Reviewerly/exHarmony huggingface dataset:
Methods for storing authentication data â€“ a historical review

Storing user credentials is a process which opens up a challenge in the information technologies. Researchers have always tried to maintain balance between usability and security. This paper aims to identify the different evolutionary steps through which user credentials have gone by. The methodology of this paper consists of content analysis of various scientific publications as well as hands-on experience by researchers in the field of cryptology and cryptanalysis. Several methods for storing authentication data are examined in chronological manner, beginning with first generation computers and latest trends in cryptanalysis. Various flaws of the examined methods are pointed out and solutions in the form of new methods are adopted by the industry. In this historical review it is concluded that with the continuous technological advances any algorithm for storing authentication data might eventually prove insecure.
Application and research of soft-switch technology in Wuhan metro communication system

With the rapid development of Urban Rail Transit, the demand and service quality of communication system for the subway is higher and higher. Good communication system is an important factor to ensure the safe operation of Urban Rail Transit. Telephone Communication is the basic hand of train command in Urban Rail Transit, including public telephone and private telephone. At present, SPC Exchange Technology is adopted in public telephone and private telephone system in Urban Rail Transit while domestic essential equipment suppliers such as ZTE, Huawei and other companies, declared phasing out the production of SPC Exchange Equipment. Thus, a new idea would be put forward to solve this problem. Soft-switch Technology can support various forms of information. It is a new network technology which integrates voice, data, image and fax services. Soft-switch technology as a representative of scientific and technological innovation can be effectively integrated with Urban Rail Transit Communication System. And the quality of communication service can also be improved. Taking Wuhan Metro as an example, this paper discusses Soft-switch technology and its application in urban rail transit communication system. After successful pilot, it can be extended to other cities.
Improved lower bound for algebraic immunity of a subclass of MM bent Boolean functions

It is known that algebraic immunity of an n-variable Boolean function is upper bounded by []. In literature, it was shown algebraic immunity of a subclass of Maiorana-McFarland (MM) bent Boolean functions is lower bounded by 2 and upper bounded by . In this paper, this lower bound is further improved. Given a Boolean function of -variables with algebraic immunity k ≥ 4, the improved lower bound helps a cryptographer to find a MM bent function of this class whose algebraic immunity is at least k − 2.
Cryptographic Symmetry Analysis with AES Algorithm for Safeguarding Data at Government Agencies

Data is very confidential information because it contains important information about the company or agency. Therefore it is necessary to secure these important data, in order to avoid misuse, theft of information or manipulation by certain parties who are not responsible. To avoid theft and manipulation of data it is necessary to implement a computer-based security system. One of them is by using cryptography. Cryptography is the study of how to change information from a normal (understandable) state / form into an incomprehensible form. One method that can be used to secure messages or information is the Advanced Encryption Standard (AES). AES is a part of symmetry cryptography. The application of AES cryptographic algorithms in securing data at government agencies can produce encryption that cannot be understood by humans and produce decryption that is exactly the same as the initial plaintext inputted, so that important government data can be secured in such a way. This research will produce a program that can encrypt and decrypt data using the AES (Advanced Encryption Standard) algorithm which will be used to secure data at Government Agencies.
Realizing an Effect Editor for AR Pop-up Picture Books by Teaching Motions

Digital picture books increase the interest of children in reading and are often used to encourage children to read. In this study, we develop a digital picture book using the augmented reality (AR) technology, which can be referred to as an AR pop-up picture book (AR book). The AR technology is used to prepare and present digital picture books in the AR space. However, developing an AR book requires technical skills and expertise, which are not possessed by common picture book writers. Therefore, we propose a new intuitive method for obtaining editing effects by teaching motions based on the demonstrations of writers using real-world objects. The results of this study denote that the proposed method is useful for achieving editing effects in AR books, enables writers to achieve editing effects in an AR book, and improves the edit accuracy.
Study on Influencing Factors of Career Choice of Excellent Teachers: Based on the Analysis of Nine Educational Autobiographies

Based on Lewin’s “Field theory”, the paper analyzes the educational autobiographies of nine outstanding teachers in primary and secondary schools, and constructs an analytical framework composed of family background, motivation for employment important events and personal experiences. It is found that there are four characteristics in their career choice, that are the awareness of “cultural gene”, the motivation of “escaping from suffering”, the training of “confusion and frustration”, and the encouragement of “important others”. It can be inferred that teachers’ early life experiences, “important others” and practical knowledge can influence their career choices.
Event prediction via spatio-temporal sequence analysis

Event prediction often refers to the process of inferring dynamic information such as human pose change, object motion trajectory and event development direction from static images or partial video, which has broad application prospects in security monitoring, automatic driving, human-computer interaction and other fields. This article proposes the means of deep learning to conduct research on sequence images' event prediction in time and space dimensions. To solve the problem of missing semantic information and lack of external information in the current event prediction research, we propose to adopt human skeleton constraint as guiding information, then complete the task from two aspects: skeleton detection and prediction in two-dimensional sequence images, image generation under skeleton guidance. The sequence images event prediction and generation model can generate realistic images with good continuity and perfect details on the basis of reasonable prediction in a short time. To verify the feasibility of our algorithm, we carried out a series of experiments on multiple deep learning network structures. The experimental results of the traditional motion detection dataset and the automatic driving dataset show the theoretical and practical value of the proposed algorithm in the field of sequence image event prediction, which has great potential for development.
ACEnet: Anatomical Context-Encoding Network for Neuroanatomy Segmentation

Segmentation of brain structures from magnetic resonance (MR) scans plays an important role in the quantification of brain morphology. Since 3D deep learning models suffer from high computational cost, 2D deep learning methods are favored for their computational efficiency. However, existing 2D deep learning methods are not equipped to effectively capture 3D spatial contextual information that is needed to achieve accurate brain structure segmentation. In order to overcome this limitation, we develop an Anatomical Context-Encoding Network (ACEnet) to incorporate 3D spatial and anatomical contexts in 2D convolutional neural networks (CNNs) for efficient and accurate segmentation of brain structures from MR scans, consisting of 1) an anatomical context encoding module to incorporate anatomical information in 2D CNNs and 2) a spatial context encoding module to integrate 3D image information in 2D CNNs. In addition, a skull stripping module is adopted to guide the 2D CNNs to attend to the brain. Extensive experiments on three benchmark datasets have demonstrated that our method achieves promising performance compared with state-of-the-art alternative methods for brain structure segmentation in terms of both computational efficiency and segmentation accuracy.
A real-time FPGA-based architecture of improved ORB

This paper proposes a real-time FPGA-based architecture of improved ORB. It proposes a strategy of redistribution of ORB feature points, which solves the problem of sorting FAST points of the whole image by response score. Besides, a strategy for offline generation of rBrief point pair patterns is proposed, which avoids online rotation of neighborhood pixels of feature points. These two strategies greatly reduce the resource consumption and processing clock cycles of the whole architecture. What’s more, the data throughput of the feature extraction step and feature description step is maximized, and finally a completely pipeline architecture is obtained. Due to the tips for parallel processing and resource reuse, the hardware implementation of the proposed architecture costs very few resources and processing cycles. The experimental results show that this architecture can detect feature and extract descriptor from video streams of 1280x720 resolution at 161 frames per second (161 fps), and the extracted ORB features perform well.
FPSeq: Simplifying and Accelerating Task-Oriented Dialogue Systems via Fully Parallel Sequence-to-Sequence Framework

A mainstream task-oriented dialogue system is stuck in the independence of modules since it follows pipeline design, and it also suffers from sequence dependence and time dependence of recurrent neural network (RNN). Thus, these systems are complicated and usually trained slowly. In this paper, we propose FPSeq, a novel, fully parall framework to simplify and accelerate task-oriented dialogue systems. Specifically, FPSeq turns pipeline design into a single sequence-to-sequence (seq2seq) model to achieve integration of each module for end-to-end training. In addition, multi-layer convolutional neural networks (CNNs) and attention mechanisms are applied in seq2seq learning to achieve parallel computations for speed improvement. Compared to the existing best model, the training speed of FPSeq is 3-10 times faster while only one-third of the number of parameters. Experimental results on CamRest676 and KVRET datasets indicate that FPSeq achieves the state-of-the-art performance in both task completion and quality of language generation.
Trust, Finance and Cryptocurrencies

This chapter aims to clarify the problem that cryptoanarchism aims to address and seeks to define cryptoanarchism as a distinct form of anarchism and examines the relationship between cryptoanarchism and cryptoanarchy. It introduces blockchain, a technology that produces distributed trust and automated value transfer with application beyond banking. In many business school textbooks, the exchange of value between people and organizations is understood to be a matter of trust and regulation. Cryptoanarchism is a movement which uses information technology in order to send and receive information free from surveillance and control by powerful institutions. The fundamental quality of technology, as far as cryptoanarchists are concerned, is the ability to ‘crypt,’ to allow people to communicate online anonymously and to protect themselves from surveillance by government and any other centralized authorities. Cryptoanarchists wish to demonstrate the irrelevance of government and other centralized powers, an aim that classical anarchists would doubtless agree with.
Screen Content Picture Quality Evaluation by Colorful Sparse Reference Information

With the rapid development of multimedia interactive applications, the processing volume of the screen content (SC) images is increasing day by day. The research on image quality assessment is the basis of many other applications. The focus of general image quality assessment (QA) research is natural scene (NS) images, now for the quality assessment research of SC images becomes very urgent and has received more and more attention. Accurate quality assessment of SC images helps improve the user experience. Based on these, this paper proposes an improved method using very sparse reference information for accurate quality assessment of SC images. Specifically, the proposed method extracts macroscopic, microscopic structure and color information respectively, and measures the differences in terms of macroscopic, microscopic features and color information between the original SC image and its distorted version, and finally calculates the overall quality score of the distorted SC image. The quality assessment model we built uses a dimension reduction histogram and only needs to transmit very sparse reference information. Experiments show that the proposed method has obvious superiority over the state-of-the-art relevant quality metrics in the visual quality assessment of SC images.
Sistem Informasi Geografis Lokasi Lahan Kelapa Sawit Berbasis Android  Di Kecamatan Mootilango

The development of information technology that exists today, making the utilization of information technology energy developing. Mootilango Sub-District is one of the districts that have enough land to make the area of palm oil land is about 182.170 (Ha) for the location of oil palm land owned by 90 people. Monitoring of plantation land is still less rapid, consequently it still takes a long time to obtain information about the state of the palm oil itself. During this time the data and location information of plantations presented are still in the form of reports containing numbers and texts. This method used is Research and Development method, this application is designed using PHP programming language software and HTML, Macromedia Dreamwever, Java programming language using Android Studio, and tools for modeling using Unified Modeling Language (UML). The conclusion of this research is the geographic information system can be applied and petrified the monitoring of plantation land more effectively and efficiently.
Våldtäkt - På distans. En granskning av begreppet våldtäkt

For hundreds of years, violence has been included as an integral part in the general definition of rape as well as a requirement in the legislation of rape offense charges. Today, however, violence is no longer a requirement in sexual offenses legislation. A rape can be committed on the internet through fellowship or if it is compared to sexual intercourse, given the gravity of the violation. From media, it appears that this is something unique to Sweden. Other countries such as Denmark and Norway refer to it as grooming or virtual sexual abuse. The meaning of both the concept of violence and the definition of rape have changed over time as society has shifted and its values. Both concepts have expanded their meanings. This societal change has been a challenge for the Swedish legislature to meet. This thesis, therefore, aims to investigate and examine the motives and the legal application that postulates that rape is possible to commit on internet. In order to clarify this, an analysis of the concept of rape has been made, which included a question regarding the definition of violence and rape from a historical and contemporary perspective. In recent years, due to changing societal values, the concept and definition of both rape and of violence have been questioned and changed. Violence has evolved to include mental forms, and rape has expanded to include acts committed without physical abuse or contact. By immersing myself in the historical concepts and legal applications of rape, including reviewing prior legal cases, and comparing these to contemporary societal views, I have been able to find out that the legislator had experienced difficulties in merging the current law and societal beliefs on these particular issues. I consider an extension of the concept of violence to be legitimate and well-founded, but that does not automatically mean that an extension of rape as a concept is legitimate and well-founded. This petition thus shows that there is reason to consider a separation between physical and virtual rape through different legislation. It is clear, however, that it is equally serious, whether it has been committed physically or committed on the Internet. The concept of rape has been the subject of discussion as to whether it should be replaced with reference to the fact that it can today take place on the Internet. Furthermore, there has been a fear that the concept will be eroded and lose its indication of seriousness. But it is not a matter of the seriousness of the crime, but rather a question of meeting law and society with legality as the basis and defining a crime for what it really corresponds to.
Desarrollo de un algoritmo de cálculo simbólico para la resolución de las ecuaciones de decaimiento y transmutación de Bateman

espanolEl modelo matematico mas adecuado para describir los cambios en la composicion isotopica de un reactor nuclear, consiste en un plantear un conjunto de ecuaciones diferenciales lineales acopladas. En 1910 el matematico Harry Bateman propuso una solucion para dicho sistema de ecuaciones, la cual se conocido como la solucion de Bateman. En el presente trabajo, se ha desarrollado un algoritmo que puede construir las soluciones a cadenas ciclicas de una forma rapida a traves del calculo simbolico. Dicho algoritmo, utiliza un analisis combinatorio de las posibles posiciones que pueden ocupar elementos repetidos, y a traves de un conjunto de funciones de variables del tipo “string”, construye las soluciones de una forma veloz y dinamica. Asi mismo, el presente trabajo incluye un analisis del tiempo de computo que consume dicho algoritmo, y propone una forma de realizar una comparacion con las soluciones existentes EnglishThe most appropriate mathematical model to describe the changes in the isotopic composition of a nuclear reactor is to propose a set of coupled linear differential equations. In 1910 the mathematician Harry Bateman proposed a solution for this system of equations, which is known as Bateman’s solution. In the present work, an algorithm has been developed that can build solutions to cyclic chains in a quick way through symbolic calculation. This algorithm, uses a combinatorial analysis of the possible positions that repeated elements can occupy, and through a set of functions of variables of type “string”, builds the solutions in a fast and dynamic way. Likewise, the present work includes an analysis of the computation time consumed by said algorithm, and proposes a way to make a comparison with the existing solutions
Efficiency Issues and Improving Implementation of Keystroke Biometric Systems

Keystroke dynamics is a heavy field for researches; a lot of solutions have been proposed in this domain using different implementations usually based on Euclidean distance for measuring similarity between features vectors. However, the Euclidean distance method has a higher error equal rate compared with other classification methods, which makes the method less effective. Therefore, in the article, the authors propose their version of keystroke dynamics implementation based on K-NN, F-NN, and Manhattan distance as classifiers to improve the authentication efficiency. The flight times and dwell time between keys are used in this study.
Analyzing and implementing a third-party state machine library for FriendlyReader and TeCST

FriendlyReader and TeCST are text simplification tools developed at Linkoping University, using an API service at the university called SAPIS. Both tools are web services that run in the browser fo ...
Efficient Decision Tree using Machine Learning Tools for Acute Ailments

Machine learning is a part of data mining which learns from previously fed data. It is one of the best tools to classify and cluster the data. These homemade medicines are used in villages to treat diseases. Thus, using the combined knowledge of Ayurveda and machine learning, the data can be used to find the target value. This target value can be modified for personal use, benefit and treatment according to the disease. In this paper, we have used machine learning algorithms and classified the data to check widely used Ayurvedic medicines. We used tools like Scikit learn and Jupiter notebook to plan a Decision tree. This is mainly used for algorithm solving and data prediction. The basic assumption of machine learning is to construct algorithms that can take input data. This input data is statistically analyzed to predict output. As we know that the current scenario of predicting earthquakes can be done by the next artificial intelligence frontier. Thus, advancements in machine learning and artificial intelligence today will have an immense change in future.
A Linked Data Model-View-* Approach for Decoupled Client-Server Applications

Separation of concern is found to be a crucial design requirement for maintainable, extendable and understandable software. Research has been done on software design patterns that ensure strict separation of concerns and by this avoid cross cutting concerns in modules of large-scale software projects. In particular, Model-View-* design patterns attempt to decouple local data and business logic from user interfaces, keeping both extendable and exchangeable. Targeting Web-applications, technologies from the domain of Linked Data and Semantic Web have been found suitable to decouple clients from servers. While the potential of both Model-View-Patterns and Linked Data interfaces is often convincingly outlined, there exists to this point little to no work that shows how the findings in said fields can be successfully employed to design large-scale decoupled client-server Web applications. In this paper, we show how lifting a suitable data representation of a Web server application run-time to Linked Data allows to build client-server applications following a decoupled Model-View-Presenter-ViewModel design pattern. This removes the need for fixed server-side APIs, detaches clients from server specifics, and allows clients to implement their business logic entirely on expected semantics of the server data.
Blockchain-based health information privacy protection

The contribution of this paper lies in, by exploring blockchain technology facing health information privacy and fmding a detailed framework and practical examples, the optimal design of blockchain is proposed to address the privacy of patients&apos; health information and data from the following aspects, such as technological frameworks, theoretical model, technical approaches, and performance evaluation metrics.