Reviewerly/exHarmony huggingface dataset:
The Internet of Things

The technology space has seen the emergence of several buzzwords, including but not limited to artificial intelligence, big data, the internet of things, and robotics. This chapter seeks to discuss the concept of the internet of things and break the very gigantesque details into understandable bits. It examines the concept of the internet of things from the standpoint of a legal practitioner who is practicing in any given jurisdiction and talks about the legal issues that attend the internet of things. Due to the fact that the internet of things refer to the interconnectivity of devices, the legal issue of data privacy and protection is discussed. Other issues like antitrust and ‘who-bears-liability' are also equally discussed. A brief insight is equally given along the lines of how these legal issues preclude the smooth rolling out of these technologies in cross-border terms and how industry players are attempting to deal with the issues.
Application of improved ant colony algorithm in mobile robot path planning

Aiming at the shortcomings of slow convergence speed and many turning points of the traditional ant colony algorithm in the global path planning of mobile robot, an improved ant colony algorithm is proposed. By adding obstacle information to improve the distance heuristic function, the probability of ants entering the deadlock path is reduced, and the number of effective search is increased. The adaptive adjustment strategy is used to design the dynamic adjustment mechanism of pheromone heuristic factor, which improves the development of the algorithm in the initial stage and takes into account the convergence in the later stage. The second search strategy is introduced to simplify the path points of ant colony algorithm and reduce the redundancy. Experiments show that the improved algorithm has good adaptability in complex environments, and the comprehensive performance index of the final path is better than that of the traditional algorithm, which can provide effective reference for the global path planning of robots in practical environments.
Education of the region in the conditions of the pandemic

Achieving a real breakthrough in the development of the economy of the country, of a particular region implies the introduction of innovative technologies into the regional education system of the constituent entities of the Federation. In the context of the coronavirus pandemic, it is necessary to apply mixed teaching methods, adjust curricula and ensure the preservation of the health of students and teachers. The analysis of the implementation of the indicators of the state program and subprograms of education development for 2020 is carried out. The structure of budget expenditures for 2019–2020 is considered.
Object detection algorithm based on improved Faster R-CNN

Aiming at the problem of the classic two-stage object detection algorithm Faster R-CNN that it is difficult to fully extract and fuse multi-scale features, an improved Faster R-CNN algorithm based on switchable atrous convolution and involution is proposed. This method first replaces the 3×3 convolution in the feature extraction module with a switchable atrous convolution to better capture the original rich information of the feature; then, replaces the 3×3 convolution in the feature fusion module with an involution further enhances the feature fusion effect at different stages. In order to test the detection effect of the algorithm, experiments were carried out on the MS COCO data set and the PASCAL VOC data set. Compared with the improved Faster R-CNN algorithm, the average precision of the proposed algorithm on the two data sets is improved by 5.5% and 2.2%, respectively. Among them, for the detection of larger objects in the COCO data set, the effect is improved more significantly.
Method for Analyzing Complex Natural Data and Detecting Anomalies

A method for analysing natural data of a complex structure based on the use of wavelet data decomposition operations and their combination with threshold functions is proposed. By using adaptive thresholds, operations for noise suppression and detection of anomalous changes in data are built. The implementation operations of the method are described and the application of neutron monitors to data is shown. We used data from the network of ground stations of neutron monitors (www.nmdb.eu), which are secondary cosmic rays. Anomalies in cosmic rays can create a radiation hazard, cause failures in radio communications, as well as defects in the operation of satellites, leading to loss of orientation and destruction. Therefore, the task of timely diagnosis of such events is relevant. The application of the method made it possible to clearly detect and evaluate anomalous changes in cosmic ray data that were observed during disturbed periods in the magnetosphere.
Other Online Tools for Fostering Creativity

This chapter introduces readers to a number of different online apps to help in facilitating creative technology activities. The chapter begins with an overview of the Chrome Music Lab suite of apps and the many possibilities this collection enables with a particular focus on what is possible with the app Song Maker. It also explores the creative possibilities of Incredibox Beepbox, ModBox, and Paint Composer. A discussion on sequencers and online drum machines follows. Drum machines such as GroovePizza, Drumbit, and 808303.studio are explored for their creative potential. A plethora of ideas are presented throughout the chapter to get learners being creative.
Questions of Time: Simultaneity, Attunement

This chapter considers the inverse perspective, namely the ways in which literature enacts or models simultaneity and convergence. It reviews some fictional experiments in achieving effects of simultaneity, and then turns to convergence. The example chosen (the vanishing of Posthumus’ ship from view as reported to Imogen by Pisanio in Shakespeare’s <italic>Cymbeline</italic>) is primarily optical, featuring the mechanics of vergence, but it serves to introduce the notion of ‘attunement’ as a central feature of cognitive process. The discussion in Chapters 5 and 6 of language in time necessarily has a psychological aspect that emerges, for example, in the discussion of ‘echoic’ effects in Chapter 5 as well as in the Shakespearean example of perceptual attunement. This psychological dimension points already towards the topic of Chapter 7.
Preliminary application of GF-7 satellite data in geological survey in Hami Area

The GF-7 satellite has high spatial resolution. This article compares GF-7, GF-1 and GF-2 in terms of image color effect, spectral resolution and feature difference, and makes a preliminary evaluation of the accuracy of remote sensing geological structure interpretation and lithology information recognition based on GF-7 data. The results show that GF-7 can accurately identify geological bodies, and it can be used to carry out remote sensing geological information extraction from 1:5,000 to 1:20,000.
A novel real-time positioning system with high-precision based on spot detection

This article researches on a real-time positioning and tracking system based on spot detection in order to measure deflection of bridges with high frame rate and accuracy, and introduces a method of adaptive threshold for locating the centroid of a spot. The efficient threshold can be captured by the way and then helps to search the ROI as well as to segment the image, which makes the system can operate in most environment under various lighting conditions. The system has reached accuracy level of 𝟏𝒎𝒎 and frame rate of 𝟏𝟎𝟎𝒇𝒑𝒔(frames per second) in simulated experiments, which prove the system is available in measurement for deflection of bridges.
The Change in the Societal Forms of the Banje-ri Settlement

The Banje-ri remain in Anseong is a highland settlement characterized by its circular ditches around the mountain top in which it is located. Constructed around the early Iron Age, there were a relatively large number of residential areas, with a total of 72. According to carbon 14 dating, the time it was constructed is estimated to be from BC the 8 to 5th century and this range also overlaps with the late Bronze Age, the time the Songguk-ri Culture was constructed. Furthermore, Anseong is in the outermost region of the Songguk-ri culture. This paper aims to examine the societal change of Banje-ri settlement during the early Iron Age in its relation to the contemporary Sogguk-ri society under the assumption that it could reveal certain aspects of the Sogguk-ri Culture. According to the complementary serration method applied to all the excavated artifacts, five developmental stages of the settlement were distinguished. This chronology was then verified through the examinations of the artifacts’ stratigraphical relations. Stage I-a is characterized by seven houses from which the artifacts produced in the middle Bronze Age were excavated. These houses had long rectangular shapes for large families and were dispersed across the large area. Stage I-b is characterized by a small number of long rectangular houses and more middle/small-sized houses for nuclear families. The early Iron Age culture was prevalent in this stage but the artifacts from the middle Bronze Age and Songguk-ri Culture were also found. The ratio of middle and small-sized houses in Stage II is 1:1. It was also when the household communities, consisting of one middle-sized house and one or two small-sized house(s) for each, were appearing. From then onwards, the early Iron Age culture prevailed while middle-sized houses gradually disappeared. Stage III was when the circular ditches were built. A large-sized house for ritual was located on the inside rim of the ditches surrounding the mountain top with a huge rock. One large-sized house, two middle-sized houses, and a few small-sized houses were located outside of the ditches. The large-sized house inside of the ditches was functioning a major role in the ritual and is assumed to be resided by the elite of the settlement. The ditches disappeared in Stage IV and two middle-sized houses and four small-sized houses existed then. Three tombs were constructed in the two graveyards formed in the lower slope. From the fact that the circular ditches were to demarcate the ritual place for the worship of the heavenly god, it is inferred that there was a natural disaster threatening people’s lives in Stage III. This event is also assumed to be related to the climate deterioration the Songguk-ri settlement underwent and the flood that swept the Jijwa-ri settlement
Integrating System Dynamics with Data Science via Graphical User Interface

This paper builds on the PySD project, which seeks to bring together System Dynamics and Data Science by migrating models into a programming environment in Python. The authors develop an interactive tool, built on top of the PySD module as a step toward accessibility, which helps further the ability of (1) simulation to be intuitive for non-experts and (2) Data Science to facilitate model structure understanding. This tool is meant to serve as a conduit through which Data Science can be leveraged in Systems Dynamics modeling efforts.
Multi-Scale Flow-Based Occluding Effect and Content Separation for Cartoon Animations

Occluding effects have been frequently used to present weather conditions and environments in cartoon animations, such as raining, snowing, moving leaves, and moving petals. While these effects greatly enrich the visual appeal of the cartoon animations, they may also cause undesired occlusions on the content area, which significantly complicate the analysis and processing of the cartoon animations. In this article, we make the first attempt to separate the occluding effects and content for cartoon animations. The major challenge of this problem is that, unlike natural effects that are realistic and small-sized, the effects of cartoons are usually stylistic and large-sized. Besides, effects in cartoons are manually drawn, so their motions are more unpredictable than realistic effects. To separate occluding effects and content for cartoon animations, we propose to leverage the difference in the motion patterns of the effects and the content, and capture the locations of the effects based on a multi-scale flow-based effect prediction (MFEP) module. A dual-task learning system is designed to extract the effect video and reconstruct the effect-removed content video at the same time. We apply our method on a large number of cartoon videos of different content and effects. Experiments show that our method significantly outperforms the existing methods. We further demonstrate how the separated effects and content facilitate the analysis and processing of cartoon videos through different applications, including segmentation, inpainting, and effect migration.
Picture Fuzzy Set Theory Applied to UP-algebras

The concept of picture fuzzy sets was first considered by Cuong and Kreinovich [6] in 2013, which are direct extensions of fuzzy sets and intuitionistic fuzzy sets. In this paper, we applied the concept of picture fuzzy sets in UP-algebras to introduce the eight new concepts of picture fuzzy sets: picture fuzzy UP-subalgebras, picture fuzzy near UP-filters, picture fuzzy UP-filters, picture fuzzy implicative UP-filters, picture fuzzy comparative UP-filters, picture fuzzy shift UP-filters, picture fuzzy UP-ideals, and picture fuzzy strong UP-ideals. The link between the eight new concepts of picture fuzzy sets in UP-algebras is also discussed.
Despeckling of SAR image using curvature optimization

Due to the coherence of the scattering phenomenon, synthetic aperture radar (SAR) images are contaminated by multiplicative speckle noise, which seriously affects the interpretation and identification of SAR images. In this paper, we introduce the curvature filters which are realized by constructing tangent planes and correcting the regularization energy into speckle noise suppression of SAR images. Compared with the ROF model, the guided filter and some classic SAR image filtering algorithms (such as Lee filter), the curvature filters show strong competitiveness in the computing time, the peak signal-to-noise ratio (PSNR) and the structure similarity (SSIM) index. In addition, we compared the performance of the three curvature optimization models of the curvature filters, and found that the total variational filter model performs better in dealing with speckle noise of SAR images, which shows that the construction of local half-window and the assumption of piecewise constant for SAR images are robust to speckle noise suppression and structure preservation.
Parallel computing model based on python in quantitative analysis

The calculation of serious technique index and using historical data is an important cornerstone for back test of trading strategy. It is a critical step that how to complete this calculation and test in determine the ultimate success of quantitative analysis. On the basis of python multiprocessing library, this paper proposes and implements a multi-process parallel computing model which is light-weight and easy-using. This model abstracts the multi-process concurrent computing as a base class which is used for all kinds of index calculation and history back tests to be independent operated. It could reduce the coupling between various strategies calculation and make full use of the CPU resources that effectively improve the computing speed of back testing strategy as well as provide a reliable guarantee for quantitative analysis.
Dark Web for the Spread of Illegal Activities Using Tor

The dark web has been in existence since about the emergence of the internet. There is still a wealth of material indexed on the web that is freely available to anyone with internet connection, regardless of region. There is even more information and data that is concealed and needs specific rights to access. Tor is well-known and extensively used anonymity software that is built on the Tor network and provides secrecy over the vulnerable web. The personal data defense is generally beneficial. This chapter provides a brief summary of established methods to gain access to this section of the web as well as examples of its talents being abused.
Intellectual Property

This chapter discusses the history and theory of intellectual property and its ethical, political, and legal foundations. It provides an overview of the U.S. intellectual property system, including discussions of patents, copyrights, trademarks, trade secrets, and ownership of research data. This chapter also examines utilitarian and rights-based rationales for protecting intellectual property and considers some moral objections to intellectual property protections. This chapter reviews some instrumental pieces of legislation and legal cases pertaining to intellectual property and discusses some ethical controversies concerning particular types of intellectual property, such as patents on computer programs and algorithms, DNA sequences, and biological materials.
Securing 5G Slices using Homomorphic Encryption

Network slicing is a powerful tool that provides 5G and future networks a robust means for managing cross-application QoS, dynamic traffic migration in response to network events, and in-network data aggregation and computation. Unfortunately, slicing inherits many of the security challenges of cloud and edge computing such as side-channel information leakage, while also encountering new challenges posed by multi-domain authorization and quantum computing. Many extant mechanisms, such as PKI, are insufficient in the face of quantum computers, and existing side-channel mitigations impose heavy overhead costs while only providing defense against known attacks. In this paper, we describe a novel approach to protecting slice control information through the use of Homomorphic Encryption (HE). HE allows quantum-resilient validation and distribution of critical information, while also enabling hierarchical control across multiple domains and providing encrypted computation. Further, threshold HE enables secure decryption and computation of control or measurement information, while protecting the entire slice against potential key-leakage by rendering any one key useless without the required quorum. The benchmark results shown demonstrate that the HE mechanisms used can be deployed in a practical manner, providing stalwart security guarantees against a variety of threats.
An Effective Hybrid Stochastic Gradient Descent Arabic Sentiment Analysis with Partial-Order Microwords and Piecewise Differentiation

Instagram, Facebook, and Twitter, among other online platforms, have become an inescapable part of our daily lives. These social media platforms are capable of exchanging news, photographs, and other contents. The sentiment analysis on these online data has risen in popularity recently, particularly in Arabic. Unusual language, which differs from the typical format of the language, distinguishes social networking platforms. As a consequence, efficient methods for assessing the vast number of new word permutations that occur on a regular basis in the digital and online environment are required. This paper presents a sentiment classification model relying on microwords and Stochastic Gradient Descent (SGD). Different effectiveness evaluation measures are used to estimate the performance of the suggested model. The suggested method effectively classifies the verification and testing tweets collection with an accuracy of equal to 88.48 percent, as per the simulation findings.
A scaling calculus for the design and initialization of ReLU networks

We propose a system for calculating a “scaling constant” for layers and weights of neural networks. We relate this scaling constant to two important quantities that relate to the optimizability of neural networks, and argue that a network that is “preconditioned” via scaling, in the sense that all weights have the same scaling constant, will be easier to train. This scaling calculus results in a number of consequences, among them the fact that the geometric mean of the fan-in and fan-out, rather than the fan-in, fan-out, or arithmetic mean, should be used for the initialization of the variance of weights in a neural network. Our system allows for the off-line design & engineering of ReLU (Rectified Linear Unit) neural networks, potentially replacing blind experimentation. We verify the effectiveness of our approach on a set of benchmark problems.
Basement depth re-valuation of anomalous magnetic bodies in the lower and middle Benue trough using Euler deconvolution and spectral inversion techniques

Spectral technique and Euler Deconvolution were applied to high-resolution aeromagnetic data of parts of Benue trough to estimate the depth of anomalous magnetic sources within the study area; Data enhancement techniques such as total magnetic intensity map, reduction to pole, regional-residual separation and upward continuation maps were employed to identify different magnetic anomalies, structural trends representing the tectonics of the location were observed trending NE-SW and N-S directions; The result of 3D Euler deconvolution for the structural index (SI) = 0, 1, 2, 3 gave depths to magnetic sources that range from -589;3 m to -2678;8 m, -459;0 m to -2691;9 m, -294;6 m to -2817;5 m, - 430;2 m to -2780;6 m respectively; The depth estimates from 2-D spectral revealed a two-layer model; The shallow magnetic depth ranges between 0;135 km to 0;200 km with a mean depth of 0;158 km and the depth to magnetic basement vary between 2;585 km to 4;878 km with a mean depth of 3;415 km; This result, therefore, indicates that the average basement depth of the study area obtained from the spectral analysis is 3;415km; This investigation, therefore provides appropriate sedimentary thickness for suitable hydrocarbon prospecting within the study area.
Online E-Clinic Service System

In Today’s time the health is a priority factor to all. The medical sector proven very useful in pre and post corona time. But people’s fears to visit hospitals as there were possibility of spreading of diseases in the hospital. Peoples mostly consider consulting doctors on calls or chats. Our application focuses on the same issue and creates a medium of communication between doctor and patients via call.
Building The New Onto The Old: Category Constraints on Category Formation

It is generally accepted that the process of forming a new category is biased by the learner’s prior knowledge. In this context, numerous studies and models have paid attention to the effects of prior domain theories on the process of forming new categories. What is yet to be understood is how this process of acquiring new knowledge might be affected by background knowledge of the very same type, i.e. by prior categories. This paper presents a few experiments showing how the formation of new categories might be facilitated by a high overlap between the new and the old categories, where overlap is operationalized as the mutual entropy between the two.