Reviewerly/exHarmony huggingface dataset:
IP crime and enforcement report 2019 to 2020

Highlighting current and emerging counterfeiting and piracy threats in the UK and overseas, including Trading Standards successful IP cases.
Implementasi Open Gl Untuk Pembuatan Objek 3d

Computer Graphics is a part of computer science that deals with the creation and manipulation of (visual) images digitally. A simple form of computer graphics is 2D computer graphics which later evolved into 3D computer graphics, image-based (image processing), and pattern recognition (pattern recognition). Computer graphics are often also known as data visualization. Graphics include images and other imagery generated by the computer in the form of lines. OpenGL (Open Graphics Library) is an API standard that can be used to create graphics-based applications, both two-dimensional (2D) and three-dimensional (3D). OpenGL is cross-platform, meaning that it can be run on various operating system platforms that exist today. using OpenGL, we first need a conception of the interface in its implementation of object protection. One method that is commonly used is to create a window-based OpenGL. To be able to conceptualize windowing in OpenGL, we need a certain tool. What we are using this time is GLUT (OpenGL Utility Toolkit).
Compose with Sounds, version 2

Compose with Sounds can be used as a stand-along software to those new to making music with sounds; however, it has been created by project director (Landy) and developer (Pearse) as part of the EARS 2 pedagogical initiative (eLearning site). It was created for 11-14 year olds (KS3 in the UK) but for anyone with no or little prior experience in sonic creativity. It has received two EU Culture grants and, within version 2, in 2020 was introduced in ten languages. Version 2 is completely recoded due to issues related to changes on operating systems (Windows, MacOS) and includes several enhancements. Compose with Sounds can be found at ears2.dmu.ac.uk/cws.
Extended Natural Numbers and Counters

Summary This article introduces extended natural numbers, i.e. the set ℕ ∪ {+∞}, in Mizar [4], [3] and formalizes a way to list a cardinal numbers of cardinals. Both concepts have applications in graph theory.
A Language-Based Approach to Smart Contract Engineering

Author(s): Kolb, John | Advisor(s): Culler, David E; Katz, Randy H | Abstract: Blockchain-based smart contracts have emerged as a popular means of enforcing agreements among a collection of parties without a prior assumption of trust. However, it has proven difficult to write correct contracts that are robust when operating in the adversarial environment of public blockchains. This thesis evaluates the ability of a domain-specific contract programming language to support the expression and systematic testing of practical smart contracts. We present the design, implementation, and evaluation of Quartz, a contract language based on the state machine model of execution.The design and evaluation of Quartz is grounded in a suite of case study smart contracts. These are intended to span a wide range of application scenarios and design patterns encountered in practice by contract developers. The language's implementation is organized around the translation of a contract to two targets: a formal specification expressed in TLA+ and an implementation expressed in Solidity. Through its support for model checking contract specifications, Quartz enables the discovery of implementation flaws identical to those that have compromised real-world smart contracts. Moreover, its generated Solidity code imposes at most minor execution overhead compared to equivalent handwritten code. Finally, we discuss Quartz's future potential to validate contracts against economic notions of correctness, which are often central concerns in contract design yet are not addressed by current verification techniques.
Chaotic System and DNA Computing operations for Image Encryption Based on Pixels Shuffling

Image encryption is one of the primary approaches which is used to keep image information secure and safe.Recently, image encryption is turning its attention to combination with the field of DNA computing.In the presented study, a novel method of image encryption is suggested and implemented based on the DNA algorithm and Chaos theory, the most important principle in image encryption is breaking the correlation amongst pixels.This algorithm performs well against chosen cipher-text attacks.Furthermore, the proposed approach was implemented and analyzed for the Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), The performance of the encryption method is analyzed using the histogram, Shannon entropy and key space.
Guides: Business Division Faculty Guide: Contact the Learning Commons!

Provides links to Western Library resources for students and faculty in the Business Division
Designing Animated Video As Education To Prevent Sexual Violence For Elementary School Children

Children is a part of the world as the successor to future generations.Childhood is a phase in which a child experiences growth and developmentwhich determines the future. Education became crucial at that time,attention and affection from parents or family are the basic rights and needsof children to be properly fulfilled. This can be tampered if a childexperiences sexual violence in his life and makes the child physically andpsychologically injured. Children are vulnerable to becoming victimsbecause they have a physical weakness and are still easy to influence but,we can prevent this by inserting good learning and advice so that they candistinguish between types of good and bad behavior. And can make themrecognize the types of sexual violence as well as prevention and how toaknowledge it in the form of animated films that can make them understandbetter because there are examples and good visual forms so they canunderstand it easily.
THE PROBLEM OF THE TECHNOLOGY OF CREATING THE IMAGE OF THE LEADER OF THE EDUCATIONAL INSTITUTION

The article reveals the psychological and pedagogical aspect of the formation of the image in the professional activity of the head of an educational institution, a teacher. The structure of the professional image and the principles of its construction are considered.The article presents the main idea of the science of imageology - as a special science of the man, whose main goal is an individual self-realization. The article presents the analysis and the modern concept of terms as “image”, “professional image”, Image of the head of an educational institution , “image of a teacher”.
Challenges for Cloud Networking Security

Cloud computing has been widely regarded as an appealing server model, as spending and operating obligations are kept to a minimum and costs are directly related to use and demand. However, when considering networking issues for distributed clouds, little support is given, and efforts are often underestimated. This Post Office discusses the new security issues found in SAIL to make fair use of cloud networking services and to avoid misuse. The SAIL initiative focuses on cloud networking and its unified management of cloud computing. The SAIL position paper presents new security challenges for SAIIL. Networks which can be reconfigured easily would allow the full benefits of the cloud world. This is the envisioned concept of cloud networking-it encompasses provisioning of on-demand guaranteed network resources in a time span that is compatible with the allocation of computing resources in a cloud today. While the network issues have not been discussed so far, it is obvious that the perceived efficiency of certain cloud-based apps heavily depends on the network that links the different web sites and connects the consumer with the cloud. Interactive software and greedy bandwidth are a good example of this.
IMPLEMENTASI STAR SCHEMA PADA STUDI KASUS PERPUSTAKAAN BERSKALA UNIVERSITAS

Libraries are service units with high storage complexity as evidenced by more data being stored for each year. The data that is not integrated makes the complex problem because every year the process that is carried out continues to increase, especially for the circulation of loans. As the number of books increases, the circulation of borrowing increases every year. On the other hand, the library must know exactly what collection of books they have and the transactions it has made. A lot of data is owned by the library cannot be utilized optimally, so that the managerial is unable to make full use of the data. In University scale libraries, this problem increases when the data is not fully integrated. In this study, the implementation of a star schema was carried out to solve problems related to data integration using a nine-step methodology, which includes selection, item selection, process dimensions, fact selection, fact storage, ensuring dimension tables, selecting database duration, changing dimensions, determining priorities, and query models. The results of this study indicate that the star schema can be implemented in the case of libraries, data warehouses and OLAP to support decision making for adding books, and produced 3 dimensions of the 4 grains found.
Correction to: Predicting user visual attention in virtual reality with a deep learning model

A correction to this paper has been published: https://doi.org/10.1007/s10055-021-00527-0
Study on Chinese text classification for FastText that combing TF-RF and improved random walk model

FastText is a text classification model by Facebook. As the model is simple in structure, it has the advantage of fast and efficient. However, when the model is used in Chinese text classification, the accurate rate will decrease. To this end, a Chinese FastText text classification method combing Term Frequency-Relevance Frequency (TF-RF) and improved random walk model is suggested in the paper. The method makes TF-R weight choice to N-gram processed dictionaries during the input stage of the FastText model, making semantic analysis by using Probabilistic Latent Semantic Analysis (PLSA), and supplements to feature words; then utilizes the improved random walk model to improve the accuracy, and the improved model is more suitable for Chinese text classification. The experiment result shows that improved model in the paper has a better effect to Chinese text classification.
Research and Implementation of Intelligent Garbage Collection Car System

Abstract With the development of artificial intelligence technology, the conditions for the introduction of intelligent garbage sorting and recycling tools in garbage sorting and recycling have gradually matured. Compared with the traditional manual recycling, intelligent garbage collection tools have considerable advantages in terms of work efficiency, personal safety and virus transmission. In this paper, an intelligent garbage collection system is designed. Through camera tracking, obstacle avoidance by laser radar and other technologies, the garbage in the area to be recycled will be automatically recycled to the designated location, and the operation and loading of the garbage car will be uploaded to the cloud server. Users can view the situation of the intelligent garbage collection system through their mobile phones or web pages.
Large-scale Ontological Reasoning via Datalog.

Reasoning over OWL 2 is a very expensive task in general, and therefore the W3C identified tractable profiles exhibiting good computational properties. Ontological reasoning for many fragments of OWL 2 can be reduced to the evaluation of Datalog queries. This paper surveys some of these compilations, and in particular the one addressing queries over Horn-$\mathcal{SHIQ}$ knowledge bases and its implementation in DLV2 enanched by a new version of the Magic Sets algorithm.
T-Miner: A Generative Approach to Defend Against Trojan Attacks on DNN-based Text Classification.

Deep Neural Network (DNN) classifiers are known to be vulnerable to Trojan or backdoor attacks, where the classifier is manipulated such that it misclassifies any input containing an attacker-determined Trojan trigger. Backdoors compromise a model's integrity, thereby posing a severe threat to the landscape of DNN-based classification. While multiple defenses against such attacks exist for classifiers in the image domain, there have been limited efforts to protect classifiers in the text domain. We present Trojan-Miner (T-Miner) -- a defense framework for Trojan attacks on DNN-based text classifiers. T-Miner employs a sequence-to-sequence (seq-2-seq) generative model that probes the suspicious classifier and learns to produce text sequences that are likely to contain the Trojan trigger. T-Miner then analyzes the text produced by the generative model to determine if they contain trigger phrases, and correspondingly, whether the tested classifier has a backdoor. T-Miner requires no access to the training dataset or clean inputs of the suspicious classifier, and instead uses synthetically crafted nonsensical text inputs to train the generative model. We extensively evaluate T-Miner on 1100 model instances spanning 3 ubiquitous DNN model architectures, 5 different classification tasks, and a variety of trigger phrases. We show that T-Miner detects Trojan and clean models with a 98.75% overall accuracy, while achieving low false positives on clean models. We also show that T-Miner is robust against a variety of targeted, advanced attacks from an adaptive attacker.
Exploring Natural Language Processing Techniques in Social Media Analysis during a Pandemic: Understanding a corpus of Facebook posts using Word2vec and LDA

People around the world have used social media extensively to communicate and express opinions especially during this time of the rapid spread of COVID-19 Nowadays, the various narratives of social media users are important that can be used in creating measures to curb the deadly disease However, the manual collection of data from social media such as Facebook and its analysis can take time Thus, this study attempted to use natural language processing (NLP) techniques such as topic modeling and word embedding to identify the concepts contained in the posts and comments of Facebook users in the Philippines regarding the pandemic This study harvested posts and comments in Facebook groups that are primarily Filipino citizens that express opinions and suggestions in COVID-19 responses Using Latent Dirichlet Allocation (LDA), this study was able to generate 10 topics related to the concepts of (1) self-discipline, (2) prayers for the frontliners, (3) total lockdown, (4) following government guidelines and protocols, and (5) flattening the curve of the disease Meanwhile, word groups generated by Word2vec developed concepts such as (1) mass testing, (2) hope for faster recovery, and (3) expectation from the government The average cosine similarity for word groups is 0 92, which implies strong relatedness of each word per group This study proved that the use of NLP techniques helped in analyzing the themes of Facebook posts and comments related to the pandemic © 2020 ACM
COMPANY ASPECT BASED SENTIMENTAL ANALYSIS OF ONLINE JOB BASED ON REVIEWS

Digital sources like sensible applications opinions and on-line feedback statistics square measure crucial resources to square measure seeking for customers’ remarks and input. These paper pursuits to help authorities entities gain insights on the needs and expectations of their customers. Towards this finish, we propose Associate in Nursing aspect-based wholly sentiment analysis hybrid technique that integrates space lexicons and rules to look at the entities clever apps evaluations. The planned model ambitions to extract the essential factors from the reviews and classify the corresponding sentiments. In this work, we tend to aim to beat the said downside by generating aspect-sentiment based mostly embedding for the businesses by trying into reliable worker reviews of them. we tend to created a comprehensive dataset of company reviews from the notable web site Glassdoor.com and utilized a completely unique ensemble approach to perform aspect-level sentiment analysis. Though a relevant quantity of labor has been done on reviews targeted on subjects like movies, music, etc., this work is that the initial of its kind. we tend to additionally give many insights from the collated embeddings, so serving to users gain a stronger understanding of their choices similarly as choose firms exploitation custom-made preferences. This approach adopts language process techniques, policies, and lexicons to deal with much sentiment analysis challenges, and convey summarized results. in step with the aforementioned results, the factor extraction accuracy improves significantly once the implicit parts square measure thought-about. Also, the incorporated classification version outperforms the lexicon-primarily based mostly baseline and therefore the completely different rules mixtures by means that of fifty in phrases of Accuracy on the average. Also, once exploitation the identical dataset, the pro- expose approach outperforms widget mastering ways that uses Extreme learning machine (ELM). However, the employment of these lexicons and pointers as input capabilities to the ELM version has achieved higher accuracy than completely different ELM models.
Studying The Variables That Impact E-learning as an Educational Alternative During COVID-19

As a result of the worlds exposure to the Corona pandemic, which led to the suspension ofinstitutions of higher education and for maintaining scientific communication with the students,a decision has been made earlierto provide lectures to the students and cooperate with them through electronic media according to the Elearningsystem. In this research, the logistic regression technique is adopted to identify the variables that have aconsiderable impact on E-learning. The variables are divided into eight independent categories. These variables arearranged according to their importance of its impact.The researchis conducted on 325 students of the Technical Institute of Al-Anbar.It is clear that the independent variables, which have a significant effect, are four variables. The correct classification rate for the built model is (80%), and its quality was tested through two tests and its quality was proven.
Illustrative presentation in formation of ESL students’ lexical skills

The article is devoted to the problems of forming and developing lexical skills by modern multimedia means of visualization in the ESL classroom. Modern technologies have been led to new possibilities to integrate multimedia tools and means of visualization in the ESL classroom. The aim of this paper is to analyze the current ESL coursebooks and coursebook supplements and give recommendations to teachers how to use the sufficient range of means of visualization effectively. As a part of research different types of questionnaires were handed to teachers and first-year students of Bachelor’s Program "Pedagogical Education (double major) and Second Foreign language " (5 years, full time) of Kazan State University. After this, a set of classes was organized for two groups of first-year students. The outcomes have been measured with qualitative and quantitative methods. The results show that the teachers do not use means of visualization and are not ready to make them the integral part of everyday lessons due to time management issues, lack of methodical ways of organization of educational process. Due to these results it can be resumed that using multimedia means of visualization as tools in the ESL classroom is highly beneficial for students and enhanced the learning process.
Novel HAAR Based Approach of Criminal Detection

In Today we are living in the world of uncertainty and with the growing changing in the world living conditions, the crime is also increasing at the rapid rate. The manual identification of the criminals using the photo traced from the CCTV, is quite the time consuming task and also error prone. We suggests the automated facial feature examination system for the criminal identification using the HAAR approach for the Facial Feature Examination. We have compared the approach using the base paper, which is based on the LBP (Local Binary Pattern) approach, the deficiency of the base papers like inability of recognising the side face , similarity percentage are improved in the proposed approach. The results which are obtained are quite satisfactory and better than the base approach.
The Code of Data Capital: A Distributional Analysis of Law in the Global Data Economy

The data economy has become an integral part of the global economy. It plays a fundamental role in issues of economic distribution and inequality, which has much to do with the legal arrangements and entitlements that shape it. Yet data and data-driven technologies are often conceptualized in terms that do not seem adequate to capture the role they play in global distribution, or which overlook the law as a key mechanism shaping distributional outcomes. Using a law and political economy approach, this article argues that conceiving of data as capital that is coded by legal mechanisms allows new ways of imagining alternative distributions of the value it generates in the global economy today. The article maps some of the legal entitlements that shape the global data economy and its distributive effects, as well as proposals for alternatives. It concludes that analyses of the distributive effects of the global data economy ought to take into account the fundamental roles that both law and technology play in shaping those effects.
STUDENTS' ANXIETY IN SPEAKING ENGLISH DURING DISTANCE LEARNING

The ability to speak a foreign language is prominently influenced by one of the obstacles, namely speaking anxiety. In fact, the researcher found that the students tended to be anxious in speaking English in class during their presentation even though it was conducted through distance learning because of the Covid-19 pandemic. Referring to this background, this study aimed to examine what the students’ anxiety in speaking English is during the distance learning and how they cope with the anxiety during the distance learning. A case study was employed in this research as one of descriptive designs in qualitative research. Moreover, the data was collected through analysing students’ self-reflection documents, a close-ended questionnaire, and an interview as the research instruments. Additionally, the participants of this study were 36 Science students at grade X of SMA Kristen Petra 1 Surabaya. The researcher discovered that the distance learning during Covid-19 pandemic caused the anxiety among the students in speaking English. Hence, it is significant for teachers as the facilitator to be able to play their roles to reduce the students speaking anxiety in a foreign language classroom.