Reviewerly/exHarmony huggingface dataset:
Framework for Sentimental Analysis of Twitter Data

Twitter like Micro-blogging sites has become a wide space for individuals or organizations across the globe to express their views and experience in the form of tweets. The surge of data can be processed using Data mining to obtain further understanding about the public opinions. sentimental analysis is used here to search needs by detecting opinions or emotions from the twitter data. Our results show the cleaned texts of individual tweets using R. Sentimental analysis of any keyword that is given by user is processed. Sentimental analysis used here is helpful in binary classification of tweets i.e. Classification of tweets into positive and negative. Consolidated to this we also analyse Multiple sentiments of the tweets. We likewise break down most extreme recurrence of catchphrase utilized in the tweets and its users. Trending hashtags according to location using location ID and pattern match technique is utilized in finding the recurrence of hashtags utilized in a tweet of explicit end client.
An Improved Image Denoising Algorithm in Wavelet Domain

In order to effectively eliminate the random noise in the noise image, based on the principle of Canny operator, an adaptive median filter is used to optimize, and an improved wavelet domain image denoising algorithm is proposed. The algorithm divides the noise image by wavelet decomposition into an approximate component for adaptive Wiener filtering, the detail component is extracted by the Canny operator based on the adaptive median filter, and the processed components are reconstructed to obtain the denoised image. The simulation results show that the proposed algorithm performs well in the random noise, and the PSNR value is greater than 24 dB. In this paper, the PSNR of the noise of the random noise is higher than that of other algorithms, and the maximum is about 12 dB, which verifies the effectiveness of the algorithm. The improved wavelet domain image denoising algorithm can remove the random noise of the image, which is a kind of excellent denoising algorithm.
Intelligent Anomaly Detection Video Surveillance Systems for Smart Cities

With the growing demands of safety for people and their properties, video surveillance has drawn much attention. These requirements have led to the positioning of cameras almost every corner. Smart video surveillance systems can interpret the situation and automatically recognize abnormal situations, which plays a vital role in intelligence monitoring systems. One vital aspect is to detect and alert generation of suspicious events then to notify operators or users automatically. A long time may pass before an event of interest to take place. In such situations, human attention may get diverted and an event of interest may get missed. In such case, video surveillance systems can effectively improve safety and security for the control and management of public areas or personal life. Independent surveillance systems to replace the traditional (human observer-oriented) systems also can relieve the workload of relative personnel.
Test Equating Requirements from an SEM Perspective

"Test Equating Requirements from an SEM Perspective." Multivariate Behavioral Research, 54(1), pp. 147–148
Research on the Method to Measuring Tower Grounding Resistance by Distributing Multi Electrodes around Local Area

The traditional methods of measuring grounding resistance need larger current lead length and long electrodes distribution distance, which brings difficulties to the measurement of tower grounding resistance in mountainous area and dense urban area. The long electrode distribution distance also consumes more manpower and material resources, and increases the economic cost of grounding resistance measurement. In order to reduce the workload of the staff, a new method of measuring tower grounding resistance is needed, which can measure the tower grounding resistance in real-time and short distance. Based on the distribution characteristics of discharge current inside and outside the tower foundation, a new method for measuring tower grounding resistance in local area of the tower foundation is proposed in this paper. This method reflects the actual discharge current to the greatest extent during the measurement process, thus reducing the influence of current distortion in the measurement and improving the accuracy of tower grounding resistance measurement under the condition of distributing electrodes in short distance.
Pseudorange measurement outlier detection for navigation with cellular signals

We present an autonomous measurement outlier detection and exclusion framework for ground vehicle navigation using cellular signals of opportunity (SOPs) and an inertial measurement unit (IMU). The experimental results demonstrate the proposed framework successfully detecting and excluding outlier measurements, improving the position root mean-squared error (RMSE) by 42%. The demo session will showcase work in progress, namely (1) demo (in the form of a video of our experiment driving in downtown Riverside, California) and (2) a poster that includes the navigation framework, the proposed outlier detection method, and the experimental results.
Influencing Factors of Language Attrition and Loss of Aged People and Training Methods

Both individual families and the whole society are being confronted with the influences of aging society which does not only mean population increase but comes with problems of healthcare and social security of the aged people. Owing to their unique linguistic codes, limited access to new media and damages to linguistic function as a result of certain diseases, they often find difficulties in communication with others. Since language is of significance for communication, sufficient attention should be paid to these people’s language attrition and loss. In the paper below, some possibly effective training methods were presented on the basis of a series of investigations, analyses and instrumental inspection in order to reconstruct their social status and values.
Composing new media

This chapter proposes a categorization by discussing some of the observable paradigms of technological ‘extensions’ as found, for example, in works by Mauricio Kagel, Pierre Schaeffer, Bruno Maderna, Renzo Rossellini, Karl-Birger Blomdahl, Luigi Nono, Boris Blacher, and Giacomo Manzoni. While opera composers’ interest in working with both visual projection technologies and modern communication media goes back to the 1920s and 1930s, magnetic tape recording and projection technology appears to be an especially prominent feature in operatic scores only after about 1950. One crucial question is what composers ‘made’ out of the possibilities, or, to put it another way, which concrete dimension of the theatrical media context a composer ‘extends’ by the use of new media. Werner Meyer-Eppler had published his influential study on electric sound generation, electronic music and synthetic speech in 1949, and from 1951 onwards, the Cologne Studio fur elektronische Musik offered sound manipulation and recording facilities based on the combination of subtractive synthesis and magnetic tape technology.
Implementation of Responsive Web Page Layout Based on Media Query and Flexible Box Model

At present, there are various types of mobile terminal devices on the market, and their screen resolutions also vary widely. How to make web pages adapt to different screen resolutions and provide users with a better browsing experience is a problem of web page layout which is urgent to be solved. This paper analyzes and elaborates the current commonly used methods to solve the problem of web page adaptation and their existing deficiencies. Then, aiming at these deficiencies, we put forward a novel mode of responsive web page layout, which uses the media query technology and flexible box model to solve the problem of web page self-adaptation and verify its feasibility and effectiveness through the practice based on this mode.
Analysis of Korea-Massive Open Online Courses in medical and dental education

Other SectionsAbstract서 론이론적 배경대상 및 방법결 과고 찰AppendixACKNOWLEDGEMENTSCONFLICTS OF INTERESTFiguresTablesReferences
JUNIOR PUPILS’ POTENTIAL TO ACHIEVE INTERDISCIPLINARY EDUCATIONAL RESULTS WHEN WORKING WITH TEXTS

The article is devoted to the relevant problem of forming junior pupils’ interdisciplinary skills. This problem can be efficiently solved by using the potential of working with texts at the primary school lessons (Russian Language, Mathematics, Surrounding World). The paper examines some peculiarities of working with texts in the context of the Federal State Educational Standard of Primary General Education in accordance with the system-activity approach helping to ensure pupils’ success in mastering all the subjects.
Fast Extraction of Pedestrian Candidate Windows Based on BING Algorithm

In the field of industrial applications, the real-time performance of the target detection problem is very important.The most serious time consumption in the pedestrian detection process is the extraction phase of the candidate window.To accelerate the speed, in this paper, a fast extraction of pedestrian candidate window based on the BING (Binarized Normed Gradients) algorithm replaces the traditional sliding window scanning.The BING features are extracted with the positive and negative samples and input into the two-stage SVM (Support Vector Machine) classifier for training.The obtained BING template may include a pedestrian candidate window.The trained template is loaded during detection, and the extracted candidate windows are input into the classifier.The experimental results show that the proposed method can extract fewer candidate window and has a higher recall rate with more rapid speed than the traditional sliding window detection method, so the method improves the detection speed while maintaining the detection accuracy.In addition, the real-time requirement is satisfied.
Dimensional Investigation Of Corrugated Steel Silo With 4650 Tons Storage Capacity

One of the failure modes of the silo structure is tearing due to the slope of the silo, which is caused by radial and gravitational forces. Therefore, dimensional measurement of silo becomes a major aspect for predicting the silo conditions. This paper presents a dimensional measurement of silos use a portable laser distance meter (LDM). Measurement process were performed on silo with a capacity of 4650 tons of grain with diameter 19000 mm and height 20000 mm. The silo walls use corrugated steel panels that joined by bolt connection. Measured steps are: LDM calibration, vertical wall measurement, plotting data and then interpretation of silo roundness condition. The results show that at 0% loading capacity, the diameter of the silo at highest position is smaller than the lowest position. However, at 100% of loading capacity deformation of the wall of the silo is occurred. At a height of 18 mm, the maximum displacement of walls reaches 300 mm.
Secure Online Voting System Using Blockchain

ONLINE VOTING SYSTEM is an online voting technique. In this system people who has right to vote in any place and whose age is above 18 years of any gender can cast his her vote online without going to any physical polling station. The main goal of voting is to come up with leaders of the people's choice. Elections in democratic countries have many issues affecting the fairness of election results. Firstly, some people do not care to vote for a variety of reasons, including lack of faith in the system and believing that the effort is not worth it. Secondly, troublesome voter-ID laws prevent citizens from voting if their ID fails to meet the requirements at the polling booth. Thirdly, voter fraud exists, where dishonest voters manage to vote multiple times for the same candidate, skewing the results. Fourthly, voting machines could be outdated and its accuracy cannot be guaranteed. Lastly, long voting lines at polling booths can discourage people from voting. Recently, much discussion and controversy arose on the missing votes of citizens in elections. Conducting elections through a DApp on the Ethereum platform can provide transparency, security and credibility to the process. This would prevent voter fraud as one voter can only have one ID and all polling systems are on the blockchain, which can identify duplicate attempts to vote . Governments can also save the logistics costs of holding physical polling booths and counting votes.
Model-based computed tomography image estimation: partitioning approach

There is a growing interest to get a fully MR based radiotherapy. The most important development needed is to obtain improved bone tissue estimation. The existing model-based methods perform poorly on bone tissues. This paper was aimed at obtaining improved bone tissue estimation. Skew-Gaussian mixture model and Gaussian mixture model were proposed to investigate CT image estimation from MR images by partitioning the data into two major tissue types. The performance of the proposed models was evaluated using the leave-one-out cross-validation method on real data. In comparison with the existing model-based approaches, the model-based partitioning approach outperformed in bone tissue estimation, especially in dense bone tissue estimation.
On the learnability of implicit arguments

It has been argued that the experiencer argument of seem is always syntactically projected, and should thus induce an intervention effect even when not overtly produced. The results of our experimental study provide evidence for this claim – English-speaking children perform poorly on raising with seem, whether the intervening experiencer argument is overt or implicit. Conversely, Spanish-speaking children show adult-like performance with the raising semi-modal verb parecer ‘seem’, which does not take an experiencer argument. This outcome raises questions regarding learnability, i.e. English-speaking children must know to project an implicit experiencer with seem, while Spanish-speaking children must not do so with the functional verb parecer. In this paper we provide a learning path that resolves this learning challenge.
Enumerating Subsequences of a Sequence and Paths of a Tree in the Order of Weight

The following two enumeration problems are addressed: (i) given a sequence A of n real numbers, the subsequences of A in the order of their weight (or sum), and (ii) given an n-vertex edge-weighted tree T, the paths of T in the order of their weight. We show that both enumerations (i) and (ii) can be done in O(nSUP2/SUP log n) time and the data structures for (i) can be constructed in O(n log n) time using O(n) space, and data structures for (ii) can be built in O(n log n) time using O(n log n) space.
Identification of Conclusive Association Entities by Biomedical Association Mining

Conclusive association entities (CAEs) in the title and the abstract of an article a are those biomedical entities (e.g., genes, diseases, and chemicals) that are specific targets on which conclusive findings about their associations are reported in a. Identification of the CAEs is essential for the analysis of conclusive associations, which is a task routinely conducted by many biomedical scientists. However, CAE identification is challenging, as it is difficult to identify the specific entities and then estimate how conclusive the findings on the entities are. In this paper we present an association mining technique to improve CAE identification. The technique is based on a hypothesis: two candidate entities in an article are likely to be CAEs of the article if a strong association between them is mined from a collection of articles. Experimental results show that, by integrating the technique with representative keyword identification indicators, CAE identification can be significantly improved. The results are of technical and practical significance to the indexing, curation, and exploration of conclusive associations reported in biomedical literature.
Punching a Ticket to Cooperstown

When exposed to principal components analysis for the first time, students can sometimes miss the primary purpose of the analysis. Often the focus is solely on data reduction and what to do after the dimensions of the data have been reduced is ignored. The datasets discussed here can be used as an in-class example, a homework assignment, or a written project, with a focus in this article as an in-class example. The data give the students an opportunity to perform principal components analysis and follow-up analyses on a real dataset that is not necessarily the easiest to handle.
How many climb the matterhorn?

In this demo abstract we present a custom-built low-power geo-phone sensor node which features on-device mountaineer classification using a convolutional neural network. The execution of such a processing-heavy algorithm on an embedded platform is enabled by optimizing the memory requirement of the neural network through advanced quantization and pipelining techniques. As a result, real-time classification with low energy consumption can be achieved.
Supervised Quantum Learning as Quantum Channel Simulation

We propose a formal mapping between supervised quantum learning and the information theoretic notion of channel simulation. The mapping is exploited to define a universal learning machines that can learn from quantum data.
Characterizing the SOM Feature Detectors Under Various Input Conditions

A classifier with self-organizing maps (SOM) as feature detectors resembles the biological visual system learning mechanism. Each SOM feature detector is defined over a limited domain of viewing condition, such that its nodes instantiate the presence of an object's part in the corresponding domain. The weights of the SOM nodes are trained via competition, similar to the development of the visual system. We argue that to approach human pattern recognition performance, we must look for a more accurate model of the visual system, not only in terms of the architecture, but also on how the node connections are developed, such as that of the SOM's feature detectors. This work characterizes SOM as feature detectors to test the similarity of its response vis-á-vis the response of the biological visual system, and to benchmark its performance vis-á-vis the performance of the traditional feature detector convolution filter. We use various input environments i.e. inputs with limited patterns, inputs with various input perturbation and inputs with complex objects, as test cases for evaluation.
Visualising Air Pollution Datasets with Real-Time Game Engines

Visualising Volunteered Geographic Information (VGI), including air pollution data, can be used as an explorative tool in the context of workshops and maker labs. This requires a technology that has a low entry-level, but provides a powerful interactive prototyping framework. We describe the potential of real-time computer game engines as visualisation tools for interdisciplinary cooperation between non-experts and experts. We discuss how properties of air pollution, including invisibility, pervasiveness and its ability to permeate organisms, can be visualised with particle systems, and outline two use cases for different output devices, including AR and VR.
Design and Feasibility Study: Customized Virtual Buttons for Electronic Mobile Devices

Smartphone users often want to customize the positions and functions of physical buttons to accommodate their own usage patterns; however, this is unfeasible for electronic mobile devices based on COTS (Commercial Off-The-Shelf) due to high production costs and hardware design constraints. In this letter, we present the design and implementation of customized virtual buttons that are localized using only common built-in sensors of electronic mobile devices. We develop sophisticated strategies firstly to detect when a user taps one of the virtual buttons, and secondly to locate the position of the tapped virtual button. The virtual-button scheme is implemented and demonstrated in a COTS-based smartphone. The feasibility study shows that, with up to nine virtual buttons on five different sides of the smartphone, the proposed virtual buttons can operate with greater than 90% accuracy.
Phase Analysis Method of Interferometric Pattern Generated for Optical Axis Direction Using Three Laser Beam Interferometry

In this paper, the authors propose a phase analysis method of an interferometric pattern generated for the optical axis direction using three-beam interferometry. Authors perform shape measurement using the proposed method. In three-beam interferometry, the fringe pattern along the optical axis direction appears by superimposing each two-beam interference fringe. Therefore, the power distribution of the fringe pattern appears along the optical axis direction. This method enables us to directly obtain shape and displacement using the interferometric pattern. Our method intended for wide application with 3D shape measurements and out-of-plane displacement measurements for the inspection and maintenance of large constructions. As the first step of developing a device for 3D shape and displacement measurement, in this paper, simulation and an experiment were used to confirm that interferometric pattern for optical axis directional appeared. Further, slope of object was measured from the phase shift of optical axis directional pattern.
Expressive Malay Online Speech Interface (EMOSI)

Speech Synthesis plays an important role in enhancing human-machine interaction. In recent decades, researchers are paying more attention on the emotional expression in the synthetic voice. This is because the appropriate emotion can help improve the naturalness of the synthetic voice and thus increase its acceptability by the public. This project aims at developing a HMM-based Malay emotional speech synthesizer that is practical to be deployed in real life application. In order to make it applicable to the public, an Expressive Malay Online Speech Interface (EMOSI) that is able to synthesize any form of Malay text input in different expression will be created.
Pre-Training a Neural Model to Overcome Data Scarcity in Relation Extraction from Text

Data scarcity is a major stumbling block in relation extraction. We propose an unsupervised pre-training method for extracting relational information from a huge amount of unlabeled data prior to supervised learning in the situation where hard to make golden labeled data. An objective function not requiring any labeled data is adopted during the pre-training phase, with an attempt to predict clue words crucial for inferring semantic relation types between two entities in a given sentence. The experimental result on public datasets shows that our approach achieves similar performance by using only 70% of data in a data-scarce setting.
Discourse Functions of actually in College English Textbooks

This study analyzes the discourse marker (henceforth DM) 1) actually in college English textbooks (henceforth CETs) which have been most commonly used...
Visualization Analysis of the Research Field of the Water Resources in China Based on Cite-Space

Based on the papers published in the Web of Science database from 1949 to 2018, this paper draws a scientific knowledge map of the researches on the water resources in China with the help of the Cite-Space visualization function, focuses on combing the research hotspots and the knowledge evolution of the water resources in China, summarizes the relevant theoretical framework, and puts forward suggestions for the further research of the water resources in China.
Metalanguage of Syntactic n-gram Representation

The question arises, how to represent non-continuous syntactic n-grams without resorting to their graphic form? Recall that continuous syntactic n-grams are simply sequences of words (obtained by following paths in a syntactic tree), but the case of the non-continuous syntactic n-gram is rather different.