Reviewerly/exHarmony huggingface dataset:
Multi-Word Expressions in Second Language Writing: A Large-Scale Longitudinal Learner Corpus Study

© 2019 Language Learning Research Club, University of Michigan In the present study, we sought to advance the field of learner corpus research by tracking the development of phrasal vocabulary in essays produced at two different points in time. To this aim, we employed a large pool of second language (L2) learners (N = 175) from three proficiency levels—beginner, elementary, and intermediate—and focused on an underrepresented L2 (Italian). Employing mixed-effects models, a flexible and powerful tool for corpus data analysis, we analyzed learner combinations in terms of five different measures: phrase frequency, mutual information, lexical gravity, delta Pforward, and delta Pbackward. Our findings suggest a complex picture, in which higher proficiency and greater exposure to the L2 do not result in more idiomatic and targetlike output, and may, in fact, result in greater reliance on low frequency combinations whose constituent words are non-associated or mutually attracted.
TASK-BASED LEARNING WORKSHEETS IN THE DEVELOPMENTOF MULTIPLE INTELLIGENCES

This project proposes the use of Task-Based Learning worksheets which have been developed as a supplementary material based on the Our World through English 1 in order to improve students’ language skills by accessing multiple intelligences learners. Nineteen students in their eighth year of Basic Education at Cornelio Crespo Toral School participated in this study for fifteen months. Data is collected from a pre-test, a post-test, and a questionnaire. The results show the improvement of students’ language learning skills by 24.04%. At the end of the study, the participants developed a sense of motivation, awareness, and increased their language learning skills through the application of the Task- Based Learning worksheets. Teachers recognized the effectiveness of new strategies and techniques implemented in their classes by applying appropriate materials to improve learning skills based on dominant intelligences.
N-Gram Language Model to Predict the Word Sequence in a Degraded Braille Document

This paper presents a feature extraction method for optical Braille recognition (OBR) system to locate, extract and convert the Braille cells in one sided Indian language Braille documents. The Braille cells are located by implementing a grid-box designed using physical properties of a Braille cell. A Braille document image is a compilation of group of six dots. The physical position of each dot and its relevance with other neighboring dots in a single cell gives various Braille characters. After the grid-box is mapped with the Braille cells in the document, the mesh characters are extracted and are then mapped with existing database to translate them in required text. Mapping of Braille cells with mesh box and separation of characters and words from a Braille document was a challenging task. The unwanted dots or degraded dots way result in incorrect mapping of characters. In this paper we have used N-gram Language Models to Predict the word Sequence in case of wrong mapping of characters in extraction and conversion of the Braille cells.
A Combination of Text Similarity And Latent Semantic Analysis (LSA) Methods In Automatic Scoring Essay

Description of type exam (essay) is considered by many experts as the most appropriate test to reap the results of a complex learning activities, because essay writing will involve the student’s ability to remember, organize, express, and integrate the ideas of the students. Just to correct the essay exam results, requiring a longer time if done manually because most do by reading an essay one by one. So that, lecturers needs to spend a lot of time to assess the answers of student’s exam. Therefore, in implementation, automatic scoring system is needed on the answer essay exam. Automated essay assessment method used in this study is a combination of Text Similarity and Latent Semantic Analysis (LSA) to look for a match and similarity level student answers with the answer key that has previously been inputted into the system. Data used in this test is 15 students with each student to answer 5 questions. Data obtained from subjects essay Basis Data I. The correlation results of that two assessment shows grades 0,946085 with an average increment of 2,08. Which means the results of the assessment system is not much different from the results of the assessment of the lectures, so that the automatic scoring system can be applied to essay type exam.
Implementation of Modified Mask RCNN

Detecting camouflage moving object from the video sequence is the big challenge in computer vision. To detect moving object from dynamic background is also very difficult as the background is also detected as moving object. Mask RCNN is a deep neural network which solves the problem of separation of instances of same object in machine learning or computer vision. Thus, it separates different objects in video. It is the extension of faster RCNN in which an extra branch is added to create an object mask simultaneously along with bounding box and classifier. After giving input, Mask RCNN gives the rectangle around the object, class to which object belong and object mask. This article introduces Mask RCNN algorithm along with some modifications for target detection from dynamic background and also for camouflage handling. After target object detection, contrast limited adaptive histogram equalization is applied. Morphological operations are used to improve results. For both challenges quantitative and qualitative measures were obtained and compared with the existing algorithms. Our method efficiently detects the moving object from input sequence and gives best results in both situations.
The Feasibility of Writing Learning Videos for Elementary School Students

Low-grade students still have difficulty in writing. Writing delays can hinder the learning process. This study aimed to develop writing learning video products for first-grade elementary school students whose validity has been tested. This research refers to the ADDIE development model procedure. However, this study did not implement and evaluate stages due to limited time, effort, resources, and finance. The subjects of this study were two material experts, two media experts, and two practitioners. The object of this research is the validity of the writing learning video. The data collection of this research used a questionnaire method by providing assessment sheets to two media expert lecturers, two material expert lecturers, and two first-grade elementary school teachers. The data from the validation results from the experts were then analyzed using the mean formula to determine the average validity score of the writing learning videos. The analysis results showed that the average validation score for writing learning videos is 4.44 with very good criteria. The average score of validation for writing learning video materials is 4.06 with very good criteria. Based on the analysis results, the writing learning video for first-grade students of SD was declared valid and had very good criteria.
Evaluation for Improving Security Management of Service Oriented Architecture At Meraki Digital Indonesia

Meraki Digital Indonesia wants to evaluate security management on Service Oriented Architecture that has been implemented in this company whether it is in accordance with the standards or not, using the COBIT 5 method. It is expected that the suitability of the maturity level can be carried out in accordance with the security management domain needed to ensure the fulfillment of the basic requirements of organizational information resources, namely the availability of integrity and availability of data or information. As well as using the Analytical Hierarchy Process algorithm to provide recommendations using decision-making in solving problems with explicit logical analysis, there are three principles that underlie AHP thinking, which is compiling hierarchies, the principle of setting priorities, and the principle of logical consistency. Then the evaluation results using COBIT 5, there are 6 security management criteria that are used as a basis for evaluating, among others, strategies &amp; policies, organizations, people, processes, technology and facilities and domains that are used are Plan and Organizes (PO), Acquire and Implement (AI), Deliver and Support (DS), and Monitor and Evaluate (ME). Whereas for recommendations needed by using analytical hierarchy processes, there are three things that need to be improved according to the wishes of stakeholders, namely the need to improve the criteria of technology with a value of 0.132, facilities with a value of 0.137, and people with a value of 0.161 according to the lowest ranking on the tested criteria.
Hybrid Neuro-Fractal Analysis of ECG Signals to Predict Ischemia

In this thesis, we propose and implement a new hybrid approach using fractal analysis, statistical analysis and neural network computation to build a model for prediction the number of ischemia occurrence based on ECG recordings. The main advantage of the proposed approach over similar earlier related works is that first useful parameters from fractal analysis of the signal are extracted to build a model that includes both clinical characteristics and signal attributes. Statistical analysis such as binary logistic regression and multivariate linear regression are then used to further explore the relation of parameters in order to obtain a more accurate model. We show that the results compare well with those of earlier work and clearly indicate that the augmentation of the above mentioned approaches improves the prediction accuracy.
To Design and Develop the Real-Time Watermarking Scheme which could be used in IPTV Applications

In view that the utilization digital strategies for sending and storing pix are establishing; it is far changing into an indispensable most vital assignment a method to protect the confidentiality, integrity and believability of pictures. This valuate paper extends to the power parameters used in cryptography strategies and learning on their take care of problems that had been developed and are in acknowledge in as lots as a result of the second instances.
Segmentation of Malayalam Handwritten Characters into Pattern Primitives and Recognition using SVM

This paper describes a lexical analysis (segmentation) approach in Pattern Recognition for Online Handwritten Character Recognition (OHCR) in Malayalam. The subunits (Pattern Primitives) in the single stroke vowel characters in Malayalam are identified and marked with pattern primitives to obtain a reference set of characters. Segmentation of the handwritten character samples into pattern primitives is made using a Combined Approach of Ramer Douglas Peucker algorithm and Eight Direction Freeman Code as per reference set. Features that are unique in the primitives of a character are extracted. The discriminating features identified are the direction of first primitive, segment count, cusp in second primitive, crossing in third primitive, and cusp in seventh primitive. The experiments were conducted on 100 samples per character that showed exact segmentation as per the reference set. With a five dimension feature set, the study achieved a recognition rate of 95.77% for five-fold cross-validation using Support Vector Machine with RBF kernel. The study shows that the segmentation of characters into pattern primitives is an effective method to realize accurate Malayalam OHCR systems for real-time applications.
To Design &amp; Develop Mobile – Based Birth Registration System for New Born Baby in Bangladesh

Being a developing country, Bangladesh has digitalized in many sectors but registration process for a new born baby in this country is still the conventional system.Manual method is complex & can cause inaccurate registration which may lead to different problems like invalid identity, cost of registration, loss of birth certificate, wrong population statistics, forgery in information and also it fritters away considerable time.Ensuring every child's birth is must for every country to gather accurate population statistics as it is essential in social and budget planning by a government to allocate enough resources to meet the needs of citizens.So, there is a huge potential of globally accessible mobile-based registration system.The ultimate purpose of this research is to create an automated birth registration system to issue birth certificate immediately to a new born baby in Bangladesh.The proposed system will help the government in terms of being a globally accessible portable system, reducing the cost of registration and by creating a national database for future use.This study aims to establish mass registration including underprivileged people from rural area through mobile system.Registered children will be able get medical support, educational & all other government facilities through this system.The meaning of a successful registration system is that it should be complete, continuous, permanent and compulsory.
Leeway Space Mandibula pada Siswa Suku Minang di Sekolah Dasar Lubuk Sikaping, Sumatera Barat

The prediction of permanent size of theet which haven’t errupted to determine the value of place needed, availability of space and predict the storage of space. Is one of important aspect in diagnosis and treatment planning on the period of mixed dentition. Prediction method that used commonly is Moyers method which the data is taken from Kaukasoid ras. The objective of the research is to see the difference of leeway space of mandibula on Minang man and woman students of elemantary school Lubuk Sikaping. The method of this research is cross sectional comprative study. 56 samples of mandibula study are taken from the student of SDN 06 Pauh, SDN 09 Pauh, and SDN 10 Pauh Lubuk Sikaping at the age of 8 to 10 years and they are Minangnese. The results are analyzed statistically by t-test on significant degree 95%. This research indicates that the large average of man mandibula leeway space on the left (1,76 mm) and on the right (1,85 mm). And the average of leeway space of woman mandibula leeway space on the left (2,03 mm) and on the right (2,16 mm). The analyze t-test result on the significant degree 95% show there is no significant difference (p&gt;0,05) between man and woman students. Therefore, it can be concluded that the large average of leeway space of man and woman mandibula in Minang students of elementary school Lubuk Sikaping showed no significant difference in size.
Decision Tree: A Predictive Modeling Tool Used in Cloud Trust Prediction

Trust is one of the important challenges faced by the cloud industry. Ever increasing data theft cases are contributing in worsening this issue. Regarding trust, author has a perception that this challenge can be handled to some extend if consumer can evaluate “Trust Value “ of the provider or can predict the same on some reliable basis. Current research is using predictive modeling for predicting trustworthiness of cloud provider. This paper is an attempt to utilize the data mining algorithm for predictive modeling. Decision Tree, a supervised data mining algorithm has been used in the current work for making predictions. Certification attainment criteria as prime basis for trust evaluation. In current scenario, data mining algorithm will classify providers in category of low, medium and high category of trust on the basis of information displayed on the public domain.
PENINGKATAN KETERAMPILAN MEMBACA BAHASA ARAB MELALUI TEKNIK LOOK AND SAY (Penelitian Tindakan Siswa Kelas IV SDIT Segar Amanah)

ABSTRACT&#x0D; &#x0D; This research aims to improve the Arabic reading skills of fourth grade of SDIT Segar Amanah students through the Look and Say technique. The subjects of this research were 32 students of fourth grade SDIT Segar Amanah. This research used a Classroom Action Research method with a model from Kemmis and Mc Taggart which consisted of planning, acting and observing, and reflecting throughout 2 cycles. The data was collected using test and observation guidelines for teaching and learning activities and observation guidelines for teacher and student. This research shows that the Look .and Say technique can improve students' reading skills in Arabic with the difference in the results of the pre-test, post-test cycle 1 and post-test cycle 2 with the class average score in the pre-test is 49.5. Then the average score results in the post test cycle 1 was 67.2 and the result of the class average score in the post-test 2 was 78.3.&#x0D; Keywords : Arabic Reading Skills, Look and Say
OTOMATISASI SISTEM PRODUK DALAM PENGOLAHAN DATA PADA PROSES HIRING DI PT.PERTAMINA (PERSERO)

One month hiring process of new workers if taken on average reaches 250-300 people, which consists of fresh graduates, experience and shipping workers (Ships). The hiring process is still done manually input into the system, so it is quite a lot of spending and human resources (HR). Reporting data and presenting data related to business processes within the company also need to be made better and informative. Therefore it is necessary to automate the system to be able to support the speed and accuracy in the hiring process. Automation is the initial general form of organizational change in the form of a tool for ease of daily work. The method used to answer, uses the TAM method. The purpose of this research is to find out how much automation on the SAP system can have an effect on working time, which is more than 8 hours a day so that excessive overtime occurs, to find out the system automation in SAP is able to efficiently process data recording that occurs repeatedly and to find out the system automation in SAP can reduce human error. The level of acceptance of SAP users towards Hiring Process Automation at PT. Pertamina (Persero) based on perceived usefulness, perceived ease of use, attitude toward using, behavioral intention to use and actual use as a whole reached 87.74%, included in the category of strongly agree.
SPARSE SIGNAL RECONSTRUCTION FROM LIMITED DATA USING BAYESIAN COMPRESSIVE SENSING VIA BELIEF PROPAGATION

Compressive sensing (CS) is a novel paradigm for acquiring signals, based on the idea that one can efficiently capture all the information of sparse domain by sampling only a part of signal through sub-Nyquist signal acquisition.As Bayesian inference is substituting conventional CS methods, the work employ Bayesian inference which depict CS matrix by a factor graph to accelerate both encoding and belief propagation (BP) decoding.Two state mixture Gaussian model is used to model prior for sparse signal.To decode a length-N signal having K large coefficients, our BCS-BP decoding algorithm uses O (K log (N)) and O (N log2 (N)) computation.BCS-BP algorithm is easily versatile to various signal models.
The Effects of Open and Closed Skills on Athletes’ Attention Types

Background: Open and closed skills require different instructional training in regard to environment.Typical closed skills include diving, race swimming, and gymnastics, whereas open skills are those that are practiced in the changing world.Multiple cognitive processes are activated during both open and closed motor behavior, such as working memory, speed of information, and attention.Attention especially affects athletes' memory and cognitive processes.Objectives: The aim of the present study was to investigate the effects of skill type (open and closed) and gender on two different attention types (selective and sustained) in athletes.Methods: The study sample consisted of 40 subjects who were divided into three groups: 10 gymnasts (representing closed skills) purposely selected from the Jordan Gymnastics Federation; 10 non-athletes (representing open skills); and 20 fencers (also representing open skills).The Leiter International Performance Scale (Leiter-3) was used to evaluate the two attention types. Results:The results indicated that athletes of both open and closed skills show greater ability in both attention types.Some differences were found regarding types of selective attention (Stroop effect), where the elite open-skills athletes (fencers) scored higher Stroop scores.Moreover, the study revealed gender differences, with females having significantly higher Stroop color congruent and color incongruent stimuli scores than males.However, males in closed skills recorded higher scores on sustained attention.Overall, it seems that skill type strongly influences cognitive function.
2D CNN and Gated Recurrent Network for Dynamic Hand Gesture Recognition with A Fusion of RGB-D and Optical Flow Data

The dynamic hand gesture is an essential and important research topic in human-computer interaction. Recently, Deep convolutional neural network gives excellent performance in this area and gets promising results. But the Researcher had focused less attention on the feature extraction process, unification of frame, various fusion scheme and sequence-to-sequence prediction of a frame. Therefore, in this paper, we have presented an effective 2D CNN architecture with three stream networks and advances weighted feature fusion scheme with the gated recurrent network for dynamic hand gesture recognition. To obtain enough and useful information we have converted each RGB-D video to 30-frame and 45-frame for input. We have calculated an optical flow for frame-to-frame by given RGB video and extract dense motion features. After finding proper motion path, we have assigned more weight to optical flow features and fuse this information to the next stage and gets a comparable result. We have also added a newest Gated recurrent network for temporal recognition of frame and minimize training time with improved accuracy. Our proposed architecture gives 85% accuracy on the standard VIVA dataset.
RUSA Achievement Awards 2019

RUSA and its Sections are home to many knowledgeable and influential librarians who place libraries users at the center of their work. Each year members of RUSA’s Achievement Awards honor the most outstanding people, institutions, and projects in the field of reference and user services. This year’s selections were made possible with the hard work of our many superb committee volunteers, the people who took the time to nominate awardees, and the vendors who sponsored the awards. For each of the awards the winner is listed with a brief summary of why they were chosen. Further information about the winners is available in the RUSA Update press releases http://www.rusaupdate.org/category/news/awards-news/. The nomination period for the 2020 Awards opens in October 2019. See the individual award websites at http://www.rusaupdate.org/awards/ for further information.—Editor