Reviewerly/exHarmony huggingface dataset:
QED Stonewall Fiftieth Anniversary Exhibition Reviews, Part 2: Editorial Note

Research Article| October 01 2019 QED Stonewall Fiftieth Anniversary Exhibition Reviews, Part 2: Editorial Note Jessica Posner Jessica Posner Jessica Posner is a queer feminist multimedia artist, performer, curator, writer, and educator. Posner practices resilience and radical vulnerability as means for healing the self, body, spirit, and each other. Her ongoing Butter Body Politic (2013—present) project—which involves live performance, video, sculpture, text, participatory workshops, and more—presents butter as a queer, fat, slippery metaphor for a radically feminist body politic. In her Sister Shark (2019) art video/performance, Posner edits all of the men out of the movie Jaws looking for her mother’s five estranged sisters—all of whom were extras in the 1975 classic Spielberg horror film. Posner organized the first Feelings: A Feminist Art Video and Film Festival in 2018. She lives and works in Syracuse, New York. jessicaposner.com. vimeo.com/jessicaposner. Search for other works by this author on: This Site Google QED: A Journal in GLBTQ Worldmaking (2019) 6 (3): 163–165. https://doi.org/10.14321/qed.6.3.0163 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Jessica Posner; QED Stonewall Fiftieth Anniversary Exhibition Reviews, Part 2: Editorial Note. QED: A Journal in GLBTQ Worldmaking 1 October 2019; 6 (3): 163–165. doi: https://doi.org/10.14321/qed.6.3.0163 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All Scholarly Publishing CollectiveMichigan State University PressQED: A Journal in GLBTQ Worldmaking Search Advanced Search The text of this article is only available as a PDF. © 2019 Michigan State University2019 Article PDF first page preview Close Modal You do not currently have access to this content.
IL CEMBALO TRANSALPINO: MUSIC FROM THE FITZWILLIAM COLLECTION Sophie Yates (harpsichord) Chandos 0819, 2019; one disc, 64 mins

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Implementing Quick Response (QR) Codes in Teaching Reading

The purposes of this research were to describe the implementation of Quick Response (QR) Codes in teaching reading, to find out the significant difference between students who are taught with and without using QR Codes, and to know the students’ responses from using QR Codes in teaching reading of English explanation texts to XI class in MAN Kota Tegal in the academic year of 2018/2019. This research used a type of experimental study with pretest-posttest control design. The results of the study described the QR Codes could be implemented in teaching reading as a teaching medium. The steps of applying this medium were (1) asking students to make a group, (2) scanning the QR Code to get reading text and worksheet of assignment, (3) doing the activities stated in QR codes, and lastly (4) discussing the result. Moreover, t-test result showed higher than t-table (4.372 > 2.011). It meant that there was significant difference from experiment and control group. In accordance with students’ responses result, it mentioned that students felt enthusiastic, motivated, and discovered new things during teaching learning process through QR Codes. Therefore, it was suggested to English teacher using QR Codes in teaching reading.
Non Linear CA based Associative Memory Model for Bone Cancer Prediction

Cancer prediction is a real time dynamic problem existing in the real world. The cause and reason for drastic spread of this disease is very difficult to understand. We have various forms and types of cancers, an abstract model to predict cancer is difficult. Although many papers are available to trace cancer, there is still room for evolving a new strategy for predicting cancer. We propose a novel Non Linear CA based associative memory which learns from various case studies analyzing the data and predicts the Bone Cancer. We have taken datasets from ICCR Datasets and processed them using Hybrid Unsupervised learning algorithm. Preliminary work was done and we have compared our work with some standard existing literature. The proposed classifier performance was found promising.
E-author/title information delivery tools in law libraries: a case study of University of Calabar Law Library

This research was carried out to determine the place of e-author/title information delivery tools in the utilization of legal information resources in the law library of the University of Calabar, Nigeria. A total of 200 law students who registered in the law library constituted the population of study. 150 students of the 200 comprised the study sample representing 75% of the population of study. With the survey design research method used for the study. Data was collected through a structured questionnaire. The data collected were analysed using frequency counts and simple percentages..The result showed a very strong and positive use of e-author/title information search engines as delivery tools in the access and utilization of legal information resources in the University of Calabar Law Library.Keywords: impactful, information, processing, utilization, web, publishing
Evaluating Taxonomic Relationships Using Semantic Similarity Measures on Sensor Domain Ontologies

The importance of sensors nowadays is all about the boom of internet of things. Sensors produce a mass of heterogeneous data continuously, and just like the data produced on the web, sensor data lack semantic information. This problem can be overcome with semantic web technologies by designing ontologies to provide a semantic structure of sensor data as well as machine readable data improving the interoperability. Those ontologies must be evaluated to verify their semantic quality and this is where semantic similarity plays its function. Semantic similarity is a metric used to know the similarity degree of two concepts in an ontology. In this research, we propose a system which evaluates taxonomic relationships in ontologies using semantic similarity through an algorithm and the accuracy measure. The applied semantic similarity measures are classified in four categories: structure-based, feature-based, content information and hybrid measures. In this research, we evaluate sensors domain ontologies using semantic similarity measures and we obtained promising results in the evaluation of the taxonomic relationships.
Parallelisation of practical shared sampling alpha matting with OpenMP

In modern filmmaking industry, image matting has been one of the common tasks in video side effects and the necessary intermediate steps in computer vision. It pulls the foreground object from the background of an image by estimating the alpha values. However, the computational speed for matting high resolution images can be significantly slow due to its complexity and computation that is proportional to the size of unknown region. In order to improve the performance, we implement a parallel alpha matting code with OpenMP from existing sequential code for running on the multicore servers. We present and discuss the algorithm and experimentation results from the perspective of the parallel application developer. The development takes less effort, and the results show significant performance improvement of the entire program.
Video7 Extended Architecture: Project Design and Statistical Analysis

The increasing number of both digital audio and video, brings up the necessity of appropriate tools for the storage and management of those kind of data. As options for the storage, there are non-relational databases (NoSQL). The diversity of existing systems provokes the interest in proposing an architecture for the management of that content, in different types of databases. This work deepens the Video7 architecture for storing and retrieving streaming audio and video files stored in non-relational key-value, tabular, document databases. Based on the architecture and suggested project design, a tool was implemented that makes use of the Apache HBase, Apache Cassandra, Project Voldemort, Redis and MongoDB databases, and is subjected to stressful routines. The purpose of stress routines is to measure insertion and queries times, in addition to their transfer rates in response to requests to a media server. The kruskal-wallis test was used to validated the measurements. Redis database presents better performance in the submitted routines, while Project Voldemort and Apache Cassandra perform poorly than other databases.
Subject Guides: The End of EndNote Desktop : Syncing with and Transferring to EndNote Online

AU Library will be canceling our subscription to EndNote Desktop in May 2021. This guide will help EndNote users determine how best to move forward and will include details on maintaining access to the current version of EndNote, as well as how to chose w
An Applicative Study of Advances in Machine Learning

In light of technological advancements abundant data has been flooding the web from varied sources. It hence becomes imperative to draw meaningful insights from this data to give a competitive edge to businesses. The major challenge in this is filtering unessential details from critical data. Machine learning is an applicative science that has optimized algorithms and models for data analysis. This paper focuses on machine learning and its assortment with Artificial Intelligence (AI) techniques for the purpose of data analysis. This paper likewise brings foreword the advancement of machine learning approach and its applications areas by highlighting the ML research done in the area of Student Performance and Cancer patient’s survival predictions.
Synthesize Inductive Invariants by K-means++ and Support Vector Machine

The problem of synthesizing adequate inductive invariants lies at the heart of automated software verification. With the rapid development of artificial intelligence, the state- of-the-art machine learning algorithms for invariants synthesis have gradually been developed and have shown its excellent performance. However, when positive samples are distributed among multiple clusters, the algorithm for intersection of half space based on SVM can not generate the candidate invariants. In order to solve this problem, a new modified algorithm, based on and k-means++ and SVM, is proposed. After sampling, our algorithm adopts k-means++ to cluster the positive samples. Then this algorithm uses SVM to distinguish each positive sample cluster from all negative samples to compute the candidate invariants. Finally, a set of theories founded on Hoare logic are adopted to check whether the candidate invariants are true invariants. If the check succeeds, the true invariants have been found. Otherwise, we should collect more samples and repeat our algorithm. Experimental results show that our algorithm can compute the candidate invariants when positive samples are distributed among multiple clusters.
Research on Academic Achievements of Three Domestic Petroleum Universities Based on PA Database from the Perspective of Language Service

As a sunrise industry, the language service industry has become the focus of domestic academic circles and translation circles in recent years.Petroleum Abstracts database literature resources provide broad and professional coverage for knowing the frontiers and dynamics of the petroleum industry in the world and for studying the petroleum industry dynamics.Based on the macro and micro level respectively, the total items and the categories published by the natural science edition of journal of three domestic petroleum universities included by PA database are analyzed.By comparing the three journals, the published specialty fields are summarized.Thus the reason for the different focuses is explored.The suggestion for the exchange of academic achievements and for the learning of academic frontiers is provided: establish a language service team on campus to facilitate the development of scientific research.
A Kind of Chinese Word Segmentation Algorithm Based on Finite Automaton

Finite automaton can be used in Chinese word segmentation technology. The finite automaton recognizing every kind of words and the Chinese word segmentation algorithm based on the finite automaton were constructed. Chinese word segmentation can be completed by using the word segmentation algorithm based on finite automaton. By example, the efficiency of the Chinese word segmentation can be improved and the part of speech dimension can be completed during segmenting words by using the Chinese word segmentation algorithm based on finite automaton.
Determining the most representative image on a Web page

textabstractWe investigate how to determine the most representative image on a Web page. This problem has not been thoroughly investigated and, up to today, only expert-based algorithms have been proposed in the literature. We attempt to improve the performance of known algorithms with the use of Support Vector Machines (SVM). Besides, our algorithm distinguishes itself from existing literature with the introduction of novel image features, including previously unused meta-data protocols. Also, we design and attempt a less-restrictive ranking methodology in the image preprocessing stage of our algorithm. We find that the application of the SVM framework with our improved classification methodology increases the F1 score from 27.2% to 38.5%, as compared to a state-of-the-art method. Introducing novel image features and applying backward feature selection, we find that the F1 score rises to 40.0%. Lastly, we use a class-weighted SVM in order to resolve the imbalance in number of representative images. This final modification improves the classification performance of our algorithm even further to 43.9%, outperforming our benchmark algorithms, including those of Facebook and Google. Suggested beneficiaries are the search engine community, image retrieval community, including the commercial sector due to superior performance.
Which type of Motion Graphics (2D, 3D and particle animations) should be created in After Effects and Houdini in terms of efficiency?

This is a research about methods of achievingMotion Graphics (2D, 3D and particles) in Houdini and After Effects. These methods were used to compare the level of efficiency in animating in both software programs, which would later analyze what software is more suitable for certain Motion Graphics. The results of this research were then later on optimized to fit into a promotional video serving as a portfolio item to the scientific animation studio, Nymus 3D.
Juries need to be told how they’re allowed to use the internet to ensure fair trials

Juries are supposed to consider evidence without influence or bias from the outside world. However, the widespread access to and use of the internet and social media threatens to undermine this, with significant consequences for our criminal justice system and those within it.Given courts cannot effectively police smart-phone use they must adapt to it. This week the Tasmania Law Reform Institute completed its year long inquiry into courts and the information age, and has recommendations as to how they can adapt.
Big Data Analytics for Crime against Women in the state of Tamil Nadu

In this growing technology field, crime rates are increasing and challenge investigative people's capabilities. Crime data generation is also increasing nowadays. With the use of conventional analytical techniques, data generated today cannot be managed effectively. It would be useful to use Big Data Analytics for that huge data instead of using standard data analysis techniques. Primarily collected data will be stored and frequently occurred data will be displayed. Based on the strong attribute the frequent data is analyzed using Big Data Analytics. Finally, the analyzed data are given as input into the Rattle tool and retrieved the actual result as output. The above pattern helps the police department to identify the criminals in the short span of time.
A Spam Detection Mechamism in Social Media using Soft Computing

Social media is gaining its popularity with growing pace. It is used for sharing information, photos, videos and other useful content in form of messages, reviews, tweets, comments etc.. More than useful information, these messages contained fraudulent content, malicious links, viruses, harassing reviews etc. These activities are increasing in numbers by spammers also called as spam users. They usually create fake profiles which look attractive to legitimate users. So, the detection of spam has become an important requirement now-a-days. An approach is used in the proposed work to detect spam using fuzzy logic and analyze through neural network multilayer perceptron. The motive behind using this approach is to learn and apply the machine learning algorithms, fuzzy logic, and (or) artificial intelligence. Also, it aimed to overcome the limitations of supervised learning algorithm by using semi - supervised approach. It has been found that the fuzzy logic applied has handled the large data set efficiently and consumed less time to detect the spammers within seconds. Thus, reducing the cost, time and need of complex software
Distributed Ledger Technology for Closed Environment

Distributed ledger technology is a system of recording digital transactions in an immutable ledger that is distributed across different locations. It is getting popular day by day not only in the public domain but also among enterprises. Various industry experts are working together to maximize the benefits of distributed ledger technology without affecting their current system flow. Distributed ledger technology not only provides a system of trust between untrusted parties, but it can also be used to improve system security with the use of complex cryptography. Enterprises are interested in distributed ledger technology because it can help in reducing cost and time of transactions but they can’t use public ledgers as transactions and business processes should be hidden from everyone except authorized users only. The heart of distributed ledger technology is consensus algorithms which help in the settlement of transactions. Different consensus algorithms that can be helpful to enterprises are reviewed, analyzed, categorized and simplified flow is shown in pictorial form along with their limitations that helps the enterprise to choose best consensus algorithms for their implementation of distributed ledgers.
A Survey of Approaches for Sentiment Analysis on Social Media

Social network is attaining significant attention in present world. By using these social network platforms such as face book, instagram, twitter through the internet facility, it is becoming our day to day life and more economical as well as very fast access data platform to all of us. However due to the massive data available on social media, there are many issues characterized such as size of the data, noise in the data and many more. Because of these issues data of social media platform becomes complex for analysis or getting the useful information. Anyway there are numerous methodologies accessible for some internet based life stage, for example, Facebook, Instagram, Tumbler and so on, so we can break down these information by utilizing Python, R and a lot more dialects of information investigation. We can recover, break down and decipher this informal community information for research reason or to settle on any future choice. With a huge number of discussions occurring on interpersonal organizations consistently they offer a rich information source that can be gotten to in a relatively easy manner. This paper gives a brief discussion about the approaches of sentiment analysis in which we elaborate about different types of methods in order to perform sentiment analysis on data sets, which is basically related to the twitter data.
ANALISIS KESALAHAN SISWA BERDASARKAN PROSEDUR NEWMAN PADA KEMAMPUAN KONEKSI MATEMATIS SISWA

The aims this research was to analysis students error using Newman Procedure. The subject this research is student of class in X MM1 SMKN 1 Balongan. Many sample were used by 6 student, consist of 2 students with lowest rank, 2 students with intermediate rank, and 2 students with high rank. The result of the analysis show that the average reading error is 38,86%, the average error in comprehension is 39,43%, the average transformation error is 34,86%, the average  processing error is 52,57%, and the encoding error rate is 84,57%. Based on the result of the analysis of the six students, it can be concluded that students rarely write things that are know and asked and rarely write conclusion. This is what causes encoding to always win from the four previous stages.
Online Path Planning of Mobile Robots Based On Elliptic Influence Domain and Improved Artificial Potential Field

In this paper, an elliptic influence domain and improved artificial potential field method (EID-IAPF) is proposed for online path planning of mobile robots. This paper has established a collision risk area model and has obtained dynamical elliptic influence domain of obstacles. Also, the velocity-repulsive potential equation is introduced to modify the traditional artificial potential field method (APF), which improves the capacity of path planning of the robots. Finally, a simulation of complex environment with narrow channels is constructed to verify the feasibility of the method, and to compare with the traditional APF. It proves that EID-IAPF can effectively improve the path planning efficiency of mobile robots.
Aligning IATE Criminal Terminology to SUMO

In this paper we apply an ontology matching system in the context of an information extraction project regarding criminal data. Our data comes from social network, in order to make better sense and analysis of the information provided we consider the IATE (InterActive Terminology for Europe) regarding its crime related sub-domain. The alignment of this terminology to an ontology is a further step towards enriching the semantics of the data. We evaluate a recently proposed domain top ontology matcher (based on Wordnet-SUMO previous alignment) to the task of aligning this IATE sub-domain to SUMO, a general purpose top ontology. Another aspect to explore is the use of multi-linguality in the disambiguation problem itself, as in the case of “alvo” (aim as target and not goal) which becomes more clear in the Portuguese than the English version.
Context in cognitive psychology of reasoning

The work we present aims to clarify what is a context in the cognitive psychology of reasoning. Although the term context is found in the literature of different cognitive psychologists, we will argue that there is no clear analysis of what should be understood by that term. We will defend that the notion of context refers to different ideas, that is, the content, the format, the perspective, the nature of the logical contents and the environment of the problems. We will suggest that while these ideas may have overlaps, it is unclear that content, format, perspective, nature of logical content and environment are equivalent notions. Making these distinctions, we will argue, can not only help you understand what a context means, but it can also help you better understand the debates about how we humans reason or how we should reason.