The purpose of this study is to propose and develop an intelligent e-learning system based on advanced document management techniques at Al-Quds Open University. In this article, we focus on a case using e-mail contents as supplement educational materials at QOU. We describe how the interactive classification system based on concept hierarchy can simplify this task. This system provides the functions to index, classify, and retrieve a collection of e-mail messages based on user profiles. By automatically indexing e-mail messages (...) using our E-mail Classification System for e-Learning, instructors and/or students can easily find their messages and find the topics. The test results of our system evaluation showed that a good classification quality has been achieved, with a precision of 77.4%, recall of 90%, and F-measure of 82.8. (shrink)

I examine the construction and evaluation of machine learning binary classification models. These models are increasingly used for societal applications such as classifying patients into two categories according to the presence or absence of a certain disease like cancer and heart disease. I argue that the construction of ML classification models involves an optimisation process aiming at the minimization of the inductive risk associated with the intended uses of these models. I also argue that the construction of these (...) models is underdetermined by the available data, and that this makes it necessary for ML modellers to make social value judgments in determining the error costs used in ML optimization. I thus suggest that the assessment of the inductive risk with respect to the social values of the intended users is an integral part of the construction and evaluation of ML classification models. I also discuss the implications of this conclusion for the philosophical debate concerning inductive risk. (shrink)

“God created, Linnaeus organized.” This remark Linnaeus liked to say captures the common idea that the proper task of scientists in classification is to discover and systematize features of the world without being committed to individual perspectives, values, and interests. However, it is rarely the case that scientists passively read nature or carve nature at its joints. My thesis investigates how scientific classification is laden with values and explores its implication. I hope to temper the influence of the (...) ideal of value-free science on the discussion of natural kinds. Contrary to the blossoming scholarship in the values and science literature, there has been little discussion about the role of values in scientific classification. Defined as groupings that correspond to real divisions in nature, natural kinds are considered to exist independently from human values and interests. I demonstrate how the assumptions behind scientific classification endorse the idea of value-free science. Using case studies, I argue that incorporating social, moral, and political values can lead to the epistemic improvement of the category. If values are ineliminable from science, then the question arises, what or whose values, in what ways, can legitimately influence science? I critically examine recently developed criteria for proper uses of values in science. I advocate evaluating values in terms of epistemic benefits. The task of assessing epistemic benefits requires scrutinizing a research program’s social and historical context. Finally, the last part of this dissertation explores how values uniquely influence natural kind terms via social entrenchment. Many philosophers identify projectibility as a defining feature of natural kinds. I look at whether social and cultural practices influence projectibility. I investigate whether these practices affect which kind terms get socially entrenched. I argue that the projectibility of natural kind terms substantially depends on our norms and values. (shrink)

In the past decades, computers have become more and more involved in society by the rise of ubiquitous systems, increasing the number of interactions between humans and IT systems. At the same time, the technology itself is getting more complex, enabling devices to act in a way that previously only humans could, based on developments in the fields of both robotics and artificial intelligence. This results in a situation in which many autonomous, intelligent and context-aware systems are involved in decisions (...) that affect their environment. These relations between people, machines, and decisions can take many different forms, but thus far, a systematic account of machine-assisted moral decisions is lacking. This paper investigates the concept of machine-assisted moral decisions from the perspective of technological mediation. It is argued that modern machines do not only have morality in the sense of mediating the actions of humans, but that, by making their own decisions within their relations with humans, mediate morality itself. A classification is proposed to differentiate between four different types of moral relations. The moral aspects within the decisions these systems make are combined into three dimensions that describe the distinct characteristics of different types of moral mediation by machines. Based on this classification, specific guidelines for moral behavior can be provided for these systems. (shrink)

Effective and specifically targeted social and therapeutic responses for antisocial personality disorders and psychopathy are scarce. Some authors maintain that this scarcity should be overcome by revising current syndrome - based classifications of these conditions and devising better biocognitive classifications of antisocial individuals. The inspiration for the latter classifications has been embedded in the Research domain criteria approach (RDoC). RDoC - type approaches to psychiatric research aim at transforming diagnosis, provide valid measures of disorders, aid clinical practice, and improve health (...) outcomes by integrating the data on the genetic, neural, cognitive, and affective systems underlying psychiatric conditions. In the first part of the paper, we discuss the benefits of such approaches in comparison to the dominant syndrome-based ones and review recent attempts at building biocognitive classifications of antisocial individuals. Other researchers, how ever, have objected that biocognitive approaches in psychiatry are committed to an untenable form of explanatory. (shrink)

We extend the hierarchy of finite-dimensional Ellentuck spaces to infinite dimensions. Using uniform barriers [Formula: see text] on [Formula: see text] as the prototype structures, we construct a class of continuum many topological Ramsey spaces [Formula: see text] which are Ellentuck-like in nature, and form a linearly ordered hierarchy under projections. We prove new Ramsey-classification theorems for equivalence relations on fronts, and hence also on barriers, on the spaces [Formula: see text], extending the Pudlák–Rödl theorem for barriers on the (...) Ellentuck space. The inspiration for these spaces comes from continuing the iterative construction of the forcings [Formula: see text] to the countable transfinite. The [Formula: see text]-closed partial order [Formula: see text] is forcing equivalent to [Formula: see text], which forces a non-p-point ultrafilter [Formula: see text]. This work forms the basis for further work classifying the Rudin–Keisler and Tukey structures for the hierarchy of the generic ultrafilters [Formula: see text]. (shrink)

A general method for constructing a new class of topological Ramsey spaces is presented. Members of such spaces are infinite sequences of products of Fraïssé classes of finite relational structures satisfying the Ramsey property. The Product Ramsey Theorem of Sokič is extended to equivalence relations for finite products of structures from Fraïssé classes of finite relational structures satisfying the Ramsey property and the Order-Prescribed Free Amalgamation Property. This is essential to proving Ramsey-classification theorems for equivalence relations on fronts, generalizing (...) the Pudlák–Rödl Theorem to this class of topological Ramsey spaces. To each topological Ramsey space in this framework corresponds an associated ultrafilter satisfying some weak partition property. By using the correct Fraïssé classes, we construct topological Ramsey spaces which are dense in the partial orders of Baumgartner and Taylor generating p-points which are k-arrow but not \-arrow, and in a partial order of Blass producing a diamond shape in the Rudin-Keisler structure of p-points. Any space in our framework in which blocks are products of n many structures produces ultrafilters with initial Tukey structure exactly the Boolean algebra \\). If the number of Fraïssé classes on each block grows without bound, then the Tukey types of the p-points below the space’s associated ultrafilter have the structure exactly \. In contrast, the set of isomorphism types of any product of finitely many Fraïssé classes of finite relational structures satisfying the Ramsey property and the OPFAP, partially ordered by embedding, is realized as the initial Rudin-Keisler structure of some p-point generated by a space constructed from our template. (shrink)

Along with the Chan’s “linguistic turn”, the significance of sutras, which were despised and even regarded as the obstacle to complete enlightenment, became accepted by the Chan. Due to Yanshou’s contributions, the principle that emphasized the diversity of teaching in terms of the relationship between meaning and expression in the Sui and Tang Dynasties has been changed into a system which stressed the importance of the root/branches relationship of the mind and words. According to Yanshou, the conflict between the Chan (...) and doctrinal teachings is resolved by highlighting the significance of words. Yanshou’s work greatly inspired the Chan’s interest in words in the Song Dynasty. (shrink)

Classifications of animals and plants have long been represented by hierarchical lists of taxa, but occasional authors have drawn diagrammatic versions of their classifications in an attempt to better depict the "natural relationships" of their organisms. Ornithologists in 19th-century Britain produced and pioneered many types of classificatory diagrams, and these fall into three groups: (a) the quinarian systems of Vigors and Swainson (1820s and 1830s); (b) the "maps" of Strickland and Wallace (1840s and 1850s); and (c) the evolutionary diagrams of (...) the post-Darwin authors (1860 on). The quinarians distinguished between affinity and analogy and used both in their classifications, whereas Strickland rejected the quinarians' belief in numerical regularity and their use of analogy. Wallace's "maps" are easily given an evolutionary interpretation, and his approach was taken up and modified by later evolutionary anatomists. Sharpe returned to Strickland's methods and merely appended a superficial evolutionary interpretation. Contrary to common belief systematics has a rich conceptual history, and many of the conceptual developments in 19th-century systematics were made by ornithologists. (shrink)

Characterizing how activity in the central and autonomic nervous systems corresponds to distinct emotional states is one of the central goals of affective neuroscience. Despite the ease with which individuals label their own experiences, identifying specific autonomic and neural markers of emotions remains a challenge. Here we explore how multivariate pattern classification approaches offer an advantageous framework for identifying emotion-specific biomarkers and for testing predictions of theoretical models of emotion. Based on initial studies using multivariate pattern classification, we (...) suggest that central and autonomic nervous system activity can be reliably decoded into distinct emotional states. Finally, we consider future directions in applying pattern classification to understand the nature of emotion in the nervous system. (shrink)

Neuromarketing has gained attention to bridge the gap between conventional marketing studies and electroencephalography -based brain-computer interface research. It determines what customers actually want through preference prediction. The performance of EEG-based preference detection systems depends on a suitable selection of feature extraction techniques and machine learning algorithms. In this study, We examined preference detection of neuromarketing dataset using different feature combinations of EEG indices and different algorithms for feature extraction and classification. For EEG feature extraction, we employed discrete wavelet (...) transform and power spectral density, which were utilized to measure the EEG-based preference indices that enhance the accuracy of preference detection. Moreover, we compared deep learning with other traditional classifiers, such as k-nearest neighbor, support vector machine, and random forest. We also studied the effect of preference indicators on the performance of classification algorithms. Through rigorous offline analysis, we investigated the computational intelligence for preference detection and classification. The performance of the proposed deep neural network outperforms KNN and SVM in accuracy, precision, and recall; however, RF achieved results similar to those of the DNN for the same dataset. (shrink)

It can be challenging to learn algorithms due to the research of business-related few-shot classification problems. Therefore, in this paper, we evaluate the classification of few-shot learning in the commercial field. To accurately identify the categories of few-shot learning problems, we proposed a probabilistic network method based on few-shot and one-shot learning problems. The enhancement of the original data was followed by the subsequent development of the PN method based on feature extraction, category comparison, and loss function analysis. (...) The effectiveness of the method was validated using two examples. Experimental results demonstrate the ability of the PN method to effectively identify the categories of commercial few-shot learning problems. Therefore, the proposed method can be applied to business-related few-shot classification problems. (shrink)

This book argues that it is again appropriate to bring "the human" to the fore, to reclaim the singularity of the word as central to the anthropological ...

A smooth rotated hyperbola model for support vector machine (SVM) is proposed. The method is based on the approximation property of the hyperbola to its asymptotic lines. The rotated hyperbola model has the least error on approximating the plus function when the angle between the two asymptotic lines is 135 degree. Experimental result shows that compared with other smooth methods, the rotated hyperbola function support vector machine (RHSSVM) reduces the compute time and can efficiently handle large scale and high dimensional (...) programs. (shrink)

In this paper, the multifeature fusion music classification algorithm and its simulation results are studied by deep confidence networks, the multifeature fusion music database is established and preprocessed, and then features are extracted. The simulation is carried out using multifeature fusion music data. The multifeature fusion music preprocessing includes endpoint detection, framing, windowing, and pre-emphasis. In this paper, we extracted the rhythm features, sound quality features, and spectral features, including energy, cross-zero rate, fundamental frequency, harmonic noise ratio, and 12 (...) statistical features, including maximum value, mean value, and linear slope. A total of 384-dimensional statistical features was extracted and compared with the classification ability of different emotional features. The deficiencies of the traditional classification algorithm are first studied, and then by introducing confusion, constructing multilevel classifiers, and tuning each level of the classifier, better recognition rates than traditional primary classification are obtained. This paper introduces label information for supervised training to further improve the features of multifunctional fusion music. Experiments show that this information has excellent performance in multifunctional fusion music recognition. The experiments compare the multilevel classifier with primary classification, and the multilevel classification with the primary classification and the classification performance is improved, and the recognition rate of the multilevel classification algorithm is also improved over the multilevel classification algorithm, proving that the excellent performance with multiple levels of classification. (shrink)

Création collective, instinctive, continue, dynamique grandiose de l'imaginaire, le sport traverse avec assurance l'histoire des peuples et n'a pas été inventé, au cours des âges, sur décision des princes ou recommandation des philosophes. Il est vivant, populaire, spontané. Il est émotion. Il est passion. C'est par là d'ailleurs qu'il échappe. Les bonnes raisons ne le touchent qu'en surface...

The concept of a function is central both to biology and to technology. But there is an intricate debate how functions as well as related entities like dispositions and roles are to be represented in top level ontologies and how they are to be related. We review important philosophical accounts and ontological models for functions and roles and discuss three models for the relation of functions and dispositions. We conclude that mainly because of the need to account for malfunctioning, functions (...) should not be treated as a subtype of dispositions, but as their sibling category. (shrink)