Reviewerly/exHarmony huggingface dataset:
Pengukuran Tingkat Kebisingan Aliran Sungai Cinangneng-Bogor dengan Menggunakan Aplikasi Sound Level Meter

Noise pollution can come from noise generated by nature, one of which is noise from river flows. Therefore, the aim of this research was to determine whether the sound intensity level of the river flow is still below the threshold value or whether it has disturbed human hearing. The research method used was to measure the sound intensity level of the Cinangneng-Bogor river flow by using a sound level meter application. Measurement of the sound intensity level was carried out at 5 measurement points, namely in the middle of the river flow, on the river bank, at a distance of 5 m, 10 m and 15 m from the river bank to the land. Each measurement was carried out for 120 seconds. The results showed that the sound intensity level of the Cinangneng-Bogor river flow at several measurement points had different values, namely from the middle of the river to away from the river the values were 96.34 DbA, 92.31 DbA, 78.93 DbA, 76.58 DbA and 76.32 DbA. In conclusion, the further away from the noise source, the lower the noise level. The sound intensity in the middle and on the river bank was above the threshold value.
LibGuides: A Guide to TED Talks: Further Research

Welcome, all! This LibGuide will explore TED Talks, the showcase of speakers presenting new ideas in a short amount of time.
Research on Key Technologies of Customer Service Oriented Knowledge Q&amp;A Robot

Dialogue robot, as the entrance service of intelligent system, has received extensive attention in recent years, especially in the field of customer service. Compared with manual customer service, dialogue robot is more efficient, more personalized and lower in cost, and can be expanded in terms of knowledge reserve and business scope. In this paper, based on the background of operation and maintenance customer service in electric power industry, the knowledge of electric power operation and maintenance is managed and serviced based on knowledge map and Text2SQL technology, and the scalable quick knowledge Q&A service is realized, which is integrated with the business system in the form of dialogue robot. In this paper, the related technologies of knowledge Q&A robot are studied and implemented.
Efforts to Improve students Learning Outcomes By using Google Classroom Covid 19 The subject Teorema Phytagoras

AbstrackTeachers and lecturers are educational, but have duties, among others, to improve performance in classroom action research in improving student learning outcomes for mathematics subjects. This research is a PTK which is often called PTK by using the Lut lewin model which consists of four stages 1. Planning 2. Action 3. Observation and 4 Reflections. The purpose of this research is to improve student learning outcomes by using google classroom for class VIII at SMPN One Atap Kandang Kapongan, Situbondo Regency. The number of students is 20 students. In data collection techniques using observation, documentation and tests and analysis techniques through models with the order of presenting information and drawing conclusions. The results of this study were to improve student learning outcomes for the subject of the Pythagorean theorem, this can be seen from the results of the percentage of student learning outcomes in cycle I reached 60% while cycle II reached 85% so that student learning outcomes tied 20% with KKM number 70 out of 100. of the complete cycle I, there are 12 students while cycle II 17 students. So it can be concluded that usinglearning media google classroom can improve student learning outcomes with the subject of the Pytagoras Theorem for class VII SMPN Satu Atap Kandang, Situbondo Regency 2020-2021.Keywords: learning outcomes, google classroom, Phytagoras
"Digital Generation" Utilization of Smartphones as Media for Student Learning Reading

This study aims to improve students 'understanding of learning to read by utilizing smartphones as learning media and to see students' responses to learning by using learning media. The research method used in this research is observation to observe the learning process, tests to determine students' understanding of learning to read, and a questionnaire to see student responses. The results that have been obtained in this study are: 1) Students are more enthusiastic and active when following the teaching and learning process, 2) the results of the test are 17 students (85%) who are complete and 3 students (15%) who are not finished, 3) Sawang Elementary School 25 students' responses to smartphone-based learning media with good categories, which means the media is effectively used as a learning medium.
Dispersive coupling between MoSe2 and a zero-dimensional integrated nanocavity

We demonstrate dispersive coupling between the neutral exciton in monolayer MoSe 2 and a zero-dimensional, small mode volume nanocavity with an estimated exciton-cavity coupling of ∼ 4.3 meV and a cooperativity of C ∼ 3.4.
THE INFLUENCE OF LIBRARY PROMOTION ON PUBLIC READING INTERESTS IN REGIONAL GENERAL LIBRARY IN TIDORE ARCHIPELAGO

The aim of this study was to discover how much influence of library promotion on public reading interests in the public library in Tidore and the promotion that have been carried out by the library. This study used quantitative descriptive research method. The population of this study was the public users/visitors of the library and 64 employees of the library. Sample was taken randomly (accidental). Data collection technique was conducted by using interview and questionnaire. The product moment correlation formula was used as data management. According to the hypothesis testing of the two variables, namely variable X (promotion) and variable Y (reading interests), it has a correlation test of 0.980 (positive). Based on the result of the data correlation using product moment at the 1% level (99% of significance level), the correlation coefficient of r correlation was 0,612, while the correlation coefficient based on the table was 0,317. This result showed that the correlation coefficient was greater than the coefficient correlation based on the table for significance level 99% (0,980>0.317). The result of t-test analysis at 1% level (significance level 99%) found that the value of t-test was greater than the value of t-table (7,217>2,704). Both of the tests showed that there was a positive and significant correlation between library promotion and public reading interests in public library of Tidore.
Macdonald-Kelce Library: Databases for On-Site Public Users: Computer Science

The lists below include databases that are available to the on-site public users at the Macdonald-Kelce Library
Dempster Shafer Algorithm For Expert System Early Detection of Anxiety Disorders

Anxiety is an excessive anxiety disorder that is often found in psychology. Some people generally do not realize that they may have symptoms of this anxiety disorder. If ignored and continued continuously, it can interfere with one's activities, reduce academic achievement, and disrupt psychological conditions that affect their lives. This expert system for early detection of anxiety disorders is carried out using forward chaining tracing techniques to explore the knowledge base, and the inference motor is the Dempster Shafer algorithm. Dempster Shafer calculation is done by combining symptom pieces to calculate the possibility of the anxiety disorder. This anxiety disorder detection system is built on the web. Then the test is carried out by comparing the value generated by the system with the value generated by two experts. The test results prove that the value generated by the system has a similarity of 85% to the value produced by the two experts. It can be concluded that implementing the Dempster Shafer algorithm for this expert system in the early detection of anxiety disorders is feasible.
Quantum computation and combinatorial structures

This thesis explores the relationship between quantum computation and combinatorial structures, with the goal of improving our understanding of the complexity of quantum computation. We begin by studying the case when the complexity of combinatorial structures can be used to provide evidence for the hardness of classically simulating quantum computations. To this end, we show that the complexity of evaluating multiplicative-error approximations of Jones polynomials can be used to bound the classical complexity of simulating random quantum computations. We then proceed by studying the contrary case, that is, when do the combinatorial structures allow for an efficient classical simulation of quantum computations? We establish an efficient deterministic approximation algorithm for the Ising model partition function with complex parameters when the interactions and external fields are absolutely bounded close to zero. This provides an efficient classical algorithm for simulating a class of quantum computations with bounded interactions between the qubits.In the second part of this thesis, we present some independent results on the efficient preparation of Fock states with a high number of photons from a resource of single photons. These Fock states are a fundamental resource in many quantum information protocols.
LibGuides: STEM Research Project | Summer 2021: Research Materials

Educating Students About the Role of Technology on Selective Attention and Memory project funded by the School of Science AISLE Grant.
Enhancing the operations for Integrity check on Virtual Instance Forensic logs using Cuckoo Filter Trees

Logs can hold pieces of evidence for the crime committed using the resources of the cloud service provider. An oppugner can hire the virtual instances, launch an attack, commit a crime to delete all the contents and close them. In such a case, logs help in tracing the oppugner. To handle such issues, the authors have recommended techniques which aid in validating the logs against tampering. The algorithm takes the advantage of the cuckoo filters that store the hashes of the log chain formed in the implemented system which aids in verifying the integrity of logs. The proposed system assists in proving the integrity of logs in the court of law, and thus making legal trails and prosecuting the oppugner or the criminal in a fair manner. The results observed in the implemented system are very promising and efficient as compared to other systems providing integrity.
LibGuides: Library Induction: Walk through the Library Virtual tour

A hub for everything you need to be introduced to the library. Click on the menu to explore further.
Foreword to the Special Section on Smart Tool and Applications for Graphics (STAG 2020)

This special issue contains extended and revised versions of the best papers presented at the 7th Conference on Smart Tools and Applications in Graphics (STAG 2020), held virtually on November 12–13, 2020. The two selected papers cover two different visual computing domains. The first contribution proposes a novel Level-of-Detail data structure (Motion Tree) to efficiently render motion blur of animated objects, while the second contribution presents an evaluation of current deep-learning based 3D registration solutions.
Enhancement of Mammogram by Hyper-elastic Property of Non-rigid Images: a Histogram Modification Scheme

Mammogram enhancement is of paramount importance for the successful detection of masses and micro calcification. We propose a hyper elastic model based new histogram modification scheme that mimics the deformation property of the breast. Unlike state-of-the-art methods, the advantage of using such model is that the anatomical topology of masses and micro calcification is preserved. Our approach is fully tested on the public available mini-MIAS database. The experimental results has earned higher average value of 7.57 in terms of effective measure of enhancement which clearly outperforms traditional techniques such as histogram equalization (1.13), contrast limited adaptive histogram equalization (6.37),brightness preserving bi-histogram equalization (2.34) and recursive mean separate histogram equalization(6.47). Most significantly, the visual inspection indicates that our method preserves the topological information of malignant breast structures without eliminating relevant image features.
LibGuides: Research Help: Books and eBooks

Use this guide to help you learn about research and perform research yourself for both academic and leisurely activities.
Hubungan Minat Baca Dengan Hasil Belajar Bahasa Indonesia Siswa Kelas V SD Negeri 1 Lepar Pongok Tahun Ajaran 2019/2020

This research was to find out the relationship between reading interest and Indonesian learning outcomes of grade V students of SD Negeri 1 Lepar Pongok in the academic year 2019/2020 which aimed to find out and to describe whether there is a relationship between reading interest and the students' learning outcomes in Indonesian.  This type of research is a correlation research with a quantitative approach. The population in this study was the grade V students of SD Negeri 1 Lepar Pongok, consist of 20 students and the entire population was sampled of the research. The techniques of collecting the datain this study were a questionnaire consisting of 20 statements with the data analysis techniques using the product moment formula.  Based on the calculation and the analysis of the data obtained by rcount of 0.946 and rtable of 0.444 so that Ha accepted. It can be conclude that there is a relationship between reading interest with learning outcomes of Indonesian for grade V students of SD Negeri 1 Lepar Pongok. The higher of the students’ interest in reading, the higher of the students’ learning outcomes.
Development of a Simplified Python Supervisory Control and Data Acquisition System

Supervisory control and data acquisition (SCADA) software has been in use for many years, having been implemented on mainframe computers to manage remote installations such as hydroelectric plants, water treatment facilities, and sewage treatment works. Advances in electronics technology that reduced mainframe computer systems to laptop dimensions, object-oriented programming software advances, and the “unit operations” concepts of chemical engineering now allow the individual experimentalist to create very small, dedicated SCADA systems to interface with equipment on desk- or benchtops, between laboratories, or even between laboratories and mobile, remote, “in-field” experimental setups.
The study of instrument recognition based on convolutional neural network

At present, the digital meter recognition is widely used in the field of power transmission and transformation, but rarely used in the petrochemical industry. This paper combines traditional image processing techniques with deep learning methods and proposes a meter recognition method based on an improved neural network model. By establishing a neural network model architecture, setting up the three convolutional layers and adding a batch normalization processing operation, the digital meters of the oil extraction platform are recognized, and the recognition rate is about 99.17%, which achieve the expectations. Through comparative research, the model constructed in this paper has a higher recognition accuracy and reflects a better recognition effect.
Named entity recognition for weather domain text in Hindi

Named entity recognition (NER) is the process of categorisation of a given entity in texts into a corresponding pre-defined category such as PE for name of the person, LOC for the name of location ...
Dub Essay #2 - U.N.I.T.Y. Sound System

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Operationalization of a Glass Box Through Visualization: Applied to a Data Driven Profiling Approach

The profiles from data-driven profiling applications are a model of the reality. The interpretability of these profiles for end users, e.g. policymakers, is often far from trivial. How and why these models are obtained by the applications are often regarded as a black box. In recent years several profiling applications used by public organizations have led to wrong interpretations of the obtained models and impacted individuals and society adversely. Hence, the research focus has increasingly shifted towards dealing with the trust and interpretability issues of the models. In support of a more careful and proper interpretation of these models, several scholars have advocated a glass box approach that aims at making these models more transparent to end users. In this paper, we operationalize the glass box approach for a Genetic Algorithm (GA) based profiling application. To enhance the interpretability of the models provided by the application, we aim at facilitating the interaction of domain experts with the models. Hereby domain experts can gain insight to the evolvement of the profiles and what happens to the profiles if we change or add a new pieces of information. Adding such an interactive visualization provides more transparency about the derived models, making them more understandable for end users and policymakers. As a result, they can better assess and explain the consequences of those models when they apply to practice.
Design and implementation of a data aggregation system for the 5G network management plane

5G networks have led to an increase in the complexity of the management plane. In order to achieve a smart and efficient management of 5G networks, new monitoring mechanisms are required. The main problem is the huge number of data sources that exist and their heterogeneity, with their own mechanisms and formats to represent the information. We will leverage the ETSI ISG Context Information Management framework (CIM) standard, which will enable high interoperability with other monitoring systems.In this work, we propose a generic architecture which allows us to aggregate and unify all this data to distribute it among interested subscribers with different purposes (e.g., data analysis, visualization). We have developed two prototypes that implement the forementioned architecture: one of them uses a NGSI-LD Context Broker from the ETSI ISG CIM standard, and the other uses Apache Kafka, an event streaming platform, as the distribution broker. We have conducted an experiment involving the two prototypes to compare them and check which fits better in a network monitoring scenario. The results have shown that, while the NGSI-LD Context Brokers are feasible in scenarios with low loads of data, the Kafka solution fits better in scenarios with high loads of data, as it could be the case of network monitoring.Finally, we will develop another implementation of the proposed architecture to be used in a real use case scenario of the monitoring of the 5G network. For the developing of all mentioned solutions, we will use Apache NiFi, a data engineering tool.
A Study of Complex Beginnings Used by Korean EFL Learners in Two different writing genres

The aim of this study is to identify the differences of complex beginnings in two different writing genres, argumentative essays and Introduction section of research proposals, written by advanced Korean EFL learners in an ESP writing class. To do this, 35 first draft of argumentative essays and 35 first draft of research proposals by 35 students were analyzed in terms of quality and quantity of the two writing genres. Of a total of 862 sentences in 13,945 words of the 35 first drafts of argumentative writing, 47.3% (408 sentences) of them included adverbials in sentence-initial (SI) position. In case of a total of 411 sentences in 8,577 words of the 35 first drafts of Introduction section of a research proposal, adverbials were found 46.7% of the sentences in SI position. Of the adverbials in SI positions, 5.6% and 5.1% respectively were complex beginnings composed of two adverbials. In order to identify complex beginnings composed of two adverbials in SI position, frequency and preference of conjunctive adverbials suggested in taxonomy types by Quirk, Greenbaum, Leech, and Svartvik (1985) were investigated. In addition, five types of complex beginnings such as stepwise orientations, compound orientation, grounded orientations, complex orientations and composite orientations suggested by Smits (2002) were distinguished. The findings will shed light on the use of adverbials by Korean EFL learners to develop coherent and cohesive relationship among sentences and maintain them throughout the contexts in two different genres.
The phenomenon of distance learning in the context of an anthropological disaster

This paper is devoted to the topic of distance learning for students. This form of training has become common in Russia in conditions of high risk of COVID-19 coronavirus infection. However, there are concerns that distance learning will become the norm. Meanwhile, the consequences of this may be negative, as education, promotion of moral growth of students will become essentially impossible. The entire education system will be reduced to informing students about certain disciplines. Thus, distance learning should not take the form of a daily norm in the education system.
The Sense of Agency of Virtual Hand Representation for Online Shopping

The advancement of virtual reality technology has made real-life manipulation possible in virtual environment since there is a feeling of control, also known as the sense of agency. However, to create a greater virtual experience (e.g., perception of size) of a real-world model (e.g., smartphone) with its model representation in digital or virtual environment (VE) is difficult. For example, the representation model (e.g., in an online shopping website) might visually differ in size compared to the physical world. This study addresses the problem by introducing a calibration method to best match the ratio of virtual hand representation with its associated object in VE and in the real world. This project creates a prototype made by off the shelf motion sensor (i.e., Leap Motion) and Unity software. User can virtually inspect online products as if he is holding the product in the real world. This study evaluates the sense of agency by comparing experience of participants before and after using the proposed prototype. Results showed that the sense of agency is much higher in the proposed method compared to conventional online shopping (i.e., no virtual inspection).
EEG representing on brain surface using volume rendering

Brain research is challenging. One of the standard research methods is electroencephalography (EEG). As a rule, this study is presented in the form of graphs. This article describes an approach in which this data is mapped onto a brain model generated from a magnetic resonance imaging (MRI) scan. This allows you to look at the EEG study from a different point of view. An MRI scan will also allow you to take into account some of the features of the brain. This is an advantage over mapping just to a brain template. This non-invasive system can be implemented to monitor the patient in real-time, for example, during space flight.
Research on Knowledge Innovation Framework Based on Internet of Things and Big Data

Abstract With the continuous development of the society, the trend of world integration has promoted the arrival of the era of big data. Since its inception, the Internet of Things has attracted extensive attention from governments, enterprises and scholars. Relevant standards organizations or research institutions try to formulate unified standards to regulate the application of the Internet of Things, but because the Internet of Things involves a wide range, there is no unified standard for the Internet of Things at present. At the same time, it optimizes the perception layer, information processing layer, network layer, application layer and other levels in the Internet of Things structural system to better enrich the theory of the Internet of Things and apply it in a broader field. Starting from the analysis of the composition of the Internet of Things, and elaborated the specific architecture of the Internet of Things and related technologies.