Reviewerly/exHarmony huggingface dataset:
Research on accelerating CEE-DGCNN event extraction algorithm based on multi-CPU platform

Abstract With the development of the Internet, the volume of information is expanding rapidly, and the complex information makes it particularly important to extract information quickly and intelligently. Event extraction algorithm is such a kind of fast and accurate information acquisition algorithm. With the development of deep learning in recent years, deep learning also shines in the field of time extraction. CEE-DGCNN network is an efficient and accurate event extraction algorithm for Chinese text. At present, the acceleration research on deep learning in the academic community mainly focuses on GPU, FPGA and other platforms. In fact, compared with these platforms, CPU is more versatile. Considering that the algorithm should have universality and universality in industrial application, this paper makes an in-depth analysis of CEE-DGCNN algorithm to study its acceleration on CPU. Experiments were carried out on x86 and ARM architectures respectively, and good acceleration effects were achieved.
Randomness Selection in Differential Evolution Using Thompson Sampling

Differential evolution is a versatile and highperformance search algorithm for optimization problems. Some algorithms adaptively change the strategy of differential evolution, and they have better performance depending on the setting of the strategy. We have developed a parameter-independent algorithm by simply rethinking the setting of these strategies in terms of randomness. Furthermore, if the adaptation process of strategies and randomness can be regarded as a Bandit problem, more efficient adaptation process can be developed. In this study, we consider adapting several randomness patterns to differential evolution using Thompson sampling, which is a bandit algorithm with very good performance. The effectiveness was confirmed by numerical experiments.
Image Sizing using Removal or Insertion of Seams based on Energy Function

Abstract The nature of the image plays a significant role in any image sizing algorithm. The technique of improving or condensing an image while preserving its key image quality is challenging. The resolutions of various display devices vary from one another in order to fit the image according to the resolution image sizing plays a vital role. In order to size the image a operator is introduced which will remove or insert the seam from an images based on the resolution of the device used. A seam in an image is related to the pixel path from up to down or right to left, the seam vector to be deleted for image size is defined by the image energy attribute. The Seam removal or insertion operator can be applied to an image and aspect ratio can be adjusted accordingly by continuously removing or adding a seam in the desired region of image. The collection and order of seams decides the picture quality, as described by the energy function. By storing the order of seams in an image that can continuously change to fit a given size in real time, multi-sized images can be produced.
Conceptual Resource-Saving Design of Real-Time Socio-Technical Systems

Abstract The article discusses the methodological resource-saving approach to the System design of socio-technical systems for real-time managing (STS RTM). The definition of STS RTM from the point of view of computer systems architecture is introduced. This approach made it possible to classify the main paradigms of using computer systems, including the modern stage, corresponding to STS RTM. For such complex systems, it is important to ensure their energy efficiency, which is ensured by the use of resource-saving models and methods for optimizing structural solutions. This is ensured by minimizing the total length of communications at the enterprise, saving computing and financial resources during system migration from a centralized structure to a functionally distributed hierarchical multi-microcontroller system. STS is a human a real-time machine system, therefore, the system’s response time to the processing of requests related to the issuance of messages to the system’s operating personnel is determined. The complex of formulated tasks and their solution on a common information and analytical base is extremely difficult without a unified system design methodology and automation tools for solving problems. Such a Framework is described in this article.
Trolling and Hate Content on Social Media Platforms

Amount of users on social media platforms have increased manifold in past few years due to availability of discounts/EMI on smart phones and cheap internet services. There has been a hike in social media users especially from teenage groups (age group 13-19) and people who are on verge of retirement/already retired or are in their later part of life (age group 50+). There has been a surge in trolling, hate content and other harmful content on various social media platforms in last few years. The various platforms have failed to control the content which is being uploaded, posted or shared. Often, the content seems entertaining for majority and they save it and forward it to their various social circles. Some choose to ignore it, while those who get offended indulge in the notorious conversation(s) and thus a chain of replies begins. It can be entertaining or abusive depending upon the content, who initiated it and who the targets are. Mostly, from neutral perspective, it is suspicious, abusive or harmful. There seems to be violation of the freedom of expression at times on these social media platforms. Though the platforms give the option of reporting the content(s), post(s), page(s) or channel(s), the social media users at large doesn’t opt to use it. It has been found that people don’t want to indulge in reporting these activities because it is not related to them or they believe that these platforms don’t take any reports/complaints seriously or it is complete waste of time or else it is a complicated process. Still, there is a section of users who report these activities irrespective of whether they are themselves target or not. They believe that it is their moral responsibility and someone must apply the clutches to these trollers and hate content perpetrators. There are positive as well negative usages of any technology which are available for disposal by mankind, here social media platforms. Therefore, it is a collective responsibility of society in large and social media users in particular to use it in fair and impartial manner. The various platforms are ethically and morally bound to take actions on abusive and hateful content on their platforms and make it safe for all.
Shocks and Surprises: Refining the Elementary Model

This chapter explores refinements of the elementary model of a brass instrument under playing conditions. The theory of spectral enrichment resulting from nonlinear sound propagation is presented in order to explain the brassy character of brass instruments when played loudly. The extreme case of shock wave (N-wave) generation in the air column of a brass instrument and its visualisation through schlieren optics are described. Spectral enrichment at moderate dynamics is examined, and the brassiness potential parameter is defined. The role of resonances of the player’s windway in performance is discussed. Evidence for the inadequacy of a single degree of freedom model for the brass player’s lips is presented, and more sophisticated models are introduced. The nature of wall vibration and methods of measurement of structural vibration in brass instruments are described, and the influence of wall vibrations on the radiated sound and the perception of the performer are addressed. Going Further sections offer more detailed treatments of nonlinear sound propagation and the analytical modelling of vibroacoustic coupling in ducts.
Classification of Worries and Consultations with School Refusal Students Using Machine Learning

This study proposes a text classification method for the automatic tagging of posts on the an Internet bulletin board system for school refusal students. Four tags are defined on the basis of the reasons for truancy as follows: Friend, Teacher, Family, and Study. A classifier is generated for each tag, and multiple tags are assigned to a sentence. The results of classifier verification showed that the accuracy of each classifier was more than 70%, and the highest was more than 85%. However, the precision was low for the classifiers other than Family. Among the solutions, such as reviewing the dataset and changing the vectorizer, we will choose the method that is appropriate for each classifier.
An Empirical Study of Classification Techniques by using Machine Learning Classifiers

In this transformational era, advancements in computational powers of machine learning applications, data classification task has put its roots from various engineering domains to an explosion of new strategies of data handling in the real-world applications scenario. Therefore, this study describes the implementation of eight classifiers (Logistic Regression, Support Vector Machines, Perceptron, Decision Tree, Random Forest, k-Nearest Neighbor, Gaussian Naïve Bayes and Linear Discriminant Analysis) on the iris dataset. Performance metrics like classification report and accuracy measures are evaluated on the iris dataset and it is observed experimentally that SVM classifier has given good accuracy measure of 99.1% over other classifiers.
Why Employees (Still) Click on Phishing Links: An Investigation in Hospitals

Employees are considered the weakest link in information security; their compliance with security policies has been a major area of research. However, employees click on phishing links even after receiving training. In this study, we explore the factors that influence information security policy compliance, using the theory of planned behavior (TPB) and integrating trust theories. We conduct a survey in hospitals to investigate the components of compliance intention and match employees’ survey results with their actual clicking data from organizational phishing campaigns. Our analysis (N = 430) revealed that TPB factors (attitude, subjective norms, and perceived behavioral control), as well as collective felt trust and trust in information security technology, have positive effects on compliance intention. However, surprisingly, compliance intention does not predict compliance behavior. Of the variables we tested, only the level of employees’ workload shows a significant relationship to their actual behavior. This study contributes to the information systems literature by understanding factors influencing compliance behavior. Also, unlike studies that assess behavior through a questionnaire, our method was able to measure observable compliance behavior using clicking data. Our findings can help organizations augment employees’ compliance with their cybersecurity policies and reduce the likelihood of clicking on phishing links.
A Real-Time Mp3 Copyright Protection System for Mobile Terminals:Practicalissues

With the development of the Internet and mobile terminals, more and more pirate digital music resources are easily disseminated online. To prevent the illegal copies propagating among mobile devices and protect the right of content providers. In this paper, we designed a practical real-time mp3 Copyright Protection System(MCPS) for mobile terminals which is based on Client/Server model and contains three parts: security channel, server and client. In particular, we established a secure channel based on SSL(Secure Sockets Layer) protocol, defined an identity authentication procedure between the server and the client. In the server, we designed RC4 based encryption algorithm for frame header, and chaotic based watermarking algorithms for frame body, respectively. In the client, we designed a novel mp3 streamd ecoder, where, for each frame, frame header is decrypted, and the embedded information is extracted and compared with its IMEI to decide whether to decode or not. The practical experiments show that the system can effectively protect copyright for digital_music and is of great.
Semantic Medical Image Analysis

The recent advancement in imaging technology, together with the hierarchical feature representation capability of deep learning models, has led to the popularization of deep learning models. Thus, research tends towards the use of deep neural networks as against the hand-crafted machine learning algorithms for solving computational problems involving medical images analysis. This limitation has led to the use of features extracted from non-medical data for training models for medical image analysis, considered optimal for practical implementation in clinical setting because medical images contain semantic contents that are different from that of natural images. Therefore, there is need for an alternative to cross-domain feature-learning. Hence, this chapter discusses the possible ways of harnessing domain-specific features which have semantic contents for development of deep learning models.
Statistical Peculiarities of Words Distribution Based on the Pastoral Letters of Andrey Sheptytsky

The article is dedicated to one of the most important areas of quantitative studies of language and statistical properties of text. The mathematical methods of text analysis were described. Average statistical parameters which were used in research were defined and analyzed. The length of sentences and words was calculated in the Pastoral Letters of Andrey Sheptytsky. Based on received data the author’s individual style was characterized. Dependencies of the number of sentences in a paragraph and the number of words in a sentence were spotted and explained. The peculiarities of words distribution in texts of the author during significant period of time were evaluated. The results were compared to the similar figures in other genres. The future prospectives of Pastoral Letters research were outlined.
A New Approach to Improving Images by Transforming their Intensity

This paper explores the creation of new ways to improve images intended for use in mobile applications. The main objective of this study is to improve the efficiency of image enhancement by transforming their intensity. To achieve this, we propose a new approach to improving the image by adaptively transforming its intensity based on an analysis of average values for the brightness sub-ranges of the initial and inverted images. To demonstrate the possibilities of this approach, new techniques of intensity transformation have been proposed. The proposed techniques provide effective image enhancement without the appearance of distortion and artifacts and are focused on use in mobile applications.
Analysis and Comparison of Different Blockchain Algorithms in IoT Security

Abstract Internet of things (IoT) and Blockchain are two advancements that are picking up notoriety since the hour of their creation. Sooner rather than later, IoT is going to impact everything we use in our daily lives. As the utilization of this innovation expands, the danger to misuse it likewise increments. Existing advancements are insufficient to manage this. Along these lines, Blockchain has risen as a successful answer for understanding the security issues identified with IoT. Information put away in Blockchain is permanent and can’t be changed very effectively. Likewise, the information is added to the block only after it is affirmed by everybody in the system, and in this manner, it is permitting secure exchanges. The individuals who approve the exchanges or transactions and include them in a block are known as miners or excavators. In this article, a detailed overview of the different Blockchain algorithms that are being used for IoT security has been explored. Also, an attempt has been made to provide a detailed overview regarding Blockchain which can act as a reference for the researchers who wish to pursue research in the Blockchain domain.
The Design and Implementation of Test System for Expression Ability Evaluation

Expression ability is a very important skill, but the current common language tests focus too much on vocabulary, grammar and writing, which is not suitable for the evaluation of expression ability. Rapid expression test(RPT) is an evaluation method designed specifically for this deficiency, but there is no supporting software system to provide service support for it. This paper analyzes the requirements of the target system, designs and implements the expression ability evaluation system based on computer and network technology, which can provide evaluation service for ordinary users and provide relevant system management support for administrators. The performance evaluation system designed and implemented in this paper provides good service support for the rapid expression ability testing method, achieves the expected performance, and the system has good scalability and scalability.
The Development of Pedagogical Thinking of Students Through the Use of Information and Communication Technologies

The paper considers the problem of the formation of pedagogical thinking of students, future teachers. The process of perceiving a problem situation and formulating a pedagogical task is analyzed. The possibilities of information and communication technologies in the implementation of the acmeological approach to the development of pedagogical thinking are considered. The results of a study of the formation of pedagogical thinking in students based on the use of information and communication technologies are presented.
Health Monitoring and Analysis using IPFS and Blockchain

India currently has no central health monitoring system in place which can provide a single platform for storing Medical records of all the citizens of our country in a systematic and secured manner. In this research, we develop a system that will not only provide a record storing platform rather, a system that can be used to perform analysis on the records stored and produce output by the means of data mining which could be used for multiple agencies like Government, Pharmaceuticals Company, and Hospitals to benefit from services like Epidemic predictability based on Preset benchmarks, help in maintaining appropriate stock of medicine, serve as Electrical Medical Records (EMRs), etc. The highlight of this research is the use of two emerging paradigm changing technologies in the medical domain, which are Blockchain and IPFS. The use of these two technologies along with the architecture model suggested in this paper can efficiently reduce the problem of security breaches faced by most of the health record systems maintained by other countries.
Face Detection: An Effort to Accomplish an Analysis in the Archaeological Field

Face detection (FD) research work is growing rapidly in computer vision field because of its broad choice of application in the world of computer technology, security, psychology, medicine, and pattern recognition. FD was recognized as the unavoidable prepossessing function for face recognition (FR), carrying its own issues as it faces its own difficulties and challenges which are quite different from that of FR. There are various traditional FD methods which face various challenges towards object clarification, posture dissimilarity, appearance changes, and other face look of different modern mankind. Machine is used to classify different kinds of features belonging to the face of a person, using various classification techniques. In this paper, different classifiers are used for face detection over ancient mankind.
Acquisition of Geoscientific Data

Ore deposits are formed by geological processes. Geoscientific survey and exploration only bring out the existing mineral endowments in a given terrain. If some surveys lead to discovery of several deposits, it speaks of the efficacy of the data acquisition, interpretation as well as the inherent mineral endowment of the given terrain. Comparative assessment of outputs of the geological and geochemical mapping and geophysical surveys including airborne operations is discussed with examples. Geological mapping is considered a preferred activity in well-exposed terrains.
Digital recruitment of innovative project teams’ leaders based on genetic algorithms

Abstract Over the past decade, innovation has become an important part of the development for large business companies. The search for promising topics, as well as the recruitment of potential applicants teams who can implement an innovative project with the maximum benefit for business at the lowest cost, led to the search for approaches to solving these problems using IT. Since the problems of such research are covered separately in different industry areas, we implemented an approach to completing project teams based on genetic algorithms. A wide review of the literature allowed us to identify some important characteristics of innovative projects, as well as to summarize the portfolio of competencies required for potential designers. These attributive characteristics of the project and the applicants’ competence should be taken into account. The developed genetic algorithm allows searching for multiple parameters simultaneously and generating new solutions through the use of different operators. The results open up a new range of opportunities for business companies and government organizations interested in successful implementation of innovations.
Blow That Horn: An Elementary Model of Brass Playing

This chapter presents an elementary model, involving some approximations and simplifications, of a brass instrument under playing conditions. This model is capable of reproducing many features of performance by musicians including control of embouchure to select one of a number of natural notes, and to pull its pitch up or down by the subtle embouchure modification termed ‘lipping’. The model explains why there is a minimum blowing pressure necessary to sound each note and why this threshold pressure increases as the played pitch rises. The model is based on a set of three equations, which have to be solved simultaneously to predict the nature of the sound radiated by the instrument. Low-amplitude self-sustained periodic solutions of the elementary model are explored, and the technique of linear stability analysis is introduced. Numerical simulation methods developed in physical modelling, including the use of bifurcation diagrams, are employed to illustrate a large range of playing situations. In a Going Further section, the theoretical and computational techniques used to identify the oscillatory states of the elementary model are explained in detail; predictions of the model are compared with the behaviour experienced by players of real brass instruments, including the trombone pedal note regime and the performance of lip and sung multiphonics.
An Enhanced Local Neighborhood-Based Niching Particle Swarm Optimization Algorithm for Multimodal Fitness Surfaces

This paper aims to introduce a niching technique based upon simple local neighborhood-based PSO for multimodal optimization. The corresponding algorithm known as Enhanced Local Neighborhood Based Niching Particle Swarm Optimization (ELNPSO) algorithm has shown promising results when used in conjunction with multimodal optimization problems, which has been established by comparing the performance with three other multimodal optimizers tested upon eleven different multimodal benchmarking functions.