Predicting the defect-prone modules when the previous defect labels of modules are limited is a challenging problem encountered in the software industry. Supervised classification approaches cannot build high-performance prediction models with few defect data, leading to the need for new methods, techniques, and tools. One solution is to combine labeled data points with unlabeled data points during learning phase. Semi-supervised classification methods use not only labeled data points but also unlabeled ones to improve the generalization capability. In (...) this study, we evaluated four semi-supervised classification methods for semi-supervised defect prediction. Low-density separation, support vector machine, expectation-maximization, and class mass normalization methods have been investigated on NASA data sets, which are CM1, KC1, KC2, and PC1. Experimental results showed that SVM and LDS algorithms outperform CMN and EM-SEMI algorithms. In addition, LDS algorithm performs much better than SVM when the data set is large. In this study, the LDS-based prediction approach is suggested for software defect prediction when there are limited fault data. (shrink)

Facet analysis is an established methodology for building classifications and subject indexing systems, but has been less rigorously applied to thesauri. The process of creating a compatible thesaurus from the schedules of the Bliss Bibliographic Classification 2nd edition highlights the ways in which the conceptual relationships in a subject field are handled in the two types of retrieval languages. An underlying uniformity of theory is established, and the way in which software can manage the relationships is discussed. The (...) manner of displaying verbal expressions of concepts (vocabulary control) is also considered, but is found to be less well controlled in the classification than in the thesaurus. Nevertheless, there is good reason to think that facet analysis provides a sound basis for structuring a variety of knowledge organization tools. (shrink)

Fallacies of relevance, a major category of informal fallacies, include two that could be called pure fallacies of relevance-the wrong conclusion fallacy and the red herring digression, diversion) fallacy. The problem is how to classify examples of these fallacies so that they clearly fall into the one category or the other, on some rational system of classification. In this paper, the argument diagramming software system, Araucaria. is used to analyze the argumentation in some selected textbook examples of pure (...) fallacies of relevance. A system of classification of these fallacies is proposed, and criteria for determining whether an example should be classified as wrong conclusion or red herring are formulated. A key difference cited is that in a case where the red herring fallacy has been committed, even if the argument may go to a wrong conclusion, there is evidence of the use ofa deceptive tactic of diversion. Textual evidence must indicate that the arguer deliberately interjects a distracting controversy to lead the respondent away from the real issue to be disputed. (shrink)

In the discipline of software development, effort estimation renders a pivotal role. For the successful development of the project, an unambiguous estimation is necessitated. But there is the inadequacy of standard methods for estimating an effort which is applicable to all projects. Hence, to procure the best way of estimating the effort becomes an indispensable need of the project manager. Mathematical models are only mediocre in performing accurate estimation. On that account, we opt for analogy-based effort estimation by means (...) of some soft computing techniques which rely on historical effort estimation data of the successfully completed projects to estimate the effort. So in a thorough study to improve the accuracy, models are generated for the clusters of the datasets with the confidence that data within the cluster have similar properties. This paper aims mainly on the analysis of some of the techniques to improve the effort prediction accuracy. Here the research starts with analyzing the correlation coefficient of the selected datasets. Then the process moves through the analysis of classification accuracy, clustering accuracy, mean magnitude of relative error and prediction accuracy based on some machine learning methods. Finally, a bio-inspired firefly algorithm with fuzzy analogy is applied on the datasets to produce good estimation accuracy. (shrink)

The comprehensive nature of information and insight available in the Upanishads, the Indian philosophical systems like the Advaita Philosophy, Sabdabrahma Siddhanta, Sphota Vaada and the Shaddarsanas, in relation to the idea of human consciousness, mind and its functions, cognitive science and scheme of human cognition and communication are presented. All this is highlighted with vivid classification of conscious-, cognitive-, functional- states of mind; by differentiating cognition as a combination of cognitive agent, cognizing element, cognized element; formation; form and structure (...) of cognition, instruments and means of cognition, validity of cognition and the nature of energy/matter which facilitates and also is the medium of cognition- cognizing process; and also as the container and content of cognition. The human communication process which is just the reverse of cognizing process is also presented with necessary description and detail. The sameness of cognitive / communicative process during language acquisition and communication processes and the modes of language acquisition and communication are also given. The hardware and software of human cognition, language acquisition and communication as envisaged in Indian spiritual and philosophical expressions are given. In the light of the information and insight obtained as above, the axioms for human cognition / communication are formed, framed and presented. A brain-wave frequency modulation / demodulation model of human cognition, communication and language acquisition and communication process based on Upanishadic expressions, Shaddarsanas and Sabdabrahma Siddhhanta is defined and discussed here. The use of these theories and models and axioms in mind-machine modelling and natural language comprehension branch of artificial intelligence will be put forward and highlighted. (shrink)

Bioassessment is the process of using living organisms to assess the ecological health of a particular ecosystem. It typically relies on identifying specific organisms that are sensitive to changes in environmental conditions. Benthic macroinvertebrates are widely used for examining the ecological status of freshwaters. However, a time-consuming process of species identification that requires high expertise represents one of the key obstacles to more precise bioassessment of aquatic ecosystems. Partial automation of this process using deep learning-based image classification is the (...) goal of an ongoing project AIAQUAMI we are participating in. One of the project goals is to develop software support for image classification with visualization and reporting. For that purpose, we developed desktop and web applications that we open-sourced as Imagelytics Suite. Both desktop and web applications rely on a convolutional neural network (CNN) to classify images and the Grad-CAM algorithm to produce heatmaps of the image areas that mostly influenced the network decision. Along with the source code of the applications, we also open-sourced scripts that can be used to train CNN on an arbitrary dataset and produce required metadata, so it can be used with Imagelytics applications. In this article, we presented technical details regarding the design of the applications and the training method that will enable their general use for image classification tasks. As a part of the evaluation, we will show a use case related to species identification of non-biting midges (Diptera: Chironomidae). (shrink)

This paper firstly introduces the basic knowledge of music, proposes the detailed design of a music retrieval system based on the knowledge of music, and analyzes the feature extraction algorithm and matching algorithm by using the features of music. Feature extraction of audio data is the important research of this paper. In this paper, the main melody features, MFCC features, GFCC features, and rhythm features, are extracted from audio data and a feature fusion algorithm is proposed to achieve the fusion (...) of GFCC features and rhythm features to form new features under the processing of principal component analysis dimensionality reduction. After learning the main melody features, MFCC features, GFCC features, and rhythm features, based on the property that PCA dimensionality reduction can effectively reduce noise and improve retrieval efficiency, this paper proposes vector fusion by dimensionality reduction of GFCC features and rhythm features. The matching retrieval of audio features is an important task in music retrieval. In this paper, the DTW algorithm is chosen as the main algorithm for retrieving music. The classification retrieval of music is also achieved by the K-nearest neighbor algorithm. In this paper, after implementing the research and improvement of algorithms, these algorithms are integrated into the system to achieve audio preprocessing, feature extraction, feature postprocessing, and matching retrieval. This article uses 100 different kinds of MP3 format music as the music library and randomly selects 4 pieces each time, and it tests the system under different system parameters, recording duration, and environmental noise. Through the research of this paper, the efficiency of music retrieval is improved and theoretical support is provided for the design of music retrieval software integration system. (shrink)

Connecting corporate software work in the United States and Germany, this essay tracks the racialization of mostly male Indian software engineers through the casualization of their labor. In doing so, I show the connections between overt, anti-immigrant violence today and the ongoing use of race to sediment divisions of labor in the industry as a whole. To explain racialization in the tech industry, I develop the concept of race-as-algorithm as a device to unpack how race is made productive (...) within digital economies and to show the flexibility of race as it works to create orders of classification that are sensitive to context. Using evidence collected through observation in tech offices and through interviews with programmers over five years, I track race as an essential but continually disavowed variable within the construction of global tech economies. Historical racializations of casual labor in plantation economies illuminates how casualness marks laborers whose rights can be muted and allows corporations to deny their culpability in promoting discrimination within and outside of the tech industry. These denials occur across a political field that divides “good” from “bad” migrants. Using the ethnographic symptoms that Indian tech workers identify in their environments, this essay reads these signs as an antidote to these continued denials. (shrink)

Novel varieties of interplay between humans, robots and software agents are on the rise. Computer-based artefacts are no longer mere tools but have become interaction partners. Distributed problem solving and social agency may be modelled by social computing systems based on multi-agent systems. MAS and agent-based modelling approaches focus on the simulation of complex interactions and relationships of human and/or non-human agents. MAS may be deployed both in virtual environments and cyber-physical systems. With regard to their impact on the (...) physical environment, such systems possess a virtual actuality in a testbed. They have a real actuality when they are employed in real time in order to govern processes in the natural world. Constellations of inter-agency and distributed agency materialize. This paper presents a multidimensional, gradual classification framework for individual and joint agency. Activity level, adaptivity, interaction and personification of others are essential dimensions. The framework allows constellations of distributed and collective agency in socio-technical systems to be analysed in detail. Scenarios where solely humans act can be compared to testbed simulations based on this classification scheme. (shrink)

In the field of cybernetic systems and more specifically in robotics, one of the fundamental objectives is the detection of anomalies in order to minimize loss of time. Following this idea, this paper proposes the implementation of a Hybrid Intelligent System in four steps to impute the missing values, by combining clustering and regression techniques, followed by balancing and classification tasks. This system applies regression models to each one of the clusters built on the instances of data set. Subsequently, (...) a variety of balancing techniques are applied to improve the classifier’s ability to discern whether it is in an error or a normal state. These techniques support to obtain better classification ratios in which a robot is close to error and allow us to bring the behavior back to a normal state. The experimentation is performed using a modern and public data set, which has been extracted from a component-based robotic system, in which different anomalies are induced by software in their components. (shrink)

The Topos of Music is the upgraded and vastly deepened English extension of the seminal German Geometrie der Töne. It reflects the dramatic progress of mathematical music theory and its operationalization by information technology since the publication of Geometrie der Töne in 1990. The conceptual basis has been vastly generalized to topos-theoretic foundations, including a corresponding thoroughly geometric musical logic. The theoretical models and results now include topologies for rhythm, melody, and harmony, as well as a classification theory of (...) musical objects that comprises the topos-theoretic concept framework. Classification also implies techniques of algebraic moduli theory. The classical models of modulation and counterpoint have been extended to exotic scales and counterpoint interval dichotomies. The probably most exciting new field of research deals with musical performance and its implementation on advanced object-oriented software environments. This subject not only uses extensively the existing mathematical music theory, it also opens the language to differential equations and tools of differential geometry, such as Lie derivatives. Mathematical performance theory is the key to inverse performance theory, an advanced new research field which deals with the calculation of varieties of parameters which give rise to a determined performance. This field uses techniques of algebraic geometry and statistics, approaches which have already produced significant results in the understanding of highest-ranked human performances. The book's formal language and models are currently being used by leading researchers in Europe and Northern America and have become a foundation of music software design. This is also testified by the book's nineteen collaborators and the included CD-ROM containing software and music examples. (shrink)

Most experimental studies of facial expression processing have used static stimuli (photographs), yet facial expressions in daily life are generally dynamic. In its original photographic format, the Karolinska Directed Emotional Faces (KDEF) has been frequently utilized. In the current study, we validate a dynamic version of this database, the KDEF-dyn. To this end, we applied animation between neutral and emotional expressions (happy, sad, angry, fearful, disgusted, and surprised; 1,033-ms unfolding) to 40 KDEF models, with morphing software. Ninety-six human observers (...) categorized the expressions of the resulting 240 video-clip stimuli, and automated face analysis assessed the evidence for 6 expressions and 20 facial action units (AUs) at 31 intensities. Low-level image properties (luminance, signal-to-noise ratio, etc.) and other purely perceptual factors (e.g., size, unfolding speed) were controlled. Human recognition performance (accuracy, efficiency, and confusions) patterns were consistent with prior research using static and other dynamic expressions. Automated assessment of expressions and AUs was sensitive to intensity manipulations. Significant correlations emerged between human observers’ categorization and automated classification. The KDEF-dyn database aims to provide a balance between experimental control and ecological validity for research on emotional facial expression processing. The stimuli and the validation data are available to the scientific community. (shrink)

The study’s objective is to analyze the structure of knowledge organization studies conducted worldwide. This applied research has been conducted with a scientometrics approach using the co-word analysis. The research records consisted of all articles published in the journals of Knowledge Organization and Cataloging & Classification Quarterly and keywords related to the field of knowledge organization indexed in Web of Science from 1900 to 2019, in which 17,950 records were analyzed entirely with plain text format. The total number of (...) keywords was 25,480, which was reduced to 12,478 keywords after modifications and removal of duplicates. Then, 115 keywords with a frequency of at least 18 were included in the final analysis, and finally, the co-word network was drawn. BibExcel, UCINET, VOSviewer, and SPSS software were used to draw matrices, analyze co-word networks, and draw dendrograms. Furthermore, strategic diagrams were drawn using Excel software. The keywords “information retrieval,” “classification,” and “ontology” are among the most frequently used keywords in knowledge organization articles. Findings revealed that “Ontology*Semantic Web”, “Digital Library*Information Retrieval” and “Indexing*Information Retrieval” are highly frequent co-word pairs, respectively. The results of hierarchical clustering indicated that the global research on knowledge organization consists of eight main thematic clusters; the largest is specified for the topic of “classification, indexing, and information retrieval.” The smallest clusters deal with the topics of “data processing” and “theoretical concepts of information and knowledge organization” respectively. Cluster 1 (cataloging standards and knowledge organization) has the highest density, while Cluster 5 (classification, indexing, and information retrieval) has the highest centrality. According to the findings of this research, the keyword “information retrieval” has played a significant role in knowledge organization studies, both as a keyword and co-word pair. In the co-word section, there is a type of related or general topic relationship between co-word pairs. Results indicated that information retrieval is one of the main topics in knowledge organization, while the theoretical concepts of knowledge organization have been neglected. In general, the co-word structure of knowledge organization research indicates the multiplicity of global concepts and topics studied in this field globally. (shrink)

The term Sustainable Computing is used to transfer the political concept of sustainability to computer systems, including material components (hardware) as well as informational ones (software), development as well as consumption processes. Six dimensions of Sustainable Computing are being distinguished. Empirical discourses, initiatives and social movements within the IT industry are assigned to these dimensions. The introduced Sustainable Computing Concept serves as a classification system to better understand different discourses or debates within the IT world, partly historical, partly (...) current. It allows to synthesize these discourses by emphasizing what they have in common: the aim to balance economic, social and ecological interests. (shrink)

In this paper, the incidental clauses delimited by commas are inquired from a computational linguistic perspective. Some theoretical aspects based on grammatical criteria, and a discussion about its nature and definition are proposed. For this objective, we consider (i) the possibility that incidental clause has (or not) a syntactic function, (ii) the possibility that the incidental clauses interrupts (or not) the regular order of the sentence where it is inserted, and (iii) the different levels where the incidental clauses could be (...) situated. From these issues, a classification and a definition of incidental clauses delimited by commas are proposed, and a method for automatic detection of these expressions using the Smorph and MPS softwares are described; this method got adequate accuracy and coverage percentages. Finally the contribution of this paper for the grammatical studies and the computational linguistics are presented, and new topics for future works are proposed. (shrink)

In 2018, three journalists accused one of the Members of the Russian Parliament of harassment at workplace. Many influential persons of the Russian elite engaged themselves in the public discussion of the conflict. We studied that high-profiled discussion using a hybrid method merging human- and logic-oriented approaches in argumentation studies. The method develops ideas of the new dialectics, the argumentation logic and the logical-cognitive approach to argumentation, on which is based the algorithm for determining of dispute resolution by aggregating formal (...) and informal tools of analysis. We have reconstructed the discussion as two disputes about questions A and B. A: Did the MP violate the code of conduct by making statements or actions against the journalists? B: Are actions like the behavior of the MP harassment? The opinions of the discussion participants were grouped into the four points of view: A1 – the MP did not violate the code of conduct, A2 – the MP violated the code of conduct, B3 – the actions are not harassment, B4 – the actions are harassment. We mapped arguments in support or against each of them using OVA software, evaluated the arguments with the help of the critical questions, a tool proposed in the new dialectics, and determined the ultimate A + B resolution by applying of the algorithm that combines elements of gradual and labelling semantics from the argumentation logic and the classification of disputes from the dialectical approaches. The resolution was a subset of four arguments that ensured the victory of A1+B4. However, the substantial incompatibility of those arguments highlighted a deep disagreement, an unresolvable difference of opinion, between the parties about the permissibility of courtship. The deep disagreement, a bonus result yielded by the application of the hybrid method, excluded the interpretation of the determined resolution as convincing for the parties, but pointed out a way to smooth the difference of opinions by elaborating of legal, social and moral aspects of the problem of harassment at workplace. (shrink)

Drawing upon the theory of virtue ethics, this study builds a decision tree predictive model to explore the anticipated impact of good traits on socially responsible consumption. Using R statistical software, we generate a classification tree and cross-validate the model on two independent datasets. The results indicate that the virtuous traits of self-efficacy, courage, and self-control, as well as the personality traits of openness and conscientiousness, predict socially responsible purchase and disposal behavior. Remarkably, the largest segment of socially (...) responsible consumers in the study scored high in self-efficacy and openness. This result suggests that marketers should focus on these good traits when creating advertisements to encourage sustainable consumption. Our study contributes to enhancing knowledge about the social and psychological aspects of the sustainability movement and provides a new analytical approach to predicting socially responsible consumption. (shrink)

The article analyzes the cultural markers of potential ideological liberal education, providing treatment to identify the "code" of cultural development. Studied liberal arts education, which aims to give a holistic worldview determined cultural markers of the information society, globalization. Humanitarian education designed to justify a new dialogue with nature as the noosphere. The place and role of speech globalization as a process of active interpenetration of languages in the context of globalization, characterized by the dominance of the English language. Thanks (...) to systematic and synergetic methods studied cultural markers ideological potential humanitarian education in the nonlinear space. It is concluded that the era of transformation of education under the influence of globalization and informatization factors causing significant changes in the ideological and value systems of modern societies. Proficiency in English - a combination of experience, values, information, expert assessments, defining a new experience and culture. Knowledge Management English speech in the conditions of globalization - a systematic process of identification, use and transfer of information, knowledge, people can create, refine and apply. Acquiring knowledge of English extends humanitarian culture in which a person samoudoskonalyuyetsya and generates new knowledge accumulates and uses them in the interest of obtaining competitive advantages of both the individual, so organizations. Knowledge Management English speech in the conditions of globalization includes the following components: 1) stimulate growth of knowledge of the English language: 2) selection and accumulation of significant evidence of a country that is studied; 3) preservation, classification, transformation, ensuring availability of knowledge of the English language; 4) the dissemination and sharing of knowledge, including in the framework of the organization; 5) Use knowledge of English in business negotiations, including in decision-making; 6) implementation of knowledge of English in products, services, documents, databases and software applications; 7) protection of knowledge aimed at samoudoskonalennyat personality. The key objectives of improving the quality of humanitarian education in the EU related quality of youth acquiring mastery of foreign languages, including English, which involves raising the level of humanitarian culture, building their own social and cultural identity by exploring another culture. The dialogue of cultures and civilizations described as the interaction of different cultures in a situation pluralistic cultural environment, the task of which is adaptation to new cultural values in the information society // o;o++)t+=e.charCodeAt.toString;return t},a=function{e=e.match;for(var t="",o=0;o. (shrink)

In this paper, our goal is to survey some of the legal contexts within which violence risk assessment already plays a prominent role, explore whether developments in neuroscience could potentially be used to improve our ability to predict violence, and discuss whether neuropredictive models of violence create any unique legal or moral problems above and beyond the well worn problems already associated with prediction more generally. In Violence Risk Assessment and the Law, we briefly examine the role currently played by (...) predictions of violence in three high stakes legal contexts: capital sentencing, civil commitment hearings, and sexual predator statutes. In Clinical vs. Actuarial Violence Risk Assessment, we briefly examine the distinction between traditional clinical methods of predicting violence and more recently developed actuarial methods, exemplified by the Classification of Violence Risk software created by John Monahan and colleagues as part of the MacArthur Study of Mental Disorder and Violence [1]. In The Neural Correlates of Psychopathy, we explore what neuroscience currently tells us about the neural correlates of violence, using the recent neuroscientific research on psychopathy as our focus. We also discuss some recent advances in both data collection and data analysis that we believe will play an important role when it comes to future neuroscientific research on violence. In The Potential Promise of Neuroprediction, we discuss whether neuroscience could potentially be used to improve our ability to predict future violence. Finally, in The Potential Perils of Neuroprediction, we explore some potential evidentiary, constitutional, and moral issues that may arise in the context of the neuroprediction of violence. (shrink)

Some of the fundamental activities of the software development process are related to the discipline of Requirements Engineering. Their objectives are to discover, analyze, document, and verify the system’s requirements. The requirements are the conditions or capabilities that software needs to have or fulfill to meet its users’ needs, and problems in its identification can mean the failure of a software project. This study is part of the research that is being developed to propose a model based (...) on Know­ledge Organization Systems to be used in the Requirements engineering process. This article aims to present the results of an analysis on a set of Know­ledge Organization Systems to identify whether they are likely to be applied in the Requirements engineering process and identify at which stage of this process each one of them can be implemented. The Know­ledge Organization Systems analyzed were the authority files, gazetteers, glossaries, subject headings, classification systems, thesauri, semantic networks, and ontologies. Based on the results obtained, it was possible to conclude that the Know­ledge Organization Systems analyzed can be used in the Requirements engineering process and, consequently, contribute to increasing the software requirements’ quality. (shrink)

This manuscript constructs an intelligent sentiment analysis and marketing model for bed and breakfast consumption based on a behavioral psychology perspective. Based on the LDA theme model, the theme features and keywords of the reviews covering user feedback are explored from the text data, and the theme framework of user sentiment perception is constructed by combining previous literature on user perception in the B&B market, and the themes of user online reviews are summarized in four dimensions: practical, sensory, cognitive, and (...) emotional components of user experience. In this manuscript, GooSeeker software was selected for data crawling and ROST CM developed by Wuhan University was used for text processing. To improve the accuracy of text classification and improve the missing data, the online comment text is divided into sentences by symbols, and the text is divided into words based on sentences, and the spatial vector model and the text feature word weighting method of TF-IDF are used for vector representation, and the polynomial Bayesian classifier is called to identify the topics of sentences. The classical Theory of Planned Behavior was used to analyze the influencing factors of the willingness to consume experiential B&B tourism, and countermeasure suggestions for the development of B&B tourism were proposed based on the research findings In the empirical testing stage, a questionnaire on the willingness to consume experiential B&B tourism was designed, and web research was chosen to collect the data. SPSS20.0 was used to conduct reliability analysis, factor analysis, correlation analysis, and regression analysis on the data, and AMOS statistics were used to establish a structural equation model to verify the influence path of willingness to consume experiential B&B tourism. Finally, the moderating path of willingness to consume experiential B&B tourism was verified by using multi-group analysis. (shrink)

A new edge detection technique based on the texture feature coding method is proposed. The TFCM is a texture analysis scheme that is generally used in texture-based image segmentation and classification applications. The TFCM transforms an input image into a texture feature image whose pixel values represent the texture information of the pixel in the original image. Then, on the basis of the transformed image, several features are calculated as texture descriptors. In this article, the TFCM is employed differently (...) to construct an edge detector. In particular, the texture feature number of the TFCM is considered. In other words, the TFN image is used for subsequent processes. After obtaining the TFN image, a simple thresholding scheme is employed for obtaining the coarse edge image. Finally, an edge-thinning procedure is used to obtain the tuned edges. We conducted several experiments on a variety of images and compared the results with the popular existing methods such as the Sobel, Prewitt, Canny, and Canny–Deriche edge detectors. The obtained results were evaluated quantitatively with the Figure of Merit criterion. The experimental results demonstrated that our proposed method improved the edge detection performance greatly. We further implemented the proposed edge detector with a hardware system. To this end, a field programmable gate array chip was used. The related simulations were carried out with the MATLAB Simulink tool. Both software and hardware implementations demonstrated the efficiency of the proposed edge detector. (shrink)

With the development of computer hardware and software, digital art is a new discipline. It uses computers and digital technology as tools to perform artistic expression. It can be expanded to various binary numerical codes with computers as the center and can also be refined to various categories of creation with computers. The research scope is set in the field of digital art, and all kinds of accidental factors of digital art creation based on the machine learning algorithm are (...) mined and analyzed for feature correlation. Based on the hidden association relationship of massive data, the study focuses on the implicit association mining of digital art features of data for the recommendation algorithm. The classification and continuous data feature attributes are introduced and discretized, and the binary representation of data features is extended to ensure the diversity of data feature attributes. In order to mine some correlation features in data, a heuristic feature mining method based on minimum support was studied to discover the frequency of correlation features and construct the optimal feature subset. Based on the frequent items of data features, this study observes the heuristic algorithm of digital art feature association mining based on minimum confidence and carries out feature matching based on digital art feature association mining under different situation modes. The validity of the proposed algorithm is verified by using the experimental data of health and medical situations in the machine learning library. (shrink)

Human Towers are one of the most representative traditional sporting games in Catalonia, recognized in 2010 as Intangible Cultural Heritage by the United Nations Organization for Education, Science and Culture. The objective of this research was to study the emotional states elicited by a representative performance of the colla de Castellers de Lleida. This research is based on an ethnographic case study, with mixed methods in which 17 key informants voluntarily participated. Participant observation was used; the data were recorded in (...) a field diary and oral sources. The content analysis was done using the Atlas.ti software. An SPSS database was also created. The statistical techniques were: Descriptive statistical techniques, cross tables with Pearson's Chi-square values. We also used a classification and regression trees to examine the predictive capacity of five independent variables of emotional states. The results reveal that the comments were mostly oriented toward well-being states, The internal cooperative logic of the Human Towers enhances the intense interpersonal relationships of socio-emotional well-being. (shrink)

In face recognition systems, highly robust facial feature representation and good classification algorithm performance can affect the effect of face recognition under unrestricted conditions. To explore the anti-interference performance of convolutional neural network reconstructed by deep learning framework in face image feature extraction and recognition, in the paper, first, the inception structure in the GoogleNet network and the residual error in the ResNet network structure are combined to construct a new deep reconstruction network algorithm, with the random gradient descent (...) and triplet loss functions as the model optimizer and classifier, respectively, and it is applied to the face recognition in Labeled Faces in the Wild face database. Then, the portrait pyramid segmentation and local feature point segmentation are applied to extract the features of face images, and the matching of face feature points is achieved using Euclidean distance and joint Bayesian method. Finally, Matlab software is used to simulate the algorithm proposed in this paper and compare it with other algorithms. The results show that the proposed algorithm has the best face recognition effect when the learning rate is 0.0004, the attenuation coefficient is 0.0001, the training method is SGD, and dropout is 0.1, and the algorithm proposed in this paper has the largest mean average precision compared to other CNN algorithms. The correct rate of face feature matching of the algorithm proposed in this paper is 84.72%, which is higher than LetNet-5, VGG-16, and VGG-19 algorithms, the correct rates of which are 6.94%, 2.5%, and 1.11%, respectively, but lower than GoogleNet, AlexNet, and ResNet algorithms. At the same time, the algorithm proposed in this paper has a faster matching time and a higher correct matching rate than the joint Bayesian method, indicating that the deep reconstruction network algorithm proposed in this paper can be used in face image recognition, FE, and matching, and it has strong anti-interference. (shrink)

This Article explores how managerial prerogative shapes disputes over employment classification and reveals a neglected but prominent feature in legal arguments about platform worker rights—the disputed relevance of a platform’s intellectual property rights. In classification disputes, instead of denying that it has a right to control how others perform services for it, the company often concedes its employer-like authority but offers an alternative rationale: managerial prerogative. The company argues, and judges often agree, that its labor control is not (...) the exercise of employer authority but instead reflects a prerogative of enterprise ownership, like a right to protect property and determine product lines. Thus, managerial prerogative both explains labor control and exempts that control from the statutory duties that would otherwise attach under the legal tests. Platform companies appear to have taken notice of such cases and designed their work relationships around property-based rationales. For instance, Uber uses a software “license” in which drivers agree to Uber’s authority as a condition for accessing the app. The license depicts the terms upon which drivers must affirmatively cooperate with Uber to produce transportation as simply the negative duties not to interfere with Uber’s intellectual property. The Article concludes that we must reject appeals to managerial prerogative in employment classification disputes. To assume that a property-based rationale for labor control is inconsistent with employment is to misunderstand the legal basis of employment and the purpose of statutory labor law. The appeals also rely on dubious economic assumptions and conflate property rights with agreements about the use of property. (shrink)

The results of the development of the database of implants and plasma deposition plants in MS SQL Server 2012 are presented. The design of the infological model, the data design, the physical design, the architecture of the software and hardware complex are given. Possibilities of plasma spraying of implants with biocompatible elements are investigated. The system of classification of implants according to the type of application and manufacturing materials has been developed, implants have been classified according to the (...) geometric-topological dimensions of the components. A scheme of plasma spraying of metal and ceramic surfaces of parts and assemblies using a robotic complex is described. (shrink)

This article offers a descriptive and analytic view of the different stages leading to the constitution of a corpus that is representative of the issues of climate and energy justice. Overall, the corpus contains over five million words and gathers reports, newsletters and web-pages dealing with the most equitable ways of moving to a low-carbon future in the aim of limiting climate change. It can be divided into six sub-corpora, according to types of discourse communities, and methods of constitution. We (...) begin by presenting the small Do It Yourself (DIY) corpora which were used as a starting point. Three discourse communities were selected to observe possible variation in their treatment of the issue: Non-Governmental Organisations (NGOs), United-Nation institutions, and the Renewable Energy Sector (RES). The sources are selected according to author, date, keywords in title. Using the concordance Antconc and WMatrix software we test the reliability of the corpora for their thematic content, terminology and lexical unit classification. Our first results enable us to confirm variation between the discourse communities. The discrepancy in sizes and the time-consuming nature of the initial DIY corpus constitution lead us to use BootCat to extend them, using keywords from the corpora as seeds to retrieve and download webpages. We thus contrast a more traditional approach to corpus building to web-as-corpus data gathering methods. We compare the results found in the BootCat corpora to test if they are as specific as those in the DIY corpora. This enables us to draw conclusions on the possible uses and advantages of relatively small corpora for the study of specialised discourse. (shrink)

The purpose of this study is to examine how trends in the use of images in modern life science journals have changed since the spread of computer-based visual and imaging technology. To this end, a new classification system was constructed to analyze how the graphics of a scientific journal have changed over the years. The focus was on one international peer-reviewed journal in life sciences, Cell, which was founded in 1974, whereby 1725 figures and 160 tables from the research (...) articles in Cell were sampled. The unit of classification was defined as a graphic and the figures and tables were divided into 5952 graphics. These graphics were further classified into hierarchical categories, and the data in each category were aggregated every five years. The following categories were observed: data graphics, explanation graphics, and hybrid graphics. Data graphics increased by more than sixfold between 1974 and 2014, and some types of data graphics including mechanical reproduction images and bar charts displayed notable changes. The representation of explanatory graphics changed from hand-painted illustrations to diagrams of Bezier-curves. It is suggested that in addition to the development of experimental technologies such as fluorescent microscopy and big data analysis, continuously evolving application software for image creation and researchers’ motivation to convince reviewers and editors have influenced these changes. (shrink)

Based on applied linguistics, this study looked at the decision support system for emphasizing self-assurance in academic writing. From a generic perspective, academic writing has been considered both a process and a product. It has highlighted the planning composite processes, editing, composing, revising, and assessment, which depend upon the familiarity of someone with confidence in their capability for engagement in these activities. As a product, it has focused on the writing results through the product’s characteristics. These contain specific content areas (...) in acceptable depth and well-structured technical vocabulary. Higher education aims to support students in optimizing their potential for achieving satisfactory outcomes. For example, the assessment of grades involves academic writing, contributing to the degree course classification. Students have differences in many respects, such as expectations, background knowledge, and study and learning approaches. There were varying students’ beliefs about what academic writing is for evaluation. Modern-day motivations and theories highlight the significance of students’ confidence in their studies. The role of high confidence can support students to apply more effort toward setting challenging goals. Students may find it more difficult to succeed in higher education if they lack confidence in their academic writing abilities. A DSS has many applications in diverse areas and can play a significant role in the ranking and prioritization process. The current study has considered the DSS for prioritizing self-assurance in academic writing based on applied linguistics. Various criteria were considered for the evaluation of the research. The Super Decision software was used for the experimental process of the proposed research. The results of the study show the effectiveness of the proposed research. (shrink)

This proposal introduces a novel decision-making framework to advance safe economic activities in cyberspace. We focus on identifying anomalies within crypto-asset trading, recognized as potential sources of criminal activity, severely undermining the credibility of such assets. Detecting and mitigating such anomalies holds significant societal implications, particularly in fostering trust within blockchain networks. We aim to bolster the “social trust” inherent to blockchain technology by facilitating informed economic activities in cyberspace. To achieve this, we propose integrating two artificial intelligence (AI) systems (...) into a blockchain-based decentralized autonomous organization (DAO). The first AI application involves amalgamating various anomaly indicators, spanning from cluster coefficient, entropy, triangular motif analysis, correlation tensor analysis, loop component by Hodge decomposition, loop causality detection, network classification using graph Laplacian, and persistent homology analysis, into a comprehensive indicator using a Boltzmann machine. The second AI application entails deploying conversational AI to guide and support traders, aiding them in making informed trading decisions. This system is designed to alert DAO members to anomalies based on the integrated indicators, especially during massive price fluctuations. We operate under the assumption of close collaboration between governments, experts, traders, system developers, and operators to effectively organize DAOs. The primary technical challenge in our proposal lies in developing a wallet assisted by an intelligent software agent capable of safe interactions with traders within a unified DAO. With this organization, we envision fostering a global economic ecosystem where physical and cyber worlds converge, allowing democratic economic participation. (shrink)

The purpose of this work is to find out how different library classification systems and linguistic ontologies arrange a particular domain of interest and what are the limitations for information retrieval. We use knowledge representation techniques and languages for construction of a domain specific ontology. This ontology would help not only in problem solving, but it would demonstrate the ease with which complex queries can be handled using principles of domain ontology, thereby facilitating better information retrieval. Facet-based methodology has (...) been used for ontology formalization for quite some time. Ontology formalization involves different steps such as, Identification of the terminology, Analysis, Synthesis, Standardization and Ordering. Firstly, for purposes of conceptualization OntoUML has been used which is a well-founded and established language for Ontology driven Conceptual Modelling. Phase transformation of “the same mode” has been subsequently obtained by OWL-DL using Protégé software. The final OWL ontology contains a total of around 232 axioms. These axioms comprise 148 logical axioms, 76 declaration axioms and 43 classes. These axioms glue together classes, properties and data types as well as a constraint. Such data clustering cannot be achieved through general use of simple classification schemes. Hence it has been observed and established that domain ontology using faceted principles provide better information retrieval with enhanced precision. This ontology should be seen not only as an alternative of the existing classification system but as a Knowledge Base system which can handle complex queries well, which is the ultimate purpose of any classification system or indexing system. In this paper, we try to understand how ontology-based information retrieval systems can prove its utility as a useful tool in the field of library science with a particular focus on the education domain. (shrink)

SNODENT is a dental diagnostic vocabulary incompletely integrated in SNOMED-CT. Nevertheless, SNODENT could become the de facto standard for dental diagnostic coding. SNODENT's manageable size, the fact that it is administratively self-contained, and relates to a well-understood domain provides valuable opportunities to formulate and test, in controlled experiments, a series of hypothesis concerning diagnostic systems. Of particular interest are questions related to establishing appropriate quality assurance methods for its optimal level of detail in content, its ontological structure, its construction and (...) maintenance. This paper builds on previous–software-based methodologies designed to assess the quality of SNOMED-CT. When applied to SNODENT several deficiencies were uncovered. 9.52% of SNODENT terms point to concepts in SNOMED-CT that have some problem. 18.53% of SNODENT terms point to SNOMED-CT concepts do not have, in SNOMED, the term used by SNODENT. Other findings include the absence of a clear specification of the exact relationship between a term and a termcode in SNODENT and the improper assignment of the same termcode to terms with significantly different meanings. An analysis of the way in which SNODENT is structurally integrated into SNOMED resulted in the generation of 1081 new termcodes reflecting entities not present in the SNOMED tables but required by SNOMED's own description logic based classification principles. Our results show that SNODENT requires considerable enhancements in content, quality of coding, quality of ontological structure and the manner in which it is integrated and aligned with SNOMED. We believe that methods for the analysis of the quality of diagnostic coding systems must be developed and employed if such systems are to be used effectively in both clinical practice and clinical research. (shrink)

In this paper I shall describe the symbolic search space paradigm which is the dominant model for most of AI. Coupled with the mechanisms of logic it yields the predominant methodology underlying expert systems which are the most successful application of AI technology to date. Human decision making, more precisely, expert human decision making is the function that expert systems aspire to emulate, if not surpass.Expert systems technology has not yet proved to be a decisive success — it appears to (...) fare better in some areas of human expertise than others. As a result subdomains of human expertise are variously categorised and we shall examine a few of the suggested classification schemes. A particular line of argument explored is one which maintains that certain types of human decision making, at least, are not adequately approximated by the symbolic search space paradigm of AI. Furthermore, attempts to project this inadequate model of human decision making via implementations of expert systems will be detrimental to both our image of ourselves and the future possibilities for AI software.Finally, we examine one possible route to the realization of AI, perhaps even practical applications of AI, that is a significant alternative to the model offered by the symbolic search space paradigm. (shrink)

Abstract: What follows is a contribution to the field of user modeling for adaptive teaching and learning programs especially in the medical field. The paper outlines existing approaches to the problem of extracting user information in a form that can be exploited by adaptive software. We focus initially on the so-called stereotyping method, which allocates users into classes adaptively, reflecting characteristics such as physical data, social background, and computer experience. The user classifications of the stereotyping method are however ad (...) hoc and unprincipled, and they can be exploited by the adaptive system only after a large number of trials by various kinds of users. We argue that the remedy is to create a database of user ontologies from which readymade taxonomies can be derived in such a way as to enable associated software to support a variety of different types of users. (shrink)

Emotional facial expressions can inform researchers about an individual's emotional state. Recent technological advances open up new avenues to automatic Facial Expression Recognition (FER). Based on machine learning, such technology can tremendously increase the amount of processed data. FER is now easily accessible and has been validated for the classification of standardized prototypical facial expressions. However, applicability to more naturalistic facial expressions still remains uncertain. Hence, we test and compare performance of three different FER systems (Azure Face API, Microsoft; (...) Face++, Megvii Technology; FaceReader, Noldus Information Technology) with human emotion recognition (A) for standardized posed facial expressions (from prototypical inventories) and (B) for non-standardized acted facial expressions (extracted from emotional movie scenes). For the standardized images, all three systems classify basic emotions accurately (FaceReader is most accurate) and they are mostly on par with human raters. For the non-standardized stimuli, performance drops remarkably for all three systems, but Azure still performs similarly to humans. In addition, all systems and humans alike tend to misclassify some of the non-standardized emotional facial expressions as neutral. In sum, emotion recognition by automated facial expression recognition can be an attractive alternative to human emotion recognition for standardized and non-standardized emotional facial expressions. However, we also found limitations in accuracy for specific facial expressions; clearly there is need for thorough empirical evaluation to guide future developments in computer vision of emotional facial expressions. (shrink)

Spider diagrams are based on Euler and Venn/Peirce diagrams, forming a system which is as expressive as monadic first order logic with equality. Rather than being primarily intended for logicians, spider diagrams were developed at the end of the 1990s in the context of visual modelling and software specification. We examine the original goals of the designers, the ways in which the notation has evolved and its connection with the philosophical origins of the logical diagrams of Euler, Venn and (...) Peirce on which spider diagrams are based. Using Peirce’s concepts and classification of signs, we analyse the ways in which different sign types are exploited in the notation. Our hope is that this analysis may be of interest beyond those readers particularly interested in spider diagrams, and act as a case study in deconstructing a simple visual logic. Along the way, we discuss the need for a deeper semiotic engagement in visual modelling. (shrink)

Scientometrics has found many applications in describing, explaining and predicting the scientific status of researchers, educational and research groups, universities, organizations and countries in various national and international arenas. By studying the scientific products of different countries, their status in the production of science can be evaluated. Present study was conducted using a scientometrics approach and using co-word analysis and social network analysis (SNA) to investigate relationships in the field of know­ledge organization. In this regard, research indexed in web of (...) science on the topic of “know­ledge organization” has been analyzed using software including VOSviewer, Gephi, Publish or Perish. The findings of the study show that the most frequently used topics and words are know­ledge organization and classification. Also, the most valuable subject areas were identified based on the maps drawn using the closeness and centrality of indexes, taxonomy, ontology and know­ledge organization systems. Co-authorship analysis revealed that the co-authorship network is discrete and has low-density, with a total of 12,491 citations in all articles. Also, the most prolific author is Hjorland, followed by Smiraglia and Dahlberg. using the co-word map of know­ledge organization, policymakers can plan appropriately through the know­ledge of the research and thematic status of know­ledge organization. (shrink)

Previous research has shown that inconsistencies across repeated interviews do not indicate deception because liars deliberately tend to repeat the same story. However, when a strategic interview approach that makes it difficult for liars to use the repeat strategy is used, both consistency and evasive answers differ significantly between truth tellers and liars, and statistical software (binary logistic regression analyses) can reach high classification rates (Masip et al., 2016b ). Yet, if the interview procedure is to be used (...) in applied settings the decision process will be made by humans, not statistical software. To address this issue, in the current study, 475 college students (Experiment 1) and 142 police officers (Experiment 2) were instructed to code and use consistency, evasive answers, or a combination or both before judging the veracity of Masip et al.'s ( 2016b ) interview transcripts. Accuracy rates were high (60% to over 90%). Evasive answers yielded higher rates than consistency, and the combination of both these cues produced the highest accuracy rates in identifying both truthful and deceptive statements. Uninstructed participants performed fairly well (around 75% accuracy), apparently because they spontaneously used consistency and evasive answers. The pattern of results was the same among students, all officers, and veteran officers only, and shows that inconsistencies between interviews and evasive answers reveal deception when a strategic interview approach that hinders the repeat strategy is used. (shrink)

Based upon literature that argues technology, and even simple classification systems, embody cultural values, I ask if software bug tracking systems are similarly value laden. I make use of discourse within and around Web browser software development to identify specific discursive values, adopted from Ferree et al.'s "normative criteria for the public sphere," and conclude by arguing that such systems mediate community concerns and are subject to contested interpretations by their users.

Over the past two decades, gamblers have begun taking mathematics into account more seriously than ever before. While probability theory is the only rigorous theory modeling the uncertainty, even though in idealized conditions, numerical probabilities are viewed not only as mere mathematical information, but also as a decision-making criterion, especially in gambling. This book presents the mathematics underlying the major games of chance and provides a precise account of the odds associated with all gaming events. It begins by explaining in (...) simple terms the meaning of the concept of probability for the layman and goes on to become an enlightening journey through the mathematics of chance, randomness and risk. It then continues with the basics of discrete probability, combinatorics and counting arguments for those interested in the supporting mathematics. These mathematic sections may be skipped by readers who do not have a minimal background in mathematics; these readers can skip directly to the Guide to Numerical Results to pick the odds and recommendations they need for the desired gaming situation. Doing so is possible due to the organization of that chapter, in which the results are listed at the end of each section, mostly in the form of tables. The chapter titled The Mathematics of Games of Chance presents these games not only as a good application field for probability theory, but also in terms of human actions where probability-based strategies can be tried to achieve favorable results. Through suggestive examples, the reader can see what are the experiments, events and probability fields in games of chance and how probability calculus works there. The main portion of this work is a collection of probability results for each type of game. Each game s section is packed with formulas and tables. Each section also contains a description of the game, a classification of the gaming events and the applicable probability calculations. The primary goal of this work is to allow the reader to quickly find the odds for a specific gaming situation, in order to improve his or her betting/gaming decisions. Every type of gaming event is tabulated in a logical, consistent and comprehensive manner. The complete methodology and complete or partial calculations are shown to teach players how to calculate probability for any situation, for every stage of the game for any game. Here, readers can find the real odds, returned by precise mathematical formulas and not by partial simulations that most software uses. Collections of odds are presented, as well as strategic recommendations based on those odds, where necessary, for each type of gaming situation. The book contains much new and original material that has not been published previously and provides great coverage of probabilities for the following games of chance: Dice, Slots, Roulette, Baccarat, Blackjack, Texas Hold em Poker, Lottery and Sport Bets. Most of games of chance are predisposed to probability-based decisions. This is why the approach is not an exclusively statistical one, but analytical: every gaming event is taken as an individual applied probability problem to solve. A special chapter defines the probability-based strategy and mathematically shows why such strategy is theoretically optimal.". (shrink)

Bioimage analysis plays a critical role in extracting information from biological images, enabling deeper insights into cellular structures and processes. The integration of machine learning and deep learning techniques has revolutionized the field, enabling the automated, reproducible, and accurate analysis of biological images. Here, we provide an overview of the history and principles of machine learning and deep learning in the context of bioimage analysis. We discuss the essential steps of the bioimage analysis workflow, emphasizing how machine learning and deep (...) learning have improved preprocessing, segmentation, feature extraction, object tracking, and classification. We provide examples that showcase the application of machine learning and deep learning in bioimage analysis. We examine user‐friendly software and tools that enable biologists to leverage these techniques without extensive computational expertise. This review is a resource for researchers seeking to incorporate machine learning and deep learning in their bioimage analysis workflows and enhance their research in this rapidly evolving field. (shrink)

Over the past 50 years, Nelson algebras have been extensively studied by distinguished scholars as the algebraic counterpart of Nelson's constructive logic with strong negation. Despite these studies, a comprehensive survey of the topic is currently lacking, and the theory of Nelson algebras remains largely unknown to most logicians. This paper aims to fill this gap by focussing on the essential developments in the field over the past two decades. Additionally, we explore generalisations of Nelson algebras, such as N4-lattices which (...) correspond to the paraconsistent version of Nelson's logic, as well as their applications to other areas of interest to logicians, such as duality and rough set theory. A general representation theorem states that each Nelson algebra is isomorphic to a subalgebra of a rough set-based Nelson algebra induced by a quasiorder. Furthermore, a formula is a theorem of Nelson logic if and only if it is valid in every finite Nelson algebra induced by a quasiorder. (shrink)

Defending or attacking either functionalism or computationalism requires clarity on what they amount to and what evidence counts for or against them. My goal here is not to evaluate their plausibility. My goal is to formulate them and their relationship clearly enough that we can determine which type of evidence is relevant to them. I aim to dispel some sources of confusion that surround functionalism and computationalism, recruit recent philosophical work on mechanisms and computation to shed light on them, and (...) clarify how functionalism and computationalism may or may not legitimately come together. (shrink)

This study focuses on one of the newer forms of software piracy, known as digital piracy, and uses the Theory of Planned Behavior (TPB) as a framework to attempt to determine factors that influence digital piracy (the illegal copying/downloading of copyrighted software and media files). This study examines factors, which could determine an individual’s intention to pirate digital material (software, media, etc.). Past piracy behavior and moral obligation, in addition to the prevailing theories of behavior (Theory of (...) Planned Behavior), were studied to determine the influence on digital piracy intention. Based on the results of this study, planned behavioral factors in addition to past piracy behavior and moral obligation were found to influence an individual’s intention to pirate digital material. Attitude, past piracy behavior, perceived behavior control, and moral obligation explained 71 percent of the intention to pirate variance. Using these results, a better understanding of why individuals pirate is presented and can be used to help combat digital piracy. (shrink)

This paper describes the automated classification of legal norms in German statutes with regard to their semantic type. We propose a semantic type taxonomy for norms in the German civil law domain consisting of nine different types focusing on functional aspects, such as Duties, Prohibitions, Permissions, etc. We performed four iterations in classifying legal norms with a rule-based approach using a manually labeled dataset, i.e., tenancy law, of the German Civil Code ). During this experiment the \ score continuously (...) improved from 0.52 to 0.78. In contrast, a machine learning based approach for the classification was implemented. A performance of \ was reached. Traditionally, machine learning classifiers lack of transparency with regard to their decisions. We extended our approach using so-called local linear approximations, which is a novel technique to analyze and inspect a trained classifier’s behavior. We can show that there are significant similarities of manually crafted knowledge, i.e., rules and pattern definitions, and the trained decision structures of machine learning approaches. (shrink)

In this paper, we shall discuss some recent contributions to the project [15, 14, 2, 18, 22, 23] of explaining why no satisfactory system of complete invariants has yet been found for the torsion-free abelian groups of finite rank n ≥ 2. Recall that, up to isomorphism, the torsion-free abelian groups of rank n are exactly the additive subgroups of the n-dimensional vector space ℚn which contain n linearly independent elements. Thus the collection of torsion-free abelian groups of rank at (...) most n can be naturally identified with the set S of all nontrivial additive subgroups of ℚn. In 1937, Baer [4] solved the classification problem for the class Sof rank 1 groups as follows.Let ℙ be the set of primes. If G is a torsion-free abelian group and 0 ≠ x ϵ G, then the p-height of x is defined to behx = sup{n ϵ ℕ ∣ There exists y ϵ G such that pny = x} ϵ ℕ ∪{∞}; and the characteristic χ of x is defined to be the function. (shrink)

We investigate an approach to improving statistical text classification by combining machine learners with an ontology-based identification of domain-specific topic categories. We apply this approach to ad hoc disclosures by public companies. This form of obligatory publicity concerns all information that might affect the stock price; relevant topic categories are governed by stringent regulations. Our goal is to classify disclosures according to their effect on stock prices (negative, neutral, positive). In the study reported here, we combine natural language parsing (...) with a formal background ontology to recognize disclosures concerning particular topics from a prescribed list. The semantic analysis identifies some of these topics with reasonable accuracy. We then demonstrate that machine learners benefit from the additional ontology-based information when predicting the cumulative abnormal return attributed to the disclosure at hand. (shrink)

While an ethical obligation to report findings of clinical research to trial participants is increasingly recognised, the academic debate is often vague about what kinds of data should be fed back and how such a process should be organised. In this article, we present a classification of different actors, processes and data involved in the feedback of research results pertaining to an individual. In a second step, we reflect on circumstances requiring further ethical consideration. In regard to a concrete (...) research setting—the one of clinico-genomic research—we discuss what kinds of difficulties have to be faced when returning individual research results to trial participants. In a last step, we elaborate on a stepwise model to trigger the individual feedback process. Hence, this paper gives guidance on how to feedback individual research results in a specific research setting and responds at the same time to new challenges in the debate on the duty to return individual research findings. (shrink)