Reviewerly/exHarmony huggingface dataset:
Building Intelligent Semantic Educational System (ISES) Based on Ontology and Semantic Web Mining

This research presents a method to build an intelligent semantic education system based on two novel techniques namely ontology and semantic web mining. Ontologies are a powerful mechanism to solve a retrieval problem that is exacerbated rapidly within the modern educational systems, when there are individual differences between instructors and learners in the previous backgrounds and levels of knowledge. In intelligent education systems, four types of ontology are identified that represent knowledge: students, content, education, and structure. There is a promising approach for satisfying the intelligent education systems requirements, which is one of the most prominent semantic Web ideas, based on commonly shared meaning (ontology) and metadata processed automatically. This approach can be supported using semantic querying and conceptual navigation for learning materials.One of the important results of this paper is the depth of most of the inferences derived from learning ontologies. Relations such as has_Part and is_Part_Of and their interplay can be easy dealing by the users. Therefore, this type of thinking can be presented through an automatic mechanism, and semantic information is necessary for reasoning about an automatic occurrence.
Advantages of Using Semi-Empirical Methods in Teaching Students at the Faculty of Chemistry of Uzhhorod National University

Semi-empirical methods of research of the properties of substances are applied during the occupations in scientific circles and play an important role in the training of students of the Faculty of Chemistry of Uzhhorod National University and also at implementation of academic year and degree projects.
PENINGKATAN KETERAMPILAN MEMBACA AWAL MELAUI METODE BERMAIN DENGAN MEDIA PUZZLE KATA PADA KELOMPOK B PAUD ISTIQOMAH SELUPU REJANG

The problem had in this classroom action research is whether early reading skills in children in the PAUD group of Istiqomah Selupu Rejang can be improved through the method of playing using word puzzle media? This research was conducted with the aim to improve early reading skill in children of group B PAUD Istiqomah Selupu Rejang. Data collection techniques used are with the test techniques for children and observation for teachers. The data analysis technique used is with the average test technique. The results obtained are the improvements that occur in children's early reading skills by achieving an average value of 3.6 with the "good" criteria in cycle I and increasing with an average value of 4.5 with the criteria of "good" in cycle II. So it can be concluded that this research experience peningkatam but only increased quantitatively while qualitatively get a fixed result.
Library-Supported Scholarship: Increasing Faculty Scholarly Reach with Author Services

The researchers' primary goal when working with faculty on the research and publication process is to empower them to independently write literature reviews, deploy surveys, collect data, analyze data, and submit manuscripts to peer-review journals and edited book collections.The authors coach faculty in doing so in a variety of ways, from one-on-one trainings to small group workshops.For faculty who have recently earned their PhD, librarians have worked with them to narrow their dissertation topic into a publishable product.As part of the publishing process, the authors have shown them how to select potential publication outlets by reviewing the journals most cited by those the faculty are citing through using Web of Science and by reviewing journal SJR index scores.To assist faculty with marketing their publications, we surveyed the college's faculty to determine their awareness of authors so that the library can assist them to increase their scholarly reach.Overall, with the exception of Google Scholar Author Profiles and LinkedIn, more than 50% of the college's faculty indicated that they were unaware of the remaining author services.This indicates there is need for librarians or educational technologists to train faculty on the benefits author services provides faculty.
Fiducial Point Location Algorithm for Automatic Facial Expression Recognition

We present an algorithm for the automatic recognition of facial features for color images of either frontal or rotated human faces.The algorithm first identifies the sub-images containing each feature, afterwards, it processes them separately to extract the characteristic fiducial points.Then Calculate the Euclidean distances between the center of gravity coordinate and the annotated fiducial points' coordinates of the face image.A system that performs these operations accurately and in real time would form a big step in achieving a human-like interaction between man and machine.This paper surveys the past work in solving these problems.The features are looked for in down-sampled images, the fiducial points are identified in the high resolution ones.Experiments indicate that our proposed method can obtain good classification accuracy.
PCA and DCT Based Approach for Face Recognition

Recognizing the identity of the target.The research of face recognition has great theoretical value involving subject of pattern recognition, image processing, computer vision, machine learning, and physiology and so on, and it also has a high correlation with other biometrics recognition methods.In recent years, face recognition is one of the most active and challenging problems in the field of pattern recognition and artificial intelligence.Face recognition has a lot of advantages which are not involved in biometrics recognition methods such as nonaggressive, friendly, conveniently, and so on .Therefore, face recognition has a prospective application foreground, such as the criminal identification, security system, file management, entrance guard system, and so on .Research in the field of face recognition knew considerable progress during these last years.Among the most evoked techniques we find those which employ the optimization of the size of the data in order to get a representation which makes it possible to carry out the recognition.For these methods, the images of faces are seen like points in a space of very great dimensions.The face space is defined by Eigen face which are eigenvectors of the set of faces.In the DCT approach we take transform the image into the frequency domain and extract the feature from it.For feature extraction we use two approach.In the 1st approach we take the DCT of the whole image and extract the feature from it.In the 2nd approach we divide the image into sub-images and take DCT of each of them and then extract the feature vector from them.
Dynamic Question Answer Generator: An Enhanced Approach to Question Generation

Teachers and educational institutions seek new questions with different difficulty levels for setting up tests for their students.Also, students long for distinct and new questions to practice for their tests as redundant questions are found everywhere.However, setting up new questions every time is a tedious task for teachers.To overcome this conundrum, we have concocted an artificially intelligent system which generates questions and answers for the mathematical topic -Quadratic equations.The system uses-i) Randomization technique for generating unique questions each time and ii) First order logic and Automated deduction to produce solution for the generated question.The goal was achieved and the system works efficiently.It is robust, reliable and helpful for teachers, students and other organizations for retrieving Quadratic equations questions, hassle-free.
Compression and Decompression of Audio Files Using the Arithmetic Coding Method

Audio file size is relatively larger when compared to files with text format. Large files can cause various obstacles in the form of large space requirements for storage and a long enough time in the shipping process. File compression is one solution that can be done to overcome the problem of large file sizes. Arithmetic coding is one algorithm that can be used to compress audio files. The arithmetic coding algorithm encodes the audio file and changes one row of input symbols with a floating point number and obtains the output of the encoding in the form of a number of values greater than 0 and smaller than 1. The process of compression and decompression of audio files in this study is done against several wave files. Wave files are standard audio file formats developed by Microsoft and IBM that are stored using PCM (Pulse Code Modulation) coding. The wave file compression ratio obtained in this study was 16.12 percent with an average compression process time of 45.89 seconds, while the average decompression time was 0.32 seconds.
CDSVR

The effective curb detection is important for navigation and decision making in self-driving. This paper proposes a Curb Detection method based on Support Vector Regression (SVR) processing pointclouds of 3D lidar, which is called CDSVR. The raw data from lidar sensor are first pre-processed to achieve coarse filtering by combining the road model and grid filtering method. A curb fitting method based on SVR is then proposed to recognize and fit the road curbs in each frame of real-time lidar data. Compared with linear and polynomial fitting methods, CDSVR is evaluated in online experiments for real scenarios. The results demonstrate that the prediction error of curb detection is below than 21cm and the processing time of one frame is less than 20ms. Therefore, CDSVR can effectively achieve the curb detection tasks with high efficiency.
Association Rule Hiding using Hash Tree

As extensive chronicles of information contain classified rules that must be protected before distributed, association rule hiding winds up one of basic privacy preserving data mining issues.Information sharing between two associations is ordinary in various application zones for instance business planning or marketing.Profitable overall patterns can be found from the incorporated dataset.In any case, some delicate patterns that ought to have been kept private could likewise be uncovered.Vast disclosure of touchy patterns could diminish the forceful limit of the information owner.Database outsourcing is becoming a necessary business approach in the ongoing distributed and parallel frameworks for incessant things identification.This paper focuses on introducing a few adjustments to safeguard both customer and server privacy.Adjustment strategies like hash tree to existing APRIORI algorithm are recommended that will be helping in safeguarding the accuracy, utility loss and data privacy and result is generated in small execution time.We implement the modified algorithm to two custom datasets of different sizes.
Penerapan Metode TOPSIS untuk Seleksi Penerima Beasiswa (Studi Kasus: SMAN 2 Tebing Tinggi Timur)

Government efforts to overcome the high cost of education by providing tuition assistance to underprivileged students in funding education, called scholarships. This scholarship is aimed at students who are economically disadvantaged. Students must have certain criteria that will be assessed by the school in considering their eligibility as scholarship recipients. Therefore, it is necessary to have a decision support system which will be able to shorten the selection time and improve quality in determining scholarship acceptance. the decision support system used is TOPSIS based on predetermined criteria. By using this method, it will be able to produce objective decisions in determining scholarship receipts at Tebing Tinggi Timur 2 High School.
AN EMG BASED HAND GESTURE RECOGNITION SYSTEM USING SVM

Hand gestures is one of the most powerful, immediate and natural means of communication.Electromyography (EMG) is the measure of electrical activity produced by the muscles which is usually represented as a function of time.EMG can be used in various applications including identifying neuromuscular diseases, sign language recognition, virtual reality, gesture to speech, robotics, and television control.The EMG based hand gesture recognition can help to develop good computer interface that increases the quality of life of the disable or aged people.The main purpose of this work is to identify the hand gestures that is classified and predefined using support vector machine (SVM).The raw EMG data is preprocessed and the statistical features are extracted, the extracted features are given to the support vector machine for training and classification and performance are evaluated using confusion matrix to determine the average classification accuracy as high as possible.
Am I Better in VR with a Real Audience?

We present an experimental study using virtual reality (VR) to investigate the effects of a real audience on social inhibition. The study compares a multi-user application, locally or remotely shared. The application engages one user and a real audience (i.e., local or remote conditions) and a control condition where the user is alone (i.e., alone condition). The differences have been explored by analyzing the objective performance (i.e., type and answering time) of users when performing a categorization of numbers task in VR. Moreover, the subjective feelings and perceptions (i.e., perceptions of others, stress, cognitive workload, presence) of each user have been compared in relation to the location of the real audience. The results showed that in the presence of a real audience (in the local and remote conditions), user performance is affected by social inhibitions. Furthermore, users are even more influenced when the audience does not share the same room, despite others are less perceived.
Geology, Petrology and Geochemistry of Volcanic Rocks Around Arba Minch, Southern Ethiopia

The study area is subpart of the southern main Ethiopian Rift and geographically bounded between UTM (Universal Transverse Mercator) coordinates of 662000m-669000m latitude and 336000m-341000m longitude.The main aim of this study is to investigate the geological, petrographic and geochemical properties of volcanic rocks around Arba Minch, southern Ethiopia.Both field and laboratory analytical techniques are employed to characterize minerals and the rock types.Eight thin section samples are prepared to study petrographic properties of minerals and five best representative samples are analyzed for whole rock chemistry using ICP-MS (Inductively Coupled Plasma-Mass Spectrometry).Petrographically, samples from the porphyritic basalt show phenocrysts of olivine and plagioclase within the fine-grained groundmass.There are rounded to subrounded holes or vesicles that appear white under plane polarized light observations and dark under cross polarized light observations which further confirms vesicular nature of the basalt.Thin section sample from rhyolite outcrop shows phenocrysts of K-feldspar and quartz within tiny fine-grained groundmass of feldspar minerals.Aphanitic basalt, Porphyritic basalt, vesicular basalt, rhyolite and dolerite are the rock units found in the study area.The geochemical results of the analyzed samples indicate silica ranges of (48.5-60.1)%.Based geochemical classifications made, rock units are classified into rhyolite, basalt, hawaiite and mugherite rock types.Trace element analytical results show all samples lie on the within plate tectonic setting.The rare earth and trace element ratios and spider diagrams confirmed that most samples are derived from magmas of asthenospheric source with little crustal contamination.
Load Balancing Policies of Web Servers: Research Analysis, Classification and Perspectives

The usage of the internet has increased rapidly from the past few years. Thus it automatically increases the internet traffic. In the internet, a web server always responds to the client or web browser's requests. The major feature of a web server is to be available, scalable and predictable. So the
Long-Distance Dependencies Don’t Have to Be Long: Simplifying through Provably (Approximately) Optimal Permutations

Neural models at the sentence level often operate on the constituent words/tokens in a way that encodes the inductive bias of processing the input in a similar fashion to how humans do.However, there is no guarantee that the standard ordering of words is computationally efficient or optimal.To help mitigate this, we consider a dependency parse as a proxy for the inter-word dependencies in a sentence and simplify the sentence with respect to combinatorial objectives imposed on the sentenceparse pair.The associated optimization results in permuted sentences that are provably (approximately) optimal with respect to minimizing dependency parse lengths and that are demonstrably simpler.We evaluate our general-purpose permutations within a finetuning schema for the downstream task of subjectivity analysis.Our fine-tuned baselines reflect a new state of the art for the SUBJ dataset and the permutations we introduce lead to further improvements with a 2.0% increase in classification accuracy (absolute) and a 45% reduction in classification error (relative) over the previous state of the art.
A Survey Paper on Identity Theft in the Internet

Identity of any internet user is stole in seconds and the user may not aware about it.There are various tools available in the internet which allow anyone to steal data of any particular user, if he/she is connected to internet.The attacker is not required to have advanced knowledge about the internet technology or how networking works.Identity theft is a tremendous issue for most Internet clients..This paper is an attempt to make reader aware about how their identity can be theft in the internet.This work expects to expand the mindfulness and comprehension of the Identity thefts that are and related cheats all through the world.
The Effect of Contextual Teaching And Learning (CTL) Learning Model on The Ability Of Concept Understanding Class VII Students of SMP 16, Kota Bengkulu

This study aims to determine the effect of the Contextual Teaching and Learning (CTL) learning model on the ability to understand the concepts of class VII students of SMP 16 Kota Bengkulu. The research carried out was quasi-experimental with a population of all students in class VII of SMP 16 Kota Bengkulu totaling 218 students. Samples were taken by random sampling technique and a sample of 60 students was obtained, 30 students in the VIIA class as the experimental class, 30 students in the VIIE class as the control class. Data collection using Instrument concept understanding ability test. Data analysis techniques using Ancova. The results showed that there was the influence of the Contextual Teaching and Learning (CTL) learning model on the conceptual comprehension ability of seventh grade students in Bengkulu City 16 Junior High School at 80.50% with an average of 82.75 and there was an effect of an initial ability of 60.50% with an average average of 82.80. It can be concluded that the ability to understand students' concepts is better by using the Contextual Teaching and Learning (CTL) learning model.
Path Navigation in ACO Using Mobile Robot

Ant colony algorithm suffers drawbacks such as slow convergence and easy to trap into local optimum, therefore the path planning for mobile robot based on an improved ant colony optimization algorithm is proposed.The workspace for mobile robot is established with grid method.A hybrid ant colony which is composed of common ants and exploratory ants is utilized to avoid trapping into local optimum.To increase the convergence speed, the pheromone update mechanism is improved by enhancing the sensitivity of the ants to the optimal path with reserving the elite ants.The optimal collision-free path can be planned rapidly in the workspace with multiple obstacles.Simulation and experiment results show that the algorithm is practical and effective.
Thermal and Power-Aware VM Scheduling on Cloud Computing in Data Center

Data centers now play an important role in modern IT infrastructures.Related research shows that the energy consumption for data center cooling systems has recently increased significantly.There is also strong evidence to show that high temperatures in a data center will lead to higher hardware failure rates, and thus an increase in maintenance costs.datacenter is often also a Cloud center This paper devotes itself in the field of thermal aware workload and VM placement for Cloud data centers.The goal of this Work is to ameliorate, through scheduling, the energy-efficiency of data center.To support this work a novel VM scheduling mechanism design and implementation will be proposed.The proposed scheduling mechanism on CloudSim will be finally validated, a well-known simulator that models data centers provisioning Infrastructure as a Service.For a comparative study, we also implemented other scheduling algorithms, non power control, DVFS.The experimental results show that the proposed scheduling scheme, combining the power-aware with the thermal-aware scheduling strategies, significantly reduces the energy consumption of a given Data Center because of its thermal-aware strategy and the support of VM migration mechanisms.
Hierarchical Access Control with Scalable Data Sharing in Cloud Storage

Cloud storage is facing the contradiction between data security and flexible data sharing, and therefore the cryptographic access control mechanisms are well studied. In particular, hierarchical access control in cloud storage is significant for many application scenarios. In these scenarios, the users are divided into several groups organized in a hierarchy, and they are assigned with different access privileges according to their groups and levels. That is, the users in higher level groups can access the data belonging to their subordinate groups while the users in lower level groups cannot access the data belonging to their superior groups. However, most of the existing hierarchical access control solutions seem to be unpractical for their inability of scalable data sharing, inefficiency of key management or lack of delegated re-encryption. In this paper, we propose a new hierarchical access control scheme based on key-aggregate encryption, and the proposed scheme realizes scalable data sharing in cloud storage which allows the users to share data with any user group. In the proposed scheme, the size of each key or ciphertext is constant and irrelevant to the scale of hierarchical user structure. Especially, our scheme improves the convenience of key management by cutting off the key derivation widely used in the existing hierarchical key assignment methods. Furthermore, the proposed scheme reduces the users’ updating overhead by introducing the delegated re-encryption into the hierarchical scenarios. Finally, the security analysis and the performance evaluation indicate that our scheme is feasible for the hierarchical data sharing applications in cloud storage.