Reviewerly/exHarmony huggingface dataset:
A COMPARATIVE STUDY OF PROFESSIONAL ATTITUDE OF SECONDARY SCHOOL TEACHERS

The role of teachers in society is vital. Dr. Sarvapalli Radhakrishnan said, "Teacher's place in society is of vital importance." He acts as a pivot for the transmission of intellectual, traditional and technical skills from generation to generation and helps to keep the lamp of civilization burning and shining. He not only guides individuals, but also decides the destiny of the Nation. The status of teachers reflects the socio-cultural ethos of the society. It is said that no pupil can rise above the level of its teachers. The present article is an attempt to find out the dependable answer to the question raised previously. Adjustment and professional attitude are two interdependable variables which influence behaviour of male and female teachers.
3D Object Tracking using Growing Neural Gas with Different Topologies

3D perception system of an autonomous robot is one of the most important technologies for performing tasks in an unknown environment. This paper proposes a real-time 3D object tracking method based on Growing Neural Gas with Different Topologies (GNG-DT). First of all, we explain a GNG-DT for learning the topological structures from the 3D point cloud data with multiple properties such as color and normal vector information. Next, we propose a real-time 3D object tracking method from the topological structure by utilizing the center of gravity in each cluster. Finally, we show some experimental results of the proposed method and discuss the effectiveness of the proposed method.
Manage the Problem

With time invested in exploring and categorizing crucial organizational assets and a crisp cybersecurity goal articulated, the problem being solved is, at the very least, understood: cybersecurity risk to critical assets. Now, managing that cybersecurity risk has a better chance for success than managing without a clear understanding of the problem.
Constructive system for double-spend data detection and prevention in inter and intra-block of blockchain

Currently, our global financial market faces lots of trouble due to migration from fiat currency to cryptocurrency and its underlying blockchain technology. Blockchain provides trust in a decentralised way for storing, managing, and retrieving the transactions. The double-spending issue arises due to the erroneous transaction verification mechanism in the blockchain. Research has shown that transaction malleability like double-spending creates millions of bitcoins losses to the owners as well as few bitcoin exchanges. This research aims to detect and prevent the double-spending of bitcoins in single and multiple blocks. In this context, double-spend data in a single block is identified using the DPL2A method. Further, the original transaction from the double-spend transaction list is identified using the ACRT method which acts as a prevention of double-spend in a forthcoming occurrence. Similarly, double-spend data in multiple blocks are identified using MBDTD along with the Cognizant Merkle tree. Finally, a system named F2DP is constructed to detect and prevent the double-spend data in inter and intra blocks of the blockchain. The result indicates these methods will act best for double-spend detection and prevention with a limited set of transaction records. Further research is needed to increase the scalability of transaction records.
Evaluation of VR Training System Focusing on Batting Eye

We approach from the two viewpoints of spatial accuracy and temporal accuracy, and our main goal is to improve the batting ability of beginners and to enable batting in actual battles. It is considered difficult for beginners to improve their abilities for environmental reasons. If a training method using a VR system is established, this can be resolved and sports can be enjoyed more easily. In addition, since visual sports training using a VR system has not been sufficiently researched, we believe that it can be used as a new sports vision training by verifying its effects and finding its usefulness. Based on these facts, this research focuses on spatial accuracy from the two perspectives of temporal accuracy and spatial accuracy, and aims to develop a system that improves the ability of the batting eye using VR technology. To do.
Obstacle Avoidance Control for Multi Robots via Imitative Learning and Reinforcement Learning.

This paper proposes an obstacle avoidance control for multi robots. The control use an imitative learning and reinforcement learning. The imitative learning is learned by Optimal Reciprocal Collision Avoidance, and the reinforcement learning is learned based on e-greedy. Simulation results via 4robots are shown in order to validity the control.
3D Reconstruction of Structure Based on Image Sequence for Supporting Operator in Decommissioning

We have developed a 3D reconstruction method based on image sequences recorded by remotely operated robots for decommissioning. This paper describes the quantitative method for evaluating reconstruction accuracy of a 3D model generated by Structure from Motion. We verify the performance of the 3D reconstructed model based on an image sequence. As a result, we confirmed that the reconstruction accuracy of 3D models can be quantitatively evaluated by comparing with a 3D point cloud measured by a laser scanner as ground truth.
Feminism, Privacy, and Law in Cyberspace

Abstract Feminism has long centered on breaking down the public and private divide that traditionally organized social relations and subordinated women. Privacy is lauded for giving women space for self-determination, but it is also criticized for creating spaces where patriarchy and misogyny can flourish unchecked. Cyberspace heightens the stakes of this tension because it creates almost limitless access to people’s personal data. We live in a datafied society powered by digital profiling, automated decisionmaking, and surveillance systems in which we no longer control our personal data; rather, it is used to control us. Women face multiple, gendered harms in cyberspace, including online harassment, digital discrimination, and sexual surveillance by the “femtech” industry. Yet the United States lacks comprehensive privacy laws, and its analog-era antidiscrimination statutes are no match for the digital world. American privacy protections hinge upon a notice-and-consent regime that puts the onus on users to protect their privacy rather than the entities that benefit from gathering individual’s personal data. Women and other marginalized people have suffered through a loss of privacy in the digital age, but activists have made efforts to ameliorate the harms of cyberspace and to shape privacy norms in a feminist and inclusive manner. It is important to understand the meaning of privacy through four waves of feminist theorizing and activism, to analyze how American privacy law responds to major gender equity challenges in cyberspace, and to examine current feminist theories and models of resistance.
Versioning, Paging, and Sor ting

In this chapter we will discuss the following:
COVID-19 Pandemic and Higher Education in Nigeria: The Reality and a Call for Sustainable Digitalization

Considering its derivable benefits, the significance of higher education to the production of societal skilled work force cannot be overemphasized.Education at this level is instrumental to a just and egalitarian society, hence, its continuous relevance to national development.However, global emergency health challenge truncates teaching-learning activities across all levels of education, higher education inclusive.The challenges include school closure, distortion of academic calendar and students' loss of access to formal physical learning environment.This paper, therefore, explores the reality of COVID-19 pandemic on Higher Education in Nigeria.Viewing this through the lens of global health challenge, with specific domestication to Nigeria, the paper was based on secondary data, sourced from existing resources, using the desk research method to establish how COVID-19 has disrupted Higher education activities.The paper contributes to knowledge, provides justification for accurate, reliable and evidence-based practical accounts of Higher Education Institutions activities during pandemic and advocates for an introduction of a sustainable digitalization of higher education services.This is with a view to promoting the deployment and applications of digital solutions (such as Learning Management System, Microsoft teams, ClassDojo, Google meet, Zoom, Google classroom, Moodle and others) for teaching, learning and other higher education management activities in Nigeria.
Deep Learning of Adaptive Control Systems Based on a Logical-probabilistic Approach

The problem of automatic selection of subgoals is currently one of the most relevant in adaptive control problems, in particular, in Reinforcement Learning. This paper proposes a logical-probabilistic approach to the construction of adaptive learning control systems capable of detecting deep implicit subgoals. The approach uses the ideas of the neurophysiological Theory of functional systems to organize the control scheme, and logical-probabilistic methods of machine learning to train the rules of the system and identify subgoals. The efficiency of the proposed approach is demonstrated by an example of solving a three-stage foraging problem containing two nested implicit subgoals
Motion of Multiple Robot in a Curved Boundary &amp; Obstacles

An attempt is made in this paper to gain the flexibility of movement of robots around the boundary of the workspace, where in many robots are moving at a time in the presence of the static curved obstacles. The boundary of the workspace may be a straight line or curve shaped. The obstacle may be polygonal or curved shaped. A program is developed for the motion of the multiple robots to move from its origin location to the desired location without colliding with the boundary, the other moving robots and the static obstacles. The program is based on the curve fitting technique. As and when the robot comes close to the curved boundary or curved barrier, it will trace the path formed by the curve equation using the technique of curve fitting. Since there are multiple robots, the path planning ensures the robots to reach their targets in minimum time. During tracing the path, if more than one robot is following the same path, priority is assigned to such robots. Multiple robots finds application in assembly operations, medical supplies and meals to patients, disinfecting the rooms for patients etc.
Accept or Take Control?

We show how to create an informational norm that constrains the use of proxies in AI-driven surveillance. The norm creates privacy in public by implementing conditions on the flow of information that controls the use of that information as proxy variables There are a variety of possible conditions. The task is to choose one that implements an acceptable tradeoff between informational privacy and information processing. The norm we propose ensures that the use of proxies is fair and to that extent implements an acceptable tradeoff between informational privacy and information processing. There is, of course, more to finding such a tradeoff than just ensuring that the use of proxies is fair, and the process we describe creates a forum for addressing tradeoff issues in general.
A Survey of the Combinatorial Paraphernalia in Protein Synthesis

Statement of the Problem: The combinatorial paraphernalia in protein synthesis to be surveyed are multifarious, embracing, phenomena, processes, activities and materials, all characterized by plurality and dissimilarity. The materials usable are phenomenal and must be a set of discrete plural and dissimilar objects, e.g. the RNA four bases of Adenine, Uracil, Guanine, Cytosine (A,U,G,C) for the activity of permutation for building genetic code. Sequences for protein type sequence composition, proliferation and diversification as inherent in protein synthesis. Methodology and Theoretical Orientation: We are in for combinatorics which is the scientific study of the phenomenon of input/output productivity exhibited by a duality of numeral entities as in permutation of specified set (n) of dissimilar discrete plural. Things and selection (r) of them. The Dalina apparatus of Input/Output Multiplicative Replication system equipped with Square Kinematics View Mixing Technique sourced from inchoate Numeration Science literature being developed by this author is in use for the computation of 4 from 4 permutations of RNA four bases, A,U,G,C constituting the 24 quadruplet genetic code as the workforce in protein synthesis. Findings: The combinatorial paraphernalia in protein synthesis identified and surveyed comprise 14 characteristics, 3 materials and 11 processes/operatives. Conclusion and Significance: The relevance of the several identified and surveyed combinatorial paraphernalia in protein synthesis has been demonstrated by the test of agreeability with the working of the Dalina apparatus of Input/ Output Multiplicative Replication Combinatorial System using the Square Kinematics View Mixing technique for the computation of permutations of RNA four bases A,U,G,C making up the 24 quadruplet genetic code as the workforce in protein synthesis for the substance of all plants and animals throughout CREATION.
Superposition Display of Soft Tissue using Mixed Reality Technology for a Laparoscopic Surgery Support System

A laparoscopic surgery is a minimally invasive surgery that reduces the burden on the patient. However, main disadvantage of the laparoscopic surgery is the narrowness of the field of view provided by an endoscopic camera. Therefore, if an organ is damaged by a surgical instrument outside the field of view, it is easily overlooked. To support the laparoscopic surgery, surgical navigation systems have been developed so far. However, conventional navigation systems provide information based on the preoperative medical images, and hence the gaps between the actual surgical situation and the navigation information become larger as the surgery proceeds. This paper proposes a method of providing predicted information on the endoscopic images. In this method, the movements of surgical instruments are measured by a motion capture system. The dynamic deformation of an organ caused by the contact between a surgical instrument and the organ is simulated and presented by superimposing the CG model on the endoscopic image. In the superposition display experiment, the superposition of the deformed flexible cube and its 3D model was confirmed.
The Effect of 3D Image Virtual Reconstruction Based on Visual Communication

Considering the problems of poor effect, long reconstruction time, large mean square error (MSE), low signal-to-noise ratio (SNR), and structural similarity index (SSIM) of traditional methods in three-dimensional (3D) image virtual reconstruction, the effect of 3D image virtual reconstruction based on visual communication is proposed. Using the distribution set of 3D image visual communication feature points, the feature point components of 3D image virtual reconstruction are obtained. By iterating the 3D image visual communication information, the features of 3D image virtual reconstruction in visual communication are decomposed, and the 3D image visual communication model is constructed. Based on the calculation of the difference of 3D image texture feature points, the spatial position relationship of 3D image feature points after virtual reconstruction is calculated to complete the texture mapping of 3D image. The deep texture feature points of 3D image are extracted. According to the description coefficient of 3D image virtual reconstruction in visual communication, the virtual reconstruction results of 3D image are constrained. The virtual reconstruction algorithm of 3D image is designed to realize the virtual reconstruction of 3D image. The results show that when the number of samples is 200, the virtual reconstruction time of this paper method is 2.1 s, and the system running time is 5 s; the SNR of the virtual reconstruction is 35.5 db. The MSE of 3D image virtual reconstruction is 3%, and the SSIM of virtual reconstruction is 1.38%, which shows that this paper method can effectively improve the ability of 3D image virtual reconstruction.
New perspectives on deep neural networks in decision support in surgery

The paper considers the development of a neural network system for predicting complications after acute appendicitis operations. A neural network of deep architecture has been developed. As a learning set, a set developed by the authors based on real clinic data was used. To select significant features, a method for selecting features based on the interquartile range of the F1-score is proposed. For preliminary processing of training data, it is proposed to use an overcomplete autoencoder. Overcomplete autoencoder converts the selected features into a space of higher dimension, which, according to Cover's theorem facilitates the classification of features according to complication and not corresponding to complication. To overcome the overfitting of the network, the dropout method of neurons was used. The neural network is implemented using the Keras and TensorFlow libraries. Trained neural network showed high diagnostic metrics on test data set.
Encourage Learning

A complex problem almost always involves interacting elements. Fully addressing just one element does not take into account how that one element interacts with the other elements. The goal is to create a whole that is made up of interacting parts.
Query Language

The Jakarta Persistence API provides two methods for querying entities—the Jakarta Persistence query language (Jakarta Persistence QL) and the Criteria API.
Gestures in ensemble performance

Gestures, defined as meaning-bearing bodily actions, play important and varied roles in ensemble performance. This chapter discusses how the term “gesture” differs from physical “motion” and perceived “action.” The functional differences between sound-producing, sound-facilitating, sound-accompanying, and communicative actions are presented, alongside how these can be performed and/or perceived as meaning-bearing gestures. The role of gestures in ensemble performance is examined from four perspectives: (1) ensemble size and setup; (2) the musical degrees of freedom of the ensemble; (3) the musical leadership; and (4) the role of machines in the musicianship. It is argued that the use of gestures varies between different types of ensembles and musical genres. The common denominator is the need for meaning-bearing bodily communication between performers, with such gestures also playing an important part in the musical communication with the audience.
POLYNOMIAL ALGORITHM FOR QUADRATIC FORMS CLASSIFICATION USING GAUSSIAN ELIMINATION

Existing methods for quadratic forms classification have exponential time complexity or use approximation that weaken the result reliability. We develop an algorithm that improves the best case of quadratic form classification in constant time and is polynomial in the worst case. In addition, new strategies were used to guarantee the results reliability, by representing rational numbers as a fraction of integers and to identify linear combinations that are linearly independent using Gaussian Elimination.DOI: 10.36558/rsc.v11i3.7391
Chris Cundy: Crude Attempt

December 01 2021 Chris Cundy: Crude Attempt Chris Cundy: Crude Attempt. Seth Rozanoff Seth Rozanoff Amsterdam, The Netherlands Search for other works by this author on: This Site Google Scholar Author and Article Information Seth Rozanoff Amsterdam, The Netherlands [Editor's note: Selected reviews are posted on the Web at http://www.computermusicjournal.org (click on the Reviews tab). In some cases, they are either unpublished in the Journal itself or published in an abbreviated form in the Journal.] Digital download, 2020, available from https://chriscundy.bandcamp.com/album/crude-attempt Online Issn: 1531-5169 Print Issn: 0148-9267 © 2021 Massachusetts Institute of Technology.2021MIT Press Computer Music Journal (2021) 44 (4): 77–78. https://doi.org/10.1162/comj_r_00584 Cite Icon Cite Permissions Share Icon Share Twitter LinkedIn Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Seth Rozanoff; Chris Cundy: Crude Attempt. Computer Music Journal 2021; 44 (4): 77–78. doi: https://doi.org/10.1162/comj_r_00584 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest search filter All ContentAll JournalsComputer Music Journal Search Advanced Search You do not currently have access to this content.
Research Progresses of Wavelet Methods and Their Applications in Mechanics

The wavelet theory shows very unique time-frequency localization and multi-resolution analysis ability in signal processing and function approximation. The wavelet basis function has excellent mathematical properties such as orthogonality, compactness, low-pass filtering and interpolation, which endows the wavelet analysis theory with great application potential in the fields of computational mathematics and computational mechanics, and creates new opportunities for breakthrough development in these fields. Since the 1990s, a large number of studies have proved that the numerical method based on the wavelet theory has very obvious advantages in solving differential equations, but at the same time, have exposed some limitations of numerical calculation application caused by the wavelet basis function itself and its unique approximation method. In order to promote the innovative application of the wavelet theory in the fields of computational mathematics and mechanics and provide researchers with a new research perspective, the development background of the wavelet analysis and the research history of methods based on the wavelet theory were reviewed, and the numerical method problems were emphasized and the research progresses made in recent years discussed. The conclusions and comments may provide a meaningful reference for the further development and improvement of quantitative mathematical solution methods based on the wavelet theory and applications in mechanics as well as solutions of a wide range of engineering problems.
Evolving a robot controller for a robotic swarm by TWEANN

This paper focuses on Topology and Weight Evolving Artificial Neural Network (TWEANN) approaches for designing controllers of a robotic swarm. TWEANN approaches are expected to design not only synaptic weights but also the appropriate network topology without the intervention of the designers. Mutation-Based Evolving Artificial Neural Network(MBEANN) is a TWEANN algorithm that only use mutations to evolve neural networks. In this paper, we applied MBEANN to design the controller for a robotic swarm. For comparison with the MBEANN approach, we used the NeuroEvolution of Augmenting Topologies (NEAT), which is a widely used TWEANN algorithm.The performance and the topology of robot controllers are compared in collective foraging tasks. The results show that MBEANN could perform as well as NEAT with smaller network topologies.
Using Forms and Group Boxes

When you fill out paper forms, you may notice that the paper forms group related items together. For example, the form may ask for your name, address, and phone number in one area of the form and ask for your gender, racial background, or marital status in another area of a form. Paper forms make it easy to enter related data in one area.