Reviewerly/exHarmony huggingface dataset:
Blockchain’s Impact on Consumer’s Perspective in the Luxury Fashion Industry: A Position Paper

Blockchain technology presents an opportunity for industries to implement for a more transparent and sustainable business model. The fashion industry is notoriously known for its complex and opaque supply chain and its negative impact on the environment and the people involved in the processes along the fashion supply chain. To address these long-standing challenges, the integration of blockchain technology has the ability to be the solution towards an ethical supply chain network. The study contributes to the current state of the fashion supply chain and the challenges it faces, outlining what blockchain technology is and its benefits in the context of the fashion industry. It also captures consumer sentiment on the subject of sustainability and transparency in the fashion industry and the perceived use and adoption of technology.
USE OF CRITICAL THINKING TECHNOLOGIES DURING ANALYSIS OF EDUCATIONAL CARTOONS IN PRIMARY SCHOOL

The development of critical thinking in the learning process is an important factor in educational reforms in Ukraine. In particular, the Law of Ukraine "On Education" states that "common to all competencies are the following skills: reading comprehension, the ability to express their opinions orally and in writing, critical and systematic thinking, the ability to logically justify their position, creativity, initiative, ability to adequately manage emotions, assess risks, make decisions, solve problems, the ability to communicate and cooperate with other people. Accordingly, the development of critical thinking becomes the basis for the formation of a modern student of the New Ukrainian school as a thinking, creative, creative, educated person. The orientation of primary school on the introduction of information and communication technologies in the educational process determines the search for modern dynamic, bright, appropriate visual aids. One such tool is a cartoon, which allows you to communicate new information in an accessible form, demonstrate behaviors, reason, draw conclusions, express their own opinions, and thus develop critical thinking of younger students.The article offers a number of techniques for the development of critical thinking of primary school children during the analysis of educational cartoons in lessons of various profiles in primary school. These are techniques such as: Bloom’s Chamomile Questions, cluster technology, associative bush method, cubing technology,brainstorming, pair work, basket of ideas, openwork saw, discussion, PRESS method, senkan, fishbone, etc. An algorithm for introducing an educational cartoon into a lesson to identify a problem, and then worked on any of these techniques. It is proved that it is inadmissible to use only independent viewing of cartoons by children without using the discussion of what they have seen, because then critical thinking will not be formed.
IN SITU CHARACTERIZATION OF FIBER-MATRIX INTERFACE DEBONDING VIA FULL-FIELD MEASUREMENTS

Macroscopic mechanical and failure properties of fiber-reinforced composites depend strongly on the properties of the fiber-matrix interface. For example, transverse cracking behavior and interlaminar shear strength of composites can be highly sensitive to the characteristics of the fiber-matrix interface. Despite its importance, experimental characterization of the mechanical behavior of the fibermatrix interface under normal loading conditions has been limited. This work reports on an experimental approach that uses in situ full-field digital image correlation (DIC) measurements to quantify the mechanical and failure behaviors at the fiber-matrix interface. Single fiber model composite samples are fabricated from a proprietary epoxy embedding a single glass rod. These samples are then tested under transverse tension. DIC is used to measure the deformation and strain fields in the glass rod, epoxy, and their interface vicinity. Initiation and propagation of the fiber-matrix debond are discussed. Full-field measurements are shown to facilitate the quantitative analysis of the traction-separation laws at the fiber-matrix interface subjected to transverse tension.
Assessing English Literacy in a Digital Age

Assessment reform is key to the transformation of College English education in China. To develop an assessment model that responds to the needs of modern society and helps learners to communicate effectively in English in future studies, at work, and in social life (Ministry of Education of the People’s Republic of China, ), it is essential that College English programs address the new challenges in Chinese society and redefine the goals of College English education in a digital age.
APLIKASI SISTEM INFORMASI KURSUS MENGEMUDI BERBASIS WEB ( STUDI KASUS : KURSUS SETIR MOBIL SANTA )

The course is one of the education provided outside the official school (non-formal) to develop self-ability and skills. Santa Car Driving Course is a skills education institution that specializes its students to be proficient in driving a car. However, the institution still registers courses by coming to the institution's location. This study aims to provide an application that helps institutions in providing course schedule information and online course registration. The method used in making this application is the PIECES method for running system analysis and the waterfall method for system requirements analysis. The result of this research is an application that is able to provide information on course schedules, registration, attendance and report notes.
Predicting True Vulnerabilities from Static Analyzer Warnings in Industry: An Attempt to Faster Releasing Software in Industry

An increasing digital world, comes with many benefits but unfortunately also many drawbacks. The increase of the digital world means an increase in data and software. Developing more software unfortunately also means a higher probability of vulnerabilities, which can be exploited by adversaries. Adversaries taking advantage of users and software vulnerabilities, by stealing data to cause harm, steal money, etc. This makes the digital world a dangerous environment. To ensure software has a minimal number of vulnerabilities, companies invest in software tools and experts to check their software for vulnerabilities. One such company is ING, the largest bank of The Netherlands. At ING they use Fortify, a static analyzer. The problem with this tool is that it gives many false positives. Therefore, pentesters and developers have to manually check all the warnings given by Fortify, which takes a lot of time and slows down the whole software development process. In this study, we propose to use supervised machine learning techniques to predict true vulnerabilities from static analyzer warnings. Using ING's data from Fortify, two highly imbalanced datasets with code metrics are created on class and method level. Various classifiers and sampling techniques are compared to determine which techniques perform the best. Next to that, we also compared the performance at different levels of granularity. Finally, we also investigate whether a dataset with different types of vulnerabilities performs better than a dataset consisting of only one vulnerability type. From our study, it is clear that Bagging in combination with ClassBalancer gives the best f-measure (0.618) for the class-level dataset, which is slightly good. Random Forest with SMOTE gives the best f-measure (0.412) for the method-level dataset, which we consider weak. Depending on the type of vulnerability, the performance can benefit from a dataset per vulnerability type. Overall, the performance found in this study shows slightly promising results when using Fortify in combination with supervised machine learning, especially compared to only using Fortify.
ANALISIS NILAI-NILAI EDUKATIF DALAM NOVEL TULANG RUSUK MENUJU SURGA KARYA MELLYANA DHIAN (TINJAUAN PSIKOLOGI SASTRA)

Novels as a form of literary work are expected to produce positive values for their readers, so that they can be sensitive to problems related to social life and encourage good behavior. Novels usually tell about the realities of human life with the surrounding environment. The limitations of the problem in this study focused on the analysis of educational values (religious values and moral values) and aspects of literary psychology in the main character in mellyana Dhian's novel Ribs to Heaven. While the purpose of this study is to analyze educational values in Novel Ribs Towards Heaven By Mellyana Dhian Review of Literary Psychology. This research uses Descriptive Qualitative data analysis techniques. Data collection is done by listening method through note-recording technique. Data analysis techniques used are flow analysis that includes three components, namely data reduction, data presentation, and conclusion drawing. From the results of the research shows the conclusion in the novel Ribs Towards Heaven By Mellyana Dhian conveys educational values that are very useful for readers by bringing the story to life, so that it can become more alive and add variety and avoid monotonous things that can make the reader bored. Educational values contained in the novel Ribs Towards Heaven By Mellyana Dhian, based on the results of the analysis consists of two aspects. The educational value is: (a) religious educational value is the highest and absolute spiritual value and is derived from human beliefs or beliefs, in the novel Ribs To Heaven. (b) The moral educational value of the value of dealing with good and bad behavior, in the novel Ribs To Heaven. And a review of literary psychology consisting of three main parts namely id, ego, superego.
Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) Control Charts Approaches in Monitoring Crime Rate

This paper is aimed at monitoring crime rate using Cumulative Sum (CUSUM) and the Exponentially Weighted Moving Average (EWMA) control charts.The crime data analyzed using these charts were extracted from the record office of the Nigeria Police Zonal Head Quarter, Irrua, Edo state. On monitoring process shift in crime rate using CUSUM and EWMA control charts, control parameters were varied in order to assess their performances. For CUSUM control chart, the decision interval(h)was varied at 2.0, 3.0, 4.0 and 5.0 while the EWMA schemes smoothening constant (w)was varied at 0.1, 0.15, 0.2 and 0.25. The finding of the study shows that CUSUM scheme with decision interval h = 2.0 performed optimally by detecting a shift in the process mean in monitoring of crime rate, while EWMA chart scheme with w = 0.2 performed optimally for EWMA chart schemes. The CUSUM control chartwas also observed to detect a smaller shift in the process mean compared to EWMA chart. Therefore, when a smaller shift in the process mean is desired, the CUSUM control chart scheme should be adopted.
Sistema informático para la distribución de uniforme escolar. Caso de estudio: provincia de Granma, Cuba

The distribution of school uniforms in the province of Granma is a process that is carried out in the different study centers of the province. The current research paper is aimed at developing a computer system that allows the control of the distribution of school uniforms in the province of Granma. It proposes a new algorithm based on Q-Learning to optimize the scheduling of the process of making school uniforms in clothing workshops. The Q-Learning algorithm of Reinforced Learning is a solution to the problem of sequencing tasks with a Flow Shop environment in a real context. The development of the computer system is based on free and multiplatform technologies. The technologies are HTML 5, CSS 3, JavaScript, Bootstrap, jQuery and CodeIgniter. Extreme Programming was used as an agile methodology of development of software and the Model-View-Controller as an architectural pattern. A comparison of the results obtained from the execution of the algorithm with real data of the entity is performed. After analysis of the tests carried out, usefulness and reliability of the software developed are checked, which contributes to the improvement of the distribution of school uniforms in the province of Granma.
Guides: Request a Research Consultation: Research Consultation Request Form

Having trouble finding the resources you need? Use this form to request an appointment with a Rasmuson Library librarian. We can meet in person, online, or by email.
Class Representative Projection for Text-based Zero-Shot Learning

There have been significant advances in supervised machine learning and enormous benefits from deep learning for a range of diverse applications. Despite the success of deep learning, in reality, very few works have shown progress in text classification. Transfer learning, known as the zero-shot learning (ZSL) or generalized zero-shot learning (G-ZSL), is receiving much attention due to its ability to transfer knowledge learned from a known (seen) domain to unknown (unseen) domains. But most of the ZSL works are relying on large training corpus and external semantic knowledge. Thus, there are very few studies that have investigated the improvement of text classification performance in sorely text-based ZSL/G-ZSL. In this thesis, a class representative framework was proposed for text-based ZSL by designing the novel projection method, learned from the seen classes, and applying it to transfer the knowledge to the unseen classes effectively. We designed a three-step approach, which consists of (1) sentence-based embeddings, (2) deep neural networks, and (3) class-based representative classifiers. Experimental results show that the proposed projection framework achieves the best classification results in text-based ZSL/G-ZSL compared with the state-of-the-art approaches investigated with three benchmark datasets including large newsgroup post of 20 classes called 20 Newsgroup Dataset and DBpedia dataset on various topics.
Agents that Listen: High-Throughput Reinforcement Learning with Multiple Sensory Systems

Humans and other intelligent animals evolved highly sophisticated perception systems that combine multiple sensory modalities. On the other hand, state-of-the-art artificial agents rely mostly on visual inputs or structured low-dimensional observations provided by instrumented environments. Learning to act based on combined visual and auditory inputs is still a new topic of research that has not been explored beyond simple scenarios. To facilitate progress in this area we introduce a new version of VizDoom simulator to create a highly efficient learning environment that provides raw audio observations. We study the performance of different model architectures in a series of tasks that require the agent to recognize sounds and execute instructions given in natural language. Finally, we train our agent to play the full game of Doom and find that it can consistently defeat a traditional vision-based adversary. We are currently in the process of merging the augmented simulator with the main ViZDoom code repository. Video demonstrations and experiment code can be found at this https URL.
Comparative Performance Evaluation of VGG-16 and Capsnet using Kannada MNIST

Abstract: Handwriting recognition is an important problem in character recognition. It is much more difficult especially for regional languages such as Kannada. In this regard there has been a recent surge of interest in designing convolutional neural networks (CNNs) for this problem. However, CNNs typically require large amounts of training data and cannot handle input transformations. Capsule networks, which is referred to as capsNets proposed recently to overcome these shortcomings and posed to revolutionize deep learning solutions. Our particular interest in this work is to recognize kannada digit characters, and making capsnet robust to rotation and transformation. In this paper, we focus to achieve the following objectives :1. Explore whether or not capsnet is capable of providing a better fit for the digit images; 2. Adapt and incorporate capsNets for the problem of kannada MNIST digit classification problem at hand; 3. develop a real time application to take handwritten input from the user and recognize the digit; 4. Compare the capsnet with other models on various parameters. Keywords: Capsule Networks, Deep Learning, Convolutional Neural Networks (CNNs), Kannada MNIST, VGG-16
Deciding Polynomial Termination Complexity for VASS Programs

We show that for every fixed degree k ? 3, the problem whether the termination/counter complexity of a given demonic VASS is O(n^k), ?(n^k), and ?(n^k) is coNP-complete, NP-complete, and DP-complete, respectively. We also classify the complexity of these problems for k ? 2. This shows that the polynomial-time algorithm designed for strongly connected demonic VASS in previous works cannot be extended to the general case. Then, we prove that the same problems for VASS games are PSPACE-complete. Again, we classify the complexity also for k ? 2. Tractable subclasses of demonic VASS and VASS games are obtained by bounding certain structural parameters, which opens the way to applications in program analysis despite the presented lower complexity bounds.
Face Swapping Using Convolutional Neural Network and Tiny Facet Primitive

Objectives  Face swapping technology has important application value in entertainment, virtual reality, film and so on. However, existing methods are limited by face pose consistency and can not overcome the influence of occlusion. Methods  We proposes a method of face swapping using convolutional neural network and tiny facet primitive. Firstly, detect the face using the cascade convolutional neural network and segment the face to determine the replacement region using fully convolutional network.Then, the Wallis transform is applied to adjust the skin color of the source image to make it consistent with the skin color of the face in the target image.After that, using facial key points detection method based on an ensemble of regression trees and Delaunay triangulation to construct the face triangulation network, then replacing faces based on tiny facet primitive. Finally, applying Poisson fusion to eliminate splicing traces between different images. Results  We evaluate the performance of the proposed method compared with existing method through qualitative and quantitative experiments. Experimental results show that face segment can well solve the problem of occlusion such as cap, glasses, and hair.Moreover, when source image and target image have different face poses, replacing face area using tiny facet primitive separately performs better than using the whole face area. Conclusions  Our method can well solve the problem of face pose consistency limitation and occlusion, which has certain practical application value.
SoK: Function-as-a-Service: From An Application Developer's Perspective

Author(s): Raza, Ali; Matta, Ibrahim; Akhtar, Nabeel; Kalavri, Vasiliki; Isahagian, Vatche | Abstract: In the past few years, FaaS has gained significant popularity and became a go-to choice for deploying cloud applications and micro-services. FaaS with its unique ‘pay as you go’ pricing model and key performance benefits over other cloud services, offers an easy and intuitive programming model to build cloud applications. In this model, a developer focuses on writing the code of the application while infrastructure management is left to the cloud provider who is responsible for the underlying resources, security, isolation, and scaling of the application. Recently, a number of commercial and open-source FaaS platforms have emerged, offering a wide range of features to application developers. In this paper, first, we present measurement studies demystifying various fea- tures and performance of commercial and open-source FaaS platforms that can help developers with deploying and con- figuring their serverless applications. Second, we discuss the distinct performance and cost benefits of FaaS and interesting use cases that leverage the performance, cost, or both aspects of FaaS. Lastly, we discuss challenges a developer may face while developing or deploying a serverless application. We also discuss state of the art solutions and open problems.
LibGuides: English - Composition and First Year Writing: Home

A research guide for students in freshman or early writing/composition classes (1005A/B, 1010, 1050, 2030, 3010, etc)
Mineral Prospectivity Mapping for Forecasting Gold Deposits in the Central Kolyma Region (North-East Russia)

Summary The emergence of a junior geological business in Russia requires support for decision-making on the choice of sites for geoprospecting on the basis of the application principle. The territory of Russia is very large, but it is completely covered by geological surveys at a scale of 1: 200,000, as well as fragmentarily by various types of geochemical and geophysical surveys on a scale of 1:50,000 - 1: 500,000. These data, together with modern remote sensing data, allow the use of MPM methods to assess the resource potential of various regions. This paper discusses the options for such a forecast, implemented on the basis of open GIS technologies, for the territory of the North-East of Russia, promising for gold and a number of other minerals.
The Types of Presupposition in the Jakarta Post's Education Articles

A speaker’s or writer’s presupposition shows a prejudice about a conversation opponent or someone being discussed. In this research, a presupposition analysis was conducted to provide information about the assumptions made by the Minister of Education and Culture Nadiem Makarim on various occasions in his speech to state his programs. It also aims to provide information to the reader that the intention conveyed by the speaker is precise and clear. Therefore, the authors declare in the various utterances that are delivered and explain the purposes. The data was taken randomly from the Jakarta Post online article about Education for a vulnerable period of one month from November 2, 2019, to December 2, 2019. This study used descriptive qualitative methods in answering questions in the problem statement; they are the explanation about what assumptions are often used by the Minister of Education and Culture and also explain the reasons for the use of these assumptions repeatedly. The assumptions found are lexical, non-factive, and counterfactual presupposition. Assumptions that are often used that aim that the use of certain expressions by the speaker is taken to presuppose other concepts (not stated), the use of certain expressions is made to presuppose the truth of the information said afterward.
Temporally Reliable Motion Vectors for Better Use of Temporal Information

We present temporally reliable motion vectors that aim at deeper exploration of temporal coherence, especially for the generally believed difficult applications on shadows, glossy reflections, and occlusions. We show that our temporally reliable motion vectors produce significantly more robust temporal results than current traditional motion vectors while introducing negligible overhead.
Pfeiffer Library: Accessing Pfeiffer Library: Individual Database Accounts

Tutorials on how to log into your online accounts at Tiffin University and Pfeiffer Library