Reviewerly/exHarmony huggingface dataset:
On the Emergence of Biologically-Plausible Representation in Recurrent Neural Networks for Navigation

Biologically plausible representations have been found to emerge in particular recurrent neural networks when training on path-integration [1, 2]. This report explores factors influencing the occurrence of entorhinal-like representations in recurrent neural networks. Reproducing simplified models from existing studies and created a hybrid model to explore additional factors, including the input features, structural properties, and regularization techniques in recurrent neural networks. Additional experiments evaluate the difference in training performance when entorhinal-like representations are introduced to a recurrent neural network. This report also assesses existing and experimental visualization techniques in their ability to visualize the performance and representation of recurrent neurons. While some experiments show specialized representations, mostly due to regularization; none of the experiments showed typical entorhinal-like representation. These results show how sensitive the emergence of biologically-plausible representations is to network conditions and training procedure, casting some doubt on the generality of the conclusions proposed in earlier work.
Improved strategies for distance based clustering of objects on subsets of attributes in high-dimensional data

This monograph focuses on clustering of objects in high-dimensional data, given the restriction that the objects do not cluster on all the attributes, not even on a single subset of attributes, but often on different subsets of attributes in the data. With the objective to reveal such a clustering structure, Friedman and Meulman (2004) proposed a framework and a specific algorithm, called COSA. In this monograph we propose various improvements to the original COSA algorithm. The first improvement targets the optimization strategy for the tuning parameters in COSA. Further, a reformulation of the COSA criterion brings down the number of tuning parameters from two to one, enables incorporation of pre-specified initial weights for the attribute distances and allows for a solution that consists of zero-valued attribute weights. The third improvement consists of a new definition of the COSA distances that yields a better separation between objects from different clusters. We compared the `old' and the improved COSA with other state of the art methods. The comparison is based on simulated and real omics data sets.
Yaşsanmışs önemli yazılım hatalarının incelenmesi ve kritik öneriler

The importance and indispensability of technology in human life is increasing day by day and software systems take place in every area of our lives. The variety of errors and error rate in the software system that we use in many areas of our daily lives provide information about the quality criteria of the software. The minimum error rate in the software modules is one of the many factors that indicate that the software is of good quality. In this paper, the types and types of software errors are examined and the errors that have great risk potential in history are examined. However, taking into account the frequently encountered errors today, critical recommendations have been made for software developers.
Semantic Service Technologies for Industrial Fault Analysis IoT

This paper presents an industrial fault analysis Internet of Things (IoT) system adopting the semantic service paradigm. Industrial vibration fault analysis becomes increasingly useful for economical and safety reasons. The architecture of vibration fault analysis IoT consists of enterprise level, gateway level and endpoint level where various vibration detection services are integrated. Semantic service involves the collection, representation and processing of relevant information of devices and data was developed. Data processing schemes and services are proposed quantifying the criteria of fault evaluation, and the relevant ontology was designed. Testing results show the effectiveness of the proposed approach and system design in increasing the flexibility and accuracy of real-time industrial vibration fault analysis.
The Design of the University Electronic Currency System Using Blockchain-Based Technology

The local currencies of South Korea were first adopted in 1997 after the economic crisis as a method to vitalize the local economy; subsequently, the currencies showed a movement.However, these local currencies have reached their operation limits owing to limited local market size and unguaranteed continuity of investment, and yet, they still exist.Meanwhile, overseas cases, namely the European Regional Development Fund (ERDP) in the European Union, SoNates in France, Bristol Pound in Bristol in the UK, Silvio Gegell in Austria, and WIR in Switzerland have stably settled as independent local currencies to promote local economy and prevent the outflow of capital and WIR in Switzerland has over 80 years of history, and it stands as an excellent example of an independent local currency that has been established to prevent the outflow of capital from a country.A characteristic of local electronic currencies such as Zeropay, Gimpopay, and Nowon Cash, which have recently become well-known, is that they are produced and used as blockchainbased local currencies in only certain regions.In the system proposed here, when transactions are initiated, multiple proof-of-transaction servers (nodes) coordinate to verify the data, which are in turn saved in the blocks of each server and ultimately saved into the blockchain database.In the blockchain database, only the transaction history verified by blockchain nodes in the network can be modified.The blockchain database used for this process is configured using one of the proofof-transaction servers in the network installed in advance.This study designed a blockchain-based in-house electronic currency that can be used at an organization only.
Object segmentation by Oriented Image Foresting Transform with connectivity constraints

Global properties, such as connectivity, shape constraints and boundary polarity, are useful high-level priors for image segmentation, allowing its customization for a given target object. In this work, we introduce a new method called Connected Oriented Image Foresting Transform (COIFT), which provides global optimum solutions according to a graph-cut measure, subject to the connectivity constraint in Oriented Image Foresting Transform (OIFT), ensuring the generation of connected objects, as well as allowing the simultaneous control of the boundary polarity. While the use of connectivity constraints in other frameworks, such as in the min-cut/max-flow algorithm, leads to an NP-Hard problem, COIFT conserves the low complexity of the OIFT algorithm. Experiments show that COIFT can considerably improve the segmentation of objects with thin and elongated parts, for the same number of seeds in segmentation based on markers.
Exploring the Relationship Between Academicians via Reference Parsing

Although the citation number is significant for a paper, it is important to determine the value of citation with the information of the citations' owner and their value for revealing the value of the citations. Our study proposes a method for parsing the reference sections of an academic publications. It will provide a graphical representation of the relationships of the people who give and cite the resulting shredding works in a weighted directional graph. Sobiad Citation Index and TUBİTAK Dergipark and ULAKBIM TRDizin were used as the data set. The proposed method was found to be successful and result show in the graphs and experimental results.
AnnaParser: Semantic Parsing for Tabular Data Analysis

This paper presents a novel approach to translating natural language questions to SQL queries for given tables, which meets three requirements as a real-world data analysis application: cross-domain, multilingualism and enabling quick-start. Our proposed approach consists of: (1) a novel data abstraction step before the parser to make parsing table-agnosticism; (2) a set of semantic rules for parsing abstracted data-analysis questions to intermediate logic forms as tree derivations to reduce the search space; (3) a neural-based model as a local scoring function on a span-based semantic parser for structured optimization and efficient inference. Experiments show that our approach outperforms state-of-the-art algorithms on a large open benchmark dataset WikiSQL. We also achieve promising results on a small dataset for more complex queries in both English and Chinese, which demonstrates our language expansion and quick-start ability.
Infinite Gaussian Fisher Vector to Support Video-Based Human Action Recognition

Human Action Recognition (HAR) is a computer vision task that attempts to monitor, understand, and characterize humans in videos. Here, we introduce an extension to the conventional Fisher Vector encoding technique to support this task. The methodology, based on the Infinite Gaussian Mixture Model (IGMM) seeks to reveal a set of discriminant local spatio-temporal features for enabling the precise codification of visual information. Specifically, it is much simpler to handle the infinite limit from the IGMM, than working with traditional Gaussian Mixture Models (GMMs) with unknown sizes, that will require extensive cross-validation. Under this premise, we developed a fully automatic encoding methodology that avoids heuristically specifying the number of components in the mixture model. This parameter is known to greatly affect the recognition performance, and its inference with conventional methods implies a high computational burden. Moreover, the Markov Chain Monte Carlo implementation of the hierarchical IGMM effectively avoids local minima, which tend to plague mixtures trained by optimization-based methods. Attained results on the UCF50 and HMDB51 databases demonstrate that our proposal outperforms state of the art encoding approaches concerning the trade-off between recognition performance and computational complexity, as it drastically reduces both number of operations and memory requirements.
Det komplexa offerskapet: en litteraturstudie om stereotypiseringen av offer för människohandel för sexuella ändamål

The purpose of this qualitative secondary analysis is to study how victims of sex trafficking are illustrated in previous research. 16 peer reviewed articles have been analysed based on a hermeneutic approach. The results of previous research are consistent: The society has a narrow view of victims, and a more complex, intersectional understanding of the victimhood is required. The victims` stories (as they are presented in previous research) are not consistent with Nils Christie s conceptualization of the “ideal victim”. This often results in victims of trafficking having difficulties to be recognized (socially as well as legally) as victims. Dominant discourses, and a strong need to separate victims of trafficking from ‘illegal immigrants’, have resulted in problematic policies and difficulties in the investigation process. Multifaceted methods within the law enforcement are required. Furthermore, this paper aims to study how well the Sweden’s Supreme Court’s criteria for credibility assessment apply to, according to previous research, the victims of sex trafficking. The criteria are guidelines used to determine the credibility of a statement in court. The conclusion is that the criteria partly are influenced by the structures that constitute Christie s “ideal victim”. Therefore, it can be hard for victims of sex trafficking to meet the specified criteria. The result is that victims have difficulties to be acknowledged as victims in, among other social spaces, courts of law. This is problematic from an individual as well as legal perspective. (Less)
Implementasi Face Recognition Menggunakan Metode Haar-Cascade Classifier Untuk Sistem Keamanan Pintu

Abstrak Paper ini berisikan hasil uji coba implementasi system keamaan pintu berbasis teknologi dengan menggunakan Face Recognition dengan metode haar-cascade classifier dan notifikasi menggunakan aplikasi telegram yang diterapkan pada miniatur pintu dengan menggunakan Raspberry Pi 2 sebagai microcontroller utama. Dimana bila ingin membuka kunci selenoid wajah user harus terlebih dahulu didaftarkan kedalam dataset. Berdasarkan hasil uji coba yang telah dilakukan bahwa system dapat 100% membedakan wajah yang telah terdaftar pada dataset dengan wajah yang tidak terdaftar pada dataset. Kata kunci: Dataset, Face Recognition, PIN, Raspberry Pi 2. Abstract This paper contains the results of a trial of implementing a technology-based security system using Face Recognition with the haar-cascade classifier method and notifications using a telegram application that is applied to miniature doors using Raspberry Pi 2 as the main microcontroller. Where if you want to unlock the selenoid face the user must first be registered into the dataset. Based on the results of trials that have been done that the system can 100% distinguish faces that have been registered in the dataset with faces that are not registered in the dataset.
Studi Kelayakan Pembangkit Listrik Tenaga Mikrohidro di Bendung Kalisapi Banjarnegara

Kalisapi Dam is a weir that is used to keep the flow of the Serayu River. This dam is using for irrigation, fishery, and flood control. Kalisapi Dam can also be an alternative supply of electricity for new environmentally friendly energy sources, by utilizing the flow of the river to be PLTMH because it has enough and stable of headnett and water flow. PLTMH is a small-scale hydropower plant that uses hydropower as the activator, the higher the fall of water, the greater the potential energy of water that becomes electrical energy. The method used to set the water debit is using the floating method, google coordinate, and map coordinates. The floating method is used to set the water debit by calculating the width and depth of the river flow. While google coordinate used to set the height of the headnett, and map coordinates to set the highest point and lowest point of flow. Kalisapi Dam has a height 5 meters of headnett and the largest power produced is 349.63 KW.
The activity approach analysis on the research of mechanisms in adoption of social experience

The article is devoted to the analysis of the significance of the fundamental provisions of the activity approach in the study of the mechanisms of assimilation of social experience. The essence of the activity approach is revealed when considering any mental phenomenon and process in its formation and functioning through the prism of the category of activity. The basis of this approach is, of course, the general psychological theory of activity, and the approach itself is an application of this theory to the study and formation of mental processes and properties. The article shows the historical insight into the development of the activity approach and its significance for the process of assimilating the social experience of previous generations, which is possible due to the activity of the exercise, carried out in specially organized conditions. The modern approaches of psychological and pedagogical mechanisms for mastering social experience are considered, as well as from the position of the activity approach, the results of the author’s empirical research on the identification of the system of conditions for the successful updating of skills are reflected. Three components of its subsystem (group of conditions) are identified and the content of the main conditions in the composition of each of these groups is investigated: the process of assimilation; storage method; organization of “business” activity, contributing to the actualization of knowledge and skills. A model of science-based knowledge and skills training has been built, the success of which is due to the consideration of the psychological mechanisms of actualization.
Image Stitching Using Non-Extensive Statistics

Nowadays there are different ways to make image stitching with help of Fiducial Point Descriptors (FPD), whose find the matches between images for an application, such as SIFT and calculates the homography with RANSAC. However, by finding the right match when we have images on differents points of view could be difficult. This paper introduces the application of q-SFT, a newest variation of SFT in a stitch algorithm, that can recognize large viewpoint changes called as LVC.
Iterable Sequences with Generators and Iterators

Storing and manipulating data in collections in JavaScript is not only easy, but also elegant. However, iterating is another matter. Consider arrays. In order to iterate and fetch the elements of an array, we use contrived syntax like the for (let i = 0; i < array.length; i++) loop, or even worse, the for-in loop. But that’s not the end of it! Every so often we will have custom objects that might need iteration. We concede defeat, and build (or consume) a custom API (think array.forEach) just so we can get each element in a particular sequence.
Leg Telescopic Folding Table using Servomotors

The current population of disabled persons is not small, and all disabled persons have all sorts of obstacles in their lives, and there are many useful things to eliminate them. For example, there are convenient things such as automatic wheelchairs made for people who can’t move their legs, traffic lights with voice for people with disabilities, and automatic eating robots for people with disabilities. There are many useful things such as self-opening doors and electric bicycles for the elderly and the general public as well as physically disabled people. Under such circumstances, what other things are useful for disabled people and the elderly? In this research, servomotor, Arduino was used to make things useful for disabled people and the elderly
A Smart Living Framework: Towards Analyzing Security in Smart Rooms

Indoor environments play a main role on people living, work, social life, and health. Especially, recent statistics show that people who are often most susceptible to the adverse health effects tend to spend more time indoors. To overcome these issues, modern rooms are well equipped with different kind of connected objects (IoT) in order to facilitate the life of inhabitants and to manage better the indoor environment by automatically controlling the indoors problems (humidity, temperature, noise, light ...) with respect to the experts recommendations and inhabitants hopes. So, the quality of indoor living depends mainly on the environments properties, their precise measurements through IoT, and how safely manage and control them. In this context, we propose a smart living framework covering a global architecture of smart rooms and their related components (sensors, actuator, server $$\ldots $$ ), and also a management system for a secure communication network respecting the existing safety and security standards. Further, we present the appropriate semantics for each part of the framework in the form of state machines. Further, we ensure the functional correctness of the proposed framework by implementing the developed state machines in the validation and verification tool Uppaal, where it gives us a satisfactory result for different scenarios.
IMPLEMENTATION OF COVERING ALGORITHM FOR THE ROBOT WITH PARALLEL STRUCTURE

The quality and depth of content Web of Science offers to researchers, authors, publishers, and institutions sets it apart from other research databases. The inclusion of News of NAS RK. Series of geology and technical sciences in the Emerging Sources Citation Index demonstrates our dedication to providing the most relevant and influential content of geology and engineering sciences to our community.Қазақстан Республикасы Ұлттық ғылым академиясы "ҚР ҰҒА Хабарлары.Геология жəне техникалық ғылымдар сериясы" ғылыми журналының
Experiment Instructions for 'Investing in prevention or paying for recovery - attitudes to cyber risk'

Experiment Instructions for paper 'Investing in prevention or paying for recovery - attitudes to cyber risk' presented at GameSec 2019, Stockholm.
Effective Function Signatures with Default and Rest Parameters

We all realize the pervasive use of functions in JavaScript. Consequently, defining functions and laying out function signatures is one thing we do a lot. Default parameters, a new feature introduced in ES6, provide us the power to improve how we detail our function signatures. They allow us to specify what the value of a parameter to a function ought to be if no value is passed in at invocation time. Along the same vein, rest parameters allow us to express that a function (or method) has no expectation to the number of arguments you can supply it—in other words, they allow us to explicitly declare variadic functions.
THE INFLUENCE OF IPS LEARNING RESULTS OF CLASS IV SD STUDENTS USING THE SNOWBALL THROWING MODEL

Abstract :The problem in this study is the result of learning IPS students of grade IV SDN 03 Bandar Buat, Low Padang city. An alternative to solving the problem is to apply the Snowball Throwing model. This research aims to describe the design, implementation and learning outcomes of students of IPS class IV SD using the Snowball Throwing model. This type of research is classroom action research (CAR) with a qualitative and quantitative approach. The results of this study showed influence from the application of the Snowball Throwing model to the learning outcomes of IPS in grade IV students, namely on the average I cycle of learning outcomes of 60.7 students and increased in cycle II by an average of 85.7. Keywords: Learning Results, IPS, Snowball Throwing Model
유사 의미 변별을 위한 문법 텍스트 구성 방안

This study is about developing grammar text to help Korean learners. Studying intermediate course, Korean learners usually make many mistakes or...
Research on Hyper-Spectral Data Processing of Rock Minerals

The most successful areas of application of hyper-spectral technology are: mineral identification and mineral mapping. Spectral reflection information and radiation information of mineral species, abundance and composition can identify altered minerals and hydrothermal mineralized alteration zones closely related to mineralization, and quantitative or semi-quantitative estimation of eclipse by correlation analysis methods. Variable strength and altered mineral content. In this study, the field spectral acquisition experiments were carefully designed, the spectral data was collected strictly according to the experimental design, and the data processing was carried out. The field spectral characteristics of different types of rocks in the study area were tested, and the spectral data characteristics of the rocks were compared and analyzed
Supplemental Material to: Big Data and Digital Aesthetic, Arts and Cultural Education: Hot Spots of Current Quantitative Research

This research was supported by a grant from the Federal Ministry of Education and Research (01JKD1711) to Benjamin Jorissen and Stephan Kroner