Reviewerly/exHarmony huggingface dataset:
PUBLIC PERCEPTION OF COMMUNITY POLICING AND CRIME CONTROL IN EKITI STATE, NIGERIA

The study examined public perception on community policing and crime control in Ekiti State, Nigeria. Security is a necessity in every human society and the implication is that, its absence threatens the survival of individuals and their properties. This is why governments worldwide invest huge resources to ensure that lives and properties of their citizens are secured. However, it is still argued that, no government has the wherewithal to supply one hundred percent security for her people, and no matter how endowed and organized a country is, it can hardly be devoid of security challenges. The study adopted purposive method in which three local government areas namely; Ado local government areas (Ekiti Central), Ikere local government areas (Ekiti South) and Ikole local government areas (Ekiti North) were selected. The study made use of quantitative methods of data collection and as a result, three hundred (300) copies of questionnaire, in which one hundred (100) copies were distributed to each local government areas were used to illicit information from the respondents. The study revealed that 62.7% have heard about community policing while 37.3% of respondents have not heard of community policing before. Also, majority with 36% of the total respondents believed that it is involving the community or local people in policing their community through the use of local vigilantes. On the effect of community policing, 30% of the majority believed that it helped in controlling crimes with the aid of information and supporting agencies. The study therefore concluded that controlling crimes in Nigeria is a daunting task for law enforcement agencies and as a result, community policing will be an effective mechanism in controlling crimes. The study thereby recommended that, to achieve the desired full impact, relevant stakeholders need to revisit the program, address the weaknesses, work against the threats and utilize as best as possible the available opportunities. also, Government needs to support and promote community oriented policing style as well as create more enlightenment to the public and inform the police of any criminality.
LibGuides: Student Resources: Getting Started

Welcome to the University Libraries! We have many services and resources to help you succeed.
LibGuides: Creative Writing: Home

A guide to helping middle-school-aged children learn the fine art of creative writing. Students will learn how to write short stories, plays, poetry and graphic novels.
Python, the Fundamentals

Python is a well-structured, powerful programming language. There are many reasons why it is useful as an introduction to scientific computing. It combines remarkable expressiveness with a clean, simple and compact language structure. It’s easy to learn.
Student science at Samara State University of Social Sciences and Education: results and prospects

Student science at Samara State University of Social Sciences and Education: results and prospects
LibGuides: A Guide for Reluctant Teen Readers: Home

This guide is a resource for teens (ages 13-18) who may be reluctant to read, who struggle to enjoy books, or who need a starting place for rekindling their previous love for reading.
The interrelations between audio compression and graphical texture detail in video games : How they affect players perception of quality

For this study three questions are being studied. Question one: “How does the audio compressionaffect the perceived video quality?” Question two is somewhat reversed: “How does the texturedetail af ...
Information-Theoretic Security of Cryptographic Channels

We discuss the setting of information-theoretically secure channel protocols where confidentiality of transmitted data should hold against unbounded adversaries. We argue that there are two possible scenarios: One is that the adversary is currently bounded, but stores today’s communication and tries to break confidentiality later when obtaining more computational power or time. We call channel protocols protecting against such attacks future-secure. The other scenario is that the adversary already has extremely strong computational powers and may try to use that power to break current executions. We call channels withstanding such stronger attacks unconditionally-secure. We discuss how to instantiate both future-secure and unconditionally-secure channels. To this end we first establish according confidentiality and integrity notions, then prove the well-known composition theorem to also hold in the information-theoretic setting: Chosen-plaintext security of the channel protocol, together with ciphertext integrity, implies the stronger chosen-ciphertext notion. We discuss how to build future-secure channel protocols by combining computational message authentication schemes like HMAC with one-time pad encryption. Chosen-ciphertext security follows easily from the generalized composition theorem. We also show that using one-time pad encryption with the unconditionally-secure Carter-Wegman MACs we obtain an unconditionally-secure channel protocol.
LSC-North Harris Library Research Guides: Energy, Manufacturing, and Trades Management: Starting Point

This research guide is designed to help students in the Bachelor of Applied Science program for Energy, Manufacturing, and Trades Management complete information research tasks.
Social Distancing AI: Using super-resolution to train an object detection model on low resolution images

This paper addresses the following hypothetical situation: suppose that we want to train an object detection algorithm but that only low resolution data is available. As a tentative solution to this problem, this paper suggest to first super-resolve the low resolution data to obtain higher resolution data that is then fed to the object detection algorithm. Super-resolution is a technique that takes a lower resolution image and “paints” in extra details in a very convincing way to produce a higher resolution output. To evaluate this approach, this paper trains the object detection model on to separate datasets: 4x down-sampled and subsequently super-resolved images and the original images. For super-resolution we use ESRGAN which is based on RaGAN. Quantitative comparison suggests that there is little difference between the two networks and thus provides some support for the approach explored in this paper. Qualitative comparison indicates that this technique only works in certain cases–when super-resolution results in images that can properly be annotated. If the contrast between the objects of interest and the background is great enough, then super-resolution will result in much clearer images that are easily annotated. In this particular scenario, using super-resolution to train object detection algorithms represents a feasible solution to the hypothetical situation assessed in this paper. This approach is tested in the context of detecting social distancing violations in restaurants using areal footage. This is of high relevance in 2020 due to the ongoing Coronavirus pandemic. (Less)
Preprocessing method comparison and model tuning for natural language data

Twitter and other microblogging services are a valuable source for almost real-time marketing, public opinion and brand-related consumer information mining. As such, collection and analysis of user ...
Research on the Application of VR Technology in Physical Education

With the continuous development of today's social science and technology, various technological products have poured into our lives. From 2D and 3D technology to the current VR (virtual reality) technology, the application fields are extremely wide. This article mainly explores the application of VR technology in physical education, and discusses the problems and results achieved in the application of this technology, analyzes the value and disadvantages of virtual reality technology in physical education, and finally the application of VR technology in s physical education learning puts forward its own hypotheses and prospects, aiming to provide ideas for expanding new physical education learning methods and increasing the fun and effects of physical education learning.
Qualitative acceptance and co-design of an app aimed at improving emotional intelligence for precarious workers

In the discussion on the work competences, the emotional competences are acquiring only in the last years a concrete popularity, although its importance is demonstrated The COVID-19 pandemic increased the effect on works and on workers uncertainly, enlarging the needs of emotional competence tools, accessible to all category of users with a special focus on those with social or economic fragilities Based on this background the project called EMOTION exe aims to develop and assess an Emotional Training Gym, a safe environment, designed for the acquisition of new socio-emotional competences It is freely browsable that leaves a high degree of autonomy using digital tools, tailored for the users with a high risk of social exclusion or job insecurity The article describes a study performed with focus groups for the qualitative acceptance of the EMOTION exe software and the consequent co-design with the potential user for further improvement The results show that the tool is highly accepted by the user groups, with some concrete proposals for improvement based on the needs of the participants that includes the centrality of the artificial tutors, the inclusion of gamification aspects, the redesign of the graphical layout and proposals of videos to be added in the multimedia library © 2020 CEUR-WS All rights reserved
Procedural Generation of Tower Defense Levels

This report aims to present a method for generating levels for tower defense games. Tower defense games are digital strategy games played by defending bases against oncoming enemies that travel alo ...
MAZE: a secure cloud storage service using Moving Target Defense and Secure Shell Protocol (SSH) tunneling

Cloud storage services have emerged as a popular destination for businesses and individuals to securely store documents due in part to being virtually accessible anywhere, anytime. However, cloud storage systems are static attack targets enabling attackers to thoroughly study the system without fear that their conclusions about the system would be rendered inaccurate. As such, computer security researchers began exploring techniques, known as Moving Target Defense (MTD), to turn distributed systems into moving targets. Whereas traditional defense mechanisms attempt to identify and cover system vulnerabilities, the underlying philosophy of MTD is that it is impossible to build perfectly secure systems. Instead, MTD techniques attempt to constantly change the attack surface in order to increase the cost (in terms of time and resources) and difficulty of executing successful attacks, in the first place. Current research in MTD, however, is lacking in implementations of MTD techniques on real systems (rather than just simulations). This work presents MAZE, a secure cloud storage system in which the files to be protected (e.g., security keys, account numbers or passwords) are split into pieces and pseudo-randomly dispersed within a large, continuously-changing maze of computers. Hopping from one computer to another within MAZE is only possible by following timely created doors, which are implemented using Secure Shell Protocol (SSH) tunnels. At any computer, there can be many open doors, each leading to a different computer. In order to retrieve a file, the user has to follow a schedule that is provided by the MAZE service to authorized users only. The schedule informs the client of which doors to traverse through to retrieve all the pieces of the file. In addition, computers within MAZE have two refresh periods: the first restarts the computer and reloads the system software from a clean copy in order to thwart potentially ongoing attacks, and the second modifies the file pieces to become incompatible with the file pieces before modification. In order for attackers to successfully retrieve a file, they must retrieve all file pieces within the second refresh period. We implemented MAZE and performed a series of experiments that demonstrated the potential of an MTD-based cloud storage system in protecting against attackers while providing reasonable response time.
Ethics and health data protection in pandemics: A reference to the case of applications for contact tracking

The analysis and massive treatment (big data) of health data using artificial intelligence algorithms, as well as platforms and applications for contact tracking and geolocation, have been proposed as necessary tools to successfully manage a situation like the current COVID-19 pandemic Examples such as those from South Korea, Norway or Singapore seem to be having an impact and Europe has been quick to endorse them, although without losing sight of its own regulatory framework, the protection of fundamental rights, and respect for basic ethical principles We raise some ethical and legal questions regarding the processing of health data in a context of public health emergency such as the present one: Legitimacy, limitations to consent, public/private relations, security, and privacy, among others To this end, we take as a reference the EU General Data Protection Regulation (GDPR), recommendations of the European Commission, guidelines of the European Data Protection Board (EDPB) and the Spanish Data Protection Agency (AEPD), pronouncements such as that of the Spanish Bioethics Committee or the recent European framework on digitalisation (February-March 2020) © 2020 Universitat Autonoma de Barcelona and Universitat de Girona All rights reserved
Library Web Development: Beyond Tips and Tricks.

"Library Web Development: Beyond Tips and Tricks.." Journal of Electronic Resources Librarianship, 32(4), p. 340
Learning from noisy labelsby importance reweighting: : a deep learning approach

Noisy labels could cause severe degradation to the classification performance. Especially for deep neural networks, noisy labels can be memorized and lead to poor generalization. Recently label noi ...
Classification of Chroma Reconstruction Method by Machine Learning Method

In this paper, we propose a method to predict subsampling scheme by using the machine learning for the chroma reconstruction of screen content images (SCIs). We create a feature matrix with thirty features, and use the classification learner, error-correcting output codes (ECOC) classifier for multiclass learning, to train the model. After testing through the model, we finally get the experimental data that shows us the correlation between the luma and chroma and the accuracy of the model. The accuracy of the model is up to 92%, which provides the decoder with an accurate subsampling scheme. Therefore, with the correct subsampling scheme, it allows the subsampled chroma to be reconstructed accurately.
A Python Approach to Message Passing

Modern high-performance computing owes its success not least to the concurrent processing of complex computing tasks on distributed systems, in networks that consist of nodes of separate machines, or on individual machines with an architecture with multiple processors.
Robust Reinforcement Learning for Quadcopter Control

Sim-to-Reality transfer in Reinforcement Learning is a promising approach ofsolving costly exploration in real systems, but it comes with the generalizationproblem of transferring policies from sim ...
Ανάλυση συναισθήματος σε ελληνικές ειδησεογραφικές ιστοσελίδες σχετικά με το θέμα της Συμφωνίας των Πρεσπών

In this thesis, lexicon-based sentiment analysis approach has been applied for the study of data collected from Greek news sites with main subject of interest being the “Prespa Agreement”. The purpose was to identify current trends, over a specific time frame, on this particular issue.For successful analysis, using the KNIME Analytics Platform, the database to be processed was originally created and included texts centered on the subject under consideration. Then, a specialized sentiment lexicon was created for this analysis and finally, the complete processing model was created and the results have been presented. In addition to a better understanding of the overall process, important elements and definitions of sentiment analysis, as well as the methodology followed at each stage of the procedure, are presented, and each step has been analyzed in depth.From the final results of the method, it is being concluded that the trend of news story during the selected carrying out period was neutral on the issue of the “Prespa Agreement”.
Digital textåterkoppling på SVA Grund

Assessment is a central part of the teaching praxis and a formative type is regarded valuable for student learning. Still, there is a gap in knowledge in how written assignments by Swedish as a sec ...
Predicting the user navigation pattern from web logs using weighted support approach

&lt;p class="Abstract"&gt;&lt;span id="docs-internal-guid-f3d644ee-7fff-d3c1-15b5-f75fe28d3e2d"&gt;&lt;span&gt;A weblog contains the history of previous user navigation pattern. If the customer accesses any portal of organization website, the log is generated in web server, based on sequence of user transaction. The weblog stored in the web server as unstructured format, it contains both positive and negative responses i.e. successful and unsuccessful responses, identifying the positive and negative response is not useful for identifying user behavior of individual user. Initially the successful response is taken, from that conversion of unstructured log format to structured log format through data preprocessing technique. The process of data preprocessor contains three step process data cleaning, user identification and session identification. The pattern is discovered by preprocessing technique from that user navigation pattern is generated. From that navigation pattern classifier technique is applied, the conversion of sequence pattern to sub sequence pattern by clustering technique. This research is to identify the user navigation pattern from weblog. The Improved Spanning classification algorithm classifies the frequent, infrequent and semi frequent pattern. To identify the optimal webpage using classificatopn algorithm from thet user behavior is identified.&lt;/span&gt;&lt;/span&gt;&lt;/p&gt;
PEMBUKAAN KEMBALI PERPUSTAKAAN DI ERA NEW NORMAL

A study using a survey method was conducted on librarians of the Indonesian Institute of Sciences (LIPI) with the aim of finding out what things they think need to be prepared if a library is reopened in the new era. It is known that all LIPI librarians are 53 people, with 38 expert librarians (71,70%) and 15 (28,30%) skilled librarians. A total of 31 questions were ask to them via Google form with a deadline for filling out 20-27 June 2020. It is known that 47 repondents answered questions. The collected data is presented in the form of a diagram, then a descriptive analysis and discussion, it can be concluded that more than 50% of the respondens agreedwith all the planning the time line for the reopening of the library, communicating to users about the services provided, limiting the number of visitors visiting, making arrangements for the course of transactions between users and librarians, library provide health detection equipment for librarians and visitors, and the most important is changes in the services by utilizing more internet based information technology. Therefore it is necessary to provide asource of information in digital form that can be accessed easily from various places wherever users are.
PERANCANGAN PERANGKAT LUNAK PENGENALAN ALAT MUSIK TRADISIONAL INDONESIA

Development of computer technology has expanded so rapidly in many areas of life, not least in edication. Transforming teaching by using advances in computer technology in education can help educators duty as educators and helps foster interest in learning independently and help the creativity of learners to learn . In the current technological developments , the introduction can be done using various types of media , one of them is the introduction of Indonesian traditional musical instruments using computer applications .The media selected for its computer applications today that stout . Therefore, the authors raised the title  Implementation recognition software using VB.Net Indonesian musical instrument  . This app was built to facilitate users familiar with Indonesian traditional musical instruments .In the preparation of this paper , the authors use research design causal relationship ( experimental ) , the authors conducted experiments and testing of applications that are made and by studying literature and writing that has to do with the problems examined . Data collection methods used are observation , it was collecting data and object-oriented . In describing the workflow applications using modeling techniques Unified Modeling Language ( UML ) . In designing the app I use Microsoft Visual Studio 2010 , Adobe Flash CS5 , and Photosoh CS3 . The conclusion is the introduction of the application of traditional Indonesian musical instrument to facilitate the introduction of traditional Indonesian musical instrument to the user in the form of images, sounds , and text to clarify the introduction of musical instruments . Keywords : Applications, Introduction to Traditional Musical Instruments Indonesia
LibGuides: ESL RESOURCES FOR ADULT LEARNERS: Vocabulary

This guide contains tips and suggestions, library resources and online resources for adult learners of English.
LibGuides: Getting Started with Archives: Glossary

This guide serves as an introduction to locating and evaluating collection description, and beginning archival research at NYPL Glossary of terms and abbreviations used in archival description
Semantic Modulation Based Residual Network for Temporal Language Queries Grounding in Video

Temporal language queries grounding in video aims to retrieve one specific moment in a long, untrimmed video by a query sentence. This is a challenging issue as a video may contain multiple moments of interests which have complex temporal dependencies with other temporal moments. To preserve the original video moment information during the multiple layers convolution operations, this paper introduces residual learning into the issue and proposes a novel semantic modulation based residual network (SMRN) that incorporates dynamical semantic modulation and multiple prediction maps in a single-shot feed-forward framework. Semantic modulation mechanism dynamically modulates the residual learning by assigning where to pay the visual attention. And the mechanism is able to adjust the weights given to different video moments with the guide of query sentence. Additionally, the network combines multiple feature maps from different layers to naturally captures different temporal relationships for precisely matching video moment and sentence. We evaluate our model on three datasets, i.e., TACoS, Charades-STA, and ActivityNet Caption, with significant improvement over the current state-of-the-arts. Furthermore ablation experiments were performed to show the effectiveness of our model.