Reviewerly/exHarmony huggingface dataset:
Some fun pedagogical techniques to teach optics to students of all ages

During the COVID-19 pandemic, educational institutions have adopted digital technologies as a medium to share the knowledge and to connect with the students. The idea of learning and teaching has taken a huge turn and needs to be customized and made innovative since the technological era has stepped in. Although the educational information and knowledge are easily available over the internet, the fruitful gains of meaningful knowledge assimilation can only be achieved under the supervision of teachers/mentors. Taking this ideology forward, this paper presents pedagogical techniques to virtually connect with students leading to successful inculcation of the theoretical knowledge with practical wisdom unto the student’s mind. The pedagogical idea was exercised with school students studying from 6th to 12th grade. Initially, a teacher-student connect was established. Then, the students were pro-actively made to understand topics through self-apprehended practicals at home, keeping up with the age-old conventional environment so as to gradually ease them in the virtual technology. Practical and tasks that were carried out throughout the pedagogy played a major part in the development of mind with curiosity, questioning and constructivism, emphasizing on the weak points and strengthening their concepts in optics.
Machine Learning Model for Classification of Vehicles Using Pass-by Noise Level

Artificial neural network model was utilized to classify vehicle types into motorcycle, light and heavy vehicles by using pass-by noise datasets. For the training, three sample datasets were collected from a one-lane and one-way road. These datasets are for 1 s pass-by maximum, 3 s pass-by maximum, and pass-by noise from maximum to below 10dB. The three datasets were analyzed to provide Z- and A-weighted and 1/3 octave band sound levels for the training. It was found that the 1 s pass-by maximum dataset led to the best explanatory power(R-square, 98.5%). The machine learning model with the 1 s pass-by maximum dataset was tested for two different roadsides and it was found that the explanatory power was greater than 90%.
MOTIVASI DAN PERSEPSI KONSUMEN PENGGUNA LAPTOP MEREK ACER (Studi Mahasiswa Fakultas Ekonomi Dan Bisnis Universitas Musamus Merauke)

This research was conducted to see the effect of motivation &amp; perception of the decision to use the Acer brand laptop on students of the Faculty of Economics and Business, Musamus Merauke University. The population in this study was 1116 of the total number of FEB students. The sample in the study was 92 respondents with the sampling method accidental porposife sampling. The technique used is multiple linear regression. From the test results, the t test &amp; F test show that the motivation &amp; perception variables have a positive effect, are significant partially, or simultaneously towards the decision to use the Acer brand laptop on FEB students at Musamus Merauke University.
A Statistical Analysis of Smartphone Use and Public Eye Health Based on the Survey in Hangzhou, Zhejiang Province

Abstract In terms of the way of information dissemination, mobile phone has become an essential tool of communication in people’s daily life. In this paper, 382 valid questionnaires were collected and SPSS data analysis was conducted to investigate the situation of smartphone use and eye health of Hangzhou citizens. The results of the survey and analysis showed that most people had very bad habits of using mobile phones, which were harmful to their eyes. Many people more or less had certain eye problems, and there was a long way to go to protect their eyes.
Introduction to Cucumber

Cucumber (Figure 6-1) is an awesome tool that allows you to develop your software using a Behavior-Driven Approach (BDA). It makes sure that business stakeholders transfer the software requirements to developers in an accurate and rigorous way so that the final software delivered fully satisfies those requirements. Also, the requirements are turned into executable specifications of the application developed, and they are executed on every new commit to make sure that no old features are broken when new ones are introduced. Cucumber is a great tool of collaboration, documentation, and test automation.
APPLICATION OF DEEP BELIEF NETWOEK FOR DETECTION OF TRYPANOSOMIASIS PARASITE IN CATTLE USING BLOOD SMEAR IMAGE

Currently, disease management, symptoms classification and diagnoses are manually performed and are time consuming due to the fact that it takes longer time for infected animal to be manually diagnosed especially those animals which are remote from veterinary. These challenges motivate the development of detection tools that can perform automatically using deep learning approaches such as convolutional neural networks which have received great acceptance in literature. This paper seeks to improve on the deep learning methods of managing animal diseases by using a trained model based on pre-trained deep belief network by stacking restricted Boltzmann machines to classify 4000 animal blood images into parasite and non-parasite class using method of contrastive divergence. Features are extracted from the images and the visible variables of the deep belief network are initialized in order to train the deep belief networks. On a final note, the deep belief network is fine tuned discriminately to compute the probability of class labels by employing back-propagation. The method’s accuracy and precision are higher than the previous state-of-the-art methods with 96.30% and 95.20% respectively. We belief this paper is among the most recent applications of deep belief network for detecting trypanosomiasis parasite in animal blood images.
AN APPROACH TOWARDS THE DEVELOPMENT OF A HYBRID CHATBOT FOR HANDLING STUDENTS’ COMPLAINTS

Abstract The communication between students and staff in most university system is done manually. This is strenuous and time-consuming with the lecturers having to answer same type of questions over and over again with same answers. This problem can be solved partially if students are availed the opportunity to interact with a chatbot which would be able to respond to their questions. Chatbots are artificial intelligence programs that are able to act and maintain a certain level of conversation with real people. The study develops a chatbot system- CSC StudentBuddy (hosted using Facebook Messenger Platform with A Facebook Page acting as the bridge), to reduce these challenges in the Department of Computer Science, University of Benin, Benin City. Data was collected by the interview method. The respondents were 400 level/final year students and lecturers in the department. The chatbot was built with an easy-to-understand non-coding bot building platform- Chatfuel. The build-up of the chatbot was then conceptualized and birthed into a functional prototype. Then, usability validation testing and analysis were conducted with the respondents and feedback was received in form of surveys. The feedback generated was used to improve the bot. Keywords: Chatbots, Communication, Conceptualized, Usability Testing, Prototype Artificial Intelligence.
A Selection of Mobile Applications in Learning English between High and Low Proficient EFL Learners in a Thai Institute

Mobile learning is a new type of learning that allows learners to access any knowledge, skills, and numerous learning resources independently. It has become a helpful tool for language learners to develop their language skills since there are many kinds of free applications which learners can download and use anywhere and anytime. However, the language learners might be unwilling to use mobile applications if there is poor network connectivity, and the applications are not user-friendly and varied. The purposes of this study were to examine the students’ selection of mobile applications in learning English and to compare the differences between high and low proficient English learners in their application usage and their progress after using the applications. The participants were 105 second-year Business Japanese students at Thai-Nichi Institute of Technology. They consisted of 48 high proficient English learners and 57 low proficient English learners. A 38-item self-report questionnaire was used to collect the data. To analyze the data, descriptive statistics and independent-samples T-Test were used. The results revealed that the mobile applications the students preferred to use in order to learn English were Google Translate, Dictionaries, and YouTube. They used the applications for translating words and sentences from English into Thai the most (M = 4.18). Moreover, there was a significant difference between two groups of the students in acquiring new vocabulary at .05 significant level (p = .035).
Implementation of Building Integrated Photovoltaics (BIPV) System in Malaysia

This thesis focuses on the implementation of Building Integrated Photovoltaics system (BIPV) in Malaysia. The purpose is to determine the application of the BIPV system, check the views of the main construction parties on this, and evaluate the performance of the BIPV system in affecting the quality of buildings in Malaysia.Nowadays, the planet faces many problems in terms of pollution and energy waste, so it is necessary to develop some renewable resources. Due to the complexity of BIPV systems and the lack of relevant knowledge and information, BIPV systems are rarely implemented in Malaysia. By the way, the qualitative method is used to obtain the demand information from the sample through interviews, because it can delve into the key areas.After the research data is collected, it should be analysed. It will determine whether the success of achieving the goal directly affects the results of this paper. To make sure the success of this article, the accuracy of the information should be ensured.As a conclusion, this thesis is very important because it will affect the popularity of the BIPV system in Malaysia's construction industry and the reputation of Malaysia, because the system may represent a country's standards in assessing whether the country has reached a higher level or on the development path. Energy saving and energy efficiency.Keywords: photovoltaic system, solar energy
Online Reviews Over Sentiment Analysis using Machine Learning: A Systematic Review

One of the key territories of NLP is Sentiment Analysis, the capacity to comprehend emotional tones in speech and text. This Systematic Literature Review has focused on papers between 2015 to 2020, taken from trusted and credible database such as IEEE Xplore, Science Direct and Springer. A total of 70 papers have been chosen for this review. This SLR approach is followed to get an effective insight on various work being done in this research field using Machine learning techniques: supervised or unsupervised. Different research questions have been looked up and discussed. The result shows that most of the work have used SVM for classification techniques and accuracy as the performance metrics. Also most of the dataset are yielded from e-commerce sites for product reviews, reviews in form of tweets from twitter and in various other fields like hospitality reviews, movie reviews and other social networking sites opinions.
Inner Eye Canthus Localization for Human Body Temperature Screening

In this paper, we propose an automatic approach for localizing the inner eye canthus in thermal face images. We first coarsely detect 5 facial keypoints corresponding to the center of the eyes, the nosetip and the ears. Then we compute a sparse 2D-3D points correspondence using a 3D Morphable Face Model (3DMM). This correspondence is used to project the entire 3D face onto the image, and subsequently locate the inner eye canthus. Detecting this location allows to obtain the most precise body temperature measurement for a person using a thermal camera. We evaluated the approach on a thermal face dataset provided with manually annotated landmarks. However, such manual annotations are normally conceived to identify facial parts such as eyes, nose and mouth, and are not specifically tailored for localizing the eye canthus region. As additional contribution, we enrich the original dataset by using the annotated landmarks to deform and project the 3DMM onto the images. Then, by manually selecting a small region corresponding to the eye canthus, we enrich the dataset with additional annotations. By using the manual landmarks, we ensure the correctness of the 3DMM projection, which can be used as ground-truth for future evaluations. Moreover, we supply the dataset with the 3D head poses and per-point visibility masks for detecting self-occlusions. The data will be publicly released.
Useful risk management tools

This chapter continues the important subject of project risk management by describing some more tools that can be used to predict, identify and investigate risk events. A wide range of risk management tools is available to project managers. Some can be used alone for specific purposes but these tools can also be used in different combinations. Brainstorming can identify risks, opportunities and possible solutions to problems by concentrating the thoughts of a group of people in a short time. Cause and effect diagrams (also known as fishbone or Ishikawa diagrams) are a powerful investigative graphical method for predicting and analysing possible causes of a defect or problem. In problem solving, Pareto analysis can be used when defining the situation to help narrow the scope of a problem. When identifying the root causes Pareto analysis can also be used to rank problems and look more closely at non-conformance data.
Knowledge sharing on QaA fora: challenges of automated interaction analysis

Q\aA fora have developed into a precious tool for online knowledge exchange. Being community-driven, openly accessible and free, getting an answer to a complicated question can nowadays be a matter of minutes. This research investigates the specific case of gis.stackexchange, a technical QaA forum used by Geographic Information Systems professionals. A central topic is the interaction between users. Based on existing research, an automated approach is elaborated and a big data analysis is performed. Also, a link between the outcomes and self-reflective behaviour found on the community meta forum is established. Factors positively influencing interaction as defined by the approach are identified (implication of the author(s), presence of images and code snippets). Furthermore, weaknesses such as the low share of interactions associated to an alteration (of the original post) are also discussed. These outcomes eventually lead to a series of recommendations for the forum itself and related formats.
New Zémor-Tillich Type Hash Functions Over GL2 (𝔽pn)

Abstract We present a large class of new Zémor-Tillich type hash functions whose target space is the finite group GL 2 (𝔽 p n ) for any prime p and power n . To do so, we use a novel group-theoretic approach that uses Tits’ “Ping-Pong Lemma” to outline conditions under which a set of matrices in PGL 2 (𝔽 p (( x ))) generates a free group. The hash functions we form are secure against known attacks, and simultaneously preserve many of the desired features of the Zémor-Tillich hash function. In particular, our hash functions retain the mall modifications property .
Penggunaan Model Pembelajaran Think Talk Write (TTW) Untuk Meningkatkan Keterampilan Membaca Pemahaman Pada Peserta Didik Kelas IV Sekolah Dasar

Abstract . The purpose of this research is to improve reading comprehension skills in fictional texts through the use of the Think Talk Write (TTW) learning model at fourth grade students at SDN Jenengan 3 Boyolali in academic year 2018/2019. This research is a Classroom Action Research (CAR) which was done in two cycle. In each cycle consists of the planning, implementation, observation and reflection stages. The subjects of this research was researchers, fourth grade teachers and fourth grade students with 28 students. Data collection techniques in this research are observation, interviews, tests, and documentation. The technique used to check the validity is triangulation technique. The data analysis technique used in this research is a comparative descriptive technique and interactive analysis techniques. Data analysis includes: data reduction, explanation, data (data display) and conclusion. The results of this research show the average class also increased, at the pre-action stage 45.71 with classical completeness of 28.57% then in the first cycle it increased to 65.65 with classical completeness of 42.85% and in the second cycle it increased to 79.46 with classical completeness of 89.28%. Based of the result, the conclusion Think Talk Write (TTW) learning model can improve the reading comprehension skill of fourth grade student at SDN Jenengan 3 Boyolali in academic year 2018/2019. Keywords: think talk write (TTW) model, skills, reading comprehension, elementary school
LibGuides: First Year Experience: Getting Around the Library

This LibGuide was created to provide information on library resources for first-year students and their instructors.
Introduction to Jasmine

In this chapter, you are going to learn Test-Driven Development (TDD) using Jasmine.
Vision-Based One-Dimensional Barcode Detection

The correct barcode detection is an important task to identify items and products from images. It is the cornerstone of the barcode decoding stage. Simply, incorrect detection leads to incorrect recognition. There are several studies which presented various level of accuracy based on the utilizing image processing or artificial neural networks. This paper proposes an image processing-based method to detect the one-dimensional barcode. The method proposed has succeeded when examined two published datasets of 215 and 1055 barcode images to reach accuracy rates of 86% and 85.8%, respectively. The yielded results of this paper have exceeded the results of the previous studies of the publishers of the datasets.
Comparative analysis of the state and development trends of the education system of the Russian Federation and the educational systems of the OECD countries

The work describes the specifics of international education statistics, presents methodological approaches to a comparative analysis of educational systems based on statistical data, and the results of a study of Russian education in comparison with the educational systems of developed countries. The work analyses the world’s emerging patterns and trends of education development in such areas as the educational attainment of the population, participation of the population in education, the organization of the educational process, financing of education, the structure of the pedagogical staff, condition of teacher’s work and teacher’s wages. The report shows how the characteristics of educational systems are associated with the economic indicators of countries and the socio-economic effects of education for people, society and economy. The analysis of the conformity of the Russian education system indicators to the emerging patterns and trends in the world is carried out, and the specific characteristics of Russian education are shown.
LibGuides: Library Item Pickup and Return Locations - Summer 2021: Pickup and Return Locations

This guide provides the pickup locations and book drop (or other return) locations at each campus.
Spending Money Wisely

Online electronic coupon (e-coupon) is becoming a primary tool for e-commerce platforms to attract users to place orders. E-coupons are the digital equivalent of traditional paper coupons which provide customers with discounts or gifts. One of the fundamental problems related is how to deliver e-coupons with minimal cost while users' willingness to place an order is maximized. We call this problem the coupon allocation problem. This is a non-trivial problem since the number of regular users on a mature e-platform often reaches hundreds of millions and the types of e-coupons to be allocated are often multiple. The policy space is extremely large and the online allocation has to satisfy a budget constraint. Besides, one can never observe the responses of one user under different policies which increases the uncertainty of the policy making process. Previous work fails to deal with these challenges. In this paper, we decompose the coupon allocation task into two subtasks: the user intent detection task and the allocation task. Accordingly, we propose a two-stage solution: at the first stage (detection stage), we put forward a novel Instantaneous Intent Detection Network (IIDN) which takes the user-coupon features as input and predicts user real-time intents; at the second stage (allocation stage), we model the allocation problem as a Multiple-Choice Knapsack Problem (MCKP) and provide a computational efficient allocation method using the intents predicted at the detection stage. We conduct extensive online and offline experiments and the results show the superiority of our proposed framework, which has brought great profits to the platform and continues to function online.
New ways to interact with devices to change the gaming experience

Gaming experience refers to the players’ overall experience when playing agame. Both game and controller have an impact on it. This project exploreshow different element arrangements on a control ...
Surface form characterization of plane-parallel elements using frequency-tuned phase-shifting interferometry

Plane-parallel optical elements, such as optical resonators, laser rods or wave plates, are widely used in many optical setups. Both planar surfaces of the element have to be manufactured with high precision in order to assure proper quality of the element and thus these surfaces have to be accurately measured. However, the interferometric measurement process, usually used for the surface form topography characterization, suffers from multiple interference patterns. This increases the total measurement error. In this paper the frequency-tuned interferometric method, that overcomes this problem, is demonstrated and compared to commonly used techniques using immersion liquid. Using a tunable laser source together with a frequency separation of the phase information from both surfaces, fringes from the first and second surface can be distinguished. Also, the interference between both surfaces can be used to obtain the wedge and thickness values of the specimen.
재독 한글학교 교사의 직무스트레스와 조직효과성 간의 관계 연구

This study aims to examine the relationship between teacher’s job stress and school organizational effectiveness and to investigate the effect of the teacher’s job stress on Korean school’s organizational effectiveness in Germany. For this purpose, this study conducted a questionnaire targeting 81 Korean school teachers in Germany. First, the results revealed that teachers’ perception of job stress was below the average. Among sub-factors of the teacher’s job stress, administrative support was the highest, followed by work overload, student instruction, principal’s leadership, relationship with teachers, and relationship with parents. The teachers’ perception of organizational effectiveness was above the average. Job satisfaction was the highest among the sub-factors of the school organizational effectiveness, followed by adaptability to the organization, job performance, and organizational commitment. Second, the differences between the teacher’s job stress and school organizational effectiveness were significantly explained by the Korean teacher’s background variables: teachers’ age, academic background, salary, education career, and the number of students. Third, Korean school teacher’s job stress was negatively correlated with Korean school organizational effectiveness. As a result of the regression analysis, the student instruction and the principal’s leadership affected the school’s organizational effectiveness. This study implies ways to improve Korean school organizational effectiveness in Germany. (Sookmyung Women’s University)