Reviewerly/exHarmony huggingface dataset:
Finite Memory Estimation-Based Recurrent Neural Network Learning Algorithm for Accurate Identification of Unknown Nonlinear Systems

This paper proposes a novel finite memory estimation based learning algorithm (FME-LA) for recurrent neural networks (RNNs) to accurately identify unknown nonlinear systems. The proposed algorithm, FME-LA, is designed through finite memory estimation (FME) whose gain is obtained under the unbiased condition by minimizing the Frobenius norm. The FME is designed on the concept of the horizon to decide how many recent measurements are considered and maintain a finite memory structure of the learning algorithm. Therefore, the proposed algorithm provides accurate performance and fast convergence for the system identification of unknown nonlinear systems under rapidly or smoothly changing circumstances with inaccurate information, such as modeling uncertainties or incorrect noise statistics. We confirm fast convergence and accurate performance of the proposed algorithm through simulation and experimental results.
The Implementation of Cooperative Learning to Developed Management of Language Learning System

The cooperative learning model is part of a learning structure that has a broad scope. Inside there are approaches, strategies, methods and techniques. One important aspect of a learning model is syntax, which is the standard steps that must be taken in implementing the model. The purpose of this study is to develop management learning system on teaching materials based on active learning in cooperative learning. The collected-data can be in the forms of poll result, stuffing and field notes on the instrument activity sheet on the state of implementation of lectures and learning. Data were analyzed using statistical methods. Hypotheses were tested using t-tests to see the impact of cooperative learning models. The results of this research are: (1) teaching materials based on active learning and (2) article related to active-cooperative learning. The results of the expert validation of learning, teaching materials to be eligible, for subsequent use in learning. In relation to the advantages of using the cooperative learning model which is proved can make a positive interdependence; recognition in responding to individual differences; students are involved in class planning and management; a relaxed and pleasant class atmosphere; establishing a warm and friendly relationship between students and teachers; and having many opportunities to express pleasant emotional experiences.
Modified Hybrid Discriminant Analysis Methods and Their Applications in Machine Learning

This paper presents a new hybrid discriminant analysis method, and this method combines the ideas of linearity and nonlinearity to establish a two-layer discriminant model. The first layer is a linear discriminant model, which is mainly used to determine the distinguishable samples and subsample; the second layer is a nonlinear discriminant model, which is used to determine the subsample type. Numerical experiments on real data sets show that this method performs well compared to other classification algorithms, and its stability is better than the common discriminant models.
Habilidades desenvolvidas na confecção de um CanSat

The ARANDU project main objective is to bring students from public schools, from the 9th grade of elementary and high school, to the engineering environment.Thus, the adopted methodology was to prepare a course in which basic classes are taught in various engineering areas, and whose final product is the construction of a pico-satellite called "CanSat".Classes take place in the theory-practice duet.The learning acquired is fundamental because it pr motes skills such as logical thinking, attention, communication, teamwork and creativity, as well as the basic knowledge necessary for creating a CanSat.These skills are important for the knowledge improvement and still have, as a secondary objective, the incentive to enter college/university or job market.In this work, the activities related of the ARANDU 2018 project will be exposed.Adopted structures, applications of the classes and obtained results will be described.And finally, the project evaluation will be shown from the students' perspective.
Multimodal, Context-Aware, Feature Representation Learning for Classification and Localization

Automatic detection of malicious or provocative social media content is increasingly important to efforts leading to counteract illicit activities in the digital platform. This paper proposes a context-aware, regional feature representation learning framework that exploits multimodal cues to improve automatic detection by enhancing classification via accurate localization. Unlike most existing multimodal approaches, which evaluate category membership of multimedia web contents only at the image level, our approach leverages object proposals to identify potential interest regions within images in order to provide more precise localization performance that in turn, in a context-aware setting, also improves classification result. The proposed attention learning module estimates the domain specific cross-modal, fine-grained regional feature correspondence, conditioned on the classification categories, by evaluating mode relevance scores in a data-driven manner. The initial classification decision is further validated using a query adaptive decision fine-tuning for a more accurate final prediction. Experiments on publicly available datasets and on in-house datasets demonstrate superior classification performance as compared to monomodal and existing multimodal baselines.
On the complexity of zero gap MIP*

The class $\mathsf{MIP}^*$ is the set of languages decidable by multiprover interactive proofs with quantum entangled provers. It was recently shown by Ji, Natarajan, Vidick, Wright and Yuen that $\mathsf{MIP}^*$ is equal to $\mathsf{RE}$, the set of recursively enumerable languages. In particular this shows that the complexity of approximating the quantum value of a non-local game $G$ is equivalent to the complexity of the Halting problem. In this paper we investigate the complexity of deciding whether the quantum value of a non-local game $G$ is exactly $1$. This problem corresponds to a complexity class that we call zero gap $\mathsf{MIP}^*$, denoted by $\mathsf{MIP}^*_0$, where there is no promise gap between the verifier's acceptance probabilities in the YES and NO cases. We prove that $\mathsf{MIP}^*_0$ extends beyond the first level of the arithmetical hierarchy (which includes $\mathsf{RE}$ and its complement $\mathsf{coRE}$), and in fact is equal to $Π_2^0$, the class of languages that can be decided by quantified formulas of the form $\forall y \, \exists z \, R(x,y,z)$. Combined with the previously known result that $\mathsf{MIP}^{co}_0$ (the commuting operator variant of $\mathsf{MIP}^*_0$) is equal to $\mathsf{coRE}$, our result further highlights the fascinating connection between various models of quantum multiprover interactive proofs and different classes in computability theory.
Mobile Forensics for Cyberbullying Detection using Term Frequency - Inverse Document Frequency (TF-IDF)

The case of cyberbullying in Indonesia was ranked third in the world in 2015 and as much as 91% was experienced by children [1]. RSA Anti Fraud Command Center (AFCC) report reports that in 2015 45% of transactions were carried out through mobile channels, while 61% of fraud occurred through mobile devices [2]. WhatsApp in July 2019, 1.6 billion users access the WhatsApp messenger on a monthly basis [10]. The data opens a reference for investigators to better anticipate cybercrime actions that can occur in the whatsapp application because more users are using the application. In this study using the TF-IDF method in detecting cyberbullying that occurs in order to be able to add a reference for investigators. The conclusions that have been obtained from the simulation of conversations between four people in a whatsapp group get the results of the cyberbullying rate that the user "a" has a cyberbullying rate of 66.80%, the user "b" has a cyberbullying rate of 50%, the user "c" has a level cyberbullying is 33.19%, user "c" has a cyberbullying rate of 0% from the data proving that the TF-IDF method can help investigators detect someone who will commit cyberbullying actions but in its development a better way is needed when preprocessing so that the abbreviation or changing words can still be detected perfectly.
DIGITAL INCLUSION, ICT IN EDUCATION IN URUGUAY

reason or another have limitations for access to ICT, is among the main objectives of Cuban society. The present chapter ventures into this issue and systematically exposes achievements, projections and barriers still existing for the gradual digital inclusion of the disabled, elderly, women, children and young people from rural schools in remote areas. Educational experiences that have been obtained are addressed, as well as pedagogical and technological challenges that still need to be resolved in order to reduce the digital divide in Cuba.
Making Sensors, Making Sense, Making Stimuli: The State of the Art in Wearables Research From ISWC 2019

The International Symposium on Wearable Computers (ISWC) has been the leading research venue for wearable technology research since 1997. In 2019, the 23rd ISWC was held in London, U.K., from Sep. 9th–13th. Following on the last eight years of successful collaboration, ISWC was colocated with the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp).
Time-reversal homotopical properties of concurrent systems

Directed topology was introduced as a model of concurrent programs, where the flow of time is described by distinguishing certain paths in the topological space representing such a program. Algebraic invariants which respect this directedness have been introduced to classify directed spaces. In this work we study the properties of such invariants with respect to the reversal of the flow of time in directed spaces. Known invariants, natural homotopy and homology, have been shown to be unchanged under this time-reversal. We show that these can be equipped with additional algebraic structure witnessing this reversal. Specifically, when applied to a directed space and to its reversal, we show that these refined invariants yield dual objects. We further refine natural homotopy by introducing a notion of relative directed homotopy and showing the existence of a long exact sequence of natural homotopy systems.
Design and Development of Game Based Learning Applications for Mathematics Learning Based on Multiple Language to Develop Verbal Capabilities

The purpose of this research is to design an application that can help students in learning.So, the authors are interested in designing game-based mobile learning applications that have mathematical content on integer material integrated with hijaiyah numbers, so that the game media has its own uniqueness.This is due to meet the needs of game based learning in teaching and learning.This design is based on the obligation to develop numeracy skills for all citizens according to Law number 20 of 2003 concerning the national education system.In addition, there is also an obligation to understand the number of hijaiyah for Muslim citizens.The research method used uses research development.The development model used is SDLC.The stages of development consist of analysis to research design.Validation is done with results that show the attractiveness of the media with some notes.The concept in this game is like a game in general that uses this type of adventure.In the game there is a mission to solve the problem.The challenge is through hijaiyah figures provided.So this game combines mathematics with hijaiyah numbers in a portable way.
Quantum secret sharing using GHZ state qubit positioning and selective qubits strategy for secret reconstruction

The work presents a novel quantum secret sharing strategy based on GHZ product state sharing between three parties. The dealer, based on the classical information to be shared, toggles his qubit and shares the product state. The other parties make their Bell measurements and collude to reconstruct the secret. Unlike the other protocols, this protocol does not involve the entire initial state reconstruction, rather uses selective qubits to discard the redundant qubits at the time of reconstruction to decrypt the secret. The protocol also allows for security against malicious attacks by an adversary without affecting the integrity of the secret. The security of the protocol lies in the fact that each party's correct announcement of their measurement is required for reconstruction, failing which the reconstruction process is jeopardized, thereby ascertaining the $(3,3)$ scheme which can further be extended for a $(n,n)$ scheme.
A Personal Tribute to David Schmeidler’s Influence

Research in Osnabrück in Germany.Two positive impressions preceded it.First, my
Adaptive Federated Learning With Gradient Compression in Uplink NOMA

Federated learning (FL) is an emerging machine learning technique that aggregates model attributes from a large number of distributed devices. Several unique features such as energy saving and privacy preserving make FL a highly promising learning approach for power-limited and privacy sensitive devices. Although distributed computing can lower down the information amount that needs to be uploaded, model updates in FL can still experience performance bottleneck, especially for updates via wireless connections. In this work, we investigate the performance of FL update with mobile edge devices that are connected to the parameter server (PS) with practical wireless links, where uplink update from user to PS has very limited capacity. Different from the existing works, we apply non-orthogonal multiple access (NOMA) together with gradient compression in the wireless uplink. Simulation results show that our proposed scheme can significantly reduce aggregation latency while achieving similar accuracy.
Novel Electro-optic Components for Integrated Photonic Neural Networks

We demonstrate PIC-based non-volatile optical synaptic elements, an essential building block in large non-von Neumann circuits realized in integrated photonics. The impact of non-idealities on the performance of a photonic recurrent neural networks is evaluated.
Local Binary Pattern and Its Variants: Application to Face Analysis

Local Binary Pattern is a descriptor whose purpose is to summarize the local structure of the images. The goal is to be able to discriminate different images. This method has gone through a large number of changes and adjustments in different types of applications. This paper reviews various LBP methods for facial expression analysis and proposes a new set of variants. Firstly, the principle of LBP is presented and the main variants for face recognition and facial expression analysis are described. Then, new variants are proposed and finally, a comparison with the referred existing ones is made and analyzed through experiments conducted on facial recognition databases YaleB and ORL, and on facial expressions recognition database JAFFE.
Searching Information Mountain on the Java Island to help improve Tourism with the Vector Space Model

Mountain expeditions and climbers are not hindered by advances in digital technology at the moment, seen increasing mountain climbing on the island of Java.This is due to the abundance of biodiversity in the mountains of the island of Java such as Mount Gede Pangrango which has many nail trees, at the foot of Mount Rinjani which is surrounded by butterfly species, Mount Merbabu with 70 species of birds, natural savanna with an area of ± 300 Ha and has the highest mountain, Mount Semeru with 3,676 meters above sea level.The potential and natural wealth can attract tourists to travel there so that it can be a factor to develop the economy in the area.This research helps tourism to search information mountain in Java Island by using the Vector Space Model (VSM) algorithm.The algorithm using to data preparation, tokenizing, filtering, stemming, calculation, and finally document ranking framework.Generated 14 sample data from search results on Google with the query "mountain on the island of Java".VSM algorithm runs well enough to produce the highest ranking of 3.716189934.
Formation Of Students’ Soft Skills In The Process Of Integration In Cdio

More and more researchers, representatives of different branches of scientific knowledge (economics, psychology, pedagogy) note the importance of soft skills to achieve competitiveness in the labor market of representatives of different professional fields. The article demonstrates the need for graduates of natural-scientific directions to develop not only hard skills, but also soft skills. In the process of research, it was possible to identify the most significant competencies for the performance of their professional duties, to identify the formation / non-formation of these competencies in studying process at the university. To achieve the goal of the research, in 2018, a survey of 68 graduates of the natural science profile of Surgut State University working in the specialty was conducted. The survey made it possible to confirm theoretical positions regarding the importance of soft skills in professional activity. The main research tool was a questionnaire survey. Questionnaires were distributed to respondents in printed copy. The questionnaire used questions that made it possible for employers to assess the importance of competencies and the level of representation of competencies among graduates by employers. By questioning and using methods of mathematical statistics, a statistically significant difference was determined between the level of development of competence formed at the university and the actual level necessary for fulfilling professional duties.
Keeping it simple: Implementation and performance of the proto-principle of adaptation and learning in the language sciences

In this paper we present the Widrow-Hoff rule and its applications to language data. After contextualizing the rule historically and placing it in the chain of neurally inspired artificial learning models, we explain its rationale and implementational considerations. Using a number of case studies we illustrate how the Widrow-Hoff rule offers unexpected opportunities for the computational simulation of a range of language phenomena that make it possible to approach old problems from a novel perspective.
A music recommendation algorithm based on clustering and latent factor model

The collaborative filtering recommendation algorithm is a technique for predicting items that a user may be interested in based on user history preferences. In the recommendation process of music data, it is often difficult to score music and the display score data for music is less, resulting in data sparseness. Meanwhile, implicit feedback data is more widely distributed than display score data, and relatively easy to collect, but implicit feedback data training efficiency is relatively low, usually lacking negative feedback. In order to effectively solve the above problems, we propose a music recommendation algorithm combining clustering and latent factor models. First, the user-music play record data is processed to generate a user-music matrix. The data is then analyzed using a latent factor probability model on the resulting matrix to obtain a user preference matrix U and a musical feature matrix V. On this basis, we use two K- means algorithms to perform user clustering and music clustering on two matrices. Finally, for the user preference matrix and the commodity feature matrix that complete the clustering, a user-based collaborative filtering algorithm is used for prediction. The experimental results show that the algorithm can reduce the running cost of large-scale data and improve the recommendation effect.
Optimal path planning based on A* algorithm for submarine mining vehicle

Deep sea mining, as a frontier area in China, urgently needs to make progress in automatic navigation technology. In order to improve the operation efficiency of the seabed mining machine on the soft seabed, the submarine mining vehicle which complete the mining work in a certain mining area need to enter the next mining area quickly and economically. As a classical algorithm, the majority of scholars consider that A * algorithm is the most practical path planning search algorithm. Considering the limitation of operation conditions, the three-dimensional diagram is transformed into two-dimensional diagram by interpolation method when the seabed terrain conditions allow, and then the obstacles can be marked in two-dimensional diagram. A* algorithm was applied into the path planning of mining truck. The simulation results of the paper show that path cost, turning time and turning mode should be considered in the process of avoiding obstacles.
Innovation and development of English education in colleges and universities in the new period

As an international language, English has an important influence on the future development of students. This paper mainly introduces the problems existing in English education in colleges and universities in China in the new period and the strategies for innovating English teaching in colleges and universities for reference.
Exploring Implications for the Competence-Based Social Studies Curriculum through the Analysis of Overseas Social Studies Curriculums

This study compared and analyzed the social studies curriculums of New York, Ontario, Canada, Australia and Singapore in order to explore what is emphasized in the social studies curriculum documents for the practice of competences cultivation. As a result of the analysis, there is no country that had a subject competency separately in the social studies curriculum. In addition, emphasis was placed on the inquiry and concept of thinking in the social studies curriculum of every countries. In terms of inquiry, not only the inquiry process and detailed activities were specified, but also questions and activities that can be used in the class were presented in various ways, and the inquiry process emphasized the cultivation of functions and thinking skills. In terms of concept, the use of concept in the process of inquiry was emphasized, and the relationship between concept understanding and competences cultivating, and the role of students and teachers for this were suggested. Based on these points, implications for the social studies curriculum in Korea were derived.
CPM R-CNN: Calibrating Point-guided Misalignment in Object Detection

In object detection, offset-guided and point-guided regression dominate anchor-based and anchor-free method separately. Recently, point-guided approach is introduced to anchor-based method. However, we observe points predicted by this way are misaligned with matched region of proposals and score of localization, causing a notable gap in performance. In this paper, we propose CPM R-CNN which contains three efficient modules to optimize anchor-based point-guided method. According to sufficient evaluations on the COCO dataset, CPM R-CNN is demonstrated efficient to improve the localization accuracy by calibrating mentioned misalignment. Compared with Faster R-CNN and Grid R-CNN based on ResNet-101 with FPN, our approach can substantially improve detection mAP by 3.3% and 1.5% respectively without whistles and bells. Moreover, our best model achieves improvement by a large margin to 49.9% on COCO test-dev. Code and models will be publicly available.