Reviewerly/exHarmony huggingface dataset:
Multi-source Data in the Geological Disasters Early Warning for Power-Grid

Abstract：In China, the frequent occurrences of geological disasters have negative effects on the people's production, life and many other fields.In the field of power-grid constructions, due to the long-term exposure of power-transmission lines to the natural environment, severe natural disasters, such as heavy rains, landslides, and collapses, will put power-transmission lines in great dangers, and will cause a lot of property loss.Therefore, the effective detection and the early warning of geological disasters are valid approaches to improve the governance and management of geological disasters.First of all, this paper analyzes the characteristics of the prevention and control of power-transmission lines, and then puts forward the main data affecting the early warning of geological disasters, which provides a theoretical basis for further realizing the early warning of geological disasters.
Data Mining Course in the Undergraduate Computer Science Curriculum

Data Mining combines tools from statistics, neural networks, and machine learning with database management to analyze large data sets.It is a well-researched area of computer science with high demand due to its usefulness in any field with large quantities of data where meaningful patterns and rules can be extracted.Therefore, many organizations and businesses can benefit from Data Mining techniques as these organizations record a massive amount of data daily.The field of Data Mining is growing rapidly and there is increasing interest in providing students with a foundation in this area.It is crucial that the emerging field of Data Mining be integrated into the Computer Science curricula.This paper will study different approaches that are used by different institutions of higher education to integrate Data Mining concepts into their curriculum.We use this data to make recommendations of how it should be taught in the undergraduate computer science program and what to include in course(s) in general and specifically in our institution.
Design of Online Pollution Source Monitoring System Based on Internet of Things

At present, the automatic water environment monitoring sensors are generally expensive and have a large maintenance workload. The monitoring methods adopted for the environment are still mainly manual monitoring, supplemented by a few automatic monitoring points. The frequency is low, the data representation is poor, and there is no immediate and true reflection of the water environment. It is be found that the environmental problems are very backward, resulting in the science and accuracy of environmental management Refinement is difficult to guarantee, and the cost of later management is very high. The system integrates sewage and flue gas online monitoring devices, sensor networks, data collectors, controllers, etc., obtains data from analytical instruments, and automatically reports the data to the pollution source online monitoring platform of the environmental protection department. Based on the cloud platform architecture, the pollution source online monitoring platform uses the industrial Internet of things to collect emission data, working condition operation data and instrument and equipment operation status data in real time. It also monitors the real-time data of pollution factors of emission enterprises, the status of production and treatment facilities and the status of real-time monitoring instruments. Through big data analysis means and monitoring model, timely find information such as excessive emissions and abnormal treatment facilities, so as the provide data support for environmental protection law enforcement decisions. The public, enterprises, operation and maintenance and law enforcement can all conduct real-time monitoring and management through mobile app. #
Comply with state directory information laws with consent forms, communication

Kristi Wold‐McCormick has been a registrar for the last 16 years, the last four and a half of them as the university registrar at the University of Colorado, Boulder. Before that, she worked in the Registrar's Office at North Dakota State in Fargo. At both institutions, she used PeopleSoft. “A few years ago, we really looked at leveraging the technology in PeopleSoft to modernize paper‐based processes,” Wold‐McCormick said.
Sentiment Analysis for Customer Opinion on Hotel Using Machine Learning Techniques

Opinions from others play a significant part to take our own decision, The people’s opinions, attitudes and emotions are a computational study toward an entity is called as Sentiment Analysis (SA) or Opinion Mining (OM). In today's world, everything like business, organization and even individuals wants to know opinion from public or customers about their presentation, products and about their services which will give clear idea about their product, portfolio in the market and if these services is not up to the mark how their services they improve, so that their business will perform better. To give output as positive, negative or neutral and find the difference of a specified user text or data from the dataset is the main task of the sentiment or opinion analysis. The opinions, sentiments and subjectivity of text are computational treatment in text mining with Sentiment Analysis (SA). With the help of sentiment analysis this paper describe the machine learning classification techniques for hotel reviews for which dataset obtained from Trip advisor hotel reviews website. System got 99.07 % accuracy for MAXENT Classifier with Train size and Test size 80% and 20% respectively.
A Novel Parts of Speech (POS) Tagset for morphological, syntactic and lexical annotations of Saraiki language

One of the important resources required for various Natural Language Processing (NLP) applications like machine translation, information retrieval and text mining, is annotated text corpora. Text corpora annotation process requires parts of speech (POS) tags to mark different parts of text with grammatical annotations in order to identify linguistic properties of a word, sentence or discourse. The process of marking text items is based on two main features 1) grammatical category and 2) context of text (word, sentence or discourse) i.e. relationship with adjacent and related text. Saraiki being one of oldest languages is still resource scarce language in recorded literature as well as in computational context. According to our study, at present, there is no tagset defined for Saraiki language. This work presents first hierarchical POS (MPOST) tag set for the Saraiki language which is designed to be used in morphological, syntactic and lexical annotations of Saraiki language corpora.
Information Sharing

From the first community cybersecurity exercise the CIAS at UTSA conducted in San Antonio in 2002, information sharing has been a key element of the community cybersecurity program. Information sharing is essential in the protection and detection aspects of programs such as the NIST cyber security framework. Information sharing helps to alert other organizations to ongoing reconnaissance and attack efforts by attackers. When it comes to cybersecurity, organizations are not in competition with each other but instead are partners in a mutual defense against attackers. This has not been an easy lesson to learn, and it has taken time, but today, there are many robust information sharing programs that help various sectors and geographic regions to band together to help each other in efforts to thwart attacks against any member of the group. Information sharing is an integral part of the community cyber security maturity model and can in fact help provide a catalyst to launch an overall cybersecurity program for a community.
Analysis on Wavelet Family based Channel Estimation for MIMO-OFDM System

Channel estimation for (MIMO-OFDM) is an important part for present and future generation broadband wireless communications. OFDM, which uses for the spaced subcarriers to improving the performance. The channel estimation schemes based on pilot reduces the transmission rate and spectral efficiency. Many conventional schemes of channel estimation are not effective in reducing noise. It leads to poor quality signals at receiver at final stage. To rectify this problem, in this paper a wavelet family based channel estimation technique, is proposed and analyzed. The proposed research aims to estimate channels and reconstruct signal via wavelet transform, dyadic wavelet transform and fractional spline wavelet transform which enhances the spectrum efficiency and transmission rate. Simulation results shows that the fractional spline wavelet transform performs well for channel estimation and data signal reconstruction.
An Efficient Method for Multiple Face Detection &amp; Recognition

The problem of Face detection and recognition is becoming a challenge due to the wide variety of faces and the complexity of the noises and background of image. In this paper we have used C-sharp and Haar algorithm to detect the face. First in this paper the image is taken with a web-camera, storing it in the database and then once again when the person comes in the frame the name of the person is displayed. This paper is done in C-sharp which was a bit difficult for us to do and we have combined both the face detection and the recognition. The proposed method has good output and a good recognition rate. The limitation of the paper is that it does not display the name of the person above the face. In the future work will be carried on the above said topic. While developing the code some sample codes in python but those were basic programs. So this paper aims to find a solution for it and developed in C-sharp. In finding the XML file of haarcascade frontal face detection we found some problems and had to do a bit of research in finding it. The code for face detection and face recognition were found in different places and in this paper the codes for the both has been combined and found some difficulty. To overcome the basic programs we have written the code in C-sharp and the difficulty which we faced in combining the two codes have been solved. The solution has been successfully implemented and the code is fully running and the output has been successfully achieved.
Image Forgery Detection Using Dct And Quantization Matrix Techniques

In today’s era the image has become useful for communication purpose. But due to the development of software and various techniques it is possible to change images in adding or removing essential feature from it without leaving a clue of real image. It is not easy for the common people to identify whether the image original or tampered. In order to avoid this problem, forgery detection came into existence. Detection of forgery refers to task of image processing to identify that the images are unique or tampered. Several techniques have been used in order to detect the forgeries from the forged image, but this issue has not yet solved. In order to solve these issues we have used Discrete Cosine Transformation (DCT) and quantization matrix techniques for identifying forged areas of image, where the quality of image is not reduced. The Discrete Cosine Transformation (DCT) is used in order for characterizing the overlapping blocks and quantization matrix is used to compress DCT values and gives both highly compressed and best decompressed image quality. Here we use block matching algorithm. This algorithm one of the most frequently used for detecting image which is duplicate. This proposed work also supports for different kinds of images such as JPEG, JPG or PNG of any size it can be either mxn or nxn.
ADM and LG Chem to Develop Sustainable Technology for Superabsorbent Polymers

Plastics EngineeringVolume 75, Issue 10 p. 44-45 Industry News ADM and LG Chem to Develop Sustainable Technology for Superabsorbent Polymers First published: 02 December 2019 https://doi.org/10.1002/peng.20220Read the full textAboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume75, Issue10November/December 2019Pages 44-45 RelatedInformation
PHYSICS TEACHING COMBINED WITH DIGITAL TECHNOLOGICAL RESOURCES (RTD): the contributions of the Arduino platform in the classroom

This study aimed to identify the literary production on the use of the Arduino platform as a digital technological resource (RED) for teaching physics concepts in high school. This is an exploratory study carried out in databases of recognized scientific journals in the areas of teaching and exact sciences. From the survey of 32 works that were characterized by the scope of this study, fourteen articles stood out that brought the results of experimental projects developed for the teaching of scientific concepts with the help of Arduino. The results of these studies indicated that the use of this RED in the development of experimental activities in the classroom, in addition to providing autonomy and the development of the student's scientific, critical and creative thinking, also proved to be a technologically viable and economically sustainable resource for low cost, but with quality and versatility equal to or greater than commercial options.&#x0D;
Finding Grade Fake and Virus Identifying in Play Store

Deceitful behaviors in Google Play, the leading favored robot application market, fuel search ranking misuse as well as malware proliferation. to spot malware, previous job has actually centred on application practicable and also permission analysis. during this paper, we often tend to introduce Justice, a distinct system that finds and leverages traces left by scammers, to sight each malware as well as applications based on go looking rank fraudulence. Fair game correlates review tasks as well as unambiguously incorporates identified testimonial relations with linguistic and also task signals obtained from Google Play application expertise (87 K applications, 2.9 M evaluations, and 2.4 M customers, gathered over 0.5 a year), to spot suspicious applications. Fair game attains over ninety-five plc. accuracy in categorizing gold normal datasets of malware, unethical as well as Bonafede apps. we tend to reveal that seventy-five plc. of the identified malware apps have interaction in search rank fraud. Fair Play discovers numerous dishonest applications that presently escape Google Baby bouncer's detection innovation. Fair Play furthermore helped the creation of rather one,000 reviews, reportable for 193 apps, that reveal a new sort of "forceful" review project: users are troubled into composing favorable evaluations and also mount as well as assess alternative applications.
Actionable Analytics on Software Requirement Specifications

The volume of data and need for churning this data to provide useful information has increased the scope of data mining and made it promising in recent years. Software intelligence (SI) (as the future of the mining software engineering data) presents theories and techniques to augment software decision making by using fact-based support systems. SI exposes software practitioners to up-to-date and relevant information to support their daily decision activities over the complete software development life cycle. Software documents contain important information for a plenty of software engineering tasks and one such important document is Software requirement specification (SRS) which details the system and user requirements. Inexplicit, ambiguous or imperfect requirements guide leads to a non-acceptable product by users. Constructing of a strong software specification can be supported by building a semantic space, validating new specification for completeness, categorization of software requirement specification and identification of significant concepts and related keywords. This paper proposes a knowledge management system for software document repositories using data analytics and demonstrates its creation and usage for a document set of software requirement specifications.
Creative processes

In this chapter, we look at creative processes that involve computing and data as material. We intentionally put this chapter in the last part of this book, also as a reflective perspective on what we wrote earlier. We emphasized making over thinking in the first two parts; now it’s finally time to explore the framing of this book. We start with the ideation and look at two different approaches before proceeding with abstraction layers and ways to shift technical perspectives within our work.
Application of Grey Catastrophe Theory and Microseismic Monitoring System in Early Warning for Tunnel Landslide

Early warning combined with engineering practices is necessary because landslides generally happen during expressway tunnel excavation.This study proposed a prediction method based on grey catastrophe theory and microseismic monitoring system to realize early warning for tunnel landslides.First, a microseismic monitoring system was installed in the excavated tunnel.Data on the precursory signal of surrounding rock instability such as micro-fracture and deformation caused by tunnel excavation were collected and preliminarily predicted according to the grey theory.Hence, a grey catastrophe prediction model was established to predict the occurrence of disasters.Second, the monitored precursory earthquake source points of instability and damage such as tunnel surrounding rock rupture and deformation were determined according to the basic principle of microseismic monitoring and positioning.Possible locations where disasters could happen were then predicted.Results demonstrate that the predicted landslide time and location of an expressway tunnel are close to the actual situation, and the system can realize accurate warning for tunnel landslides.This study provides a reference for real-time landslide prediction in tunnel excavation.
In Case You Haven't Heard…

The American Psychological Association (APA) has called on Mark Zuckerberg to ban hate speech on Facebook, citing decades of scientific research demonstrating that such speech can cause significant psychological harm to the target audience, observers and society as a whole, an APA news release stated. “We are asking Facebook to act as a leader and intervenor, as opposed to a bystander,” APA CEO Arthur C. Evans Jr., Ph.D., said in a letter to Facebook CEO Zuckerberg. “Facebook's sharing of hate speech not only traumatizes both the intended victim and observers but may also prompt those who see it to become more prejudiced. By not taking corrective action, Facebook is knowingly harming the welfare of consumers, employees and its shareholders.” Experiencing persistent hate speech “leads to people becoming numb to its use and lowers the perceived value and worth of the victims, increasing prejudice,” he wrote. Among the actions the APA is seeking, Facebook should: establish and empower a permanent civil rights infrastructure, create an internal mechanism to flag hateful content automatically and enable individuals who are targets of hate and harassment on Facebook to connect with a live Facebook employee.
Musik für Maschinen?! – Wo sich die Wissenschaft der Medien, des Computers und der Musik treffen und wie sie zusammenarbeiten könnten

Musicology and computer science do not only come together in areas such as the use, analysis and performance of digitized data, but also meet in unexpected places such as in context of critical media studies and inquiries about the material and aesthetic conditions of digitality. Such „exploratory interactions“ with computers and their aesthetics might resonate well with musicology. This mini-contribution firstly presents a historical situation in which for a short period in the 20th century the machinic music of digitality became audible. It then formulates, just as briefly and sketchily, the socio-critical potential of music-oriented approaches, especially rhythm analysis, still to be tested, when it comes to grasp and understand digitality in as many facets as possible (socio-technological, aesthetic, historical and epistemic). Thereby, a fourth partner might be of importance: pedagogy.
Performance based Machine Learning Algorithm for Topic Oriented Text Categorization

With the growth of societal news on the web, public opinions are given major importance in decision-making. Researchers of text-based mining have made number of evaluations and were diversified using different data mining methods so as to make the conclusions positive, negative and neutral. So, opinions of people are considered to mine the social information as people give superfluous interest to the reports. In this paper the newspaper data set is considered to find the opinion mining to evaluate the sentiment. Sentiment Analysis is used to compute the opinions of people before they judge on a particular issue. Machine Learning is one of the important approaches for analysis of sentiments. Different methods like Naïve Bayes, SVM, Maximum entropy and SLDA are used for classifying the sentiments. Predictions based on precision, f-measure, recall are done to determine which method best suits the classification.
The Journal “Librarian” as a Source on the History of Librarianship in Siberia and the Far East of the Pre-Revolutionary Period

The study of the history of librarianship is an urgent task of modern historical and library research. Its solution is possible if a large number of historical sources are identified and analysed. One of them is the pre-revolutionary journal “Librarian”, which differs from other periodicals of that time by its high informative content on the topic. Due to the lack of comprehensive studies of the “Librarian” journal as a historical source, this article for the first time considers this pre-revolutionary professional periodical as a source for studying the history of librarianship in Siberia and the Far East of the pre-revolutionary period. The purpose of this study is to identify and analyse the informative potential of the “Librarian” journal, which is useful for the reconstruction of the history of librarianship in Siberia and the Far East. The methodological basis of the research is based on the principles of historicism, objectivity and consistency. The article uses the methods of source studies, comparative and content analysis. The obtained results show that the journal “Librarian” is an important source for studying the history of librarianship in the Siberian-Far Eastern region. It contains numerous interesting facts about the libraries of the region, their structure and functioning, allows us to identify the sources of their financing and quantitative indicators of work, trace their dynamics, replenish the regional bibliography of special literature and restore the names of benefactors, Siberians and Far Easterners — members of the Society of Library Science. This study fully reveals the informative potential of this periodical, expands the idea of periodicals as important historical sources for the study of the history of librarianship of the country as a whole and its various regions. It can be useful in conducting specific historical studies of librarianship of the country of the pre-revolutionary period.