Reviewerly/exHarmony huggingface dataset:
PREDICTIVE MAINTENANCE OF SINGLE PHASE AC MOTOR USING IOT SENSOR DATA AND MACHINE LEARNING (SIMPLE LINEAR REGRESSION AND MULTIPLE LINEAR REGRESSION ALGORITHMS)

Predictive maintenance techniques are proposed to find out the condition of operating equipment in order to predict when failure will take place or maintenance will be essential. The crucial aim is to provide cost savings over schedule based preventative maintenance or unexpected reactive maintenance, which could result in machinery being unavailable throughout the critical periods. There are many approaches for predicting failures, in this project current analysis approach is used where the voltage and current of electricity is measured which is supplied to the motor. But these analyses can't situate by themselves. Architecture is desirable to sustain the end-to-end workflow that allows for processing at the edge and moves the data from the integrated network to a central depository for analysis and monitoring. To do predictive maintenance, firstly we have to build an integrated network of PZEM-004T meter with a Node MCU ESP8266 -12E Module that will monitor and collect data about the voltage, current, and active power of AC motor under test which are used here as key variables for determining the status of AC motor. Our approach consists of two stages. The first incorporates data gathering, data processing, and then applying supervised learning methods to gain insights from the data and the second follows the first to build predictive models which can work easily and efficiently as per our requirement. Using Regression ML (Machine Learning) an algorithm that is Simple Linear Regression (SLR) And Multiple Linear Regression (MLR) machine under test (motor 1 and motor 2) performance can be optimize and provide new statistic patterns which make the backbone of prediction analysis. The machine learning algorithm is applied to the collected and processed data based on which results are obtained. The obtained test result is compared with obtained predicted result based on which the prediction accuracy of each machine learning algorithm is decided. Accuracy can be further improved by using much more data while applying the machine learning algorithms, as the number of data streams increases prediction accuracyincreases.These models are trained for long time to respond to new data or new values and then it delivers the results we need with more accuracy.
Selection of Test Case Features Using Fuzzy Entropy Measure and Random Forest

Faults are extracted from the source code, from the pre -processed metrics and the related fault data.The generated faults are represented as a data set and are categorised into code, design and other features.Selection of features and identifying the importance of the attributes from the given set of test cases is one of the important tasks in the software testing phase.A Fuzzy based evaluation of features using the Entropy measure and Hurwicz criterion has been carried on the code and design metrics for different test cases.The datasets have been further analysed using the Random Forest Approach for identifying the feature that has the higher priority.The results obtained using the Fuzzy Entropy measure and the Random Forest approach exhibits a similarity of 95 % in identifying the feature importance.The results show that the feature NUM_OPERANDS is having the highest impact from the given list of features by applying Fuzzy Entropy measure and the model built using Random Forest approach.
Secure Online/Offline Attribute-Based Encryption for IoT Users in Cloud Computing

To ensure the security of mass data sharing in the Internet of Things, the cloud computing platform is supposed to provide data-storage services. The ciphertext-policy attribute-based encryption (CP-ABE) schemes has attracted wide-scale attention since users can access the cloud platform in a fine-grained manner. However, there are still some problems in the existing CP-ABE schemes when directly applied in the Internet of Things environment. The problem of simultaneously achieves large computational cost in the encryption and decryption. Moreover, the privacy of access control policy actually still remains unresolved. To fill the gap of the existing schemes, this paper proposes a suitable data sharing scheme for IoT devices which can’t always be online. We use the online/offline CP-ABE technology with privacy, while hiding the access control structure and reducing the computational cost of the devices when they are online. The asymptotic complexity comparison also shows that our scheme achieves high computation efficiency.
Adaptive Authentication Technologies in Behavioral Analysis Solutions of Robotic Systems

The paper considers some common aspects of the design of adaptive authentication technology that acts as an executive mechanism in the event of incidents recorded by systems of intelligent control and monitoring.In particular, the author considers in detail the class of User and Entity Behaviour Analytics systems representing an intelligent analytical layer over existing technologies of security and allowing one to identify the deviations in the behaviour of users, and prioritize the recorded incidents.The paper considers in detail the area of application of adaptive authentication technologies in robotic systems.The urgency of the perfection of modern agent authentication methods in mobile robotic groups is defined by the prompt growth of propagation of group robotics in the solution of a wide spectrum of tasks.As a response to the found anomalies in the behaviour of a mobile robotic group agent, it is offered to carry out an additional procedure of authentication, selecting the technique of additional authentication according to the type of the found anomaly and previously constructed profile of a certain subject of access.
Creative Writing from Theory to Practice: Multi-Tasks for Developing Majmaah University Students' Creative Writing Competence

This research investigates the efficiency of applying creative writing multi-tasks in developing level 4 female English major students' creative writing competence.The study conducted for 12 weeks in 2018-2019 academic year, in Zulfi College of Education, Majmaah University, Kingdom of Saudi Arabia (KSA).The sample consists of 64 female students divided equally into two groups: experimental and control groups.The experimental group studied an advanced college writing course supported by the creative writing multitasks designed by the researcher.A group of pre and posttest design was applied in the study.When the pre and posttest's scores of the experimental group were analyzed and compared, it was detected that there was a statistically considerable difference in the pre-and posttest scores, in favor of posttest's score.Also, it shows that there was a significant difference in the mean scores of the experimental and control group posttest's scores, favoring the experimental group posttest's score.These results prove the main research hypothesis: Creative writing multi-tasks have a significant impact on developing the experimental group's creative writing competence, compared to the control group.The findings indicate that using creative writing multitasks has a positive effect on developing the students' creative writing competence in both fiction and nonfiction essays.It is recommended for English language teachers to adopt similar creative writing multitasks when teaching writing skill.
Suggestions on Accelerating the Implementation of Artificial Intelligence Technology in University Information System

In order to cope with the challenge of New Engineering Education, to make up for the insufficiency of high quality educational resources in colleges and universities, the single form of teaching, and the lack of individualized and innovative education, we recommend intelligently reconstruct or upgrade the university information system by using emerging technologies such as “artificial intelligence” as the core and taking cultivating high-quality innovative talents as the ultimate goal, thereby improving the information-based teaching environment of college education in China, improving the quality of teaching, reducing the cost of high-quality teaching resources, accelerating the process of educational intelligence in China’s colleges and universities, and realizing the strategy of strengthening the country through education.
Mobile Based Voting Application

Now a days electronic voting is a good practice, although it contains some issues like long lingering lines, time consumption, registration process being tedious and lack security; due to which people may not turn up at polling station in fear of been bullied to vote someone else they don't wish to. The proposed project is based on mobile voting application. Mobile-base voting application can prevent above issues and it is the most secure way to vote as it contains fingerprint and face verification technique. In this proposed project the user to registers with application. Further the user will have to provide details along with his fingerprints or face-scan according to user's desire. Post registration the user will authenticate themselves by providing fingerprint or face-scan; if the fingerprint or face-scan matched with that of the stored in Firebase then and only then the user is authenticated, hence user need not remember any password in order to log in to application. This will reduce the complex task of remembering the password and increase the security as the bio-metric is unique to every person. The proposed architecture is expected to provide secured access to only authenticated users of a system within a short period of time and prohibit violators from gaining any access. This purposed system prevents duplication of vote and allow voter to vote in their comfort zone.
PERMAINAN ULAR TANGGA DAN KARTU PINTAR PADA MATERI BANGUN DATAR

Playing is near the world of children. The development of the times, science and technology make the purpose of playing not only for mere pleasure, but also need to be inserted educative values in it. The snake ladder game is a game that is liked by elementary school students. Learning mathematics with a snake ladder game media can motivate students to continue learning to develop their abilities by actively involving students in learning. The game of snakes and ladders combined with smart cards can help the students' mathematical learning process to build up flat material. Learning by playing can provide opportunities for students to explore, discover themselves, practice and get a variety of concepts and innumerable understandings and this is where the learning process takes place The teacher is not only limited to transferring knowledge but also guiding students to be skilled in finding concepts of knowledge with experience itself through an inspirational and pleasant learning atmosphere. Thus mathematics subjects which are one of the important sciences that are learned for elementary school students, because they are always used in solving problems in everyday life into pleasant subjects.
Integrating Cloud World Synergy in ELT to Adults: Perspectives of Handheld Technologies

&lt;p&gt;The outcomes of modern technology have turned real-world interaction into a virtual community, then into a cloud one. These giant leaps aided by the excitement created by the possibilities inherent in learning through handheld technologies made using mobile devices in English language teaching (ELT) indispensable. This paper is aimed to deeply overview available handheld technologies and their features that can enable teachers in their mission. It investigates the synergy of a group of mobile devices of smartphones, tablets, iPods, iPads, E-readers, and classroom response systems, among others. These devices have been effective in everyday activities, and are expected to enrich ELT, especially in communities where there is a lack of community of practice (CoP) on the target language. To this aim, this paper was cored around reviewing the potential handheld technologies have in language classrooms. The main data were obtained from the rich body of literature, shedding more light on their properties in creating interactive communication in and out of classrooms. The findings revealed that handheld technologies can be successfully integrated into English language teaching and learning. Pedagogically, teachers are encouraged to exploit mobile devices into their classroom practices after closely testing their specifications, and scanning their advantages and shortcomings.&lt;/p&gt;
Model-based On-board Decision Making for Autonomous Aircraft

Powerful, small and lightweight sensors in combination with advanced failure detection, diagnosis, and prognostics techniques provide up-to-date data on the health status of a Unmanned Aerial System (UAS). In an autonomous UAS, this information must be used for automatic planning and execution of contingency actions to keep the UAS safe in adverse conditions.We present DM (Decision Maker), a software component which uses model-based reasoning, backtracking search to iteratively construct contingency plansthat are safe for the UAS to execute and pose minimal interruption to the mission goals. The DM, which has been developed within the NASA Autonomous Operating System (AOS) project thus fills the gap between Prognostics and Health Management and autonomous flight operations.In this paper, we describe DM and its reasoning/search algorithm and present the supporting modeling framework for the construction of system and fault models. An flight with a DJI S1000+ octocopter with fault injection will be used as our case study.
A greedy randomized adaptive search procedure application to solve the travelling salesman problem

The main objective of this article is to show an algorithm capable to find a minimal total length evaluation function roundtrip in symmetric Travelling Salesman Problem (TSP).Application of concepts related to Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristics, with a 2D Euclidean distance between nodes and return to start point.It was implemented through two instances defined in the TSPLIB.As results, it was observed that in all iterations the value of the initial solution, such as constructive heuristic, minimized over the course of local search optimization process, developed by the assumptions of the 2-Opt heuristics, where the best results found (836909 km) was established for simulation considering a total of 5000 iterations.The traditional TSP solution has a strong implication in determining product delivery routes for customers established in different locations, inspired by the vendors' need to deliver products in different locations (the cities) using a shorter route, reducing the time required for the trip and the possible costs.Furthermore, the use of efficient TSP resolution methods can be adapted to applications found in industrial process practices, such as determining the delivery routes of materials to traverse a range of sectors from a common distribution center.
Implementation of chain story techniques to improve english speaking ability at imanuel YPK vocational high school, Sorong City

The function of English as the international language that connects various countries with different languages makes English as an important communication tool to be learned and taught for students from various levels of education as the provision to face the current era of globalization. The chain story technique that implemented in this research, is a technique that is suitable to be used to teach students who have not dared to actively use English. This technique helps students of Imanuel YPK Vocational High School, Sorong City to work as a team and help each other to construct the sentence. This study was designed in the form of Classroom Action Research (CAR). The method of this research is a qualitative and quantitative method. The qualitative to explain the condition before and after the action. The quantitative to count the score of the students. As for the subject in this research is the Class X Automation and Office Management. This is done in order to obtain valid and reliable research data. Data collection techniques used were observation, test and interview. Results of the study showed that: (1) Based on the observation, the students are changed to be more brave and confident to speak English; (2) Based on the test, there is a very significant change towards the positive, when compared to the value of very good and good in cycle 1 which is 42% while in cycle 2 is 80%, so there is an increase of 38%; (3) Based on the interview, the students were happy and giving the good responses about the treatment and the progress they have done
Las tareas problematizadoras como propuesta para el desarrollo del pensamiento complejo

Complex thinking seen more as a trend or the most current must be seen as a path towards the development of competences that can give tools to solve tasks/projects and these must be considered from the stage of preparation towards the profesional life, it means in the universitary studies; with that in mind the Community Networks Project for the Renewal of Teaching – Learning in Higher Education (RECREA) suggests the application of a guide for the preparation of instructional designs aimed at the development of complex thinking, the application of the research in teaching and the integration of information and communication technologies. Design problem-solving tasks within the instructional design, contribute to learning based on complex thinking and to the development of the competences described in the graduation profile and the objectives of the subjects; achieving educational experiences that are meaningful for learning.
Object-Oriented State Abstraction in Reinforcement Learning for Video Games

We present a novel method to obtain object-oriented state representations for video games. Inspired by the mechanism of attention to objects in human vision, we try to make the agents automatically detect the important objects during the learning process. The detection is directed by the Q value based on the abstract state representations. The process does not require human prior knowledge and provides a faster and lighter way for AI playing games. We present empirical results on the Battle City game to validate our method. In comparison with raw images input and other preprocessing methods, our approach achieves better final results and uses smaller state space.
Open Source Software Survivability Prediction Using Multi Layer Perceptron

Many organizations develop software systems using Open Source Software (OSS) components. OSS components have a high risk of going out of support, making dependency on OSS components risky. So, it is imperative to perform risk assessment during the selection of OSS components. A model that can predict OSS survivability provides an objective criterion for such an assessment. Currently, there are no simple, quick and easy methods to predict survivability of OSS components. In this paper, we build a simple Multi Layer Perceptron (MLP) to predict OSS survivability. We performed experiments on 449 OSS components containing 215 active components and 234 inactive components collected from GitHub. The evaluation results show MLP achieves 81.44% validation accuracy for survivability prediction on GithHub dataset.
Solarmeter Design for High Solar Radiation Measurement and Experimental Validation

In this study, a solar meter was designed to measure high solar radiation. The solar meter uses the characteristic properties of a solar cell in order to measure solar radiation. In this way, measurements can be carried out without any limitations. The solar radiation equation was entered into the ARDUINO microcontroller in the solar meter, and the results were compared through another commercial solar meter. These results were entered into STATGRAPHIC software and three different functions with high regression values were obtained. These three functions were entered into the Arduino microcontroller and the experiments were repeated. According to the comparisons made using commercial device, R 2 values were determined as 0.944, 0.936, 0.938, and 0.986 for the first equation and for three different functions, respectively. Based on the values obtained, it has been determined that the solar meter can make highly accurate measurements and after the development of appropriate functions, it can be employed especially in high solar radiation concentrated systems.
Data-Driven Detection of Anomalies and Cascading Failures in Traffic Networks

Traffic networks are one of the most critical infrastructures for any community. The increasing integration of smart and connected sensors in traffic networks provides researchers with unique opportunities to study the dynamics of this critical community infrastructure. Our focus in this paper is on the failure dynamics of traffic networks. We are specifically interested in analyzing the cascade effects of traffic congestions caused by physical incidents, focusing on developing mechanisms to isolate and identify the source of a congestion. To analyze failure propagation, it is crucial to develop (a) monitors that can identify an anomaly and (b) a model to capture the dynamics of anomaly propagation. In this paper, we use real traffic data from Nashville, TN to demonstrate a novel anomaly detector and a Timed Failure Propagation Graph based diagnostics mechanism. Our novelty lies in the ability to capture the the spatial information and the interconnections of the traffic network as well as the use of recurrent neural network architectures to learn and predict the operation of a graph edge as a function of its immediate peers, including both incoming and outgoing branches. To study physical traffic incidents, we augment the real data with simulated data generated using SUMO, a microscopic traffic simulator. Our results show that we are able to build LSTM-based traffic-speed predictors with an average loss of 6.55 × 10^−4 compared to Gaussian Process Regression based predictors with an average loss of 1.78 × 10^−2. We are also able to detect anomalies with high precision and recall, resulting in an AUC of 0.8507 for the precision-recall curve. Finally, formulating the cascade propagation problem as a Timed Failure Propagation Graph, we are able to identify the source of a failure accurately.
DIGITAL TECHNOLOGY FOR EDUCATION VERSUS ENTERTAINMENT: A QUESTIONNAIRE

At a time when the world at large has gone entirely digital, we take a closer look at our students and ask whether we can call them techsavvy learners in the true sense of the word. There is some evidence in favour of the assumption that they go about their millennial lives as children of technology: we hardly ever see them without their smartphones; they always seem to have one more text message to send; they routinely take selfies to post them online before our eyes. These examples alone make it all too easy to take their digital literacy for granted. We assume that their preferences, both in and outside the classroom, are in synch with a fully digital state of mind, their study habits included. However, there is no guarantee that our students take an equally digital approach to learning and studying, as doing something for fun and doing something for education are not necessarily two sides of the same coin. In order to shed more light on the issue, a questionnaire has been designed containing five carefully framed questions with no explicit reference to proficiency in the use of modern technology, allowing for a more realistic insight into whether and how digital literacy can become part of one’s learning experience. A 100 sample size representative of students majoring in English at the University of Banja Luka, Bosnia and Herzegovina should provide at least some tentative answers about the extent to which they use their digital skills to learn more about the language they are studying.