Reviewerly/exHarmony huggingface dataset:
De Re Updates.

In this paper, we propose a lightweight yet powerful dynamic epistemic logic that captures not only the distinction between de dicto and de re knowledge but also the distinction between de dicto and de re updates. The logic is based on the dynamified version of an epistemic language extended with the assignment operator borrowed from dynamic logic, following the work of Wang and Seligman (Proc. AiML 2018). We obtain complete axiomatizations for the counterparts of public announcement logic and event-model-based DEL based on new reduction axioms taking care of the interactions between dynamics and assignments.
Meningkatkan kemampuan menyajikan data dalam diagram batang melalui penerapan model pembelajaran problem based learning (PBL) di sekolah dasar

Abstract . This article contains the result of research conducted on fourth grade elementary school students. As for the background of this research is the low ability of fourth grade students in presenting data on bar charts. The low ability of students in this material is influenced by: (1) students’ ability to solve problems is still low, (2) students often make mistakes in placing the components on bar chart, (3) students are not careful in reading data, and (4) distance learning by giving lots of practice questions makes students confusion. Efforts to improve the ability to present data on bar charts carried out in this study were to apply the problem based learning, especially about presenting data in bar charts. This research is a classroom action research. The results of this study indicate an increase in the value of the evaluation results carried out at the end of each cycle. This increase in learning outcomes proves that the problem based learning model is able to improve students’ ability to present data on bar charts.
PENGARUH PENGGUNAAN MODEL PEMBELAJARAN BERMAIN PERAN TERHADAP KETERAMPILAN MENYAMPAIKAN TEKS NEGOISASI SISWA KELAS X SMA N 1 RANAH PESISIR

This research is motivated by the low interest of students in speaking. This study aims to describe the skills of conveying the negotiation text of students before and after using the role playing learning model and the influence of the role playing model on the delivery of negotiation text skills in class X SMA N 1 Ranah Pesisir. This type of research is quantitative with experimental methods.The sample in this study were 24 students of class X IPA 1. The data in this study were the skills scores of Submitting Negotiation Texts before and after the role playing model of class X students of SMA N 1 Ranah Pesisir. The results of this study can be concluded as follows. First, the skill of conveying the negotiation text before using the role playing learning model obtained an average score of 65.51 with sufficient qualifications (C). Second, the skill of delivering negotiation texts after using the Role Play learning model has an average score of 76.15 with good qualifications (C). Third, based on the t-test, there is an effect of the Role Play learning model on the skills of conveying negotiation text for class X SMA N 1 Ranah Pesisir because tcount = 6.67 and t table = 1.71. accepted and H0 rejected.
Subgraph Augmentation with Application to Graph Mining

Graph classification, which aims to identify the category labels of graphs, plays a significant role in drug classification, toxicity detection, protein analysis etc. However, the limitation of the general scale of benchmark datasets makes easily causes graph classification models to fall into overfitting and undergeneralization. In this chapter, the M-Evolve framework is introduced for graph classification (Zhou et al., Data augmentation for graph classification. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management, pp. 2341–2344, 2020; Zhou et al., M-evolve: structural-mapping-based data augmentation for graph classification. In: IEEE Transactions on Network Science and Engineering, pp. 1–1, 2020), a novel technique for expanding graph structured data spaces and optimizing graph classifiers. Typical graph tasks such as node classification and link prediction are unified to generate graph classification patterns, demonstrating some applications to multiple tasks in graph mining. One of the main contributions of this chapter is to apply the technique of subgraph augmentation for various tasks. The M-Evolve is general and flexible, which can be easily combined with existing graph classification models. Extensive experiments are conducted on real datasets to illustrate the effectiveness of our framework.
Solving multiple linear regression problem using artificial neural network

Multiple linear regressions are an important tool used to find the relationship between a set of variables used in various scientific experiments. In this article we are going to introduce a simple method of solving an MLR problem that uses an artificial neural network to find the accurate and expected output from MLR problem. Different ANN types with different architecture will be tested, the error between the target outputs and the calculated ANN outputs will be investigated. A recommendation of using a certain type of ANN based on the experimental results will be raised. [FP1] [FP1] Please merge this abstract into a single paragraph.
SMART VISION BASED TECHNOLOGY FOR BLING AND IMPAIRED PEOPLE

The Smart Vision based technology for blind and visually impaired people is a developing area. The assistive technology helps the visually impaired by providing them with a greater independence. By enabling them with a day – to - day activities like indoor navigations, obstacle detections, locating the door and lost objects etc. The extension in this project is to detect the indoor objects and provide the specific object name through speech. Even though different assistive technologies are available for the blind, most of them have complex designs which are developed for specific purpose and are expensive for the commercial production.
An Amalgam Approach for Secured Communication in VANET

In VANET, the vehicles are constructed with advanced communication mechanism along with sensor devices, this system transform the details of own vehicles such as  speed, location, road warnings to nearby vehicles and RSU(road side units) by wireless interface such as DSRC(dedicated short range communication), the communication is in the vehicle to vehicle and vehicle to infrastructure. In VANET, the vehicles are sharing the information regarding Road accidents, conditions, whether report, adjacent vehicle speed extra,,without any modification. so the communication should be very secured and reliable. For the purpose of strong security, this paper proposed cryptographic encryption method. This paper explain the structure of AES symmetric key block cipher algorithm and combine the AES algorithm with RSA algorithm(an amalgam approach)  for the feasible communication then evaluate the encryption decryption simulation time of the proposed model with NS2 software. This optimal technique is helpful to provide authenticated communication to the VANET.
Morpheme-Based Chemical Term Analysis and Recognition

Term recognition is the foundation of natural language processing, especially in chemical domain. The most important feature of domain text is terminology. Because of the variety and the complexity of chemical terms, chemical term NER is too difficult to be used in a production environment such as patents search. Based on the theory of morphemes and data of Chinese patents, we construct a chemical morpheme classification according to the composition characteristics and formation rules of chemical terms. A simple and stable HMM (The Hidden Markov Model) model is used to model the word formation relationship among different morphemes. The improved forward algorithm is applied to estimate the word formation probability in terminology recognition. It solves the problem of poor recognition of the long terms in low frequency in traditional statistical methods. It also solves the problem of subjectivity and completeness in establishing rules to some extent. Finally, the F1 reaches 91.58% in chemical patents.
Image Compression based on Octagon Based Intra Prediction

Recently image coding has been an important research area in many fields. Various compression algorithms have been developed in different ways for image compression. One of the ways in image coding is prediction based image coding. This paper proposes a novel technique for finding the prediction of a current pixel. Instead of traditional four mode prediction, this paper proposes an eight mode prediction scheme. The proposed method is tested with nine traditional images and compared with four recent methods. Experimental results substantially proved that the proposed method is better than recent methods..
APLIKASI EDUKASI PENGENALAN RENTAL MOBIL DI BATAM MENGGUNAKAN AUGEMENTED REALITY BERBASIS ANDROID

Education example in media promotion of car rental services. The application of this education has a purpose where in its application the public can use car rental services and easily determine the car they want to use. Augmented Reality is an interaction that combines virtual objects into two dimensions or three dimensions which are then combined together so as to create a mix between realistic and virtual. Augmented reality is a multimedia that connects mobile devices as a means of taking pictures or objects and converting them into the form of applications that describe real situations or called 3D. Android is a Linux-based operating system that has been developed by the Open Handset Alliance such as software, hardware, and providers on Google, HTC, Intel, Motorola, Qualcomm, and T-Mobile which have the advantage of completeness of available applications. Carrying out an activity such as offering a car rental service is not easy because there is so much competition in the world. In this way there is still no significant improvement and less attractive
On the Shape of Timing Distributions in Free-Text Keystroke Dynamics Profiles

Keystroke dynamics is a soft biometric trait. Although the shape of the timing distributions in keystroke dynamics profiles is a central element for the accurate modeling of the behavioral patterns of the user, a simplified approach has been to presuppose normality. Careful consideration of the individual shapes for the timing models could lead to improvements in the error rates of current methods or possibly inspire new ones. The main objective of this study is to compare several heavy-tailed and positively skewed candidate distributions in order to rank them according to their merit for fitting timing histograms in keystroke dynamics profiles. Results are summarized in three ways: counting how many times each candidate distribution provides the best fit and ranking them in order of success, measuring average information content, and ranking candidate distributions according to the frequency of hypothesis rejection with an Anderson-Darling goodness of fit test. Seven distributions with two parameters and seven with three were evaluated against three publicly available free-text keystroke dynamics datasets. The results confirm the established use in the research community of the log-normal distribution, in its two- and three-parameter variations, as excellent choices for modeling the shape of timings histograms in keystroke dynamics profiles. However, the log-logistic distribution emerges as a clear winner among all two- and three-parameter candidates, consistently surpassing the log-normal and all the rest under the three evaluation criteria for both hold and flight times.
Applications Of Diophantine Equations In Chemical Reactions And Cryptography

This paper is concerned with practical applications of Diophantine equations and is intended for all readers interested in applied mathematics. We briefly explain an idea of encryption in Caesar ciphering in cryptography. Linear Diophantine equations are used to solve the chemical equations.
Robust Foreground Segmentation in RGBD Data from Complex Scenes Using Adversarial Networks

Foreground segmentation is a fundamental problem in many artificial intelligence and computer vision based applications. However, robust foreground segmentation with high precision is still a challenging problem in complex scenes. Currently, many of the existing algorithms process the input data in RGB space only, where the foreground segmentation performance is most likely degraded by various challenges like shadows, color camouflage, illumination changes, out of range camera sensors and bootstrapping. Cameras capturing RGBD data are highly active visual sensors as they provide depth information along with RGB of the given input images. Therefore, to address the challenging problem we propose a foreground segmentation algorithm based on conditional generative adversarial networks using RGB and depth data. The goal of our proposed model is to perform robust foreground segmentation in the presence of various complex scenes with high accuracy. For this purpose, we trained our GAN based CNN model with RGBD input data conditioned on ground-truth information in an adversarial fashion. During training, our proposed model aims to learn the foreground segmentation on the basis of cross-entropy loss and euclidean distance loss to identify between real vs fake samples. While during testing the model is given RGBD input to the trained generator network that performs robust foreground segmentation. Our proposed method is evaluated using two RGBD benchmark datasets that are SBM-RGBD and MULTIVISION kinect. Various experimental evaluations and comparative analysis of our proposed model with eleven existing methods confirm its superior performance.
Methods of copyright protection

Currently, the traditional objects of civil law are used in many areas, not only in terms of tangible assets (property and property rights), but also in the form of intangible - the results of intellectual activity. The main income of the economies of the developed countries of the world is obtained as a result of the creation of new intellectual property, their use in business relations. This requires a solid legal framework and a legal mechanism that guarantees the legitimate interests of right holders.
ANALISIS FAKTOR-FAKTOR YANG MEMENGARUHI PENGGUNAAN SISTEM INFORMASI AKADEMIK KHUSUS ORANG TUA

This time, parent's academic information system service or SIORTU is often found on several campuses. One of the campuses that provides this system is Islam Indonesia University. This system made for helping parents of students to monitor their children's academic activities. Until now, many parent of student who have not used this system. There are 20.068 SIORTU accounts provided for parents of students from 2015 to 2018. But, only 7.361 or 36,68% account who active between April 2018 and Maret 2019. This research discusses factors that influence to use siorto and why these factors are included. Expectations of this research, gave feedback to owner of SIORTU service to improve that system, provide references for future research and provide references for educational institution. So that, SIORTU can be use as expected. This research is a quantitative research, which is done by analyzing the data in the form of voting from 75 respondents. The research respondent is parent of student from Islam Indonesia University who have used this system from April 2018 to March 2019. The software who they use to analyze is SmartPLS 3 by Partial Least Squares (PLS) method. The result of analysis who obtained was pointing that factors that influence this system are social influence, facilitating condition, habit, behavioral intention. These factors are evidence from the result of the analysis which show a positive value on original sample estimate and significant value on T statistic.
SISTEM INFOMASI RESERFASI DAN PENGINAPAN PADA LEMBAGA PENJAMINAN MUTU PENDIDIKAN (LPMP) JAMBI BERBASIS WEB

Having a building and accommodation facilities is an extra value for the Education Quality Assurance Agency (LPMP) in receiving non-tax state revenue (PNBP), initially the buildings and accommodations contained in this institution were only used as facilities and infrastructure which included activities within the scope of the institution's work. In itself, in recent times, decisions and policies have been made by policies on the use of existing buildings and inns to make them more useful. At LPMP Jambi Province, data processing for building and lodging rentals is done manually, the manual processing is not finished in its implementation, reservations for lodging or building facilities for manual activities are running, online-based information systems are thought to help process data processing for building and lodging rentals at the LPMP office Jambi, with an online database-based method, the design of the reservation information system can make it easier for managers and customers to access the buildings and inns that are arranged.
Green Cloud Broker for Energy-Efficient Services in Cloud Computing Environment

Abstract: Environmental issues are receiving great attention from IT business and governance around the world. As a matter of fact, greenhouse gases, climate change and sustainability continue to grow; and IT businesses will remain struggling for improving their environmental impacts. Green Computing, Information and Communication Technologies (ICTs) or IT initiatives are now moving towards cloud or building their business applications on the cloud infrastructure. In addition to cost-effectiveness, scalability, and promised high uptime; greenness of infrastructure and services have been increasingly adapted over cloud in developing and underdeveloped countries. The paper analyzed the current green ICTs usage in higher education institutions. For the purpose, it selected an organization for primary data collection and case observation, investigation and analysis. Finally, the paper produced a green cloud broker framework for decision support in selecting and adapting green i.e., energy-efficient cloud products and services in educational institutions. It also implemented an energy-saving technique called Dynamic Voltage and Frequency Scaling (DVFS) technique which can also be used to reduce energy consumption levels of the cloud data centers where ICT products and services run in real sense. During the experimentation and simulation, a toolkit called CLOUDSIM was used. As a final research outcome, an energy-efficient framework DPS-MS: An Energy-Efficient Cloud Service Broker (EECSB) was developed for helping the cloud service users/decision makers.
Pelatihan Penggunaan Teknologi untuk Pengajaran Bahasa Inggris secara Inovatif Di Kelas untuk Guru-Guru MGMP Bahasa Inggris di Kabupaten Bantul

The application of CALL (Computer Assisted Language Learning) and MALL (Mobile Assisted Language Learning) based technology in language learning in the classroom is not new in this era. A variety of applications are available for free on the internet. However, the knowledge of teachers in Indonesia about the functions and ways of implementing these applications is still low. With this training, it is hoped that teachers will be increasingly able to use CALL and MALL-based applications and explain the pedagogical side simultaneously.
A SURVEY ON FREQUENT PATTERN MINING IN UNCERTAIN BIG DATA

Pattern mining is a significant way to mine data in attaining fascinating correlation statistics within the dataset. In that respect, different versions of pattern mining techniques are considered, specified as frequent itemset mining, sequence pattern mining, and structure mining. Frequent Pattern mining is a rising analytical task which is performed on data statistics using Big data, Machine Learning, Data Mining tools, and drives to bring out knowledge supported with domain target. Lately, researchers hold up close to mining frequent pattern across uncertain transaction dataset. Researchers get hold of to mining itemsets on uncertain big data that have got voluminous attention supported with Apache Hadoop and Spark framework. This paper attempts to present a comprehensive outline using specific approaches to perform pattern mining on uncertain data in the Big Data aspects. At first, we look into the trouble attached with pattern mining techniques related to Apache Hadoop, Apache Spark, parallel and distributed processing and examine them in the big data view. Frequent itemsets mining in uncertain data has been analyzed and this composition reasons out with open issues and further enhancement of present approaches.
PENERAPAN MODEL PEMBELAJARAN GALLERY WALK DENGAN MEDIA GAMBAR UNTUK MENINGKATKAN HASIL BELAJAR SISWA

This research was conducted because of the low learning outcomes of class X students of MA Syiar Islam Maibit in learning Economics. This is because the learning process is less innovative so that students are less enthusiastic in participating in Economics learning. The model used in this research is classroom action research with Kurt Lewin's model which consists of two cycles, each cycle having 4 stages, namely: planning, action, observation and reflection. The data techniques used were interviews, observation, documentation and tests. The results showed that: 1) The application of the Gallery Walk method can increase the activities of teachers and students. Evidenced by the results of observations of teacher activity in the first cycle who obtained a total score of 73.30 (sufficient), increased to 85 (good) in cycle II. It is also proven by the increase in the results of observations of students from the acquisition of a total score of 66.60 (enough) in the first cycle, increasing to 86.60 (good) in the second cycle. 2) The improvement of learning outcomes in Economics learning through the Gallery Walk method has increased. This can be seen from the class average value in the pre-cycle of 68.52 (less) with a proportion of 64%, in the first cycle it became 74.20 (sufficient) with a proportion of 80%, then increased to 89.28 (good) with the proportion of 92% in cycle II.Keyword: Koperatif Tipe Gallery Walk, learning outcomes
Penerapan Sistem Absensi Fingerprint Dengan Menggunakan Visual Basic 6.0 di CV. MEDIA INOVASI

Attendance is an important thing for an agency or company. because it is used in calculating the amount of an employee's salary or wages and from attendance it can also see the discipline of employee attendance. Therefore, in its implementation, the attendance process requires accuracy in its implementation so as not to hinder company performance. This final project is designing an employee attendance system at CV. INNOVATION MEDIA which is useful for providing good attendance information quickly and easily, also through this study is expected to provide convenience to employees of CV. INNOVATION MEDIA in doing attendance. Employee attendance system design at CV. INNOVATION MEDIA was developed using Visual Basic 6.0 software and with Finger Print as a tool. This system records employee attendance in the form of a daily attendance list. It is used to accommodate the data needed to streamline the information system. With this system, it is expected that the data processing process will be more effective and efficient. In searching for data it will be easier. The purpose of this study is to design an employee attendance information system which is expected to help the performance of the company, especially in the Human Resources sector, become faster and more practical.