Reviewerly/exHarmony huggingface dataset:
Study on the optimisation ability of natural selection mechanism

In recent years, evolutionary algorithms have developed rapidly and become an important method for solving complex and nonlinear optimisation problems. Many evolutionary algorithms, such as differential evolution algorithm (DE), artificial bee colony algorithm (ABC) and brainstorming algorithm (BSO), adopt the natural selection principle of 'survival of the fittest' to determine the individuals of new populations. For a long time, researchers regard the selection operator as an important part of maintaining the evolution of the algorithm, and seldom distinguish the optimisation ability of the selection operator. In fact, the natural selection operator also has some abilities to optimise. For this reason, this paper takes DE algorithm as an example to construct different DE variants, and compares the optimisation results of them with the standard DE algorithm. Simulation results show that the new algorithm which only using natural selection can achieve certain optimisation results, meanwhile, DE algorithm which removing its greedy selection operator only has poor performance. This proves that natural selection operator has certain optimisation ability. Theoretical analysis shows that natural selection mechanism can determine a searching baseline during evolution and make exploration and exploitation fuse with each other.
Managing social work according to the educational philosophy of Ho Chi Minh City University of Technology and Education

This article helps administrators, social workers to see the reality and difficulties in organizing, managing and implementing social activities for students at the Ho Chi Minh City University of Technical and Education - a school that does not specialize in social work, but there are diverse and diversified community-oriented activities.
Fourier Series

Unique in its clarity, examples, and range, Physical Mathematics explains simply and succinctly the mathematics that graduate students and professional physicists need to succeed in their courses and research. The book illustrates the mathematics with numerous physical examples drawn from contemporary research. This second edition has new chapters on vector calculus, special relativity and artificial intelligence and many new sections and examples. In addition to basic subjects such as linear algebra, Fourier analysis, complex variables, differential equations, Bessel functions, and spherical harmonics, the book explains topics such as the singular value decomposition, Lie algebras and group theory, tensors and general relativity, the central limit theorem and Kolmogorov's theorems, Monte Carlo methods of experimental and theoretical physics, Feynman's path integrals, and the standard model of cosmology.
Video Summarization Based on Gaussian Mixture Model and Kernel Support Vector Machine for Forest Fire Detection

Exponential growth in the generation of multimedia data especially videos resulted to the development of video summarization concept. The summary of the videos offers a collection of frames which precisely define the video content in a considerably compacted form. Video summarization models find its applicability in various domains especially surveillance. This paper intends to develop a video summarization technique for the application of forest fire detection. The proposed method involves a set of processes namely convert frames, key frame extraction, feature extraction and classification. Here, a Merged Gaussian Mixture Model (MGMM) is applied for the process of extracting key frames and kernel support vector machine (KSVM) is employed for classifying a frame into normal frame and forest fire frame. The simulation analysis is performed on the forest fire video files from FIRESENSE database and the results are assessed under several dimensions. The final outcome proves the efficiency of the presented MGMM-KSVM model in a considerable way.
Vector Isolated Minimum Distance Filtering for Image De-Noising in Digital Color Images

Image de-noising forms a crucial component of digital image processing. The state-of-the-art vector median filtering based image de-noising approaches like the median filtering, the vector median filtering and the basic vector directional filtering and their extensions process the vector pixels jointly in the red, green and blue components. Consequently any smoothing applied therein is leveraged on all the color components equally. In this paper we propose that processing the vectors in isolation, that is, each color component taken separately, and then smoothed by minimising the aggregate distance between the pixels in each color component will lead to more efficient de-noising of noisy images. We demonstrate the superiority of the proposed method compared against vector filtering approaches using several images and test measures.
Machine Learning based Twitter Sentimental Analysis in Business Field

iSocial inetworking isites ilike itwitter ihave imillions iof ipeople ishare itheir ithoughts iday iby iday ias itweets. iThis ipaper iaddresses ithe iproblem iof isentiment ianalysis iin itwitter; ithat iis iclassifying itweets iaccording ito ithe isentiment iexpressed iin ithem: ipositive, inegative ior ineutral. iTwitter iis ian ionline imicro-blogging iand isocial-networking iplatform iwhich iallows iusers ito iwrite ishort istatus iupdates iof imaximum ilength i140 icharacters. iIt iis ia irapidly iexpanding iservice iwith iover i200 imillion iregistered iusers, iout iof iwhich i100 imillion iare iactive iusers iand ihalf iof ithem ilog ion itwitter ion ia idaily ibasis i- igenerating inearly i250 imillion itweets iper iday. iDue ito ithis ilarge iamount iof iusage iwe ihope ito iachieve ia ireflection iof ipublic isentiment iby ianalyzing ithe isentiments iexpressed iin ithe itweets. iAnalyzing ithe ipublic isentiment iis iimportant ifor imany iapplications isuch ias ifirms itrying ito ifind iout ithe iresponse iof itheir iproducts iin ithe imarket, ipredicting ipolitical ielections iand ipredicting isocioeconomic iphenomena ilike istock iexchange. iThe iproject iis ito idevelop ia ifunctional iclassifier ifor iaccurate iand iautomatic isentiment iclassification iof ian iunknown itweet istream.
<i>Environmental Science: Atmospheres</i> joins the Environmental Science journal family

Neil Donahue, Editor-in-Chief, and Anna Rulka, Executive Editor, introduce the inaugural issue of Environmental Science: Atmospheres .
Pembelajaran Bahasa Sastra Melalui Pemberdayaan Kompetensi Guru

Language has a central role in students' intellectual, social and emotional development. Languages ​​support students' success in learning all fields of study. Therefore, language learning must be interesting and fun for students. Indonesian language and literature learning in some schools is still not in accordance with what is expected. Teachers tend to use theoretical learning techniques so learning is rigid and boring. As a result, Indonesian language and literature have not yet become lessons that students enjoy. Literature teachers have not been able to use compelling methods. Many literary teachers lack sufficient interest and talent regarding literature. The impact of failure on students in developing, language skills, and positive attitudes towards Indonesian language and literature.&#x0D; Improving the quality of Indonesian education in the era of globalization must be comprehensive or comprehensive, emphasizing the implementation of the autonomy of education management, by creating various ways to achieve the objectives of national education as a whole and to immediately catch up with other countries. A tool to measure the success of a learning that is teachers who are innovative, creative and can choose the right learning points.&#x0D; Steps to become a creative teacher include (1) becoming an explorer of the mind, (2) developing questions (3) developing as many ideas as possible, and (4) creating an interesting and fun learning model
Early Validation of Functional Requirements and Transition to Source Code with Event-B

The cost of fixing software requirements errors after deployment is so high that it is vital to come up with ways to find and fix requirements errors early in the life-cycle of a project. The work in this paper advocates for the use of formal methods as an alternative approach to guarantee the correctness of the software from requirements to code. We present a formal-methods based approach for the early validation of functional requirements. Our approach relies on formal methods techniques such as program refinement, correctness-by-construction (CbyC), and automated code generation. We present two case studies that showcase our approach; for the case studies, we discuss design decisions, flaws encountered, and lessons learned.
Challenges encountered with the use of mobile phones to deliver public health services in the Greater Accra Region of Ghana- A qualitative study

Abstract Background The adoption and application of medical technologies is one of the six health system building blocks of the World Health Organization that ensures access and quality of health services for which the mobile phone is identified as a potential tool due to its general adoption and use by people, including healthcare providers. In spite of this there are some challenges that restrict the opportunities that the mobile phone technology could offer for delivery of public health services. This study explored the challenges encountered in the use of the mobile phone to deliver public health services in the Greater Accra Region of Ghana. Methods Qualitative research approach was employed in the study and data analysis done conducted with the use of NVIVO version 11 software package to facilitate thematic analysis of data. Results The key findings of the challenges encountered by healthcare providers in the provision of public health services comprised Management and leadership, Finance, Access, Infrastructure, Technical and Human resources. Conclusions The implication of this study is that despite the high adoption of the mobile phone by healthcare providers, there were also key challenges constraining the uptake of mHealth for public health services. A new analytical framework was developed to aid analysis of mHealth Challenges.
Particle Smoothing

SummaryThis chapter describes particle smoothing algorithms, i.e. algorithms to compute the distribution of past states Xt−k given data y0:t for a given state-space model.An important distinction is between on-line algorithms and off-line algorithms. On-line algorithms are able to perform smoothing at every time t, at a cost that stays constant over time. They are said to be “forward-only”, as they process the data recursively (in the same way as a particle filter).Off-line algorithms compute the smoothing distribution of a fixed data-set y0:T. They consist of running a particle filter forward in time, from t = 0 to t = T, then doing some type of backward pass, from time t = T to time 0. That prevents these algorithms to be used in any realistic on-line scenario.Off-line algorithms may be further decomposed into two classes of algorithms: backward sampling algorithms, and two-filter smoothing algorithms. These two classes correspond to the two decompositions of the smoothing distribution that we derived at the end of Chap. 5.It will become quickly apparent that smoothing is a more difficult task than filtering. The practical implication is that naive algorithms tend to degenerate quickly (i.e., for k large), while less naive algorithms are either expensive (i.e., have a \(\mathcal {O}(N^2)\) complexity) or specialised (to a certain class of functions, or to state-space models fulfilling certain conditions), or both. In particular, most smoothing algorithms are restricted to state-space models such that the process {Xt} admits a tractable transition density.
Improved Logarithmic Search for Efficient Video Compression

For efficient video compression, the BMAs should be designed and implemented in such a way that that the Motion Estimation takes very less time and will have lesser complexity. In this paper, two new algorithms namely Improved Logarithmic Search (ILS) and Zero motion predicted ILS (ZMILS) are proposed which are based on the basic idea of Three Steps Search (TSS) algorithm. In these BMA, the search pattern of proposed algorithms changes the efficiency both in terms of complications required for each macro block (MB) and quality of the compensated images. We improved the TSS and NTSS by changing the searching pattern of locations in reference frame and by adding no movement early prediction case with these algorithms we further reduced the computations. The computations required by the new developed algorithm are lesser per macro block and even 50% of few existing techniques while retaining the quality of the reconstructed image.
PENGEMBANGAN PERANGKAT PEMBELAJARAN IPA DENGAN MENGGUNAKAN METODE BRAINSTORMING UNTUK MENINGKATKAN BERPIKIR KRITIS DI KELAS V SEKOLAH DASAR

ABSTRACTResearch on this development was intended to produce device learning of a syllabus, lesson plans, sheets of students activity, book students, and tests the ability of think critically students on subjects science class grade 5 second semester. The kind of research this namely research the development of which reference on the model 4D, with stage define, design, development and disseminate. Subject research is the primary school grade 5. Research instruments composed of sheets assessment validity syllabus, lesson plans, sheets of students activity, book students, and tests the ability of think critically. Based on the results they actually obtained (1) syllabus developed valid with a value of 4.10 criteria perfectly valid (2) lesson plans developed valid with a value of 4,25 criteria perfectly valid (3) sheets of students activity developed valid with a value of 4.3 criteria perfectly valid (4) books students who developed valid with a value of 4,25 criteria perfectly valid (5) tests the ability of think critically developed valid with a value of 4.45 criteria perfectly valid. The results of research tests the ability to think critically students obtained the percentage completion of achievement 96,83% the average value of 80.Keywords: device learning, brainstorming, the ability to think critically.ABSTRAKPenelitian pada pengembangan ini bertujuan untuk menghasilkan perangkat pembelajaran yang berupa silabus, rencana pelaksanaan pembelajaran (RPP), lembar kegiatan siswa (LKS), buku siswa, dan tes kemampuan berpikir kritis siswa pada mata pelajaran IPA kelas V semester 2. Jenis penelitian ini yaitu penelitian pengembangan yang mengacu pada model 4D, dengan tahapan Define, Design, Development dan Disseminate. Subyek penelitian adalah siswa-siswi SD kelas V. Instrumen dalam penelitian terdiri dari lembar penilaian validitas silabus, RPP, LKS, buku siswa, dan tes kemampuan berpikir kritis. Berdasarkan hasil penilaian diperoleh (1) silabus yang dikembangkan valid dengan nilai 4,10 dengan kriteria sangat valid. (2) RPP yang dikembangkan valid dengan nilai 4,25 dengan kriteria sangat valid. (3) LKS yang dikembangkan valid dengan nilai 4,3 dengan kriteria sangat valid. (4) Buku siswa yang dikembangkan valid dengan nilai 4,25 dengan kriteria sangat valid. (5) tes kemampuan berpikir kritis yang dikembangkan valid dengan nilai 4,45 dengan kriteria sangat valid. Hasil penelitian untuk tes kemampuan berpikir kritis siswa diperoleh presentase ketuntasan prestasi 96,83% dengan nilai rata-rata 80.Kata Kunci: Perangkat pembelajaran, brainstorming, kemampuan berpikir kritis.
An Enhance Scheme of Visual Secret Share for Lossless Recovery

Algorithms in Visual Cryptography usually uses a sharing scheme where instead of sharing the secret or message directly, it is embedded into multiple shares which are then shared between the intended individuals whereby upon receiving them the decrypting algorithm on the receiving end restores the original secret. A novel cryptographic scheme will not only hide the data, but also will do it in an efficient way which will further ensure that the algorithm is robust to noises and attacks. The proposed algorithm utilizes bitwise operations for efficient hiding of data. Also, it is important that the secret image is losslessly recovered.
Book Review(s)

This study examined the Twitter streams and websites of 36 university innovation centers and identified 14 service categories the centers offered. Exploring the present Twitter use practices of innovation centers and the services the centers provide can inform the design and planning of service offerings at new innovation centers and support training for center staff in the use of this social media platform. In addition, existing innovation centers can benchmark their service offerings against those services. Furthermore, mapping the services the innovation centers offer to the activities in an innovation workflow model can help center managers optimize the information architecture of their websites and resource guides. In this way, students can easily be informed about the help and resources available for each activity or phase of the innovation process. A comparison of the tweet categories identified in the present study with those of academic libraries assembled in a previous study revealed significant overlap, but some differences as well. In contrast to the Twitter accounts of academic libraries, the Twitter accounts of innovation centers did not tweet about their information services even if they offered them. Innovation centers also did not use Twitter to provide Q&A services to their users. Furthermore, innovation centers tweeted not only about the technological resources they provided, but also about the human resources they recruited to serve as student mentors and advisors. Finally, technology use was more mediated in innovation centers than in libraries, and some centers offered their users fee-based assistance from professionals with their 3D design and printing tasks.
Retracted: Traffic identification and traffic analysis based on support vector machine

The above article, published online on 2nd June 2019 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors, the journal Editors, David W. Walker, Jinjun Chen, Nitin Auluck and Martin Berzins, and John Wiley and Sons Ltd. The retraction has been agreed due to inaccuracies in the data resulting in foundational errors throughout the article that are beyond the scope of an erratum. The main reason being that support vector machine (SVM) algorithm is mainly used to solve small sample problems, the efficiency and accuracy will be affected if there are too many eigenvectors in the network data stream. Another error is that the network traffic classification method based on SVM is not a very good method.1
Is it a Cyber Security Strategy for Social Development?

Digital technologies have continued to transform economies; however, many developing countries are yet to exploit their benefits for social development. These benefits bring out good governance, secure interactive services, and sustainable growth. In conjunction with the World Bank, the National Bureau of Statistics (Nigeria) in 2019, reported that 83 million people lived below the national poverty line. It is also reported by the United Nations Development Programme that the cause of ravaging poverty in Nigeria which has roughly 136 million internet users which amounts to 66 percent of the reported 205 million populations in 2020, is cyberspace abuse. By 2030 the United Nations expects countries to have embraced the spread of Information and Communication Technologies and global interconnectedness which accelerates human progress, bridges the digital divide, and develops knowledge societies. This paper explores the potential of the cyberspace strategy for Nigeria to support social development. Among the results the paper presents is the extent to which digital technologies are being used and can be adapted to improve education, health, and political processes. The paper concludes by assessing the impact of social development brought about by the cyberspace strategy of Nigeria. [191]
TL;DR

Can law keep up with runaway technology? In an era of runaway corporate surveillance, artificial intelligence, deep fakes, election hacking, social media disinformation, do-it-yourself biology, genetic modification, automation, and three-dimensional printed medical implants, law has seemed to take a back seat to rampant technological change. To listen to Silicon Valley barons, there is nothing any of us can do about it.CAN LAW KEEP UP? calls their bluff. The book provides a fresh look at law, at what it actually is, how it works, and how we can create the kind of laws that help humans survive and thrive in the face of technological change. It shows that law can keep up with technology because law is a kind of technology – social technology built by humans out of cooperative fictions like firms, nations, or money. To survive the challenges of the future, we need a new kind of law, and a new way of understanding how humans use language to cooperate, to build an ever-growing and ever-changing system of understandings about how we can secure the benefits of changing technology to all.
Optimized Multi-layer Machine Learning Technique for Movement Detection and Tracking in Video Data Stream

With the advent in technology, security and authentication has become the main aspect in computer vision approach. Moving object detection is an efficient system with the goal of preserving the perceptible and principal source in a group. Surveillance is one of the most crucial requirements and carried out to monitor various kinds of activities. The detection and tracking of moving objects are the fundamental concept that comes under the surveillance systems. Moving object recognition is challenging approach in the field of digital image processing. Moving object detection relies on few of the applications which are Human Machine Interaction (HMI), Safety and video Surveillance, Augmented Realism, Transportation Monitoring on Roads, Medical Imaging etc. The main goal of this research is the detection and tracking moving object. In proposed approach, based on the pre-processing method in which there is extraction of the frames with reduction of dimension. It applies the morphological methods to clean the foreground image in the moving objects and texture based feature extract using component analysis method. After that, design a novel method which is optimized multilayer perceptron neural network. It used the optimized layers based on the Pbest and Gbest particle position in the objects. It finds the fitness values which is binary values (x_update, y_update) of swarm or object positions. Method and output achieved final frame creation of the moving objects in the video using BLOB ANALYSER In this research , an application is designed using MATLAB VERSION 2016a In activation function to re-filter the given input and final output calculated with the help of pre-defined sigmoid. In proposed methods to find the clear detection and tracking in the given dataset MOT, FOOTBALL, INDOOR and OUTDOOR datasets. To improve the detection accuracy rate, recall rate and reduce the error rates, False Positive and Negative rate and compare with the various classifiers such as KNN, MLPNN and J48 decision Tree.