Reviewerly/exHarmony huggingface dataset:
Matrix Factorization Based on BatchNorm and Preference Bias

With the rapid development of science and technology, huge amounts of information fill people's lives, and the accompanying information overload phenomenon has become an urgent problem to be solved. Because the recommendation system can quickly find the products users want in the massive item information, to a certain extent It has attracted much attention to solve the problem of information overload. Matrix factorization is a commonly used technique in recommendation systems. It can effectively improve the recommendation effect when the scoring matrix is sparse. However, due to its own reasons, matrix factorization has many problems such as sparseness, cold start, and low interpretability. In the field of deep learning, because the normalization technology BatchNorm can optimize the training process, accelerate the training speed and make the training results more stable, it has been studied by a large number of scholars. In this paper, Matrix Factorization Based on BatchNorm and Preference Bias is proposed. BatchNorm is combined with matrix factorization, user and item preferences are added, and Adam algorithm is used for optimization. Experiments show that the algorithm in this paper has a good recommendation effect on sparse matrix.
Generating Fluent Chinese Adversarial Examples for Sentiment Classification

Highly accurate classifiers can be trained by existing machine learning models, however, most of these classifiers do not consider the adversarial attack. This makes these classifiers vulnerable to adversarial examples. In order to improve the ability of sentiment classifiers to resist the adversarial attack, it is very important to generate high-quality adversarial examples. Most of the existing methods that generate natural language adversarial examples aim at English text with relatively simple strategies, but a single transformation strategy is easily detected by the defender. In this paper, we propose a new method to generate Chinese natural language adversarial examples, which is called AD-ER (Adversarial Examples with Readability). The first step is to select the important words in the text, which have great impact on the sentiment classifier. Then we proposed four variant strategies to replace the important words and the best candidate word is selected heuristically under the constraints of its readability and maximum entropy model. The simulation results on a real shopping review dataset verify that the examples generated by our method can produce large attack disturbance to the classifiers. Different from other examples, our examples have good readability and diversity, which are more fluent and harder to be detected.
Note alla traduzione

The Italian translation of the literary work of Adalberto Alves A presença dos dias / La presenza dei giorni is accompained by some usuful translation notes edited by Elena Chiarini in this volume.
3D Joints Extraction Using Single Frame Human Body Point Cloud

We demonstrate 3D joints extraction from a single frame human body point cloud captured by a 3D camera. Average normalized error is less than 5.7 cm for 12 joints in the human body.
Multiplication of Whole Numbers in the Curriculum: Singapore, Japan, Portugal, the USA, Mexico, Brazil, and Chile

Abstract This chapter shows how the teaching of multiplication is structured in national curriculum standards (programs) around the world. (The documents are distributed by national governments via the web. Those documents are written in different formats and depths. For understanding the descriptions of the standards, we also refer to national authorized textbooks for confirmation of meanings.) The countries chosen for comparison in this case are two countries in Asia, one in Europe, two in North America, and two in South America: Singapore, Japan, Portugal, the USA (where the Common Core State Standards (2010) are not national but are agreed on by most of the states), Mexico, Brazil, and Chile, from the viewpoint of their influences on Ibero-American countries. (The National Council of Teachers of Mathematics (NCTM) standards (published in 2000) and the Japanese and Singapore textbooks have been influential in Latin America. Additionally, Portugal was selected to be compared with Brazil). To distinguish between each country’s standard and the general standards described here, the national curriculum standards are just called the “program.” The comparison shows the differences in the programs for multiplication in these countries in relation to the sequence of the description and the way of explanation. The role of this chapter in Part I of this book is to provide the introductory questions that will be discussed in Chaps. 3, 4, 5, 6, and 7 to explain the features of the Japanese approach. (As is discussed in Chap. 1, the Japanese approach includes the Japanese curriculum, textbooks, and methods of teaching which can be used for designing classes, as has been explored in Chile (see (Estrella, Mena, Olfos, Lesson Study in Chile: a very promising but still uncertain path. In Quaresma, Winsløw, Clivaz, da Ponte, Ní Shúilleabháin, Takahashi (eds), Mathematics lesson study around the world: Theoretical and methodological issues. Cham: Springer, pp. 105–122, 2018). The comparison focuses on multiplication of whole numbers. In multiplication, all of these countries seem to have similar goals—namely, for their students to grasp the meaning of multiplication and develop fluency in calculation. However, are they the same? By using the newest editions of each country’s curriculum standards, comparisons are done on the basis of the manner of writing, with assigned grades for the range of numbers, meanings, expression, tables, and multidigit multiplication. The relationship with other specific content such as division, the use of calculators, the treatment of multiples, and mixed arithmetic operations are beyond the scope of this comparison. Those are mentioned only if there is a need to show diversity.
Block-Chain Based Incentive in Vehicular Ad Hoc Networks Using Credit Coin

Vehicular ad hoc networks (VANET) are otherwise called wise transportation frameworks. VANET guarantees auspicious and exact correspondences between vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) to improve street wellbeing and upgrade the productivity of traffic stream. Because of its open remote limit and high versatility, VANET is powerless against pernicious hubs that could get entrance into the system and do genuine medium access control (MAC) layer dangers, for example, denial of service attacks, information alteration attacks, pantomime attacks, Sybil attacks, and replay attacks. With the prevalence of Block Chain comes grave security related concerns. Accomplishing security and discernibility at the same time stays an open inquiry. Endeavors have been made to address the issues, while they may expose to explicit situations. We propose a vehicular declaration convention Echo-Announcement in Credit Coin. It accomplishes productivity and protection safeguarding for the useful use in sending declarations. We plan an impetus component dependent on Block chain in Credit Coin. Clients oversee notoriety focuses while they acquire or spend coins as motivating forces. In the interim, Credit Coin despite everything jam security and accomplishes obscurity. Besides, in view of Block chain, Credit Coin forestalls numerous security attacks and accomplishes contingent protection since Trace administrator will follow malignant hubs when a startling occasion happens.
Placer Gold Deposits

Placer gold deposits are abundant in Mongolia and form through endogenic and exogenic processes. Deposits are classified into four major genetic types: (1) eluvial-weathering zone, (2) deluvial, (3) proluvial, and (4) alluvial. The most economic deposits are often sourced from upper Cretaceous rocks and formed in late Cenozoic alluvial fans (Liskun and Badamgarav, Kaynozoyskaya litologiya Mongolii (Cenozoic lithology of Mongolia). In: Proceedings of Joint Russian-Mongolian Geological Expedition. Nauka, p 160; 1977). Carboniferous, upper Permian, upper Jurassic, and lower to upper Cretaceous conglomeratic successions also act as an intermediate supply. Distribution of these deposits is reflected in comprehensive geomorphological studies and follows mountainous regions of Altai, Khangai, and Khentii ranges of Mongolia. Surrounding these mountains, proluvial-alluvial type placer gold deposits are formed and change to more proluvial type in dry and hot climate. In terms of primary gold mineralization zones, Mongolian territory is divided into (1) Khangai- Khentii, (2) Altai, (3) Gobi, Southern Mongolia, and (4) Eastern Tenger mountain zones. Representative primary gold mineralization types are gold-quartz, gold-quartz sulfide, gold-skarn, and gold-silver.
Analysis of Single-Agent Game: Case Study using Minesweeper

Minesweeper is a popular single-agent puzzle video game with simple rules to play. Despite previous works that explored the complexity of the game and solving the games, limited works had been conducted to determine the reasons for its popularity and the underlying mechanisms for its entertainment values. This study is a unique take on the minesweeper game where the minesweeper attractiveness is investigated using the game refinement theory, which through the game progress model and success rate of the minesweeper game, the measures of motion in mind are derived. Such a measure has been applied to various configurations of the game, where the possible number of mines that maximizes different playing requirement of the player can be determined.
Image Classification Schemes Based on Gradient Matrix and Contrast Matrices

Abstract Texture classification and categorizing are used in various pattern recognition applications and classification texture that possesses a characteristic appearance. This work aims to provide an improved scheme of enhanced classification decision with the need to increase the precision time significantly. This research studied the discriminating characteristics of textures by extracting the feature from gradient matrix (GM), the features were extracted using the first-order gradient feature vector, three Gradient Matrices were established, one for Max value, another for Min value and last was the Average value, these matrices were calculated by extracting the gradient along x-axis and y-axis and the gradient along the diagonal. A feature vector consist of 210 features was calculated to represent each image sample and contrast matrix CM, The feature extracted from CM1 was The difference between the sum of the neighborhood values of 3x3 pixels those larger than the pixel values (center pixels) divided by their number and the sum of the neighborhoods values of 3x3 pixels those smaller than the pixel value divided by their number total feature vector was 210, Four types of Euclidean distance metrics were used for classification decision purposes. The concepts “average” and “standard deviation” were calculated to perform the interentra scatter analysis for each feature to find out the best discriminating features that can be used. The final result of the test set of GM is 98.3 while training set was 97.3, the final result of the test set of CM is 98.2 while training set was 95.7.
AI development and application of AI-based solutions in the area of information and data management in Poland

The intensity of cyberattacks aimed at information resources of Polish organisations is growing. Polish entrepreneurs are concerned about hacking attacks and cybercrime prevalent in the contemporary digital world. Tools traditionally applied in the cybersecurity area are becoming insufficient in ensuring protection against ever more sophisticated types of cyberattacks. Therefore, it seems reasonable to search for new solutions that can support organisations in combating cyberthreats. One of them can be application of Artificial Intelligence (AI) in the domain of information and data management in Polish organisations. These solutions offer new capacities that can be successfully utilised for the benefit of organisations that wish to secure themselves against growing occurrences of cyberattacks. Yet, the knowledge of Polish organisations pertaining to possibility of applying AI in the cybersecurity area is relatively low. This needs to be changed as the application of AI in this domain is no longer an option but a necessity.
Optimization on Malaria Computer Aided Diagnostic System

Malaria is infectious tropical disease found in tropical countries, caused by unicellular protozoan parasite. Microscopic based diagnosis of malaria is conducted by manually examining a thin blood smear that is acquired from the infected patients. This method requires a trained human interaction and therefore it is time consuming and prone to errors. Computer Aided Diagnostics (CAD) for Malaria was developed to speed up the diagnosis and maintaining the accuracy. The experimental results showed that the system is able to recognize the infected red blood cells, the species and the life phase of the infecting Plasmodium. However, the average runtime of the detection using the original version is 41.45 seconds per image, which is too long if it will be used in the field. By measuring the runtime of each process in the program, optimization can be done by re-writing or substituting the algorithm that causes the longest runtime. Four modifications are proposed: Connected Component Labelling with Bounding Box, Contour Tracing Labelling without Inner Contour Extraction, Downscaled Clump Splitting, and Concave Point Based Clump Splitting. The experimental results showed that the system has an average runtime of 1.73 seconds while maintaining the same level of accuracy compared to the original one.
Imprint-Based Input Techniques for Touch-Based Mobile Devices

Touchscreens translate touches of all kinds into 2D coordinates. This limits the input vocabulary and constrains effective interaction to touches by the fingertip. Previous tabletop research extended the input vocabulary with a myriad of promising input techniques using the shape of fingers and hands. However, these techniques are not applicable to mobile devices due to differences in size, ergonomics, and technology. We conducted ideation sessions (N=17) to explore novel input techniques and use cases for imprint-based touch sensing on mobile devices. As a case study, we present FlexionTouch, a novel input technique that recognizes the finger flexion on a touchscreen. Using the finger flexion as an additional input dimension, FlexionTouch provides an always-available shortcut and can be used for value inputs, document previews, and gestures. We propose five example use cases for FlexionTouch input which we evaluated in a second user study (N=20). While the low resolution of the capacitive images leads to a less accurate input compared to tabletops, participants still find the presented use cases helpful. As our input technique is purely software-based, it can be readily deployed to every mobile device with a capacitive touchscreen.
LP2PB: Translating Answer Set Programs into Pseudo-Boolean Theories.

Answer set programming (ASP) is a well-established knowledge representation formalism. Most ASP solvers are based on (extensions of) technology from Boolean satisfiability solving. While these solvers have shown to be very successful in many practical applications, their strength is limited by their underlying proof system, resolution. In this paper, we present a new tool LP2PB that translates ASP programs into pseudo-Boolean theories, for which solvers based on the (stronger) cutting plane proof system exist. We evaluate our tool, and the potential of cutting-plane-based solving for ASP on traditional ASP benchmarks as well as benchmarks from pseudo-Boolean solving. Our results are mixed: overall, traditional ASP solvers still outperform our translational approach, but several benchmark families are identified where the balance shifts the other way, thereby suggesting that further investigation into a stronger proof system for ASP is valuable.
Distributed Dimensionality Reduction Fusion Estimation: An H∞ Approach

This paper is concerned with the distributed H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> fusion estimation problem with unknown statistical property of system noise from the stochastic dimensionality reduction strategy (SDRS). A stability condition to determine effective selection probabilities of the SDRS is derived. Then, the design of optimal weighting fusion criterion is converted into a convex optimization problem, which can be solved by standard software packages. Target tracking system is given to show the advantages and effectiveness of the proposed method.
Learning Target‐Adaptive Correlation Filters for Visual Tracking

Abstract Correlation filters (CF) achieve excellent performance in visual tracking but suffer from undesired boundary effects. A significant amount of approaches focus on enlarging search regions to make up for this shortcoming. However, this introduces excessive background noises and misleads the filter into learning from the ambiguous information. In this paper, we propose a novel target‐adaptive correlation filter (TACF) that incorporates context and spatial‐temporal regularizations into the CF framework, thus learning a more robust appearance model in the case of large appearance variations. Besides, it can be effectively optimized via the alternating direction method of multipliers(ADMM), thus achieving a global optimal solution. Finally, an adaptive updating strategy is presented to discriminate the unreliable samples and alleviate the contamination of these training samples. Extensive evaluations on OTB‐2013, OTB‐2015, VOT‐2016, VOT‐2017 and TC‐128 datasets demonstrate that our TACF is very promising for various challenging scenarios compared with several state‐of‐the‐art trackers, with real‐time performance of 20 frames per second(fps).
Design and Implementation of Digital Content Resource Registration Service System

In response to the current rampant piracy of Internet criminals and the difficulty of protecting the rights of contents authors, with reference to the existing copyright protection systems or platforms, a set of digital content resource registration and service systems have been designed and implemented. It mainly includes modules such as registration management, user management, content management, identification code management, tool management, and information push. Users can register different types of digital works metadata on the system, including but not limited to video, audio, image and other types. After user registration and system review, the system will produce and distribute copyright identification codes based on the work metadata and platform information to be released. The user can use the local tool provided by the system to load the identification code into the work, or use the tool to parse the identification code from the work. Users can use the parsed identification code as evidence for rights protection.
Entanglement Flowing, Freezing, and Thawing in a Two-Reservoir Spin System

We examine entanglement dynamical flow among all participants of a two-reservoir spin system. “Freezing” and “thawing” phenomena are identified. A set of novel entanglement constraint inequalities is discovered with tetrahedron representation.
Synthesis of parameterized families of correctly functioning sigma-pi neurons

Abstract The ΣΠ-neuron is a biologically inspired formal model for logical information processing. The ΣΠ-neuron model adequately reflects information processing processes in the cerebral cortex and in the dendritic trees of neurons. The advantage of the ΣΠ-neuron model is the ability to accurately represent any Boolean function and the possibility of constructive learning (direct construction) in a single pass of the training sample. Another possibility is the direct construction of an ensemble of ΣΠ-neurons that function correctly on the training sample. This article discusses a new algorithm for constructing such ensemble of ΣΠ-neurons in parameterized form. This form can also be easily represented as a single ΣΠ-neuron with a hidden layer of linear and threshold linear units. In some cases, this makes it easier to retrain on new inputs by setting the appropriate control parameter values.
The Comparative Study on Underlying Features of PainingTang-ka Images and Natural Images

Abstract Our purpose was to find the difference between the color features and texture features of natural images and painted Tang-ka images. Taking natural images as a reference, painted one were analyzed in HSV color space. The natural image and painted Thang-ga texture features were extracted, using the Tamura’s method. The data showed that the natural image’s coarse was larger than the painted Tang-ka, and painted Tang-ka were more saturated than natural images. Compared with natural images, the painted Tang-ka’s directonality has higher value. By contrast, the red Tang-ka had a higher value than the golden one.
A tracker selection model for augmented reality applications

Performance degradation When running augmented reality applications in wearable platforms can be greater than expected, as desktop and mobile platforms present different levels of hardware capabilities, and consequently, different performance restrictions. This work addresses the object tracking problem using a decision model that prioritizes using the least computationally intensive algorithm whenever possible. This could be achieved by analyzing different metrics regarding image interference such as occlusion and image noise. The OTS (Object Tracking SWitcher) model allows automatic switching of different trackers to balance application's performance without compromising its tracking quality. It was validated by synthetic case studies that comprise different object classes that can be tracked, focusing on augmented reality applications that can run on restricted platforms. It was possible to reach a performance improvement of a factor of three, While keeping a minimum quality defined by a reprojection error of 10 pixels when compared to the use of only the best algorithm independent of its computational cost.
Application of Saliency Methods for Extracting Tree Features in Outdoor Scenes

The growing demand for accurate results in agricultural environments consolidates the so-called precision agriculture in which saliency analysis has brought possibilities for the effective application of computer vision techniques. The saliency measured by computer algorithms follows a logic of attention similar to the human visual system in which the protuberant regions are identified due to some features that make them more evident and prone to draw more attention. Thus, the salient features are preserved in such a way that the most evocative scene components are highlighted to emphasize the relevant areas. In this paper, we present a saliency map refinement approach, and we use it to compare saliency estimation methods in the detection of trees. Their performance is evaluated by counting the number of areas correctly detected and labeled as a tree, as well as the segments incorrectly categorized as a tree. We present and discuss the results to point out the salience method that best corresponds to the refinement approach we propose. Fourteen saliency methods are compared using an annotated database of manually segmented images that were collected in different scenarios where trees are emphasized in the foreground.