Reviewerly/exHarmony huggingface dataset:
Citation Practices in the Introduction and Discussion Sections of Indonesian Writers’ Research Articles

RINGKASAN To build a research environment, undergraduate students are now demanded to produce research article (RA) as one of requirements to graduate. Among many aspects to create persuasive RA, there is citation. However, it is widely acknowledged that in the process of writing RA, students rarely give attention to the citation. In fact, the use of citations will affect the persuasiveness of the RA itself. Therefore, this study is aimed to find out the use of citation observed from the types, the functions, and the reporting verbs in the RAs written by Indonesian EFL students. This study was a corpus based approach. The corpus consisted of 34 research articles written by English department students of Universitas Negeri Malang. The citations in the introduction and discussion sections were taken as the data. Later on, the data were analyzed manually and using software called MorphAdorner and AntConc. In results, the type was dominated with integral verb in both introduction and discussion sections while the occurrence of integral naming and non-integral citation were acknowledged differently in each section. Regarding the function, the introduction section was dominated with citation as support to the writer’s claim while the discussion section was dominated with citation as a comparison to sources with similar findings. For the reporting verbs (RVs), there were 47 RVs found in total. Either introduction or discussion section was dominated with the use of state/stated which was employed in different citation functions. Writers’ cultural and discipline background, writers’ position, insufficient knowledge about citation, evaluative vocabulary and the study area they investigate are the reasons which I strongly believe affect the writers in this trend of citing. Therefore, it is suggested that students are socialized into English discourse and academic writing practices which include citation practices in the curriculum. Kata Kunci : Research Articles; Citation Practices; Citation Types; Citation Functions; Reporting Verbs; EFL Students 1 1 1 1 MicrosoftInternetExplorer4 0 2 DocumentNotSpecified 7.8 磅 Normal 0
Approximating Complex Arithmetic Circuits with Guaranteed Worst-Case Relative Error

We present a novel method allowing one to approximate complex arithmetic circuits with formal guarantees on the worst-case relative error, abbreviated as WCRE. WCRE represents an important error metric relevant in many applications including, e.g., approximation of neural network HW architectures. The method integrates SAT-based error evaluation of approximate circuits into a verifiability-driven search algorithm based on Cartesian genetic programming. We implement the method in our framework ADAC that provides various techniques for automated design of arithmetic circuits. Our experimental evaluation shows that, in many cases, the method offers a superior scalability and allows us to construct, within a few hours, high-quality approximations (providing trade-offs between the WCRE and size) for circuits with up to 32-bit operands. As such, it significantly improves the capabilities of ADAC.
Object Detection and Recognition of Swap-Bodies using Camera mounted on a Vehicle.

Object detection and identification is a challenging area of computer vision and a fundamental requirement for autonomous cars. This project aims to jointly perform object detection of a swap-body and to find the type of swap-body by reading an ILU code using an efficient optical character recognition (OCR) method. Recent research activities have drastically improved deep learning techniques which proves to enhance the field of computer vision. Collecting enough images for training the model is a critical step towards achieving good results. The data for training were collected from different locations with maximum possible variations and the details are explained. In addition, data augmentation methods applied for training has proved to be effective in improving the performance of the trained model. Training the model achieved good results and the test results are also provided. The final model was tested with images and videos. Finally, this paper also draws attention to some of the major challenges faced during various stages of the project and the possible solutions applied.
Then and now: Contrasts in the scope of information retrieval

It’s an honour to feature Stella Dextre Clarke in this issue. She is a past winner of UKeiG’s prestigious Tony Kent Strix Award, Vice Chair of the UK branch of the International Society for Knowledge Organization and presented at last year’s Tony Kent Strix Memorial Lecture at the Geological Society in London. For those of you who couldn’t attend the event, she has written an extensive feature that traces the history of the award winners going back to 1998, articulating how their research and achievements reflect the scope and evolution of information retrieval through the years.&#x0D; Keywords: Information Retrieval, Search, Awards, Tony Kent Strix, Knowledge Organisation
Cloud-Based Technology for Small and Medium Scale Enterprises : A Decision-making Paradigm using IPA, AHP and Fuzzy-AHP Techniques

Small and medium scale enterprises (SMEs) are the backbone of the world economy. In today's challenging and dynamic business environment, popularly referred to as VUCA short for volatility, uncertainty, complexity and ambiguity, SMEs need to continually adapt and adopt technological solutions to stay competitive. Cloud computing is a disruptive information and communication technology (ICT) tool, which can be leveraged by SMEs for this purpose. However widespread adoption of cloud computing in SMEs is elusive. In this paper, we analyse the attributes that influence the adoption of cloud computing in SMEs using techniques like importance performance analysis (IPA), analytic hierarchy process (AHP) and fuzzy-AHP. IPA technique is used to identify the areas of improvement for service providers as also improve their efficiency. AHP technique has been used to rank different attributes of the technology in the order of preference from an SME's perspective. Both results are studied conjointly thereby re-iterating the importance of certain attributes of the technology so as to help managers devise strategies to increase the adoption of cloud-based technologies.
UKeiG: Committed to Continuing Professional Development

UKeiG’s professional development programme continues to be a huge success attracting delegates from all sectors and disciplines of the library and information profession. In this issue we share delegate feedback on Ned Potter’s “Better social media for libraries” and the practical ideas and applications that colleagues took back to the workplace.&#x0D; Keywords: CPD, Professional Development, Social Media
Flow ball-assisted training : immediate effects on vocal fold contacting

Background: The flow ball is a device that creates a static backpressure in the vocal tract while providing real-time visual feedback of airflow. A ball height of 0 to 10 cm corresponds to airflows ...
LibGuides: Continuity of Library Services: About the Library

A guide on how the library can help you with online teaching and learning in Spring 2020. Please see ut.edu homepage for COVID-19 updates
What we talk about when we talk about beautiful data visualizations

‘Beautiful’ is an adjective often used in descriptions of well-designed data visualizations. How the concept is used, however, reveals that it is applied to characterize a variety of qualities. Going beyond mere descriptions, the use of the concept also lays bare a certain ambivalence among scholars and practitioners towards how beauty matters, and which means it serves in data visualization. Interrogating ‘beautiful’ as a characterizing word, combined with a study of cases of ‘best practice’ used as examples of beautiful visualizations in various discourses, this chapter presents an analysis of what is regarded as beautiful within the field of data visualization design. This, in turn, can inform the understanding of what beauty means in visualizing data, in the purpose of facilitating the viewer’s comprehension and engagement.
LibGuides: Continuity of Library Services: Updates and FAQ

A guide on how the library can help you with online teaching and learning in Spring 2020. Please see ut.edu homepage for COVID-19 updates
The Doll Store Online Shop Application

In the current era, a system in a business is really needed. For example in a store, an application system or website will be very helpful in the process of promotion and dissemination of information to the public. Managing and processing data manually is vulnerable to weaknesses, such as errors and delays in sales, recording customer data, recording ordering data and storing data manually will be difficult when the data is needed. This condition is also experienced by Nufus Doll Store, therefore E-commerce is a new system in the world of business that uses online services. Many items can be offered through e-commerce such as selling dolls online using the web. By this system, customers do not have to bother coming to the store and can order it at any time without a time limit. Some applications that are joined together into a package are sometimes referred to as a package or application suite (application suite). E-Commerce Application at Nufus Doll Store is designed using macromedia dreamweaver, php, mysql, xampp and photoshop. The design of this website online is expected to attract customer interest and can be an effective sales medium.
ANALYSIS OF OVO APPLICATION SENTIMENT USING LEXICON BASED METHOD AND K-NEAREST NEIGHBOR

Money that has a function as a measuring tool, medium of exchange, and payment tools is transformed according to the development of the digital era with the issuance of electronic money. Ovo is an electronic money application in Indonesia. The public can provide a review of the service ovo application on the google play store. Further, the company can see how the responses from the user regarding the product as an evaluation of application performance so that improvements can be made. This requires a system for analyzing reviews by applying sentiment analysis use the R language. The initial stage of sentiment analysis is pre-processing which consists of case folding, cleansing, stopword, slang-word, and stemming. The data classification process is divided into two classes, namely positive and negative classes using the lexicon-based method, the data that has been carried out is then divided into training data and test data that will be used in the training and testing process using the Confusion Matrix. The results of the accuracy of the system using the k-nearest neighbor algorithm of 93.84%. with a positive preposition of 96,29%, negative preposition of 68,75%, positive recall of 96,18%, negative recall of 73,33% and error system of 6,16%.
Evaluating Adversarial Robustness for Deep Neural Network Interpretability using fMRI Decoding

While deep neural networks (DNNs) are being increasingly used to make predictions from high-dimensional, complex data, they are widely seen as uninterpretable black boxes, since it can be difficult to discover what input information is used to make predictions. This ability is particularly important for applications in cognitive neuroscience and neuroinformatics. A saliency map is a common approach for producing interpretable visualizations of the relative importance of input features for a prediction. However, many methods for creating these maps fail due to focusing too much on the input or being extremely sensitive to small input noise. It is also challenging to quantitatively evaluate how well saliency maps correspond to the truly relevant input information. In this paper, we develop two quantitative evaluation procedures for saliency methods, using the fact that the Human Connectome Project (HCP) dataset contains functional magnetic resonance imaging (fMRI) data from multiple tasks per subject to create ground truth saliency maps. We then introduce an adversarial training method that makes DNNs robust to small input noise, and demonstrate that it measurably improves interpretability.
From permutation to arithmetic entropy

A method for analyzing sequential data sets, similar to the permutation entropy one, is discussed. The characteristic features of this method are as follows: it preserves information about equal values in the embedding vectors; it is exempt of combinatorics; it delivers the same entropy value as does the permutation method, provided the embedding vectors have no equal components. In the case they do, obtained entropy is greater than the permutation one.
LibGuides: Lower Grades Citation Guides: First and Second Grade

This LibGuide is a resource for teachers of K-4. It provides collective information on citation lessons specialized by grade level.
Maneuvering Target Joint Detection and Tracking Using Multi-Frame Integration

The authors present an efficient joint detection and tracking algorithm for maneuvering target. To exploit the space-time correlation of the target among successive frames, we derive an expectation multi-frame test statistic containing a quantifiable term of target motion character by probabilistic dynamic programming. A joint filtering and smoothing estimation based on the interacting multiple model (IMM) is developed to design and calculate the state transition probability of target motion. The proposed algorithm promises a satisfying detection performance in that the designed state transition probability can steer the test statistic to be integrated along the real target trajectory more likely. Besides, better tracking performance can be obtained since the outputs of the proposed algorithm are filtered or even smoothed trajectories of the detected targets. Simulation results illustrate the performance of the proposed algorithm.
Feature Selection Optimization Using Genetic Algorithm for Spambot Detection in an OSN

The process of Feature Selection (FS) in Machine Learning (ML) techniques is significant in reference to any the ML based prediction model. Use of significant features for model building elevates the overall performance of the ML model manifolds. In this paper, we have found out and analyzed the best feature sets in the available datasets to build two models for spambot detection in Online Social Networks (OSNs) with a specific reference to Twitter. We have used the Genetic Algorithm (GA) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) techniques for Feature Selection. To compare the results of both FS techniques, we have again built two models using Random Forest (RF) and K-Nearest Neighbor (KNN) algorithms. This study also includes the experimentation to study the effects of biasing in genuine accounts with spambot accounts. The results show that the performance of classifiers is better for Genetic Algorithm based optimized feature set. The accuracy of the models has been found to be better for the biasing cases within the ranges of 0% to 30% spambot accounts.
LibGuides: Gardening and Horticulture Open Access Resources: General How-to Guides and Resources

This guide provides many open access (free to use) resources regarding agriculture, horticulture, and other topics usually covered within the University Extension programs.
STUDENTS’ ATTITUDES AND PERCEPTIONS ON THE USE OF DUOLINGO AS A LANGUAGE LEARNING APPLICATION

This research aimed at finding out the students’ attitudes and perceptions toward the learning of English language through Duolingo application. This mixed method study was carried out by distributing questionnaire to 60 participants and interviewing 10 participants who were chosen from academic year 2014, 2015, and 2016. The participants must be students who took the English language subjects as their academic courses and also used the Duolingo to learn English language. The data of this study were collected through closed-ended questionnaire using Likert-scale method consisted 21 questions that were divided into 2 categories; attitudes with 7 questions and perception with 14 questions. The results of the study showed that the mean score of attitudes was 4.1 and the perceptions was 4.1 both the attitudes and the perceptions of the respondents of Syiah Kuala University students toward the use of the Duolingo application as a language learning tool is positive. In conclusion, Duolingo application is considered as a comfortable application to use and a common application used by university students as a learning language tool especially English.
Exploring the Formalization of Brain Cognition in the Age of Artificial Intelligence

In the contemporary society where the Internet has almost reached its peak, artificial intelligence has gradually become an important proposition for the development of science and technology. From the traditional perspective, people’s cognition of the brain is limited to the human point of view, but in the era of artificial intelligence, due to the large number of robots, people will deal with artificial intelligence in a wide range of daily life. In this context, it is clear that the current human cognition of the brain will gradually be eliminated and replaced with the breakthrough of artificial intelligence technology. The problem of brain cognition was widely recognized and heatedly discussed by scientists as early as 1956. In the modern era, with the maturity of science and technology, the problem of the formalization of brain cognition will also be redefined with the advent of the artificial intelligence era. This article starts the relevant discussion and hopes to contribute to the in-depth discussion of the problem of formal cognition of brain cognition in China.
Naive bayes for web penetration behavior classification based on word segmentation improvement

After using naive bayes algorithm to mark, train and classify the web log, it is not good to find out the web penetration behavior. In this paper, a parametric word segmentation algorithm suitable for web penetration behavior classification is proposed by analyzing the characteristics of URL parameters and perfecting the operation process of naive bayes. It is proved that this algorithm can effectively reflects the behavior features and greatly improve the classification performance of naive bayes by application and contrast.
ADEQUATE IMPROVEMENT FOR SPATIAL VIDEO SCALING FOR VIDEO SURVEILLANCE APPLICATIONS

Spatial Video Scaling (SVS) is a global standard method for video Surveillance Applications. The proposed Spatial Video Scaling (SVS) is designed to estimate the objects in the occupied area and its interconnected vectors. By introducing this SVS framework based interconnected motion vector used to convert the Three-dimensional (3-D) space to the two-dimensional image plane (2-D) at sufficient distance. It consists of several stages of video enhancement and shows an overview of the proposed spatial video scaling (SVS) method. The proposed SVS method is suitable for applications where the accuracy of motion estimation is vital. The proposed SVS video encoding is offered in four phases. The primary phase is the pre-processing stage; in this, unnecessary background areas were removed. Then the Local motion Estimation vectors and global motion Estimation vectors are calculated for better elements detection. Then the extraction of features with Spatial Video Scaling based video enhancement and detection technique. Finally, the performance factors is calculated based on the best features that are found. Finally, the sum of the objects in the movement of the image is smoothed, and the video is compensated.
Parameterizing Human Speech Generation

In modern days synthesis of human images and videos is arguably one of the most popular topics in the Data Science community. The synthesis of human speech is less trendy but deeply bonded to the mentioned topic. Since the publication of WaveNet paper by Google researchers in 2016, the state-of-the-art approach transferred from parametric and concatenative systems to deep learning models. Most of the work on the area focuses on improving the intelligibility and naturalness of the speech. However, almost every signiﬁcant study also mentions ways to generate speech with the voices of different speakers. Usually, such an enhancement requires the model’s re-training in case of generating audio with the voice of a speaker that was not present in the training set. Additionally,studies focused on highly modular speech generation are rare. There fore there is a room left for research on ways to add new parameters for other aspects of the speech, like sentiment, prosody, and melody. In this work, we aimed to implement a competitive text-to-speech solution with the ability to specify the speaker without model re-training and explore possibilities for adding emotions to the generated speech. Our approach generates good quality speech with the mean opinion score of 3,78 (out of 5) points and the ability to mimic speaker voice in real-time, which is a signiﬁcant improvement over the baseline that merely obtains 2,08. On top of that, we researched sentiment representation possibilities. We built an emotion classiﬁer that performs on the level of the current state of the art solutions by giving an accuracy of more than eighty percent.
THE READABILITY LEVEL OF READING PASSAGES ON ENGLISH TEXTBOOK FOR GRADE NINE IN INDONESIA

Textbook is a major resource for students in teaching and learning process of English. The basic component of textbook is text. This is in line with text-based or genre-based approach applied by the K-13 curriculum in Indonesia. However, the publication from Ministry of Education (2016) in achievement of 15 year-old Indonesian students in Programme for International Student Assessment (PISA) shows that they did not have significant improvement in reading skill. One factor assumed is the readability level of reading passages on the textbook used in teaching and learning process. It is concerned with the level of difficulty from the text to be understood by the students. This study aims to investigate how the readability level of reading passages on English textbook for grade nine in Indonesia is. The writer uses “Think Globally Act Locally (2018 revision)” which is written and published by Ministry of Education in Indonesia.  A descriptive qualitative research is employed in this study. There are three genres of reading passages in the book to be analyzed: procedure, narrative, and report text. The data was collected by documentation technique. To analyze the data, the writer used Flesch Reading Ease formula. This formula is the most widely used formula, the most tested, reliable, and the best in school text. The results of this study show that the readability level of 12 reading passages on English textbook for grade nine in Indonesia is varied. The range is from very easy to fairly difficult.
LibGuides: Virtual Book Display: Home

Explore virtual collections of books and ebooks by monthly themes curated by University librarians!