Reviewerly/exHarmony huggingface dataset:
Adaptive Testing Tool for Students with Dyslexia

Dyslexia is a neurological and lifetime condition that is often inherited. One out of ten people have some or the other traits of dyslexia, and because of this around 20 % face difficulties in reading and writing. Appropriate guidance provided to students with dyslexia at an early age can reduce the problems faced by them drastically. With massive strides in technology, a digital solution to this problem can prove to be more effective and efficient. For this purpose, a helping aid in the form of an android application is devised. It will help to fasten the learning process among these students who come across a wide variety of digital tools and are more prone to get attracted to such tools for learning than the standard pen-paper tools. This application will help the user to master writing by practicing alphabets, numbers and words.
Leveraging Technology-Mediated Adult and Distance Learning for Economic Growth in Africa#

Following the rudiments of contextual analysis, and based on theoretical and philosophical analyses, this paper explores how technology mediated adult and distance learning might contribute to the economic growth of Africa, all things remaining equal. It proceeds from the perspective of analysing the related contextual situations of selected countries in Africa through the brief review of Africaâ€™s technology readiness, and posited that the possible gains that could be made from the application of adult and distance learning are tacitly located in somewhat perfect management of systems and sub-systems in education and the economy. Based on this analysis, it was proposed that whatever might be the state of Internet and technology readiness Africa has achieved, the successful creation of the nexus for economic growth is circumscribed unless the continentâ€™s political stability is assured now and in the future.
Multi Factor Authentication for Student and Staff Access Control

This paper proposes a model to improve security, by controlling who accesses the University of Zambia Campus, Student Hostels and Offices.The proposed model combines Barcode, RFID, and Biometrics Technology to automatically identify Students and Staff.A component to track visitors' physical location and movements in real time is also included to ensure visitors go to authorized places.A baseline study based on International Standard Organisation 27002 standard was conducted to measure the level of security at UNZA.This result shows that UNZA has uncontrolled access into the campus environment, student hostels and offices.The results from this study were used to develop the proposed model.When the RFID reader installed at any of the entrances detects an RFID tag number, the system requests for a fingerprint scan and scans the database for a match.If both RFID card and fingerprint belong to a registered Student or Staff, the entrance door or Turnstile is released open and access is granted otherwise access is denied.In case of the visitor the National ID number is tied to the RFID tag number.The visitors' RFID tag has a GPS module fixed to it.Once the visitor is granted access their movements and physical location are tracked in real time.
Perfil estudiantil: uso de WhatsApp y Facebook

The relationship between smartphones , WhatsApp, Facebook and students of the upper secondary level is evident, something that should be taken into account is the profile and the academic area in which students are trained. The present exploratory research looks for the correlation that exist between the use that the students of preparatory level give, with the applications WhatsApp and Facebook. A quantitative structured survey was applied to 228 students of Program II of the UAPUAZ and the data obtained thorough the Chi Square method and Correlation Coeficient Pearson were correlated by means of cross SPSS tables. It is concluded that students who are trained in the economic -administrative area give greater use of these applications inside the classroom.
Conducting Laboratory Experiments Properly with Statistical Tools

This hands-on half-day tutorial consists of two sessions. Part~I covers the following topics: Preliminaries; Paired and two-sample t-tests, confidence intervals; One-way ANOVA and two-way ANOVA without replication; Familiwise error rate. Part~II covers the following topics: Tukey's HSD test, simultaneous confidence intervals; Randomisation test and randomised Tukey HSD test; What's wrong with statistical significance tests?; Effect sizes, statistical power; Topic set size design and power analysis; Summary: how to report your results. Participants should have some prior knowledge about the very basics of statistical significance testing and are strongly encouraged to bring a laptop with R already installed. They will learn how to design and conduct statistical significance tests for comparing the mean effectiveness scores of two or more systems appropriately, and to report on the test results in an informative manner.
Single station estimation of earthquake early warning parameters by using amplitude envelope curve

In this study, new empirical relationships to estimate key parameters in Earthquake Early Warning (EEW) system including magnitude, epicentral distance and Peak Ground Acceleration (PGA) are introduced based on features of the initial portion of P-wave’s amplitude envelope curve.For this purpose, 226 time series recorded by bore-hole accelerometers of Japanese KiK-net are processed for earthquakes with magnitudes from 3 to 7.2  and epicentral distances of less than 50 km. Hereby, an improved single station method for estimation of epicentral distance and two new methods for estimation of magnitude and amplitude of  are proposed based on exponentially envelope curve as  in known (B – Δ) method. A scaling relationship of B × Tr – Δ is proposed to estimate epicentral distance which is well correlated for larger earthquakes, with results more robust and reliable than the previous method (B – Δ). Non-dimensional parameter,  depends on earthquake magnitude and  parameter in the above-mentioned function. By using the features of acceleration envelope curve and peak amplitude of P-waves, scale parameter  is proposed that is well correlated with magnitude and has capability of estimating magnitude with standard deviation of less than 0.77 magnitude unit.  is proportional to a part of area under envelope curve as a function of magnitude. Moreover, it is indicated that  in a single station can be estimated by using envelope curve characteristics of initial P-waves portion.
Towards a Standard to Assess Blockchain & Other DLT Platforms

There are more and more Distributed Ledger Technologies (DLT) and it becomes difficult to assess them due to unfounded marketing claims and their open networks, which can easily be under attack. This paper presents an initial DLT assessment framework as discussed as part of the ITU focus group on application of distributed ledger technology and how it has been applied to assess one of the major existing DLT platforms at time of writing, i.e., Ethereum.
HUBUNGAN MOTIVASI EKSTRINSIK DENGAN HASIL BELAJAR MATEMATIKA SISWA KELAS V SD SE-GUGUS I KECAMATAN MARPOYAN DAMAI PEKANBARU

ABSTRACTThe purpose of this research was to know whether there is a significant relation between extrinsic motivation and mathematics learning outcomes of fifth grade students of Elementary School in regional I of Marpoyan Damai District, Pekanbaru. This type of research is quantitative using the correlational method. The sample selection uses Cluster Sampling technique, so that in this research a sample of 183 students. Data collecting conducted by using questionnaire, interview and documentation techniques. Data analysis techniques in this research used correlation techniques of product moment. The results of data analysis obtained a correlation coefficient of 0,452 and t-value higher than t-table or 6,815 &gt; 1,653, so that from the results of this research it can be concluded that there is a significant relation between extrinsic motivation and mathematics learning outcomes the increase of extrinsic motivation, followed by an increase in mathematics learning outcomes of fifth grade students of Elementary School in regional I of Marpoyan Damai District, Pekanbaru.
<i>The Library Staff Development Handbook: How to Maximize Your Library’s Most Important Resource</i>. By Mary Grace Flaherty. Lanham, MD: Rowman &amp; Littlefield, 2017. Pp. xiii+139. $45.00 (paper). ISBN 978-1-4422-7036-7.

Previous articleNext article No AccessReviewsThe Library Staff Development Handbook: How to Maximize Your Library’s Most Important Resource. By Mary Grace Flaherty. Lanham, MD: Rowman & Littlefield, 2017. Pp. xiii+139. $45.00 (paper). ISBN 978-1-4422-7036-7.Melissa Fraser-ArnottMelissa Fraser-ArnottLibrary of Parliament, Ottawa, Canada Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by The Library Quarterly Volume 89, Number 1January 2019 Article DOIhttps://doi.org/10.1086/700666 Views: 118Total views on this site For permission to reuse, please contact [email protected]PDF download Crossref reports no articles citing this article.
Image Hiding on Audio Subband Based On Centroid in Frequency Domain

ABSTRAK Audio watermarking adalah mekanisme penyembunyian data pada audio. Metode penyembunyian data yang digunakan dalam penulisan ini adalah Lifting Wavelet Transform (LWT), Fast Fourier Transform (FFT), Centroid dan Quantization Index Modulation (QIM). Langkah pertama adalah host audio tersegmentasi menjadi beberapa frame. Kemudian sub-band terpilih diubah oleh FFT dengan mengubah domain sub-band dari waktu ke frekuensi. Proses centroid digunakan untuk menemukan titik pusat frekuensi untuk lokasi penyisipan untuk mendapatkan output yang lebih stabil. Proses penyematan dilakukan dengan QIM. Kinerja watermarking oleh parameter yang disesuaikan memperoleh nilai imperceptibility dengan Signal to Noise Ratio (SNR) &gt; 21 dB, Mean Opinion Score (MOS)&gt; 3.8 dengan kapasitas = 86.13 bps. Selain itu, untuk sebagian besar file audio terwatermark yang diserang, metode ini tahan terhadap beberapa serangan seperti Low Pass Filter (LPF) dengan fco&gt; 6 kHz, Band Pass Filter (BPF) dengan fco 50 Hz - 6 kHz, Linear Speed Change (LSC) dan MP4 Compression dengan Bit Error Rate (BER) kurang dari 20%. Kata kunci: FFT, subband, LWT, Centroid, Audio Watermarking, QIM ABSTRACT Audio watermarking is a mechanism for hiding data on audio. Data hiding methods used in this paper are Lifting Wavelet Transform (LWT), Fast Fourier Transform (FFT), Centroid and Quantization Index Modulation (QIM). The first step is to segment host audio into several frames, then the selected sub-band is changed by the FFT by changing the sub-band domain from time to frequency. The centroid process is used to find the center of frequency for the insertion location to get a more stable output. The embedding process is done by QIM. The watermarking performance by adjusted parameters obtains the imperceptibility value with Signal to Noise Ratio (SNR)&gt; 21 dB, Mean Opinion Score (MOS)&gt; 3.8 with a capacity = 86.13 bps. In addition, for most of attacked watermarked audio files, this method is resistant to several attacks such as Low Pass Filter (LPF) with fco&gt; 6 kHz, Band Pass Filter (BPF) with fco 50 Hz - 6 kHz, Linear Speed Change (LSC) and MP4 Compression with Bit Error Rate (BER) less than 20%. Keywords: FFT, subband, LWT, Centroid, Audio Watermarking, QIM
Metode Hibridasi Artificial Bee Colony dan Fuzzy K-Modes untuk Klasterisasi Data Kategorikal

Fuzzy K-Modes is an effective method for clustering categorical data. This method is as extensions of fuzzy k-means algorithm by using modes in the process of matching the dissimilarity measure to update centroid of the cluster and to obtain the optimal solution. Nevertheless, Fuzzy K-Modes has the disadvantage of the possibility of stopping in the optimal local solution. Artificial Bee Colony (ABC) is an optimization method that has been proven effective and has the ability to obtain global solutions. This study proposes a hybridization between the Artificial Bee Colony algorithm and Fuzzy K-Modes for clustering categorical data. The implementation of hybridization between Artifical Bee Colony and Fuzzy K-Modes (ABC-FKMO) has been proven to be able to improve the performance of categorical data clustering especially in the aspects of Objective Function, F-Measure, and Accuracy. The test results with datasets of the Soybean Disease, Breast Cancer and Congressional Voting Records from the UCI data repository, showed the Accuracy averages of 0.991, 0.615, and 0.867. Objective Function is better at an average of 2.73%, F-Measure is better at an average of 4.31% and Accuracy is better at an average of 5.16%.
Uses of information resources: An analytical study of library services of MNV university

The Institution which provides higher education is University.The university library plays major roles to full-fill their objectives.As we know a university library contains print and electronic information resources.Students, Researchers and Teachers come together on same platform and getting their required information.Today it has been seen that users required print as well as electronic infor mation.So there is a new way opened for library science researchers how libraries are maintain their information resources.How libraries manage electronic resources for the purpose of better utilization.In this paper I try to analyses the uses pattern and management of e-resources
Report of the Cataloging Norms Interest Group (CNIG) Meeting. American Library Association Midwinter Meeting, Denver, February 2018

"Report of the Cataloging Norms Interest Group (CNIG) Meeting. American Library Association Midwinter Meeting, Denver, February 2018." Technical Services Quarterly, 36(1), pp. 95–96
Distributed strategies for computational sprints

Computational sprinting is a class of mechanisms that boost performance but dissipate additional power. We describe a sprinting architecture in which many, independent chip multiprocessors share a power supply and sprints are constrained by the chips' thermal limits and the rack's power limits. Moreover, we present the computational sprinting game, a multi-agent perspective on managing sprints. Strategic agents decide whether to sprint based on application phases and system conditions. The game produces an equilibrium that improves task throughput for data analytics workloads by 4--6x over prior greedy heuristics and performs within 90% of an upper bound on throughput from a globally optimized policy.
Interpreting Intermittent Bugs in Mozilla Applications Using Change Angle

Learning in evolving environments involves learning from data where the statistical characteristics can change over time. Current change detection algorithms that are used online for data streams detect whether a change has occurred in the data but there is always a detection delay. None of the existing online techniques can accurately pin-point the exact location of when the change starts to occur, which can be critical. We present a novel method Change Angle and we show, for the first time, how to pin-point online the location at which change starts to occur. We apply our Change Angle method in the application area of software revision control using Mozilla data, where it is important to detect not only the presence of change but also to pin-point accurately the location of when change starts to occur.
A coarse-to-fine copy-move image forgery detection method based on discrete cosine transform

&lt;span&gt;Copy-move forgery is a type of image forgery where one part of an image is copied and pasted in other regions of the same image, and it is one of the most common image forgeries to conceal some information in the original image. Discrete Cosine Transform (DCT) is one of the detection techniques which the detection rate relies intensely on the size of block used. Small block size is known for its ability to detect fine cloned objects, but the drawback is it produces too many false positive and requires high execution time. In this research, a method to overcome the weaknesses of using small block size by applying the coarse-to-fine approach with the two-tier process is proposed. The proposed method is evaluated on fifteen forged images on the CoMoFoD dataset. The results demonstrated that the proposed method is able to achieve high precision and recall rate of over 90% as well as improves the computation time by reducing the overall duration of forgery detection up to 73% compared to the traditional DCT method using small block size. Therefore, these findings validate that the proposed method offers a trade-off between accuracy and runtime.&lt;/span&gt;
IDM-WSDM 2019

The first workshop on Interactive Data Mining is held in Melbourne, Australia, on February 15, 2019 and is co-located with 12th ACM International Conference on Web Search and Data Mining (WSDM 2019). The goal of this workshop is to share and discuss research and projects that focus on interaction with and interactivity of data mining systems. The program includes invited speaker, presentation of research papers, and a discussion session.
A New Robust Methodology of Image Compression based on CDF Wavelets

It is used specially for the compression of images where tolerable degradation is required.With the wide use of computers and consequently need for large scale storage and transmission of data, efficient ways of storing of data have become necessary.With the growth of technology and entrance into the Digital Age, the world has found itself amid a vast amount of information.Dealing with such enormous information can often present difficulties.Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level.The reduction in file size allows more images to be stored in a given amount of disk or memory space.It also reduces the time required for images to be sent over the Internet or downloaded from Web pages.JPEG and JPEG 2000 are two important techniques used for image compression.
Dampak pemanfaatan ICT dalam pendidikan

ICT has been considered a fundamental need in the world of education. All aspects of education cannot be separated from the support of ICT utilization. However, several studies have found that ICT has not had a significant impact in improving the quality of the education process. Some problems are often discussed, among others; 1) ICT understanding dichotomy as a tool. ICT is used as a tool not as an ultimate goal to be achieved. 2) ICT as a new area. In most cases, educators consider ICT as a new area (subject matter) not a new way of teaching and interaction with students. 3) Several phenomena in ICT among others; the impact of the use of ICT is not clear because of the absence of assessment indicators, very little data is obtained regarding ICT in education, ICT used in isolation is not integrated with other subjects and best practice is rarely disseminated so it does not have a broad impact.
EFFECT OF INNOVATIVENESS AGILITY ON PERFORMANCE OF SAVINGS AND CREDIT CO-OPERATIVES IN KENYA

Globalization and rapid technological developments have contributed to uncertainty and unpredictability in all sectors which have emphasized the importance of the ability of an organization to adapt to unexpected changes, something that is considered to be critical to achieving and maintaining a steady performance. The study established effect of innovativeness agility on performance of savings and credit co-operatives in Kenya. The study used explanatory cross-sectional design. The study employed stratified random sampling technique in coming up with a sample size of 204 respondents from a total of 433 of representatives of management staff working in savings and credit co-operatives in Kenya. The study concluded that there is a strong correlation coefficient between Performance of Saccos and innovativeness agility. The study recommended that that policy and practice for performance should be carefully evaluated and the results of that evaluation fed back into improved approaches. Key Terms: Agility strategy, Competition, Innovativeness, Organizational performance, Quality Management, s strategic Agility CITATION: CITATION: Ade, E. M., Namusonge, G. S., &amp; Sakwa, M. (2019). Effect of innovativeness agility on performance of savings and credit co-operatives in Kenya. The Strategic Journal of Business &amp; Change Management, 6 (1), 135 – 149.
Weak RSA Key Discovery on GPGPU

We address one of the weaknesses of the RSA ciphering systems \textit{i.e.} the existence of the private keys that are relatively easy to compromise by the attacker. The problem can be mitigated by the Internet services providers, but it requires some computational effort. We propose the proof of concept of the GPGPU-accelerated system that can help detect and eliminate users' weak keys. We have proposed the algorithms and developed the GPU-optimised program code that is now publicly available and substantially outperforms the tested CPU processor. The source code of the OpenSSL library was adapted for GPGPU, and the resulting code can perform both on the GPU and CPU processors. Additionally, we present the solution how to map a triangular grid into the GPU rectangular grid \textendash{} the basic dilemma in many problems that concern pair-wise analysis for the set of elements. Also, the comparison of two data caching methods on GPGPU leads to the interesting general conclusions. We present the results of the experiments of the performance analysis of the selected algorithms for the various RSA key length, configurations of GPU grid, and size of the tested key set.
A new feature subset selection model based on migrating birds optimisation

Feature selection represents a fundamental preprocessing phase in machine learning as well as data mining applications. It reduces the dimensionality of feature space by dismissing irrelevant and redundant features, which leads to better classification accuracy and less computational cost. This paper presents a new wrapper feature subset selection model based on a recently designed optimisation technique called migrating birds optimisation (MBO). Initialisation issue regarding MBO is explored to study its implications on the model behaviour by experimenting different initialisation strategies. A neighbourhood based on information gain was designed to improve the search effectiveness. The performance of the proposed model named MBO-FS is compared with some state-of-the-art methods regarding the task of feature selection on 11 UCI datasets. Simulation results show that MBO-FS method achieves promising classification accuracy using a smaller feature set.
Learning Time Patterns

This chapter is important in that it lays a foundation for claims throughout this book that entrainment serves a platform for learning. In this chapter, this idea is developed in the context of learning categories of meter (e.g., duple meter vs. triple meter). The key difference is that entrainment depends on coupling parameters supplied by external driving rhythm force, whereas learning depends on a binding parameter which is strengthened simply by repeated synchronous activity of two or more oscillations. Against a backdrop of evidence indicating that musicians especially possess skill in recognizing metric categories, this chapter develops the coupling–binding distinction with the aim of showing that what people learn when exposed to metrical time patterns are global attractors instilled by learning a variety of different instances in a given metric category.