Reviewerly/exHarmony huggingface dataset:
Implementation of CNOT and Toffoli gates with higher-dimensional spaces

Minimizing the number of necessary two-qubit gates is an important task in quantum information processing. By introducing non-computational quantum states in auxiliary spaces, we construct effective circuits for the controlled-NOT (CNOT) gate and the n-control-qubit Toffoli gate with (2n-1) qubit-qudit gates and (2n-2) single-qudit gates. We propose the polarization CNOT and Toffoli gates based on the designed quantum circuits in linear optics by operating on the spatial-mode degree of freedom of photons. Our optical schemes can be achieved with a higher success probability and no extra auxiliary photons are needed.
Detection of malaria parasites in blood smear image using color-intensity feature extraction

Malaria is one of the life-threatening diseases that affect millions of innocent lives each year, mainly in tropical areas where the most serious illness is caused by the species of Plasmodium falciparum. The conventional microscopy used in the diagnosis of malaria disease has proved to be inefficient since the process is time-consuming and the result is difficult to be reproduced. The alternative diagnosis techniques which yield the superior standard results are expensive and hence inaccessible to poor countries and rural areas. Therefore, this study aims to develop a prototype system that detects malaria parasites automatically from microscopic images by using the color-intensity feature extraction. Two objectives had been made for this study which is to develop an automatic malaria parasite detection system and to detect the malaria parasites in the microscopic blood images using color-intensity feature extraction. The input image is processed with image processing algorithms which include image sharpening, image segmentation (Canny Edge Detection and Watershed segmentation), and feature extraction of the malaria parasites (color-intensity feature extraction). Overall, the accuracy test of the proposed system achieved 98.7% when tested in 300 blood smear images.
Measuring Mobility and Room Occupancy in Clinical Settings: System Development and Implementation

BACKGROUND: The use of location-based data in clinical settings is often limited to real-time monitoring. In this study, we aim to develop a proximity-based localization system and show how its longitudinal deployment can provide operational insights related to staff and patients' mobility and room occupancy in clinical settings. Such a streamlined data-driven approach can help in increasing the uptime of operating rooms and more broadly provide an improved understanding of facility utilization. OBJECTIVE: The aim of this study is to measure the accuracy of the system and algorithmically calculate measures of mobility and occupancy. METHODS: We developed a Bluetooth low energy, proximity-based localization system and deployed it in a hospital for 30 days. The system recorded the position of 75 people (17 patients and 55 staff) during this period. In addition, we collected ground-truth data and used them to validate system performance and accuracy. A number of analyses were conducted to estimate how people move in the hospital and where they spend their time. RESULTS: Using ground-truth data, we estimated the accuracy of our system to be 96%. Using mobility trace analysis, we generated occupancy rates for different rooms in the hospital occupied by both staff and patients. We were also able to measure how much time, on average, patients spend in different rooms of the hospital. Finally, using unsupervised hierarchical clustering, we showed that the system could differentiate between staff and patients without training. CONCLUSIONS: Analysis of longitudinal, location-based data can offer rich operational insights into hospital efficiency. In particular, they allow quick and consistent assessment of new strategies and protocols and provide a quantitative way to measure their effectiveness.
Retraction: Neural Networks for the Web Services Classification (Journal of Physics: Conference Series 1432 012076)

Published 15 September 2020 This article, and others within this volume, has been retracted by IOP Publishing following clear evidence of plagiarism and citation manipulation. This work was originally published in Spanish (1) and has been translated and published without permission or acknowledgement to the original authors. IOP Publishing Limited has discovered other papers within this volume that have been subjected to the same treatment. This is scientific misconduct. Misconduct investigations are ongoing at the author’s institutions. IOP Publishing Limited will update this notice if required once those investigations have concluded. To date, there is no evidence to suggest anyone other than Amelec Viloria / Jesus Silva was directly culpable for the actions that led to retraction. IOP Publishing Limited request any citations to this article be redirected to the original work (1). Anyone with any information regarding these papers is requested to contact conferenceseries@ioppublishing.org.
Cloud computing adoption status in Oman (Arab) higher education: unified theory of acceptance and use of technology in education management

Cloud computing is offering various solutions to the world and in this paper we are exploring the possible solutions in higher education system. The emphasis is on cloud adaptation in Arab world education system. We took case study of Oman higher education system. We explore the factors that have slowed cloud adoption mainly in higher education and find meaningful solutions to improve the usage of cloud in colleges and universities. Responses to examination inquiries give information about the present condition of moderate cloud selection in higher education. A possible solution could be the adoption of cloud computing and its services. The examination will give knowledge about why higher education work force is reluctant to adapt to this technology. Cloud computing additionally has a few issues and concerns like virtualisation, security and trust. This study explores into the slow adoption of cloud in higher education. Cloud adaptation in developing countries specially in Arab world is needed where higher education is in developing stages. In this study we focused on education sector especially higher education.
Publicity and Its Role in Investigating the Crimes of Expression of Opinion - A Comparative Study

Publicity has an important and prominent role in defining expressive crimes or not, because most expressive crimes are not achieved without publicity, and for this it is considered one of the basic and main principles in defining expressive crimes, and this is what most laws went to, and given the importance of this pillar, we set out to clarify and study it through What the Iraqi, Egyptian, French and Algerian laws referred to, and by talking about the traditional manifestations of saying, pointing, drawing, or ..., as well as the modern aspects of publishing on radio, television and social media. There is a common aspect among the laws, which is to define all aspects that constitute a crime of expression, while the difference is in defining the punishment for the perpetrator.
Promoting The Students Speaking Skill By Implementing Collaborative Learning Method In Teaching Speaking Skill

This research was aimed at knowing the implementation of Collaborative Learning promotes students’ speaking skill at the second semester English Education Department Muhammadiyah University of Makassar. This research applied a quasi-experimental design; the non-equivalent control group design. The sample was taken by using purposive random sampling technique. The total number of samples was 38 students of two classes consisting of class II G was experimental class and II C was the control class. There was speaking test as the instrument. The statistical result analysis of SPSS 25 showed that in accuracy sig 2-tailed = 0.000 is less than 0.05 and in fluency sig 2-tailed = 0.000 is less than 0.05. This result rejects the first null hypothesis which states that there is no significant difference between the mean score of pretests and posttest of the students’ speaking skills. This research concluded that the use of Collaborative Learning in teaching speaking promote the students’ speaking skills in terms of accuracy and fluency.
Distributed Updation and Authentication of Aadhaar Leveraging Blockchain Technology

Blockchain is a distributed, decentralized public ledger. It allows digital information to be distributed and is immutable, creating a new backbone for the Internet. It is a series of immutable time stamped records with no central authority. Data or transactions are stored in the form of blocks that are cryptographically sealed and chained to one other. We seek to exploit blockchain’s exemplary advantages of security and decentralized distribution in a government application. Currently when a person wants to create or change his identification details, he has to navigate individually to different offices of the government. The government information is stored and managed by a centralized administrator. In order to eliminate the centralized dependency and to save the time and energy of the applicant, data acquired while creating a government identification card or number can be stored in a blockchain. Any changes made by the applicant to his data can be distributed to all the government departments that are the members of the blockchain network. It also uses a self-executing contract with a set terms of agreement called a smart contract. We create a consortium blockchain to optimize the parameters of time and security.
An effective secured peer-to-peer energy market based on blockchain architecture for the interconnected microgrid and smart grid

Abstract One of the most significant current topics in the energy market is the decentralized operation of the power system wherein the entire discipline is constructed based on the consensus concept. In such a framework, an agreement among all effective participants in the market should be brought without the presence of an independent arbitrator. This paper proposes a secured energy market architecture based on peer-to-peer (P2P) idea to provide an appropriate platform based on the decentralized network and key aspects of energy market, including network architecture, interface communication, and network security. It is apparent that communication interfaces connecting the market participants is a fundamental property for achieving this purpose and that must be secured against the malicious attacks. In this regard, reaching the secured consensus is guaranteed by providing a new blockchain platform coincided by P2P energy market. The energy market is conducted by an effective Relaxed Consensus-Innovation (RCI) based algorithm with the aim of bringing the power/price exchanged among connecting participants in the form of P2P structure. In the proposed model, a microgrid and a smart grid are considered as the market participants, who tend to negotiate with each other in a way that follow their own benefits in the secured environment. The microgrid includes the wind turbine (WT), photovoltaic (PV), tidal turbine and storage unit to satisfy its demand and the smart grid is composed of distributed generations (DGs) and lines in the form of the IEEE 24-bus test system. In order to handle the uncertainty effects in the problem, a stochastic framework based on unscented transform (UT) is proposed in the P2P energy market. In order to assess and verify the fault-tolerant system ability against the cyber-attack, the fault data injection attack (FDIA) is modeled and applied to the P2P energy market in a blockchain platform. The simulation results approve the appropriate performance and applicable nature of the proposed concepts in this paper.
Sistem Informasi E-Learning Berbasis Website Untuk SMA Negeri 1 Wonogiri

The Political and Economic Risk Consultation (PERC) has released survey results that cite the education system in Indonesia from the 12 countries ranked last. The quality of education of several factors, one of which is learning media. This research will lead to the learning media, namely e-learning. Utilization of e-learning will be very helpful in teaching and learning, and can even overcome problems that occur in SMA Negeri 1 Wonogiri. The problem experienced is a compilation of classes that have class hours. Because the teacher faces off, the class does not accept learning. This website-based e-learning information system will be developed using PHP and mySQL using the waterfall method. The results of the black-box test states that the e-learning information system can run according to its function and based on based on Usability testing, the average results are 84, which can be concluded that the system is in the good category and can be accepted by users.
Dynamic Managerial Cognitive Capabilities: Exploring the Micro Foundation of a Firm's Innovation

Despite research begin to investigate the micro-macro link between a very important yet under-investigated capabilities—a firm’s dynamic managerial cognitive capabilities—and its macro-level outcomes, they focus on particular types of cognitive capabilities, offering a partial picture for the working mechanisms of dynamic managerial cognitive capabilities. In this study, we systematically investigate how a firm’s dynamic managerial cognitive capabilities are decomposed into different subdimensions respectively and functioning as a whole in affecting an entrepreneurial firm’s innovation. By conducting three studies including simulation, content analysis, survey, and second-hand data, the consistent results show that cognitive-related sensing capability negatively, while cognitive-related seizing and reconfiguring capabilities positively affect an entrepreneurial firm’s innovation performance. Our findings provide a more complete and fine-grained view of the effects of micro-level dynamic managerial cognitive capabilities on a firm’s macro-level innovation.
Взаимодействие соционики и психософии на конкретном примере

The variants of the interaction of two typologies – socionics and psychosophy are considered on the example TIM LII ELFV. It is shown clearly the complementarity but not the conflict of typologies. The examples of manifestations of functions identified typologies in everyday life are given.
The Construction of Smart Learning for Minority University English Learning From the Perspective of Smart Classroom

Wisdom learning is an innovation of learning style under the guidance of the smart Classroom concept, and it is an effective means to improve the efficiency of university students' language learning in the information age. This paper introduces the smart learning mode of English in minority university from the concept of the smart classroom and its interactive, experiential and diversified characteristics. It focuses on the learning design of the smart learning mode before, during and after the class. Smart learning is an effective solution to the problems of unbalanced English education resource, low initiative and efficiency in English learning in especially the underdeveloped area in China.
LibGuides: Educational Psychology LibGuide - Public Library: Books and E-Books

Learning is a complicated process. Each child is an individual and has individual needs or styles of learning. The focus of this LibGuide is to provide parents and educators with the information they need to help a child learn.
대학 교양영어 수업의 조별활동에서 학업 수준별 만족도에 관한 연구

The purpose of this study is to explore the class satisfaction by the high and low academic achievement level students of collaborative group work in college general English course. The negative perceptions of two groups about collaborative group work were surveyed respectively. Data was collected from 122 first-year university students. The results were as follows: First, the highest group showed more satisfaction than the lowest in terms of the effects and perception of the group work. Second, the five major negative opinions of the group work from the highest group included the poor accuracy of the answers, lack of preparation, conflict after debate, cluttered atmosphere, and absence of team members. Those of the lowest were cluttered atmosphere, conflicting opinions, conflict after debate, difficulty in meeting time, and absence of team members.
Interconnection Despite Limited Connection: Impact of Integrating Asynchronous, Social Constructivist Activities to Grade 10 Public School Students’ Learning Experience in the Time of Covid-19

In a public high school in San Rafael, Bulacan, where this action research was conducted, it was identified through the Department of Education survey that the majority of students relied only on mobile phones and data to connect to the internet. Due to the students’ varying situations, the school decided to adopt the Modular Distance Learning approach, where learning was done by answering self-learning modules (SLMs). Some synchronous classes were still conducted but observed to have low attendance. The current setup also limited peer-peer and student-teacher interaction and opportunities for collaborative work. This prompted the researchers to explore the opportunities and see the impact of integrating asynchronous, social constructivist activities with the SLMs. Specifically, the research aimed to find out if these activities can 1) aid in ensuring that the important knowledge, skills, attitudes are learned and applied, and 2) foster students’ collaboration and active class participation. Influenced by backwards lesson planning, social constructivism, and the 70:20:10 frameworks, which all give emphasis to learner-centeredness, hands-on practice, and collaboration, the researchers planned asynchronous activities using the class’ existing Facebook group. Students’ learning artifacts, scores, and answers to reflection activities support that these asynchronous activities were useful in fostering better learning, participation, and interaction in modular teaching. The research findings also substantiate the remote learning best practices found in literature. By applying the recommended improvements to the approach, schools can benefit from the proposed activity planning strategy for remote learning during the pandemic.
Practical Research on Higher Vocational English Precision Teaching Mode under the Background of Educational Big Data

The continuous development of information technology has made big data an important means for people to integrate information. How to carry out more accurate education work by grasping the effectiveness of teaching has become a problem that needs to be addressed by teachers. This article starts with the specific learning situation of higher vocational students and discusses specific ways to use big data to improve teaching effectiveness, hoping to help students strengthen the learning effect while accumulating certain educational experience for other educators.
Double Back-Propagation and Differential Machine Learning

We have introduced a novel (ζ, e)-Double Back-propagation Scheme (DBS) applicable to any parametric model with convergence properties in terms of Mean Square Error. The DBS indicates that with an optimal number ζ of DBS updates, and appropriate e learning rate vector for all the model parameters, the Mean Square Error of both training and testing data get to be decreasing, and converge to zero for the training data. The DBS recommends a local Stochastic Gradient Descent (SGD) per observation after the model parameters have been obtained after a first-step estimation with any chosen optimization framework. It has been applied to the Shallow Potts Neural Network Model developed in a previous research by (Alahassa & Murua (2020)), and the results are outstanding. Not the least, we prove mathematically that under an assumption that if there exists a differentiable function that associate covariables (predictors) and target variables (our outputs) as well as their respective local DBS associated parameters, for each observation, we can make the train error and the test error converge to zero simultaneously by applying a dist-NN-h-Taylor Series-PMI model. This last model dictates that we can always differentiate sufficiently the model parameters using a combination of Taylor Approximation Theorem with h ≥ 2 order with a Perfect Multivariate Interpolation (PMI) framework, and finally, an optimal distance (dist) for a suitable Train-Test covariables association. Our main conclusion is that overfitting, mainly with the convergent DBS optimizer is the beginning of a new type of learning method, as we can still generalize our parametric model with local neighborhood learning with multivariate interpolation and fine tuned empirical differentiation.
A Novel Multi-objective Particle Swarm Algorithm Based on a Neighborhood to Search Depth in Task Scheduling by Considering a New Security Model

Cloud computing is a novel technology that provides users with better opportunities to gain access to services on the Internet. Users should utilize organizational services to meet their needs. They can also benefit from non-organizational services with high capacity but limited security. This study aims to provide a new security model that addresses security requirements for tasks and data as well as security strength for resources and communication paths. The proposed security model is defined security distance concept. Minimizing security distance has to do with task scheduling so that the resources can be matched with the security level and the data will be fitted into the appropriate communication path. The proposed scheduling algorithm takes the server profit into account in addition to the minimum security distance. The increased server profits can lead to higher resource sharing by the servers. The proposed scenario is implemented based on a neighborhood to search depth in task scheduling. This algorithm utilizes a novel ‘far and near neighborhood’ approach to select the best particle position. The approach generates both diversity and convergence in the set of answers. Finally, the proposed algorithm is compared with three other similar scheduling algorithms obtained by VNPSO, MPSO and NSGAII, considering the security of the cloud computing environment. The computational results show the effectiveness of the proposed algorithm to obtain resources with similar security and higher server profits.
Cyber Crime and Insurance

A data breach is a nightmare. Lawyers need to understand cyber insurance to protect clients information and their own law firms. Law firms have a special exposure when hacked because of client files with personal and other sensitive information.The first line of defense in protecting company or law firm data is to create an effective computer policy against theft of its data by its own employees.Traditional liability insurance do not cover internet exposure and risks.The standard commercial liability policy(CGL) does not cover data related liability. Computer specific policies provide specific grants of coverage.These policies limit coverage of bad acts of persons who are not authorized to use the computer and therefore exclude acts by employees.An excellent source for understanding cyber security is,The ABA Cybersecurity Handbook: A Resource for Attorneys, Law Firms and Business Professionals edited by Jill D. Rhodes and Robert S. Litt. (ABA Publishing, 2017). The Handbook provides guidance for attorneys in all practice areas.