Reviewerly/exHarmony huggingface dataset:
Stakeholder's Experiences and Challenges in Supporting Kindergarten Learners in Blended Learning Approach during the Covid–19 Pandemic

The problem and the aim of the study The Covid-19 pandemic has changed the global educational landscape. It forces the entire students and educators to stay at home and utilize the distance learning mode. This study described the experiences and challenges of school administrators, kindergarten teachers, and kindergarten parents in supporting the kindergarten learners in a blended learning approach of the identified schools in the Districts of Sindangan and Bacungan Zamboanga del Norte, Philippines during the school year 2020–2021.Research methods This study used a qualitative research design through phenomenology in gathering, analyzing, and generating the themes from the data collected. There were 30 respondents of this study who were selected through purposive convenience sampling technique.Results The findings revealed that the stakeholders maintain an optimistic attitude despite their frustrations. They have done utmost dedication and exercised Bayanihan Spirit. However, they also got worried that students may not be acquiring learning at all. Some of the parents personally answer the module instead of just facilitating it for the kids. The parents use positive reinforcement in motivating their sons or daughters to answer the module. The principals, teachers, and parents unanimously acknowledge that blended learning is the most appropriate method while face-to-face classes are still suspended. In terms of challenges encountered, the parents recognize that some are illiterate; they lack the skills and patience in teaching their kids; and lastly, the kindergarten teachers had doubts if the students indeed answered the module's assessment tasks.Conclusion The stakeholders manifested dedication in supporting the kindergarten learners in blended learning approach during the covid–19 pandemic. Nonetheless, they were adamant as to quality learning was attained due to their personal shortcomings as sub-teachers and the credibility and reliability of the answered modules. Therefore, it is recommended that the parents should undergo training to assist their children in their studies while blended learning is still in place.
Augmented Reality Objek Wisata Bogor Menggunakan Algoritma Lucas Kanade Dengan Metode Marker Based Tracking

Information technology today, is very developed and easy to find. Especially in information on Bogor tourist attractions such as the Bogor Palace, Tugu Kujang, and Pakansari Stadium. However, the data information held is not completely valid. Because many tourists get data that is not suitable, due to the lack of information obtained. Therefore, the researchers tried to make an android-based "Tourism Object in Bogor" application using Augmented Reality (AR) technology and the Lucas Kanade Algorithm, as well as Marker Based Tracking efforts to make it easier to get the information desired by tourism. Bogor is one of the cities in West Java Province that attracts many tourists, especially domestic tourists. However, there are still many tourist attractions in Bogor that are still many tourist attractions that have not been visited and are still not widely known by tourists. Until now, researchers have tried to make an android-based "Tourism Object in Bogor" application so that tourists know the shape of objects and information such as the Bogor Palace, Tugu Kujang, and Pakansari Stadium. Using Augmented Reality (AR) technology, the technology itself has photos, sounds, and 3d objects that can bring virtual 3d objects into the real world. The "Tourism Object in Bogor" application uses Android Studio, Unity, Sketchup, Vuforia, and Visual Studio. In order to make it easier for tourists to identify data on tourist attractions they want to visit. The application "Tourism Objects in Bogor" serves to share data information for local and foreign tourists, because this is an opportunity for the Bogor Regional Government to improve services and facilities in Bogor, so that tourists feel safe arriving and visiting Bogor.
Social and philosophical understanding of a human existence in the context of the coronavirus pandemic

The article provides a socio-philosophical analysis of the impact of the coronavirus pandemic on human existence. Various views on this phenomenon are considered, both positive, based on the belief in scientific and technological progress and the development of new nanobiomedical information and cognitive technologies, with the help of which the virus will be defeated, and negative, based on the prejudice of a global conspiracy and digital totalitarianism, of the degradation of humanity under the influence of new information technologies. There is still no consensus about this phenomenon: how it arose and what prospects await humanity. The protracted epidemic has radically changed the usual world order on a global scale. The forecasts of a constant recurrence of the disease are especially alarming, which means a change in social life not in a quantitative, but in a qualitative aspect. New social norms will shape new social behavior and institutionalize it over time. The pandemic has been a catalyst for digitalization in all spheres of public life: from education and leisure to production activities. The distant way of social life gives rise to new social stereotypes, creates a new social reality. These tendencies require philosophical understanding.
Automatic Measurement of Acquisition for COVID-19 Related Information

This paper investigates data representation and extraction procedures for the management of domain-specific information regarding COVID-19 information. To integrate among different data sources, including data contained in COVID-19 related clinical texts written in natural language, Natural Language Processing (NLP) techniques and the main tools available for this purpose were studied. In particular, we use an NLP pipeline implemented in python to extract relevant information taken from COVID-19 related literature and apply lexicometric measures on it.
Smart Auto Roll Sejadah ‘Prayer Mat’ / Mohd Amirul Akmal Mohd Fadzil

Smart Auto Roll Sejadah needs to be highlighted in the necessities of worship around the world especially among muslims. This is because I had done some research and there are few problems that people have when they perform their prayer. One of the problems is people that use sejadah ,they will not roll it back and just leave it on the floor. Because of that, the prayer mat will easily get dirty and need to be cleaned up. The main idea or the main function of my product is, this prayer mat can roll in and out to use it before and after we perform our prayer.Another function is my prayer mat has a sensor that can correct our foot position.My company target population for sure muslim in Malaysia . There are some channels that my company uses to promote this product. For example like online shops and my own retail.For online shops there are Instagram, Facebook, Twitter and my own web which is SmartAutoRole.com . Customers can get info and buy my product there.
Comparison of Poisson and Quasi-Poisson Regression: A Simulation study

Poisson regression is often used to model count data. However, it requires the assumption of equidispersion which not always met in the real application data. Quasi-Poisson can be considered as an alternative to handle this problem. The objective of this essay is to explain about the Quasi-Poisson regression, the likelihood construction, parameter estimation, and its implementation in real life data. The numerical method used in this study is Newton-Raphson which is equivalent to Iterative Weighted Least Square (IWLS) at the end of calculation. The simulation results for the data with the above problem showed that, in case of overdispersion, Quasi-Poisson regression with Maximum Quasi-Likelihood method provided a good fit to the data compared to Poisson regression.
Improving Students’ Ability In Writing DescriptiveText By Using Pop-up Book AT SMP SWASTA ISLAM NUR IHSAN TEMBUNG

Pop Up Book is the role of media is very important in the learning process.The presence of the Pop Up book media can support the learning process,facilitate students in understanding the learning material. This research was aimedto improve reading through Pop Up Book media the seventh grade students ofSMP Swasta Islam Nur Ihsan. The present study aims to explore the influence ofusing pop-up book. The subject of this study was the XI grade students of seniorhigh school which consisted of 31 students. The methode of this research wasclassroom action research (CAR) that consisted 2 cycle. The instruments used pre-test, post-test, observation and interview. This study used both quantitative andqualitative data.Quantitatively, the data was obtained form the students’ score of test. Theresult of the test of pre-test showed that the mean of the students’ score was 69,51which only 22,58% or 4 form 31 students who passed minimum passinggrade(MPG). Qualitatively, the data was taken form observation and interview. Inobservation, the researcher observed the situation and condition before and afterthe treatment. And while interview, the researcher asked some question to theteacher and the students about their feeling responds before and after using pop-up book. Based on the result of data analysis there was improvement on studentswriting skills in each cycle and strengthened by the observation and the interviewthat showed the condition or situation of the class was students motivated,interested and enthusiastic during teaching learning process which using pop-upbook.
Online Library Discussion Room Reservation System

Studying for an exam and discussion about the assignment with friends in a comfortable and quiet environment are the most important factors for the success of the student in academic. TARUC library provides the best discussion or study environment by offering discussion room booking which requires the student to book it by walk-in to the counter. However, the current system used by the library is a manual system, where records are maintained by hand. The manual system is well known to problems such as prone to human error, slow processing speed, require physical access and much more. This has brought a lot of inconvenience for the room manager as well as students. In order to overcome this problem, an alpha version of the online library discussion room booking system has been developed to solve the problems above. However, there are still some limitation and improvements can be made for the alpha version system. Therefore, enhancements are being proposed in this project to improve the alpha version system in order that it will be fully ready and could be implemented for the real business environment of the Library.Enhancements of the user interface, system process or bug fixing will be made on the login, staff, room, schedule, and the reservation module of the Online Library Discussion Room Reservation system. Besides that, student and register module will be added to the existing system. Furthermore, the software development methodology used for this project is the Iterative and Incremental model. Moreover, the testing methodologies used for this project are unit testing, user acceptance testing and integration testing.Finally, the result of this project was satisfying. The project had achieved the enhancements being proposed. But, it could still be further improved to yield better results.
Business Model Canvas : Hoverboard “S” / Muhammad Rozaimie Rosli

The target market of my new development product is the students that stay at the big campus university. I believe that my new product development will help the students to have a better life styles. The idea of making my new development product which is Hover board “S” is when I saw there are many students are fighting to get into the bus in the morning of weekdays. They are a hardworking student that want to arrive at the class on time. If they cannot get into the bus, they will walk from college to class. This would affect the students’ performance because of exhausted when arrive at the class and they cannot pay full attention to lecture. In order to solve the problem, I proposed the product that can improve their mobility during the time the students at the campus. Besides going to class, they also can use the Hover board “S” to go to college activities and important meeting if the place of activities is far away from their college. The hover board “S” is designed for the students easy to carry it everywhere. This is because the size of hover board is not so big and they can bring it into the class. I confident that the hover board “S” can reduce the time consuming of the students and they can use their time wisely to study the academic properties. With the unique features and function at the hover board “S”, it can attract the students to buy my product in the future
LibGuides: Cataloging Manual: Upload & Merge Records in Koha

The Northwest Arkansas Community College Cataloging Manual. After retrieving the MARC records from OCLC, they must be uploaded into Koha.
Estrategia de evaluación de la calidad de los cursos virtuales

In higher education there is a growth in the offer of virtual courses and with this arises the need to ensure the quality of these academic processes. This project aims to sensitize the university community in the culture of quality in virtual education. For this, different strategies for evaluating the quality of the courses were reviewed. A sample of courses was taken, information was collected from graduates, teachers, and students, and those responsible for the aforementioned instances were interviewed. Finally, an own instrument was designed and evaluated for the observation of the courses was designed and evaluated with the intention of providing an alternative for the evaluation of courses in the search for quality.Keywords: Virtual education; virtual courses; quality of virtual education; ICT.
Telopea Park High School Students using Speech Synthesiser

Research School of Physical Sciences, Department of Engineering Physics - Dr. Barry Luther-Davies, Dr. Rengko Dragila, Mr. Robert Whelan, Dr. Ken Inall, Dr. Bruce Millar & others
Vibrational effects on the formation of quantum W states

We theoretically investigate the formation of W states in a tripartite system composed of three charge qubits coupled to vibrational modes. The electromechanical coupling is responsible for second-order virtual processes that result in an effective electron-electron interaction between neighbor qubits, which leads to the formation of W states. Based on the Lang-Firsov transformation and perturbation theory, we analytically solve the quantum dynamics, providing a mathematical expression for the maximally entangled W state. Dephasing is also taken into account, paying particular attention to the robustness of bipartite entanglement against local dephasing processes.
High Reliance on Media Usage Diminishes Memory of Experiences on TARUC Students

In this modern era, social media played an important role in humans’ daily life. Peoplespend time on social media to do a lot of things such as communicating with friends, share personalexperience and etc. Young adults are considered as heavy user of social media, this is because theywere influenced with social media as they grew up, they use social media more frequently thanusers from other generation, this had led to their high reliance on social media.In this research, it tends to study to what extend young adults depend on social media, andto understand how they spend their time on social media. The main idea of this research is to findout how does the high dependence on social media could affect humans’ memory. There are fivechapters in this research and the dependence on social media and memory impairment occurs inhumans’ brain would be discussed.
Knowledge Mining from Health Data: Application of Feature Selection Approaches

This paper aims to measure the performance of feature selection approaches for mining knowledge from heath datasets. We compare seven popular knowledge mining approaches namely relaxed lasso, random forest, ReliefF, OneR, information gain, t-test and Chi-squared test. Support vector machine (SVM) classifier applies to determine the accuracy and area under curve (AUC) values of the knowledge miners. We use six popular Affymetrix and cDNA datasets. Results reveal that relaxed lasso works well with Affymetrix and relaxed lasso with random forest approaches perform well with cDNA datasets. This paper will enrich the existing literature and assist to identify best feature for knowledge mining on the health informatics domain.
Optimal Rates of Distributed Regression with Imperfect Kernels

Distributed machine learning systems have been receiving increasing attentions for their efficiency to process large scale data. Many distributed frameworks have been proposed for different machine learning tasks. In this paper, we study the distributed kernel regression via the divide and conquer approach. This approach has been proved asymptotically minimax optimal if the kernel is perfectly selected so that the true regression function lies in the associated reproducing kernel Hilbert space. However, this is usually, if not always, impractical because kernels that can only be selected via prior knowledge or a tuning process are hardly perfect. Instead it is more common that the kernel is good enough but imperfect in the sense that the true regression can be well approximated by but does not lie exactly in the kernel space. We show distributed kernel regression can still achieves capacity independent optimal rate in this case. To this end, we first establish a general framework that allows to analyze distributed regression with response weighted base algorithms by bounding the error of such algorithms on a single data set, provided that the error bounds has factored the impact of the unexplained variance of the response variable. Then we perform a leave one out analysis of the kernel ridge regression and bias corrected kernel ridge regression, which in combination with the aforementioned framework allows us to derive sharp error bounds and capacity independent optimal rates for the associated distributed kernel regression algorithms. As a byproduct of the thorough analysis, we also prove the kernel ridge regression can achieve rates faster than $N^{-1}$ (where $N$ is the sample size) in the noise free setting which, to our best knowledge, are first observed and novel in regression learning.
Research Guides: Digital Literacy FLC (Spring 2021): Fact-Checking and Evaluating Online Sources

Resources from the spring 2021 Digital Literacy Faculty Learning Community at Rowan University.
LibGuides: WSU System Strategic Planning Resources: Further Reading on Strategic Planning

A collection of materials created and curated by the Environmental Scanning subcommittee of the WSU System Strategic Planners. These resources are organized into the six topical areas for the assumed trends outlined in the WSU System Strategic Plan .
Broadening the set of algorithms and use-cases for analog combinatorial optimization accelerators

Recent experimental results show how classical accelerators based on analog computing can outperform quantum annealing alternatives in benchmark tasks that require dense connection matrices. In Hewlett Packard Labs, we have been studying two alternatives: integrated coherent Ising machines and mem-HNNs (based on memristive crossbar arrays). An important challenge for commercial viability is that different industrial workloads typically benefit from the availability of a variety of optimization algorithms and require a broad range of template combinatorial optimization problems. In this talk, we will discuss our recent progress in going beyond Max-Cut, and we will propose a broader range of algorithms. This flexibility in algorithm choices and template problems is an important step forward to address the wide variety of enterprise-level use-cases such as airline scheduling, supply chain optimization, real-time bandwidth management, gene sequencing, etc.
Symposium: COVID-19 and Big Questions of Public Administration

"Symposium: COVID-19 and Big Questions of Public Administration." Asia Pacific Journal of Public Administration, 43(3), p. 130
Research Guides: Profiles in Teaching and Learning with Student Media Projects: Communicating Discipline Research Through Video Podcasts (Vodcasts)

This online gallery highlights a diversity of student created projects that Library Media Services has supported over the years. More in-depth description of each project can be found on secondary pages.
Use of computer technology competencies at the foreign language lessons = Використання інформаційно-комп’ютерних технологій на заняттях з іноземної мови

Kupar M.S. Use of computer technology competencies at the foreign language lessons / M.S. Kupar // Молодий вчений. – 2020. - № 7.1 (83.1). – С. 81-84. – DOI: https://doi.org//10.32839/2304-5809/2020-83.1-21
A Real-Time Two-Stage Detector for Static Monitor Using GMM for Region Proposal

CNN-based object detectors have been widely exploited for vision tasks. However, for specific real-time tasks (e.g. object detection on static monitor), the enormous computation cost makes it difficult to work. To reduce the computation cost for object detection on static monitor while inheriting high accuracy of CNN-based networks, this paper proposals a method with a two-stage detector using Gaussian mixture model for region proposal. We test our method on MOT16 datasets. Compared with original models, the two-stage detectors equipped with Gaussian region proposal achieve a better performance with the mAP increased by 0.20. We also design and train a light-weight detector based on our method, which is much faster and more suitable for mobile and embedded device with little drop in accuracy.
MACHINE LEARNING BASED DATA FUSION SCHEME FOR INTRUSION DETECTION

Interruption recognition framework assumes a significant part in the organization correspondence based applications where the malignant hubs may create enormous volume of traffic to fall the framework. There are different exploration works are presented by various scientists with the end goal of recognition and anticipation of interruption exercises. Quite possibly the most well known methodologies depends on AI strategies. The preparation exactness of AI framework chooses the identification pace of interruption location framework. Addressing the informational collection in the less difficult organization would further develop arrangement execution better. In the current framework Energy aware Fuzzy Data Fusion Framework (EFDFF) that will intertwine the information with the worry of energy factors. Anyway this work needs its exhibition in the event of essence of more repetition and the unessential information in the framework. In the proposed research technique, it is overwhelmed by presenting the original system to be specific Machine Learning based Data Fusion Method (MLDFM). In the proposed research structure at first element determination is done to give the significant highlights by choosing ideally utilizing SVM based particle swarm improvement approach (SVM-PSO). Then, at that point in chosen ideal highlights, weighted Euclidean distance applied to address the multi dimensional highlights in the one dimensional organization. This one dimensional component portrayal of information would be given as contribution to the replicator neural network (RNN) for the grouping precision testing as far as discovering assaults present. This exploration work is assessed in the MATLAB reenactment climate from which it is demonstrated that the proposed research approach prompts give the preferred outcome over the other examination techniques.
LibGuides: Newspapers: Newspapers and News Sites on the Web

To highlight the Reed Database Subscriptions that contain or are Newspapers in a digital format.