Reviewerly/exHarmony huggingface dataset:
SASCNN: A Systolic Array Simulator for CNN

Convolution Neural Networks (CNN) are used in many applications ranging from real-time object detection to robot-motion planning. CNNs are implemented on high-performance systems like multi-core CPU and GPU, these are of high power in nature and thus cannot be deployed in edge devices due to their limited battery power. The edge device has to provide real-time performance along with being low power, this prompts for an exploration of novel architectures catered towards the processing of CNNs. The recent works towards this goal have been the development of CNN accelerators using systolic array spatial architectures. The row-column stationary data-flow approach maximizes the reuse of weights, input feature maps and output feature maps across the array. Different applications require different performance, area and energy needs, and this makes it imperative to quickly prototype the architectural ideas and perform design space exploration. The challenging part is the non-trivial interactions between different architectural design parameters, as they play an important part in the complex design decisions. Hence, a hardware simulator to accelerate CNN is designed in this work. It is based on systolic array and uses row-column stationary data-flow with a near memory computing approach. The simulator supports different numerical precision such as 16-bit and 8-bit floating-point along with numerous design parameters such as the size of the systolic array, latency of MAC operation, PE local memory size, PE local memory latency and external memory latency. The functionality of the proposed design is verified on AlexNet. The Destiny memory modelling tool, along with energy and area estimation model, is used to perform a system study to investigate the trade-offs between different architectural design parameters.
CELI 3 (B2) Sample Test Teacher’s Feedback

CELI 3 (B2) Sample Test CELI (Certificate of knowledge of the Italian Language) The Examination is assessed directly by the University of Perugia. The University will inform if the examination has been passed or failed. If a section of the examination has been failed, you are given the opportunity to retake that section within a year. Registrations need to be received two months prior to the exam date. Please complete this sample test and email it back to us at info@speakitalynyc.com to find out your score.
LibGuides: Department of Accounting & Finance: Style Guide

This guide provides print and online resources to support faculty and students in the department of accounting to meet the teaching, learning, and research needs
ENGLISH TEACHER’S PERCEPTION TOWARDS THE USE OF ROLE-PLAY IN TEACHING SPEAKING

Speaking is a productive skill that allows people to communicate by using a language. A lot of students have difficulties in speaking English. One of the best ways of learning speaking is by using role-play in which this method can make the learning process more interesting and make students can practice in different social contexts and roles. Therefore, this study aims to find English teachers' perception towards the use of role-playing in teaching speaking at SMPN 24 o Palembang. The informants of this study were all the English teachers of SMPN 24 Palembang. The data were collected by using observation, interview and documentation. The results showed that not all teachers knew and applied roleplay in teaching speaking.Keywords: English teacher, perception, role-play, teaching speaking
Improving the Reading Comprehension Ability by Applying the Cooperative Integrated Reading and Composition (CIRC)

Reading comprehension is a very important skill to support the student learning process and is very useful when they are working on test questions. Apart from the importance of understanding reading skills, there are still many students who have not been able to master this skill well. This research is classroom action research (CAR) by applying the Cooperative Integrated Reading and Composition (CIRC) learning model because it has been proven to improve the students' reading comprehension skills. This study was carried out with 2 cycles to find out how the implementation and evaluation of learning to read comprehension of the CIRC type cooperative model that can improve comprehension reading skills in class VII A students of SMP Negeri 1 Singkawang. The results of this study were analyzed by quantitative and qualitative analysis. The results of this study cannot be generalized to other subjects. The research results suggest further implementation of the CIRC model into different subjects and problems.
TML Project Planning Approach and Closing Thoughts

This book has introduced all aspects of TML, which applies AutoML to data streams integrated with Apache Kafka that allows developers to build TML solutions that are scalable, frictionless, and elastic in the cloud. The importance of frictionless and elasticity is a unique characteristic of TML solutions and a differentiating factor with conventional machine learning (CML). We also formally defined TML along with the five features of TML solutions such as data fluidity, joining data streams, standardization of data streams to JSON, integration of data streams with AutoML, and the ability to create TML solutions with low code. TML is based on the belief that fast data requires fast machine learning for fast decision-making. This does not mean that all fast data needs TML, because if there is no need to make fast decisions, then TML makes little sense.
ANALISIS GAYA BAHASA PADA LIRIK LAGU DALAM ALBUM MANTRA-MANTRA KARYA KUNTO AJI DAN HUBUNGANNYA DENGAN PEMBELAJARAN BAHASA INDONESIA SMA

ABSTRACTAnalysis of Language Style on Song Lyrics in the Mantra Albums by Kunto Aji and Their Relationship with Indonesian Language Learning in Senior High School. Thesis of Indonesian Language and Literature Education Study Program. Faculty of Languages and Arts Education IKIP PGRI Bojonegoro. Advisor (I) Abdul Ghoni Asror, M.Pd., (II) Moh. Fuadul Matin, S.S., M.Pd. The purpose of this study is to describe the style of language and the meaning contained in the song lyrics in the spell album by Kunto Aji and their relationship with Indonesian Senior high school learning. This research is a qualitative research using a qualitative descriptive approach. The research data collection technique is data analysis that is identifying data, data classification, data analysis, data description and data interpretation. The results of this study indicate that the style of language or speech in the song lyrics in the album spells by Kunto Aji there are 19 data. As for that (1) comparative language styles amounting to 6 data, including (a) personification of 2 data, hyperbole 4 data, (2) satire language style totaling 1 data, covering (a) irony 1 data, (3) affirmative language style totaling 9 data, including (a) repetition of 6 data, (b) anaphoric 2 data, (c) epiphora 1 data, (4) conflicting language style totaling 3 data, including (a) paradox 3 data. The relationship between this study and Indonesian Language Learning is that there is a SK (Competency Standard) in grade X semester II about student creativity in studying styles.Keywords: language style, learning, song lyrics, spells, kunto aji
ARALD: Arabic Annotation Using Linked Data

The evolution of the traditional Web into the semantic Web makes the machine a first-class citizen on the Web and increases the discovery and accessibility of unstructured Web-based data. This development makes it possible to use Linked Data technology as the background knowledge base for unstructured data, especially texts, now available in massive quantities on the Web. Given any text, the main challenge is determining DBpedia's most relevant information with minimal effort and time. Although, DBpedia annotation tools, such as DBpedia spotlight, mainly targeted English and Latin DBpedia versions. The current situation of the Arabic language is less bright; the Web content of the Arabic language does not reflect the importance of this language. Thus, we have developed an approach to annotate Arabic texts with Linked Open Data, particularly DBpedia. This approach uses natural language processing and machine learning techniques for interlinking Arabic text with Linked Open Data. Despite the high complexity of the independent domain knowledge base and the reduced resources in Arabic natural language processing, the evaluation results of our approach were encouraging.
Lessons from China: Understanding the Role of Mobile Applications in China’s Response to COVID-19

The COVID-19 pandemic has impacted the society and human life profoundly.Since reported in China in December, 2019, the global confirmed cases have exceeded 24 million (as of August 27, 2020 according to Worldometers.info).The students from Mass Academy of
The Impact and Potential of Using Blockchain Enabled Smart Contracts in the Supply Chain Application Area

Blockchain potential in supply chain management (SCM) has increased considerably over the last few years, both in academia and industry. However, according to the literature, few researchers have tackled the real impact of blockchain in changing businesses and creating value. This research fully delved into an analysis of the SCM function with specific focus on measuring the potential of using a blockchain-based system in terms of enhancing effectiveness, trust and transparency. The main contributions of this research aim to address the main challenges of blockchain enabled smart contracts implementation in the field of SCM through a deep qualitative research that highlights the inconsistencies and misfits that are common in that application area.
LEARNERS STUDY HABIT AND PERCEPTION ON E-LEARNING AT SELECTED UNIVERSITY, SAUDI ARABIA

Study habit of the students is very important for succeed in the education qualification,due to the pandemic situation teaching the students taken place through e-learning.Hence this to aim to assess the students habit, perception of E-learning.A descriptive study design was adopted in this study. A total of 323 students undergoing a 4 Years of Baccalaureate nursing program, Arts and science college students at the College of Applied Medical Sciences, Arts and science college at various university, Saudi Arabia was selected using convenience sampling. This study was carried out during the academic year of 2020-2021. The data were collected using a questionnaire such as the five-point Likert scale. The responses obtained were subjected to statistical analysis using SPSS software.The results indicated that the students were strongly agreed for using, electronic device like computer,internet, all are very useful in my studies during examination and also e-learning was effective in learning. When compare the results female students, arts and science students strongly agreed for the e-learning than the male, nursing students.Students familiarity in using the computer also shows that female students ,arts and science students were more familiar in using computer for their study, and also students stated computer is user friendly for their students .Regarding the perception of the e-learning shows female students ,arts and science students were stated e-learning is flexible , preferred for their education because of its encouraging for self-learning .
LibGuides: RAE - Research Administration and Engagement - Research Lifecycle & Support: Predatory Publishers

This guide provides links for services and tools for projects, writing, planning, and management as you progress through the research project from inception to publication.
Non-invasive Group Activity Identification Using Neural Networks

Human activity recognition has been a topic of discussion for long. Proper identification would lead to better automation, surveillance, and more comfortable living. Although single person activity is comparatively easier to detect and significant research have been done recently, the challenge lies in identification of group activity. Existing research for identification of group activity is either computer vision-based or wearable device-based. However, computer vision might breach privacy and heavy in computation whereas wearable devices are based on people’s will and might be discomforting as well. Therefore, in our proposed work we have used linear data, i.e., distance of the person from the sensor to predict group activity with high accuracy, at the same time it is non-invasive, and is automated. The proposed work has been conducted using customized multiple ultrasonic sensor grids on 10 individuals in a closed lab environment. The evaluation of experimental results shows an accuracy of 95.48% in group activity identification using neural networks.
Rethinking teacher training: Covid-19 and the rise of e-learning

He Covid-19 pandemic has caused an exponential change in the educational environment. The impact of epidemiological situation has been so powerful, that it can be considered that a new paradigm has been born based on semi-presence as new didactic normality. We witness the new and accelerated context where Information and Communication Technologies (ICT) have acquired a greater role than they used to ever have. Under this new perspective, which also involves a strong reflection on the teaching-learning processes, a review of existing technological resources and their functionality at present is proposed. Taking all of this into consideration, during the beginning of the 21st century the technological advances in the field of education have been significant. Management platforms, resources on the Internet, or other media and simultaneous interaction are some of the key tools in a world immersed in a rethinking that goes far beyond a classroom.
Challenges of teaching large classes at UNAM

This article is part of a thesis study that sought to investigate challenges experienced in teaching large classes at UNAM, Hifikepunye Pohamba Campus. Lecturing in large classes can be of grave concern to anyone because of the various challenges involved. Employing a qualitative case study design, this article explores the challenges experienced by lecturers and student teachers in large classes.The participants for the study were three teacher educators who teach classes with one hundred students or more, nineteen student teachers and three campus management members. Data were collected through face- to- face semi-structured interviews, focus group interviews, non-participant classroom observations, and document analysis. Data were analysed through means of thematic and content analysis. The results revealed that large class sizes hinder implementation of active teaching approaches and strategies, impact negatively on the learning activities, assessment tasks and feedback given to student teachers. Among others, the article recommends provision of appropriate resources in creating a conducive teaching and learning environment for large classes. It also recommends that teacher educators should be provided with continuous professional development programmes in how they could handle large classes as well as various assessment strategies that they could use in such classes.
Participatory Agent-Based Modelling for Flood Risk Insurance

In the context of climate change adaptation, there has been a recent research focus on the impact of flood insurance on flood risk reduction behaviour. ABM has been recently used in such researches to model the interaction of stakeholders. Building on this foundation, we propose the integration of participatory methods to capture the socio-cognitive and behavioral aspects of flood risk insurance, which have been missed in such models. The results of our suggested line of research on Participatory ABM for Flood Risk Insurance can support public and private sector considering their preferences and contextual requirements.
Loma Linda University Libraries: Mobile Printing: LLU Print Center

Details the various methods available for printing from mobile devices. Instructions for printing and managing print jobs through the LLU Print website.
Mining the IODP Database for Relationships Between Lithology and Physical, Chemical, and Magnetic Properties

During each International Ocean Discovery Program (IODP) expedition a vast array of data, typically amounting to hundreds of gigabytes to several terabytes of information, are collected from drill cores. These data include physical, chemical, and magnetic properties and digital images collected continuously or every few centimeters along the cores using automated track systems, as well as a variety of analyses conducted on discrete subsamples taken from the cores. Coring just since the start of Expedition 349 in January 2014 has recovered over 50 km of core, resulting in a very large amount of data, most of which are accessible from the IODP LIMS database. Some of the properties typically measured include P-wave velocity, density, magnetic susceptibility, natural remanent magnetization, natural gamma radiation, and visible spectral reflectance. In addition, the lithology of all cores is described based mainly on visual characteristics of the surface of the split cores, visual examination of smear slides and thin sections, and compositional or mineralogical information derived from geochemical analyses. Our goal in this study is to mine these data for interrelationships that would otherwise be difficult to assess given the way the data are partitioned by specific property within the database. In particular, we extract basic lithologic information from the complex array of descriptive information and then tie that information to all other observations in order to characterize the physical, chemical, and magnetic properties of a myriad of lithologies.
Why Is FMWhatsApp Not Installing? Common Reasons to Watch Out For

We all have seen how Whatsapp has given us a great social platform. It is a type of platform that has allowed people to use it in the way they want or ...
Analysis of the Need of Augmented Reality (AR) Based Learning Media for the Procedure Text Material

Learning media is one of the most important aspects that support success in a learning process. In the current 21st century, interesting learning media are technological-based, fit with the life of millennial students, and view the development of 4.0 industrial revolution era. In learning procedure text, the students will be more interested in the media innovation to help generate their ideas in writing. This research aims to analyze the need for technology-based learning media for Bahasa Indonesia teachersand VII grade students of junior high school in the procedure text material in Magelang city. This is a qualitative descriptive research with the data collection techniques carried out include questionnaire and interviews. The data are in the form of curriculum analysis, procedure text material, and the students’ characteristics which are analyzed interactively. The results show that: (1) the entire material is in accordance with the competence standards, basis competencies, and indicators of the 2013 Curriculum; (2) the students have difficulty in understanding linguistic material in the form of written texts; (3) the level of creativity gives rise to ideas, and the students’ ability to switch ideas into the written form is still low; and (4) the learning media used are still conventional. Therefore, the teachers and the students need the development of technology-based learning media that can help them to be more active and creative in writing procedure texts.
PENERAPAN METODE NAIVE BAYES CLASSIFIER DALAM ANALISIS BUTIR SOAL (STUDI KASUS: SMP NEGERI 4 SAPE)

One of the components low education is an evaluation. The learning process to teach. The teacher's attention in the evaluation is only pressuring on the final result gained by the student. This assessment is used to assess the drawing up of learned progress reports, and improve the learning process. Study deals with application of grain analysis problems. An analysis of the article on the purpose of identifying the quality or quality of the matter. This study is intended to produce an application for a problem item analysis that can facilitate the teacher's analysis of the problem item. The method used in the analysis of this article is the Naive Bayes Classifier , in which the Naive Bayes Classifier's method for the quality of consideration based on the state of difficulty and the cumulative power of matter so that the problem can be known whether it is acceptable, revised, or completely rejected. A study conducted by the system has been successful and accurate, the Naive Bayes Classifier's methods prove to be able to classify lecture.
ExSim at eHealth-KD Challenge 2020 Combining NLP and Word Embeddings for Entity Recognition

This paper describes the system submitted to the eHealth-KD Challenge 2020-Task A: entity recognition. The system utilizes a supervised learning methodology to recognize entities within Spanish texts; namely, it applies NLP and word2vec techniques to create a unique labeled dictionary of entities in the training set. These labels are propagated into new entities that are found in the testing set via semantic similarity measurement. The simplicity of our system shows low performance with F1=0.32, precision=0.29, and recall=0.34. Finally, the system is discussed from different aspects: challenges, earlier attempts, current system’s characteristics, and possible future work.