Reviewerly/exHarmony huggingface dataset:
A Stochastic Composite Augmented Lagrangian Method for Reinforcement Learning

In this paper, we consider the linear programming (LP) formulation for deep reinforcement learning. The number of the constraints depends on the size of state and action spaces, which makes the problem intractable in large or continuous environments. The general augmented Lagrangian method suffers the double-sampling obstacle in solving the linear program. Motivated from the updates of the multipliers, we overcome the obstacles in minimizing the augmented Lagrangian function by replacing the intractable conditional expectations with the multipliers. Therefore, a deep parameterized augmented Lagrangian method is proposed. The replacement provides a promising breakthrough to integrate the two steps in the augmented Lagrangian method into a single quadratic penalty problem. A general theoretical analysis shows that the solutions generated from a sequence of the constrained optimization converge to the optimal solution of the linear program if the error is controlled properly. A theoretical analysis on the quadratic penalty algorithm without using target networks under a neural tangent kernel setting shows the residual can be arbitrarily small if the parameter in the network and the optimization algorithm is chosen suitably. Preliminary experiments illustrate that our method is competitive with other state-of-the-art algorithms.
Research on the Integrated Construction of Electronic Technology Courses for the Cultivation of Applied Talents in Higher Vocational Colleges

Under the new situation, higher vocational and technical education should highlight the characteristics of vocational education and innovate curriculum and teaching models in terms of cultivating high-quality applied and skilled talents. This paper takes the construction of electronic technology courses compulsory for higher vocational communication and electronics majors as the main research object, comprehensively analyzes the current situation of course teaching, focusing on reshaping the course system, optimizing course content, innovation in teaching organization forms, environmental resources and teacher construction, etc., and deeply discusses the integrated construction strategy of electronic technology courses in higher vocational colleges, and put forward the curriculum reform methods suitable for the characteristics of higher vocational student. This method can provide useful reference for the cultivation of applied talents in higher vocational colleges.
IoT Ethic In Scientific Communications

IoT is now essential for the resource allocation of organized things and people. Science is one of the social institutions that now need in the Internet of Things technology to develop the interoperability of heterogeneous devices and scientific research services. The system of interactions with IoT technology for professional scientific communities, which have special ethical rules for responding to political, economic, social and cultural challenges of society, deserves special rules. Poor contextual awareness of the scientific community is closely related to the problem of protecting scientific data in IoT networks from bad compatibility and inability to connect to the specified communication channels. The search and analysis of scientific communications by existing IoT services is limited by the design limits of the methodological use of connecting IoT devices. The ethical norms of the scientific community can be seen in IoT technologies as constraints, indicators, characteristics and reinforcements for machine learning and IoT human-machine communications.
Machinery Monitoring and Maintenance System Using Decision Tree Model for Fault Prediction

This paper presents a design and implementation of the machinery monitoring and maintenance system. The proposed system has two advanced features including supervision of machinery in real-time and potential fault prediction by using decision tree model. The monitoring system is designed using IoT technologies to collect machine data including power consumption and operation states. Moreover, the potential faults of monitored machines are predicted by the proposed algorithm using decision tree model. The whole system has been implemented and applied in a real factory to demonstrate its performance.
Research on Dedicated Data Set for Deep Learning Processor Precision Verification

With the rise of the artificial intelligence wave, deep learning processors have received extensive attention from academia and industry due to their strong computing power, low power consumption, small area and other architectural advantages. In order to ensure algorithm compatibility, deep learning processors include many precision designs, its verification space is huge. For this reason, based on the traditional hierarchical verification, in the system-level precision verification, a dedicated data set is proposed. The experiment shows that compared with the traditional random data set, dedicated data set can greatly reduce the simulation time while ensuring the completeness of the verification.
Out of Your Mind!? Embodied Interaction in Sports

People engage in sportive activities for reasons beyond improving their athletic performance. They also seek experiences like fun, adventure, a feeling of oneness, clear their heads, and flow. Since sport is a highly bodily experience, we argue that taking an embodied interaction perspective to inspire interaction design of sports systems is a promising direction in HCI research and practice. This workshop will address the challenges of designing interactive systems in the realm of sports from an embodied interaction perspective focusing on athletes’ experience rather than performance. We will explore how interactive systems enhance sports experience without distracting from the actual goal of the athlete, such as freeing the mind. We will focus on several topics of interest such as sensory augmentation, augmented experience, multi-modal interaction, and motor learning in sports.
Demonstrating TapID for Rapid Touch Interaction on Surfaces in Virtual Reality for Productivity Scenarios

We demonstrate a novel approach to bring quick touch interaction on surfaces to Virtual Reality, which is a challenge for current camera-based VR headsets that support free-hand mid-air interaction or physical hand-held controllers for input. In our approach, we use our wrist-worn prototype TapID to complement the optical hand tracking from VR headsets with inertial sensing to detect touch events on surfaces, which establishes the same interaction modality that is present on today’s phones and tablets. Each TapID band integrates a pair of inertial sensors in a flexible strap, from whose signals TapID reliably detects surface touch events and identifies the finger used for touch. This event detection is then fused with the optically tracked hand poses to trigger input in VR. Our demonstration comprises a series of VR applications, including UI control in word processors, web browsers, and document editors. These applications showcase the beneficial use of rapid tapping, typing, and surface gestures in Virtual Reality.
Well-Being and Efficiency in Financial Sector Analyzed with Multiclass Classification Machine Learning

The main research goal is the identification of the most important well-being parameters determining worker’s efficiency in the financial sector from 2005 until 2020 in the time of great changes in the socio-economic situation in Slovenia. Data were collected in 2005, 2010, 2015, and 2020 - key periods of important milestones in economic growths and declines in Slovenia for 2723 financial workers. All data are analyzed using the ML classification method to identify the most important attributes (well-being parameters) determining worker’s efficiency. To prevent possible overfitting and/or underfitting there is a prescribed adequate tree depth for each decision tree as an additional domain knowledge added to the presented ML solution. We chose a binary decision tree learning, that is simple to understand and interpret with an ability to handle both numerical and categorical data.Decision trees generated with the ML classification show, that workers with low efficiency (estimated as “poor” or “inadequate”) were mostly out of work. In 2005 the most important influential factor was psychological fatigue. From 2010 to 2020, physical fatigue was the most important influential factor.External socio-economic factors determine the level of well-being and efficiency. Adequate level of well-being is the basis of workers’ efficiency and their health. The conclusions are based on the data from 2005 to 2020. Presented approach based on implementation of ML is a tool for identification of gripping points for intervention at work to maintain adequate level of workers well-being in a new working reality.
The Topological Mu-Calculus: Completeness and Decidability

We study the topological μ-calculus, based on both Cantor derivative and closure modalities, proving completeness, decidability, and finite model property over general topological spaces, as well as over T 0 and T D spaces. We also investigate the relational μ-calculus, providing general completeness results for all natural fragments of the μ-calculus over many different classes of relational frames. Unlike most other such proofs for μ-calculi, ours is model theoretic, making an innovative use of a known method from modal logic (the ‘final’ submodel of the canonical model), which has the twin advantages of great generality and essential simplicity.
Understanding Statistics

Most participants of MobileHCI will have had to deal with statistics: sometimes formal statistics with tests and probabilities, sometimes informally ‘eyeballing data’. Even if you do not use statistics in your own work, you are likely to need to interpret the statistics in other people’s papers and reports. This tutorial is intended to help you navigate the often confusing discussions about the use and misuse of statistics, to help you gain a ’gut feeling’ for statistics and also know when not to trust those instincts. The tutorial builds on the instructor’s recent book “Statistics for HCI” and also extensive freely available videos and other online material.
Analyzing User Requirements and Interface Designing on Mobile Solutions for Waste Segregation

Segregation of our waste is essential as the amount of waste being generated today caused an immense problem. Many items in regular household waste is biodegradable and/or recyclable and in fact, only a very minor portion is actually meant to be disposed of. Owing to this we decided to formulate a plan for a mobile application named Segrify, that would help in assisting regular people; no matter their level of skill with technology; with the segregation of waste. It is strongly founded on the principles of human computer interface (HCI) to make interaction and UX as smooth as possible. Aside from having designs for an interesting flashcard based game for younger users, the design would incorporate the use of an AI chatbot assistant which, when spoken to, would classify the requested item into the correct criteria of waste. It would also include a community chat feature encouraging community participation and interaction as well as a feed section to deliver the latest news and updates to the users. Aside from having designs for an interesting flashcard based game for younger users, the design would incorporate the use of an AI chatbot assistant which, when spoken to, would classify the requested item into the correct criteria of waste. It would also include a community chat feature encouraging community participation and interaction as well as a feed section to deliver the latest news and updates to the users.
Corpus, experimental and modeling investigations of cross-linguistic differences in pronoun resolution preferences

We investigate the impact of syntactic alternatives on pronoun resolution in ambiguous constructions in English and French. Previous research detected language-specific preferences in pronoun resolution in utterances of the type “The postman met the streetsweeper before he went home”. These preferences have been attributed to the interaction of information structural and syntactic constraints inducing a subject bias on the one hand, and Gricean reasoning processes taking into account alternative syntactic constructions on the other hand. A corpus study of four English and French corpora shows that an alternative construction which takes a subject antecedent (“The postman met the streetsweeper before going home”) is much less frequent in spoken English than French. A Rational Speech Act (RSA) model with corpus frequencies integrated as language-specific costs on the use of each construction makes empirical predictions for pronoun resolution preferences in French and English for sentences with “avant”/“before” which have been tested before but also for sentences with “après”/“after” which have not been tested so far. New experimental data show a very good fit of the model predictions for pronoun resolution preferences in English as well as for the differences in antecedent choices between French and English. However, experimental data showing differences in antecedent choices between French sentences with “après” and “avant” deviate from model predictions, indicating that more factors need to be taken into account. The combination of Bayesian modeling, corpus analyses and experimental data shows that RSA models can make relevant and falsifiable predictions for cross-linguistic variation in processing.
Parameter estimation of a truncated regression model based on improving numerical optimization algorithms

Abstract Limited dependent variable models, including truncated regression models, have traditionally been estimated by the method of maximum likelihood. The conventional optimization algorithms; which is known as Quasi-Newton algorithm namely BFGS Quasi-Newton algorithm is used to reach the optimum values for estimated parameters. In this paper, the nature-inspired algorithm is employed to improve the numerical optimization algorithms to better estimation. Our Monte Carlo simulation results suggest that our proposed improving can bring significant improvement relative to others, in terms of mean squared error and prediction mean squared error.
Chi-Squared Test Analysis on Hybrid Cryptosystem

: Nowadays, the internet has reached every aspect of our day-to-day life. The idea of cryptography is to provide security. It is an encryption technique used for network security when different networks are interconnected and become vulnerable to attacks and intrusions. Different algorithms, like DES, 3-DES, Modified DES, RSA, and Modified RSA algorithms for encryption, have been reported. In this paper, a hybrid cryptosystem which is the combination of the traditional DES and RSA has been discussed. The performance analysis, such as the chi-squared test and then frequency analysis of the hybrid algorithm have been discussed in this article to show the novelty of the combined DES and RSA work, and a comparative study has been performed with the traditional DES and RSA techniques. The chi-squared methodology is a statistical way of evaluating the quality of ciphertext. If the ciphertext needs to be strong then a high value of chi-squared is desired.
The Influence of Internet Communications on the Basic Values of a Metropolitan City Resident

The effectiveness of communication strategies depends on the congruence of public communications with the basic values of the target audience. The values can be defined as the phenomena of social reality and as figurative associations to information stimuli. Communications are built on the mental and linguistic basis of society; it reflects the values that are traditional for this society. In the digital era, basic values in the form of figurative associations are still an integral part of people's public consciousness. Due to the fact that associations are related to social attitudes of people, their assimilation and transmission of the system of values, this poses the question about the extent to which associations were modified under the influence of the digital and media environment. Associations explicate people's collective and individual perceptions that are currently continuing to undergo a modification. This article is based on the material obtained as a result of studying positive events of the residents of Krasnoyarsk. The respondents were offered to name an important positive event and three association words connected to it. The nature of a research method is mediated by the content of public consciousness, which reflects the social experience of people who live in the same territory, but in different conditions and possess differentiated knowledge, habits and interests. In addition, the specificity of the paper is the following: it focuses on the qualitative study of the main groups of words denoting these events. In the course of the study, the authors have come to the conclusion that the digital environment of a metropolitan city influences the worldview of metropolitan city residents and is perceived by them as a communication tool, the space for communication and recreation. The basic life values remain the same: relationships in family and with friends, childbirth, communication with nature and with animals, favourite activities, professional fulfillment, etc.
Generation and Evaluation of Flow Graphs for Cooking Recipes

Forms of text showing the procedure to achieve a particular purpose include cooking recipes, operation manuals, methods and algorithms given in papers, and descriptions in patents. As the most common type of such documents, an enormous number of recipes have been posted and shared on cooking recipe sites on the web. These are described in listed items where the cooking procedures are numbered, but it takes time to understand the common steps among different cooking procedures and the differences among the completed dishes that have been prepared. One way to solve this difficulty is to visualize a recipe's graph structure. In this paper, we propose a method of generating flow graphs for cooking recipes. This method consists of a structural analysis method and a graph visualization method. Furthermore, we evaluate the generated flow graphs using actual recipes.
Text Document Orientation Detection Using Convolutional Neural Networks

Identifying the orientation of scanned text documents has been a key problem in today’s world where every department of any cooperation is surrounded by documents in one or another way. In this paper, our emphasis is on the more challenging task of identifying and correcting the disorientation of general text documents back to normal orientation. Our work aims to solve the real-world problem of orientation detection of documents in PDF forms which can be later used in further document processing techniques. All further document processing tasks depend on detecting the correct orientation of the document. To do this, the convolutional neural network (CNN) is used which can learn salient features to predict the standard orientation of the images. Rather than the earlier research works which act mostly between the horizontal and vertical orientation of non-text documents only, our model is more robust and explainable as it works at page level with text documents. Also, we have accelerated to a different level with proper explanation and interpretability. The proposed approach runs progressively in real time and, in this manner, can be applied to various organizations as well.
Intermediate coordinate based pose non-perspective estimation from line correspondences

In this paper, a non-iterative solution to the non-perspective pose estimation from line correspondences was proposed. Specifically, the proposed method uses an intermediate camera frame and an intermediate world frame, which simplifies the expression of rotation matrix by reducing to the two freedoms from three in the rotation matrix R. Then formulate the pose estimation problem into an optimal problem. Our method solve the parameters of rotation matrix by building the fifteenth-order and fourth-order univariate polynomial. The proposed method can be applied into the pose estimation of the perspective camera. We utilize both the simulated data and real data to conduct the comparative experiments. The experimental results show that the proposed method is comparable or better than existing methods in the aspects of accuracy, stability and efficiency.
Leakage-Resilient Secret Sharing With Constant Share Size

In this work, we consider the leakage-resilience of algebraic-geometric (AG for short) codes based ramp secret sharing schemes extending the analysis on the leakage-resilience of linear threshold secret sharing schemes over prime fields that is done by Benhamouda et al. in the effort to construct linear leakage-resilient secret sharing schemes with constant share size. Since there does not exist any explicit efficient construction of AG codes over prime fields with constant field size, we consider constructions over prime fields with the help of concatenation method and constructions of codes over field extensions. Extending the Fourier analysis done by Benhamouda et al., one can show that concatenated algebraic geometric codes over prime fields do produce some nice leakage-resilient secret sharing schemes. One natural and curious question is whether AG codes over extension fields produce better leakage-resilient secret sharing schemes than the construction based on concatenated AG codes. Such construction provides several advantage compared to the construction over prime fields using concatenation method. It is clear that AG codes over extension fields give secret sharing schemes with a smaller reconstruction threshold for a fixed privacy parameter <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula> . In this work, it is also confirmed that indeed AG codes over extension fields have stronger leakage-resilience under some reasonable assumptions. Furthermore, we also show that AG codes over extension fields may provide strong multiplicative property which may be used in its application to the study of multiparty computation. In contrast, the same cannot be said for constructions based on concatenated AG codes, even when we are considering multiplication friendly embeddings. These advantages strongly motivate the study of secret sharing schemes from AG codes over extension fields. The current paper has two main contributions: (i) we obtain leakage-resilient secret sharing schemes with constant share sizes and unbounded numbers of players. Some of the schemes constructed without the use of concatenation also possesses strong multiplicative property (ii) via Fourier Analysis, we analyze the leakage-resilience of secret sharing schemes from codes over extension fields. This is of its own theoretical interest independent of its application to secret sharing schemes from algebraic geometric codes over extension fields.