Reviewerly/exHarmony huggingface dataset:
Ολική Βελτιστοποίηση: Μέθοδος της Διαφορικής Εξέλιξης και Παραλλαγές

In this work we deal with the optimization of problems of nonlinear functions using the method of Differential Evolution.This thesis consists of 7 chapters and an Appendix with the description of the minimization problems with a known minimum that we use to apply the Differential Evolution Algorithm.The first chapter, which is introductory, refers to the concept of optimization, the mathematical formulation of optimization problems as well as the concept and properties of the objective function.The second chapter refers to optimization methods, which are classified based on specific characteristics. This chapter also refers to some basic principles of optimization methods as well as the properties that define their quality. Moreover, the chapter summarizes a few basic optimization methods. These methods are: The Newton-Raphson method, Steepest Descent, Random Walk, multistart techniques and the Simulated Annealing method.The third chapter describes the Evolutionary Algorithms. Differential Evolution is a member of these algorithms. The methodology and the operators of Genetic Algorithms are also described in this chapter.The fourth chapter presents the Differential Evolution Algorithm. The methodology of the classical Differential Evolution method is described as well as the role and importance of the control parameters of the algorithm.The fifth chapter deals with the different strategies of the of the Differential Evolution method and the notation DE/x/y/z. The strategies are described and numerical examples are given for each one of them.The sixth chapter is a brief description of a few Differential Evolution variants, such as JDE, JADE and SADE.Finally, in the seventh chapter, we conduct some experiments by applying the Differential Evolution algorithm to a set of test problems. In these experiments, the values of the control parameters are adjusted in order to make a comparative study using8the outcomes. Mathematica and C programming language were used for the experiments.
The vortex atoms

In the middle of the nineteenth century, the emergence of vortices in fluids was a challenging topic. Mastering vortices in the laboratory with coloured smoke or water had become accessible since the late 1850s, but these sporadic experiments did not help to provide an insight into the laws of vorticity. Thus, theoreticians tried to grasp the problem mathematically; first and foremost, Hermann von Helmholtz, in his seminal and widely recognized paper in 1858, postulated the existence of vortices based on vortex strings (Wirbelfäden) in an ideal fluid – a frictionless and incompressible fluid with constant density. Because of these idealized conditions Helmholtz arrived at a similarly idealistic vortex theory claiming the eternal existence of vortices in ideal fluids. If vortex strings in ideal fluids, e.g. the ether, exist in perpetuity, then vortices are assumed to be more perennial then atoms. It was William Thomson, the later Lord Kelvin, who pleaded vortex atoms with “infinitely perennial specific quality”. These observations led to the development of an early “string theory”. Although completely illusory, this string theory occupied the greatest minds of this time.
LibGuides: DBA - Management and Instruction: Accounting

This LibGuide is intended to provide a library research home base for students enrolled in the Benson School of Business DBA program for Management and Instruction.
Anonymization via Clustering of Locations in Road Networks

Author(s): Haunert, Jan-Henrik; Schmidt, Daniel; Schmidt, Melanie | Abstract: Data related to households or addresses needs be published in an aggregated form to obfuscate sensitive information about individuals. Usually, the data is aggregated to the level of existing administrative zones, but these often do not correspond to formal models of privacy or a desired level of anonymity. Therefore, automatic privacy-preserving spatial clustering methods are needed. To address this need, we present algorithms to partition a given set of locations into k-anonymous clusters, meaning that each cluster contains at least k locations. We assume that the locations are given as a set T ⊆ V of terminals in a weighted graph G = (V, E) representing a road network. Our approach is to compute a forest in G, i.e., a set of trees, each of which corresponds to a cluster. We ensure the k-anonymity of the clusters by constraining the trees to span at leastterminals each (plus an arbitrary number of non-terminal nodes called Steiner nodes). By minimizing the total edge weight of the forest, we ensure that the clusters reflect the proximity among the locations. Although the problem is NP-hard, we were able to solve instances of several hundreds of terminals using integer linear programming. Moreover, we present an efficient approximation algorithm and show that it can be used to process large and fine-grained data sets.
On Finger Stretching and Bending Dynamics as a Biometric Modality

Studies on the characterization of the dexterity of fingers and hands improve the understanding of how humans interact with computing devices. In this study, finger bending patterns captured by flex sensors worn on the fingers are characterized to build a biometric authentication system. The modality uses an array of resistive sensors fitted in a smart glove worn by users while typing. The study encompasses 55 users, 23 of them entered a 9-digit PIN on a laptop’s number pad, and 32 of them typed a 10-length alphanumeric password on the full-sized keyboard. The results demonstrate that the users are authenticated using features built from the flex sensors relating to their PIN and password with a mean EER score of 7.49% and 9.76%, respectively. We further assessed the potential of using individual fingers to authenticate users in both the biometric systems and found that even the fingers not used for typing exhibited discriminative patterns due to movement dynamics during the typing process. This assessment highlights the potential for designing lightweight biometric modalities utilizing dexterity and patterns based on fewer fingers.
About Efficient Algorithm for Factoring Semiprime Number

The complexity needed to factor large semiprime numbers is in the heart of public key cryptography. It is very important to identify cases where semiprime factorization can be done efficiently. This article introduce mathematical method for semiprime factorization. Hopefully it will help researchers to close further gaps and make public key cryptography safer [1,2].
Neural Networks and Deep Learning

Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this text includes methods that were chosen for their relevance, simplicity, and generality. Topics range from introductory to research-level material, making it accessible to advanced undergraduate and beginning graduate students from the engineering and physical sciences. The second edition features new chapters on reinforcement learning and physics-informed machine learning, significant new sections throughout, and chapter exercises. Online supplementary material – including lecture videos per section, homeworks, data, and code in MATLAB®, Python, Julia, and R – available on databookuw.com.
Versatile Photonic Entanglement Synthesizer in the Spatial Domain

Multimode entanglement is an essential resource for quantum information. Continuous-variable encoding in the optical domain has recently yielded large temporal and spectral entangled states [1] . We present results [2] - [4] that re-establish spatial encoding as a contender in the game of continuous-variable quantum information processing i.e. strategies to generate and engineer multimode entangled states at the outputs of nonlinear waveguide arrays ( Fig. 1a ). Such states are especially interesting because they are by nature distributable in real quantum networks and protocols. In addition, scalability, reconfigurability, subwavelength stability, reproducibility, and low cost make our scheme an appealing quantum technology with respect to bulk-optics-based multipartite-entanglement approaches.
化学气相沉积法制备低镁含量的MgxZn1-xO纳米线紫外光电传感器

To solve the problem that ZnO ultraviolet photosensors is poor in detecting deep ultraviolet light, a method of fabricating Mg doped ZnO nanowires was proposed to adjust the ZnO energy band, so as to improve the sensitivity of ZnO ultraviolet photosensors in detecting deep ultraviolet light. The MgZnO nanowires were characterized by scanning electron microscope(SEM), energy spectrum analysis(EDS), transmission electron microscope(TEM) and other characterization methods. The results show that MgZnO nanowires were successfully prepared. The ZnO nanowire detector and the Mg doped ZnO nanowire detector were test with the 254 nm deep ultraviolet light, and the test results show that the photoresponse of the Mg doped ZnO detector to the 254 nm deep ultraviolet light was enhanced, the photocurrent increased from 0.02 μA to 0.57 μA. The detector is prepared by Mg doped ZnO nanowires, which can effectively improve the ZnO nanowires detectability in detecting deep ultraviolet light. It will provide beneficial reference for the design and preparation of deep ultraviolet detectors.
Promena kao oblik trajanja i uslov opstanka: Imperativ prilagođavanja u svetu svekolikih promena

Universality of change is a way of formulating the fact that all entities capable of being observed and even thought of – individuals, their variously formed groups, the society, the world of ideas and consciousness in maximally imaginable number of variegated forms and locations and the universe itself – are subject to change. Speaking of change is tantamount to speaking about all conceivable forms of existence and therefore about the universe of all things we encounter, create or imagine. These are the reasons because of which the subject of change – as a matter of principle – cannot ever be exhaustively treated.
A Bayesian Convolutional Neural Network for Robust Galaxy Ellipticity Regression

Cosmic shear estimation is an essential scientific goal for large galaxy surveys. It refers to the coherent distortion of distant galaxy images due to weak gravitational lensing along the line of sight. It can be used as a tracer of the matter distribution in the Universe. The unbiased estimation of the local value of the cosmic shear can be obtained via Bayesian analysis which relies on robust estimation of the galaxies ellipticity (shape) posterior distribution. This is not a simple problem as, among other things, the images may be corrupted with strong background noise. For current and coming surveys, another central issue in galaxy shape determination is the treatment of statistically dominant overlapping (blended) objects. We propose a Bayesian Convolutional Neural Network based on Monte-Carlo Dropout to reliably estimate the ellipticity of galaxies and the corresponding measurement uncertainties. We show that while a convolutional network can be trained to correctly estimate well calibrated aleatoric uncertainty, -the uncertainty due to the presence of noise in the images- it is unable to generate a trustworthy ellipticity distribution when exposed to previously unseen data (i.e. here, blended scenes). By introducing a Bayesian Neural Network, we show how to reliably estimate the posterior predictive distribution of ellipticities along with robust estimation of epistemic uncertainties. Experiments also show that epistemic uncertainty can detect inconsistent predictions due to unknown blended scenes.
Register Transfer Level Disparity generator with Stereo Vision

This tool can generate binary files for Xilinx FPGAs for “Stereo Vision-based disparity generation”. With related vendor tools this project can be ported to other types of FPGAs (such as Intel technology). Implementation is done using VHDL and Verilog hardware description languages. The tool is available in 3 stages 1). Functional Verification 2). Stereo Camera integration 3). Disparity Generation. Documentation is available for users who are interested in modifying for different platforms. Components that are used during physical setup are explained in the documentation and based on the requirements they can be changed. In order to use this tool, the user must have prior experience in hardware description languages, experience in Xilinx tools will be an additional advantage.
Aerial Image Enhanced by Using Dark Channel Prior and Retinex Algorithms Based on HSV Color Space

Enhancing aerial images plays an important role in many remote sensing applications; aerial images are often affected by dust, smoke and fog. In this paper, a new algorithm was proposed to improve aerial images. The proposed algorithm using Dark Channel Prior (DCP) to enhance the color compounds only in HSV space and a Multiscale Retinex (MSR) using to enhance the lightness component in the same space. To know the efficiency of enhancement aerial images, the no-reference quality measures as Natural Image Quality Evaluator (NIQE) and Wavelet Quality Evaluator (WQE) Have been calculated, which are used to see the quality of the proposed method in comparison with DCP, Histogram equalization (HE), Image Entropy and Information Fidelity (IEIF) and Multiscale Retinex with color restoration (MSRCR). Through the analysis of the results, it is found that the proposed method has succeeded in improving aerial images better than other methods.
Unpacking the Score: Fluxus and the Material Legacy of Intermediality

It is October 1959. I am visiting George Brecht’s just opened exhibition at the Reuben Gallery in New York. Titled toward events: an arrangement and displaying various objects as propositions, the exhibition is difficult to classify—it is neither an “object exhibition” nor can one really see “performances” (Fig. 1).[1] The “toward” in the title suggests an experiment; the “arrangement”— a musical connotation. In fact, the concepts presented here have been derived from music. The objects are treated like scores. Before putting up his show, Brecht—a chemist by profession and an intriguing personality—had worked for various US companies such as Johnson and Johnson, authoring five U.S. patents and two co-patents, feminine tampons among others. His move towards fine arts coincided with his attendance at John Cage’s classes at the New School for Social Research, known for propagating new approaches to composing sound, music, and noise. As a result of his studies, Brecht conceives of textual notations of varying lengths that allow a great deal of freedom in their execution. These works stand apart from his contemporary Allan Kaprow’s instructions for Happenings that, more prescriptive, constrained room for improvisation (see, for instance, his 18 Happenings in 6 Parts from 1959). In his creative practice, Brecht also differs markedly from Cage, who organizes everyday sounds into musical compositions. Instead, Brecht accepts everyday situations, chance events, and “all occurrences” that might result from an encounter between the participants and the objects as a legitimate outcome. (Here, my use of the word “participants” rather than “viewers” emphasizes the subjects’ engagement over the passive, disembodied viewing.) Brecht wants to ensure that “the details of everyday life, the random constellations of objects that surround us, stop going unnoticed.”[2] To present these details, constellations, or occurrences in the context of a creative, authorial project, Brecht writes scores for them—an important aspect of my present contestation with the material legacy of Fluxus.
Implementation Of The K-Means Cluster Algorithm In Rice Production Mapping And As A Decision Support For Agricultural Function Transition

According to the Food and Agriculture Organization of the United Nations (FAO) in 2014 Indonesia ranked 3rd with a total rice production of 70.6 million tons, but it still remains a rice importing country. As one of the districts known as rice barn, Sukoharjo is targeted to continue to increase crop productivity every year to keep up with the growing population, so it is necessary to know areas with less optimal yields, and minimize changes in agricultural land use change. A mapping method for harvest results is needed to group data in each region based on the similarity of harvest data. In data mining, clustering techniques are known that can be used to map harvest productivity data based on their similarity. This study applies clustering techniques using the KMeans algorithm to map rice harvest productivity data by dividing data into 3 groups, namely many, medium, and less. The research method used is SDLC (Software Development Life Cycle) with a waterfall model. The K-Means algorithm is implemented using website-based programming to map harvest productivity data using attributes of planting area and rice production. The results of the mapping are visualized into a recommendation of agricultural land clustering and agricultural products as well as one of the decision makers in the transfer of agricultural functions so that subdistricts that have a lot of productivity, are moderate and lacking based on the characteristics of the data
Membangun Budaya Literasi dengan Memanfaatkan Media Digital Instagram

In today's digital era, technological developments have advanced society and caused many changes in various aspects of life. Digital developments also have an impact on literacy culture, which causes reading materials to only be used as extensions. People are more interested in their smart devices than other reading materials. This happens because everything is already available on their smart devices as an example of digital development. By using their gadgets, they no  longer need to carry printed books, reading materials can be accessed easily anywhere and anytime. The existence of this phenomenon can be used to improve the literacy culture of the community by utilizing digital developments. The task of education circles through the current learning process is not only to emphasize strengthening old literacy capacities, but also strengthening new digital literacy capacities. Literacy is more than just reading, when we read the events that occur around us, literacy can also be realized, because literacy is also the ability of everyone to use their skills.
Kindy talk free workshop

5 June 2021- The Centre for Modern Languages’ Kindy Talk Team successfully organised a 3-hour free online workshop on Using Technology for Early Childhood Educators via Google Meet from 9 a.m. to 12 p.m. with 17 early childhood educators, many of whom are from Kuantan and 3 as far as from Selangor and Kelantan.
Non-EFL Students Vocabulary Learning Strategies

As development progresses, international competition and cooperation cannot be avoided.  This phenomenon will encourage students to participate in it.  Therefore, the ability to speak English is an important component to be involved in this phenomenon.  Various countries in the world have been competing to apply English to their children from an early age.  This study will focus on students' perceptions of vocabulary strategies in learning English.  This study involved 32 participants from different universities and data collection was done through a questionnaire.  The results showed that the participants liked to use learning strategies, and they agreed that using strategies in learning could improve the quality of vocabulary learning.  As well as train their language skills, reasoning abilities, and understanding of the content of word use.  Even though they are not consistent with just one strategy, from the data, presented, they almost ever do all the strategies offered.
A Weibo Recommendation Algorithm Integrating User Interests

A Weibo recommendation algorithm integrating user interests is studied in this manuscript. Among the algorithms based on content similarity recommendation, the LDA algorithm is one of the most used and classic algorithms. Therefore, this paper uses the LDA algorithm to mine the user interest distribution and uses the cosine similarity algorithm to calculate the similarity between the general microblog to be recommended and the user's interest. The proposed algorithm is designed by considering the similarity of user interest based on the semantic level and the similarity of the social relationship based on the follow relationship are then considered, a better recommendation effect can be achieved. To validate the model, the proposed algorithm is simulated on the data collected from the Weibo. The accuracy is higher than before.
Subject Guides: COM 1330: WEBSITES & SPEECHES

Research tips and recommended sources for COM 1330 students working on Informational and Persuasive Speeches
MENINGKATKAN HASIL BELAJAR TEMA 7 MELALUI MODEL PEMBELAJARAN PROBLEM BASED LEARNING KELAS V

THE IMPROVEMENT OF LEARNING OUTCOMES OF THEME 7 BY USING PROBLEM BASED LEARNING MODEL IN GRADE V STUDENTS This research is motivated by the low learning outcomes of fifth grade Empang 2 elementary school students in theme 7. Only 64,29% of the total number of students in the class achieved KKM. This is caused by students tend to be passive in learning as well as conventional learning models which are less uplifting and students learning interested to understand the material comprehensively. To overcome these problems researchers provide a solution by implementing the Problem Based Learning model in the learning process. This study aims to improve learning process and learning outcomes of students in theme 7 grade V elementary school through the PBL model. The research method used was classroom action research with Kemmis and MC Taggart models conducted in 2 cycles. The participants of this study were grade VA students in Empang 2 elementary school Bogor with 29 students. Data was collected using an observation sheet and also a worksheet. The results showed that the average value of students' learning outcomes increased from 73,3 in the first cycle to 85,71 in the second cycle. Likewise with students' mastery learning, in the first cycle 64,29% increased significantly to 89,3% in the second cycle. In addition learning process in first cycle to second cycle had been improvement significantly, this can be seen from the activeness of students during learning process is very high. The data above shows that the application of the PBL model is effective for improving learning outcomes of students in theme 7 grade V in elementary school.
Smart Contract Security and Privacy Taxonomy, Tools, and Challenges

Blockchain smart contract technology implementations are growing rapidly. The resilient and accurate design of smart contracts for these intelligent applications however is a huge challenge because of the complexities involved. Smart Contract modernizes traditional processes of production, technology, and industry. It is self-verifiable, self-executable, and enclosed in Blockchain that removes the demand of trustworthy mediator. The major issue that needs to be addressed to make smart contract successful is security and privacy issues. In the paper, a survey was conducted on available taxonomy for security and privacy concerns and a new taxonomy proposed that could accommodate all potential threats. A detailed review of available security and privacy audit tools has also been done for common smart contract platforms. At last, identified the challenges required to be addressed to make the smart contract more efficient.
A template for useful proof of work

Cryptocurrencies and numerous other dispersed frameworks use agreement calculations so as to accomplish concession to information. The calculation utilized by Bitcoin and numerous different cryptog...