Reviewerly/exHarmony huggingface dataset:
SERVER-SIDE PROCESSING TECHNIQUES FOR OPTIMIZING THE SPEED OF PRESENTING BIG DATA

Big data is the latest industry keyword to describe large volumes of structured and unstructured data that are difficult to process and analyze. Most organizations are looking for the best approach to managing and analyzing large volumes of data, especially in decision making. Large data causes the process of presenting information to be slow because all the large amounts of data must be displayed so that specific techniques are needed so that the presentation of information remains fast even though the data is already large. The website generally processes requests to the server, and then if the required data is available, the server will send all the data. This causes all processes to be based on the client-side. So that the client load becomes heavy in displaying all the data. In this study, server-side processing techniques will be applied so that all processes will be handled by the server and the data sent is not all direct but based on periodic requests from the client. The results of this study indicate the use of server-side processing techniques is more optimal. Based on the results of testing the data presentation speed comparison with server-side processing techniques 98.6% is better than client-side processing.
How does social media affect cryptocurrency value? A case study of bitcoin in Thailand

Emergence of crypto currencies has developed technological revolution in global financial markets.What factors determine crypto valuation have an important effect on business and investment.The paper outlines the ongoing research on the interactions between social media and bitcoin value in Thai crypto market.The research model is constructed to examine the dynamic interactions between social media and bitcoin value.The data mining technique using in this research is vector error correction models.The expected results will show how bullish forum posts affect future bitcoin values, who has more effects on bitcoinsilent majority or vocal minority.Research findings will reveal whether social media sentiment is important in determining bitcoin's value.This research provides new insights into Thai digital currency market as well as the economic impact of social media.
Secure Enterprise and Read Performance Enhancement in Data Deduplication for Secondary Storage

With the tremendous growth of available digital data, the use of Cloud Service Providers (CSPs) are gaining more popularity, since these types of services promise to provide convenient and efficient storage services to end-users by taking advantage of a new set of benefits and savings offered by cloud technologies in terms of computational, storage, bandwidth, and transmission costs. we propose solutions for different data types (text, image and video) for secure data de-duplication in cloud environments. Our schemes allow users to upload their data in a secure and efficient manner such that neither a semi-honest CSP nor a malicious user can access or compromise the security of the data. Moreover, we propose proof of storage protocols including Proof of Retrievability (POR) and Proof of Ownership (POW) so that users of cloud storage services are able to ensure that their data has been saved in the cloud without tampering or manipulation. Experimental results are provided to validate the effectiveness of the proposed schemes. proposes a method to improve the read performance by investigating the recently accessed chunks and their locality in the backup set (data stream). Based on this study of the distribution of chunks in the data stream, few chunks are identified that need to be accumulated and stored to serve the future read requests better. This identification and accumulation happen on cached chunks. By this a small degree of duplication of the de-duplicated data is introduced, but by later caching them together during the restore of the same data stream, the read performance is improved. Finally the read performance results obtained through experiments with trace datasets are presented and analyzed to evaluate the design.
Ore potential of granitic rocks of the Gargan block, Eastern Sayan

Based on the analysis of modern genetic models, an algorithm for extracting the derivatives of potentially ore-bearing magmas among Precambrian rocks of the tonalite-trondhjemite-granodiorite associations (TTGA) is developed and tested. The algorithm is implemented as a sequence of geochemical criteria to identify the genetic nature of the sources of substance and on this basis to distinguish the products of melting of geochemical reservoirs enriched in Au and other ore elements. The proposed algorithm (a set of potential geochemical criteria of ore content) can be used for metallogenic zoning of TTGA rocks, within ancient cratons.
Pengaruh Kualitas Pembelajaran, Kualitas Tutor dan Motivasi Terhadap Prestasi Belajar Mahasiswa Universitas Terbuka Palembang

This study aims to determine the effect of learning quality, tutor quality and motivation both jointly and partially on student achievement at the Palembang Open University (Pokjar Pangkalan Lampam - Tulung Selapan. The research approach is quantitative research with associative research type. The population of this study is 186. students. The sampling method for probability with the Stratified Random Sampling method. The sample of this study was calculated using the Slovin formula with an error rate of 10%, the number of samples was 65 students as respondents. The first sample was tested using the Instrument Validity Test and the Instrument Reliability Test. The analysis model used in this study is multiple linear regression analysis. The regression calculation can be Y = -1.649 + 0.567X1 + 0.351X2 + 0.457X3. Interpretation of the multiple regression equation regarding the influence of the Learning Quality Variables (X1), Tutor Quality (X2) and Learning Motivation (X3), on Student Learning Achievement (Y). The results of the calculation of the three coefficients of the independent variable are positive, this indicates a positive linear relationship (unidirectional), meaning that the quality of learning, quality of tutors and learning motivation, the better, the better the student achievement. Obtained a correlation coefficient (R) of 0.712, with a level of closeness between variables of 0.712 which is in the interpretation of the correlation value (0.60-0.799) means that the relationship between the two variables is significant and the level of closeness is strong. The coefficient of determination value R2 = 0.507, which means that the variables of Learning Quality, Tutor Quality, and Learning Motivation are able to explain the Student Learning Achievement Variables of 0.507 or 50.7%, while the remaining 49.3% is explained by other factors not examined.
PERBANDINGAN LITERASI INFORMASI MAHASISWA PEMULA POLITEKNIK NEGERI BATAM

This study aims to compare the level of information literacy of first-year students across different studies offered by major at Polytechnic Negeri Batam. The method used is a descriptive quantitative approach through a questionnaire conducted to 93 respondents. The sampling method uses purposive sampling. This study takes ALA concept of information literacy which are standard 1 about to able to identify a personal need for information, standard 2 about can access current knowledge and idnetify gaps, standard 3 is about can construct strategies for location information and data and standard 5 is about can review research process and compare and evaluate information and data. The results of this study are that level of student’s information literacy are in Good level. This level get results are 54% of correspondents, 42% satisfactory, low is 3% and only 1% got very satisfactory. This mostly can be showed by how they can review research process, compare and evaluate information and data.
Evaluation of Drainage Channels on Pabuaran Road Cibinong District of Bogor Regency

Drainage can be generally defined as a technical measure to reduce excess water, whether from rain, seepage, or excess irrigation water from an area / land, so that the function of the area / land is not disturbed. This study aims to analyze, assess and evaluate the condition and capacity of the channel in the sub-district Pabuaran Road Bogor Cibinong District to discharge the flooding. Data and information used is primary data in the form of rainfall data from the Meteorology and Geophysics from the nearest irrigation hall as well as secondary data, the authors survey directly at the sites. In the flood discharge processing method using two methods of hydrograph Unit hydrograph Unit Synthetic Synthetic Nakayasu and ITB. The results of both methods is used the largest flood discharge. Getting the design flood discharge using Synthetic Unit Hydrograph ITB on Channel A of 6,434 m3 / sec. Analysis of the results of the calculation of the existing discharge chute, the discharge contained on Channel A of 2.10 m3 / sec and Channel B amounting to 0.21 m3 / sec limpas both channels experience. Alternative solutions to the problems that limpas channel or unsafe they are planning a new dimension channel.
Analisis Kesalahan Penggunaan Kara dan Node pada Siswa JLMC (Japanese Language Management Center)

This article examines the use of conjunctions or setsuzokujoshi of kara and node that mean reasons in Japanese. The subjects in this study were students of the Nippo class who were studying at LPK Japanese Language Management Center (JLMC). This research uses descriptive analysis method by collecting data from students to answer 6 questions about kara and node. The results showed that students understanding about use of kara and node was good enough, with a percentage 59%. Then based on the results of the item analysis, can be seen that the students made more mistakes in kara form than node form, with the error percentage in kara reach 62% and node 21%. The main cause of students lack of understanding about the differences of kara and node is the teacher who does not explain in detail the differences between kara and node. Besides that, learning material or book that students used there is no details explanation about different of kara and node.
The Effect of the application of the Cooperative Learning Model Type Snowball Throwing Against an increase in the activity of learning to the learners on subjects Science in grade VII Inclusive SMPN 23 Padang

The research was distributed by the low activity of learning to learners in an inclusive classroom while learning the IPA take place where student activity still centered on teachers so that students not actively in learning. This research aims to find out how big the influence of cooperative learning model type Snowball Throwing against learning activities learners in learning the IPA in the VII inclusive classroom junior high school 23 Padang. This type of research is the Quasy alphabets experiment using Control-Group design Only. This research was carried out in class VII2 as class experiments with the number of learners 32 people (with 3 learners ABK) and VII3 class as the class of the control to the number of learners 32 people (with 2 of HER students). The instruments used in the research in the form of the now learners learning activities that contains items of the statement drawn up in accordance with a predetermined indicators. Data analysis technique used is comparing the difference of two average learners with learning activities begins conducting a test of its homogeneity and normality, so that in the end done with test t (t-test).The value of the rat experimental 92.42 class average and average value of kotrol class 70.08. Hypothesis test results data learning activities students class experiments and gained control of that class Fhitung &lt; Ftabel then the hypothesis is accepted. This means that there is a positive influence towards learning activities learners by implementing cooperative learning model type Snowball Throwing.
DEVELOPMENT OF THE NEURAL NETWORK FOR SOLVING THE PROBLEM OF SPEECH RECOGNITION

The article discusses a method for solving the problem of speech recognition on the example of recognizing individual words of a limited dictionary using a forward propagation neural network trained by the error back propagation method. The goal was to create a neural network model for recognizing the solution of individual words, analyze the training characteristics and behavior of the constructed neural network. Based on the input data and output requirements, a feedback neural network selected. To train the selected neural network model, a back propagation algorithm was chosen. The developed neural network demonstrated the expected behavior associated with learning and generalization errors. It found that even if the generalization error decreases as the learning sequence increases, the errors begin to fluctuate regardless of the introduction of a dynamic learning rate. The network sufficiently trained to meet the generalization error requirements, but there is stillroom to improve the generalization error. Practical results of training the constructed neural network at different sizes of the training sample presented.
Distribution and transportation control of high-speed and flexible packing production line for medical kit based on green technology

In order to overcome the high power consumption of the traditional flexible box packing production line, this paper proposes a green technology-based control method of the box packing production line. The method installs sensors and controllers respectively. Using the real-time data fed back by sensors, it analyses the operation of the current box packing production line, constructs the kinematic model of the box packing transportation, and accesses a large number of peripheral circuits, using green technology, respectively from the transmission speed, working state and other angles, to achieve the control of the production line distribution transmission. The experimental results show that the average packaging time of the control method is 0.8375 min, the power consumption is 4232.857 kw, and the control performance is higher.
JPR volume 56 issue 1 Cover and Back matter

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Reputation and Security Based File Sharing Model using P2P Networks

The present system fails to utilize the trust in the social network which is based on Peer to Peer (P2P) file sharing systems. To overcome this issue, a trust management system named “Social Link” is used to utilize the social network and predefined transaction links. The Social Link manages the novel weighted transactions and networks. The link is constructed using the historical file transaction. Two friends can share their files and increased trust can be guaranteed with the help of Social Link. The Networkof Weighted Transaction (NWT) can be calculating the successful transaction and it finds trust over the client on server. By this process, Social Link will reduce transaction misbehaving, avoids free riding and promotes nodes to transact data files to non friends. Whitewashing and collision can also be rectified using Social Links.
Digitalized Invention, Decentralized Patent System

Abstract Throughout the history of patent law, the manner of representation of invention influenced the process of the patent office in prosecuting them. This chapter traces how changes in the representation of the invention—from material to textual to digital—transformed patent prosecution. Early inventions were represented by working models, the materialized invention that needed little or no examination by the patent office, as they were the inventions themselves. Substantive examination became necessary when the representation of the invention shifted from material to textual, the point in history where the invention became textualized and represented by the patent specification, the written document that encompassed the invention. The textualized invention, apart from effecting critical changes in patent prosecution, centralized the operations of the patent office. With the adoption of new technologies like blockchain and artificial intelligence (AI), the manner of representation of invention will undergo yet another change resulting in the further evolution of patent prosecution. Like digital photography which changed the representation of images by radically changing the backend process, the digitalized invention will change the backend process of the patent office, ie, patent prosecution. The most significant systemic consequence of the digitalization of the invention will be the decentralization of patent system.
Visual Augmentation of Source Code Editors: A Systematic Mapping Study

The ninth IEEE Working Conference on Software Visualization (VISSOFT 2021) builds upon the success of the previous eight editions of VISSOFT, which in turn followed after six editions of the IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT) and five editions of the ACM Sympo0sium on Software Visualization (SOFTVIS). In 2021, VISSOFT will take place and be co-located with ICSME.
Safely caching HOG pyramid feature levels, to speed up facial landmark detection

&lt;p&gt;This thesis presents an algorithm for improving the execution time of existing Histogram of Oriented Gradients (HOG) pyramid analysis based facial landmark detection. It extends the work of [1] to video data. A Bayesian Network (Bayes Net) is used as a policy network to determine when previously calculated features can be safely reused. This avoids the problem of recalculating expensive features every frame. The algorithm leverages a set of lightweight features to minimize additional overhead. Additionally, it takes advantage of the wide spread adoption of H.264 encoding in consumer grade recording devices, to acquire cheap motions vectors. Experimental results on a difficult real world data set show that policy network is effective, and that the error introduced to the system remains relatively low. A large performance benefit is realized due to the use of the cached features.&lt;/p&gt;
A Quantitative Analysis of Defect Prevention in E-commerce Projects

E-commerce is a transaction of buying or selling online. It is a methodology of modern business which addresses the need of business organizations, vendors and customers to reduce cost and improve the quality of goods and services while increasing the speed of delivery [1]. In the emerging global economy, e-commerce and e-business have increasingly become a necessary component of business strategy and a strong catalyst for economic development. E-commerce promises better business for Small and Medium Enterprises (SME) and sustainable economic development for developing countries [2]. With the advent of e-commerce business, many software providers have started developing e-commerce solutions. However, the emphasis has to be given on developing defect free e-commerce portals. The concept of defect removal effectiveness and its measurement are central to software development. As per Software Engineering Institute Website defect removal is one of the top expenses in any software project and it greatly affects schedules [3]. According to Caper Jones, for improvements in productivity, cost, and schedule, it is important to use better defect prevention and removal techniques [4]. This quantitative analysis is done on five e-commerce projects. The lessons learnt from one project are fed into the development process of the subsequent projects that helped in preventing the similar defects. This facilitated in reduction in the count of User Acceptance Test defects, in the projects developed subsequently.
Telemetry Based Anomaly Detection and Correlation in Data Center

Data center is a complex amalgamation of servers where there are thousands of services, storage, networking, routers, switches and softwares providing services 24x7 to cus- tomers. Services provided can range from websites, storage, cloud platform, Email marketing etc. A team is established to detach the anomaly generated from the monitoring system. Anomaly or issues in servers cause high downtime of service. Detecting these anomalies with high accuracy and performing Root cause analysis has been a major issue. The team often remediates the symptom than the anomaly. With the use of Artificial Neural networks a trained model can provide solutions with high accuracy and scalablility which result in higher uptime and reduced MTTR for customers.
Magnetic Resonance Image Segmentation and its VHDL Implementation

From experiments, it is shown that the Co-occurrence matrix for one still MRI brain image does not provide enough information for segmentation. The 6D Co-occurrence image segmentation idea for 3D MRI image is modified and implemented in 2D MRI image segmentation. That idea is to take two or three images as input at the same time and then process them with 3D Co-occurrence matrix. With this kind of processing a lot of information was brought into the Co-occurrence matrix, which is enough to segment the images. To compare the result, some other segmentation ideas were tested in this project. From the results, it can be seen that the MRI image segmentation based on the Co-ocurrence texture analysis with two images or three images sampling is practical and the result satisfying. The segmentation is simulated in MATLAB. After the simulation, the segmentation is implemented in FPGA using VHDL. MODELSIM is used for FPGA functionality simulation. The result is close the MATLAB simulation. This makes it possible to implement the system with FPGA hardware.
The Design of Augmented Reality-Based Synectic Model Device in Writing Short Stories

A Short story is a miniature of people's experience while the characters, plot, and setting aim to record imaginative events (Stanton, 2017). When making up story ideas, students have problems developing story facts such as plot, characters, and settings (Sayuti, 2006). This barrier emerged conflicts that were unevenly distributed across all stages of the course. The direct characterization employed in storytelling made the short stories less varied. The physical and setting depicted did not work out optimally. The advantage of using the synectic model is that it can allow students to look for and makeup concepts to describe objects through an analogy process. Augmented Reality allows users to interact with an object's interface and see it in a well-designed and attractive 3D format, so it can solve student difficulties in developing story ideas in writing short stories
Prediksi Penyebaran Informasi di Twitter dengan Metode Pembelajaran Mesin dengan Fitur Linimasa

Abstract — Social Media Network has been an important information source, and the information propagation within the network gave an impact on politics, marketing, and entertainment industry. Our aim is to predict a tweet whether the information will be propagated further. The previous research has focused on analyzing this task with a wide range of learning methods and features, such as content and account features. Timeline features are proposed as features that can further predict information propagation and as we compared the performance with content and account features. The dataset consists of 43.229 tweets, we predict the information propagation with logistic regression, support vector machines, and random forest learning method with these features. Our result indicates that the timeline feature can be a good candidate for predicting information propagation and the random forests learning method consistently performs better. From the training result, we further calculate feature importance. Recently tweets, engagement with another user and previous liked tweets on the timeline features contributed to more popular tweets.