Reviewerly/exHarmony huggingface dataset:
Analyzing Offline Social Engagements: An Empirical Study of Meetup Events Related to Software Development

Software developers use a variety of social media channels and tools in order to keep themselves up to date, collaborate with other developers, and find projects to contribute to. Meetup is one of such social media used by software developers to organize community gatherings. We in this work, investigate the dynamics of Meetup groups and events related to software development. Our work is different from previous work as we focus on the actual event and group data that was collected using Meetup API. In this work, we performed an empirical study of events and groups present on Meetup which are related to software development. First, we identified 6,327 Meetup groups related to software development and extracted 250,36 9 events organized by them. Then we took a sample of 452 events on which we performed open coding, based on which we were able to develop 9 categories of events (8 main categories +&#x201C;Others&#x201D;). Next, we did a popularity analysis of the categories of events and found that Talks by Domain Experts, Hands-on Sessions, and Open Discussions are the most popular categories of events organized by Meetup groups related to software development. Our findings show that more popular categories are those where developers can learn and gain knowledge. On doing a diversity analysis of Meetup groups we found 20.46&#x0025; of the members on average are female, and 20.34&#x0025; of the actual event participants are female, which is a larger proportion as compared to numbers reported in previous studies on gender representation in software engineering communities. We also found evidence that the gender of Meetup group organizer affects gender distribution of group members and event participants. Finally, we also looked at some data on how COVID-19 has affected the Meetup activity and found that the event activity has dropped, but not stalled. A substantial number of events are now being organized virtually. The results and insights uncovered in our work can guide future studies related to software communities, groups, and diversity-related studies.
A Quantum Resistant Chameleon Hashing and Signature Scheme

Chameleon signatures introduced by Krawczyk and Rabin are based on well-established hash-and-sign paradigm. It is a non-interactive signature scheme that simultaneously provides the properties of non-transferability and non-repudiation. The chameleon hash function is a trapdoor one-way function which prevents everyone except the holder of the trapdoor information from computing collision on a message digest. The chameleon signature scheme achieves non-transferability as the recipient of the signature is the holder of the trapdoor information. He could be able to compute collision on the hash value and hence no third party could be able to identify the real signer. In the initial constructions of chameleon signature schemes, the occurrences of collisions expose the secret key of the recipient. This strongly prevents the recipient to compute hash collisions, partially undermining the concept of non-transferability. Hence it is important to overcome this key exposure problem, and its aligned problems of key revocation and key redistribution. Also the existing chameleon signature schemes are based on the hard problems in number theory such as integer factorization or the discrete log problem over various groups. The construction of a large-scale quantum computer would render insecurity to these schemes. Hence as recommended by NISTIR 8105, we propose a quantum resistant chameleon hashing and signature scheme based on hard problems in coding theory. The scheme also satisfies the security properties of chameleon signature, such as collision resistance, semantic security, key exposure freeness, non-transferability and unforgeability. As code-based cryptosystem is an important candidate of postquantum cryptosystem, the proposed code-based chameleon signature scheme would be a promising alternative to the number theoretic based schemes. In addition, we also propose a method to transform the code-based chameleon hashing scheme into an ordinary signature scheme and prove its unforgeability in the random oracle model.
Boomerang Uniformity of Popular S-box Constructions

In order to study the resistance of a block cipher against boomerang attacks, a tool called the Boomerang Connectivity Table (BCT) for S-boxes was recently introduced. Very little is known today about the properties of this table especially for bijective S-boxes defined for n variables with n ≡ 0 mod 4. In this work we study the boomerang uniformity of some popular constructions used for building large S-boxes, e.g. for 8 variables, from smaller ones. We show that the BCTs of all the studied constructions have abnormally high values in some positions. This remark permits us in some cases to link the boomerang properties of an S-box with other well-known cryptanalytic techniques on such constructions while in other cases it leads to the discovery of new ones. A surprising outcome concerns notably the Feistel and MISTY networks. While these two structures are very similar, their boomerang uniformity can be very different.
Progress and Challenges of Hand-eye-foot Coordination for Mobile Manipulator

The goal of mobile manipulators is to perform complex operational tasks autonomously in a structured and unstructured environment and to work or closely interact with humans. Mobile manipulators brings more complicated engineering problems and deeper scientific problems. It is not easy to simply combine the research results of mobile platforms and robot arms to solve the unique and complex problems: hand-eye-foot coordination for mobile manipulator. Firstly, this paper mainly presented a survey of mobile manipulator from three aspects: autonomous grasping strategy, mobile platform and path planning. Especially, we discussed the basic principle of space trajectory planning for mobile manipulators and its practical application combined with vision, and further divided them into six categories according to different modeling principles. In conclusion, we suggest that mobile manipulators still face three major challenges: uncertainty in high-dimensional space, highly coupled dynamic nonlinearity, real-time performance of dynamic task planning.
A Strategy for Multi-target Paths Coverage by Improving Individual Information Sharing

The multi-population genetic algorithm in multi-target paths coverage has become a top choice for many test engineers.Also, information sharing strategy can improve the efficiency of multi-population genetic algorithm to generate multi-target test data; however, there is still space for some improvements in several aspects, which will affect the effectiveness of covering the target path set.Therefore, a multi-target paths coverage strategy is proposed by improving multi-population genetic algorithm based on individual information sharing among populations.It primarily contains three aspects.Firstly, the behavior of the sub-population covering corresponding target path is improved, so that it can continue to try to cover other sub-paths after covering the current target path, so as to take full advantage of population resources; Secondly, the populations initialized are prioritized according to the matching process, so that those sub-populations with better path coverage rate are executed firstly.Thirdly, for difficultly-covered paths, the individual chromosome features which can cover the difficultly-covered paths are extracted by utilizing the data generated, so as to screen those individuals who can cover the difficultly-covered paths.In the experiments, several benchmark programs were employed to verify the accuracy of the method from different aspects and also compare with similar methods.The experimental results show that it takes less time to cover target paths by our approach than the similar ones, and achieves more efficient test case generation process.Finally, a plug-in prototype is given to implement the approach proposed.
Bayesian Convolutional Neural Network: Robustly Quantify Uncertainty for Misclassifications Detection

For safety and mission critical systems relying on Convolutional Neural Networks (CNNs), it is crucial to avoid incorrect predictions that can cause accident or financial crisis. This can be achieved by quantifying and interpreting the predictive uncertainty. Current methods for uncertainty quantification rely on Bayesian CNNs that approximate Bayesian inference via dropout sampling. This paper investigates different dropout methods to robustly quantify the predictive uncertainty for misclassifications detection. Specifically, the following questions are addressed: In which layers should activations be sampled? Which dropout sampling mask should be used? What dropout probability should be used? How to choose the number of ensemble members? How to combine ensemble members? How to quantify the classification uncertainty? To answer these questions, experiments were conducted on three datasets using three different network architectures. Experimental results showed that the classification uncertainty is best captured by averaging the predictions of all stochastic CNNs sampled from the Bayesian CNN and by validating the predictions of the Bayesian CNN with three uncertainty measures, namely the predictive confidence, predictive entropy and standard deviation thresholds. The results showed further that the optimal dropout method specified through the sampling location, sampling mask, inference dropout probability, and number of stochastic forward passes depends on both the dataset and the designed network architecture. Notwithstanding this, I proposed to sample inputs to max pooling layers with a cascade of Multiplicative Gaussian Mask (MGM) followed by Multiplicative Bernoulli Spatial Mask (MBSM) to robustly quantify the classification uncertainty, while keeping the loss in performance low.
Adaptive Truncation technique for Constrained Multi-Objective Optimization

The performance of evolutionary algorithms can be seriously weakened when constraints limit the feasible region of the search space.In this paper we present a constrained multi-objective optimization algorithm based on adaptive ε-truncation (ε-T-CMOA) to further improve distribution and convergence of the obtained solutions.First of all, as a novel constraint handling technique, ε-truncation technique keeps an effective balance between feasible solutions and infeasible solutions by permitting some excellent infeasible solutions with good objective value and low constraint violation to take part in the evolution, so diversity is improved, and convergence is also coordinated.Next, an exponential variation is introduced after differential mutation and crossover to boost the local exploitation ability.At last, the improved crowding density method only selects some Pareto solutions and near solutions to join in calculation, thus it can evaluate the distribution more accurately.The comparative results with other state-of-the-art algorithms show that ε-T-CMOA is more diverse than the other algorithms and it gains better in terms of convergence in some extent.
Encryption Based On Multilevel Security for Relational Database EBMSR

Cryptography is one of the most important sciences today because of the importance of data and the possibility of sharing data via the Internet. Therefore, data must be preserved when stored or transmitted over the Internet. Encryption is used as a solution to protect information during the transmission via an open channel. If the information is obtained illegally, the opponent/ enemy will not be able to understand the information due to encryption. In this paper we have developed a cryptosystem for testing the concepts of multi security level. The information is encrypted using more than one encryption algorithm based on the security level. The proposed cryptosystem concerns of Encryption Based on Multilevel Security (MLS) Model for DBMS. The cryptosystem is designed for both encryption and decryption.
Overview of AIWolfDial 2019 Shared Task: Contest of Automatic Dialog Agents to Play the Werewolf Game through Conversations

The AIWolf project has been holding contests to play the Werewolf game ("Mafia") by automatic agents for a couple of years.A difficulty of the Werewolf game is that the game is an imperfect information game, where a player's role is hidden from other players.Players are required to infer the roles of other players through free conversations; players of a specific role should tell a lie, while others try to break through lies.We employ this werewolf game as a novel way of evaluations for dialog systems.Because the werewolf game forces players to deceive, persuade, and detect lies, neither inconsistent nor vague response are evaluated as "unnatural", losing in the game.Our werewolf game competition and evaluation could be a new interesting evaluation criteria for dialog systems, but also for imperfect information game theories.In addition, the werewolf game allows any conversation, so the game includes both task-oriented and non-task-oriented conversations.This aspect would provide a handy intermediate goal rather than to create a general dialog system from scratch.In this AIWolfDial 2019 shared task, five participant agents played games in English and Japanese.We performed subjective evaluations on these game logs.
ANALISIS PERBANDINGAN ALGORITMA DECISION TREE DENGAN SUPPORT VECTOR MACHINE UNTUK MENDETEKSI KOMPETENSI MAHASISWA KONSENTRASI INFORMATIKA KOMPUTER STUDI KASUS : POLITEKNIK LP3I JAKARTA, KAMPUS DEPOK

Detection of computer informatics student competence is indispensable for anticipating students who have a very poor performance in following the learning process in an educational institution for the purpose of all educational institutions are creating a qualified student. It can be seen in the results of the 5th and 6th semester students who have gained employment. Polytechnic LP3I Jakarta Depok one vocational education institution founded to create a human being who has the ability / skills required by the company so that the concept is to offer education that have Link and Match. Competitors who have the same goals is one of the challenges to be faced by the agency so we need a solution to overcome it. One solution is the detection of computer informatics student competence of students. This can be done by using data mining techniques. One data mining techniques used are support vector machines (SVM). Support vector machine method is able to overcome the problem of high-dimensional, addressing the problem of classification and regression with linear or nonlinear kernel that can be the ability of learning algorithms for classification and regression, but the support vector machine has a problem in the appropriate parameters. To overcome these problems required method of decision tree as a comparison, for the selection of appropriate parameters. Several experiments were conducted to obtain optimum accuracy. Experiments using support vector machine and decision tree which is used to optimize the parameters C, and e population. Training data used computer informatics student data from 2012 to 2014 academic year. The experimental results show the decision tree method of data that is equal to 92.50% with a ratio of 60 training data were compared with data vector machine that is equal to an accuracy of 92.56% and the second T-Test metod done that method has a probability value of < 0.05 which algorithm C4.5. Keywords : Detection, Competence, Support Vector Machine, Decision Tree
Identification in the service of national solidarity

The transition to the total dematerialization of procedures and transactions requires the establishment of an environment of trust allowing in particular the secure identification of all stakeholders. We propose a structured, hierarchical and universal model of identification that uniquely identifies each stakeholder (administration, citizen, ...) while protecting personal data against any manipulation, access or disclosure without the approval of their owner. Our model uses the United Nations service domain classification and is based on a coding system that provides unique interoperability and identification at the global level while preserving country sovereignty. We introduce a universal code assigned to each citizen or entity of the e-government platform. This codification will support local identification and universal interoperability. Its implementation is achieved through the introduction of the code proposed in the X.509 V3 digital certificate. to illustrate our model, we applied it to the field of national solidarity and more precisely to the allocation of subsidies to the most needy. Our approach allows reliable identification to directly target the most needy reliably.
Contribuições para a gestão de dados científicos: análise comparativa entre modelos de ciclo de vida dos dados | Contributions to the management of scientific data: comparative analysis among life cycle models

RESUMO O objetivo foi analisar as intersecções entre os elementos dos modelos de ciclos de vida dos dados das iniciativas do DCC, DataONE e o CVD-CI. Trata-se de uma pesquisa descritiva, qualitativa e bibliográfica. Verificou-se que há correspondências entre etapas (nem sempre de um para um) dos ciclos de vida dos dados analisados. Foi possível constatar que o CVD-CI condensa várias atividades em uma única etapa, o que pode dificultar a sua aplicabilidade. De uma maneira geral, os modelos propostos ainda carecem de maior detalhamento para poderem ser aplicados diretamente por pesquisadores/curadores.Palavras-chave: Ciclo de Vida dos Dados; Curadoria Digital; Dados científicos; Tecnologia da Informação.ABSTRACT The objective was to analyze the intersections among the data life cycle model elements of the DCC, DataONE and CVD-CI initiatives. It is a descriptive, qualitative and bibliographical research. It was verified that there are correspondences between stages (not always one-to-one) of the analyzed data life cycles. It was possible to verify that the CVD-CI condenses several activities in a single step, which can hinder its applicability. In general, the proposed models still need to be further detailed so that they can be directly applied by researchers/curators.Keywords: Data Life Cycle; Digital Curation; Scientific Data; Information Technology.
Identity crime in the UK

This chapter deals with the definition, measurement, detection and prosecution of offences that appear to defy the categories to which criminology has made us accustomed. Identity crime is characterized by a degree of hybridity, in that it can be perpetrated by offenders from diverse backgrounds and affiliations. It presents itself with the hazy traits perceptively identified in the introduction to this collective volume. In brief, it prompts questions around the possible evolution of crime, the professional skills this requires and the type of subculture in which offenders are embedded.
IMPLEMENTASI AUGMENTED REALITY SEBAGAI ALAT BANTU PADA PENDERITA BUTA WARNA BERBASIS ANDROID

Color blindness is a condition where one can not distinguish a certain color that can be distinguished by a person with a normal eye. A person suffering from color blindness may be caused by birth defects or from overuse of drugs. Color blindness has two types: Blind Partial Color that is blind of color of this type can not see two kinds of colors such as red-green, and blue-yellow whereas other types Blind Colors total that people only see black and white (monochromatic) suffered by men, while women are merely as carriers or recessive genes. Regarding Android smartphone camera there are already applications that use Augmented Reality system by using a camera where there will be 2D or 3D objects that will be displayed to real world objects. The AR app will use the Marker based tracking method AR which uses a marker or a two-dimensional object marker that has a pattern to be read through a camera connected to an Android smartphone, usually a black and white square illustration with a thick black border and a white background.
Classification Algorithms Analysis in the Forest Fire Detection Problem

The development of information technology allows applying complex mathematical algorithms. For example, machine learning (ML) procedures are used in almost all humans life areas: smart home systems, online recommendation systems intelligent chatbots and so on. This creates a huge demand for specialists in data analysis and ML. Modern data analysis packages often do not require deep knowledge from a specialist, which allows to apply all ML algorithms without a deep understanding of their work. However, the main problem is that the data is not suitable for the algorithm and as a result, the algorithm cannot detect all the patterns or does it incorrectly. This situation can be acceptable in pet projects and is completely unacceptable in cases where the algorithm error costs a lot of money or human lives. In this paper the analysis of ML algorithms and the possibility of their application to forest fires data are done.
“MATHEMATICA” IN TEACHING STUDENTS MATHEMATICS

&#x0D; &#x0D; &#x0D; &#x0D; The relevance of the topic of the article is due to the process of modernization of higher mathematical education in Russia, which has led to a significant change in curricula and the need to look for ways and forms of training that would allow students to learn the necessary material within the time granted for studying, while obtaining the maximum necessary amount of skills, knowledge, and competencies. The objective of the article is to justify the ways and principles of the development and implementation of new pedagogical and information technologies in the educational process, the organization of professional education of students in technical areas based on the integration of mathematics and computer science. The leading method of the study of this problem is the methodological analysis and subsequent synthesis, which, by analyzing the didactic content of the sections in mathematics and the possibilities of the computer mathematical environment called Mathematica, reveals the necessary methods and ways of developing and using modern computer technologies in the mathematical education of engineering students. It is proved that one of the main tools for implementing the methods for solving the indicated problem should be considered a computer, namely, the mathematical environment called Mathematica, and the basic principles of its systemic implementation in the educational process of the university have been identified. The materials of the article may be useful to teachers of mathematical disciplines of higher educational institutions, the computer programs and pedagogical software products created in Mathematica can serve as models for the development of similar pedagogical software products.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D;