Janani Durairaj (10344975), Elena Melillo (10344978), Harro J. Bouwmeester (10344981) et al. · Figshare · 2021
<p>Classification framework of gradient boosting trees, to deal with a large number of residue-based features as well as allow for intuitive selection of the most predictive residues. A separate gradient boosting tree (GbT-s) is trained on each kind of feature across all aligned residue indices. The weights obtained from all the GbT-s classifiers are pooled (by taking the sum of the normalized weights) to select the top 30 residues. All feature values of these selected residues are used as input to the final classifier GbT. The parameter settings of the GbT-s and GbT classifiers are listed in Materials and Methods.</p> <p>(PDF)</p>
Cited by 0Open access
Koroncziová, Dominika · Brno University of Technology Digital Library (Brno University of Technology) · 2014
Cílem této práce je návrh a implementace klasifikačního software postaveného na knihovně RapidMiner. Výsledná aplikace bude sdružovat nejpoužívanější algoritmy a procesy implementované v RapidMineru do jednoduchého použitelného programu. Součástí nároků na aplikaci je jednoduché rozhraní pro ovládání z příkazové řádky, stejně jako grafické rozhraní zjednodušující nastavení více parametrů. Aplikace má také umožňovat tvorbu samostatných jednoúčelových programů, sloužících na opakovanou klasifikaci s použitím předem natrénovaného modelu. Nad rámec původního zadání je implementována i práce s textovými daty z Wikipedie, jejich stáhnutí a předzpracování a následné použití jako trénovacích dat. Text práce se zabývá postupně jednotlivými algoritmy a popisem kvalifikačních algoritmů, jejich vlastnostmi a použitím, a popisuje návrh a implementaci systému. V rámci práce byla vykonána i sada několika testů pro ověření výkonu a funkcionality aplikace. Jejich výsledky jsou shrnuty v závěru práce.
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Jiyuan Feng (21213107), Bin Yu (14464), Wee Hoe Tan (20824415) et al. · Figshare · 2025
<div> In the current globalised educational environment, higher education increasingly relied on educational technology to enhance teaching and learning outcomes. Therefore, exploring the decisive factors influencing the adoption of educational technology was crucial for its successful implementation. This paper employed a systematic review using the PRISMA method to investigate four key dimensions affecting educational technology adoption: Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions. Through a thorough examination of relevant literature, this review deepened the understanding of the core factors influencing the adoption process. A total of 1,891 studies related to educational technology adoption, published between 2015 and 2024, were initially identified, with 39 studies remaining after careful selection for analysis. The classification analysis revealed that all articles were categorised under the four themes: Performance Expectancy (8 articles), Effort Expectancy (18 articles), Social Influence (5 articles), and Facilitating Conditions (8 articles). This review provided valuable insights for higher education institutions aiming to enhance educational quality through the adoption of advanced educational technologies, and it also made a significant contribution to the existing academic literature. However, the interactions between the four dimensions warrant further exploration. </div>
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Jiajie Tan (17606883), Yingying Li (50341) · Figshare · 2024
<div><p>The purpose of this study is to understand how consumers perceive amenities and their impact on promoting positive consumer emotions and comprehend the role of amenities in fostering urban consumption. We collected over 120,000 comments spanning 60 months (2015–2019) from 18 urban shopping centers in Shanghai. By applying text mining methods, we constructed a panel data model on the perception of four types of amenities and consumer emotions. Results indicate that different perceptions of amenities yield significantly different effects on consumer emotions. Specifically, we found that perceptions of cultural and safeguarded amenities significantly influence consumer emotions, albeit with different directions of impact. In contrast, perceptions of commercial and natural amenities did not significantly affect consumer emotions. The findings of this study provide a key reference for how to scientifically plan and reasonably introduce the types of amenities in urban consumption space, so as to reflect the promoting effect of amenities on urban consumption.</p></div>
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Mina Cintho Ozahata · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2014
Um grande número de medicamentos utilizados no tratamento contra o HIV agem procurando inibir a ação das proteínas transcriptase reversa e protease. Mutações existentes nas sequências dessas proteínas podem estar relacionadas à resistência aos medicamentos e podem prejudicar o desempenho de um tratamento. O estudo do genótipo dos vírus pode ajudar na tomada de escolhas específicas em tratamentos para cada indivíduo, tornando maiores a chance de sucesso. Com a maior acessibilidade a exames de genotipagem, uma grande quantidade de sequências do vírus está disponível, contendo um grande volume de informação. Padrões de ocorrência de mutações são exemplos de informações contidas nessas sequências e são importantes por estarem relacionados à resistência aos medicamentos. Um dos caminhos que pode ser capaz de nos levar ao entendimento desses padrões de mutações é a aplicação de técnicas de agrupamento e biclustering. Essas técnicas visam a geração de grupos ou biclusters que possuam dados com propriedades em comum. São empregadas em casos em que não há grande quantidade de informação prévia e existem poucas hipóteses sobre os dados. Assim, pode-se encontrar os padrões de mutações que ocorrem nessas sequências e tentar relacioná-los com a resistência aos medicamentos, utilizando métodos de agrupamento e bicluster em sequências de protease e transcriptase reversa. Existem alguns sistemas que tentam predizer a resistência ou susceptibilidade das sequências, porém, devido à grande complexidade dessa relação, ainda é necessário esclarecer o vínculo entre combinações de mutações e níveis de resistência fenotípica. Desta forma, a principal contribuição deste trabalho é o desenvolvimento de um framework baseado na aplicação dos algoritmos KMédias e Bimax às sequências de transcriptase reversa e protease de pacientes infectados com HIV, em uma codificação binária. O presente trabalho também introduz uma representação visual dos grupos e biclusters baseada em dados de microarranjos para casos em que se tem grandes volumes de dados, de forma a facilitar a visualização da informação extraída e a caracterização dos grupos e biclusters no domínio da doença.
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Hipólito Sousa, Pedro Mêda · Open Repository of the University of Porto (University of Porto) · 2015
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TORSELLO M. A, CASTIELLO, CIRO, FANELLI, Anna Maria · CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) · 2006
Cited by 15
May Alhazzani (5452238), Fahad Alhasoun (5452241), Zeyad Alawwad (10701409) et al. · Figshare · 2021
<p>It shows all sub-processes to identify attractor profiles. It relies on two data sources: Call Detail Records (CDRs) and Points of Interests (POIs) to detect attractors and relate types of places (POIs) to each attractor pattern.</p>
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Tsui, Eric · PolyU Institutional Research Archive (Hong Kong Polytechnic University)
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Shamik Tiwari (4490185), Akhilesh Kumar Sharma (10288628), Izzatdin Abdul Aziz (17782422) et al. · Figshare · 2025
<div><p>Texture is a significant component used for several applications in content-based image retrieval. Any texture classification method aims to map an anonymously textured input image to one of the existing texture classes. Extensive ranges of methods for labeling image texture were proposed earlier. However, computing the performance of these methods in the presence of various degradations is always an open area of discussion. Image noise is always a dominant factor among various image degradation factors, affecting the performance of these methods and making texture classification challenging. Therefore, it is essential to investigate the interpretation of these methods in the presence of prominent degradation factors such as noise. Applications for Segmentation-Based Fractal Texture Features (SFTF) include image classification, texture generation, and medical image analysis. They are beneficial for examining textures with intricate, erratic patterns that are difficult to characterize using conventional statistical techniques accurately. This paper assesses two texture feature extraction methods based on SFTF and statistical moment-based texture features in the presence and absence of Gaussian noise. The SFTF and statistical moments-based handcrafted features are passed to a multilayer feed-forward neural network for classification. These models are evaluated on natural textures from Kylberg Texture Dataset 1.0. The results show the superiority of segmentation-based fractal analysis over other approaches. The average accuracy rates using the SFTF are 99% and 97% in the absence and presence of Gaussian noise, respectively.</p></div>
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Victoria Vargas (14504413), Weston W. Blakeslee (14504416), Colin A. Banas (14504419) et al. · Figshare · 2023
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Sravya Madala, Vani K. Suvarna, Pranathi Jalapally · Smart innovation, systems and technologies · 2022
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Loo-Nin Teow, Kia-Fock Loe · arXiv (Cornell University) · 2013
We define a generalized likelihood function based on uncertainty measures and show that maximizing such a likelihood function for different measures induces different types of classifiers. In the probabilistic framework, we obtain classifiers that optimize the cross-entropy function. In the possibilistic framework, we obtain classifiers that maximize the interclass margin. Furthermore, we show that the support vector machine is a sub-class of these maximum-margin classifiers.
Cited by 1Open access
Yun Ma, Hao Du · 2021
Cited by 1
Kenneth Fjell · Journal of Public Policy · 2001
Cross-subsidization is a frequent topic in public debates and often stigmatized in the wake of deregulation. Public monopolies increasingly find themselves operating not only in regulated markets, but in non-regulated markets where they are accused of illegally using resources from the regulated market to stifle competition. Similar anticompetitive allegations can be made against private multiservice firms with market power. However, definitions of cross-subsidization are many and this affects the debate about the issue and possible strategic motives behind cross-subsidization, its possible consequences for competition, and measures that might be taken against it. This paper organizes definitions that regulators are likely to encounter into three types involving cost transfer, temporary loss or permanent loss. Based on these distinctions, a novel classification framework is developed according to underlying motivation and consequences for competition. The four cases arising from the framework are subsequently discussed in terms of relevancy for public and private firms, and consequences for competition and welfare.
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Seventh Session · 2009
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Hugh G. Lewis, Margaret Brown · ePrints Soton (University of Southampton) · 1997
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Information Visualization, Ulrika Wiss, David Carr · 2015
This paper presents a framework for a cognitive classification of three-dimensional information visualization. Three cognitive aspects are discussed: attention, abstraction, and affordances. Based on these aspects, fifteen three-dimensional information visualization designs are studied. We find that attention and abstraction techniques are fairly well represented, but that affordances are more scarce. Based on this, we suggest that three-dimensional information visualizations are still mainly seen as computer graphics. We suggest that the next step for this research field is to consider three-dimensional information visualization a full-fledged user interface.
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Nazmus Sakib (8944931), G. M. Shahariar (20629829), Md. Mohsinul Kabir (20629832) et al. · Figshare · 2025
<div> Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation. However, categorizing raw recipes found online into appropriate food genres can be challenging due to a lack of adequate labeled data. In this study, we present a dataset named the “Assorted, Archetypal, and Annotated Two Million Extended (3A2M+) Cooking Recipe Dataset” that contains two million culinary recipes labeled in respective categories with extended named entities extracted from recipe descriptions. This collection of data includes various features such as title, NER, directions, and extended NER, as well as nine different labels representing genres including bakery, drinks, non-veg, vegetables, fast food, cereals, meals, sides, and fusions. The proposed pipeline named 3A2M+ extends the size of the Named Entity Recognition (NER) list to address missing named entities like heat, time or process from the recipe directions using two NER extraction tools. 3A2M+ dataset provides a comprehensive solution to the various challenging recipe-related tasks, including classification, named entity recognition, and recipe generation. Furthermore, we have demonstrated traditional machine learning, deep learning and pre-trained language models to classify the recipes into their corresponding genre and achieved an overall accuracy of 98.6%. Our investigation indicates that the title feature played a more significant role in classifying the genre. </div>
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Yow, Li Wen · IEEE DataPort · 2025
This repository contains the code and documentation for a computational framework that leverages machine learning techniques to enable accurate classification of bacterial species, even closely related strains.The framework integrates genomic analysis methods, such as motif screening and single nucleotide polymorphism (SNP) extraction, to derive informative features from bacterial genomes. These genomic insights are then fed into machine learning models, which are trained to reliably differentiate between bacterial species based on their distinctive patterns and characteristics.
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