Reviewerly/exHarmony huggingface dataset:
Comparison of the EigenFace, Fisher and LBPH methods of facial recognition, implemented in OPENCV

In today's world the identification of individuals is necessary, both to carry out banking transactions, to register attendance at work, or to make purchases via the Internet. The problem is that identification documents can be stolen, duplicated, and used by other people, whereas the use of identifiers such as username and password on websites tends to make people forget their password or username. Using biometric identifiers is a better option to the aforementioned problems, such as fingerprint and facial recognition. Facial recognition is the least invasive method for the individual, since it does not require touching surfaces and with the current covid-19 problem it would be the best option. To do facial recognition, there are several techniques and mathematical models, the objectives of this article were to make a speed comparison of the facial recognition methods provided by the OPENCV library which are: EigenFace, Fisher and (Histograms of local binary patterns) LBPH. Detection and recognition times were tested for 590 photos, and the Eigenface (PCA) method was found to be faster than the Fisher method and the Logical Binary Pattern History method.
Abstractions for software communication: Programming protocols in typescript

More software parallelization results in more software communication and therefore the need for software communication protocols. Protocol logic in a program is also called the coordination concern. Separating this coordination concern from the regular computation concern in a distributed application can result in higher quality software code. This can be achieved by providing a software engineer facilities for programming protocols based on a global protocol definition. Not only will the coordination be separated from the compu-tation concern, but the defined protocol can also be statically validated. Generating the coordination layer for a distributed application also saves time and reduces programming errors instead of implementing this layer manually. This thesis reports on research for adding software protocol abstractions to the pro-gramming language TypeScript. TypeScript is a statically compiled and typed version of the programming language JavaScript, which is a popular language for programming dis-tributed applications. Various concrete abstractions that are needed for the protocol abstraction layer are di-vided over three conceptual layers. The first conceptual layer provides abstractions needed for starting the protocol and a role based messaging system. The second layer provides a programming interface for each distributed process that is part of the protocol. This in-terface will enable static protocol validation and with a professional development environ-ment, facilities like code statement completion and code navigation will be present. The third layer provides the global protocol definition with the corresponding programming syntax, through an external DSL. A runtime facility for starting up the protocol, to make sure all involved distributed soft-ware processes are present, is called the Mediator. This Mediator role collects the physical address details of all the protocol involved roles and delivers this information to these roles. After this startup process the Mediator dies and the protocol has started for the involved protocol roles. Messages are specified and can be continuously received, but processed when a role is ready for a specific message. Static protocol validation is based on state machine simulation per role. The generated API will have objects for all states, and the methods of these objects represent the transitions between states. These transitions can only be made once, which is checked at runtime to guarantee protocol safety. Performance penalty tests indicate a low decrease of performance due to the extra abstraction layer, and this happens only when the amount of messages increase to high volumes. Normally the implementation of the coordination concern of a distributed application can be error prone, but with a generated coordination layer and static validation, protocol constraints are enforced and therefore errors are reduced.
Software defect prediction based on CS-BP neural network

Abstract Software defect prediction can detect whether there are defects in the program module so as to effectively reduce the unnecessary cost of software development and maintenance. In this paper, the limitation of the traditional BP neural network in the field of defect prediction leads to the inaccuracy of the prediction results. By using the global optimization ability of cuckoo search, the BP neural network is improved, the important initial parameters of the network are optimized, and the software defect prediction method of CS-BP is proposed. The experimental results show that compared with traditional machine learning algorithms such as BP neural network, J48 and SVM, CS-BP method has a better effect on the prediction of software defects.
Knowledge Graph Enhanced Transformer for Generative Question Answering Tasks

Generative question answering tasks usually suffer from the challenge of the lack of external knowledge. The generative question answering model cannot understand the intention of questions effectively because the questions asked by users are short and the amount of information is insufficient. Therefore, it needs to be supplemented by external knowledge. In this paper, we propose a generative question answering model combined with knowledge graph (KG-Transformer), which can solve the problem of inaccurate generation caused by the above challenge. The advantage of KG-Transformer is that it designs a knowledge retrieval module which can obtain external knowledge from the knowledge graph as a supplement to the intention of question. Besides, compared with the traditional sentence similarity method and hard fusion, it uses a soft switching mechanism, which can switch between the knowledge vector and the question vector, effectively extracting knowledge information and questions information and then fusion. Experiments on a benchmark dataset demonstrate that our model has robust superiority over compared methods in generating informative and accurate answer.
Research Guides: Gender and Women's Studies (GWS) Portal: GWS at UW-Madison

Your gateway to gender and women's studies resources at the UW-Madison Libraries and beyond.
Byzantine-tolerant Distributed Grow-only Sets: Specification and Applications

In order to formalize Distributed Ledger Technologies and their interconnections, a recent line of research work has formulated the notion of Distributed Ledger Object (DLO), which is a concurrent object that maintains a totally ordered sequence of records, abstracting blockchains and distributed ledgers. Through DLO, the Atomic Appends problem, intended as the need of a primitive able to append multiple records to distinct ledgers in an atomic way, is studied as a basic interconnection problem among ledgers. In this work, we propose the Distributed Grow-only Set object (DSO), which instead of maintaining a sequence of records, as in a DLO, maintains a set of records in an immutable way: only Add and Get operations are provided. This object is inspired by the Grow-only Set (G-Set) data type which is part of the Conflict-free Replicated Data Types. We formally specify the object and we provide a consensus-free Byzantine-tolerant implementation that guarantees eventual consistency. We then use our Byzantine-tolerant DSO (BDSO) implementation to provide consensus-free algorithmic solutions to the Atomic Appends and Atomic Adds (the analogous problem of atomic appends applied on G-Sets) problems, as well as to construct consensus-free Single-Writer BDLOs. We believe that the BDSO has applications beyond the above-mentioned problems.
LibGuides: Business: Essential Resources

A research guide designed to introduce you to the field of business. You'll find the materials, search tools, and other resources you need to start your research. If you need any assistance, please contact your librarian
Large Scale Covid-19 Detection with Blood Platelets Using Artificial Neural Network

Detection of COVID-19 by using patient’s blood platelets using an artificial neural network to perform large-scale automated testing. The deep learning model uses the CBC test results to detect the virus with an accuracy of 89.26%, which achieve higher accuracy than the widely used RT-PCR test. The model has achieved accuracy with only a thousand rows, which assures that the model can achieve better results with more data. The objective of the paper is to provide an automated and accurate method to detect COVID-19 using machine learning to apply it in large-scale testing, to help in containing the virus and prevent the spread of the virus. The scope of the paper is on the detection methodology using the blood platelets values extracted from the complete blood cycle (CBC) testing and discussing the future possibilities of improving the automated prevention method. The paper uses a dataset provided by Hospital Israelita Albert Einstein in Brazil, which has over 50 features of different tests as Influenza A, Influenza B, Uria, etc.…, many of these features had missing values or wasn’t relevant to the existence of the virus in the body; therefore, the feature selection led to filtering the 17 blood features. The K-Nearest Neighbour (KNN) Imputation imputed the missing values in the 17 filtered values. The analysis & visualization of the blood features concluded that the complete blood cycle test values highly correlated with each other, and there is a change occurs due to the presence of the virus is clear, especially to Eosinophils and Leukocytes, at which they represent the white blood cells forming the immune system that reacts against any virus or bacteria attracting the human body. The paper has applied five different machine learning algorithms: logistic regression, support vector machine (SVM), random forest, K neighbours and decision tree. Meanwhile, in the second approach, used an artificial neural network with intensive use of network optimization and hyperparameter tuning to achieve the highest accuracy possible.
A Multi-planar Approach to Encoding Story Worlds for Dynamic Narrative Generation

Tabletop Role-Playing Games transport the player to a fantastical fictional world. This world is inhabited by characters, players and objects. Prior to the commencement of play, the Dungeon Master prepares not only the rules of the world but an account of historical events and the current world state. While the rules provide the player with boundaries of play, the character sheets store the current player state, and the back story provides context for the happenings during the game session. Consider how often a story is told where, “In a land far away lived…”. Rarely does a story rely on a universe where all existents are spontaneously spawned into being. Instead, vast historical worlds with cultures, histories and languages are created. This context provides the reader/viewer/player with an understanding of the world in which they find themselves. Players learn of warring factions, key artefacts, and are introduced to key drivers of the worlds drama. When Non-Playing Characters (NPC) are introduced into the game, the dungeon master draws on this history to form quests and to feed the players a view of this world. These behavioural systems, however, react to a player’s moves with little consideration for the world context. This lack of context leads to the trope of the robotic NPC with little awareness of the world. How do we ingrain this knowledge of a contextual world?
AN EXTREME BOUNDS ANALYSIS OF THE IMPACT OF THE COVID-19 OUTBREAK ON CRYPTOCURRENCIES

The aim of this paper is to find out if the COVID-19 outbreak in the USA has a robust impact on the prices of cryptocurrencies. Inspired by the literature related to the determinants of cryptocurrency prices and based on data availability, six potential determinants of cryptocurrency prices and five proxies for the COVID-19 outbreak were selected. The impact of the COVID-19 outbreak was tested using two approaches of extreme bounds analysis and the robustness of our findings was further checked with different cryptocurrencies (Bitcoin, Ethereum, Litecoin and Bitcoin Cash). Our results show that new deaths from the COVID-19 have a robust positive impact on the price of cryptocurrencies while the impact of new confirmed cases, total cases, and total deaths is not robust. In line with previous studies, it is also found that economic uncertainty, stock, gold, and oil prices are robust determinants of the value of cryptocurrencies.
Intellectual Property and Critical Theories

Abstract This chapter briefly summarizes the impact of critical theoretical methods on intellectual property (IP) scholarship. It speculates that the influence of critical legal theory on IP is greater than typically acknowledged or understood, and draws on scholarly examples at the juncture of critical and liberal theories to make this point.
Implementasi Kebijakan Kawasan Tanpa Rokok (KTR) di SMA Negeri 17 Medan

&lt;p&gt;&lt;strong&gt;&lt;em&gt;Introduction:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; Medan City Government has Regional Regulation No. 3 of 2014 concerning No-Smoking Area, the aim is to create a clean and healthy space and environment. In fact there are still those who violate the regulations of the Local Government where one of the teaching and learning process in SMA 17 Medan, there are still smoking. &lt;strong&gt;Objective:&lt;/strong&gt;Research is descriptive qualitative. Research informants consisted of school principals, teachers, students and security guards. &lt;strong&gt;Results&lt;/strong&gt;: The implementation of the No Smoking Area policy in SMA 17 Medan has not run optimally due to 4 factors, namely: Communication factors, lack of socializing the application of No-Smoking Area; the resource factor, the lack of facilities and infrastructure for the application of No-Smoking Area and the absence of specific guidelines as information for implementing the policy; Disposition factors, lack of commitment from policy implementers; and bireaucratic factors, there is no formation of policy making groups, no evaluation of the application of No-Smoking Area is carried out.&lt;strong&gt;Suggestion&lt;/strong&gt;: The Medan City Education Office increased No-Smoking Area socialization, increased supervision, imposed sanctions on schools that did not implement No-Smoking Area. To the school, to increase No-Smoking Area socialization, apply strict sanctions and form a No-Smoking Area policy-making working group.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt; &lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords: Implementation, No-Smoking Area.&lt;/em&gt;&lt;/strong&gt;&lt;strong&gt;&lt;em&gt;&lt;/em&gt;&lt;/strong&gt;&lt;/p&gt;
LibGuides: Halloween: Creature Feature

If you are looking for a LibGuide to help you find resources for all things related to the spookiest holiday of the year, then look no further!
Soft decoding of short/medium length codes using ordered statistics for quantum key distribution

Quantum key distribution (QKD) is a cryptographic communication protocol that utilizes quantum mechanical properties for provable absolute security against an eavesdropper. The communication is carried between two terminals using random photon polarization states represented through quantum states. Both these terminals are interconnected through disjoint quantum and classical channels. Information reconciliation using delay controlled joint decoding is performed at the receiving terminal. Its performance is characterized using data and error rates. Achieving low error rates is particularly challenging for schemes based on error correcting codes with short code lengths. This article addresses the decoding process using ordered statistics decoding for information reconciliation of both short and medium length Bose–Chaudhuri–Hocquenghem codes over a QKD link. The link’s quantum channel is modeled as a binary symmetric quantum depolarization channel, whereas the classical channel is configured with additive white Gaussian noise. Our results demonstrate the achievement of low bit error rates, and reduced decoding complexity when compared to other capacity achieving codes of similar length and configuration.
Experimental research on disturbance resistant polarization modulation mode for quantum key distribution

A free-space quantum key distribution (QKD) system based on mobile equipment can provide an effective method to construct a real-time full-coverage multi-node network. However, the existing free-space QKD systems based on mobile devices encounter the challenge regarding the lack of stability caused by equipment disturbance. The robustness of the QKD polarization encoder against mobile device disturbance will be significant. Owing to the inevitable disturbance in practical applications, even the polarization-maintaining fiber (PMF) cannot maintain its polarization-maintaining characteristics well, which in turn affects the stability of some systems based on PMF. Therefore, in order to ensure that stable coding can be achieved under disturbances, we propose a two-way differential modulation mode, in which stable coding can still be achieved even under disturbances. At the same time, in order to verify the actual anti-disturbance characteristics of the mode, the polarization-modulated unit (PMU) with a two-way differential modulation mode is used in this study to generate four long-term stable polarization states subjected to the disturbances with a frequency of 200 Hz. At the same time, the PMU has a higher insertion loss, which makes the influence of crosstalk on the system more obvious. We also discuss two ways i.e. the time domain and frequency domain, to reduce the crosstalk which is caused by the imperfection of the device. The experiment is performed at a repetition frequency of 250 MHz, and a commercial avalanche single-photon detector is used to detect the system’s quantum bit error rate (QBER). Under the condition of no disturbance, the average QBER is 0.39% in 2 h. Then a vibration of approximately 200 Hz is used to simulate the practical disturbances, the average QBER is 0.36% in 2 h, and the fluctuation range of the QBER is only within 0.2%. We propose the first feasible encoding scheme in disturbed environments to ensure the long-term stability of the encoded polarization states, which is expected to be used in the multi-node expansion of the quantum network.
Keyphrase Generation with Recurrent Neural Network and Attention Model

There is currently an information overload happening in the world of digital media, with millions of articles being published in a single day. This has raised concerns regarding how someone can not only document and catalogue these articles for preservation purposes, but as well as produce a summary for others who might want a quick understanding of its contents, as producing a summary for every article takes a long time. As such, in order to tackle this issue, automation is intended to streamline the entire process. The purpose of this study is to examine the effectiveness of a model when it uses an attention model, versus one without. To clarify, the model will initially not feature any attention model of any sort, be it Bahdanau or Luong. We intend to qualitatively evaluate as to whether or not the attention model alone is capable of producing better results. These results would be obtained using F1-Score, Precision and Recall evaluation methods. The research will first evaluate the original version of a model, that does not feature any attention mechanism, and obtaining the F1-Score, Precision, and Recall, then tabulating those results. Following that, the attention model will be incorporated into the model, and the new modified model will be tested again, and the results will be tabulated. For the purposes of this study, three datasets will be used, namely the Gigaword dataset, as well as two datasets generated for the purposes of this study, namely a dataset featuring Coronavirus News, and a dataset featuring Oil and Gas News.
PENGARUH PENGGUNAAN MEDIA CETAK BERBASIS LEAFLET TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN SEJARAH

The problems in this study are 1) the low learning outcomes of history 2) the inactivity of students in learning. 3) Saturated learning media. 4) Leaflet-based print media has never been used in learning. The purpose of this study was to determine the effect of the use of leaflet-based print media on student learning outcomes in history subjects in class X Odd Semester SMK Trisakti Jaya Bandar Lampung. The method used in this study is an experimental method, data analysis uses statistical formulas, the population in this study is all students of class X SMK Trisakti Jaya Bandar Lampung for the academic year 2021/2022. They are spread over 6 classes with a total of 141 students. From the population, 2 classes were taken as samples, namely Class X Office, which amounted to 30 students as the experimental class and X Online Business and Marketing, which amounted to 27 students as the control class by using cluster random sampling technique. To measure the learning variables, the writer uses a test, which is in the form of a multiple choice test of 40 items, which are tested for validity and reliability. Data analysis used simple statistical analysis with t-test formula. Based on the results of the hypothesis test of the similarity of the two averages, using thit the obtained value thit = 15.95 with the test criteria used is accept if  otherwise  rejected. By taking the 5% ( significance  level  >  so  that it is rejected and  accepted. Thus, There is an effect of using leaflet-based print media on student learning outcomes in history subjects in class X Odd Semester SMK Trisakti Jaya Bandar Lampung Academic Year 2021/2022.
Problematika Sarana dan Prasarana Pendidikan

The problem of education that occurs in Indonesia is the problem of the lack of educational infrastructure, especially in remote areas. This is caused in the quality of education. There are so many students who cannot enjoy the same facilities and infrastructure as students in the city. This proves that the government pays little attention to the existing facilities in remote areas. This problem is usually caused by several factors, including the blocked allocation of funds because there are many situations where school funds must be used to make infrastructure for certain purposes. And another factor is poor maintenance which can happen because the school does not pay much attention to how to take care of the infrastructure that has been provided, indifference and lack of supervision from the government make many school facilities neglected. The results of the students were not comfortable using the facilities because many were damaged. Keywords: Problematics, Facilities, Infrastructure.