Reviewerly/exHarmony huggingface dataset:
Quantum Arithmetic Circuits Simulation using IBM – Quantum Experience

The futuristic computing systems with low power dissipation are of interest among Researchers. Reversible logic provides less power dissipation as well as individual output assignment for each individual input. Hence designing reversible circuits are of great importance which finds significant application in Quantum Computing. It is a kind of computing that performs operations on data using quantum mechanical properties, such as superposition and entanglement. Unlike classical computing, quantum computing works on quantum bits. Qubits are processed by Quantum circuits, the basic building blocks of Quantum Computers. In this paper reversible Quantum arithmetic circuit like half adder, full adder, half subtractor and full subtractor are simulated using IBM Q simulator and the corresponding truth tables are verified.
Anomaly Detection at ATM Center using Machine Learning Algorithm

This paper proposes a new supervised algorithm for detecting abnormal events in confined areas like ATM room, server room etc. The aim of proposed work is to establish a technical base that will support a more secure and convenient social infrastructure, and one of the technologies that make up the technical base in the abnormal behavior detection using image processing. Generally, abnormal behavior detection is a method in which a model is created using normal behavior data and any behavior deviating from the model is deemed abnormal. In many cases, it is difficult to comprehensively collect abnormal behavior data in advance, thus being able to detect abnormalities with a model created using only normal behavior data is extremely useful for actual implementation. This article first shows application examples of abnormal behavior detection using image processing, which is followed by typical examples of abnormal behavior detection through motion image processing.
Hopeful Men@LT-EDI-EACL2021: Hope Speech Detection Using Indic Transliteration and Transformers

This paper aims to describe the approach we used to detect hope speech in the HopeEDI dataset. We experimented with two approaches. In the first approach, we used contextual embeddings to train classifiers using logistic regression, random forest, SVM, and LSTM based models. The second approach involved using a majority voting ensemble of 11 models which were obtained by fine-tuning pre-trained transformer models (BERT, ALBERT, RoBERTa, IndicBERT) after adding an output layer. We found that the second approach was superior for English, Tamil and Malayalam. Our solution got a weighted F1 score of 0.93, 0.75 and 0.49 for English, Malayalam and Tamil respectively. Our solution ranked 1st in English, 8th in Malayalam and 11th in Tamil.
Research on enterprise level cross domain integrated data inventory method based on DMAIC model

When traditional inventory methods sort out the data, the data format is not standardized, which leads to the long query time of inventory data. To solve this problem, this paper proposes an enterprise level cross domain integrated database storage method based on DMAIC model. Through the collection of cross domain integrated data for filtering and integration, the data are transferred to the central database in turn, and the data warehouse is established. The core data in the collected data is identified by using DMAIC model, and the core data is summarized into the inventory range. Then, the relevant data with high similarity are matched, and labels and data catalog are made to provide support for data positioning and query. The results show that compared with the traditional method, the query time of inventory data is shortened by 0.57s.
Interactive Virtual Reality as an Anatomy Teaching Tool: A Randomized Controlled Trial of a Trigeminal Nerve Virtual Reality Model

Objective: This study was aimed to investigate the effectiveness of a virtual reality (VR) model, as compared with textbooks, for teaching the anatomy of the trigeminal nerve.
A Post-processing Trajectory Publication Method Under Differential Privacy

Differential privacy is an effective measure of privacy protection in data analysis. We propose a differential private trajectory data publication method based on consistency constraints in road network space to significantly improve the accuracy of a general class of trajectory statistics queries. First of all, Laplace noise is injected into statistical data of each road segment. And then, in the post-processing phase, consistency constraint is employed to hold over the noisy output. Based on both synthetic datasets, we do experiments to evaluate the performance of the proposed method. The experimental results show that the proposed method achieves high availability and efficiency.
Unsupervised deep learning on seismic data to detect volcanic unrest

&amp;lt;p&amp;gt;The significant efforts of the last years in new monitoring techniques and networks have led to large datasets and improved our capabilities to measure volcano conditions. &amp;amp;#160;Thus nowadays the challenge is to retrieve information from this huge amount of data to significantly improve our capability to automatically recognize signs of potentially hazardous unrest.&amp;lt;br&amp;gt;Unrest detection from unlabeled data is a particularly challenging task, since the lack of annotations on the temporal localization of these phenomena makes it impossible to train a machine learning model in a supervised way. The proposed approach, therefore, aims at learning unsupervised low-dimensional representations of the input signal during normal volcanic activity by training a variational autoencoder (VAE) to compress, reconstruct and synthesize input signals. Thanks to the internal structure of the proposed VAE architecture, with 1-dimensional convolutional layers with residual blocks and attention mechanism, the representation learned by the model can be employed to detect deviations from normal volcanic activity. In our experiments, we test and evaluate two techniques for unrest detection: a generative approach, with a bank of synthetic signals used to assess the degree of correspondence between normal activity and an input signal; and a discriminative approach, employing unsupervised clustering in the VAE representation space to identify prototypes of normal activity for comparison with an input signal.&amp;lt;/p&amp;gt;
All guides: Using Videos in Canvas: SAGE Video

This guide provides instructions on linking and embedding Library videos, including playlists and clips, in your Canvas course and Reading List.
LibGuides: *Visitors' guide to the GTU library*: Open Access Resources

The GTU library offers a wide range of services to the community. Learn more about getting a card and using the GTU library here!
Power-Efficient Combinational Circuits Using Reversible Gate

With the advancement, the demand for more efficient power circuits is increasing in electronic industries. The alternative technology gains this aim as reversible logics which helps to design various digital circuits with almost zero power loss. In this paper, a new 3 × 3 gate has been proposed which have multiple functions and is universal in nature. There is one on one mapping in reversible gate that is every input has its unique output. The standard combinational circuits have been verified by using the proposed reversible gate. This proposed gate is highly efficient based on the performance comparison and can be used in various nano-electronic application.
An Analysis of Performance of An Anaerobic Fixed Film Biofilter (AnF2B) Reactor in Treatment of Cassava Wastewater

The cassava starch wastewater contains organic materials (as BOD, COD) in high concentrations so it has the potential to cause pollution in the aquatic environment. Several methods of cassava starch wastewater treatment have been used to reduce the concentration of organic matter (pollutants) in cassava starch wastewater, including Activated Sludge, Stabilization Pond, Anaerobic-Aerobic filter process. However, various studies continue to be carried out to get higher processing efficiency on the factors that influence it. Several factors influence the efficiency of wastewater treatment processes, including the type and origin of decomposing microorganisms, hydraulic residence time (HRT), organic load rate (OLR), process design, pH, and temperature. The research aimed to evaluate the performance of the AnF2B reactor in treating cassava starch wastewater, in which the reactor performance is shown by changes in organic matter removal (COD removal) and biogas production. The research is conducted using 3 types of AnF2B reactors wherein each AnF2B reactor contains a bee nest-shaped bio-filter as a growth medium for the consortium of indigenous bacteria. The AnF2B reactor operates in anaerobic conditions with a set temperature of 29–30 °C and a pH of 4.5–7. In each AnF2B reactor, cassava starch wastewater is fed with different OLR so that each reactor has an HRT of 5, 6, and 7 days. The concentration of COD at the influent and effluent of the reactor was measured and the biogas was produced using the APHA standard method. The results showed that the AnF2B reactor had a satisfactory performance in COD removal and biogas production, which at HRT: 6 days and OLR of 1.72 g/L·day found that the maximum COD removal was 98 % and the volume of biogas of 4.8 L/L·day was produced on the 12th day.
Describing Brachiopods Shape Based on Fusion of Curvature and Fourier Descriptors

The fossils classification has a great importance in palaeontological studies. They make it possible to understand the biodiversity in its morphological dimension and they show the morphological transformations suffered during the biological evolution. In this paper, we propose a descriptor for fossils classification and particularly Brachiopods. The proposed descriptor is a fusion between the curvature and Fourier descriptors. The curvature properties provide an apparently powerful cue to the underlying structure of the curve and captures completely the structure of planar curve. In addition, it is stable and complete. Fourier descriptors are powerful features for the recognition of two-dimensional connected shapes and is supported by the well-developed and well-understood Fourier theory. We used the Fourier descriptors proposed by Ghorbel, this set of invariants is also stable and complete. Experimental results are performed to illustrate the performance of the proposed descriptor.
LibGuides: Test Preparation Materials: Math

A guide to the test preparation materials available in the OHS Library, Frederick County Public Libraries, and online.
Analisis Usability Situs AMOr Menggunakan System Usability Scale pada PT PLN UPDK Keramasan

Usability analysis on the website can help in evaluating and developing the website. Currently, many websites provide a variety of information, but not a few websites cannot fulfill the main purpose of creating a website so that they often disappoint users in accessing the website. Through usability analysis can help improve system use and perspective of use. Likewise on the AMOr website (Organization Management Application), usability analysis can provide input for PT PLN UPDK Keramasan in developing the AMOr website more innovatively. Where in this study using the System Usability Scale method. The results of the analysis were obtained from respondents using a questionnaire that had been provided by the SUS Method itself. As for the results of the analysis of the SUS score in this study, namely 77, with an Acceptable level on the Accetability Ranges side, occupying Grade C on the Grade Scale side and being in the Good position on the Adjective Rating side. This shows that the AMOr Website has been accepted by the employees of PT PLN UPDK Keramasan as a useful website that can help in finding company information, and is satisfied with its access.
SISTEM INFORMASI TRACER STUDY ALUMNI STMIK INDONESIA BANJARMASIN BERBASIS WEB

A study on graduate tracing is generally called a tracer study, thus a tracer study is a study conducted on university graduates related to the transition of higher education to the world of work. The management of a tracer study at the Indonesian College of Computer and Information Management (STMIK) in Banjarmasin has not been given much attention and the campus has had difficulty tracing alumni data. The purpose of this research is to provide alumni information and reports on the results of tracer study data collection from alumni of STMIK Indonesia Banjarmasin. Data collection methods used are literature study, field study (interviews, questionnaires and observations). The final result of designing this application produces a web-based tracer study information system for STMIK Indonesia Banjarmasin alumni which can make it easier for the campus to obtain information on alumni data so that it helps in tracking alumni.
The Use of STAD Model in Teaching English

The research aims to describe the use of Students Team Achievement Division as a cooperative learning model in teaching English to students of SMPN 2 Poso. The subject this research was the eighth grade students at SMPN 2 Poso. Data were collected by observation, interview, documentation and questionnaire. The findings show that the English teacher of SMPN 2 Poso applied STAD model consists of five steps in teaching English. Keywords: student teams achievement, model, teaching English
Employing distributional semantics to organize task-focused vocabulary learning

How can a learner systematically prepare for reading a book they are interested in? In this paper, we explore how computational linguistic methods such as distributional semantics, morphological clustering, and exercise generation can be combined with graph-based learner models to answer this question both conceptually and in practice. Based on highly structured learner models and concepts from network analysis, the learner is guided to efficiently explore the targeted lexical space. They practice using multi-gap learning activities generated from the book. In sum, the approach combines computational linguistic methods with concepts from network analysis and tutoring systems to support learners in pursuing their individual reading task goals.
Subject Guides: ORGA 1070 : Achieving Service Excellence: Commitment

This guide provides access to quality resources relevant to the topics covered in NSCC's ORGA 1070: Achieving Service Excellence course. It is a collaborative effort of NSCC Organizational Learning and NSCC Libraries.
Using Whatsapp as MALL Tool to Enhance ESL Learners Performance in Pakistan

This exploration has studied the educational impact of WhatsApp as an important tool of Mobile Assisted Language Learning (MALL)in ESL learners academic performance at grade 8 in Pakistan. For the current investigation ESL learners from Lahore were the population of the studywhereas the sample size was of 100. All these learners were selected through random sampling method. At the initial stage the learners were given a pre-test and after that they were divided into two groups i.e. controlled and experimental group students. The teaching time was of 1 month and after a month a post test was conducted similarly structured like the pretest. The overall results gathered from the data reflect that the performance of the experimental group learners was much better than the controlled group. It was found out that WhatsAppas a MALL tool has ben significantly beneficial for the learners.
Automated User Interface Generation using Generative Adversarial Networks

A website is the most important marketing tool for a business.Industries are discovering the huge amount of opportunity a digital presence creates.Equally important for a website is a good User Interface because it can make or mar your digital presence and customer base.As a result, people who do not possess the required technical knowledge suffer critical losses due to the lack of a website or a website with substandard UI.The primary objective of this system is to "Enable everyone to create for the web", focusing more on the latter problem.The goal is to design a machine algorithm that always serves a new set of interactive vector-based UI mock-up images based on the user responses to a predefined number of questions.The proposed system can be used in various fields such as creating website designs for businesses, portfolios, online stores, blog sites, etc. Deep learning and GAN models will help the algorithm learn exact user requirements, preferences, and modifications.GAN will also help the system to deliver a set of new design mock-ups every time eliminating the current problem of a predefined number of templates.
Teaching Design and Implementation of Design Mode in the Course of Java Programming in Higher Vocational Colleges

Abstract Java programming is one of the important courses for computer majors such as software technology in higher vocational colleges. The course has strong logic and abstraction, and is rich in content and practical. When studying this course, students should not only master the Java language and object-oriented programming ideas and methods, and cultivate programming habits, but also learn to use design patterns to efficiently solve real-world problems. In order to achieve the expected teaching goals in the limited class hours, universities must carry out teaching design work. This article will put forward some views on how to optimize the software design model teaching design and teaching activities based on the analysis of related concepts and teaching status.
Sparse to Dense and Back Again: Image Search on Lucene

The ImageNet challenge has produced a number of pre-trained Deep Learning models that have surpassed human performance for image classification. These models are used to generate semantically expressive vector representations from images in the form of dense vectors. Because these vectors have been shown to retain so much of the image semantics, they are good candidates for use in Image Search.The Lucene inverted index architecture is optimized for searching against a sparse, high dimensional vector space, commonly seen in text corpora. Since its release in 1999, countless person-hours of effort have gone into making Lucene the most powerful and usable open source platform for text search in the world. It would, therefore, be desirable to leverage the Lucene platform for image search as well. However, Lucene was not designed to work well with dense, low-dimensional vectors from images.This work explores some Approximate Nearest Neighbor (ANN) techniques by which image vectors can be projected back into a sparse, high dimensional space without significant loss of information, thus making it possible to use Lucene (and Lucene derivative platforms such as Solr or Elasticsearch) for Image Search. It also presents results of some experiments using Solr and a medium sized image corpus.
Initial Centroid Determination Using Simulated Annealing Algorithm

Initial randomly generated centroids are commonly used in k-Means clustering method. Random initial centroids k-Means to be trapped in optimum local solution which results in sub-optimal cluster quality. This study examines Simulated Annealing algorithm in determining initial centroids on k-Means. Each k-Means clustering will be tested on result of reduction and without dimension reduction. Based on the results evaluation of k-Means clustering results with initial centroid Simulated Annealing algorithm improve quality cluster with percentage change value 21.2% in the high dimensional data and 25.1% in the dimension reduction data, this shows that initial centroid calculated Simulated Annealing algorithm is able to obtain the best cluster with significant results.
THE URGENCY OF IMPROVING THE METHODS OF DEVELOPING THE SKILLS OF INDEPENDENT LEARNING OF FUTURE TEACHERS (ON THE EXAMPLE OF INFORMATION TECHNOLOGY IN EDUCATION)

The basis of a modern education system is a quality and high-tech environment. Its creation and development is technically complex, but such an environment serves to improve the education system, the introduction of information and communication technologies in the educational process. The article also considers that the widespread introduction of modern information and communication technologies in education will lead to the informatization of science, intellectualization of educational activities, deepening integration processes, improving the infrastructure of the education system and its management mechanisms. Effective organization of pedagogical educational processes on the basis of modern information technologies allows the team creating distance learning courses and electronic literature to unite teachers, computer programmers, and relevant specialists, improve the distribution of tasks among teachers, improve the organization of the educational process and monitor the effectiveness of pedagogical activities. The introduction of modern information technologies in the educational process contributes to the deepening of the field of science through the renewal and deepening of professional knowledge and skills of students, modeling of studied events and processes, the expansion of independent activities of students through a variety of educational activities. , individualization and differentiation of the teaching process based on the introduction of interactive communication opportunities, mastering the strategy of the student's learning materials using the capabilities of artificial intelligence systems, the formation of information culture in him as a member of the information society; The presentation of events through computer technology plays an important role in increasing the interest and activity of students in the basics of science.