Reviewerly/exHarmony huggingface dataset:
A Multi-Use Case Scientific Sensor Node

&amp;lt;p&amp;gt;Nanometrics' Pegasus digitizer is the basis for a scientific grade node and is the latest development in many years of designing and building reliable seismic instruments for the scientific and monitoring community. Coupled in a grab-and-go quick deploy package with a variety of sensors enables responses to many types of events and environmental measurements. These types of systems are not only for hazards, such as earthquakes and volcanoes, but can form the basis of better tools used for critical structure and microzonation studies using ambient noise.&amp;amp;#160; Pegasus takes advantage of a complete ecosystem of software, making planning, deploying and data harvesting very simple and straightforward as well as providing a dataset that includes automatically generated metadata in the form of StationXML and standard miniSEED data files.&amp;amp;#160; Pegasus design criteria was based on optimal SWaP (Size, Weight and Power) and makes it unique in short to long duration deployments without swapping of units in the field, while its broad sensor compatibility enables many types of measurements and is completely compatible with the advantages of Nanometrics smart sensors.&amp;lt;/p&amp;gt;
Creativity and Culture

looks at why and how emoji encourage creative expression and documents the many playful ways in which they’re used. It asks why people translate works of literature into them and how swearing in emoji is more to do with language play than actual verbal abuse. It considers these questions within the context of the way that social media is itself encouraging a boom in creativity and user-made content and how emoji culture is very much part of this - and particularly its relation to meme culture. The chapter also looks at how emoji both reflect different aspects of modern culture in their design and are being incorporated within modern culture itself.
The Effect of Reward and Facilitating Condition on Employee Motivation in Postal Sector

The variables taken in this study are Reward (extrinsic and intrinsic) is something given to the employees for their good work or behaviour. Facilitating condition is an organizational and technical infrastructure exists to support the employees whereas Employee motivation is regard as how employees act towards their work that shows how productive and effective they are. The purpose of this study is to associate the effect of reward and facilitating condition on employee motivation and actions to motivate the employees of the Postal Sector. Standard Questionnaire is used as instrument. The population of the study are employees of the Post Offices. The data was collected from 101 employees of the Postal Sector. Simple random sampling method has been used for the study.Data were analyzed by using Reliability, T-test and Regression. Regression analysis is applied to find the effect of reward and facilitating condition on employee motivation. The study concludes that the reward has a significant positive impact on employee motivation. The study also shows the significant impact of facilitating condition on employee motivation. Managerial implications along with suggestions and recommendation for future research have also been examined in the end of the paper.
English Online Learning in the Age of Global Pandemic: How Do Teachers and Students Feel?

Numerous researchers examine teachers' and students’ experiences in online learning at the college level. But there are a few sources that explore the implementation of English online classes at a Vocational high level. This issue is highly needed since the theory and researches dealing with this topic at this level are still rare. The present study aims to close the gap by investigating the implementation of English online classes. The participants were six female English teachers and one hundred and seventy students at one state vocational high school in Central Java, Indonesia. The current research analyzes not only numerical data but also narrative data, which is customary for qualitative research to address the research questions. The instruments use questionnaires and a semi-structured interview. The overall results revealed that technology could help both teachers and students in conducting teaching and learning activities, even though some constraints such as limited data plan, network difficulties, and lack of teacher-students engagement. Furthermore, understanding materials became top rank challenged for participants during the on line class. The current study contributes theoretical and practical benefits to improve the implementation of online learning in the age of global pandemic.
TEXT MINING CUSTOMER REVIEWS FOR ASPECTBASED RESTAURANT RATING

This study applies text mining to analyze customer reviews and automatically assign a collective restaurant star rating based on five predetermined aspects: ambiance, cost, food, hygiene, and service. The application provides a web and mobile crowd sourcing platform where users share dining experiences and get insights about the strengths and weaknesses of a restaurant through user contributed feedback. Text reviews are tokenized into sentences. Noun-adjective pairs are extracted from each sentence using Stanford Core NLP library and are associated to aspects based on the bag of associated words fed into the system. The sentiment weight of the adjectives is determined through AFINN library. An overall restaurant star rating is computed based on the individual aspect rating. Further, a word cloud is generated to provide visual display of the most frequently occurring terms in the reviews. The more feedbacks are added the more reflective the sentiment score to the restaurants’ performance.
Effects Of High Intensity Interval Training On Congnitive Function In Older Adults

PURPOSE: To explore the effects of high intensity interval training on cognitive function in older adults, and to provide new methods and theoretical basis for delaying cognitive function decline in older adults. METHODS: Eligible subjects over 60 years old in Beijing area were randomly divided into control group (CON), high intensity interval training group (HIIT) and moderate intensity continuous training group (MICT). HIIT and MICT groups underwent a 12-week training. Before and after training, all subjects accepted maximum oxygen uptake test, digit span test (DST), trail making test (TMT) and stroop test. RESULTS: After 12 weeks training, in HIIT group, compared with pre-training and CON group, the maximum oxygen uptake level was increased significantly, and the number of digits in the forward and backward digit span test was increased significantly, and the time to complete the TMT-A and Stroop test was significantly reduced, and the accuracy of the Stroop test was significantly improved. Compared with MICT group, the maximum oxygen uptake level of HIIT group was increased significantly. But in MICT group, compared with pre-training, the maximum oxygen uptake level was increased significantly, and the number of digits in the forward digit span test was increased significantly, and the accuracy of the Stroop test was significantly improved. Compared with CON group, the number of digits in the forward and backward digit span test was increased significantly. CONCLUSIONS: High intensity interval training can significantly improve the short-term memory, reaction speed and anti-interference ability in older adults, but it has no obvious effect on improving attention. These positive changes may be related to the increase of maximum oxygen uptake level. Compared with the traditional moderate intensity continuous training, high intensity interval training has a more significant effect on the improvement of cognitive function in older adults.
Virtual Reality Simulation LUMC

During the graduation period, I have worked with Leiden University Medical Center on bringing to reality the first steps to creating a complementary training tool for their residents. As a result, together with an IMT&S team, we designed and created a demo application which simulates a kidney transplant surgery and the anesthesia procedure in a virtual operating room.
基于智能手机的汉语移动学习(M-learning)研究

With the development of technologies such as the Internet, big data, cloud computing, artificial intelligence, and mobile terminals, the combination of mobile learning and traditional Chinese teaching is a general trend. The application of mobile learning in Chinese teaching events extends the traditional teaching classroom, strengthens the teaching context of Chinese teaching, and ensures the modernity of Chinese classroom teaching. There are still many problems in the application of mobile learning to Chinese teaching. However, from the perspective of the development of mobile learning, mobile learning is undoubtedly an epochal trend in the development of Chinese teaching models. According to teaching practice, the classroom application of mobile learning software to assist Chinese teaching can enhance the interest, convenience, timeliness and interactivity of teaching. The mobile learning model makes the traditional Chinese classroom more personalized, and teaching is more conducive to individual development. Mobile learning can break the limitations of practice and space and effectively integrate students' scattered time. The reasonable use of mobile phone software can effectively assist traditional classroom teaching, make up for the shortcomings of traditional classroom teaching, and help students improve their Chinese proficiency. Through teaching practice, there are still shortcomings in the classroom application of mobile learning mode. Mainly manifested in the rationality of smart phone software selection, practicality of application, student self-control ability and dependence on software. In this regard, the author puts forward several suggestions on the application of mobile learning models in Chinese teaching, which will play a role in inducing more systematic and perfect mobile learning in Chinese teaching in the future.
CHARACTERISTICS AND ORIGIN OF IRON MINERALIZATION IN NORTHERN SANANDAJ – SIRJAN ZONE (IRAN – IRAQ)

The studied iron mineralization is located in the northwestern parts of the Sanandaj – Sirjan Zone (SaSZ) of Iran and extends inside Iraq. This zone is bordered by the Urumieh – Dokhtar magmatic arc and the Zagros Thrust Zone, which is the boundary between the Arabian and Iranian plates. The SaSZ is very important for its iron, manganese and gold mineralizations. The main iron ore localities and mining sites in the area are studied in this work. The study included field characterization, petrologic and geochemical analysis. The aim of the present work is to study the genesis and paragenetic history of the Fe mineralization in this zone. The results indicate a two-phase formation process with two different paragenesis of iron mineralization in most of the localities studied in the region of the northern Sanandaj – Sirjan Zone; one of low temperature and the other formed at high temperature. The first phase represents sedimentary exhalative iron oxides layers. The second phase is metamorphogenic, following orogenesis, metamorphism, and plutonism. High-temperature fluids released from the solidification of a large plutonic body remobilized iron oxides of the first phase and caused deposition as magnetite and high-temperature silicate veins within higher stratigraphic levels.
Relaxed Attention: A Simple Method to Boost Performance of End-to-End Automatic Speech Recognition.

Recently, attention-based encoder-decoder (AED) models have shown high performance for end-to-end automatic speech recognition (ASR) across several tasks. Addressing overconfidence in such models, in this paper we introduce the concept of relaxed attention, which is a simple gradual injection of a uniform distribution to the encoder-decoder attention weights during training that is easily implemented with two lines of code. We investigate the effect of relaxed attention across different AED model architectures and two prominent ASR tasks, Wall Street Journal (WSJ) and Librispeech. We found that transformers trained with relaxed attention outperform the standard baseline models consistently during decoding with external language models. On WSJ, we set a new benchmark for transformer-based end-to-end speech recognition with a word error rate of 3.65%, outperforming state of the art (4.20%) by 13.1% relative, while introducing only a single hyperparameter. Upon acceptance, models will be published on github.
WAB Learns: MS WEIRD: Reading Activities

Middle School WAB Extended Independent Reading Days A selection of lesson ideas to encourage reading
Self-assessment Optimization Through WhatsApp Features for Increasing Students' Listening Comprehension

The article is aimed to inform that self-assessment optimization through WhatsApp features can Increase the students’ listening comprehension. The action research is used to gain the data. It consists of 4 steps, like planning, acting, developing, and reflecting stage. It conducted for two cycles. The informants of this research come from fourth semester of English Education Program at STAIN Mandailing Natal. The instruments of collecting the data are an interview guide, online questionnaire, Listening script, and field note. Qualitative and quantitative data were analyzed in this analysis. Qualitative data would be collected by observation, interviewing, and surveying. The listening examination will collect quantitative evidence. It will be evaluated using a listening comprehension score calculation. The result of the research showed the increasing on students’ listening comprehension through self-assessment optimization, it can be seen from the students’ scoring in each meeting.
Teaching speaking skills through retelling story technique at senior high school

The objectives of this research were to find out whether there was a statistically significant improvement on students’ speaking skills in English after the students were taught the retelling story technique and to investigate the relation between students’ responses and their speaking achievement. This study was conducted through quantitative approaches, with a total of 30 tenth-grade students at SMAN 1 Gadingrejo. The data were collected by using a speaking test and questionnaire. Data were analyzed by using a Paired Sample t-test and a Pearson Product Moment. The result showed that there was a statistically significant improvement in students’ speaking skills in English after the students were taught the retelling story technique, it can be seen from the result of the Paired-Sample T-Test where the significant value was lower than 0.05 (0.000.309). Hence, it can believe that the retelling story technique is effective to improve students’ speaking skills in English and also the students’ response plays q big role in their achievement after the implementation of the technique in learning language process. Keywords : speaking skills, retelling story technique, a physical object.
Introducing HydroPy, an updated global hydrology model rewritten in Python

&amp;lt;p&amp;gt;Global hydrological models (GHM) are a useful tool to investigate the water cycle, to evaluate its sensitivity towards systematic changes, e.g. human impacts, and to project future conditions in river catchments for varying scenarios. They have been successfully applied for decades and there is still room for improvement.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Recently, we revised the Max Planck Institute for Meteorology&amp;amp;#8217;s Hydrology model (MPI-HM), which is an established GHM that was used in multiple case studies and inter-comparison projects. While still performing well, its source code (mainly Fortran77) has become increasingly difficult to maintain, thus hampering the implementation of new processes. For this reason, the model was rewritten from scratch based on the MPI-HM process formulations. The new model is mainly written in Python, thereby taking advantage of the highly optimized numpy and xarray libraries, and, hence, is aptly renamed to HydroPy. Using the original formulations, we make sure to preserve or even improve the old model&amp;amp;#8217;s skill while the switch to Python allows for much easier debugging and interactive model development.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In our presentation, we will evaluate the performance of the new HydroPy model and demonstrate its skill to simulate river discharge. Furthermore, we compare HydroPy to its predecessor MPI-HM and discuss the reasons of differences between their results.&amp;lt;/p&amp;gt;
Knowledge Management System Implementation: Expert System / Nor Adilla Mansor

In this millennial era, artificial intelligence is rapidly growth and it is a method that has been used to solve the problem in the variety field such as business, medical, agriculture, mechanical, and so on as a business automation. The usage of this artificial intelligence may allow the computing systems solve the problems roughly at the human level. Even the power of artificial intelligence is quite powerful in this era, but it cannot go beyond the human nature which means it can solve just for a specific problem, but cannot completely replace as a human being. Based on the Yarushkina et.al (2018) the intellectual systems closely related to the artificial intelligence must contain the knowledge of the Problem Area (PrA) and also should have the problem solving methods that can solve the issues in assigning the task such as machine learning methods, knowledge engineering methods, and ontologies method
Secure and Manage Passwords with Encryption and Cloud Storage

Tech users often face a challenge to create and remember a secure and sophisticated password for various software services or tools they use for entertainment, work, or utility such as streaming platforms, shopping sites, email account, etc. One thing common in all these services is a password and it’s difficult for the user to memorize and maintain all these passwords and end up setting up common or simple passwords and due to this accounts of various users across various services are compromised to brute force attacks or even social engineered out of them and even worse if the same password is used over various accounts. In this paper, we present a solution that uses encryption and cloud storage to efficiently secure and manage user passwords and add an extra layer of protection, ensuring integrity, availability and security without making users remember multiple passwords.
한국어 문화 교육을 위한 문학 텍스트 활용 방안에 대한 고찰 - 학습자 및 교수자 요구조사를 바탕으로 -

Journal of the International Network for Korean Language and Culture 16-2, 121-147. Among various texts in Korean cultural education, the present study considers Korean literature about society and culture helps learners to understand about Korean society and culture as important material for cultural education. In order to examine the practical use of such literature texts, this study seeks to conduct a foundational study through a needs assessment for two groups, the learners and the instructors. The research participants are advanced Korean learners at a university-affiliated Korean language education institute and instructors teaching Korean language and literature. The stages of research include initial explanation and interview, questionnaire, review of the questionnaire, survey, and post-survey confirmation questioning. The results of the survey show different characteristics in the demands between the two groups. The instructor group used the literature texts by focusing on the understanding of Korean society and culture as well as developing the language abilities, the learner group showed a great interest in Korean society and culture but their desire was to learn Korean language and culture in a more entertaining method. Therefore, they preferred literature that were famous and popular rather than those that are highly valued for their literary history and content, and they also showed a higher response than the instructor group in the reconstruction of cultural texts as a learning technique. Based on such results of the needs assessment, the present study provides educational suggestions for the effective use of various literature texts as a textual material for education. (Yonsei University)
HAFIS Enterprise / Muhammad Syafiq Suhaimi... [et al.]

HAFIS are packaging metal straws manufactured by our own company. We chose to retail these products because of the increasing demand and in metal straw products in Malaysia.Since Malaysians are becoming more aware of the environmental problems, more of them are looking for metal straws to minimize the usage of plastic straws. Our product does not only the metal straw itself, it also includes the brush and the pouch with a high-quality packaging.The retail price of or products is RM 13 per unit. The price of the item is pretty affordable and pretty much similar to existing metal straw products by other distributor and to be honest even cheaper from all the high-end brands like P .M. Lee Sdn. Bhd. We believe that our product will able to attract customers' attention and will able to compete with the already established brands in the market. This is because our product is affordable and has additional value that interest customers.In the organizational structure of the HAFIS Enterprise, we have executive manager, administrative manager, operation manager, marketing manager, general manager and financial manager. We also will hire sales assistants, operation staffs, marketing personnel, and clerk to ensure the sales of our products will run smoothly and the packaging operation can be conducted efficiently with excellent marketing strategies planned out by the marketing team.
A Citation Analysis of Physics Research Publications of University of Mysore

A citation analysis of research publications of University of Mysore covered by Web of Science was performed as a way of determining the information sources cited by the scholars in the field of physics. In the present study, 312 research publications of Physics were chosen as a sample from the year January 2009 to December 2018. There were 8733 citations in 312 research publications.Aim of this study wasto examine the different citation parameters like forms of literature, country wise scattering of literature and authorship pattern. Further, study also attempted to present the ranked list of top 25 cited journals and prolific authors in the field of physics.
Diff-Net: Image Feature Difference based High-Definition Map Change Detection.

Up-to-date High-Definition (HD) maps are essential for self-driving cars. To achieve constantly updated HD maps, we present a deep neural network (DNN), Diff-Net, to detect changes in them. Compared to traditional methods based on object detectors, the essential design in our work is a parallel feature difference calculation structure that infers map changes by comparing features extracted from the camera and rasterized images. To generate these rasterized images, we project map elements onto images in the camera view, yielding meaningful map representations that can be consumed by a DNN accordingly. As we formulate the change detection task as an object detection problem, we leverage the anchor-based structure that predicts bounding boxes with different change status categories. Furthermore, rather than relying on single frame input, we introduce a spatio-temporal fusion module that fuses features from history frames into the current, thus improving the overall performance. Finally, we comprehensively validate our method's effectiveness using freshly collected datasets. Results demonstrate that our Diff-Net achieves better performance than the baseline methods and is ready to be integrated into a map production pipeline maintaining an up-to-date HD map.