new insights on the remaining challenges.
Search-oriented Differentiable Product Quantization.

Product quantization (PQ) is a popular approach for maximum inner product search (MIPS), which is widely used in ad-hoc retrieval. Recent studies propose differentiable PQ, where the embedding and quantization modules can be trained jointly. However, there is a lack of in-depth understanding of appropriate joint training objectives; and the improvements over non-differentiable baselines are not consistently positive in reality. In this work, we propose Search-oriented Product Quantization (SoPQ), where a novel training objective MCL is formulated. With the minimization of MCL, query and key's matching probability can be maximized for the differentiable PQ. Besides, VCS protocol is designed to facilitate the minimization of MCL, and SQL is leveraged to relax the dependency on labeled data. Extensive experiments on 4 real-world datasets validate the effectiveness of our proposed methods.
A TYPOLOGY OF TEXTURES IN SOUTH NAGHADEH INTRUSIVE ROCKS, NORTHWESTERN IRAN

South Naghadeh is abundant in intrusive rocks. The region is part of Laramide magmatism in the Sanandaj–Sirjan zone and, from a petrological point of view, consists of syenogranite and monzogranite, granodiorite, quartz diorite, quartz monzodiorite, quartz monzonite, quartz syenite, and olivine gabbro. Available textures in local granitoid rocks include granular, granophyric, graphic, perthitic, and myrmekitic. The textures represent the formation conditions of the minerals, their layout in the rocks, and their physiochemical transformations during or after crystallization. The textures of local plutonic rocks (such as perthitic and granophyric) and lack of metasomatic aureoles and primary biotite are suggestive of high water vapor pressure and low emplacement depth of these rocks. The corona texture found in olivine gabbros was of the magmatic type.
Das Narrative – bildlich: Geschichten bildlich übersetzen und die Welt erobern

No AccessVisual Storytelling im Design ThinkingApr 2021Das Narrative – bildlich: Geschichten bildlich übersetzen und die Welt erobernFelicidad Romero-TejedorFelicidad Romero-TejedorSearch for more papers by this authorhttps://doi.org/10.3139/9783446468900.003SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2021Pages: 17-58Print ISBN: 978-3-446-46835-1eISBN: 978-3-446-46890-0 Copyright & Permissions© 2021 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
Semi-supervised exemplar learning for object detection in aerial imagery

Deep convolutional neural networks (CNNs) have proven to be successful for learning task-specific features that achieve state-of-the-art performance on many computer vision tasks. For object detection applications, the introduction of region-based CNNs (R-CNNs), and its successors, Fast R-CNN and Faster R-CNN, has produced relatively high accuracies and run-time efficient results. With Faster R-CNN, a region proposal network (RPN) is employed to share convolutional layers for both object proposals and detection with no loss in accuracy. However, these approaches are trained in a fully supervised manner, where a large number of samples for individual object classes are required, and classes are pre-determined by manual annotation. Large-scale supervision leads to limitations in utility for many real-world applications, including those involving difficult-to-detect, small, and sparse target objects in variable environments. Alternatively, exemplar learning is a paradigm for discovering visual similarities in an unsupervised fashion from potentially very small numbers of examples. Surrogate classes or outliers are discovered via the inherent empirical characteristics of the objects themselves. In this work, we merge the strengths of CNN structures with pre-processing steps borrowed from exemplar learning. We employ a semi-supervised approach that combines the ability to use generically-learned class-relatedness with CNN-based detectors. We train and test the approach on a set of aerial imagery generated from unmanned aircraft systems (UAS) for challenging real-world, small object detection tasks.
Don't Give Up on Large Optimization Problems; POP Them!

Resource allocation problems in many computer systems can be formulated as mathematical optimization problems. However, finding exact solutions to these problems using off-the-shelf solvers in an online setting is often intractable for "hyper-scale" system sizes with tight SLAs, leading system designers to rely on cheap, heuristic algorithms. In this work, we explore an alternative approach that reuses the original optimization problem formulation. By splitting the original problem into smaller, more tractable problems for subsets of the system and then coalescing resulting sub-allocations into a global solution, we achieve empirically quasi-optimal (within 1.5%) performance for multiple domains with several orders-of-magnitude improvement in runtime. Deciding how to split a large problem into smaller sub-problems, and how to coalesce split allocations into a unified allocation, needs to be performed carefully in a domain-aware way. We show common principles for splitting problems effectively across a variety of tasks, including cluster scheduling, traffic engineering, and load balancing.
Holistic defenses against microarchitectural attacks

Execution context isolation is a key security requirement in personal computers, edge devices, and more importantly on multitenant computing environments such as the Cloud. It is vital that data belonging to one context (e.g., a process, enclave, or virtual machine) cannot be accessed or modified by another context without explicit permission, particularly in consideration of a remote adversary. However, the level of context isolation provided by today’s systems is not well aligned with the security needs of personal users, cloud providers, and customers of cloud computing services alike. Current hardware enforces isolation at the architectural level. However recent high-profile attacks demonstrated that isolation guarantees are weak at the microarchitectural-level. To make matters worse, a lot of the defenses against microarchitectural defenses aim to protect specific side-channels rather than providing a more comprehensive solution. In this paper we describe our recent and ongoing efforts in providing holistic defenses against microarchitectural attacks.
Research on the Relationship Between Online Learning Behavior and Learning Effect of College Students in the Digital Learning Environment

This study determined 7 indicators that affect the learning effect of online learning behaviors by consulting relevant literature materials, and used SPSS21.0 to analyse and research the learning behavior data of college students.The study found that the length of the online learning time interval has a significant impact on the online learning effect of college students.The learning effect of students in the short-time interval group is significantly higher than that of the students in the long-time interval group.Different time interval groups have a certain effect on students' final exam results.Test efficiency, test completion rate, and test timeliness have significant effects on college students' learning effects, while the number of forums initiated, the number of replies, and the average test attempt rate have little effect on learning effects.The results show that: decentralized learning is conducive to improving the online learning effect of college students; the online teaching platform should be more intelligent and have automatic reminder function; teaching resources should be based on knowledge points and suitable for fragmented learning; teachers should pay more attention to the learning process of students' management, strengthen the supervision of teaching links; students should strengthen the training of knowledge points.This research provides an effective path for how to improve the teaching level of teachers and the learning effect of students under the new teaching mode.
RESOURCE-BASED LEARNING OF THE DISCIPLINE "HIGHER SCHOOL PEDAGOGY" IN THE CONDITIONS OF DISTANCE EDUCATION

The article on the basis of the analysis of theoretical literature and own practical experience of teaching the discipline "Higher School Pedagogy" characterizes the essence and features of network technologies as a pedagogical technology of resource-based learning of students. An example of the implementation of resource-based learning of students in the study of the discipline "Higher School Pedagogy" using network technologies, which made it possible to create a distance course using the online platform Moodle. It was found that the development of a distance course using various activities and resources of the Moodle platform, its further implementation in the distance learning process makes it interactive, activates students through the use of network projects as one of the priority practice-oriented tasks in these realities, provides effective distance communication, objective control of students' knowledge.
Mutual influence definition of high school students’ basic educational dominants and aspiration levels

The appearance of synergistic effect in the humanist (by L. Zade definition) educational systems according to known Hegelian law should be accompanied by quantitative and qualitative transformations of certain indicators characterizing the human factors influence on decision making. It is proved that such indicators are basic educatio- nal dominants which determine the attitude towards risk and characterize the motivation to achieve success (risk-- taking) / failure avoidance (risk aversion) and the aspiration level, which is one of personality backbone factors and characterize the self-assessment adequacy. Basic educational dominants are found through the solution of the closed decision-making task by constructing a limited points number (five) and further analysis of the estimated utility function of the 12-point scale continuum. Characteristic points of this function are the so-called determined lottery equivalents with corresponding utility n0,25, n0,5, n0,75.The aspiration levels are found through the open decision-making problem solution by constructing on a formal- ly unlimited number of points and further utility function analysis of the 12-point scale continuum. Characteristic points of the estimation function: n– the education result, which corresponds to the negative jump of usefulness in the imagination of those, who study on the acceptability of a particular level of the scale; n0 — the education result, which corresponds to the transition from a negative to a positive perception ratings of the scale; n* is the learning outcome that corresponds to the maximum positive jump of usefulness in the perception of a certain mark on the scale, which in this case is considered as the aspiration level. The m = 208 ninth-graders set the ratio of people who are vulnerable, indifferent and risk-taking in the proportion: VUL: IND: RT  1: 2.27: 10.6.By the prioritization method it was dephased a qualitative rank estimates of 12-point scale giving them corresponding weighted coefficients of significance. Students’ aspiration levels identity regardless of attitude to risk is established, as well as greater consistency of opinions of those tested regarding the acceptability of higher scale scores. Charac- teristic points’ correlation analysis of the utility functions constructed for closed and open decision-making problems revealed a statistically probable relationship between the characteristic points: n0,25–n–, n0,5–n0, n0,75–n*.
Post-Reading Comprehension Questions and Task Types in Vision: A Locally Developed Textbook for Teaching English as a Foreign Language

Abstract Responding to the call for perusing the post-reading comprehension questions in various EFL textbooks, the current study aimed to investigate the post-reading comprehension questions and task types in the Vision series including three student books and their accompanying workbooks in light of Freeman’s (2014) taxonomy. Following a descriptive content analysis procedure, the post-reading comprehension questions in each student books and its accompanying workbook were categorized and counted by the researchers and the Kappa coefficient was 0.97. The results revealed that Content questions were the most dominant type in all the student books and workbooks except for Vision 3 in which Language questions were the most frequent of all. The results also showed that the highest frequency of post-reading comprehension questions belonged to Explicit (Content) and Form (Language) in student books and Explicit and Implicit (Content), Form (Language), and Personal Response (Affect) in workbooks. The results of Kruskal Wallis test of independent samples indicated a significant difference in terms of Affect type across the student books and workbooks of Vision series. The findings raise the EFL material developers’ awareness of the existing post-reading comprehension questions and tasks to enhance the quality of reading sections of EFL textbooks. The results also help the teachers to supplement the books with the missing types and take a comprehensive approach to developing the learners’ reading skills.