Reviewerly/exHarmony huggingface dataset:
The Use of Microsoft Office 365 In Mathematics Learning During The COVID-19 Pandemic

Abstract. The Covid-19 virus is currently sweeping the world, including Indonesia. The COVID-19 pandemic has changed various aspects of human life today, especially in the world of education. This requires all elements of education to be able to adapt in the process of learning activities. One of the effective solutions in implementing learning during this pademic period is online learning. Online learning is carried out to activate classes even though schools have been closed considering the time and place they are at risk during this pandemic. The teaching and learning process which is usually done face-to-face in the classroom must now be done through distance learning. This is done to support the government's efforts to reduce the rate of spread of the COVID-19 virus. The government has established policies for studying from home, working from home, and praying at home, for this reason this policy must really be implemented by the entire community. The learning process from home can be done through online or distance learning with the use of information and communication technology, one of which is the use of Microsoft Office 365. This study aims to determine how the use of Microsoft Office 365 in learning mathematics during the COVID19 pandemic, so the results of this study It can be used by teachers as a reference in the use of media for online mathematics learning and teachers become more concerned about the various obstacles experienced by students. The method used in this research is literature study, which examines relevant previous studies and concludes based on the results obtained. The results of this study indicate that there are several obstacles experienced by teachers and students in the use of Microsoft Office 365, namely bad signals, servers down and difficult to access, additional internet quota costs, unlimited teaching hours, lack of communication and socialization between teachers and students, mastery in Microsoft Office 365 usage which is still low. In addition, the use of Microsoft Office 365 learning activities can be varied by using the features provided, such as conducting video conferencing, holding online quizzes, giving assignments, there is also a whiteboard application that can be used when learning with video conferencing via Microsoft Teams, especially in learning mathematics, so that the learning carried out is not much different from face-to-face learning in the classroom, it's just that it is implemented in a different room and virtual. There are still a lot of features in Microsoft Office 365 that can be used in the learning process, so that learning activities are not boring. Then it can reduce costs (fees) for out-of-town teachers and teaching time to be flexibility, making it easier to update teaching materials and check assignments. So it can be concluded that the Covid 19 pandemic has had various impacts on the use of Microsoft Office 365 in learning mathematics.
Analysis of Students’ Speaking Ability in Video Project at STKIP Muhammadiyah Muara Bungo

The current advancement of vlogs in YouTube channel has challenged lecturers to make use of its potential for students' speaking enhancement.This research was aimed to investigate students' speaking ability seen from their video projects.These video projects were vlogs made by the first semester students of English language education department academic year 2019/2020 of STKIP Muhammadiyah Muara Bungo as the assignment in Basic Spoken English class.Descriptive quantitative research was used in order to investigate the improvement of students' speaking ability.There were 27 vlogs that became the data for this research.They were from three different assignments from nine students who were categorized from three different level of English proficiency (high, average, and low).Scoring rubric for speaking proposed by Brown and Abeywickrama [1] was used.The result showed that the students spoke confidently.However, their speaking ability was varied; some students had an improvement whereas others did not.Mastering grammar and vocabulary became the most influencing factors in the improvement of the speaking ability based on the data gathered.It means that the use of vlog as the video project assignment is more effective if the students master in grammar as well as/and have enough vocabulary related to the topic discussed, so that their speaking ability improves.
Assessment of Levels and Ecological Risks of Some Selected Potentially Toxic Metals in Soils around Onne Dumpsite, Rivers State, Nigeria

The concentrations of selected potentially toxic metals and other soil physico-chemical variables in soil receptacles of a solid waste dumpsite at Onne, Nigeria were assessed to ascertain the levels of contamination and ecological risks. Surface soils (0 – 20 cm depth) from four sampling areas (north, south, east and west) of the dumpsite were analyzed for Cd, Pb, Ni, As and Cr, using atomic absorption spectroscopy. Single and integrated ecological risks indices were calculated using established models. Results revealed the mean values (mg/kg) of Cd (1.00 – 3.09), Pb (125.37 – 285.48), Ni (10.37 – 16.17), As (0.26 – 0.87), Cr (52.16 – 77.17). Assessment of ecological risk indices for north, south, east and west showed {PLI (2.38, 1.27, 1.17 and 1.33), EF (1.01, 16.0, 13.90 and 56.0), Cd (21.50, 11.10, 9.49 and 10.90), PERI (392.0, 132.0, 148.0 and 157.0), PIAvg (5.17, 2.55, 2.27 and 2.56), PINemerow (7.75, 3.80, 3.18 and 3.38) } respectively. These implied that the soils around the dumpsite area were polluted due to enrichment of the selected metals and therefore of low quality. Ecological risk reduction strategies were also recommended.
Beautiful Neduvangiyam also known as Nagasuram

The purpose of this study is to understand one of the earliest known non-brass double-reed instrument called Nagasuram (Nadaswaram). Our ancestors while defining Tamil music grammar in parallel focused on sound engineering, which helped them to invent new musical instruments. Sangam era alone saw more than 30 percussion and wind instruments. Among them, few instruments like Veenai, Urumi and Nagasuram are worth mentioning since their design techniques were known only to a handful of families. Their performance really stands out due to their versatile and adaptable nature to all genres of music. Music instrument, like any other scientific invention goes through the same process of trial and error before getting standardized for general use. Instruments with strong adherence to scientific and acoustic principles gain prominence among the rest, as they undergo minimal structural changes. Nagasuram (Nadaswaram) is one such instrument, which was passed on to us for generations. This instrument readily complies with acoustic principles such as sound impedance, Helmholtz resonance, wave theory etc. to get the characteristic of a loudest non-brass wind instrument.
Water Balance Supporting the Irrigation Water Demand in Java Island, Indonesia

Java is the most populous island with the largest percentage of rice fields in Indonesia. However, rice fields in Java Island often experience water shortages, so an analysis of the potential water availability for irrigation in Java is required. This research aims to analyze water's potential to meet irrigation water needs in each catchment area in Java. In this research, the potential for irrigation water in Java is calculated based on the balance of water balance between water availability and DMI and Irrigation water needs. This research is divided into two parts: (1) analysis of water availability using the WFLOW hydrological simulation; and (2) water demand analysis based on population statistical data. Based on this research, it can be concluded that the water balance between water resources and irrigation water needs in Java is still in the surplus category, even though there are deficits in several catchment areas (WS): in the Kepulauan Seribu, Wiso Gelis, and Welang Rejoso WS. WS with the most water availability is generally located in wide (WS) areas, while several WS with abundant water needs is generally located in WS with the densest population. According to The Central Bureau of Statistics (BPS), the agricultural area in Java has decreased by an average of 20 thousand hectares per year, so that the demand for irrigation water on the island of Java will also decrease. Consequently, the excess water potential in Java Island needs to be allocated to meet the needs of DMI, which are increasing every year. In addition, the results also show that the development of irrigation areas in the future should be focused on large (WS) areas that have the potential for significant amounts of irrigation water.
Tailoring effective requirement's specification for ingenuity in Software Development Life Cycle.

Software Requirements Engineering (SRE) process define software manuscripts with sustaining Software Requirement Specification (SRS) and its activities. SRE comprises many tasks requirement analysis, elicitation, documentation, conciliation and validation. Natural language is most popular and commonly used to form the SRS document. However, natural language has its own limitations wrt quality approach for SRS. The constraints include incomplete, incorrect, ambiguous, and inconsistency. In software engineering, most applications are object-oriented. So requirements are unlike problem domain need to be developed. So software documentation is completed in such a way that, all authorized users like clients, analysts, managers, and developers can understand it. These are the basis for success of any planned project. Most of the work is still dependent on intensive human (domain expert) work. consequences of the project success still depend on timeliness with tending errors. The fundamental quality intended for each activity is specified during the software development process. This paper concludes critically with best practices in writing SRS. This approach helps to mitigate SRS limitation up to some extent. An initial review highlights capable results for the proposed practices
Enhancing the students' skill in writing a narrative text using peer-editing

The aims of this research were: 1) to identify whether peer-editing can enhance the students’ skill in writing a narrative text and 2) to describe the situation of the classroom when peer-editing technique is implemented. The method research used was classroom action research which consisted of two cycle. Each cycle consisted of planning, acting, observing, and reflecting. The research subject was the students of grade XI Bahasa dan Budaya of an SMA in Kudus in the academic year of 2019/2020. It comprised of 35 students with 12 boys and 23 girls. The qualitative data were collected by observation, questionnaire, and interview. The quantitative data were collected by conducting tests. The qualitative data were analyzed by condensing the data, displaying the data, and drawing conclusion. The quantitative data were analyzed by comparing the mean score of the students’ pre-test, post-test 1, and post-test 2. The result of the research showed that there were improvements on the students’ skill in writing a narrative text when peer-editing technique is implemented. Keywords: writing narrative text, peer-editing, classroom action research.
Motion Blur Image Restoration by Multi-Scale Residual Neural Network

Abstract Blind deblurring is a basic subject of computer vision and image processing. Motion image deblurring is divided into non blind deblurring and blind deblurring by whether to estimate the blur kernel. Blind deblurring is easy to produce motion artifacts because of the inaccurate estimation of the blur kernel. Non blind deblurring is the best choice for the current blurred image processing. The purpose of this paper is to further improve the definition of blurred image, restore the edge information of contour, and strengthen the repair of texture details. Based on the multi-scale convolution neural network, a multi-scale residual network is proposed, which can comprehensively extract image features, enhance image feature fusion, and constrain image generation by combining multi-scale loss function with anti loss function. The performance of the algorithm is evaluated by testing the peak signal to noise ratio (PSNR) structure similarity and restoration time of the generated image relative to the clear image. This algorithm improves the average PSNR on GOPRO testset, and reduces the recovery time accordingly. It can successfully recover the detail information lost due to motion blur. This algorithm has simple network structure, strong robustness and good restoration effect, and is suitable for dealing with various image degradation problems caused by motion blur.
Smart Cars, Telematics and Repair

Recent years have seen a surge in the use of automotive telematics. Telematics is the integration of telecommunications and informatics technologies. Using telematics in cars enables transmission of data communications between the car and other systems or devices. This opens up a wide range of possibilities, including the prospect of conducting remote diagnostics based on real-time access to the vehicle. Yet, as with any new technology, alongside its potential benefits, the use of automotive telematics could also have potential downsides. This Article explores the significant negative impact that the growing reliance on telematics systems could have on competition in the market for repair services. Our analysis highlights two main areas where the use of telematics for vehicle diagnostics may pose a threat to competition and consumer choice. First, we focus on the manner by which manufacturers communicate with their customers via the telematics system. Due to the special relationship between car manufacturers and their consumers, which is often based on trust and loyalty, alongside the “captive audience” status of drivers, we argue that communications emanating from the car’s telematics system could be deceptive. Second, we explore the negative impact that the shift away from on-board diagnostics to telematics could have on independent repair shops’ access to diagnostic information. Fortunately, the law can adapt to keep pace with these new technological and commercial developments. This Article articulates the combined multi-prong, multi-agency policy approach needed to maintain an effective right to repair cars in the new age of telematics. Among other things, our analysis supports an update of state consumer protection legislation and an increased policing by the Federal Trade Commission of practices employed by car manufacturers. In addition, we highlight the need to consider certain amendments to intellectual property laws that effectively aid car manufacturers in maintaining exclusive control over their telematics systems and diagnostic data.
Creating and Comparing Dictionary and Word Embedding Models to Measure Discrete Emotional Appeals in German Political Text

Previous research on emotional language relied heavily on off-­the-­shelf sentiment dictionar­ies that only measure negative and positive tone. These dictionaries are often tailored to non­-political domains and use bag­-of-­words approaches which come with a series of disadvantages. This paper creates and validates a (1) novel emotional dictionary specifically for political text and (2) word embedding models combined with neural­-network classifiers that overcome lim­itations of the dictionary approach. Both tools can measure emotional appeals associated with eight discrete emotions. The different approaches are validated on 10,000 crowd­-coded train­ ing sentences. The results highlight the strengths of word embeddings, but also important differences between both approaches. Furthermore, both approaches outperform widely used off­-the-­shelf dictionaries in measuring emotional language in German political communica­tion.
THE APPLICATION OF NAVIGATION SYSTEM BASED ON THE AUGMENTED REALITY TECHNOLOGY FOR THE SURGICAL TREATMENT OF ORBITAL TUMORS

Objective. To assess the effectiveness and feasibility of using an intraoperative navigation system based on augmented reality technology in the surgical treatment of intra-orbital tumors. Methods. Two patients with intra-orbital tumors were operated on with the application of the intraoperative navigation system. The virtual volumetric model was designed on the basis of files in the Digital Imaging and Communications in Medicine (DICOM) format, taking into account the fact that the quality of reconstruction depends on the quality of the input data and the accuracy of the reconstruction system. The required structures and parameters of color rendering for inclusion in the model were selected taking into consideration a specific clinical situation. Then the model was subjected to processing and modification to facilitate visualization. The prepared and optimized model was loaded into Microsoft HoloLens2 augmented reality glasses. In the preoperative period, using the possibilities of full screen image zoom and rotation of 3D model, the planning of the surgical intervention was carried out with the participation of all members of the surgical team. Intraoperatively, a 3D skull model was superimposed on the patient along bony landmarks (lower orbital edge and nasal bones). Surgical access and surgery were performed in the projection of the visualized tumor. Results. In the first case, the surgical planningas the preoperative method of pre-visualising asurgical intervention was used by means of the possibilities of model zooming and rotating; a detailed preoperative tumor assessment was made. In the second case, the navigation system was used in the process of diagnostic orbitotomy to facilitate the access to the tumor. Conclusion. Augmented reality allows highly detail visualization of individual anatomical models. Models are interactive, adaptive to real time and manipulating does not require the special skills. The technologies are flexible and can be programmed to perform a number of tasks (diagnostics, preoperative planning and intraoperative navigation). Models might be used for surgical training of surgeons to possess the skills. What this paper adds For the first time, the possibility of a navigation system application based on augmented reality technology in the surgical treatment of intra-orbital tumors has been shown. The technique has been found to be useful both in the preoperative planning and during surgical intervention.
IDENTIFICATION OF DAMAGE GEAR LANDING SYSTEM OF CESSNA AIRCRAFT

Designing a system to identify damage based on damage symptom data, so as to get repair handling in accordance with the procedure using a forward chaining expert system, where the expert system is one of the computer systems that aims to solve problems by imitating the human mindset as an expert applied to one of them. Aircraft components that are frequently maintained and damaged are found, namely the landing gear of the Cessna Grand Caravan C208-B aircraft. In the process of making the damage identification system in this final project, the UML (Unified Modeling Language) modeling paradigm and the PHP programming language are used. From the research results, the landing gear damage identification system of the Cessna Grand Caravan C208-B aircraft using a forward chaining expert system can facilitate the search for damage and handling for users or technicians in dealing with a symptom that occurs in the landing gear of the Cessna Grand Caravan C208-B aircraft
Semantic-aware transformation of short texts using word embeddings: An application in the Food Computing domain

Most works in food computing focus on generating new recipes from scratch.However, there is a large number of new online recipes generated daily with a large number of users reviews, with recommendations to improve the recipe flavor and ideas to modify them.This fact encourages the use of these data for obtaining improved and customized versions.In this thesis, we propose an adaptation engine based on fine-tuning a word embedding model.We will capture, in an unsupervised way, the semantic meaning of the recipe ingredients.We will use their word embedding representations to align them to external databases, thus enriching their data.The adaptation engine will use this food data to modify a recipe into another fitting specific user preferences (e.g., decrease caloric intake or make a recipe).We plan to explore different types of recipe adaptations while preserving recipe essential features such as cuisine style and essence simultaneously.We will also modify the rest of the recipe to the new changes to be reproducible.
Syntactic Nuclei in Dependency Parsing – A Multilingual Exploration

Standard models for syntactic dependency parsing take words to be the elementary units that enter into dependency relations.In this paper, we investigate whether there are any benefits from enriching these models with the more abstract notion of nucleus proposed by Tesnière.We do this by showing how the concept of nucleus can be defined in the framework of Universal Dependencies and how we can use composition functions to make a transition-based dependency parser aware of this concept.Experiments on 12 languages show that nucleus composition gives small but significant improvements in parsing accuracy.Further analysis reveals that the improvement mainly concerns a small number of dependency relations, including relations of coordination, direct objects, nominal modifiers, and main predicates.
Embedding, aligning and reconstructing clinical notes to explore sepsis

Abstract Objective Our goal was to research and develop exploratory analysis tools for clinical notes, which now are underrepresented to limit the diversity of data insights on medically relevant applications. Results We characterize how exploratory analysis can affect representation learning on clinical narratives and present several self-developed tools to explore sepsis. Our experiments focus on patients with sepsis in the MIMIC-III Clinical Database or in our institution’s research patient data repository. We found that global embeddings assist in learning local representations of clinical notes. Second, aligning at any specific time facilitates the use of learning models by pooling more available clinical notes to form a training set. Furthermore, reconstruction of the timeline enhances downstream-processing techniques by emphasizing temporal expressions and temporal relationships in clinical documentation. We demonstrate that clustering helps plot various types of clinical notes against a scale, which conveys a sense of the range or spread of the data and is useful for understanding data correlations. Appropriate exploratory analysis tools provide keen insights into preprocessing clinical notes, thereby further enhancing downstream analysis capabilities, making data driven medicine possible. Our examples can help generate better data representation of clinical documentation for models with improved performance and interpretability.
Topic Modeling for Maternal Health Using Reddit

This paper applies topic modeling to understand maternal health topics, concerns, and questions expressed in online communities on social networking sites. We examine Latent Dirichlet Analysis (LDA) and two state-of-the-art methods: neural topic model with knowledge distillation (KD) and Embedded Topic Model (ETM) on maternal health texts collected from Reddit. The models are evaluated on topic quality and topic inference, using both auto-evaluation metrics and human assessment. We analyze a disconnect between automatic metrics and human evaluations. While LDA performs the best overall with the auto-evaluation metrics NPMI and Coherence, Neural Topic Model with Knowledge Distillation is favorable by expert evaluation. We also create a new partially expert annotated gold-standard maternal health topic