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Articles 2701 - 2730 of 6328
Full-Text Articles in Entire DC Network
Ubiratan D’Ambrosio: Celebrating His Life And Legacy, Milton Rosa, Daniel Clark Orey
Ubiratan D’Ambrosio: Celebrating His Life And Legacy, Milton Rosa, Daniel Clark Orey
Journal of Humanistic Mathematics
On May 12th, Brazil and the world said goodbye to one of its biggest names in mathematics education, Ubiratan D’Ambrosio (December 8, 1932 – May 12, 2021). D’Ambrosio is recognized both throughout Brazil and internationally for having been the creator of ethnomathematics, a concept that acknowledges, values, and respects different mathematical ideas, procedures, and practices developed by the members of distinct cultural groups. D’Ambrosio analyzed the history of explanations of life and of natural evolution in different cultures. In the last years, his motivation had been the pursuit of peace, in all its four dimensions: individual, social, environmental, …
The Genius Box, James Propp
The Genius Box, James Propp
Journal of Humanistic Mathematics
Who gets called a genius, and why? What effect does having a special category of people called "geniuses" have on an intellectual community and on individuals within it? Drawing on my own experience, and reflecting on writings by Moon Duchin, Elizabeth Gilbert, and others, I try to find some answers.
The List: Proverbs For Calculus, Bruce H. Pourciau
The List: Proverbs For Calculus, Bruce H. Pourciau
Journal of Humanistic Mathematics
Topics chosen from first-year calculus illustrate a number of “sayings” or “proverbs,” the first three, for example, being: be awed, like a child; meaning before truth; and act with intention. Many are proverbs for life as well as mathematics.
An Interdisciplinary Rendezvous Between Mathematics And Literature: Reflections On Beauty As A Perspective In Comparative Disciplinary Didactics And A Thematic Approach To Interdisciplinary Work In Upper Secondary School, Uffe Thomas Jankvist, Helle Rørbech, Jesper Bremholm
An Interdisciplinary Rendezvous Between Mathematics And Literature: Reflections On Beauty As A Perspective In Comparative Disciplinary Didactics And A Thematic Approach To Interdisciplinary Work In Upper Secondary School, Uffe Thomas Jankvist, Helle Rørbech, Jesper Bremholm
Journal of Humanistic Mathematics
In this paper we propose a thematic focus on aesthetics in the context of an interdisciplinary collaboration between mathematics and literature (Language Arts) as a way to further students’ reflections on and deeper understanding of what characterizes the two subjects. Furthermore, we argue that approaching aesthetics through the perspective of literacy can potentially strengthen students’ understanding of ways of thinking particular to specific (academic) disciplines; ways of thinking that are otherwise often hidden when teaching focuses on more pragmatic aspects. G. H. Hardy’s A Mathematician’s Apology from 1940 serves as the recurring illustrative example in our discussions of the pedagogical …
Plot Extraction And The Visualization Of Narrative Flow, Michael A. Debuse
Plot Extraction And The Visualization Of Narrative Flow, Michael A. Debuse
Theses and Dissertations
In order to facilitate the automated extraction of complex features and structures within narrative, namely plot in this study, two proof-of-concept methods of narrative visualization are presented with the goal of representing the plot of the narrative. Plot is defined to give a basis for quality assessment and comparison. The first visualization presented is a scatter-plot of entities within the story, but due to failing to uphold the definition of plot, in-depth analysis is not performed. The second visualization presented is a graph structure that better represents a mapping of the plot of the story. Narrative structures commonly found within …
Using Big Data Analytics To Optimize Practical Large Databases, Po-Chun Lu
Using Big Data Analytics To Optimize Practical Large Databases, Po-Chun Lu
Master of Science in Computer Science Theses
Big data analytics is gaining popularity for enterprises in optimizing their business processes ranging from retailers, supply chains, to online shopping stores. Existing practical raw data are far from usable to achieve the goal. Therefore, a good data pre-processing approach is required and is a key step to success. We propose to research on the effectiveness of data pre-processing and the business process based on a real world database. Our methodology involves natural language processing. Our key goal is to study appropriate methods with big data analysis techniques that can handle errors, ambiguity, and repeated descriptions caused by human languages. …
Entity Retrieval Using Fine-Grained Entity Aspects, Shubham Chatterjee, Laura Dietz
Entity Retrieval Using Fine-Grained Entity Aspects, Shubham Chatterjee, Laura Dietz
Computer Science Faculty Research & Creative Works
Using entity aspect links, we improve upon the current state-of-the-art in entity retrieval. Entity retrieval is the task of retrieving relevant entities for search queries, such as "Antibiotic Use in Livestock". Entity aspect linking is a new technique to refine the semantic information of entity links. For example, while passages relevant to the query above may mention the entity "USA", there are many aspects of the USA of which only few, such as "USA/Agriculture", are relevant for this query. By using entity aspect links that indicate which aspect of an entity is being referred to in the context of the …
Directed Graphs Of The Finite Tropical Semiring, Caden G. Zonnefeld
Directed Graphs Of The Finite Tropical Semiring, Caden G. Zonnefeld
Rose-Hulman Undergraduate Mathematics Journal
The focus of this paper lies at the intersection of the fields of tropical algebra and graph theory. In particular the interaction between tropical semirings and directed graphs is investigated. Originally studied by Lipvoski, the directed graph of a ring is useful in identifying properties within the algebraic structure of a ring. This work builds off research completed by Beyer and Fields, Hausken and Skinner, and Ang and Shulte in constructing directed graphs from rings. However, we will investigate the relationship (x, y)→(min(x, y), x+y) as defined by the operations of tropical algebra and applied to tropical semirings.
Frameaxis: Characterizing Microframe Bias And Intensity With Word Embedding, Haewoon Kwak, Jisun An, Elise Jing Jing, Yong-Yeol Ahn
Frameaxis: Characterizing Microframe Bias And Intensity With Word Embedding, Haewoon Kwak, Jisun An, Elise Jing Jing, Yong-Yeol Ahn
Research Collection School Of Computing and Information Systems
Framing is a process of emphasizing a certain aspect of an issue over the others, nudging readers or listeners towards different positions on the issue even without making a biased argument. Here, we propose FrameAxis, a method for characterizing documents by identifying the most relevant semantic axes (“microframes”) that are overrepresented in the text using word embedding. Our unsupervised approach can be readily applied to large datasets because it does not require manual annotations. It can also provide nuanced insights by considering a rich set of semantic axes. FrameAxis is designed to quantitatively tease out two important dimensions of how …
Consulting Place As Stakeholder: Accessing The Input Of Ecological Community, Hunter Adkisson
Consulting Place As Stakeholder: Accessing The Input Of Ecological Community, Hunter Adkisson
Landscape Architecture Undergraduate Honors Theses
This is a project about how landscape architects approach the landscape in their design process. Indigenous worldviews hold that the world is living and animate in its own right. When we consider stakeholder engagement in this light, the need arises to extend the definition of stakeholders to include the ecological communities of place – the flora, fauna, soils, and other non-human elements of place. To gather that input, I experimented with techniques to access a greater awareness of ecological community at two sites with different levels of urbanity and types of land management practices. This experimental approach was surprisingly successful …
Hierarchical Mapping For Crosslingual Word Embedding Alignment, Ion Madrazo Azpiazu, Maria Soledad Pera
Hierarchical Mapping For Crosslingual Word Embedding Alignment, Ion Madrazo Azpiazu, Maria Soledad Pera
Computer Science Faculty Publications and Presentations
The alignment of word embedding spaces in different languages into a common crosslingual space has recently been in vogue. Strategies that do so compute pairwise alignments and then map multiple languages to a single pivot language (most often English). These strategies, however, are biased towards the choice of the pivot language, given that language proximity and the linguistic characteristics of the target language can strongly impact the resultant crosslingual space in detriment of topologically distant languages. We present a strategy that eliminates the need for a pivot language by learning the mappings across languages in a hierarchicalway. Experiments demonstrate that …
Dehumor: Visual Analytics For Decomposing Humor, Xingbo Wang, Yao Ming, Tongshuang Wu, Haipeng Zeng, Yong Wang, Huamin Qu
Dehumor: Visual Analytics For Decomposing Humor, Xingbo Wang, Yao Ming, Tongshuang Wu, Haipeng Zeng, Yong Wang, Huamin Qu
Research Collection School Of Computing and Information Systems
Despite being a critical communication skill, grasping humor is challenginga successful use of humor requires a mixture of both engaging content build-up and an appropriate vocal delivery (e.g., pause). Prior studies on computational humor emphasize the textual and audio features immediately next to the punchline, yet overlooking longer-term context setup. Moreover, the theories are usually too abstract for understanding each concrete humor snippet. To fill in the gap, we develop DeHumor, a visual analytical system for analyzing humorous behaviors in public speaking. To intuitively reveal the building blocks of each concrete example, DeHumor decomposes each humorous video into multimodal features …
Rnnrepair: Automatic Rnn Repair Via Model-Based Analysis, Xiaofei Xie, Wenbo Guo, Lei Ma, Wei Le, Jian Wang, Lingjun Zhou, Yang Liu, Xinyu Xing
Rnnrepair: Automatic Rnn Repair Via Model-Based Analysis, Xiaofei Xie, Wenbo Guo, Lei Ma, Wei Le, Jian Wang, Lingjun Zhou, Yang Liu, Xinyu Xing
Research Collection School Of Computing and Information Systems
Deep neural networks are vulnerable to adversarial attacks. Due to their black-box nature, it is rather challenging to interpret and properly repair these incorrect behaviors. This paper focuses on interpreting and repairing the incorrect behaviors of Recurrent Neural Networks (RNNs). We propose a lightweight model-based approach (RNNRepair) to help understand and repair incorrect behaviors of an RNN. Specifically, we build an influence model to characterize the stateful and statistical behaviors of an RNN over all the training data and to perform the influence analysis for the errors. Compared with the existing techniques on influence function, our method can efficiently estimate …
Effect Of Team Cohesion Nn Flow: An Empirical Study Of Team-Based Gamification For Enterprise Resource Planning Systems In Online Classes, Yu Zhao, Mark Srite, Sumin Kim, Jinwoong Lee
Effect Of Team Cohesion Nn Flow: An Empirical Study Of Team-Based Gamification For Enterprise Resource Planning Systems In Online Classes, Yu Zhao, Mark Srite, Sumin Kim, Jinwoong Lee
Business and Information Technology Faculty Research & Creative Works
Pedagogy using gamification has recently received much attention as a way of enhancing student learning and retention. Additionally, academic institutions are making extensive use of online resources to expand teaching beyond the traditional classroom setting. Both academic institutions and companies utilize virtual teams to accomplish remote teamwork, particularly in a post-COVID environment. Despite the growing interest in incorporating gamification into teaching for business school courses, prior researchers have paid little attention to team-based gamification in the online learning environment. The purpose of this study is to examine if team members' perceived team cohesion influences their perceptions of flow. Also, we …
Unified Conversational Recommendation Policy Learning Via Graph-Based Reinforcement Learning, Yang Deng, Yaliang Li, Fei Sun, Bolin Ding, Wai Lam
Unified Conversational Recommendation Policy Learning Via Graph-Based Reinforcement Learning, Yang Deng, Yaliang Li, Fei Sun, Bolin Ding, Wai Lam
Research Collection School Of Computing and Information Systems
Conversational recommender systems (CRS) enable the traditional recommender systems to explicitly acquire user preferences towards items and attributes through interactive conversations. Reinforcement learning (RL) is widely adopted to learn conversational recommendation policies to decide what attributes to ask, which items to recommend, and when to ask or recommend, at each conversation turn. However, existing methods mainly target at solving one or two of these three decision-making problems in CRS with separated conversation and recommendation components, which restrict the scalability and generality of CRS and fall short of preserving a stable training procedure. In the light of these challenges, we propose …
Indonesian Sentence Boundary Detection Using Deep Learning Approaches, Joan Santoso, Esther Irawati Setiawan, Christian Nathaniel Purwanto, Fachrul Kurniawan
Indonesian Sentence Boundary Detection Using Deep Learning Approaches, Joan Santoso, Esther Irawati Setiawan, Christian Nathaniel Purwanto, Fachrul Kurniawan
Knowledge Engineering and Data Science
Detecting the sentence boundary is one of the crucial pre-processing steps in natural language processing. It can define the boundary of a sentence since the border between a sentence, and another sentence might be ambiguous. Because there are multiple separators and dynamic sentence patterns, using a full stop at the end of a sentence is sometimes inappropriate. This research uses a deep learning approach to split each sentence from an Indonesian news document. Hence, there is no need to define any handcrafted features or rules. In Part of Speech Tagging and Named Entity Recognition, we use sequence labeling to determine …
An Automated Method To Enrich And Expand Consumer Health Vocabularies Using Glove Word Embeddings, Mohammed Ibrahim
An Automated Method To Enrich And Expand Consumer Health Vocabularies Using Glove Word Embeddings, Mohammed Ibrahim
Graduate Theses and Dissertations
Clear language makes communication easier between any two parties. However, a layman may have difficulty communicating with a professional due to not understanding the specialized terms common to the domain. In healthcare, it is rare to find a layman knowledgeable in medical jargon, which can lead to poor understanding of their condition and/or treatment. To bridge this gap, several professional vocabularies and ontologies have been created to map laymen medical terms to professional medical terms and vice versa. Many of the presented vocabularies are built manually or semi-automatically requiring large investments of time and human effort and consequently the slow …
Towards A Large-Scale Intelligent Mobile-Argumentation And Discovering Arguments, Controversial Topics And Topic-Oriented Focal Sets In Cyber-Argumentation, Najla Althuniyan
Towards A Large-Scale Intelligent Mobile-Argumentation And Discovering Arguments, Controversial Topics And Topic-Oriented Focal Sets In Cyber-Argumentation, Najla Althuniyan
Graduate Theses and Dissertations
User-generated content (UGC) platforms host different forms of information, such as audio, video, pictures, and text. They have many online applications, such as social media, blogs, photo and video sharing, customer reviews, debate, and deliberation platforms. Usually, the content of these platforms is provided and consumed by users. Most of these platforms, mainly social media and blogs, are often used for online discussion. These platforms offer tools for users to share and express opinions. Commonly, people from different backgrounds and origins discuss opinions about various issues over the Internet. Furthermore, discussions among users contain substantial information from which knowledge about …
Self-Supervised Contrastive Learning For Code Retrieval And Summarization Via Semantic-Preserving Transformations, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang
Self-Supervised Contrastive Learning For Code Retrieval And Summarization Via Semantic-Preserving Transformations, Duy Quoc Nghi Bui, Yijun Yu, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
We propose Corder, a self-supervised contrastive learning framework for source code model. Corder is designed to alleviate the need of labeled data for code retrieval and code summarization tasks. The pre-trained model of Corder can be used in two ways: (1) it can produce vector representation of code which can be applied to code retrieval tasks that do not have labeled data; (2) it can be used in a fine-tuning process for tasks that might still require label data such as code summarization. The key innovation is that we train the source code model by asking it to recognize similar …
Make It Easy: An Effective End-To-End Entity Alignment Framework, Congcong Ge, Xiaoze Liu, Lu Chen Chen, Baihua Zheng, Yunjun Gao
Make It Easy: An Effective End-To-End Entity Alignment Framework, Congcong Ge, Xiaoze Liu, Lu Chen Chen, Baihua Zheng, Yunjun Gao
Research Collection School Of Computing and Information Systems
Entity alignment (EA) is a prerequisite for enlarging the coverage of a unified knowledge graph. Previous EA approaches either restrain the performance due to inadequate information utilization or need labor-intensive pre-processing to get external or reliable information to perform the EA task. This paper proposes EASY, an effective end-to-end EA framework, which is able to (i) remove the labor-intensive pre-processing by fully discovering the name information provided by the entities themselves; and (ii) jointly fuse the features captured by the names of entities and the structural information of the graph to improve the EA results. Specifically, EASY first introduces NEAP, …
Latinx Students’ Mathematics Anxiety And Their Study Habits: Exploring Their Relationship At The Postsecondary Level, Luis M. Fernandez, Xiaohui Wang, Olga Ramirez, Cristina Villalobos
Latinx Students’ Mathematics Anxiety And Their Study Habits: Exploring Their Relationship At The Postsecondary Level, Luis M. Fernandez, Xiaohui Wang, Olga Ramirez, Cristina Villalobos
School of Mathematical & Statistical Sciences Faculty Publications
Increasing Latinx students’ success in college-level mathematics calls for exploration on their mathematics anxiety as it relates to study habits. Using a sample of Latinx students in a Hispanic Serving Institution and their levels of mathematics anxiety, pairwise analyses revealed significant differences among subgroups. Moreover, regression analyses showed Latinx students’ study habits being predictive of mathematics anxiety. As a result, recommendations are provided that could alleviate mathematics anxiety and its effects on Latinx college students.
Swarm Differential Privacy For Purpose-Driven Data-Information-Knowledge-Wisdom Architecture, Yingbo Li, Yucong Duan, Zakaria Maamar, Haoyang Che, Anamaria-Beatrice Spulber, Stelios Fuentes
Swarm Differential Privacy For Purpose-Driven Data-Information-Knowledge-Wisdom Architecture, Yingbo Li, Yucong Duan, Zakaria Maamar, Haoyang Che, Anamaria-Beatrice Spulber, Stelios Fuentes
All Works
Privacy protection has recently been in the spotlight of attention to both academia and industry. Society protects individual data privacy through complex legal frameworks. The increasing number of applications of data science and artificial intelligence has resulted in a higher demand for the ubiquitous application of the data. The privacy protection of the broad Data-Information-Knowledge-Wisdom (DIKW) landscape, the next generation of information organization, has taken a secondary role. In this paper, we will explore DIKW architecture through the applications of the popular swarm intelligence and differential privacy. As differential privacy proved to be an effective data privacy approach, we will …
Prediction Method For Health Degree Of Front Bearing Of Wind Turbine Generator And Implementation, Yin Shi, Guolian Hou, Chi Yan, Linjuan Gong, Xiaodong Hu
Prediction Method For Health Degree Of Front Bearing Of Wind Turbine Generator And Implementation, Yin Shi, Guolian Hou, Chi Yan, Linjuan Gong, Xiaodong Hu
Journal of System Simulation
Abstract: Aiming at the deterioration trend of front bearing of doubly-fed wind turbine generator, a new combined modeling method is proposed to predict health degree of front bearing of generator. The GMM is used to identify operating conditions of wind turbines. The temperature model of front bearing based on ELM is established respectively in each sub-condition. Combining with temperature residual characteristics and time-frequency characteristics of vibration signal, the health degree of front bearing is calculated. Based on attention mechanism, the Bi-LSTM neural network is proposed to model and predict health degree of front bearing. The result shows that the …
The Early Medieval Transition: Diet Reconstruction, Mobility, And Culture Contact In The Ravenna Countryside, Northern Italy, Anastasia Temkina
The Early Medieval Transition: Diet Reconstruction, Mobility, And Culture Contact In The Ravenna Countryside, Northern Italy, Anastasia Temkina
USF Tampa Graduate Theses and Dissertations
This research project evaluates the effects of increased mobility and culture contact on dietary practices, and on dietary variation among people buried at two northern Italian sites, Chiunsano di Ficarolo and Chiesazza di Ficarolo, located near the ancient Roman capital of Ravenna and dating 4th to 7th century CE. The Early Medieval period was a time of change, political instability, migration and invasion of the “barbarian” tribes, and diet was not unaffected. In particular, it is hypothesized that a new staple crop, millet, was introduced and that meat consumption had increased. The goal of this research is to use stable …
Turkic Interlingua: A Case Study Of Machine Translation In Low-Resource Languages, Jamshidbek Mirzakhalov
Turkic Interlingua: A Case Study Of Machine Translation In Low-Resource Languages, Jamshidbek Mirzakhalov
USF Tampa Graduate Theses and Dissertations
Machine Translation (MT) has the potential to bridge the gap between the developed world and the marginalized communities by making information more accessible in real-time. While there are over 7000 spoken languages in the world, only about a hundred have access to high-quality MT systems and even fewer enjoy the benefits of more advanced language technologies. Unfortunately, resource scarcity and the lack of digital infrastructure are only some of the many challenges associated with globalizing NLP. Many large-scale multilingual studies and datasets often get little to no feedback from native speakers or linguistic experts of the languages involved, leading to …
Spatial Knowledge Representation Model Of Simulation Scenario Based On Ontology, Zhu Jie, Hongjun Zhang
Spatial Knowledge Representation Model Of Simulation Scenario Based On Ontology, Zhu Jie, Hongjun Zhang
Journal of System Simulation
Abstract: Military simulation scenario has abundant spatial knowledge and is closely related to various models of combat simulation. In view of the lack of uniform specification for the description of simulation scenario knowledge, it is necessary to construct a spatial knowledge representation model in line with spatial thinking to effectively analyze the spatial entities and their interrelationships in simulation scenario. The ontology method is used to establish spatial knowledge domain ontology and form the formal description specification of spatial knowledge concept; the spatial knowledge structure is described hierarchically by using the method of concept knowledge tree, clarifying the semantic logic …
Identifying Optimal Course Structures Using Topic Models, Tehut Tesfaye Biru
Identifying Optimal Course Structures Using Topic Models, Tehut Tesfaye Biru
Dartmouth College Undergraduate Theses
This research project investigates whether there exists an optimal way to structure topics in educational course content that results in higher levels of engagement among students. It is implemented by fitting topic models to transcripts of educational videos contained in the Khan Academy platform. The fitted models were used to extract topic trajectories across time for each video and subsequently clustered based on whether they have similar “shapes”. The differences in mean engagement metrics per cluster suggest that some course shapes are more palatable to students regardless of subject matter. Additionally, the topic trajectories suggest a constant progression of topics …
On The Generalization Of Interval Valued Fuzzy Generalized Bi-Ideals In Ordered Semigroups, Muhammad S. Ali Khan, Saleem Abdullah, Kostaq Hila
On The Generalization Of Interval Valued Fuzzy Generalized Bi-Ideals In Ordered Semigroups, Muhammad S. Ali Khan, Saleem Abdullah, Kostaq Hila
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, a new general form than interval valued fuzzy generalized bi-ideals in ordered semigroups is introduced. The concept of interval valued fuzzy generalized bi-ideals is initiated and several properties and characterizations are provided. A condition for an interval valued fuzzy generalized bi-ideal to be an interval valued fuzzy generalized bi-ideal is obtained. Using implication operators and the notion of implication-based an interval valued fuzzy generalized bi-ideal, characterizations of an interval valued fuzzy generalized bi-ideal and an interval valued fuzzy generalized bi-ideal are considered.
Why Cauchy Membership Functions: Efficiency, Javier Viana, Stephan Ralescu, Kelly Cohen, Anca Ralescu, Vladik Kreinovich
Why Cauchy Membership Functions: Efficiency, Javier Viana, Stephan Ralescu, Kelly Cohen, Anca Ralescu, Vladik Kreinovich
Departmental Technical Reports (CS)
Fuzzy techniques depend heavily on eliciting meaningful membership functions for the fuzzy sets used. Often such functions are obtained from data. Just as often they are obtained from experts knowledgable of the domain and the problem being addressed. However, there are cases when neither is possible, for example because of insufficient data, or unavailable experts. What functions should one choose and what should guide such choice? This paper argues in favor of using Cauchy membership functions, thus named because their expression is similar to that of the Cauchy distributions. The paper provides a theoretical explanation for this choice.
Lexical Complexity Prediction With Assembly Models, Aadil Islam
Lexical Complexity Prediction With Assembly Models, Aadil Islam
Dartmouth College Undergraduate Theses
Tuning the complexity of one's writing is essential to presenting ideas in a logical, intuitive manner to audiences. This paper describes a system submitted by team BigGreen to LCP 2021 for predicting the lexical complexity of English words in a given context. We assemble a feature engineering-based model and a deep neural network model with an underlying Transformer architecture based on BERT. While BERT itself performs competitively, our feature engineering-based model helps in extreme cases, eg. separating instances of easy and neutral difficulty. Our handcrafted features comprise a breadth of lexical, semantic, syntactic, and novel phonetic measures. Visualizations of BERT …