Reviewerly/exHarmony huggingface dataset:
Multi-path Feature Mining Network for Stereo Matching

Many existing networks for disparity estimation have attained satisfactory performance, but it still is a challenge to gain high-quality disparities for the inherently ill-posed regions and improve detail in disparity map. To tackle this problem, we propose a Multi-path Feature Mining Network(MFMNet), which contains two sub-networks: initial disparity estimation network and disparity refinement network. Specially, to generate high-quality disparity with rich detail, we specially design a initial disparity estimation network with multi-scale feature fusion and richer feature extraction module to capture context information and gain more reliable features. Furthermore, we propose a disparity refinement network with atrous spatial pyramid pooling to enhance disparity refinement performance. In this work, we adopt one-dimension single direction(1SD) correlation to calculate matching cost rather than the 1D correlation used widely. During training, we adopt a novel loss function strategy to perform online hard point mining, which enhance the overall network performance. Experimentation shows that our multi-path feature mining network provides state-of-the-art performance on FlyingThings3D and KITTI datasets.
Signature analysis system using a convolutional neural network

Identity verification using biometric methods has been used for many years.A special case is a handwritten signature made on a digital device or piece of paper.For the digital analysis and verification of its authenticity, special methods are needed.Unfortunately, this is a rather complicated task that quite often requires complex processing techniques.In this paper, we propose a system of signatures verification consisting of two stages.In the first one, a signature pattern is created.Thanks to this, the first attempt to verify identity takes place.In the case of approval, the second stage is followed by the processing of a graphic sample containing a signature by the convolutional neural network.The proposed technique has been described, tested and discussed due to its practical use.
Equívocos e efeitos da memória no âmbito de atuação do bibliotecário: reflexões sob o viés da política de desenvolvimento de coleções

To discuss the mistakes and aspects of memory, in order to solve theoretical problems and, therefore, practical problems of the same in the work of the librarian. The methodological procedure adopted is the bibliographic review using the elementary qualities to the field of Social Memory in consonance with its application in a hypothetical case study, justifiable due to the exploratory character and its applicability in several typologies of libraries or information units. Here are some misunderstandings that will be analyzed: The reductionism of the field of Social Memory, the rescue of memory, univocity, neutrality and the place of memory as a safeguard. Afterwards, it is necessary to reflect on the fundamental characteristics of memory (procedural construction, duration, polymorphism, intentionality, dichotomy) in the librarian's doing, specifically in the politics of collections development, for a discussion that fosters salutary practices and reduces misconceptions - or even objectifying devices - in the workplace. In addition, the field of Social Memory is interdisciplinary, but with the intention of promoting transdisciplinary discussions, which reinforces the need to think about the librarian's performance beyond the usual tools and practices within his field of training, because if the focus of this professional is the user, so it is necessary to adapt the demands of the social body. It is concluded that the discussion of the conceptual tools of the Social Memory field, applied to the librarian's role, are key elements in the review and strengthening of policies, as well as strengthening the library's mission and vision. In short, memory is action..
Fusion of Localization Estimates in Multistatic Passive Radar

In multistatic passive radar, target location estimates from both multilateration and array-based localization methods would be available. Based on insights from the comparative analysis of the methods as a function of geometry, a method of selecting the best target location estimate is proposed. The Kalman filter is used to fuse the localization estimates. Experimental verification is achieved using data collected from a target that was simultaneously detected using three different illuminators of opportunity. The filtered estimates have an accuracy within 100 m for a target at a receiver range of 6 km.
RANCANG BANGUN “TELEGRAM BOT API” UNTUK LAYANAN SISTEM INFORMASI AKADEMIK DI UNWAHA MENGGUNAKAN METODE LONG POLLING

Today, the information system needs are not limited to the importance of the information, but the ease and speed of getting the information is a priority that must be fulfilled. This makes many instant messaging applications appear. One of them is a telegram that has features the BOT telegram API, which is a special protocol for connecting information from a system to a user through Instant Messaging. &#x0D; In this research, the researcher used BOT features of the instant messaging application for Academic Information system at KH. A Wahab Hasbullah University includes data KHS, KRS, information dissemination, transcripts of the score, lecture schedules and others. This research used the Long Polling method. This method is used because it can be implemented on a local PC server that is owned by KH. A Wahab Hasbullah University. This telegram BOT has a better speed compared to conventional web versions, this speed testing is done in two steps. First, Use of a BOT of this Telegram has better speeds compared to conventional web version, this speed test is carried out by two steps, 1) the result of BOT telegram using 512 kb Bandwidth with average is 2.98 seconds, conventional web is 5.39 seconds; 2) the result of BOT Telegram using 1 MB bandwidth with average is 2.44 seconds, conventional web is 3.15 seconds.
Massive Ship Fault Data Retrieval Algorithm Supporting Complex Query in Cloud Computing

Lou, H., 2019. Massive ship fault data retrieval algorithm supporting complex query in cloud computing. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 1013–1018. Coconut Creek (Florida), ISSN 0749-0208.Aiming at the problems of the current retrieval algorithm for massive ship fault data retrieval in cloud computing, which does not support complex query, large retrieval cost and low precision, a massive ship fault data retrieval algorithm supporting complex query in cloud computing based on query performance prediction is proposed. Introducing the Lagrangian algorithm to preprocess the ship fault data information; combining the attribute values of the ship fault data and the context to calculate the similarity between different attributes, and identifying the same attribute according to the similarity; The attribute recognition result is queried by using multiple retrieval models, and the model complex query request is converted into a one-dimensional query key value, and the query key values obtained by the plurality of models are predicted, and the search result with the optimal prediction performance of the complex query mode is used as the final result. The experimental results show that the proposed algorithm has good retrieval accuracy in complex query mode, and it has less overhead than the current search algorithm.
Trajectory Control by Binocular Visual Space Based Visual Servo Using Image Teaching

Trajectory control is important in terms of safety and efficiency．Direct teaching of joint angle can be cited as one of trajectory control．However, this method requires re-teaching when there is a change in the position of the work target．On the other hand, since the proposed method controls the trajectory by changing the image, there is an advantage that it is unnecessary to re-teaching even in such a case．The effectiveness of the proposed method is shown by simulation．
On the Impact of Bad Smell Agglomerations on Software Quality

When a system evolution is not planned, developers can take decisions that degrade the system quality. To cope with this problem, refactoring can be applied to the source code aiming to increase code quality without modifying the software external behavior. To know when to refactor, the concept of bad smells can be used. Bad smells are snippets of source code that suggest the need of refactoring. However, bad smells does not always appear isolated. The aim of this study is to understand the impact of bad smell agglomerations on the software quality by evaluating a large dataset of open source systems. To achieve our goal, we plan to use data mining techniques complemented with correlation analysis of the dataset.
Review of Handbook of Graph Theory, Combinatorial Optimization, and Algorithms

Some (admittedly controversial) models of physical reality propose that it is, at the fundamental level, based on a certain type of graph, called a spin-network (and this among other models of physical reality based on graphs). Recently, astronomers have verified that the otherwise empty reaches of intergalactic space are laced with wispy tendrils of hot gas that connect galaxies. On a more quotidian level, the machine on which I'm typing this document is constructed out of components that are essentially graphs, those components being connected by electrical edges forming an even larger graph, and this one device in turn being connected via various links to millions of other nodes in a huge global graph called the internet. The notion of a graph encompasses all levels of reality, from the subatomic through everyday life and reaching out to the cosmological scale.
Digital Voting Systems Deploying the use of Blockchain Technology

Blockchain is a list of records called blocks which are linked through the use of cryptography.Each block contains a cryptographic hash of the previous block, a timestamp and transaction data.A summary of the all transactions are kept in a mekle tree root hash and stored as part of the header of a block.By design blockchain is highly resistant to modification of data.The case study uses blockchain technology to deploy a digital voting system and tries to provide a more decentralized approach to digital voting
Implementation of Open Science in Lithuania

The number of open science policies being adopted in Europe by universities and research institutions is constantly increasing, however many European countries face difficulties while implementing open science practically. This publication reveals the Lithuanian landscape of open science policies and institutional involvement in open science practices. Prerequisites for sustainable and consistent open science implementation such as open science infrastructure, incentives for researchers, research assessment, and repositories' compliance with EC requirements on a national level are discussed.
Evaluating Saudi University Students’ English Writing Skills Using an Analytic Rating Scale

The purpose of this study was to investigate the extent to which Saudi university students master the main aspects of ESL Composition Profile proposed by Jacobs et al. (1981). The study also aims at analyzing Saudi English-majors students’ text length features and examining whether they are associated with their text quality aspects. It analysed the essays written by 88 students studying English language at Prince Sattam bin Abdulaziz University in Al-Kharj and Al-Imam Muhammad bin Saud Islamic University in Riyadh. The study yielded a number of results. The most important of which is that Saudi students can produce essays of analytic quality features at a level that ranging from poor to fair. A positive correlation was also found between text length and writing quality aspects in the students' essays. Based on these findings, the researcher provided a number of pedagogical implications and some suggestions for further research were provided.
A Concept of Captcha Based Dynamic Password

Background: The conventional text passwords are by far the main means of authentication and they will continue to be popular as they are easy to deploy and to use. However, they have been largely exposed to different kind of attacks like guessing, phishing and key-logger attacks. Objective: It is efficient to use both CAPTCHA and text password in a user authentication to create an additional layer of security over the passwords. Captcha and password work side by side and independently in such captcha-assisted systems. Captcha filters out the suspicious programs from the human beings and password recognizes the legitimate user among the human beings. Method: In this paper, we have suggested a dynamic password scheme combining the traditional text password and captcha. User authentication will be verified by different passwords at different login session based on the captcha presentations. Results: Suggested method does not replace the conventional password process rather than modifying it. Therefore, users’ current sign-in experience is largely preserved. It will be implemented in software alone, increasing the potential for large-scale adoption on the Internet. Conclusion: The scheme is easy to implement and will be useful to improve the security to a great extent.
A Tool for Building Multi-purpose and Multi-pose Synthetic Data Sets

Modern computer vision methods typically require expensive data acquisition and accurate manual labeling. In this work, we instead leverage the recent progress in computer graphics to propose a novel approach of designing and generating large scale multi-purpose image data sets from 3D object models directly, captured from multiple categorized camera viewpoints and controlled environmental conditions. The set of rendered images provide data for geometric computer vision problems such as depth estimation, camera pose estimation, 3D box estimation, 3D reconstruction, camera calibration, and also pixel-perfect ground truth for scene understanding problems, such as: semantic and instance segmentation, object detection, just to cite a few. In this paper, we also survey the most well-known synthetic data sets used in computer vision tasks, pointing out the relevance of rendering images for training deep neural networks. When compared to similar tools, our generator contains a wide set of features easy to extend, besides allowing for building sets of images in the MSCOCO format, so ready for deep learning works. To the best of our knowledge, the proposed tool is the first one to generate large-scale, multi-pose, synthetic data sets automatically, allowing for training and evaluation of supervised methods for all of the covered features.
On the Robustness of Noisy ACE Algorithm and Multi-Layer Residual Learning

In this paper, we address the issue of computing the maximal correlation functions for jointly distributed high-dimensional random variables. In such cases, the operations in the alternative conditional expectation (ACE) algorithm can only be implemented by an approximated manner, which is modeled as a variational ACE algorithm with noise. We study the computational behaviors of this algorithm, where the optimal tradeoff between the learning rate, computation accuracy, and convergence rate is investigated. In addition, we establish a connection between the variational ACE algorithm and the residual learning architecture. Our results illustrate interesting interpretations of how multi-layer residual structure benefits function learning.
POSE ESTIMATION FOR SKELETON DETECTION

This thesis is based on efficiently detecting the joints and coordinates of the person and limbs are highlighted with color dots and connecting them with drawn lines.The architecture will give briefs about activation functions and GPUs available on the used interfacing platform.Activation Rectified linear unit which used for computer vision to find body joint coordinates.This method uses COCO model for key points challenge and method works for all static image given to the process.
Practical Fall Detection Algorithm based on Adaboost

In order to improve the accuracy and efficiency of the fall detection, we proposed a fall detection algorithm based on Adaboost with single-layer decision tree under six-axis acceleration (three-axis acceleration, three-axis angular acceleration) time features. We set two thresholds for the resultant linear acceleration. When the value of the resultant linear acceleration is within these two thresholds, the algorithm of fall detection classifier is triggered. The fixed window is used to intercept the time waveform of the six-axis acceleration and extract the time features. We selected seven features with less computational complexity, and finally used these seven features to construct a fall detection model based on Adaboost with single-layer decision tree. Our algorithm can achieve 99.08% accuracy in the data set collected by ourselves, and has high specificity and sensitivity. The most critical point is that the algorithm proposed in this paper has a small computational cost and can be transplanted onto the embedded system, which is a practical and reliability fall detection method.
On the Geometric Realisation of Equal Tempered Music

Since the time of Pythagoras (c.550BC), mathematicians interested in music have asked, “What governs the whole number ratios that emerge from derivations of the harmonic series?” Simon Stevin (1548-1620) devised a mathematical underlay (where a semitone equals 21/12) that gave rise to the equal temperament tuning system we still use today. Beyond this, the structure of formalised musical orderings have eluded many of us. Music theorists use the tools and techniques of their trade to peer into the higher-order musical structures that underpin musical harmony. These methods of investigating music theory and harmony are difficult to learn (and teach), as complex abstract thought is required to imagine the components of a phenomenon that cannot be seen. This paper outlines a method to understanding the mathematical underpinnings of the equal tempered tuning system. Using this method, musical structure can be quantitatively modelled as a series of harmonic elements at each pulse of musical time.
Polyphonic overtone singing: An acoustic and physiological (MRI) analysis and a first-person description of a unique mode of singing

This paper describes a unique singing mode, tentatively labeled “polyphonic overtone singing”. In overtone singingthe vocal harmonics of a stabile fundamental frequency are filtered by the singer i ...
Restart Operator for Optimization Heuristics in Solving Linear Dynamical System Parameter Identification Problem

In this study, the parameter identification problem for linear dynamical systems is considered. The system is assumed to be represented as a linear differential equation in general form, so the right-hand side equation contains input function and its derivatives. This problem statement extends the order reduction problem, where we need to find the equation of the lower order to approximate the real system output observations. Considered problem is reduced to an optimization one. The reduced problem is complex, and we propose the combination of stochastic optimization algorithm and restart operator. This operator aim is to prevent the algorithm stagnation by starting the search over again if no remarkable solution improvement is detected or if algorithm searches in the area where stagnation had been detected.
Cost and Effect of Using Scheduling Security Model in a Cloud Environment

Resource scheduling is concerned with selecting the most appropriate resources to meet the needs of consumers. This is a complex task in Cloud Computing because of the large amount of available resources such as applications and data storage facilities. This is compounded further when security issues and quality of service are also factored in. A Scheduling Security Model (SSM) for Cloud Computing has been developed to address these issues. This paper will apply the SSM model on some examples with different scenarios to investigate the cost and the effect on the service requested by customers.
On the Succinctness of Atoms of Dependency

Propositional team logic is the propositional analog to first-order teamlogic. Non-classical atoms of dependence, independence, inclusion, exclusionand anonymity can be expressed in it, but for all atoms except dependence onlyexponential translations are known. In this paper, we systematically comparetheir succinctness in the existential fragment, where the splitting disjunctiononly occurs positively, and in full propositional team logic with unrestrictednegation. By introducing a variant of the Ehrenfeucht-Fra\{i}ss\'{e} gamecalled formula size game into team logic, we obtain exponential lower bounds inthe existential fragment for all atoms. In the full fragment, we presentpolynomial upper bounds also for all atoms.
THE INFLUENCE OF USE AUDIO VISUAL MEDIA TO INCREASE THE DEVELOPMENT OF EARLY CHILDHOOD LANGUAGE

The problem in this research is the development of early childhood language that has not been expected. The research aim to determine the influence of use audio visual media to increase the development of early childhood language. The research methods used are experimental methods with pre-experimental design. The samples in this research were children aged 5-6 years, amounting to 41 children. The data collection techniques used are observations. Analysis of data in this research using simple linier regression tests. The results showed that there was a significant influence on the use of audio visual media against early childhood language skills. This means that the use of audio visual media in the learning process in early childhood can help to increase the development of early childhood language. Thus, the role of teacher is expected in the use of audio visual media to increase the development of early childhood language.
PENGEMBANGAN MEDIA PAPAN FLANEL UNTUK MEMFASILITASI KEMAMPUAN KONSEP BILANGAN ANAK PADA KELOMPOK B

Learning media are the most important part of implementing school learning. A preliminary study in group B of the Cendrawasih I Kindergarten and TK Cendrawasih II found that the use of learning media was used when needed. More practical media used aremarkers whiteboard and blackboardand magazines to convey information related to the concept of numbers. Whereas for early childhood more media is needed which can be used directly to practice concentration and provide new experiences for children. The results of identification and analysis of the problem, researchers followed up by designing flannel board media as a solution in facilitating the ability of the concept of child numbers in group B. In this study using the method of Design Based Research (DBR) developed by Reeves to design, develop, and test feasibility a product to overcome problems in learning. The product is designed using the main ingredients of brown duplex and flannel cloth. The research subjects were teachers and children in group B of Cendrawasih I Kindergarten and TK Cendrawasih II. Data collection is done by interviews, expert validation, teacher assessment, observation of child treatment during product use, and documentation. The product design was declared feasible by the expert validator, then revised according to suggestions and carried out the implementation of the school where the research was conducted. Product implementation was carried out in group B of Cendrawasih I Kindergarten and Group B of TK Cendrawasih II. In general, the product is declared feasible to be used as a learning medium about the concept of numbers based on the teacher's assessment and observations of the child's treatment of the product. Reflections on product development, namely to produce flannel board media to facilitate the ability to conceptualize child numbers in group B.