Reviewerly/exHarmony huggingface dataset:
A Meta-analysis on the Correlation Between Gifted Student Selection Approach and their Gifted Performances

본 연구는 선행연구를 종합하는 메타분석 방법을 활용하여 기존의 선발방식이었던 지필 평가와 교사관찰추천제를 비교하고 영재교육대상자 선발방식에 따라 선발점수와 영재교육 프로그램 수행점수 간 상관에차이가 있는지 확인하였다. 그 결과 영재교육대상자 선발과 수행 간의 상관 효과 크기는 통계적으로 유의미하며 0.244(p<.000)로 작은 효과 크기가 관찰되었다. 집단의 이질성은 I2가 58.0%로 중간 크기의 이질성을 보여주었으며 이질성의 원인을 탐색하기 위해 영재교육대상자 선발 방법과 교육영역의 집단 간 분산을 확인한 결과 교육영역에서 이질성의 원인을 확인하였다. 이에 교육영역별 동질한 집단인 수학과 과학영역에서 지필 평가와 교사관찰추천제에 의한 선발과 수행 간 상관 효과 크기를 확인한 결과, 교사관찰추천제에 의한 선발과 수행 간의 상관 효과 크기가 통계적으로 유의미하게 나타났다.This study compares the paper and pencil based evaluation and teacher observation recommendation system, which was a conventional selection method, by using a meta-analysis method that synthesizes previous studies. As a result, the correlation effect size between the selection score and the performance score of the gifted education subjects was statistically significant, and the effect size was as small as 0.244. The heterogeneity of the group was 58%, showing medium-sized heterogeneity, and a moderators effect analysis was performed to investigate the cause of heterogeneity. As a result, the cause of heterogeneity was confirmed in the domain. In addition, in the mathematics and science domain, the correlation effect size between the selection score and the performance score by the paper and pencil based evaluation and the teacher observation recommendation system was statistically significant.
An Approach to Cohort Selection in Cloud for Face Recognition

Face recognition is such a problem where the accuracy is dependent on the quantity and variations of the training images. Increase of training data enhances the recognition accuracy in most cases. However, to collect and store a huge number of data in a standalone storage device is a big problem. Therefore, the researchers are being motivated towards cloud computing. Nowadays, the technology of cloud computing has made the task fairly ease even when a huge volume of data is required. This paper presents a cloud-based cohort selection approach which can be incorporated into a face recognition system. In this scheme, the cohort images as well as the training images can be accessed from the cloud servers through network connectivity. So the storage and maintenance costs are reduced whereas the accuracy is increased.
A Conflict Theory and Historical Analysis on the Causalities of Terrorism : And the causes of the 9/11 attacks as a case study

A Conflict Theory and Historical Analysis on the Causalities of Terrorism : And the causes of the 9/11 attacks as a case study
Research Guides: LSC 375: Social Media Analytics (Fall 2020): For Your First Assignment

This guide provides links to selected resources from among library collections and services to support students in LSC 375.
Assessing Chemistry Teachers Knowledge and Skills in Using ICT in Teaching Organic Chemistry at the Senior High School in the Ashanti Region

The advancement of science and technology vis-a-vis the constant need to improve upon the teaching practice is a course that when successfully put together would efficiently be very advantageous to the students and the teacher. The purpose of the study was to assess the barriers of ICT use, Support system and teachers’ knowledge and skills of ICT use in the teaching of Chemistry in senior high schools (SHSs) in the Ashanti Region. The teachers sampled for the study were from the various types of Senior High Schools (SHSs) such as mixed or co-educational SHSs, single sex female and single sex male in the Ashanti Region. The research instrument that was used to collect the data was questionnaire. Descriptive statistics were carried out to analyze the data using Statistical Package for Social Scientist (SPSS) software version 16. The findings of the study identified perceived barriers of ICT integration in teaching in the SHSs as lack of enough or limited access to computers/computer lab, non-availability of computer software, lack of time in school schedule for integrating ICT and lack of adequate technical support. It also included not get any current technical support for provision of technical course for operating and maintaining computer system and having a technician in the classroom. Teachers’ knowledge and skill in technology use was not seen as a barrier to ICT integration in teaching. It is recommended that computer laboratories should be setup in SHSs and furnished with computers and software that will enable teachers plan and deliver their lesson effectively using ICT. The time table of the SHSs should be reviewed to cater for ICT integration which teachers’ perceived to be time consuming. Keywords: Administrative support, Technical Support, Information and Communication Technology, Senior High School and West African Examination Council DOI: 10.7176/JEP/11-24-03 Publication date: August 31 st 2020
An Unsupervised Word Level Language Identiﬁcation of English and Kokborok Code-Mixed and Code-Switched Sentences

: Considering the increasing uses of multilingual text, the need for an automatic word level language identiﬁcation model is raised. In this regard, we present an unsupervised model for word level language identiﬁcation of English and Kokborok code-mixed and code-switched sentences. Several works have already been reported for various languages, including various Indian languages. But, to the best of our knowledge, ours is the ﬁrst language identiﬁcation work dedicated to low resource English-Kokborok language pairs. The proposed model combines a frequency lexicon based, character n-gram language model and a language dependent morphological dictionary-based model for correctly classifying each word. The model which is suitable for low resource languages that do not have a large number of annotated dataset is able to achieve a good performance with word accuracy level of 84%.
Performance analysis of User Requests and VM assignment in Cloud Environment

The complexity of user jobs in the cloud environment is increasing day by day since many organizations are migrating their on-premise operations to cloud centers which in turn leading to huge traffic during peak hours. The cloud providers must be able to manage the traffic efficiently and provision the resources to the dynamic cloud users without any delay. This paper explores the various behaviors of incoming jobs and VM assignment in Azure cloud cluster and the following observations are made: i) Day and hourly analysis of job requests ii) Day and hour wise task assignment to virtual machines iii) Average CPU utilization for consolidated virtual machines iv) VM categorization and VM count v) Deployment ID and Subscription ID analysis.
A Sustainable Energy Efficient Internet of Medical Things (IoMT)based Framework fore-healthcare

The internet of things ( IoT) is becoming very popular in several fields due to its autonomous, low-cost sensor operations. In health and medical applications, IoT devices develop ecosystems to detect patient health conditions such as blood pressure, oxygen level, heartbeat, temperature, etc. and take appropriate measures in an emergency. This is used to transfer healthcare data from patients to remote users and post-analysis medical centers. Various solutions have been suggested to monitor the health condition of patients using the Wireless Body Area Network (WBAN) based upon low power nodes but demanding and interesting difficulties are preventing increased energy consumption and communications costs. The issue of unbalanced energy consumption between biosensor nodes degrades the timely transmission of information from patients to remote centers and negatively affects the medical system. In addition, the patient’s sensitive data is transmitted over the insecure internet and is subject to vulnerable security risks. The privacy of data and malicious traffic integrity are therefore another major problem in medical research. This research paper aims to establish a proposed sustainable, secure and energy-efficient Internet of Medical Things (IoMT) based framework for e-healthcare which aims primarily at decreasing the overhead contact and energy usage between biomass sensors while conveniently transmitting health data, and also at safeguarding patients’ medical information against unauthentic and malicious nodes.
Introduction to logistic regression.

For random field theory based multiple comparison corrections In brain imaging, it is often necessary to compute the distribution of the supremum of a random field. Unfortunately, computing the distribution of the supremum of the random field is not easy and requires satisfying many distributional assumptions that may not be true in real data. Thus, there is a need to come up with a different framework that does not use the traditional statistical hypothesis testing paradigm that requires to compute p-values. With this as a motivation, we can use a different approach called the logistic regression that does not require computing the p-value and still be able to localize the regions of brain network differences. Unlike other discriminant and classification techniques that tried to classify preselected feature vectors, the method here does not require any preselected feature vectors and performs the classification at each edge level.
A LOW POWER FPGA IMPLEMENTATION OF AHYBRID SHA3-AES DESIGN FOR ENCRYPTING DATADURING TRANSMISSION

Encryption is a mechanism where readable data is translated to unreadable format. It cant be accessed by intruder.In biomedical application the medical data information should be secret. The paper presents the FPGAimplementation of a proposed hybrid method combining the features of SHA3 (Secure Hash Algorithm3 and AES(Advanced Encryption Standard) algorithm for encrypting data during transmission. The proposed method iscompared with the Existing method which uses SHA and AES as encryption standard. The AES and SHA 3algorithm is combined to increase the security level. It was observed from the results that the proposed methodimproved the power consumption by around about 47 percent. The proposed encryption is new one of its own kindin structure, operations and results. Using Quartus for Cyclone II, implementation is done in 90nm CMOStechnology.
LibGuides: OneSearch: The Library Discovery Tool: Home

This guide is here to help the Cal State LA campus become more familiar with the library discover tool and how it works.
The evaluation of higher vocational education level based on fuzzy set theory

higher vocational education; evaluation index; fuzzy set theory
A Muti-Feature based Noise Detector for Random-Valued Impulse Noise

In order to improve the lack of execution efficiency and detection capability of traditional random valued impulse noise detection algorithms, this paper starts with the construction of feature vectors with strong noise mapping capability, and improves the feature used as input of the neural networks. A feature vector with strong capability of mapping noise is obtained by combining and accumulating multiple ROLD and ROAD of different orders. At the same time, based on the regular pattern of gray value changes in digital images (from light to dark), a new feature complementary to the current feature statistic is proposed. Simulation results indicates that the neural network is superior to the traditional method in terms of both in detection performance and execution efficiency.
Big Data and Clustering

This chapter is devoted to an introductory discussion on clustering big data. In particular, we briefly reconsider all the most common clustering methods, presented in the previous chapters, and evaluate how they work when the data size increases. The analyses are not based on big data in a strict sense. In fact, the data we investigate do not pose memory/storage problems. Nevertheless, some preliminary relevant conclusions can be drawn even handling “non-small” size data.
DISAIN APLIKASI DASBOARD TRAFFIC WORKORDER PADA PT.DIGITAL PRINTING

PT Digital Printing is the supervisor of printing services using computer technology media. In itsdevelopment, it continues to innovate to provide systems to be computerized effectively andefficiently, especially in services. In the service of PT Digital Printing with paper tickets printedas a media queue for customers, by having a system like this makes information services tocustomers a long time. So that for recording customer data and order data, in the process ofprinting jobs do not produce clear information to the customer, resulting in a report given to thecustomer cannot be conveyed not quickly. With these problems the writer makes a Work Orderapplication based on the website, making it easy for the Customer to see the results of the workorder process. With PHP programming language and design with Unified Modeling Language(UML). This new system is used to display the Dasboard Work Order to the Customer. So withthis system built officers are faster in providing order information, so that information can bevery easy and fastKeywords: Application, Dasboard, Work order
Handling Adaptive Compromise for Practical Encryption Schemes.

We provide a new definitional framework capturing the multi-user security of encryption schemes and pseudorandom functions in the face of adversaries that can adaptively compromise users’ keys. We provide a sequence of results establishing the security of practical symmetric encryption schemes under adaptive compromise in the random oracle or ideal cipher model. The bulk of analysis complexity for adaptive compromise security is relegated to the analysis of lower-level primitives such as pseudorandom functions.
Energy Is Not Conserved

Because Newton's third law and Newton's second law proved to be wrong, then according to the new second law of motion and the new third law of motion, the new mechanics principle is produced, the most important and remarkable is, that the momentum is not conserved And the principle of energy is not conserved, it be found.
Identification of Telltale Signature by Using Method of Adaptive Neuro-Fuzzy Systems

The article is devoted to the problem of using the method of adaptive neuro-fuzzy networks to assess the informativeness of the telltale signature of the object of protection. In ANFIS, a fuzzy system is used to represent knowledge in an interpreted form, as well as the ability to train a neural network to optimize the parameters of a fuzzy system. The training data base was based on the results of the previous study, which consisted in building a decision support subsystem for identifying the set of telltale signature of a protected object based on expert judgment. It contains information about the informativeness of each group of telltale signature and is used in the process of learning a neural network. Constantly changing the parameters of the membership functions when learning a neuro-fuzzy system allows you to more accurately configure the system to solve the task. The study showed the possibility of using the method of adaptive neuro-fuzzy networks in the process of evaluating the informativity of the telltale signature.
Explainable Intelligence - XAI, the third wave of AI

For the field of AI to reach any measurable sense of maturity, we'll need methods to debug, error-check, and understand the decision-making process of machines. The lack of trust was at the heart of many failures of one of the best-known AI efforts. Artificial intelligence (AI) is a transformational $15 trillion opportunity, but without explainability, it will not reach any measurable sense of deployment.  We are now entering third wave of AI where AI systems will become capable of explaining the reasoning behind every decision made by them. The AI systems themselves will construct models that will explain how it works.  XAI is all about improving trust of AI-based systems. At one end it brings fairness, accountability and transparency to the front and center of AI; and on the other end it enables us to control and continuously improve our AI systems. In this session, I will go over why the AI needs to be explainable, what does that mean, the state of the art of explainable AI as well as various approaches to build it.
THE USED OF A MEDIUM OF LEARNING SONG FOREIGN LANGUAGE IN LEARNING SPEAK STRANGER IN ELEMENTARY SCHOOL

In support of an effective and efficient learning process, teachers need to determine how to strategize in appropriate learning. One of the strategies used in foreign language learning is to use learning media, but most teachers do conventional learning without using any learning media. Song is one of the appropriate learning media in language learning especially foreign languages. The purpose of this paper is to show the benefits of using learning media for foreign language songs in foreign language learning at elementary school so the teacher can switch to using effective learning media. The results obtained from the study of this article is that the use of songs on strengthening foreign language skills is recommended because it can help students master 2 of 4 skills, namely listening and speaking. Learners are also more motivated by the use of Song Media in learning because songs create a learning environment that is not boring. Although search websites about songs in learning are declining, but until now it is still sought and quite attractive to the public.
A Condition-Action Rule-Based Integration Platform for the Internet of Things

The vigorous development of micro-electro-mechanical systems has enabled the possibility of Internet of Things that envisions interactions between tens of, or possibly hundreds of, smart things such as computers, sensors, and actuators to realize a cyber-physical environment. With the number of devices, it will become tedious and difficult to configure and management the interactions between these things. Therefore, this paper presents an integration platform which allows smart things to be plug-and-play and condition-action rules to be established between things visually. We describe the specifications and architecture of the proposed platform, and also illustrate the implementation. We believe our work will alleviate the complexity of managing and configuring medium-scale of smart things, and pave the way for the solution of large-scale Internet of Things.
Automating the resolution of information system incidents using efficient Machine Learning algorithms

Automated ML is a set of methods that allow non-experts touse Machine Learning so easily, to ameliorate its efficiency and to dig more in their researches. Machine learning knew recently a big success and an ever-growing number of fields rely on its performance. Nevertheless, this success is based on human machine learning experts to do some tasks manually.Moreover, because these tasks are complex, especially for non-ML-experts, a rapid growth of machine learning applications has appeared and the demand for ML methods and processes that is handy and simple to use is more and more important.The design of an effective ML requires expert’s knowledge toimprove algorithms in orderto optimize results. So how can we use, for example, K-fold cross-validation to look for an optimal tuning parameter? Andhow can this process be made more efficient? The idea of machine learning pipeline is based on the automation of machinelearning workflows. It consists on training a given modelthrough several steps. However, we can remark that the word ‘pipeline’ refers to one-way flow of data which is not the case ofML pipelines. In this context, machine learning pipelines rely on repetition of steps and continuous improvement of learning which make them very cyclical and iterative. Therefore, we get successful algorithms and models with good accuracy. The development of the Tree-based Pipeline Optimization Tool (TPOT) recently allows the optimization and the automatic design of the machine learning pipelines when given a problem to deal with without human participation. Therefore, how can we optimize machine learning pipelines using TPOT and a version of genetic programming? which is an automated method for creation of computer programs from a high-level problem statement of a problem.To see how tooptimize the automatic design of machine learning pipelines, we will put all these algorithms into practical application tomanage the information system incidents of one the insurance leaders in the world.
정부 주도로 개발된 유아교육 프로그램의 현황과 프로그램 활용에 대한 유치원 교사의 인식 실태

This study examined educational programs for early children developed by the government and early children teachers' recognition on applying those programs to field last for 10 years. The subjects of this study were 36 government-developed early childhood education programs and 253 kindergarten teac...
Quantum Hilbert Image Scrambling and SVD-Based Watermarking Scheme for Rightful Ownership

Digital watermarking provides the solution for problems such as copyright and authentication in today’s digital world of communication. Trustworthy watermarking techniques should provide the protection for rightful ownership, robustness and resist against attacks such as filtering and modification. In this paper, we proposed an efficient watermarking scheme based on singular value decomposition (SVD) and quantum Hilbert image scrambling. In the proposed watermarking scheme, first watermark is scrambled using quantum Hilbert image scrambling then perform alpha blending on scrambled watermark and SVD transformed cover image followed by alpha mixing operation. Finally, perform SVD operation of the generated signal; after alpha blending operation, we get watermarked image. The experimental results show strength of the proposed technique in terms of the robustness and security. Performance of the proposed scheme is tested on different image quality parameters of watermarked and host image. These are peak signal-to-noise ratio (PSNR), mean square error (MSE) and normalized cross-correlation (NCC), average difference (AD), maximum difference (MD), and structural contents (SC).
Research on Expert System in Power Network Operation Ticket

This paper realizes the automatic generation system of reversing operation ticket which aiming at the problem of insufficient flexibility and intelligence by expert system technology. By analyzing the characteristics of the power system, the knowledge base and the inference engine which constitute the operation ticket expert system are studied separately to design a knowledge base with a more concise knowledge representation. The Rete algorithm was used in the study of reasoning mechanism, and the design of the operation ticket expert system was completed finally.
Corruption and Audit in Strategic Argumentation.

Strategic argumentation provides a simple model of disputation and negotiation among agents. Although agents might be expected to act in our best interests, there is little that enforces such behaviour. (Maher, 2016) introduced a model of corruption and resistance to corruption within strategic argumentation. In this paper we identify corrupt behaviours that are not detected in that formulation. We strengthen the model to detect such behaviours, and show that, under the strengthened model, all the strategic aims in (Maher, 2016) are resistant to corruption.
Blockchain: Proposed Architecture and It’s Applications

Blockchain technology, which is known as the basis of bitcoin and various other crypto currencies, is nowadays having enormous attention.The basis of this technology lies in immutable ledger that allows the transactions to occur in a decentralized manner which provides anonymity to the customers.The current paper gives an overview of the blockchain technology; its process flow and various types or categories.Architecture on blockchain technology has been proposed, which can be used on almost every domain of it.Also a comparison of various architectures that have been proposed previously has been carried out based on some identified parameters.Finally at the end various application areas of the technology have been discussed.