Reviewerly/exHarmony huggingface dataset:
A Verification of AprilTags for a Pharmacy Application

AprilTags are an artificial tag that provides pose estimation. Commonly, it is used to determine global coordinates of a space so that robots can determine where they are within the area. In this project, however, the AprilTags were attached to a specific object needing to be moved. The scope was to verify the robustness and functionality of the tags in order to determine the plausability of them being used for a Pharmacy application.The Pharmacy is a highly crucial part of the hospital system and the time of the Pharmacists is of the upmost importance. One of the tasks of a Pharmacist is to unload the boxes of medication from delivered orders and organise it into the dispensary. Robotic arms already exist to help with the retrieval and stocking in the dispensary. However, the process of sorting the delievered orders has not been automated and this is a timeconsuming task for a Pharmacist or Pharmacist assistant. Hence, the thought towards verifying the functionality of AprilTags was to determine whether they could be used on medication packaging to potentially automate the process of unboxing.The method undertaken to verify the tags took on a couple of stages. In each stage, an OpenMV H7 Camera was used for the detection process. This camera was attached to Haddington Dynamics’ Dexter HDI robotic arm. An AprilTag was attached to the test object and tests were run to verify the tags ability to handle various distances between the camera and tag, the size of the tag, the angle of the camera, occlusion to the tag, and lighting.The results of these tests were interesting. It appeared that there was only a limited range of distances, tag sizes, camera angles, and occlusion that could still result in a detection accuracy above 80%. The smallest tag that gave functional results was the 25mm tag. The optimal conditions for high accuracy was the camera being between 10 and 20 cm above the tag with a camera angle of 90 degrees, with controlled lighting and no more than 17% occlusion.From the results and analysis, the tags are a possibility for automating the unboxing of medication packages. Further testing needs to be conducted with the pose estimation to determine its accuracy. Other detection methods may need to be used alongside the AprilTags since this project’s testing has demonstrated the limited range from where the tag can be detected.
Subject Guides: Linking to Library Resources: Troubleshooting

A guide to assist in linking to content in Stoxen Library databases within Blackboard courses
University Library: Eagle Search: Alma and Primo VE: FAQ's

This guide includes information about the new next-generation Integrated Library System called EagleSearch coming to the library on July 13, 2021.
Research on the Design of Loan Anti Fraud Cloud Platform Based on Z10 Experimental Platform

Based on the analysis of the design and implementation of the loan anti fraud system, combined with the practical experience of the mainframe development environment, this paper expounds the development and design framework of the loan anti fraud cloud platform. Under the Z10 mainframe architecture and its openstack framework, Hadoop technology, we put forward the solutions of key technical problems, such as improving loan fraud prediction speed and disbursement speed, optimizing fuzzy matching model, improving the fault tolerance of matching model, improving the effect of loan anti fraud, using star network model to establish the user network with loan fraud, etc.
The Effect of Formal, Non-formal, and Informal Language Learning Environment towards English Skill Achievement on Students’ Standardized Tests (A Comparative Study of Acehnese Alumni’s Perception of Kampung Inggris Pare)

This study examines the impact of formal, non-formal, and informal language learning environment towards English skill achievement on students’ standardized tests. The variables used in this study are formal, non-formal and informal learning. This study applied purposive sampling which the population of this study were the alumni of Kampung Inggris Pare whose TOEFL and IELTS score. The sample were 16 respondents on High Intermediate level and 14 respondents on advance level of learning. I used questionnaire and in-depth interview as the primary technique of data collection. Thus, the instruments used are Google Form for questionnaire and interview guide. The findings of the analyses show that each learning environment give postive impact towards English skill achievement. But non-formal learning give the most influenced effect towards the alumni English skill achievement on standardized test. The benefits from the students experience in Kampung Inggris Pare as a non-formal learning are: (a) English skill improvement; (b) Good time management; (c) New relations; and (d) Practicing English skill.
Neural Abstractive Unsupervised Summarization of Online News Discussions.

Summarization has usually relied on gold standard summaries to train extractive or abstractive models. Social media brings a hurdle to summarization techniques since it requires addressing a multi-document multi-author approach. We address this challenging task by introducing a novel method that generates abstractive summaries of online news discussions. Our method extends a BERT-based architecture, including an attention encoding that fed comments' likes during the training stage. To train our model, we define a task which consists of reconstructing high impact comments based on popularity (likes). Accordingly, our model learns to summarize online discussions based on their most relevant comments. Our novel approach provides a summary that represents the most relevant aspects of a news item that users comment on, incorporating the social context as a source of information to summarize texts in online social networks. Our model is evaluated using ROUGE scores between the generated summary and each comment on the thread. Our model, including the social attention encoding, significantly outperforms both extractive and abstractive summarization methods based on such evaluation.
Handwrite Recognition using Convolutional Neural NetworK

Handwriting is a technique of speaking and keeping statistics in normal existence even after the advent of new technologies. A handwritten person is generated with the aid of processing a series of strokes.[3] A shape or a shape-primarily based characterization of the stroke is used wherein a stroke is taken into consideration to be a string of functions of the shape. An input stroke is compared with   strokes gift in the database using a flexible string matching technique.[3] A entire person is identified by way of analyzing all of the stroke additives. The handwritten textual content reputation machine can be  utilized in diverse applications[3]..
LibGuides: HACC User Support: Student Log In Instructions

Tech support provides effective and timely technical support for all HACC students, faculty, and staff.
Enrollment-Less Training for Personalized Voice Activity Detection

We present a novel personalized voice activity detection (PVAD) learning method that does not require enrollment data during training. PVAD is a task to detect the speech segments of a specific target speaker at the frame level using enrollment speech of the target speaker. Since PVAD must learn speakers' speech variations to clarify the boundary between speakers, studies on PVAD used large-scale datasets that contain many utterances for each speaker. However, the datasets to train a PVAD model are often limited because substantial cost is needed to prepare such a dataset. In addition, we cannot utilize the datasets used to train the standard VAD because they often lack speaker labels. To solve these problems, our key idea is to use one utterance as both a kind of enrollment speech and an input to the PVAD during training, which enables PVAD training without enrollment speech. In our proposed method, called enrollment-less training, we augment one utterance so as to create variability between the input and the enrollment speech while keeping the speaker identity, which avoids the mismatch between training and inference. Our experimental results demonstrate the efficacy of the method.
The Effect of the TSD Mindful Self Coaching Education Program on the Mindfulness State of Adults

The purpose of this study is to investigate the effect of the TSD (Thinking, Saying, Doing) Mindful Self Coaching Education Program on the mindfulness state of adults. 28 adults in Jeju, South Korea were the sample of this study. The adults were assigned into 13 experimental groups and 15 control groups. 12 educational sessions of the program were conducted once a week for five hours from March 20th to June 5th, 2019 for the experimental group. The mindfulness state was measured by 24 questions, and the difference between the responses of the two groups was tested by paired t-test. The main results are as follows. First, the experimental group showed significant differences in 19 out of 24 questions. Second, the experimental group showed significant differences in positive emotions, attention, and self-control among the five sub-categories of the mindfulness state. Third, the experimental and control groups showed significant differences in all four sub-categories except for attention concentrations among the five sub-categories of the mindfulness state. The results of the study suggest the meaningful effectiveness of the TSD Mindful Coaching Program applying both coaching and mindfulness in an educational program. Also, future studies to ensure and enhance the effects are necessary.
IMPROVING THE STUDENTS’ VOCABULARY MASTERY THROUGH THE USE OF KIM (KEYWORD, INFORMATION, AND MEMORY CLUE) STRATEGY AT THE EIGHT GRADE STUDENTS OF SMP DWIJENDRA DENPASAR IN THE ACADEMIC YEAR 2019/2020

This study aims to improve the vocabulary of VIII-G class students of SMP Dwijendra Denpasar through the use of KIM strategy in the academic year 2019/2020. This research was a classroom action research. This research used two cycles, where each cycle consists of four stages, namely planning, implementing, observing, and reflecting. The subjects of this study was the students of VIII G class SMP Dwijendra Denpasar. The instruments used in this research were tests, observation sheet, interview guide, and lesson plans. In collecting the data, the researcher used observation and interview methods. The result of this research showed that there was an improvement in the students’ vocabularies. It could be seen from the students’ pre – test and post – test scores. The mean score of the students pre – test in this research was 54.5, while the mean score of post - test 1 was 73.7 and it was improve in the post-test II became 85. The students’ observation result by using KIM strategy was very satisfied because the students could follow each instruction that was given by the teacher. The result of interviewing the students showed that they could motivated and improved their vocabularies’ in English subject by using KIM strategy. It could be concluded that the use of KIM strategy could improve the students’ vocabularies.
Differences Between Major Depression Disorder and Controls in the Recognition of Facial Expression: Evidence From Event-Related α Oscillations

Traditional routing in the Internet is best-effort which makes it challenging for video streaming since no throughput, jitter, delay or loss rate is guaranteed. As different paths have different characteristics, path differentiation such as multipath routing is a promising technique to be used for meeting QoS requirements of media-intensive applications. Using overlay networks different paths are offered which enable more flexibility in QoS and congestion control while the reliability of the connections is enhanced.Software Defined Networking (SDN) is known to be a promising solution to the problems of routing as it provides fine-grained control over packet handling. Relying on SDN, we propose an adaptive multipath provisioning scheme ensuring maximal bandwidth and resiliency of media transfer in overlay networks. The scheme is a time slot-based approach which dynamically finds multipaths. It relies on both active probing and traffic prediction.The experimental results confirm that a more accurate prediction together with more frequent probing lead to fewer number of path re-calculation and also indicate that the proposed scheme enhances the reliability of connections while a more balanced load is achieved in the network compared to the shortest path-based scheme.
A Diachronic Study on the Content Validity of the 2016-2019 TEM-8 Section A Based on Corpus

TEM-8 is an important high-risk examination for all senior English majors. By exploring the content validity of the section A part of the 2016-2019 TEM-8 reading, this paper aims to provide reference for the future direction of TEM-8 reading, and also to help students understand some of the contents of the TEM-8 reading examination in recent years to help them prepare for the exam. This paper mainly compares with the requirements of the TEM-8 test syllabus to explore the content validity of the reading article in the theme, genre, vocabulary density and length of the article in 2016-2019. It is concluded that in terms of theme and genre, the articles in recent years basically meet the requirements of the syllabus of the TEM-8 examination, but in the genre, the proportion of argumentative papers and narratives is on the high side, which should be deleted. Besides, this paper builds a corpus of reading articles in recent years, and uses LancsBox corpus retrieval software to make statistics on lexical type, token and type-token ratio. In terms of lexical density, the difficulty of articles in recent years basically meets the requirements of the syllabus of the TEM-8 examination, but the distribution of lexical density in 2017 is slightly unreasonable, so we should pay attention to avoid this phenomenon in the future. In terms of the length of the article, in addition to the uneven distribution of the text words in 2017, the length of the articles in this four years is reasonable, which meets the requirements of the total number of words in the syllabus of the TEM-8 examination and the number of words read per minute.
A computational model to predict the visibility of alpha-blended images

Alpha blending is often used as a means of semi-transparently rendering an image over another background image. However, this blending technique has a problem in that the visibility of the blended foreground image depends on the background image. In particular, if the background contains a high-contrast texture, the visibility of the foreground image is greatly impaired by contrast masking. Therefore, it would be desirable to be able to adaptively adjust the blending parameter (alpha) to compensate for the masking effect. For this purpose, a model that can predict the visibility of alpha-blended images is necessary. In this study, we tested the effectiveness of early spatial vision models that can explain contrast masking as candidates for the prediction model. As experimental stimuli, we used alpha-blended images generated from various types of images such as textures, natural scenes, and artworks. The visibility matching task was used to measure visibility, where the participants matched the visibility of the foreground patch in the test image to that of the reference by adjusting the alpha value of the test image. There were two types of conditions: matching between images with the same foreground patches and matching between images with different foreground patches. 2000 different combinations of image patches were used for each condition. As a result, we found that the conventional spatial vision model could not predict the matching data well. To explain the data, we propose a content-adaptive feature aggregation mechanism which adaptively weights image features, such as spatial frequency and color information, based on the original appearance of the foreground image when aggregating those features into a single visibility level. We will show that this adaptive weighting mechanism is important for accurately predicting the visibility of arbitrary images through ablation studies.
Language Function of Selected Cosmetics Advertisement in Online Media

The research is a descriptive qualitative approach to describe the types of language function and how to use it. The researcher produces descriptive data in the form of complex descriptions in this approach, examines words by words, and conducted that natural situation study, then drawing the conclusion is the last step required. The research data are from twelve advertisements, which has a relation with the function of the language. The findings showed that there were five types of language function. The most dominant language function used by the cosmetics brands advertisement is personal function. The second-place used by the advertisement is representational function. The third most are instrumental function. The fourth is the imaginative function. The last is the interactional function. Meanwhile, heuristic and regulatory functions are not found in cosmetic advertisements in Online Media.
UMP, Dapur Infaq collaborate on digital infrastructure development for community benefit

KUANTAN, 6 April 2021 - Universiti Malaysia Pahang (UMP) and Pertubuhan Dapur Infaq Ummah Kuantan (Dapur Infaq) for the first time collaborated in the development of a digital application that will benefit the local community.
Text Summarization with Sentimental Analysis

In today’s world, Modern organizations deal with terabytes of text, such as email, that often plays a significant role in their day to day operations. The user has to face a task of identifying useful information from these data which is difficult and it requires some amount of time. One possible means is to use text summarization. Text summarization is the process of identifying the most valued/meaningful information in a document and compressing that information into a shorter version preserving its overall meaning. Sentiment analysis is about determining the text given by the user whether it is Positive, Negative or Neutral. We used Gensim Algorithm for generating text summary. This algorithm automatically summarizes the given text, by extracting one or more important sentences from the text. This project is about text summarization which includes sentiment analysis. In UI, a text box will be displayed, which is used to take the input text from the user which need to be summarize. Then it will pre-process the text and show the summarized content. It will be taking input as URL of an article and it is going to provide Title, Author, Publication Date, Sentimental analysis, Keywords, URL of an Article.
Impact Of Achievement In Mathematics At Senior Secondary On The Academic Performance Of A Student At Graduation Level, Non-Mathematics Programs

Education is the process of receiving or giving systematic instructions especially at a school, college or university level. The aim of education is to bring out the best from the individual. Also, education is required for all around development of the student to make him successful in his life. The objective of the education is to transform a student into productive citizen who can use his knowledge, talent and skills to sustain himself and help others while pushing the human race forwarded in the area of equality, equity and harmony. Knowledge is a combination of facts, information and skills through experience or education i.e. the theoretical and practical understanding of a subject. Academic performance or academic achievement is the extent to which a student or institution has to attain the short- or long-term educational goals. Education goals are to make a student passionate lifelong learner, ready to take risks, able to solve problems, think critically, work independently, creative, careful and make him to think to give back to society. In this paper we analyse the academic performance of students studying Non-Mathematics based programs at Graduation level with special reference to achievement in Mathematics at Senior Secondary level, as compared to the students who have not studied Mathematics at Senior Secondary level.
Correlation between Students’ Reading Habit and Writing Skill in Opinion Essay

The purpose of this study was to describe the correlation between students’ reading habit and their writing skill in opinion essay. The population of this study was the fourth semester students of English Education Department at class E.01 inUniversitas Maritim Raja Ali Haji, Tanjungpinang. The sample in this study was taken using cluster random sampling technique that was class E.01 with 29 students. Correlatioan method was applied in this study. There were two instruments in collecting the data; the first instrument was to measure students’ reading habit, in this study, questionnire were administered to the samples. The second instrument was to measure students’ writing skill in opinion essay, in this study, an instruction asking the students to write opinion essay were given to the students. The data collected then were calculated by using Minitab 17 and SPSS 25 version. Based on the analysis of the research, it can be seen that the results of the correlation using SPSS 25 are 0.849, it i s higher than r table value in the significance of 5% (rcalculation = 0.849 > rtable (5%) =0.367), it can be conclude that H0 was rejected and Ha was accepted. Moreover, based on the normality test the pvalue is 0.100 and it is bigger than 5%. It means that the data is normally distributed. From the results of several tests, it can be concluded that there was a correlation between students’ reading habits and writing skill in opinion essay atthe 4thsemester students of English Education Department at class E.01 inUniversitas Maritim Raja Ali Haji, Tanjungpinang. Therefore, it can be concluded that the more students read, the better their writing skill.
Study of Rooftop Hybrid Solar Wind Renewable Energy Applications for East Coast of Peninsular Malaysia

The project is focused into improve the power generation of rooftop solar wind turbine by increasing the speed of prevailing wind flow through wind turbine.
Overview of MeOffendEs at IberLEF 2021: Offensive Language Detection in Spanish Variants

We would like to thank CONACyT for partially supporting this work under grants CB-2015-01-257383 and the Thematic Networks program (Language Technologies Thematic Network). Hugo Jair Escalante is supported by CONACyT under project grant CONACYT CB-S-26314. This work is also partially supported by the grant P20 00956 (PAIDI 2020) from Andalusian Regional Government, a grant from European Regional Development Fund (FEDER), the LIVING-LANG project [RTI2018-094653-B-C21], and the Ministry of Science, Innovation and Universities (scholarship [FPI-PRE2019-089310]) from the Spanish Government.
Analisa dan Implementasi Controller untuk Device PTMP Menggunakan Cloud UISP pada PT. Bandar Abadi

A wireless network is a network that uses electromagnetic waves as the transmission medium. Wireless networks have advantages over wired transmission media such as ease of installation, expansion, and lower costs. In wireless networks there are several topologies that are commonly used, namely Point to Point and Point to Multipoint. This topology uses at least 2 devices to transmit data. This in turn makes it difficult to manage devices because of the large number of devices needed. To overcome this issue, the author uses a Controller, namely Cloud UISP to manage all existing PTMP devices. With this device, it enables IT to detect, register and configure PTMP devices all in one place. In designing this network the author uses Network Development Life Cycle (NDLC) method. The results of this implementation make it easier for IT to manage all Ubiquiti PTMP devices in the company.
Proof Sheet of Moon Rock Press Conference

Research School of Earth Sciences, Physical Sciences - Moon Rocks Analysis - Dr. B. W. Chappell, Mr. M. I. Vernon, Dr. W. Compston, Mrs. A. Brown, Prof. A. E. Ringwood, Dr. J. E. Lovering, Dr. S. R. Taylor, Dr. W. Compston, Mr. J. Pennington