Reviewerly/exHarmony huggingface dataset:
Insight Into Quantum Computing

Newtonian physics has provided an explanation for the interactions occurring in the everyday world while encouraging the development of technology, such as computers, that utilize our understanding of physics. However, classical computers based on Newtonian physics fail to operate on an advanced level necessary in the growing fields of dark matter or machine learning. As an alternative, quantum mechanics provide the potential for an improved computing system. The nonlinearity and superposition properties of quantum computing ensure that quantum computers will be better suited in certain matters, such as simulating quantum systems or factoring insurmountable numbers, when compared to classical computers. Advances in machine learning and dark matter detection with the use of quantum technology exemplify the true potential of quantum computing. While quantum computing has the capability to advance the world, the realistic means of creating a quantum computer is hindered by the difficulties of quantum mechanics. For example, measuring qubits through entanglement and isolating a quantum computer are both tasks posing as barriers in the path of quantum computing. Nevertheless, experiments overcoming these obstacles demonstrate a means to achieve the implementation of quantum computers to solve scientific mysteries. This paper will review the potential applications of quantum computing while also considering the problems it faces. It will stress the importance of research in quantum mechanics and a future focused on improving quantum technology. &#x0D;
Chaos to fractals

In undergraduate classrooms, while teaching chaos and fractals, it is taught as if there is no relation between these two. By using some non linear oscillators we demonstrate that there is a connection between chaos and fractals. By plotting the phase space diagrams of four nonlinear oscillators and using box counting method of finding the fractal dimension we established the chaotic nature of the nonlinear oscillators. The awareness that all chaotic systems are good fractals will add more insights to the concept of chaotic systems.
Implementasi Google Apps for Education sebagai Upaya Peningkatan Keterampilan Pendidik di SMP Negeri 20 Kota Bandung

This study aims to improve the skills of educators at SMP Negeri 20 Bandung by applying LMS, namely Google Apps For Education (GAFE). This research is a school action research using a quantitative approach. The population of this research is all teaching staff at SMP Negeri 20 Bandung. The sampling technique used was total sampling, which used the entire population of 46 educators. The data collection technique is a direct observation of the Google Classroom application. Data collection tool in the form of observation sheets. Data collection was carried out three times during the research period: pre-cycle, cycle 1, and 2. The data analysis technique used started with data reduction, data presentation, and concluding. The study results show that the application of the Learning Management System through Google Apps For Education can improve the skills of educators at SMP Negeri 20 Bandung City. The value of pre-cycle skills is 31.46% (very low). After the implementation of cycle 1, the skills of educators increased to 56.17% (high enough); in cycle 2 it also managed to rise to 73.22% (high).
Modelling of Laboratory Information Systems in Higher Education Based on Enterprise Architecture Planning for Optimizing Monitoring and Equipment Maintenance

&lt;span lang="EN-US"&gt;It is possible to conduct scientific research, experiments, measurements, or training in a laboratory. Each department at FMIPA UNNES features several laboratories to complement class lectures for the students. Students can recognise concepts, cultivate scientific attitudes, and improve their critical thinking skills through lab practice. Utilising laboratory resources effectively and efficiently is expected of good laboratory management. Testing of lab equipment is required to ensure proper functionality and readiness for practicum use. Maintaining an eye on the equipment's condition and fixing any damage as soon as it becomes apparent is crucial for providing proof. The drawbacks of manually recording tool repairs are poor paperwork and equipment problems that are untraceable online. With the help of this study, the FMIPA UNNES environment departments will be able to monitor the upkeep of their lab equipment. The research approach starts with a literature review, followed by the first round of data collecting and observation, the design of an EAP-based system, system testing, system analysis, and system assessment. This research aims to create a product for the Monitoring Information System for the Maintenance of Laboratory Equipment using the SDLC (System Development Life Cycle) methodology. Testing involves the use of black box testing. The system's UAT grade of 88% implies that it is appropriate for use and may employ to simplify laboratory equipment management.&lt;/span&gt;
Pengaruh Metode Problem Based Learning (PBL) terhadap Hasil Belajar Siswa pada Mata Pelajaran Bahasa Inggris Kelas X SMK IT Al Qimmah

This study aims to determine the effect of the Problem Based Learning Method on Student Learning Outcomes in English Subject Class X SMK IT Al Qimmah academic year 2021/2022 . The method of learning English at SMKN 2 Selong is dominated by the old teaching method, namely the lecture method and giving assignments, this causes students to be passive and accept what is given by the teacher. Besides that, students are also not enthusiastic in the learning process and students prefer to be silent, so that communication only goes one way, therefore to solve this problem the researcher tries to use the Problem Based Learning Method on Student Learning Outcomes in English Class X SMK IT Al Qimmah Academic Year 2021/2022. This research is an experimental study with the research subjects used are students of class X.A as the experimental group with a total of 27 students and class X.B as a control group with a total of 27 students. After collecting and processing data, the researcher got the average score for the experimental group, which was 85.18, while in the control group it was 71.56. In testing the hypothesis, the researcher used the t-test formula. The researcher found that the t-test value was 4.276 and the t-table was at a significant level of 5%, namely 1.684, so the hypothesis was accepted. This means that there is an effect of the Problem Based Learning Method on Student Learning Outcomes in Class X English Subjects at SMK IT Al Qimmah academic year 2021/2022.
Improving Students Speaking Skill Through Role-Play in Universitas Teknologi Mataram

Speaking is one of tough skills that should be mastered by students in learning English. The aim of the research is to improve student’s speaking skill through role play technique. The subjects of this research were 24 students at the third semester of Secretary Department of Universitas Teknologi Mataram Academic Year 2019/2020. The result showed that there was a significant improvement of student’s speaking skill after using role play technique in teaching learning process. The students are able to speak in English fluently and confidently. The finding shows that role-play teaching technique is work well and can be applied to improve students speaking skill.
Neural Network-Based Robust Guaranteed Cost Control for Image-Based Visual Servoing of Quadrotor

In this article, a neural network (NN)-based robust guaranteed cost control design is proposed for image-based visual servoing (IBVS) control of quadrotors. According to the dynamics of three subsystems (yaw, height, and lateral subsystems) derived from the quadrotor IBVS dynamic model, the main control design is to solve the robust control problem for the time-varying lateral subsystem with angle constraints and uncertain disturbances. Considering the system dynamics, a two-loop structure is conducted. The outer loop uses the linear quadratic regulator to solve the Riccati equation for the lateral image feature system, and the inner loop adopts the optimal robust guaranteed cost control to solve the lateral velocity system. For the lateral velocity system, the optimal robust control problem is transformed to solve the modified Hamilton-Jacobi-Bellman equation of the corresponding optimal control problem utilizing adaptive dynamic programming. The implementation is accomplished with the time-varying NN and the designed estimated weight update law. In addition, the stability and effectiveness are proved by the theoretic proof and simulations.
The Workforce Diversity on Employee Performance in Toyota of Bowie, United States of America

The study examines workforce diversity on employee performance in Toyota of Bowie, United States of America. The primary aim was to examine the interactions between workforce diversity and employee performance. The study employed survey research design and simple random sampling techniques. Eighty-six (86) questionnaires were administered to the respondents of the selected firm via google form. The data are presented in the table as frequency distribution and descriptive statistics. Four hypotheses formulated were tested by using Linear Regression and Pearson Correlation. Results showed that gender diversity accounts for 9.3% influence on employee efficiency. There exists a moderate relationship between religious diversity and employee effectiveness in the organization. Ethnicity diversity influences the quality of service. There exists a weak relationship between age diversity and employee satisfaction. It was concluded that workforce diversity is also an influencer of employee performance and recommended among others that organisations should formulate policies that encourage employee development, as this will create a wide pool of knowledge within the organization thus enhancing organizational competitiveness.
The Right Way to Avoid Contamination by COVID-19 Virus Based on Barnes-Hut Algorithm

The spread of COVID-19 virus (known as Corona) has an exponential growth all around the world. China, the epicenter of the epidemic, is the most infected country. Tell 07/04/2020, she count 81 740 infected, 3331 death and dramatic socio-economic consequences. At start we have believed that stay at home is possible solution, but next we have thought that this is not the right way as new mutated virus appears. So, as there are no medicines, the best solution is to coexist with the virus. Our approach is in this direction. Keep safe distance (1m or 3 feet) is the most relevant consign in order to surround the spread of the epidemic. Our approach is used to detect possible proximity of persons and to protect them in advance before contamination. We propose an algorithm, Barnes-Hut algorithm, based on Quad, a data structure which detects some proximity relative to persons and groups of persons. Alert is raised when the proximity between parsons is not respected. The algorithm can be used in decision making (e.g close frontiers). Experiments on real world dataset show the efficiency of the algorithm.
Enhancing Post-Pandemic EFL Education by Leveraging Immersive, NLP-Driven, AI-based Tools That Promote Collaboration and Interactivity within an Educational Approach

This paper aims to improve post-pandemic English as a Foreign Language (EFL) education by leveraging immersive, NLP-driven, AI-based tools that promote collaboration and interactivity in teaching. It is because the COVID-19 pandemic has significantly disrupted conventional language education, leading to a shift towards online instruction and requiring new language learning strategies. The study used a mixedmethods approach integrating quantitative and qualitative data collection and processing strategies to examine the effectiveness of collaborative and interactive AI-powered natural language processing (NLP) applications on EFL instruction in a post-pandemic online teaching environment. To collect data, teachers, and students at the University of Abomey-Calavi (UAC) in Benin were surveyed, interviewed, and observed during online language learning sessions. The data was analysed using both descriptive and inferential statistical methods. The study used questionnaire surveys to analyze the quantitative data and the thematic (content) analysis method to identify significant trends and themes in the qualitative data collected through semi-structured interviews and online class observations. The results revealed the advantages and disadvantages of using AI-supported collaborative and interactive language learning in EFL instruction, the learning methodologies and assessment approaches used in AI-supported online collaborative learning, the role of technology in supporting lifelong learning, and the impact of ICT teacher training on the integration of AI-supported online collaborative learning in EFL instruction. The outcomes provide new insights into the impact of AI-assisted collaborative and interactive language learning on EFL instruction and its implications for EFL teachers and students in the post-COVID-19 era.
Impact of change leadership on perceptions of organizational performance after ERP implementation: the moderating role of vendor support in a Pakistani context

This research focuses on the impact of change leadership of ERP on organizational performance with moderating role of vendor support.To test our ideas, data was collected from both technical and non-technical employees of public and private sector organizations located in Rawalpindi and Islamabad (Pakistan) which implemented ERP in the recent past.Data were analyzed through structural equation modelling using SmartPLS.Results suggest that change leadership was positively related to enhancing organizational performance after ERP implementation.However, vendor support moderated this link such that the impact of change leadership was higher when organizations received higher levels of vendor support.
Aggregate Query Frameworks for Preserving Privacy Data in Big Data Analytics

Abstract Data utility and data privacy are both serious issues that must be considered when datasets are released to use in big data analytics because they are traded-off issues. That is, high-utility datasets are generally high risks in terms of privacy violation issues. Likewise, datasets are formed to be high security in terms of privacy preservation, they often lead to data utility issues. To address these issues in datasets, several privacy preservation models have been proposed such as k-Anonymity, l-Diversity, t-Closeness, Anatomy, k-Likeness, and (l p1 , . . . , l pn )-Privacy, i.e., all users’ explicit identifier values and all unique quasi-identifier values in datasets are removed and distorted respectively. Unfortunately, these privacy preservation models are static data models and still have data utility issues that must be addressed. Thus, they could be insufficient to address privacy violation issues in big data analytics. For this reason, a new efficient and effective privacy preservation model is proposed in this work such that it is based on aggregate query answers that can guarantee the confidence of the range and the minimized number of values that can be re-identified. The aims of the proposed privacy preservation model are that aside from privacy preservation constraints, the complexity and data utility are also maintained as much as possible. Furthermore, we show that the proposed model is a privacy preservation model that is efficient and effective by using extensive experiments.
Predictive Analysis Pendidikan Menggunakan Machine Learning di Sumatera Barat

This study uses big data, namely the socio-economic 2019 data. The focus of this research is Education. Education is an important factor in life, but in West Sumatra using the socio-economic 2019 data it is still in the low category and far from the national average. In this study will predict the factors that influence education in West Sumatra with the data classification method. Methods for classifying large amounts of data have been developed, including Machine Learning. Machine Learning is a field of technology that is currently being widely used to create algorithms with large data (big data). The machine learning method used is Naive Bayes and Bagging. Furthermore, the two models were tested and showed that the Naive Bayes model gave the best performance compared to the Bagging model based on the values of accuracy, sensitivity and specificity. So the Naive Bayes model is the best machine learning model for predicting the factors that affect education, namely household members, gender and regional classification.
Statismof a divided nation and static ideological territorialization of memory : Focusing on the analysis of the Independence Hall of Korea

이 논문은 국가테러리즘적인 분단국가주의를 활용함으로써 분단국가의 ‘국민-만들기’를 수행하던 한국의 분단국가주의가 민주화를 거친 후 권위주의 정권이 해체되었음에도 불구하고 지속되고 있는 현실을 지적한다. 분단국가주의는 여전히 분단적대성을 활용하면서 문화적 폭력을 만들어 내고 있으며, 기념관과 같은 공간은 분단국가주의가 역사적인 집단의 기억을 국가이념적으로 영토화하는 장소로서 기능하고 있다. 독립기념관은 이러한 대표적인 공간이자, 식민과 독립이라는 기억을 활용하여 분단적대성의 기억 코드를 영토화하는 양상을 보이는 공간이다. 여기에서는 독립기념관의 공간 내러티브를 분석함으로써 전면적인 서사가 아님에도 분단국가주의적으로 작동하는 기억의 영토화된 현황을 밝힌다. This study points out the reality that Korea’s divided statism, which is carrying out ‘nation-making’ of a divided statism by utilizing national terrorism, continues despite the dissolution of authoritarian regimes after democratization. However, divided statism still creates cultural violence while utilizing division antagonism, and spaces such as memorials function as places where divided statism territorializes the historical group’s memory through national ideology. The Independence Hall of Korea is a representative space, and it is a space that shows the aspect of territorializing the memory code of division hostility by utilizing the memory of colonialism and independence. In this study by analyzing the spatial narrative of the Independence Hall of Korea, reveals the current state of territorialization of memories that operate in a way of divided statism, even though it is not a typical narrative.
PERSONALITY CLASSIFICATION USING DATA MINING

Personality classification is the process of analyzing and summarizing the relevant emotional information in the text, so as to infer the personality traits in the text.Personality is a complex, abstract concept that refers to characteristic patterns of thinking, feeling, and behaving including motivations, emotions, beliefs, and typical approaches to interacting with others.This project comes across areas where it has access to large amounts of person behavioral data.This learning can now be used to classify/predict user personality based on past classifications.The system analyses vast user characteristics and behaviors and based on the patterns observed, it stores its own user characteristics patterns in a database.The system now predicts new user personality based on personality data stored by classification of previous user data.This system is useful to social networks as well as various ad selling online networks to classify user personality and sell more relevant ads.Also the system is useful for government agencies to observe user personality and predict new user personality on a large scale.
The Aesthetics of a Movement Realized by Digital Special Effects : Representation and Realism

오늘날 영화는 디지털 테크놀로지를 활용해 새로운 움직임을 보여 주고 있다. 과거의 관습적인 움직임과는 달리 정지와 가속, 추상적 움직임 등을 활용해 인간의 시지각을 벗어난다. 또한 이러한 움직임은 대상을 재현하기보다는 시공간을 해체하면서 힘과 강도를 표현한다. 이러한 움직임이 끌어내는 새로운 영화적 효과는 무엇보다 정동(affect) 개념을 통해 이해할 수 있는데, 대표적인 것이 "포스트-시네마" 연구이다. 포스트-시네마 담론은 정동 이론을 토대로 이러한 움직임이 지닌 새로운 가능성을 찾아낸다. 그 결과는 주체와 객체의 구분을 무너뜨린다. 그리고 영화적 움직임과 일상적 사물의 운동을 같은 것으로 본다. 그 결과 이들의 주장이 마주하는 것은 영화적 움직임의 해체 혹은 소멸이다. 그러나 디지털 특수효과로 구현된 새로운 움직임을 ‘사전 가속(pre accelration)’과 ‘애니메티즘(animetism)’의 개념으로 해석해 내면 디지털 특수효과로 구현된 새로운 움직임의 의미를 다르게 이해할 수 있다. 움직임에는 ‘사전 가속’의 단계가 작용한다. 그리고 디지털 특수효과는 주로 ‘레이어(layer)’를 교차하여 움직임을 만드는 이른바 ‘애니메티즘’으로 구현된다. 따라서 이러한 움직임은 주체와 객체의 분리를 없애는 비재현적인 것이라기보다는 재현의 여지를 지니고 있으며, ‘상관 불가능성(dis-correlation)’의 리얼리즘이라는 측면에서 이해할 수 있다. Today"s movies are showing new movements using digital technology. Unlike conventional movements in the past, it uses stop, acceleration, and abstract movements to escape human perception. In addition, these movements express strength and strength while dismantling space-time rather than reproducing objects. The new cinematic effects of these movements can be understood above all through the concept of affect, and the representative one is the "post-cinema" study. Post-cinema discourse finds new possibilities of this movement based on the theory of sentiment. As a result, the film movement and the movement of everyday objects are viewed as the same, breaking the distinction between the subject and the object. As a result, what their arguments face is the dissolution or extinction of cinematic movements. However, if new movements implemented by digital special effects are interpreted as concepts of "preacceleration" and "animationism", the meaning of new movements implemented by digital special effects can be understood differently. The step of "preacceleration" acts on the movement. And digital special effects are mainly implemented by so-called animatism, which creates movement by crossing layers. Therefore, this movement has room for reproduction rather than non-reproduction to eliminate the separation of subjects and objects, and can be understood in terms of realism of "dis-correlation".
Pengembangan Sistem Informasi Kredit Rumah Pegawai Pada Balai Pengelolaan Das Agam Kuantan Padang

After conducting directly research into the Balai Pengelolaan DAS Kuantan Agam to find out the problems being faced by observations and interviews (interviews) with interested parties, it was found that data in the processing of home loan system was still manually. Processing data uses Microsoft Office Excel by input data to the tables and using formulas in Excel. This is find the problems about processing data. The problem that find double data in the management data. The information have a long time for processing data. The solve for this problem is development of housing credit data management. Development is make a program that uses a database to data storage and data processing to quickly and precisely. So the report will be faster, precise and accurate. For running this system have a very adequate device. The methodology in this research is field research, library research and laboratory research.
Externalities in Education, Scientific Knowledge and Scientific Research

This paper explores how different activities of the State: the outcomes of education, scientific knowledge and research, and technology are interdependent with both positive and negative externalities of society and market structure. It discusses specifically the significance of education, the information wealth of a global knowledge society and the dilemma of the economics of knowledge, which, at the same time have important implications for private investment and intellectual property protections of the new knowledge. This paper aims to examine the complex interactions between the market's role and State intervention in order to achieve two goals: satisfying monetary interests and maintaining balance between technological innovation and productivity gains. Additionally, governmental policy tools play a crucial role in providing equal access to education, open-source knowledge, and research and development opportunities, which allows both society and inventors to benefit from new technology.