Reviewerly/exHarmony huggingface dataset:
Predicting Voting Outcomes Using Data Analytics and Machine Learning Algorithms

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
An Efficient Speculative Task Detection Algorithm for MapReduce Schedulers

Background: The MapReduce programming model was developed and designed for Google File System to efficiently process large distributed datasets. The open source implementation of the Google project was called Apache Hadoop. Hadoop architecture comprises of Hadoop Distributed File System (HDFS) and Hadoop MapReduce. HDFS provides support to Hadoop for effectively managing large datasets over the cluster and MapReduce helps in efficient large-scale distributed datasets processing. MapReduce incorporates strategies to re-executes speculative task on some other node in order to finish computation quickly, enhancing the overall Quality of Service (QoS). Several mechanisms were suggested over default Hadoop’s Scheduler, such as Longest Approximate Time to End (LATE), Self-Adaptive MapReduce scheduler (SAMR) and Enhanced Self-Adaptive MapReduce scheduler (ESAMR), to improve speculative re-execution of tasks over the cluster. Objective: The aim of this research is to develop an efficient speculative task detection mechanism to improve the overall QoS offered over Hadoop cluster. Methods: Our studies suggest the importance of keeping a regular track of node’s performance in order to re-execute speculative tasks more efficiently. Results: We have successfully reduced the detection time of speculative tasks (~ 15%) and improved accuracy of correct speculative task detection (~10%) as compared to existing mechanisms. Conclusion: This paper presents an efficient speculative task detection algorithm for MapReduce schedulers to improve the QoS offered by Hadoop clusters.
The dangers of false news: how sensational content and outgroup cues strengthen support for violence and anti-muslim policies

Does reading sensationalized false news stories make people more violent and dis- criminatory? Research on false news has focused more on its di↵usion and less on its e↵ects. This study tested the e↵ects of sensationalization, outgroup cues, and public opinion perception on support for violence and anti-Muslim policies. We used an online survey experiment with a realistic, interactive website treat- ment detailing a homicide story in small-town America, written in the style of a false news article. We found that sensationalist language increased individuals’ support for violence by provoking feelings of anger and fear, while identifying the suspect in the homicide as a Muslim refugee, versus specifying no outgroup a liation, increased support for anti-Muslim policies. Lastly, perceived public support for violence increased the likelihood of upvoting or writing violent com- ments. This study contributes to our understanding of the ill e↵ects of false news and the public debate on online content moderation.
Participatory Learning Through Instructional Games for Functional Literacy Students of SKB Binjai

The purpose of this study is to develop participatory learning through instructional games for functional literacy students of Sanggar Kegiatan Belajar (SKB) Binjai.In general, the students of functional literacy program are adults who have not had time to complete their education in formal education, so this research is carried out to help these adults learn, given that adults will only learn something that appropriate with their needs.Based on the preliminary research, it is found that the learning process recently uses a conventional approach where the curriculum, questions, discussions, and assessments are designed by the tutor according to the needs of the learners.Through this participatory learning, students are given the freedom to determine learning programs, design, and develop learning patterns as well as release their stress from daily routine through instructional games.Learning through instructional games is defined as the application of technology in the world of learning for an educational process.The media is a tool that can be used as a channel to achieve teaching objectives.If the media is designed properly and appropriately, it can be a fun learning with high interactivity element, and it can stimulate students to remember more about the material of learning.The most common obstacles encountered in nonformal learning are the lack of collaboration among the students' during the learning process and moreover tutor rarely gives a reflection on each meeting so that the shortcomings experienced by each student on each meeting cannot be determined and improved at the next meeting.Therefore, learning instructional games which consists of collaboration steps with tutor to plan, observe, and do reflection about the lessons.Based on the data analysis, the implementation of instructional games can increase learning activity.Increased learning activities will lead to the improvement of the quality of learning process and learning products.The application of these two aspects are proven can help students to identify the urgency of the problems occurred in the classroom, and seek for a solution in order to achieve more meaningful learning process.This result is corresponding with the concept of learning which is a process undertaken by a person to obtain changes in overall behavior that derived from the results of his/her own experience in interaction with the environment.
Exploration on the Construction of Industrial Colleges of Local Normal University

Due to the lack of engineering application-oriented research ability in local normal universities, and the lack of service industry enterprises or local economic and social development experience, how to establish industrial colleges has become the current problem that some local normal universities need to solve. Based on the existing practice of colleges and universities, this paper analyzes the operation mode of industrial colleges, and then puts forward a new mode for the establishment and operation of industrial colleges according to the weak characteristics of science and engineering in local normal colleges, to improve the quality of talent cultivation in normal universities.
How do motivational text messages impact motivation to exercise?

We study the motives of regular and non-regular exercisers' engagement with motivational text messages and the importance individuals attribute to visual presentation. A total of 160 individuals were surveyed (80 regular exercisers and 80 non-regular exercisers). We found regular exercisers use motivational text messages in order to encourage their exercise routine. Non-regular exercisers use motivational text messages mainly to try to boost their exercise motivation. Individuals, independent of their exercise profile, prefer to see motivational text messages presented in a mixed way, sometimes as text-only and sometimes embedded in a visual presentation. Participants reported that an aesthetically appealing visual presentation helps instill a positive feeling regarding the text, and the visual presentation was considered as important as the textual content. We conclude with a number of implications for the design of activity trackers.
Model Pembelajaran Tenses Menggunakan Rumus Mathematic English (MatEng)

Tenses mastery is an ability that must be possessed by students to improve their English skills both oral and written. The aim of this study is to find out the implementation of tenses learning based on MATENG (Mathematic-English) formula in the English Education Study Program at Muria Kudus University. The method used is descriptive method. The results showed that: 1) the implementation of the learning model tenses using the MATENG formula (Mathematic English) includes 3 aspects; mastery of the names of 16 tenses, functions and formulas; 2) the learning process of tenses starts from appraisal, then main activity used the PPP method, and individual tasks for students; 3) the students' response to the implementation of the learning model tenses using the MATENG formula is stated to be very good.
My Subject: Psychology: Books & E-books

Find out more about the library resources available to you.Here you will find information about finding books, journal articles conference proceedings, databases, other libraries... and more!
Bidirectional Associative Memory with Block Coding: A Comparison of Iterative Retrieval Methods

Recently, Gripon and Berrou (2011) have investigated a recurrently connected Willshaw-type auto-associative memory with block coding, a particular sparse coding method, reporting a significant increase in storage capacity compared to earlier approaches. In this study we verify and generalize their results by implementing bidirectional hetero-associative networks and comparing the performance of various retrieval methods both with block coding and without block coding. For iterative retrieval in networks of size $$n=4096$$ our data confirms that block-coding with the so-called “sum-of-max” strategy performs best in terms of output noise (which is the normalized Hamming distance between stored and retrieved patterns), whereas the information storage capacity of the classical models cannot be exceeded because of the reduced Shannon information of block patterns. Our simulation experiments also provide accurate estimates of the maximum pattern number that can be stored at a tolerated noise level of 1%. It is revealed that block coding is most beneficial for sparse activity where each pattern has only $$k\sim \log n$$ active units.
Penerapan Website Sistem Pengajuan Cuti Pegawai Pada Kantor Kecamatan Ciawi Bogor

Limitations of the process on filing employee leave at the Ciawi Bogor sub-district office tend to be ineffective and inefficient so that in the process it makes both parties (employees and operators) have a difficulty. In addition to the leave filing files that are piled up, sometimes the operator forgets to process when there are employees who apply for leave. The research objective is to produce a web-based leave filing program so as to make it easy for users to apply for and process leave. The method of developing a software system uses the waterfall model. The results of the study in addition to displaying information about office activities or staffing on the main page, there are also facilities for filing leave, and changing the status of leave applications. Through this website employees had a view of information about the office activities and make the leave submission process online.
ArmTouch

Interacting with elements inside a virtual reality (VR) experience is usually done with a controller. However, they tend to be clunky and cumbersome to use. We designed an alternative controller that allows for a rich touch interaction. Our prototype uses the forearm for touch input in VR. The forearm is easy to find through proprioception and also displayed through the HMD. We implemented two versions, one using a touchpad mounted at the forearm and one where the input is realized through touching only the skin of one's arm. Users can select items of different menu types and through different gestures. A user study showed that both concepts show good usability, but none of the two touch mechanisms was preferred over the other.
Gesture Recognition and Localization Using Convolutional Neural Network

Gesture recognition based on computer vision, which is natural and intuitive, is getting more and more attention in the field of human-computer interaction. Due to the limitations of existing gesture recognition methods, this paper presents an efficient and effective solution, which is divided into two main parts: dataset collection and the convolutional neural network (CNN) design. Firstly, a novel method is proposed to collect the hand gesture dataset through the sliding window, which makes it easy to capture arbitrary gesture data in any background, and the whole process is simple and fast. Secondly, a novel CNN named HandNet is designed for improving the performance of the gesture recognition and localization. The bone structure of the proposed CNN is HandBlock, which has the ability of richer feature expression and adaptive weight expression between high-level features and low-level features. The experimental results show that the proposed model achieves comparable performance with the state-of-the-art methods.
Bridging the Map? Exploring interactions between the Academic and Mapping Communities in OpenStreetMap

This talk presents an initial inquiry into the relations between the Academic and Mapping communities in OpenStreetMap, based on a review of recent publications, interviews of colleagues, and self-reflection of the authors. By this, we aim to understand how and when research-community interactions come to be, what is their nature, and how can these be improved and made more productive for both sides.
Utility-Based SK-Clustering Algorithm for Privacy Preservation of Anonymized Data in Healthcare

Background: The increasing need for various data publishers to release or share the healthcare datasets has imparted a threat for the privacy and confidentiality of the Electronic Medical Records. However, the main goal is to share useful information thereby maximizing utility as well as ensuring that sensitive information is not disclosed. There always exist utility-privacy tradeoff which needs to be handled properly for the researchers to learn statistical properties of the datasets. Objective: The objective of the research article is to introduce a novel SK-Clustering algorithm that overcomes identity disclosure, attribute disclosure and similarity attacks. The algorithm is evaluated using metrics such as discernability measure and relative error so as to show its performance compared with other clustering algorithms. Methodology: The SK-Clustering algorithm flexibly adjusts the level of protection for high utility. Also the size of the clusters is minimized dynamically based on the requirements of the protection required and we add extra tuples accordingly. This will drastically reduce information loss thereby increasing utilization. Results: For a k-value of 50 the discernabilty measure of SK algorithm is 65000 whereas the Mondrian algorithm exhibits 70000 discernability measure and the Anatomy algorithm has a discernability measure of 150000. Similarly, the relative error of our algorithm is less than 10% for a tuple count of 35000 when compared to other k-anonymity algorithms. Conclusion: The proposed algorithm executes more competently in terms of minimal discernability measure as well as relative error, thereby proving higher data utility compared with traditionally available algorithms.
Capacity Management in Hyper-Scale Datacenters using Predictive Modelling

Big data applications have become increasingly popular with the emerge of cloud computing and the explosion of artificial intelligence. Hence, the increasing adoption of data-hungry machines and se ...
The Analysis of Data Collected by Nodes and Smart Phones in Network

In this work we analyze the data collected from the network. On the basis of data collection and analysis, the diagnosis model is constructed, and the samples are statistically analyzed to find the implicit slow change. Under certain conditions, the sample distribution function is established to predict the change range. This study takes the scenario of physiological parameter monitoring.
MANFAAT ICT SEBAGAI MEDIA PEMBELAJARAN DI SD DHARMAJAYA PALEMBANG

This study aims to determine the benefits of Information and Communication Technologies (ICT) or more often we know Information and Communication Technology (ICT) as a learning media. ICT is a media or tool that is used to balance technological progress. This research method uses Qualitative Methods. data collection techniques with triangulation (combined). With the use of ICT that is effective and efficient, attractive, optimal, and stimulates the creativity of students, ICT is one of the learning media that is widely used in various fields of education because it increases effectiveness and efficiency in the learning process.
Constructing the Intelligence Management System of Students' Campus Sports

Through the intelligent bracelet of RFID technology, digital campus platform and campus sports intelligence management system, the comprehensive collection and management of students' behavior track, sports data, running, and related data of students' physical activity can be realized, the enthusiasm of students for sports can be stimulated, both the effectiveness and pertinence of teachers' physical education and the scientific and accurate school sports management can be improved for the students' physical health level.
USE OF E-RESOURCES IN UNIVERSITY LIBRARIES OF SEVEN NORTH EASTERN STATES OF INDIA

E-Resource is a media to help the information seeker to find all e-published information.Among them some of the e-resources are freely available and some are priced.E-resource is the digital medium for communication of information.The benefits of e-resorces are ---online avialability, 24X7 easy access and simultanious use.A good number of Universities have been discharging higher education in North East Region with good library support.It is utmost important to acquinted with e-resources in addition to traditional collection for updated knowledge and information.The Universities are the centres of higher education and research.The speed and scale of electronic revolution can be expected to have impact on research collection with a force not felt since the arrival of printing press.It undoubtly bring new opportunities for information provisions to users/researchers.So the collection will change to the truely hybrid resource which technology makes possible.The use of electronic resources is growing more rapidly than expected and the use of old journals in electronic format is increasing even more rapidly than use of electronic resources overall.This article will help to get a clear picture of the use of e-resources in University Libraries of seven North Eastern states of India
TVCG Guest Editors' Introduction

The papers in this special issue were presented at the 2019 IEEE Pacific Visualization Symposium (IEEE PacificVis 2019), which was held in Bangkok, Thailand from April 23 to 26, 2019 hosted by Chulalongkorn University. The IEEE Pacific Visualization Symposium, sponsored by the IEEE Visualization and Graphics Technical Committee (VGTC), aims to foster greater exchange between visualization researchers and practitioners especially in the Asia-Pacific region.
Variational Method Integrating Edge Detection and Smoothing in Digital Images

There is a consensus in computer vision about the importance of the scale concept for edge extraction and for image smoothing or representation. In this paper we explore a variational approach that allows to put together edge detection and image smoothing in a uniﬁed linear scheme. Basically, the functional proposed by Mumford and Shah is re-written as an energy deﬁned with two arguments: the ﬁrst one representing smooth versions of the original image and the second one encompassing its edge set. We follow known results in the variational analysis to obtain a numerical scheme to minimize the energy. We apply Fourier analysis to verify that the iterative scheme converges to a low-pass representation of the original image in the ﬁrst argument and a high-pass signal in the other one. In the experimental results we show that the obtained scheme encourages intraregion image smoothing in preference to interregion blurring with edge localization at a desired scale.
Awareness-dependent Distribution of Visual Bottom-up Attention

The stimulus-driven contribution to the allocation of attention is bottom-up attention. Although bottom-up selection is typically quick and potent, it remains unclear how bottom-up attention will be distributed when multiple salient stimuli are presented simultaneously and whether this distribution depends on awareness. Here we performed psychophysical and functional magnetic resonance imaging (fMRI) experiments to examine these issues. In our experiments, each texture stimulus had a regular Manhattan grid of 13 × 37 low luminance bars, presented in the lower visual field on a dark screen. All bars were identically oriented except for the foreground region of 2 × 2 bars with another orientation. There were four different foregrounds with 0°, 25°, 50°, and 90° orientation contrasts between the foreground bars and the background bars. In each texture stimulus, a pair of foregrounds was centered in the lower left and lower right quadrants at 5.83° eccentricity, one of which was 90° foreground. Thus, there were three possible texture stimuli: 90° + 0°, 90° + 25°, and 90° + 50° in our experiments. Low- and high-contrast masks, which had the same grid as the texture stimuli, rendered the whole stimulus visible (Experiment 1) and invisible (Experiment 2, confirmed by a forced-choice test) to subjects, respectively. In the psychophysical experiment, the Posner cueing paradigm was adopted to measure the spatial cueing effect of 90° foreground on an orientation discrimination task and thus the other foreground (i.e., 0°, 25°, and 50°) served as the distractor. We found that, when orientation contrast of the distractor increased, both the cueing effect and the fMRI BOLD signal in areas V1–V4 of 90° foreground fell off monotonically in Experiment 1 (the “Gradient” mechanism), but was constant in Experiment 2 (the “Winner-take-all” mechanism). These findings indicate an awareness-dependent distribution of visual bottom-up attention in human visual areas.
Construction and Practice of Practice Teaching System Based on Printing and Packaging Characteristics

In order to better serve the printing and packaging industry and highlight its characteristics, it is essential to build a relatively perfect practical teaching system. This paper first introduces the composition and construction of the practical teaching system, and then focuses on practical training, social practice, curriculum design and graduation design and other practical teaching methods and the ultimate results. Perfect practice teaching will certainly be conducive to the cultivation of practical and innovative talents.
Performability Model for Assessing NoSQL DBMS Consistency

Over the last decades, NoSQL database management systems (DBMS) have been adopted as a prominent technology for big data applications. NoSQL provides high performance and scalability, but there are trade-offs for meeting these non-functional requirements. A major issue is related to eventual consistency between database replicas to achieve improved performance and availability. Usually, NoSQL DBMSs allow the adoption of distinct consistency levels to mitigate problems related to outdated information, though raising the consistency level implies in loss of performance. Such a trade-off may not be trivial to be assessed, since some consistency levels may waste or overuse system resources without obtaining better performance or availability. This paper presents a technique based on generalized stochastic Petri nets to assess NoSQL DBMS consistency regarding latency and availability. A case study is presented to demonstrate the influence of consistency and replication factors on system performance.