Reviewerly/exHarmony huggingface dataset:
Development of Interactive Electronic Book Based Mathematics Teaching Materials on Cube and Cuboid in Junior High Schools

This research is motivated by the students' difficulties in imagining the building of three-dimensional space of cubes and cuboids especially when imagining the diagonal of space and the diagonal plane.Based on these problems researchers conducted research aimed at developing electronic book (e-book) based mathematics teaching materials on cube material and cuboids for the eighth grade of junior high school.E-book based mathematics teaching materials made by utilizing Adobe Acrobat Pro applicationis a document format in PDF form that can be inserted three-dimensional images and video.This research is a development by modifying the model of Thiagarajan (1974), comprising the steps of define, the design stage and develop stage.The subjects of the trial were the 8th grade students of SMP Negeri 2 Pagedangan.From the results of testingan e-book based mathematics teaching materials by the four validation experts, an average score of 4.42 was obtained from a maximum score of 5.00 with a very good category.From the results of the trial of e-book teaching materials by students obtained an average score of 4.06 from a maximum score of 5.00 with a good category.Overall, the interactive electronic books based on mathematics teaching materials are suitable to be used in learning cube and cuboid material.
Quiet Book Media Development to Improve Ecosystem Material Learning Results in Class V Elementary School

The objective of this study is to find out (1) Quiet Book media development procedures (2) Feasibilityof developing Quiet Book media. This type of research is Research and Development (R &amp;amp; D)research, with a trial design of One Group Pretest-Posttest Design. A limited-scale trial was carriedout on 5 VA class students and a large-scale trial was conducted on 25 VB grade students at theElementary School in Wringinanom village. Data collection was conducted using questionnaires,observations, and tests . Questionnaires are used to obtain student response data, observations areemployed to obtain learning implementation data, and tests used are to obtain learning outcomesdata on cognitive aspects of students. The results showed that the developed media had beendeclared feasible by obtaining 92% validity percentage, 93% practicality of learning implementation,and effectiveness of student learning outcomes from pretest to posttest which is 75.04 to 93.52, sothat an average increase in scores of 18 was obtained. Effectiveness was also analyzed using N-Gainwith Gain value of 0.74. So if it is interpreted in the Normalized Gain index table according to Hake,it is included in the High category (0.70 &amp;lt;g &amp;lt;1.00). Thus, it can be concluded that the development ofQuiet Book media is declared feasible to be used as a learning media
Strengthening Tertiary Students Writing Skills Through T.R.E.N.D. Model

Writing has always been subjected as a difficult task for students taking English language subjects during their first two semesters studying in tertiary education. For these students, writing a composition has been a task they would prefer to avoid doing. One of many reasons is the inability to first generate and organize their ideas for writing tasks. Besides, they faced difficulty in expressing themselves fluently or being able to write sentences that are grammatically correct in the target language. Realizing the importance of writing skills among undergraduates in the tertiary education, a study was carried out on 200 undergraduates who attended a day Malaysian University English Test (MUET) workshop to examine students’ writing ability through a proposed model of Transferring, Restructuring, Engaging, Negotiating and Documenting (T.R.E.N.D.). The findings had shown significant improvement in learners’ writing in term of coherency and the development of ideas after the workshop. As a whole, the use of T.R.E.N.D. Model had helped to improve students’ writing ability in terms of not only language proficiency, but also their level of confidence.
User Behavior and Trust Evaluation in Cloud Computing

Cloud computing helps organizations to dynamically increase the resource needs as and when needed, without the need to purchase them. Security is a basic concern in cloud computing, and threats can occur both internally and externally. Users can access the cloud infrastructure for software, operating system and network infrastructure provided by the Cloud Service Providers (CSP). Evaluating the user behavior in the cloud computing infrastructure is becoming more and more important for both Cloud Users (CSs) as well as Cloud Service Providers The CSPs must ensure the safety of users accessing the cloud. Since user authentication alone is not enough to ensure the safety of users, user behavior trust plays a critical role in ensuring the authenticity of the user as well as safety. In this paper, we present the importance of user behavior in modeling trust, associated evaluation principles and comparison between different trust models.
Energy efficiency in virtual machines allocation for cloud data centers with lottery algorithm

&lt;p&gt;Energy usage of data centers is a challenging and complex issue because computing applications and data are growing so quickly that increasingly larger servers and disks are needed to process them fast enough within the required time period. In the past few years, many approaches to virtual machine placement have been proposed. This study proposes a new approach for virtual machine allocation to physical hosts. Either minimizes the physical hosts and avoids the SLA violation. The proposed method in comparison to the other algorithms achieves better results.&lt;/p&gt;
IMPLEMENTASI SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT TULANG PADA MANUSIA MENGGUNAKAN METODE FORWARD CHAINING

Bone disease is a condition that damages the skeleton and makes bones weak and vulnerable to fractures. The high disease is caused by ignorance and lack of knowledge about the disease. Therefore, an expert system was created to diagnose bone disease in humans. The method used in making this expert system is the forward chaining method, forward chaining method using the PHP programming language and MySQL database. The results of this study are the application of expert systems to diagnose human bone disease using a forward chaining method that can be accessed by the public at large to diagnose early symptoms of bone disease without limited distance and time used.
Making use of students' digital habits in higher education: What they already know and what they learn

Varieties of digital practices have increasingly become part of people’s everyday lives and people, in general, use these communicative practices on a daily basis, mostly for social and entertaining purposes. As to higher education, researchers have pointed out that digital technology could be a useful tool in how to learn more effectively, if it is based on the abilities that students bring with them into higher education from their everyday life (for example, Buzzard et. al., 2011). In this case study, we explore the issue of students' digital practices in everyday life as well as in higher education, in a teacher training programme at a Swedish University. The aim is two-fold: on the one hand, to provide knowledge regarding students' everyday experiences of digital practices and the ways in which these are utilised in higher education; on the other hand, to contribute to the understanding of the ways in which higher education contributes to challenging and developing students' digital skills. Twenty-nine students from teacher training programmes participated in the study by answering a questionnaire. The results show that the students’ digital habits are not being used or acknowledged in higher education, except for when it comes to their Teacher Training Practice (TTP). Furthermore, the results also show that higher education contributes to students’ digital skills. This, we argue, could be of interest for teachers and researchers in teacher training programmes and for teachers in primary to tertiary education, in developing education activities with digital technology based on pupils’ and students’ digital habits. We can also see that the study can inspire other teachers in higher education, where the idea of using students’ digital habits perhaps is not yet taken into consideration.
The Development of Natural Disaster Digital Literacy (DILIBA) Android Based of Students’ Understanding at Primary Teacher Education Study Program, Peradaban University.

The used of internet, by increasingly gadget usage of Indonesian as much as 132,7, should be able to use positive thing such as developing natural disaster digital literacy.Indonesia territory is located in natural disaster prone area, such as hydrometeorology.It is included annual natural disaster which always hit Indonesia; flood and landslide disasters have high intensity.To minimize it Government collaborate with college has various effort to overcome it; however, natural disaster costs caused by hidrometeorologi still occurred especially on rainy season.Based on that case, it is needed to natural disaster education to the community by using the newest technology which can be used by anyone, anywhere and anytime such natural disaster digital literacy, this breakthrough can be done by habituating academic community as the user of the technology, they are the college students to utilize their gadget as media of natural disaster digital literacy.The development of digital media, facilitate natural disaster education enforcement for the college.Based on the case, researcher deliver this paper entitled The Development Concept of Natural disaster Digital Literacy (DILIBA) Android Based of Students' Understanding at Primary Teacher Education Study Program, Peradaban University.The aim of this research: 1) Draw up an understanding material of hidrometeorologi natural disaster for students of Primary Teacher Education Study Program, Peradaban University; 2) Create development concept of digital literacy Media Android based (DILIBA); 3) Make a digital comic application concept of natural disaster that can be used in all phone android based.
Path planning of UAV in mountain area’s forest rescuing

In forest rescuing, unmanned aerial vehicle(UAV) can not save all the areas at a time due to the influence of its physical properties and risk factor. So it is extremely important to bring the service efficiency of the UAV into full play. The optimal path planning problem of the UAV for forest rescuing is presented and a mathematic model of the problem is built up. On the basis of this, a fuzzy clustering -PSO - genetic algorithm is presented. The computational amount is decreased, a method combined of both the shortest distance and point clustering is adopted. The simulation test result indicates that when task number less than 30, particle swarm algorithm is superior to genetic algorithm, and vice versa. Both methods plan the same airline but time, and it can resolve the path planning problem of the UAV for water environmental monitoring effectively.
Journalist Use of Social Media: Guidelines for Media Organizations

Basic journalistic tenets such as transparency, gatekeeping and objectivity were considered at risk due to the rise of use of social media by journalists and news media. Resultantly, large numbers of news agencies have started issuing provisions and guidelines for their staff to manage their social media use. This study explores the complex relationship of selected news organizations with given use of social media. The content analysis is applied on the guidelines for the use of social media obtained from 12 news organizations, and their link with basic journalism principles is explored. The key purpose of the current study is to provide insight for scholars and Arab media management to have better understanding of journalists use of social media and how these guidelines are implemented by various leading news agencies. Practically, the observations in the study are helpful for news organizations who are defining their provisions or rules for social media use by their journalists.
An Improved Measurement-Oriented Marginal Multi-Bernoulli/Poisson Filter

The measurement-oriented marginal multi-Bernoulli/Poisson (MOMB/P) filter is an attractive approach for multi-target tracking.However, the effect of measurement on predicted target states may be weakened when the hypothesized tracks are separated, even if the measurement is close to the predicted target state.This is due to the inaccuracy of the missed detection hypothesis probabilities in the marginal association probabilities.To solve this problem, an improved MOMB/P (IMOMB/P) filter is proposed in this paper, by considering the measurement information in the missed detection hypotheses.Simulation results reveal a favorable comparison to the MOMB/P filter in terms of the Optimal Subpattern assignment (OSPA) distance and cardinality estimation.
Regression Task on Big Data with Convolutional Neural Network

As one of most widely utilized methods in deep learning, convolutional neural network (CNN) has been proven effective in many machine learning applications, especially in the areas of image understanding and computer vision. However, CNN is mainly used for applications with the approach of classification, while its usage for regression is not well-studied. In this work, we propose a strategy based on CNN with Visual Geometry Group Network (VGG) for image regression task. We have applied this method on images of MNIST processed with labels of continuous number. In our study, the original discrete classes of handwriting numbers are converted into float numbers with respect to normal distribution, thereby the traditional classification task in MNIST becomes a regression one. In our study, different loss functions such as Mean Absolute Error (MAE) and Log-cosh have been applied and validated. Final results generated by model trained with CNN with VGG with 10-fold cross-validation can be obtained, where MAE is less than 0.25, compared to the much higher error of around 3 with the use of other loss functions and convolutional layers. The significantly reduced error suggests the applicability of our proposed method.
The Relationship between Technology Usage and Marital Conflicts among Young Married Couples in Jimma Town

This study is conducted with the objective of investigating how technology usage causes marital conflict among married couples in Jimma town. The study employed mixed research design and collected data from 198 married couples that were randomly selected from the population. Data was collected using self-prepared questionnaire, standardized scales questionnaire and interview guide and analyzed using thematic data analysis method for qualitative data and quantitative data analysis method for quantitative once. The study found that technology usage was appropriate in marital relationship but only when the couples used technology in appropriate ways resulted in marital conflict. Among these technologies, Facebook, mobile usage and television watching statistically significant positive relationship with marital conflicts, r=.788, r=.642, and r=.63 respectively. The study also revealed that time spent on those technologies, issues of trust between couples, money and the time when couples have to use these technologies were the common causes of marital conflicts as a result of technology usages. In line with the findings obtained it was recommended that different organization such as welfare offices, NGOs and religious organizations should have to assign trained family and marriage counselors and social workers.
Providing Ontology-Based Access Control for Cloud Data by Exploiting Subsumption Property among Domains of Access Control

Cloud computing has pulled in numerous business organizations and users because of its simplified administration effort, minimal maintenance cost and pervasive access to out-sourced resources, which can be hardware or software.Users share these resources in large-scale environments over the Internet.Stringent access control must be implemented in a cloud storage system for protecting sensitive information.Access control models in the current literature such as Discretionary Access control (DAC), Mandatory Access Control model (MAC), Role-Based Access Model (RBAC) or Attribute Access Control Model (ABAC) consider the entities of access control in isolation and thus leading to incorrect access control decisions.In this paper, Ontology-Based Access Control is proposed.This proposal uses an ontology to model the entities associated with access control and their interrelationships among them, which could be effortlessly adjusted to Cloud environments.Ontology promises to streamline knowledge sharing among the entities.Subsumption property is exploited over concepts, properties and individuals.The experimental results show that the number of rules to be stored in Policy Base is reduced and reasoning time is also considerably reduced because of applying subsumption property and hence access decision is made faster.Also, our work is compared with the existing works against the state of art models with the help of access control metrics provided by the National Institute of Standards and Technology (NIST).Our work answers the queries related to metric effectively than the existing works.Hence the performance of the system is increased and suitable for securing cloud data.
Analisis Tingkat Kerawanan Longsor Dengan Integrasi Analytical Hierarchy Process dan Pemodelan Spasial Sistem Informasi Geografis di Kabupaten Aceh Tenggara

&lt;p&gt;Southeast Aceh District in Aceh Province is a district that often experiences landslides. High rainfall (&amp;gt;1600 mm/year) and hilly areas with slope levels above 40% are also indicators of landslide vulnerability. The study aims to determine the criteria for the biggest contributors to landslide vulnerability using the Analytical Hierarchy Process (AHP) method and find out the distribution of landslide vulnerability in Southeast Aceh District by using spatial modeling using Geographic Information Systems (GIS). Spatial data as a parameter in making landslide models includes 4 (four) parameters, they are land cover, rainfall, slope and soil movement. These parameters have sub-parameters such as land cover parameters that have sub-parameters, i.e empty land, shrubs, rice fields, fields/moor, gardens, settlements, rivers, secondary forests and primary forests. The slope parameters have sub-parameters i.e slope 0-8%, slope of 8-15%, slope of 15-25%, slope of 25-45%, slope&amp;gt; 45%. Rainfall parameters have sub-parameters which are 2,500-2,700 mm/yr, 2,700-2,900 mm/yr, 2,900-3,400 mm/ yr, 3,400-3,600 mm/yr and 3,600-3800 mm/yr. The parameters of soil motion have sub-parameters, i.e middle and middle high movements. These parameters and sub-parameters become questionnaires by Expert Choice 11 as Analytical Hierarchy Process (AHP) software. This questionnaire then becomes an interview material for expert experts to determine the weight values (parameters) and scores (sub-parameters). The weight values and scores obtained from the Expert Choice 11 application are used by the ArcGIS 10.6 to create a spatial model of the distribution of landslide vulnerabilities. Research has produced spatial distribution of landslide vulnerability with a low level of vulnerability distribution of 209,523.56 ha (49%), moderate vulnerability of 158,170.14 ha (37%) and high vulnerability of 56,640.76 (13%)&lt;/p&gt;
Review of Theoretical Research on Artificial Intelligence

This is the age of information explosion and the era of rapid development of new technology. In this era, artificial intelligence has also made a breakthrough development, and has become one of the most popular disciplines and research directions. The research results of artificial intelligence will be able to create more intelligent "more advanced products", and make it beyond human intelligence in more and more fields, artificial intelligence will improve and make greater contribution to the social development and human life.
Face Gestures Detection using Improved Viola-Jones Algorithm

Many studies indicate that words and sentences represent only 7% of our ways of communicating with our world, while the bulk goes to our movements and gestures that are translated into the minds of the recipients unconsciously of them.Face detection is an important topic in computer vision.Viola-Jones is a powerful approach of identifying objects, especially facial recognition.Viola-Jones is subjected to a number of parameters that affect its performance.The measuring factor has the most impact on facial recognition and provides a balance between speed and accuracy in face detection.In this paper, the improved Algorithm of Viola Jones has been used by modifying the measurement factor using a genetic algorithm to determine face gestures.In this paper, the KNN classifier, MFCC (Mel Frequency Cepstral Coefficient), and the Extract feature are used in evaluating the detection of face gestures.First, we take the picture as input and use signal processing techniques to convert it to time domain references.For detecting the front face gestures accurately and efficiently, MFCC will be used with LBP (Local Binary Pattern) and DOG (Difference of Gaussians) to extract the feature.Based on the result of feature extracting, the KNN classifier classifies the activity of our input signal.Experimental results show that the proposed approach is superior to other ways of recognition.
Automatic moving foreground extraction using random walks

&lt;p&gt;In this paper, we propose a novel approach for automatic foreground extraction in video frames by analyzing the spatiotemporal aspect. We divide our contribution to tree steps: Automatic seeds detection, formulating the energy function, and using the random walk algorithm to minimize this function. First, we detect seeds by extracting a sparse of good features to track in the current frame and compute the difference between those pixels and its adjacent in the previous frame, the difference of pixels is treated in HSV color space to make the result more accurate, we thresholds this difference, and we classify moving and stationary pixels. Secondly, we formulate our foreground extraction as a graph based problem, then we define an energy function to evaluate spatiotemporal smoothness. Finally, we applied the random walk algorithm with seeds detected in the first step to minimize the energy function problem, the solution leads to evaluate the potential that every pixel in the video sequences is marked in motion or a stationary pixel. We suggest that our unsupervised method has the potential to be used for many kinds of motion detection and real-time video.&lt;/p&gt;