Reviewerly/exHarmony huggingface dataset:
Research on Vision Control System of Pipeline Robot

As the "blood vessel" of the city, pipelines are all over the underground of the city. To inspect the pipeline conveniently and intuitively, the pipeline robot needs to enter the pipeline and transmit the real-time image inside the pipeline through the camera module of the robot. However, most pipeline robots rely on manual attitude control for turning and other operations. This paper studies the problem of automatic navigation when the robot is running in the pipeline with high water pressure, which can assist the operator to control the robot.The basic principle is that the video signal of the camera is transmitted to the host computer through the optical fiber, and the upper computer processes the image to determine whether to turn and the direction of turning, and then sends instructions to the attitude change module. This method can accurately judge the turning direction, and good results are obtained in the experiment.
Gesture Recognition Based on Dual-channel Feature Fusion

In order to solve the problems of traditional gesture recognition based on artificial feature extraction, such as complicated operation, low accuracy, and insufficient feature extraction of classic convolutional neural network, we propose a two-stage dual-channel convolutional neural network. The entire network structure is divided into two stages which including a segmentation stage and a recognition stage. In the segmentation stage, a network consisting of a fully convolutional residual network and a Pyramid Pooling Module (PPM) module are used to execute the segmentation. As the shown in the experimental verification results, the proposed segmentation network designed has a very good effect in light changes and complex environments; For the recognition stage, we use a network which is composed of a two-channel convolutional neural network. The input of two channels is the RGB image and the feature map segmented by the segmentation network, and the output is the fusion of the extracted features of the two channels. For experimental verification, we paper use the OUHANDS data set. In theory, the recognition accuracy rate reaches 97.31%, and the network size and parameters are several times smaller than those of classic networks such as Lenet-5, ResNet-18, and VGGNet.
Anomalous Event Detection Methodologies for Surveillance Application

Automatic visual surveillance systems serve as in-place threat detection devices being able to detect and recognize anomalous activities which otherwise would lead to potentially harmful situations, and alert the concerned authorities to take appropriate counter actions. However, development of an efficient visual surveillance system is quite challenging. Designing an unusual activity detection mechanism which is accurate and real-time is the primary challenge. Review of literature carried out led to the inference that there are some attributes which are essential for a successful unusual event detection mechanism for surveillance application. The desired approach must detect genuine anomalies in real-world scenarios with acceptable accuracy, should adapt to changing environments and, should require less computational time and memory. In this chapter, an attempt has been made to provide an insight into some of the prominent approaches employed by researchers to solve these issues with a hope that it will benefit researchers towards developing a better surveillance system.
Forming the Civic Participation and Culture Interethnic Interaction of Students’

The article is devoted to the formation of civic participation and culture of interethnic interaction of students. The urgency of forming of civic participation and culture of interethnic interaction is conditioned by the demands of a modern multi-ethnic society. Thanks to the increasing mobility, the society of many countries is becoming multinational. Civic participation and the culture of interethnic interaction becomes an important factor in all spheres of public life. The list of materials and methods used during the pedagogical experiment on the formation of civic participation and culture of interethnic interaction is described. The logic of organizing a pedagogical experiment of students included 4 stages: preparatory, ascertaining, formulating and controlling. A definition of the concept of "civic participation and culture of students’ interethnic interaction" was developed. The diagnostic toolkit of the experiment was selected in accordance with the criteria for of civic participation and culture of interethnic interaction of students. Experimental work has revealed that the students' readiness for productive civic participation and interethnic interaction directly depends on their level of interethnic interaction culture. The most effective means of forming culture of interethnic interaction between students is their active involvement in a multiethnic environment, as well as civic participation in local self-government on issues of interethnic politics.
Field Animation

Vector fields visualization is quite common in many scientific disciplines and many methods have been developed for this purpose. Python is probably the ideal glue language to write applications that exploit the capabilities of modern graphic cards through the Open Graphics Library. A brief introduction to Python and OpenGL will preface our approach in writing easily reusable code to create a Python package to represent vector fields through particles that move along the flow lines of the field at a speed and color proportional to its modulus. An example application will be shown to illustrate how interactive control of speed, color and number of animated particles is possible as the whole rendering process happens in the GPU in real time. A background image can be shown to add information for the interpretation of the results.
National Responses for Persons Deprived of Liberty during the COVID-19 Pandemic in the Philippines

The main purpose of this paper is to review the national responses for persons deprived of liberty (PDLs) during the coronavirus disease 2019 (COVID-19) pandemic in the Philippines. The researcher discusses the major responses that have been carried out such as easing the rules on parole grant and executive clemency, providing human consideration to the vulnerable segments, and improving the corrections facilities health management. These responses are expected to decrease the growth of virus infection inside the corrections facilities, protect the condition especially of the vulnerable segments, and ensure the overall safety of the community. This paper specifically recommends for the need to expand the virtualization of judiciary functions to the provincial zones, place the release of the vulnerable segments in priority order, and technically improve the health management of corrections. However, as current responses may just represent temporary measures due to the crisis, this paper further urges for responses that will eventually lead to long-term decongestion of corrections facilities or reduction of the perennially high prison population of the country.
Cloud Risk Resilience

Cloud computing has been instrumental in transforming the way we store, access and process data. With mobility being the primary objective of the current market, cloud computing offers exactly that. Cloud offers convenient access to a shared pool of computing resources that can be configured and deployed with minimal effort which is used to deliver computing services over the internet. Exercising these advantages come with a plethora of security risks that need to be addressed. The security issues in cloud are complex due to the nature of implementation and regulations that govern them. In this article, we examine existing research on cloud risk and the various frameworks to manage risk. The objective is to map the risk with the audit control and technology that will help in mitigating the risk. We analysed the various cloud security solutions and came up with a list that best help in the effective management of the cloud risk and security issues.
THE CONCEPTION AND SIGNIFICANCE OF FACILITATION IN THE STUDIES OF FOREIGN SCIENTISTS

The author of the article analyzes the works of foreign scientists, determines the essence of facilitation, and reveals the conception of pedagogical facilitation. In the article the role and skills of facilitative teacher are characterized. It was determined that pedagogical facilitation is a specific type of pedagogical activity of the teacher, which aims to help the student in self-development, self-realization, selfimprovement, to promote his personal growth, the disclosure of abilities, cognitive capabilities.
Mitigation of Resource Depletion in AD-HOC Network

This paper is based on detection and prevention of Sleep deprivation Attack that takes place in MANET. The MANET’s have defects like open medium, dynamically changing network topology, cooperative algorithm and lack of centralized monitoring and management point. Due to these defects, Effective communication between mobile nodes is essential for proper or smooth working of network. In Sleep Deprivation attack, the energy power and bandwidth of victim node gets depleted. In this paper a methodology is developed which will mitigate, detect and prevent Sleep deprivation attack in the network. The method like packet analyzer and detected list along with alarm communication will be used to detect and prevent Sleep Deprivation attack.
Research on optimal path Modeling based on DP Model

Abstract Nowadays, the emergence of all kinds of games greatly enriches our life and enlightens our wisdom; As a vehicle of enlightenment, the game itself involves the choice of a variety of strategies and the choice of routes and solutions. In the case of multiple constraints, the core idea of strategy choice games is to make the optimal solution to a certain problem, and such a choice plan needs the support of a variety of theories, such as game theory dynamic programming, the application of operations research, and so on. In this case, it is essentially a given condition of the game, using the above known mathematical model to find the optimal solution, that is, under the condition of meeting the safety of the end, the most money is left When the weather is known and the map is known, we can make the most optimal solution; by using the DP model and the correlation of the TSP problem, we have found a certain rule: give priority to choosing the mine that can bring us income, and then replenish the resources when there is a problem with the resources, so as to plan the best route. For the calculation of money, we take the reverse program to calculate and deduce, and find that level 1 and level 2 can finally make money, and give the specific value in the detailed explanation of their respective problems. Under normal circumstances, it is impossible to know the changes of the weather in the future, so it is necessary to make different analyses for different weather conditions every day; here, we assume a certain strategy, that is, to accept the relatively non-optimal solution with a certain probability, and then through the increase of the number of iterations, we finally retrieve the optimal solution in this hypothesis.
Root Finding

As the name suggests, the roots of a function are one of its most important properties. Finding the roots of functions is important in many engineering applications, such as signal processing and optimization. For simple functions such as f(x)=ax2+bx+c, you may already be familiar with the “quadratic formula” below,xr=−b±b2−4ac2a, which gives xr, the two roots of f exactly. For more complicated functions, the roots can rarely be computed using such explicit or exact means. By the end of this chapter, you should understand the root finding problem, and we will introduce two algorithms for finding roots of functions, their properties and limitations.
Introduction

With the rapid development of Internet of Things (IoT), mobile devices, and social networks, our world has become more connected than ever before, resulting in ubiquitous linked data, more generally, graphs. To discover the knowledge from the connective world, graph analysis is the de facto technique. In the consensus study report (National Research Council, Frontiers in massive data analysis. The National Academies Press, Washington, DC, 2013), National Research Council of US National Academies points out that graph analysis is one of the seven major computational methods of massive data analysis. A wide array of applications such as social network analysis, recommendations, semantic web, bioinformatics, intelligence surveillance, and image processing utilize graph analysis techniques to discover helpful insights. However, unlike decades ago, nowadays graphs are large, sparse, and highly dynamic. The classical methods of graph analysis become inefficient or even infeasible. Large-scale graph analysis becomes a problem that both industry and academia trying to solve. In this chapter, we first introduce the background of large-scale graph analysis and briefly review existing solutions; then we introduce three advanced graph analysis tasks which are popular and fundamental but not yet have efficient solutions on large graphs; third, we summarize the research issues of the large-scale graph analysis, especially for the advanced graph analysis tasks. Finally, we present an overview of this book.
Рhilosophical understanding of philosophy. Higher school without philosophy.

The conversation raises the question of the universal understanding of philosophy in order to question about the level of the contemporary's ability to understand philosophy in accordance with its original way of being. The statement of the question is connected with the catchy oddities of the current situation. We are talking about the current desire of the philosophizing community to justify the benefits of philosophy, and its substantive presence in the academic environment through the development of "competence philosophies". The spreading philosophies of "what you want", with a departure in the partial moments of a given problem, communicate a system of certain truths. But is it being introduced into a philosophical state? And do they preserve philosophy itself? Also, today, there are enough proposals to convey philosophical thought in a world separation from institutionalization. But, by all means, a fashionable and famous thinker. Or philosophize along with something attractive. With a scandal, for example. Basically, such offers are in demand. Therefore, thinking “for the money” is actively scattering. I will call this philosophy through subscription.At the same time, the applications offer spicy or hot topics with the prefix: a philosophical meeting, a philosophical view, a philosophical understanding. What do the joint stays of people who associate with the philosophy attached to the vital lead to? The aim of the article is to study the level of a contemporary's ability to understand philosophy in accordance with its original way of being. The main tasks are: 1) assessment of the current situation of actively spreading innovative teaching of philosophy; 2) analysis of the thinking of a person who is in a position where, on the one hand, “competence-based philosophy” and “craft philosophy” are being strengthened, on the other hand, the philosophy of the academy is removed from classical universities as unnecessary - under the conditions of the global market; 3) view of philosophy as an absolute unity.Research methods: The research is based on the metatheoretical method, since it allows one to describe philosophy in an inalienable way, in accordance with its nature. Avoiding methodological confusion, metatheory makes it possible to examine philosophy formally and encourage thinking, testing its power.For reflection, the comparability of the experiences of philosophy in itself and of the involved philosophy is proposed.
An Efficient Capsule Network Reconfigurable Hardware Accelerator for Deciphering Ancient Scripts with Scarce Annotations

Capsule network is a new class of deep neural network that emerges to mitigate the traditional convolutional neural network's inefficiency in terms of preserving spatial relationships of image entities and has been used recently in novel classification tasks. It performs well on small datasets especially those with scarce annotations as in the case of ancient scripts. Nevertheless, it requires intense computations especially for high-dimensional matrix operations. To mitigate this limitation, this paper proposes a capsule network hardware accelerator for deciphering ancient scripts with scarce annotations. The proposed model has a reconfigurable functionality that reduces the computation latency handling intense computations efficiently while achieving a state-of-the-art performance in recognizing handwritten characters with an overall accuracy of 0.9891 and a loss of 0.021. To investigate the feasibility of the proposed model, the capsule network inference is performed on both GPU and the proposed hardware accelerator. By achieving a latency reduction of 2x, the proposed accelerator outperforms the GPU making it a suitable solution for accelerating capsule network inference in deciphering ancient scripts.
CLASSIFICATION OF NETWORK PROTOCOLS WITH APPLICATION OF MACHINE LEARNING METHODS AND FUZZY LOGIC ALGORITHMS IN TRAFFIC ANALYSIS SYSTEMS

This paper presents a new effective approach to analyzing network traffic in order to determine the protocol of information exchange. A brief description of the structure of the algorithm for classifying network packets by belonging to one of the known network protocols is given. To define the protocol, the principle of high-speed one-packet classification is used, which consists in analyzing the information transmitted in each particular packet. Elements of behavioral analysis are used, namely, the transition states of information exchange protocols are classified, which allows to achieve a higher level of accuracy of classification and a higher degree of generalization in new test samples. The topic of the article is relevant in connection with the rapid growth of transmitted traffic, including malicious traffic, and the emergence of new technologies for transmitting and processing information. The article analyzes the place of traffic analysis systems among other information security systems, describes the tasks that they allow to solve. It is shown that when recognizing the internal state in which a particular protocol may be in the process of information exchange at the handshake stage, a classifier of network packets of the application level can be useful. To classify network packets, we used fuzzy logic algorithms (Mamdani model) and machine learning methods (neural network solutions based on logistic regression). The paper presents 4 stages of developing a network packet classifier – monitoring and collecting packet statistics of the most famous network traffic protocols, preprocessing primary packet statistics, building a classifier for network packets and testing. The test results of the constructed software module capable of identifying network protocols for information exchange are demonstrated.
Tool validation

There exists considerable disagreement within the digital forensic community on the subject of tool validation. It should not be inferred from this chapter that tool vendors are producing substandard tools but, rather, that there are issues that need to be addressed concerning the validation of tools and processes that are used to examine digital traces. Digital forensic tools are used to identify evidence regarding the guilt or innocence of persons accused of having committed a crime and for which the potential penalties are severe. If the evidence is incorrect due to tool error, the innocent might be incarcerated, the guilty might be free to reoffend and certainly the reputation of the examiner and employer will be damaged, possibly irretrievably beyond repair.
Eluding Side Channel Attacks by using Masking 128Bit AES Design

Advanced encryption standard is detailing for data crypto graphing. The algorithm used universally for cryptography and secure data transmission, the algorithm puissant to intruders, who often attack via side channels. One of the observed attacks was estimate the power implanted in AES core and processed probable scrutinizing to guess the key on multiple iterations. So in order to elude side channel attacks and reduce power consumed in AES standard, design proposed with masking and pipeline scheme. This design helps in shrinking power consumption as compare to AES algorithm and upgrade to withstand from attacks. Another major improvement in the design is LUT’s used for masking and original algorithm almost equal, area phenomenon also solved out. The proposed algorithm implemented in VERTEX-7 FPGA board and simulated using Xilinx Vivado 2015.2 and Modelsim.
Big Data Mining Based on Computational Intelligence and Fuzzy Clustering

The availability of a huge amount of heterogeneous data from different sources to the Internet has been termed as the problem of Big Data. Clustering is widely used as a knowledge discovery tool that separate the data into manageable parts. There is a need of clustering algorithms that scale on big databases. In this chapter we have explored various schemes that have been used to tackle the big databases. Statistical features have been extracted and most important and relevant features have been extracted from the given dataset. Reduce and irrelevant features have been eliminated and most important features have been selected by genetic algorithms (GA). Clustering with reduced feature sets requires lower computational time and resources. Experiments have been performed at standard datasets and results indicate that the proposed scheme based clustering offers high clustering accuracy. To check the clustering quality various quality measures have been computed and it has been observed that the proposed methodology results improved significantly. It has been observed that the proposed technique offers high quality clustering.
Reconnaissance Phase

In warfare, “reconnaissance” is the process of collecting information about enemy forces using different detection methods. In ethical hacking, reconnaissance is the first phase targeted to gather and learn as much as information available about the target using tools like internet sources, social engineering techniques, dumpster diving, email harvesting, Whois database, etc. This chapter introduces different tools and techniques used during the active and passive reconnaissance phases in detail. Reconnaissance consists of footprinting, scanning, and enumeration techniques used to covertly discover and collect information about a target system. During reconnaissance, an ethical hacker attempts to gather as much information about a target system as possible. It can use active (by directly interacting with the target which have risk of getting caught like social engineering methods) or passive (like visiting target website) information-gathering methods in order to identify the target and discover its IP address range, network, domain name, mail server, DNS records, employee names, organization charts, and company details. The chapter also provides the details of possible countermeasures to be implemented on website to avoid revealing more information to the attackers.