1,721,276 research outputs found
Towards Human Cognition Level-based Experiment Design for Counterfactual Explanations (XAI)
Full text linkExplainable Artificial Intelligence (XAI) has recently gained a swell of
interest, as many Artificial Intelligence (AI) practitioners and developers are
compelled to rationalize how such AI-based systems work. Decades back, most XAI
systems were developed as knowledge-based or expert systems. These systems
assumed reasoning for the technical description of an explanation, with little
regard for the user's cognitive capabilities. The emphasis of XAI research
appears to have turned to a more pragmatic explanation approach for better
understanding. An extensive area where cognitive science research may
substantially influence XAI advancements is evaluating user knowledge and
feedback, which are essential for XAI system evaluation. To this end, we
propose a framework to experiment with generating and evaluating the
explanations on the grounds of different cognitive levels of understanding. In
this regard, we adopt Bloom's taxonomy, a widely accepted model for assessing
the user's cognitive capability. We utilize the counterfactual explanations as
an explanation-providing medium encompassed with user feedback to validate the
levels of understanding about the explanation at each cognitive level and
improvise the explanation generation methods accordingly.Comment: 5 pages, 2 figure
Gender Classification Using Smartphone Sensors and Machine Learning Approaches
No full textGait analysis is typically associated with the pattern of the human walk. Determining it with computational means can be helpful in many ways-from identifying individual humans to detecting gait-related diseases. In comparison to the expensive approaches and devices, which are limited to laboratories, smart- phones with motion sensors are low-cost solutions through which we can analyze mobility and gait patterns. Thus, in this work, we present the usage of smartphone sensors for data acquisition followed by machine learning-based gender classification, which is a baseline for different gait-related tasks. In this regard, we collected data from 14 persons in different tracks, paces, and movement styles; after adequate normalization, iterative feature elimination, and Monte-Carlo experiment-based ML training, we found the Decision Tree is the most optimal algorithm with attaining 90.6 % balanced-accuracy
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Multi-Criteria Framework for Region Selection in On-Demand Rural Mobility for mybuxi
No full textDie Herausforderungen bei der Bereitstellung inklusiver, nachhaltiger und effizienter Mobilitäts- und Transportdienstleistungen in ländlichen und halbländlichen Regionen der Schweiz werden aufgrund sozioökonomischer Veränderungen, Umweltziele, demografischer Veränderungen und der Grenzen der konventionellen öffentlichen Verkehrsnetze immer größer. Diese Arbeit implementiert einen Rahmen für die multikriterielle Entscheidungsanalyse (MCDA) in Form eines digitalen Tools, um die strategische Expansion des On-Demand-Elektromobilitätsdienstes von mybuxi in der Schweiz zu unterstützen. Durch die Integration verschiedener Datenquellen, darunter georäumliche, demografische, sozioökonomische, und betriebliche Indikatoren für die Erreichbarkeit mit öffentlichen Verkehrsmitteln, bewertet das Framework die Eignung von Regionen für den Einsatz von On-Demand-Mobilitätsdiensten. Die Daten wurden von den Schweizer Bundesbehörden erhoben und mithilfe fortschrittlicher räumlicher Analyse- und Python-basierter Datenintegrationstechniken verarbeitet. Die Expertenmeinung des mybuxi-Managements wurde eingeholt und für die Gewichtung von 15 Unterkriterien herangezogen. Die Analyse bewertete insgesamt 2053 Gemeinden mit Filtern für die beste Erreichbarkeit mit öffentlichen Verkehrsmitteln und Bevölkerungsfiltern, um weitere 1247 Gemeinden zu identifizieren, wobei Wienfelden, Altstätten und Davos als die am besten geeigneten Standorte für ein potenzielles Dienstleistungsangebot ermittelt wurden. Eine Sensitivitätsanalyse bestätigte die Robustheit des Rahmens durch die Bewertung mehrerer strategischer Szenarien. Darüber hinaus zeigt die Studie eine starke Übereinstimmung mit den Zielen der Vereinten Nationen für nachhaltige Entwicklung (SDGs), insbesondere in den Bereichen soziale Gerechtigkeit, wirtschaftliche Entwicklung und Klimaschutz. Diese Forschung leistet einen Beitrag zum Bereich der Mobilitätsplanung, indem sie die Herausforderungen in einem strukturierten und datengestützten Rahmen für die Auswahl von Regionen angeht. Sie bietet sowohl eine reproduzierbare Methodik als auch umsetzbare Erkenntnisse für politische Entscheidungsträger, Dienstleister und alle betroffenen Interessengruppen, die an der Umstellung auf nachhaltige Mobilität im ländlichen Raum beteiligt sind.The challenges of providing sustainable, inclusive, and efficient transportation in rural and semirural regions are becoming increasingly prominent due to socio-demographic shifts, environmental goals, and the limitations of conventional public transportations. This thesis develops a Multi-Criteria Decision Analysis (MCDA) framework to support the strategic expansion of mybuxi’s on-demand electric mobility services within Switzerland. Integrating diverse data sources which including geospatial, demographic, socio-economic, operational, and public transport accessibility indicators—the framework systematically evaluates regional suitability for the deployment of on-demand mobility services. Data were collected from Swiss federal authorities and processed using advanced spatial analysis and Python-based data integration techniques. Stakeholder engagement, including expert input from mybuxi management, informed the weighting of 15 carefully selected sub-criteria, ensuring practical relevanc. The analysis assessed a total of 2053 municipalities with filters of public transport accessibility classes and population numbers to further identify 1,247 municipalities, revealing Weinfelden, Altstätten, and Davos as the highest-ranked locations for potential expansion. Sensitivity analyses confirmed the framework's robustness under multiple strategic scenarios. Furthermore, the study demonstrates strong alignment with multiple United Nations Sustainable Development Goals (SDGs), especially in areas of social equity, economic development, and climate action. This research contributes to the growing field of mobility planning by addressing the gap in a structured, data-driven region selection model, providing both a replicable methodology and actionable insights for policymakers, service providers, and stakeholders involved in sustainable rural mobility transitions.by: Muhammad Yaseen MujahidMasterarbeit Fachhochschule Technikum Wien 202
Multi-Criteria Framework for Region Selection in On-Demand Rural Mobility for mybuxi
No full textDie Herausforderungen bei der Bereitstellung inklusiver, nachhaltiger und effizienter Mobilitäts- und Transportdienstleistungen in ländlichen und halbländlichen Regionen der Schweiz werden aufgrund sozioökonomischer Veränderungen, Umweltziele, demografischer Veränderungen und der Grenzen der konventionellen öffentlichen Verkehrsnetze immer größer. Diese Arbeit implementiert einen Rahmen für die multikriterielle Entscheidungsanalyse (MCDA) in Form eines digitalen Tools, um die strategische Expansion des On-Demand-Elektromobilitätsdienstes von mybuxi in der Schweiz zu unterstützen. Durch die Integration verschiedener Datenquellen, darunter georäumliche, demografische, sozioökonomische, und betriebliche Indikatoren für die Erreichbarkeit mit öffentlichen Verkehrsmitteln, bewertet das Framework die Eignung von Regionen für den Einsatz von On-Demand-Mobilitätsdiensten. Die Daten wurden von den Schweizer Bundesbehörden erhoben und mithilfe fortschrittlicher räumlicher Analyse- und Python-basierter Datenintegrationstechniken verarbeitet. Die Expertenmeinung des mybuxi-Managements wurde eingeholt und für die Gewichtung von 15 Unterkriterien herangezogen. Die Analyse bewertete insgesamt 2053 Gemeinden mit Filtern für die beste Erreichbarkeit mit öffentlichen Verkehrsmitteln und Bevölkerungsfiltern, um weitere 1247 Gemeinden zu identifizieren, wobei Wienfelden, Altstätten und Davos als die am besten geeigneten Standorte für ein potenzielles Dienstleistungsangebot ermittelt wurden. Eine Sensitivitätsanalyse bestätigte die Robustheit des Rahmens durch die Bewertung mehrerer strategischer Szenarien. Darüber hinaus zeigt die Studie eine starke Übereinstimmung mit den Zielen der Vereinten Nationen für nachhaltige Entwicklung (SDGs), insbesondere in den Bereichen soziale Gerechtigkeit, wirtschaftliche Entwicklung und Klimaschutz. Diese Forschung leistet einen Beitrag zum Bereich der Mobilitätsplanung, indem sie die Herausforderungen in einem strukturierten und datengestützten Rahmen für die Auswahl von Regionen angeht. Sie bietet sowohl eine reproduzierbare Methodik als auch umsetzbare Erkenntnisse für politische Entscheidungsträger, Dienstleister und alle betroffenen Interessengruppen, die an der Umstellung auf nachhaltige Mobilität im ländlichen Raum beteiligt sind.The challenges of providing sustainable, inclusive, and efficient transportation in rural and semirural regions are becoming increasingly prominent due to socio-demographic shifts, environmental goals, and the limitations of conventional public transportations. This thesis develops a Multi-Criteria Decision Analysis (MCDA) framework to support the strategic expansion of mybuxi’s on-demand electric mobility services within Switzerland. Integrating diverse data sources which including geospatial, demographic, socio-economic, operational, and public transport accessibility indicators—the framework systematically evaluates regional suitability for the deployment of on-demand mobility services. Data were collected from Swiss federal authorities and processed using advanced spatial analysis and Python-based data integration techniques. Stakeholder engagement, including expert input from mybuxi management, informed the weighting of 15 carefully selected sub-criteria, ensuring practical relevanc. The analysis assessed a total of 2053 municipalities with filters of public transport accessibility classes and population numbers to further identify 1,247 municipalities, revealing Weinfelden, Altstätten, and Davos as the highest-ranked locations for potential expansion. Sensitivity analyses confirmed the framework's robustness under multiple strategic scenarios. Furthermore, the study demonstrates strong alignment with multiple United Nations Sustainable Development Goals (SDGs), especially in areas of social equity, economic development, and climate action. This research contributes to the growing field of mobility planning by addressing the gap in a structured, data-driven region selection model, providing both a replicable methodology and actionable insights for policymakers, service providers, and stakeholders involved in sustainable rural mobility transitions.by: Muhammad Yaseen MujahidMasterarbeit Fachhochschule Technikum Wien 202
Automated Prediction of Good Dictionary EXamples (GDEX): A Comprehensive Experiment with Distant Supervision, Machine Learning, and Word Embedding-Based Deep Learning Techniques
Full text linkDictionaries not only are the source of getting meanings of the word but also serve the purpose of comprehending the context in which the words are used. For such purpose, we see a small sentence as an example for the very word in comprehensive book-dictionaries and more recently in online dictionaries. The lexicographers perform a very meticulous activity for the elicitation of Good Dictionary EXamples (GDEX)—a sentence that is best fit in a dictionary for the word’s definition. The rules for the elicitation of GDEX are very strenuous and require a lot of time for committing the manual process. In this regard, this paper focuses on two major tasks, i.e., the development of labelled corpora for top 3K English words through the usage of distant supervision approach and devising a state-of-the-art artificial intelligence-based automated procedure for discriminating Good Dictionary EXamples from the bad ones. The proposed methodology involves a suite of five machine learning (ML) and five word embedding-based deep learning (DL) architectures. A thorough analysis of the results shows that GDEX elicitation can be done by both ML and DL models; however, DL-based models show a trivial improvement of 3.5% over the conventional ML models. We find that the random forests with parts-of-speech information and word2vec-based bidirectional LSTM are the most optimal ML and DL combinations for automated GDEX elicitation; on the test set, these models, respectively, secured a balanced accuracy of 73% and 77%
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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