Reviewerly/exHarmony huggingface dataset:
Foundations of a live data exploration environment

Context: A growing amount of code is written to explore and analyze data, often by data analysts who do not have a traditional background in programming, for example by journalists. Inquiry: The way such data anlysts write code is different from the way software engineers do so. They use few abstractions, work interactively and rely heavily on external libraries. We aim to capture this way of working and build a programming environment that makes data exploration easier by providing instant live feedback. Approach: We combine theoretical and applied approach. We present the \emph{data exploration calculus}, a formal language that captures the structure of code written by data analysts. We then implement a data exploration environment that evaluates code instantly during editing and shows previews of the results. Knowledge: We formally describe an algorithm for providing instant previews for the data exploration calculus that allows the user to modify code in an unrestricted way in a text editor. Supporting interactive editing is tricky as any edit can change the structure of code and fully recomputing the output would be too expensive. Grounding: We prove that our algorithm is correct and that it reuses previous results when updating previews after a number of common code edit operations. We also illustrate the practicality of our approach with an empirical evaluation and a case study. Importance: As data analysis becomes an ever more important use of programming, research on programming languages and tools needs to consider new kinds of programming workflows appropriate for those domains and conceive new kinds of tools that can support them. The present paper is one step in this important direction.
Digital Image Steganography Using Modified LSB and AES Cryptography

Internet of Things (IoT) serves as part of our routine life activities nowadays and the secrecy of data has been compromised and cyber-crimes are increasing at an alarming rate therefore, the needs of a secure environment is vital in order to secure the transmitting data. This calls for a method to secure the digital messages being sent over the internet. In this paper we propose a modified concept on hiding the confidential data in an image. Here the Image Steganography is achieved using Modified LSB. Modified LSB uses a certain condition to replace the bits of the confidential data at the least significant bit position of the pixels in the image so Cryptography approach is achieved using AES. In this way, Steganography and Cryptography when used together ensures enhanced security of digital messages. Experimentally we found that the proposed approach is less prone to passive and active attacks. Also, as in nature it is hybrid approach which preserves the confidentiality of the information better than existing approaches.
Tourism Geographic Information System using Google API Banten

Banten Province as a Province adjacent to the Capital City of Jakarta and Banten Province is a province that is very well known because it has tourist areas in districts and sub-districts in Banten that have the main attraction to be visited by tourists, but the lack of information about existing tourist objects , and in searching for tourist information there are still many using maps manually, so we need an application that provides information services about tourist attractions in Banten, Web information system design provides information about the potential of the region as a tourist attraction in Banten Province. The geographic information system of web-based tourism in the province of Banten by using the Google Map API that can facilitate tourists searching, the location of users, interesting places and to find out the natural beauty and history in the province of Banten. This system is designed to make it easier for users to use and be more interactive. Supported by facilities to show the direction to the tourist attractions chosen by the user, as well as the addition of data visualization. This system is expected to be a guide and dissemination of travel information in Banten Province. Presentation of information in the form of images and maps will make it easier to understand users who will get the information effectively and efficiently. With the presence of this application is provided to meet the information needs of attractions in Banten Province
Predicting Breast Cancer Survivability

this study concentrates on Predicting Breast Cancer Survivability using data mining, and comparing between three main predictive modeling tools. Precisely, we used three popular data mining methods: two from machine learning (artificial neural network and decision trees) and one from statistics (logistic regression), and aimed to choose the best model through the efficiency of each model and with the most effective variables to these models and the most common important predictor. We defined the three main modeling aims and uses by demonstrating the purpose of the modeling. By using data mining, we can begin to characterize and describe trends and patterns that reside in data and information. The preprocessed data set contents were of 87 variables and the total of the records are 457,389; which became 93 variables and 90308 records for each variable, and these dataset were from the SEER database. We have achieved more than three data mining techniques and we have investigated all the data mining techniques and finally we find the best thing to do is to focus about these data mining techniques which are Artificial Neural Network, Decision Trees and Logistic Regression by using SAS Enterprise Miner 5.2 which is in our view of point is the suitable system to use according to the facilities and the results given to us. Several experiments have been conducted using these algorithms. The achieved prediction implementations are Comparison-based techniques. However, we have found out that the neural network has a much better performance than the other two techniques. Finally, we can say that the model we chose has the highest accuracy which specialists in the breast cancer field can use and depend on.
Statistical Approaches to Detect Anomalies

The term anomaly is derived from a Greek word anomolia meaning uneven or irregular. Anomalies are often referred to as outliers in statistical terminology. For a given set of data if we plot a graph and observe, all the data points that are relative to each other will be plotted densely, whereas some data points which are irrelevant to the data set will be lied away from the rest of the points. We call those points as outliers or anomalies. Anomaly detection is also called as deviation detection, because outlying objects have attribute values that are significantly different from expected or typical attribute values. The anomaly detection is also called as exception mining because anomalies are exceptional in some sense. Anomalous data object is unusual, irregular or in some way, inconsistent with other data objects. In this case, unusual data object or irregular patterns need not be termed as not occurring frequently. If we take a large data set or a continuous data stream, then an unusual data object, that occurs ‘one in a thousand’ times, can occur millions of times in billions of events considered. To find out the anomalies in data sets, we have many approaches like statistical, proximity–based, density–based and cluster–based. Statistical approaches are model-based approaches where a model is created for the data and objects are calculated with respect to how they are relative with all other objects. In this paper, we will be discussing various statistical approaches to detect anomalies. Most statistical approaches to outlier detection are based on developing a probability distribution model and considering how probable objects are under that model.
Cyberbullying Detection in Social Networks: A Multi-Stage Approach

Cyberbullying, defined as the violent harassment of an individual towards a victim in electronic media, is a serious problem nowadays.If not prevented or mitigated, it can lead to affective disorders, poor academic performance, problems in social relationships, andultimately -to suicide attempts in youngsters and children.Because manual supervision in social networks (a space where cyberbullying can naturally occur) is laborious, automated approaches for cyberbullying detection are desirable.However, a considerable number of approaches treat this problem as merely aggressive text message detection, without considering the frequency of the harassment.The approach proposed in this work, in contrast, views cyberbullying detection as a process of three consecutive stages: aggressive text message detection, alleged aggressor and victim detection, and cyberbullying case detection.This approach was tested using a dataset extracted from Twitter; the approach obtained an F-score of 0.947 for the positive (cyberbullying) case.
Hotel-Related Factors and Employee Performance &amp;#34;The Case of Jordanian Four Star Hotels&amp;#34;

The study addresses the challenge of employee performance (EP) at the four-star hotels in Jordan by focusing on how hotel-related factors influencing EP. Multiple regression was used to predict EP and explain the impact of five predictors that are organization culture (OC), organization structure (OS), manager attitude (MA), empowerment (EM), and training culture (TC). A correlation was used to compare the relationship between study variables. The results of multiple regression indicated that EM was the strongest predictor of EP followed by MA, and TC, whereas OS and OC found to not influence the EP. Overall interrelations among the independent variables showed a positive strong relationship and positively related to EP. Based on the study findings, several recommendations are offered. Finally, the implications for management are discussed.
The use of machine learning algorithms for image recognition

The article presents a way of using machine learning algorithms to recognize objects in images. To implement this task, an artificial neural network was used, which has a high adaptability and allows work with a very large set of input data. The neural network was described using a program written in the MATLAB simulation environment. The basic problem faced by the designer of objects recognition is to collect a sufficient training set of images to achieve the high probability of correct recognition. The set of learning patterns in the artificial neural networks may contain from several dozen thousands to one million training samples. In this article at the beginning the neural network was pre-trained trained based on the images included in the publicly available CIFAR 100 database, which are characterized by a small size of 32x32 pixels. It contains 70 000 images assigned to 10 basic categories. Then the author's database, consisting from 1000 pedestrians, cars and road signs was used. The article contains a description of applied algorithm, method of supervised learning and correction of weight coefficients, selection of activation function and operation on max pooling filter. The results of proposed solution are presented in the form of screenshots from calculations and in figures depicting results of recognized objects. Attention was also paid to the impact of used database for learning the network on the speed of calculations and recognition efficiency. The proper selection of number and types of layers, number of neurons, activation function and the value of the learning factor is very important in designing the neural network in application to objects recognition contained in the images. The problems occurring in the process of learning the neural networks and suggestions for their further improvement are also presented.
Robots on Blockchain: Emergence of Robotic Service Organizations

Radical changes in the technological environment have been forcing service providers to consider whether, if so, how to automate any aspects of their services with robots and other emerging technologies. Some service providers have been adopting robotic service assistants, and even creating organizations partially or fully automated by robots. However, some service providers have not been able to fully take advantage of RSAs’ benefits in a way that enhances customer service experiences. We review those challenges of RSAs and discuss the potential application of blockchain technology in governing a robotic service organization, the concept we propose in this study. Drawing on transaction cost theory and resource-based theory, we discuss theoretical implications of the impact of blockchain technology on the governance of a robotic service organization. Our study represents one of the first theoretical research to evaluate the impact of blockchain technology in a robotic service economy.
PENGARUH MEDIA PEMBELAJARAN TERHADAP HASIL BELAJAR IPS DITINJAU DARI MINAT BELAJAR SISWA SEKOLAH DASAR

This study aimed at examining whether or not the teaching media gave impact to the social-subject learning outcome viewed from the studentsâ€™ interest. This was an experimental study. The study employed experimental design treatment by level 2x2. The sampling participants were the fifth graders of 86 Public Elementary School, Kota Tengah and 78 Public Elementary School, Kota Tengah, Gorontalo City, academic year of 2017/2018. The participants were selected through multi stage simple random sampling. The result of this study revealed that there was a significant impact of the teaching media usage towards the social-subject learning outcome that was viewed from the studentsâ€™ interest.
Pelatihan Penulisan Artikel Ilmiah dan Publikasi di Jurnal bagi Guru SMAN 4 Tualang, Kabupaten Siak

WRITING SCIENTIFIC ARTICLES AND PUBLICATIONS TRAINING IN JOURNALS FOR TEACHERS OF SMAN 4 TUALANG, SIAK REGENCY. The training of the article writing and journal publication was held in SMAN 4 Tualang, Kabupaten Siak-Riau due to teachers’ problems covering the lack of article writing knowledge, low motivation and awareness of the importance of conducting research and its dissemination particularly for teachers’ professional development. Moreover, the teachers did not know much about journals information whereby they could publish their article writing. Therefore, the outreach community team from Faculty of Education and Teachers’ training, Universitas Lancang Kuning Pekanbaru conducted this program in order to solve the teachers’ problems. This training was conducted in one day (8 hours) consisting of two sessions. In the first session (8-12 a.m.), the participants were given the materials about the essence, elements, and knowledge of article writing followed by making article draft (how to make a good title, abstract and introduction). In the second session (1-5 p.m.), the trainer gave materials pertaining to how to deal with publication process from registration, login, and article online submission in journals. The simulations were given as the trainer guided the participants to register to ELT Lectura FKIP Unilak Journal, Bio-Lectura Journal, and Lectura: Journal Pendidikan UNILAK, login, check and read information in the journals. In short, this training facilitated the SMAN 4 Tualang teachers’ knowledge and skills of article writing and they know how to publish their articles. The outreach team suggests future outreach community program conduct the same activity since there are many school teachers need the training of article writing and publication in journals.
A novel conceptual model of intrusion related gold bearing systems and exploration tools

Despite numerous debates conducted in the last two decades, the concept of intrusion related gold systems IRGS remains controversial and sometimes befuddling.The key issue drifts from case to case, i.e., initial to subsequent proposed classifications, presence of gold in reduced fluids-porphyritic environments, non-porphyry gold in orogenic terrains and participation of non-magmatic gold fluids in depositional processes.Trying to avoid atypical or particular aspects of certain deposits, a genuine metallogenetic depiction intends to enhance the intrusion related systems meaning.Gold is either a major constituent or a mere byproduct.A vertical metal zonation develops from surface to depth: Au, Ag  Cu, Pb, Zn  Cu, Au  Cu, Mo (Au), W  Fe, Cu, Au (Co,W)  U, Ce, La.Whether the relationship between different intrusion related occurrences is well known at shallow depth (epithermal, mesothermal, porphyry), so far less knowledge and understanding is assigned to deep seated mineralization (porphyry, Iron Oxides-Copper-Gold/IOCG).A specific relationship between those two deep seated ore styles emerges, that is the IOCG, confined to magmatic-hydrothermal type, is situated in the root zone of a deep porphyry system.Complementary information about updated classic exploration tools encompasses specifically geochemical association, geophysical signature, key alteration minerals, Au/Ag ratio and, last but not least, type minerals that contain/include gold in each intrusion related environment.A further valuable tool is given by the estimate of Au grade range specific to each gold bearing mineral sample in shallow or deep seated setting.
Separability of symmetric states and vandermonde decomposition

Abstract Symmetry is one of the central mysteries of quantum mechanics and plays an essential role in multipartite entanglement. In this paper, we consider the separability problem of quantum states in the symmetric space. We establish the relation between the separability of multiqubit symmetric states and the decomposability of Hermitian positive semidefinite matrices. This relation allows us to exchange concepts and ideas between quantum entanglement and Vandermonde decomposition. As an application, we build a suite of tools to investigate the decomposability and show the power of this relation both in theoretical and numerical aspects. For theoretical results, we establish the witness for the decomposability similar to the entanglement witness and characterize the decomposability of some subclasses of matrices. Furthermore, we provide the necessary conditions for the decomposability. Besides, we suggest a numerical algorithm to check whether a given matrix is decomposable. The numerical examples are tested to show the effectiveness.
Development and Application of Parts Assembly Guidance System Based on Augmented Reality

In the traditional assembly process, it is difficult for operators to quickly understand assembly process information from the instruction manual, which results in inefficient assembly process. Therefore, an assembly guidance system based on augmented reality is about to be proposed in this paper. Also, in view of the problem that geometric models cannot fully express part assembly relationships, this paper proposes to analyze and construct the assembly semantic information model of parts based on the part object model. On the basis of the above semantic information model, the assembly relationship between parts is visually modeled, and these information models are accurately superposed on the real assembly guidance environment by using AR and virtual space modeling technology. Finally, we recursively decompose the parts assembly situation in this paper, and establish the part assembly guidance prototype system to verify the order and accuracy of the part assembly guidance process.
IMPLEMENTASI MEDIA GAME EDUKASI QUIZIZZ UNTUK MENINGKATKAN HASIL BELAJAR MATEMATIKA MATERI SISTEM PERSAMAAN LINEAR TIGA VARIABEL KELAS X IPA 7 SMA NEGERI 15 SEMARANG TAHUN PELAJARAN 2019/2020

Improving the quality of education can be done by updating the learning process. One way is to update the learning approach or method. An interesting and enjoyable learning atmosphere in the classroom needs to be realized so that the learning process can run and the quality of education improves. The purpose of this study: a) determine the increase in student learning outcomes with the Quizizz Game media; b) know the improvement in process skills; c) know the students' responses. This research is a Classroom Action Research (CAR) with the subject of the research being the students of class X IPA 7 of SMA Negeri 15 Semarang. Data collection techniques by means of tests, observations, and questionnaires. The results of the study are: a) there is an increase in student learning outcomes from cycle I by 95 and cycle II by 96; b) there was an increase in students' process skills by 81 in cycle I and by 92 in cycle II; c) there is a positive response from students by 80% in cycle I and cycle II by 93%.  Keywords: Educational Games, Quizizz, Learning Outcomes
Teacher Performance, Parent's Role, and Student Learning Outcomes in Muhammadiyah Junior High School

The purpose of this research was to determine the effects of teacher performance and the role of parents toward student learning outcomes of Indonesian Language, Mathematics, English, and Natural Sciences in the grade 8 of Muhammadiyah 8 Junior High School Yogyakarta.This was a quantitative research with ex post facto approach.The research sample was 98 grade 8 students taken by simple random sampling technique.Data collection techniques was by questionnaires and documentation.The collected data were analyzed with descriptive analysis and hypothesis testing with Generalized Linear Model (GLZ).The results showed that (1) teacher performance significantly affect Indonesian Language learning outcome by 0,046/4,6% of Beta value; The role of parents also significantly affect Indonesian Language learning outcome by 0,040/4,0% of Beta value; (2) teacher performance affect Mathematics learning outcome by 0,020/2,0% of Beta value; the role of parents insignificantly affect Mathematics learning outcome by 0,001/0,1% of Beta value; (3) teacher performance insignificantly affect English Language learning outcome by 0,005/0,5% of Beta value; the role of parents significantly affect English Language learning outcome by 0,073/7,3% of Beta value; (4) teacher performance insignificantly affect Natural Sciences learning outcome by 0,000/0% of Beta value; the role of parents significantly affect Natural Sciences learning outcome by 0,028/2,8% of Beta value; The results of this research reaffirm the importance of the family' role as part of the tri-center of education (school, family, and community) which is a characteristic of Indonesia education.The family environment has an important role in improving student achievement in school.
Asymmetric multiple-image encryption based on equal modulus decomposition and frequency modulation

In this paper, an asymmetric multiple-image encryption based on equal modulus decomposition (EMD) and frequency modulation is proposed. First, every original image is frequency modulated by its corresponding predesigned phase function. Then a multiplexed spectrum can be obtained by multiplexing the extracted spectrums, which are extracted from the Fourier spectrums of original images via a filtering procedure. After inversely Fourier transforming the multiplexed spectrum, the obtained multiplexed image is further encoded by EMD. Compared with the previous EMD, the scheme gains higher security due to the lack of public keys. The encryption principle is described in detail and various numerical simulation results are presented to demonstrate the feasibility and security of our proposal.