Reviewerly/exHarmony huggingface dataset:
Investigation on the Possibility of Using Available Sunshine Duration Data of a Relatively Close Region to Estimate Global Solar Radiation for a Different Region

Estimation of global solar radiation using existing models becomes necessary in areas where measurements are not carried outdue to lack of technical knowledge, unavailability of measuring instrument and cost of getting such measurements if available.In this study, the possibility of estimating the global solar radiation for a particular location using another location&amp;#39;s sunshine duration data is explored due to the closeness in the latitude of the two locations and to what extent is the estimation true.&nbsp; Ibadan&amp;#39;s (latitude 7.37750N) sunshine duration data is used as Iwo&amp;#39;s (latitude 7.62920N) sunshine duration data and employed in the Angstrom - Prescott&amp;#39;s sunshine based model, while retaining the latitude of Iwo in the model, mean sunset/rise hour angle and extraterrestrial radiation. The sunshine duration data for Ibadan (2008 - 2012) was gotten from International Institute of Tropical Agriculture, Ibadan while the measured global solar radiation data for Iwo (2014 - 2015) was measured at Bowen University Iwo, Osun state in Nigeria. The estimated global solar radiation for Iwo is validated with measured global solar radiation at Iwo by carrying out some statistical analysis like mean bias error (-0.03), root mean square error (0.81), mean percentage error (-0.23), Nash-Sutcliffe error (r2) or coefficient of determination (0.88), coefficient of correlation (0.94). The estimated values when validated against the measured values performed excellently well. Hence it is possible to use the available sunshine duration data of another location as the sunshine duration data when estimating the global solar radiation available at the location of interest.
Investigating the Efficiency of Functionalized PAMAM-GO Nano-Composite for Nitrate Removal from Aqua Solutions

Due to the high solubility of nitrate in water, conventional treatment methods fail to remove it. This research investigated for the first time in national and global level, the efficiency of functionalized PAMAM-Go nanocomposite for nitrate removal from aquatic solutions. GO was synthesized by modified Hummers method. AFM images were used to characterize the GO and the AGO. Experiments were performed in a batch reactor and the main factors of pH, reaction time, and concentration of PAMAM_GO were investigated. The highest removal efficiency was obtained as 84% at 5 mL/L functionalized PAMAM_GO, pH of 3 and 25 min reaction time. The results showed that nitrate removal by functionalized PAMAM-Go nanocomposite is directly correlated with nanocomposite concentration and contact time while it is inversely correlated with pH and initial concentration of nitrate. It seems that ion exchange between nitrate and chloride is the main mechanism of nitrate removal by functionalized PAMAM_GO nano composite according to functionalization of PAMAM-Go using hydrochloric acid. This method can be used as a suitable method for in situ treatment of nitrate and many  pollutants in water and wastewater, due to its easy operation, no need for high levels of expertise and sophisticated equipment, no need for large space of construction, low initial investment, low price, availability of raw materials, simple synthesis of graphene oxide and  easy  to functionalize.
Resurrection of the Dead and the Organization of the Society of Electronic e-Beings.

Alexander Bolonkin in his works [1-7] proposed methods of electronic immortality of modern people. He predicted the gradual replacement of biological humanity E-beings, considered their advantages and disadvantages (see List of references in given articles). The author considers methods and modern possibilities of resurrection of long-dead outstanding personalities. It also considers the principles and organization of the new E-society, its goals and conditions of existence.
Generalized Elliptical Slice Sampling with Regional Pseudo-priors

In this paper, we propose a MCMC algorithm based on elliptical slice sampling with the purpose to improve sampling efficiency. During sampling, a mixture distribution is fitted periodically to previous samples. The components of the mixture distribution are called regional pseudo-priors because each component serves as the pseudo-prior for a subregion of the sampling space. Expectation maximization algorithm, variational inference algorithm and stochastic approximation algorithm are used to estimate the parameters. Meanwhile, parallel computing is used to relieve the burden of computation. Ergodicity of the proposed algorithm is proven mathematically. Experimental results on one synthetic and two real-world dataset show that the proposed algorithm has the following advantages: with the same starting points, the proposed algorithm can find more distant modes; the proposed algorithm has lower rejection rates; when doing Bayesian inference for uni-modal posterior distributions, the proposed algorithm can give more accurate estimations; when doing Bayesian inference for multi-modal posterior distributions, the proposed algorithm can find different modes well, and the estimated means of the mixture distribution can provide additional information for the location of modes.
NEXT GENERATION SYSTEM ASSISTANT

One of the goals of Artificial intelligence (AI) is the realization of natural dialogue between humans and machines. In recent years, the dialogue systems, also known as interactive conversational systems are the fastest growing area in AI. This paper also presents an assistance system for helping deaf-mute people or elderly singletons. The proposed system assists deal-mute people or elderly singletons in the shortest possible time to report, the report also uses SMS intimate to achieve offline report. This paper also proposes a novel approach to defining and simulating a new generation of virtual personal assistants as multi-application multi-domain distributed dialogue systems. The subject of the paper is a personal assistant design. The goal of personal assistant is a daily activities list planning. ThePersonal assistant will assist the customer that is human operator for planning is an optimum succession of desired activity.
Scaling up deep neural networks: a capacity allocation perspective

Following the recent work on capacity allocation, we formulate the conjecture that the shattering problem in deep neural networks can only be avoided if the capacity propagation through layers has a non-degenerate continuous limit when the number of layers tends to infinity. This allows us to study a number of commonly used architectures and determine which scaling relations should be enforced in practice as the number of layers grows large. In particular, we recover the conditions of Xavier initialization in the multi-channel case, and we find that weights and biases should be scaled down as the inverse square root of the number of layers for deep residual networks and as the inverse square root of the desired memory length for recurrent networks.
Trends of Traditions and Modernization in Studying and Developing Professional Actors and Directors of Drama Theatre

The aim of this paper is to analyze the traditional and contemporary trends in the education and formation of professional actors and directors of the drama theater. The article consistently outlines the principles of educating young artists based on the innovative method of the PASVIS, developed on the basis of the Experimental Studio of Theater Studies ECMATEDOS at the Kharkiv State Academy of Culture.The relevance of the topic lies in the lack of elaboration of the topic of the complex of professional theater pedagogical process at universities of Ukraine.The research methodology includes basic and specialized methods of theatrical and artistic approaches.Results. A complex of tendencies of education and training of professional actors and directors of the drama theater has been formed from traditions to the present. The practical embodiment of the students’ performances in the context of innovative solutions in ECMATEDOS is analyzed in chronological section from the foundation of ECMATEDOS to the present day. The essence of the experimental style of the theatre and pedagogical process for working with students of theater universities is revealed.The novelty is to analyze the possibility of an alternative way of education and the formation of actors and directors of drama theater in professional structures, and the current range of problems associated with this multicomponent process.The practical significance includes the option of creating an experimental laboratory to carry out the search for equipment and technology of the actor and director of the drama theater in line with the world of theatrical techniques.Keywords: education of professional actors and directors, theater pedagogy, theatre educational tendencies, ECMATEDOS, PASSVIS, EMENIM.
Purification Hamiltonians

We study the Jaynes-Cummings interaction when initial mixed states, for the atom or the field, are considered. The evolved mixed field density matrix is purified to a wavefunction that describes the interaction between a quantised field and an artificial four-level atom. This allows us to use the Araki-Lieb inequality to calculate the field entropy from the atomic entropy. We then generate {\it artificial} Hamiltonians that reproduce the field entropy dynamics. We finally show that more realistic Hamiltonians may be considered by using two entangled two-level atoms.
Sample Efficient Graph-Based Optimization with Noisy Observations

We study sample complexity of optimizing ``hill-climbing friendly'' functions defined on a graph under noisy observations. We define a notion of convexity, and we show that a variant of best-arm identification can find a near-optimal solution after a small number of queries that is independent of the size of the graph. For functions that have local minima and are nearly convex, we show a sample complexity for the classical simulated annealing under noisy observations. We show effectiveness of the greedy algorithm with restarts and the simulated annealing on problems of graph-based nearest neighbor classification as well as a web advertising application.
ReviewerNet: Visualizing Citation and Authorship Relations for Finding Reviewers

We propose ReviewerNet, an online, interactive visualization system aimed to improve the reviewer selection process in the academic domain. Given a paper submitted for publication, we assume that good candidate reviewers can be chosen among the authors of a small set of relevant and pertinent papers; ReviewerNet supports the construction of such set of papers, by visualizing and exploring a literature citation network. Then, the system helps to select reviewers that are both well distributed in the scientific community and that do not have any conflict-of-interest, by visualising the careers and co-authorship relations of candidate reviewers. The system is publicly available, and it has been evaluated by a set of experienced researchers in the field of Computer Graphics.
Library Websites of Central Universities in India: A Webometric Analysis

The central university library websites of India and their web impact factor (WIF), website analysis, web links and ranking were investigated in this study. Data were collected by using search engines such as Google, Yahoo and search engine optimisation tools, such as Backlink Watch and SEOquake add-on for Firefox browser. The result of the study indicates that the majority of the central university library websites in India have a higher number of web pages, and the numbers of link pages are less. Suggestions are given to improve the WIF of the examined library websites.
Analisis Tata Kelola Dan Perencanaan Investasi Teknologi Informasi Dengan Metode Cobit Dan Val It

Abstract - IT Governance and the development of appropriate information technology, aligned with business strategy and in accordance with the target is a priority, but often development projects are not expected to match the even, there are many information technology development project failure or canceled in the middle of the road. That's because information technology governance and IT investment planning are not good. It is necessary to analysis IT governenace and planning of IT investment. The selected sample is PT. Candi Malindo Bangkit with five (5) respondents involved. Tools in this study using the COBIT framework for data and opinions about IT governance and Val IT for IT investment planning. The selected domain from the COBIT framework are DS4 (continuous service), DS5 (information system security) and DS11 (data management), and the domain of Val IT are Value Governance (VG), Portfolio Management (PM) and Investment Management (IM) . Then based on the analysis can be known maturity level of IT governance and IT investment planning. The analysis shows that the current PT. Candi Malindo Bangkit still at maturity level 1 (one) or at the level of the initial/Adhoc which means IT governance and IT investment planning has been no standardization process, yet organized and implemented based on the needs of a sudden.Keywords: Audit, IT Governance, COBIT, Val IT
Dynamic Anonymized Evaluation for Behavioral Continuous Authentication

Emerging technology demands reliable authentication mechanisms, particularly in interconnected systems. Current systems rely on a single moment of authentication, however continuous authentication systems assess a users identity utilizing a constant biometric analysis. Spy Hunter, a continuous authentication mechanism uses keystroke dynamics to validate users over blocks of data. This easily-incorporated periodic biometric authentication system validates genuine users and detects intruders quickly. Because it verifies users in the background, Spy Hunter is not constrained to a password box. Instead, it is flexible and can be layered with other mechanisms to provide high-level security. Where other continuous authentication techniques rely on scripted typing, Spy Hunter validates over free text in authentic environments. This is accomplished in two phases, one where the user is provided a prompt and another where the user is allowed free access to their computer. Additionally, Spy Hunter focuses on the timing of different keystrokes rather than the specific key being pressed. This allows for anonymous data to authenticate users and avoids holding personal data. Utilizing a couple K-fold cross-validation techniques, Spy Hunter is assessed based on how often the system falsely accepts an intruder, how often the system falsely rejects a genuine user, and the time it takes to validate a users identity. Spy Hunter maintains error rates below 6% and identifies users in minimal numbers of keystrokes. Continuous authentication provides higher level security than one-time verification processes and Spy Hunter expands on the possibilities for behavioral analysis based on keystroke dynamics.
Top-N Recommendation Model Based on SDAE

Collaborative filtering is the mainstream approach to personalized recommendation. For the cold start problem faced in collaborative filtering, it is a hot research topic to introduce the user's side information into the recommendation model. Different from the matrix decomposition idea adopted in the existing methods, we propose a Top-N recommendation model using the side information of the user based on the reconstruction function of the stacked denoising auto-encoder. Experimental results show that the model outperforms the existing method in Recall. In addition, we explore the influence of missing ratings and user side information vector into the loss computation. The experimental results show that ignoring the missing ratings in the loss function is beneficial to improve the performance of the model.
Environment Engine for Situated MAS

In the multi-agent system research community, there is general consensus that the environment is important for multi-agent systems (MAS). However, most researchers minimize the responsibilities of the environment by reducing it to inter-agent communication, or neglecting to integrate it as a main element of their MAS models, which can be sufficient depending on the focus and objectives of their work. As a consequence of these decisions, the potential of MAS is not fully exploited. In some cases, the environment is a key element that cannot be written off as inter-agent communication, as it currently is in classical MAS. In our opinion it is important to focus the MAS around the environment. Reducing the environment to inter-agent communication deprives multi-agent systems of great potential. Our point of view is that the environment is an active entity with its own processes that can change its state, regardless of the activity of its embedded agents. We propose including the environment as an entity with a set of laws. Laws can be considered rules that cannot be broken by agents. However, some researchers have been interested in integrating the environment as first class and have proposed some interesting models. Unfortunately, they are not sustained by practical applications. The aim of this paper is to contribute in two ways: first, to propose an MAS model where an environmental engine is integrated; the capabilities of this model are comparable to those of a physics engine. Second, we propose an implementation of this model and some practical cases where it can bring concrete added value.
An Advance Paper Generator using Fuzzy Logic - A Novel Approach

Examination is important of examining the quality of a candidate's knowledge at each phase.It test the expertise and skills of the students in any area.Hence, conducting exam at each phase may lead to some issues such as time and other resources while creating the test papers not automatically .So a computing method make the problem simpler which generates question paper automatically.Question paper generator system is implemented by considering these problems , by which paper can be generated easily .The method is based on the concept of fuzzy logic which helps in generating question paper each time with user defined complexity phase.Paper can be generated at any time.We have make use of random function so that unique paper get generated every time.Security is also maintained using MYSQL tool.
Regular Expressions with Backreferences: Polynomial-Time Matching Techniques

Regular expressions with backreferences (regex, for short), as supported by most modern libraries for regular expression matching, have an NP-complete matching problem. We define a complexity parameter of regex, called active variable degree, such that regex with this parameter bounded by a constant can be matched in polynomial-time. Moreover, we formulate a novel type of determinism for regex (on an automaton-theoretic level), which yields the class of memory-deterministic regex that can be matched in time O(|w|p(|r|)) for a polynomial p (where r is the regex and w the word). Natural extensions of these concepts lead to properties of regex that are intractable to check.
University of Southampton - Response to Guidance on the Implementation of Plan S

The responses to the questions below comprise feedback to cOAlition S on the Plan S guidance from the University of Southampton. These points are based on discussion at the University Open Research Group and consultation with professional and academic staff in all Faculties. The University wholly embraces the idea of a fully open future for research and the general principle of beginning to deliver on these goals from January 2020. We, as an institution, have been deeply involved in the progress to Open Access (OA), developing EPrints open source software for institutional and subject repositories of which ePrints Soton was an early example. Overall, we are supportive of innovation and disrupting the publishing market, but we are aware of a complex and varied publishing environment.
A Novel Neural Network Structure Constructed according to Logical Relations

To solve more complex things, computer systems becomes more and more complex. It becomes harder to be handled manually for various conditions and unknown new conditions in advance. This situation urgently requires the development of computer technology of automatic judgement and decision according to various conditions. Current ANN (Artificial Neural Network) models are good at perceptual intelligence while they are not good at cognitive intelligence such as logical representation, making them not deal with the above situation well. Therefore, researchers have tried to design novel models so as to represent and store logical relations into the neural network structures, the type of which is called KBNN (Knowledge-Based Neural Network). In this type models, the neurons and links are designed specific for logical relation representation, and the neural network structures are constructed according to logical relations, allowing us to construct automatically the rule libraries of expert systems. In this paper, the further improvement is made based on KBNN by redesigning the neurons and links. This improvement can make neurons solely for representing things while making links solely for representing logical relations between things, and thus no extra logical neurons are needed. Moreover, the related construction and adjustment methods of the neural network structure are also designed based on the redesigned neurons and links, making the neural network structure dynamically constructed and adjusted according to the logical relations. The probabilistic mechanism for the weight adjustment can make the neural network model further represent logical relations in the uncertainty.
Nearest Neighbor Classification for High-Speed Big Data Streams using Spark

High speed data streaming and data mining is the most contemporize challenges in machine learning.This demand methods displaying a high process effectiveness, with ability to continuously update their structure and handle ever-arriving big variety of instances.in this paper, we have a tendency to present a new incremental and distributed classifier based on the favored nearest neighbor algorithmic rule, adapted to such a exigent situation.This technique, enforced in Apache Spark, includes a distributed metric-space ordering to perform quicker searches.a vast live {of information of data of knowledge} containing useful data, referred to as big data, is created frequently.For handling such large volume of data, there's a necessity of big data structures, for example, Hadoop Map reduce, Apache Spark then on.Among these, Apache Spark performs up to one hundred circumstances speedier than ancient systems like Hadoop Map reduce.we have a tendency to concentrate on the plan of partition grouping calculation and its execution on Apache Spark.
Imaging in the Mobile Domain

This article outlines the current state of imaging software with an emphasis on mobile sharing of images and mobile sharing of imaged data. The second portion focuses on the mobility of imaging design devices, highlighting the accessibility and the wider application of mobile devices.
IMPLEMENTASI LOGIKA FUZZY DALAM MENENTUKAN JURUSAN BAGI SISWA BARU SEKOLAH MENENGAH KEJURUAN (SMK) NEGERI 1 AIR PUTIH

Abstract - The process of selecting majors by prospective students by SMK Negeri 1 Air Putih is done manually. There are students who feel they are not compatible with their interests when getting lessons at school, this results students change schools and some drop out of school. Other things that can also have an effect such as students who move and dropout. In this study a system for implementing fuzzy logic was built using the method Tsukamoto. From the results of the research, the results of the Tsukamoto method were able to provide departmental recommendations which matches the subject that has high grades. Keywords - Fuzzy Tsukamoto, Fuzzy Logic, Prospective New Students.