A vehicle-commodity matching problem is presented for service providers to reduce the cost of the logistics system. The vehicle classification model is built as a Gaussian mixture model, and the expectation-maximization algorithm is designed to solve the parameter estimation of GMM. A nonlinear mixed-integer programming model is constructed to minimize the total cost of VCMP. The matching process between vehicle and commodity is realized by GMM-EM, as a preprocessing of the solution. The design of the vehicle-commodity matching platform for (...) VCMP is designed to reduce and eliminate the information asymmetry between supply and demand so that the order allocation can work at the right time and the right place and use the optimal solution of vehicle-commodity matching. Furthermore, the numerical experiment of an e-commerce supply chain proves that a hybrid evolutionary algorithm is superior to the traditional method, which provides a decision-making reference for e-commerce VCMP. (shrink)

This paper presents an in-depth analysis of tennis match scene classification using an adaptive Gaussian mixture model parameter estimation simulation algorithm. We divided the main components of semantic analysis into type of motion, distance of motion, speed of motion, and landing area of the tennis ball. Firstly, for the problem that both people and tennis balls in the video frames of tennis matches from the surveillance viewpoint are very small, we propose an adaptive Gaussian mixture model parameter estimation (...) algorithm, which has good accuracy and speed on small targets. Secondly, in this paper, we design a sports player tracking algorithm based on role division and continuously lock the target player to be tracked and output the player region. At the same time, based on the displacement information of the key points of the player’s body and the system running time, the distance and speed of the player’s movement are obtained. Then, for the problem that tennis balls are small and difficult to capture in high-speed motion, this paper designs a prior knowledge-based algorithm for predicting tennis ball motion and landing area to derive the landing area of tennis balls. Finally, this paper implements a prototype system for semantic analysis of real-time video of tennis matches and tests and analyzes the performance indexes of the system, and the results show that the system has good performance in real-time, accuracy, and stability. (shrink)

Acoustic emission technique is a common approach to identify the damage of the refractories; however, there is a complex problem since there are as many as fifteen involved parameters, which calls for effective data processing and classification algorithms to reduce the level of complexity. In this paper, experiments involving three-point bending tests of refractories were conducted and AE signals were collected. A new data processing method of merging the similar parameters in the description of the damage and reducing the dimension (...) was developed. By means of the principle component analysis for dimension reduction, the fifteen related parameters can be reduced to two parameters. The parameters were the linear combinations of the fifteen original parameters and taken as the indexes for damage classification. Based on the proposed approach, the Gaussian mixture model was integrated with the Bayesian information criterion to group the AE signals into two damage categories, which accounted for 99% of all damage. Electronic microscope scanning of the refractories verified the two types of damage. (shrink)

The sampling-based motion planner is the mainstream method to solve the motion planning problem in high-dimensional space. In the process of exploring robot configuration space, this type of algorithm needs to perform collision query on a large number of samples, which greatly limits their planning efficiency. Therefore, this paper uses machine learning methods to establish a probabilistic model of the obstacle region in configuration space by learning a large number of labeled samples. Based on this, the high-dimensional samples’ rapid collision (...) query is realized. The influence of number of Gaussian components on the fitting accuracy is analyzed in detail, and a self-adaptive model training method based on Greedy expectation-maximization algorithm is proposed. At the same time, this method has the capability of online updating and can eliminate model fitting errors due to environmental changes. Finally, the model is combined with a variety of sampling-based motion planners and is validated in multiple sets of simulations and real world experiments. The results show that, compared with traditional methods, the proposed method has significantly improved the planning efficiency. (shrink)

This paper presents a kernel density estimation method by means of real-coded crossovers. Functions of real-coded crossover operators are composed of probabilistic density estimation from parental populations and sampling from estimated models. Real-coded Genetic Algorithm (RCGA) does not explicitly estimate probabilistic distributions, however, probabilistic model estimation is implicitly included in algorithms of real-coded crossovers. Based on this understanding, we exploit the implicit estimation of probabilistic distribution of crossovers as a kernel density estimator. We also propose an application of crossover kernels (...) to Expectation-Maximization estimation (EM) of Gaussian mixtures. (shrink)

We propose a novel probabilistic image selection method for the Web image gathering system we proposed before. It employed two-step processing: (1) Gather HTML files of Web pages related to given keywords, analyze them and fetch only Web images expected to be highly related to the keywords. (2) Select only relevant images from the gathered images based on the image-feature-based clustering. In this paper, we propose building a generative model based on the Gaussian mixture model to represent the distribution (...) of image features of images related to the given keywords, and applying it to select images instead of the processing (2). We call the new system ``Probabilistic Image Collector''. We show the effectiveness of our proposed system by the experimental results. (shrink)

Automatic moving object detection and tracking is very important task in video surveillance applications. In the present work the well known background subtraction model and use of Gaussian Mixture Models have been used to implement a robust automated single object tracking system. In this implementation, background subtraction on subtracting consecutive frame-by-frame basis for moving object detection is done. Once the object has been detected it is tracked by employing an efficient GMM technique. After successful completion of tracking, moving object (...) recognition of those objects using well known Principal Component Analysis, which is used for extracting features and Manhattan based distance metric is used for subsequent classification purpose. The system is capable of handling entry and exit of an object. Such a tracking system is cost effective and can be used as an automated video conferencing system and also has applications like human tracking, vehicles monitoring, and event recognition for video surveillance. The proposed algorithm was tested on standard database on complex environments and the results were satisfactory. (shrink)

An intervention may have an effect on units other than those to which it was administered. This phenomenon is called interference and it usually goes unmodeled. In this paper, we propose to combine Lauritzen-Wermuth-Frydenberg and Andersson-Madigan-Perlman chain graphs to create a new class of causal models that can represent both interference and non-interference relationships for Gaussian distributions. Specifically, we define the new class of models, introduce global and local and pairwise Markov properties for them, and prove their equivalence. We also (...) propose an algorithm for maximum likelihood parameter estimation for the new models, and report experimental results. Finally, we show how to compute the effects of interventions in the new models. (shrink)

In the data collection phase, the digital images are captured using sensors that often contaminated by noise (undesired random signal). In digital image processing task, enhancing the image quality and reducing the noise is a central process. Image denoising effectively preserves the image edges to a higher extend in the flat regions. Several adaptive filters (median filter, Gaussian filter, fuzzy filter, etc.) have been utilized to improve the smoothness of digital image, but these filters failed to preserve the image edges (...) while removing noise. In this paper, a modified fuzzy set filter has been proposed to eliminate noise for restoring the digital image. Usually in fuzzy set filter, sixteen fuzzy rules are generated to find the noisy pixels in the digital image. In modified fuzzy set filter, a set of twenty-four fuzzy rules are generated with additional four pixel locations for determining the noisy pixels in the digital image. The additional eight fuzzy rules ease the process of finding the image pixels,whether it required averaging or not. In this scenario, the input digital images were collected from the underwater photography fish dataset. The efficiency of the modified fuzzy set filter was evaluated by varying degrees of Gaussian noise (0.01, 0.03, and 0.1 levels of Gaussian noise). For performance evaluation, Structural Similarity (SSIM), Mean Structural Similarity (MSSIM), Mean Square Error (MSE), Normalized Mean Square Error (NMSE), Universal Image Quality Index (UIQI), Peak Signal to Noise Ratio (PSNR), and Visual Information Fidelity (VIF) were used. The experimental results showed that the modified fuzzy set filter improved PSNR value up to 2-3 dB, MSSIM up to 0.12-0.03, and NMSE value up to 0.38-0.1 compared to the traditional filtering techniques. (shrink)

In this paper, we propose an adaptive Gaussian incremental expectation stadium parameter estimation algorithm for sports video analysis and prediction through the study and analysis of sports videos. The features with more discriminative power are selected from the set of positive and negative templates using a feature selection mechanism, and a sparse discriminative model is constructed by combining a confidence value metric strategy. The sparse generative model is constructed by combining L1 regularization and subspace representation, which retains sufficient representational power (...) while dealing with outliers. To overcome the shortcomings of the traditional multiplicative fusion mechanism, this paper proposes an adaptive selection mechanism based on Euclidean distance, which aims to detect deteriorating models in time during the dynamic tracking process and adopt corresponding strategies to construct more reasonable likelihood functions. Based on the Bayesian citation framework, the adaptive selection mechanism is used to combine the sparse discriminative model and the sparse generative model. Also, different online updating strategies are adopted for the template set and Principal Component Analysis subspace to alleviate the drift problem while ensuring that the algorithm can adapt to the changes of target appearance in the dynamic tracking environment. Through quantitative and qualitative evaluation of the experimental results, it is verified that the algorithm proposed in this paper has stronger robustness compared with other classical algorithms. Our proposed visual object tracking algorithm not only outperforms existing visual object tracking algorithms in terms of accuracy, success rate, accuracy, and robustness but also achieve the performance required for real-time tracking in terms of execution speed on the central processing unit. This paper provides an in-depth analysis and discussion of the adaptive Gaussian incremental expectation stadium parameter estimation algorithm for sports video analysis. Using a variety of county-level algorithms for analysis and multiple solutions to improve the accuracy of the results, we obtain a more efficient and accurate algorithm. (shrink)

In this essay, we examine the use of resting state fMRI data for psychological inferences. We argue that resting state studies hold the paired promises of discovering novel functional brain networks, and of avoiding some of the limitations of task-based fMRI. However, we argue that the very features of experimental design that enable resting state fMRI to support exploratory science also generate a novel confound. We argue that seemingly key features of resting state functional connectivity networks may be artefacts resulting (...) from sampling a ‘mixture distribution’ of diverse brain networks active at different times during the scan. We explore the consequences of this ‘mixture view’ for attempts to theorize about the cognitive or psychological functions of resting state networks, as well as the value of exploratory experiments. (shrink)

Effective feature representation is the key to success of machine learning applications. Recently, many feature learning models have been proposed. Among these models, the Gaussian process latent variable model for nonlinear feature learning has received much attention because of its superior performance. However, most of the existing GPLVMs are mainly designed for classification and regression tasks, thus cannot be used in data clustering task. To address this issue and extend the application scope, this paper proposes a novel GPLVM for clustering. (...) Specifically, by combining GPLVM with the subspace clustering method, our C-GPLVM can obtain more representative latent variable for clustering. Moreover, it can directly predict the new samples by introducing a back constraint in the model, thus being more suitable for big data learning tasks such as analysis of chaotic time series and so on. In the experiment, we compare it with the related GPLVMs and clustering algorithms. The experimental results show that the proposed model not only inherits the feature learning ability of GPLVM but also has superior clustering accuracy. (shrink)

This paper takes up issues related to the notion of chemical substances arising from their mereological and modal features. Related notions are elements and compounds, into which substances are sub-divided, and the general notion of mixture, which as a special case might involve several substances, but covers other cases too. These are essentially macroscopic concepts. Some of the chemical arguments for this claim have been presented elsewhere. The present paper is a metaphysical treatment of matter as categorised by the (...) major chemical concepts bearing on distinctions between homogeneous and heterogeneous matter, and between a single and several substances. (shrink)

This study aims to identify the necessary strategies for the development of a sustainable financial system. For this purpose, a novel approach could be provided for soft computing with Gaussian-based fuzzy DEMATEL approach to understand the significant levels and impact-relation degrees of these criteria. For robustness check, this evaluation has also been performed for triangular and trapezoidal fuzzy sets. There are many novelties of this study. Firstly, computer science has a significant role in the decision-making process. Another specificity is that (...) the use of Gaussian numbers with fuzzy numbers is a new area. In addition, interval type-2 fuzzy sets also provide a significant advantage in decision-making under uncertainty. The results demonstrate that the size of the alternative financing, investment in efficient projects, and effective advertisement/promotions are the most important items to affect the performance of alternative banking system of emerging economies. Hence, it is recommended that the new banking applications should be applied by the state or the state can provide some incentives for foreign banks to invest in emerging economies, such as tax reduction. Another important point is that the financial intermediations should generate a component financial analysis team to examine the financial reports of the companies in detail so that the financial credibility of these companies can be evaluated more effectively. (shrink)

Exploratory analyses are an important first step in psychological research, particularly in problem-based research where various variables are often included from multiple theoretical perspectives not studied together in combination before. Notably, exploratory analyses aim to give first insights into how items and variables included in a study relate to each other. Typically, exploratory analyses involve computing bivariate correlations between items and variables and presenting them in a table. While this is suitable for relatively small data sets, such tables can easily (...) become overwhelming when datasets contain a broad set of variables from multiple theories. We propose the Gaussian graphical model as a novel exploratory analyses tool and present a systematic roadmap to apply this model to explore relationships between items and variables in environmental psychology research. We demonstrate the use and value of the Gaussian graphical model to study relationships between a broad set of items and variables that are expected to explain the effectiveness of community energy initiatives in promoting sustainable energy behaviors. (shrink)

I describe two candidate representations of a mixture. The first, which I call the ‘standard representation’, is not a good representation of a mixture in spite of its widespread popularity. The second, which I call ‘Gibbs’ representation’, is less widely adopted but is, I argue, a much better representation. I show that, once we have a precise mathematical structure that can be used to represent thermodynamic systems, and once an adequate perspective on representation is adopted, Gibbs’ representation trumps (...) the standard representation. (shrink)

Cavendish is critical of two of the experimental sciences of her day: chemistry and microscopy. Rather than creating new things, as their practitioners claim, they produce 'hermaphroditical mixtures'. I trace this startling metaphor to the alchemical tradition and suggest how its origins can help us to understand Cavendish's position. In her view, the chemists and microscopists exaggerate their own power and creativity, and fail to recognise that human creativity belongs primarily to imagination. I show how this theme is worked out (...) in Cavendish's paired texts, Observations on Experimental Philosophy and the fictional Blazing World. (shrink)

In his works on natural sciences, primarily in the Physics, Aristotle focuses on different forms of metabolē and distinguishes movement in general from substantial change. The On generation and corruption deals with the latter. When reading this treatise, one should pay particular attention to the concept of mixture. Apart from being the subject of a specific chapter, the problem of mixture permeates the whole work. But what exactly is mixture? Is it a simple combination of small parts? (...) Can a compound of water and wine be called mixture? If so, is this mixture and nothing more? In the course of the discussion, it is argued that the Aristotelian idea of mixis does not correspond to the concept that is usually associated with it. Rather, it is shown that mixis is fundamental for comprehending the physical world and constitutes not only the term per quem the first elements of all material bodies originate, but also plays a fundamental role in all natural sciences, particularly, in biology. (shrink)

A mixture preorder is a preorder on a mixture space (such as a convex set) that is compatible with the mixing operation. In decision theoretic terms, it satisfies the central expected utility axiom of strong independence. We consider when a mixture preorder has a multi-representation that consists of real-valued, mixture-preserving functions. If it does, it must satisfy the mixture continuity axiom of Herstein and Milnor (1953). Mixture continuity is sufficient for a mixture-preserving multi-representation (...) when the dimension of the mixture space is countable, but not when it is uncountable. Our strongest positive result is that mixture continuity is sufficient in conjunction with a novel axiom we call countable domination, which constrains the order complexity of the mixture preorder in terms of its Archimedean structure. We also consider what happens when the mixture space is given its natural weak topology. Continuity (having closed upper and lower sets) and closedness (having a closed graph) are stronger than mixture continuity. We show that continuity is necessary but not sufficient for a mixture preorder to have a mixture-preserving multi-representation. Closedness is also necessary; we leave it as an open question whether it is sufficient. We end with results concerning the existence of mixture-preserving multi-representations that consist entirely of strictly increasing functions, and a uniqueness result. (shrink)

This is a translation of Duhem's Le mixte et la combination chimique (1902) together with eight related essays including Les theories de la chaleur (1895), Thermochimie (1897), L'oeuvre de M. J. H. van 't Hoff (1900) and a short extract from Traité d'énergétique (1911) dealing with the nature of mixtures.

This paper implements the continuous Hindi Automatic Speech Recognition (ASR) system using the proposed integrated features vector with Recurrent Neural Network (RNN) based Language Modeling (LM). The proposed system also implements the speaker adaptation using Maximum-Likelihood Linear Regression (MLLR) and Constrained Maximum likelihood Linear Regression (C-MLLR). This system is discriminatively trained by Maximum Mutual Information (MMI) and Minimum Phone Error (MPE) techniques with 256 Gaussian mixture per Hidden Markov Model(HMM) state. The training of the baseline system has been done (...) using a phonetically rich Hindi dataset. The results show that discriminative training enhances the baseline system performance by up to 3%. Further improvement of ~7% has been recorded by applying RNN LM. The proposed Hindi ASR system shows significant performance improvement over other current state-of-the-art techniques. (shrink)

In this article, we propose a new method to learn the underlying acyclic mixed graph of a linear non-Gaussian structural equation model with given observational data. We build on an algorithm proposed by Wang and Drton, and we show that one can augment the hidden variable structure of the recovered model by learning multidirected edges rather than only directed and bidirected ones. Multidirected edges appear when more than two of the observed variables have a hidden common cause. We detect the (...) presence of such hidden causes by looking at higher order cumulants and exploiting the multi-trek rule. Our method recovers the correct structure when the underlying graph is a bow-free acyclic mixed graph with potential multidirected edges. (shrink)

In order to solve the shortcomings of particle swarm optimization in solving multiobjective optimization problems, an improved multiobjective particle swarm optimization algorithm is proposed. In this study, the competitive strategy was introduced into the construction process of Pareto external archives to speed up the search process of nondominated solutions, thereby increasing the speed of the establishment of Pareto external archives. In addition, the descending order of crowding distance method is used to limit the size of external archives and dynamically adjust (...) particle parameters; in order to solve the problem of insufficient population diversity in the later stage of algorithm iteration, time-varying Gaussian mutation strategy is used to mutate the particles in external archives to improve diversity. The simulation experiment results show that the improved algorithm has better convergence and stability than the other compared algorithms. (shrink)

A mixture preorder is a preorder on a mixture space (such as a convex set) that is compatible with the mixing operation. In decision theoretic terms, it satisfies the central expected utility axiom of strong independence. We consider when a mixture preorder has a multi-representation that consists of real-valued, mixture-preserving functions. If it does, it must satisfy the mixture continuity axiom of Herstein and Milnor (1953). Mixture continuity is sufficient for a mixture-preserving multi-representation (...) when the dimension of the mixture space is countable, but not when it is uncountable. Our strongest positive result is that mixture continuity is sufficient in conjunction with a novel axiom we call countable domination, which constrains the order complexity of the mixture preorder in terms of its Archimedean structure. We also consider what happens when the mixture space is given its natural weak topology. Continuity (having closed upper and lower sets) and closedness (having a closed graph) are stronger than mixture continuity. We show that continuity is necessary but not sufficient for a mixture preorder to have a mixture-preserving multi-representation. Closedness is also necessary; we leave it as an open question whether it is sufficient. We end with results concerning the existence of mixture-preserving multi-representations that consist entirely of strictly increasing functions, and a uniqueness result. (shrink)

Mathematicians use the word ‘deep’ to convey a high appreciation of a concept, theorem, or proof. This paper investigates the extent to which the term can be said to have an objective character by examining its first use in mathematics. It was a consequence of Gauss's work on number theory and the agreement among his successors that specific parts of Gauss's work were deep, on grounds that indicate that depth was a structural feature of mathematics for them. In contrast, French (...) mathematicians had a less structural, more problem-oriented approach to mathematics and did not speak of depth so readily. (shrink)

This study is to explore the gesture recognition and behavior tracking in swimming motion images under computer machine vision and to expand the application of moving target detection and tracking algorithms based on computer machine vision in this field. The objectives are realized by moving target detection and tracking, Gaussian mixture model, optimized correlation filtering algorithm, and Camshift tracking algorithm. Firstly, the Gaussian algorithm is introduced into target tracking and detection to reduce the filtering loss and make the acquired (...) motion posture more accurate. Secondly, an improved kernel-related filter tracking algorithm is proposed by training multiple filters, which can clearly and accurately obtain the motion trajectory of the monitored target object. Finally, it is proposed to combine the Kalman algorithm with the Camshift algorithm for optimization, which can complete the tracking and recognition of moving targets. The experimental results show that the target tracking and detection method can obtain the movement form of the template object relatively completely, and the kernel-related filter tracking algorithm can also obtain the movement speed of the target object finely. In addition, the accuracy of Camshift tracking algorithm can reach 86.02%. Results of this study can provide reliable data support and reference for expanding the application of moving target detection and tracking methods. (shrink)

Aristotle’s On generation and corruption raises a vital question: how is mixture, or what we would now call chemical combination, possible? It also offers an outline of a solution to the problem and a set of criteria that a successful solution must meet. Understanding Aristotle’s solution and developing a viable peripatetic theory of chemical combination has been a source of controversy over the last two millennia. We describe seven criteria a peripatetic theory of mixture must satisfy: uniformity, recoverability, (...) potentiality, equilibrium, alteration, incompleteness, and the ability to distinguish mixture from generation, corruption, juxtaposition, augmentation, and alteration. After surveying the theories of Philoponus (d. 574), Avicenna(d. 1037), Averroes (d. 1198), and John M. Cooper (fl. circa2000), we argue for the merits of Richard Rufus of Cornwall’s theory. Rufus (fl. 1231–1256) was a little known scholastic philosopher who became a Franciscan theologian in 1238, after teaching Aristotelian natural philosophy as a secular master in Paris. Lecturing on Aristotle’s De generatione et corruptione, around the year 1235, he offered his students a solution to the problem of mixture that we believe satisfies Aristotle’s seven criteria. # 2004 Elsevier Ltd. All rights reserved. (shrink)

Speaker recognition under mismatched conditions is a challenging task. Speech signal is nonlinear and nonstationary, and therefore, difficult to analyze under realistic conditions. Also, in real conditions, the nature of the noise present in speech data is not known a priori. In such cases, the performance of speaker identification or speaker verification degrades considerably under realistic conditions. Any SR system uses a voice activity detector as the front-end subsystem of the whole system. The performance of most VADs deteriorates at the (...) front end of the SR task or system under degraded conditions or in realistic conditions where noise plays a major role. Recently, speech data analysis and processing using Norden E. Huang’s empirical mode decomposition combined with Hilbert transform, commonly referred to as Hilbert–Huang transform, has become an emerging trend. EMD is an a posteriori, adaptive, data analysis tool used in time domain that is widely accepted by the research community. Recently, speech data analysis and speech data processing for speech recognition and SR tasks using EMD have been increasing. EMD-based VAD has become an important adaptive subsystem of the SR system that mostly mitigates the effect of mismatch between the training and the testing phase. Recently, we have developed a VAD algorithm using a zero-frequency filter-assisted peaking resonator and EMD. In this article, the efficacy of an EMD-based VAD algorithm is studied at the front end of a text-independent language-independent SI task for the speaker’s data collected in three languages at five different places, such as home, street, laboratory, college campus, and restaurant, under realistic conditions using EDIROL-R09 HR, a 24-bit wav/mp3 recorder. The performance of this proposed SI task is compared against the traditional energy-based VAD in terms of percentage identification rate. In both cases, widely accepted Mel frequency cepstral coefficients are computed by employing frame processing from the extracted voiced speech regions using the respective VAD techniques from the realistic speech utterances, and are used as a feature vector for speaker modeling using popular Gaussian mixture models. The experimental results showed that the proposed SI task with the VAD algorithm using ZFFPR and EMD at its front end performs better than the SI task with short-term energy-based VAD when used at its front end, and is somewhat encouraging. (shrink)

Some points are made about substance properties in their role of introducing mass terms. In particular, two conditions of distributivity and cumulativity of mass predicates expressing these properties are not the independent pair they first appear to be. A classification of macroscopic substance concepts is developed. This needs to be complemented in some way by the introduction of a modal qualification reminiscent of Aristotle's distinction between actual and potential presence of substances in a mixture. Consideration of the latter feature (...) has prompted Joe Earley to raise the question of whether there is any salt in the sea. I try to argue that there is. (shrink)

The performance of most of the state-of-the-art speaker recognition systems deteriorates under degraded conditions, owing to mismatch between the training and testing sessions. This study focuses on the front end of the speaker verification system to reduce the mismatch between training and testing. An adaptive voice activity detection algorithm using zero-frequency filter assisted peaking resonator was integrated into the front end of the SV system. The performance of this proposed SV system was studied under degraded conditions with 50 selected speakers (...) from the NIST 2003 database. The degraded condition was simulated by adding different types of noises to the original speech utterances. The different types of noises were chosen from the NOISEX-92 database to simulate degraded conditions at signal-to-noise ratio levels from 0 to 20 dB. In this study, widely used 39-dimension Mel frequency cepstral coefficient features were used, and Gaussian mixture model–universal background model was used for speaker modeling. The proposed system’s performance was studied against the energy-based VAD used as the front end of the SV system. The proposed SV system showed some encouraging results when EMD-based VAD was used at its front end. (shrink)

BACKGROUND -/- In biomedical ontologies, mereological relations have always been subject to special interest due to their high relevance in structural descriptions of anatomical entities, cells, and biomolecules. This paper investigates two important subrelations of has_proper_part, viz. the relation has_grain, which relates a collective entity to its multiply occurring uniform parts (e.g., water molecules in a portion of water), and the relation has_component, which relates a compound to its constituents (e.g., molecules to the atoms they consist of). -/- METHOD -/- (...) We distinguish between four kinds of complex entities and characterize them in first order logic. We then discuss whether similar characterizations could be given in description logics, and finally apply the results to mixtures. -/- RESULTS -/- At first sight, collectives and compounds seem to be disjoint categories. Their disjointness, however, relies on agreement about what are uniform entities, and thus on the granularity of description. For instance, the distinction between isomeric subtypes of a molecule can be important in one use case but might be neglected in another one. We demonstrate that, as implemented in the BioTop domain upper level ontology, equivalence or subsumption between different descriptions of same or similar entities cannot be achieved. Using OWL-DL, we propose a new design pattern that avoids primitive subrelations at the expense of more complex descriptions and thus supports the needed inferences. (shrink)

Now with extra footnotes, by editorial demand! Final version accepted by Oxford Studies in Ancient Philosophy. -/- This essay consists in a trick and a potential insight. The trick consists in a minimalist interpretation of color mixture. The account of color mixture is minimalist in the sense that, given certain background assumptions, there is no more to Timaeus’ account of color mixture than the list of the chromatic pathēmata and the list of how these combine to elicit (...) perceptions of all the colors. The only potential controversial elements of the minimalist interpretation are the relevant background assumptions and the interpretation of the chromatic pathēmata. The potential insight concerns a motive that Plato, in the guise of Timaeus, may have for presenting an account of color mixture. Specifically, I shall argue that on the minimalist interpretation, Plato may be read as reconciling the Democritrean four color scheme with an older tradi- tion where white and black are the fundamental chromatic opposition. As we shall see, this bears on the interpretation of the chromatic pathēmata. (shrink)

This paper investigates continuities and changes in the definition of sickle cell disease in 1950s Brazil, taking into account that diseases have a history and are recognized as such according to the knowledge and perceptions available in a certain historical period and specific location. In the post-war era, new diagnostic tools, inheritance theories and, in particular, discussions on the concepts of race and racial relations, both nationally and internationally, were changing previous racialist and racist views. Nonetheless, the Brazilian medical interpretations (...) of sickle cell disease continued to racialize it and even use deep-rooted racist formulations to explain its symptoms or the existence of the disease. It is argued that the celebration of racial mixture and racial democracy might have concealed racist presumptions biasing the study of sickle cell disease. Although race as a biological concept gradually gave way to other genetic expressions, in Brazilian medical papers on sickle cell disease, race continued to influence the interpretation of the disease, along with the persistence of concepts of heredity through blood mixture. (shrink)

Like Samiksha Goyal, many have asked—was Gandhi a Philosopher, deeply committed to moral principles, or a mass leader who was political strategist par excellence? In my response, I argue that scholars have created a false dichotomy between Gandhi the philosopher and Gandhi the pragmatic politician because usually these two are considered as different as chalk and cheese. Politicians are not expected to be moral and spiritual persons are not expected to be pragmatic. But, this article explains that it is wrong (...) to even think in terms of such a dichotomy because Gandhi evolved as a unique combination of a philosopher who had a highly moral and spiritual position that was necessarily political, and a shrewd pragmatic politician who had a political position that was necessarily moral and spiritual. Hence, the mixture was the essence. (shrink)

From a modern point of view, compounds are contrasted with elements of which they are composed, and the two categories combine to give the category of substances. Mixtures, on the other hand, might be understood to contrast with pure substances (substances in isolation), so that mixtures are quantities of matter containing several substances (be they compounds or uncombined elements) whereas pure substances are understood to be quantities of matter exhausting the material contents of a region of space which contain only (...) one substance, and might be either a compound or an element. But heterogeneous quantities of matter (comprising several phases) might also be understood to be mixtures. Thus, it is common to speak of a mixture of ice, liquid water and water vapour in equilibrium at the triple point of water, although there is only a single substance present. The general concept of mixture as treated by Gibbs’ phase rule is a quantity of matter comprising either several substances or several phases, “or” being used in the inclusive sense. Gibbs’ phase rule is a relatively recent development in the history of the concept of chemical substance, dating from the latter half of the nineteenth century. The concepts and distinctions it presupposes have not always been apparent. I trace some of the important conceptual developments underlying the important distinctions at issue here from Aristotle, who didn’t distinguish either substance and phase, or what are now called compounds and solutions. (shrink)

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and (...) tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method’s sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results. (shrink)

For Anaxagoras, both before the beginning of the world and in the present, “all is together” and “everything is in everything.” Various modern interpretations abound regarding the identity of this “mixture.” It has been explained as an aggregation of particles or as a continuous “fusion” of different sorts of ingredients. However—even though they are not usually recognized as a distinct group—there are a number of other scholars who, without seemingly knowing each other, have offered a different interpreta- tion: Anaxagoras’ (...) mixture as an “interpenetration” of different ingredients, which are as far-extended as the whole mixture is. As a result, there are different entities occupying the same place at the same time. This explanation assigns to Anaxagoras the same model of mixture which was later used by the Stoics. A new book by Marmodoro helps us to clarify this position. (shrink)

As is well known, Descartes’ doctrine on the relations of mind and body involves at least the following two theses: the real distinction of mind and body is compatible with their substantial union; and the siting of the mind at the tip of the pineal gland is compatible with its presence throughout the body. Th is essay seeks to perform three main tasks. One is to suggest that, so far as Descartes is concerned, the doctrine that arises out of the (...) combination of and blocks off the problems that are alleged to arise for mind-body interaction. A second is to illustrate how, in a certain vision of Descartes’ thought, and are more closely connected to each other than is generally explicitly recognised. And a third is to illustrate how one grade of mixture of stuff-types that the ancient Stoics envisaged both provides a model for answering Descartes’ demands and has a reputable pedigree within the tradition to which he was heir. (shrink)

In his introduction to part 2 of the Common Knowledge symposium on xenophilia, the journal's editor tours the reader through two private apartments and through two public art collections in an effort to establish that aesthetically coherent mixtures of apparently immiscible objects from widely divergent cultures are possible and also morally glamorous. Xenophobia at its least reprehensible, he argues, is a fear of ecumenism and its consequences, as well as a fear of one's own conversion — of “turning Turk.” Xenophilia (...) at its most admirable is a pursuit of coherent mixtures where others cannot imagine their possibility. Bits lifted from reputedly pure and organic wholes may be transformed by means of overlap and mediated juxtaposition into a novel milieu that has a wholeness, authenticity, and charisma of its own. Such coherence depends on minds that are capable of loving what does not satisfy their narcissism and that can sense in the products of their own culture elements or signs of enervation, anomie, lack, derangement, waywardness, rigidity, preciousness, or warping. The author concludes that xenophilia neither signals nor facilitates the adulteration that xenophobes so fear. (shrink)

Mixture item response theory models include a mixture of latent subpopulations such that there are qualitative differences between subgroups but within each subpopulation the measure model based on a continuous latent variable holds. Under this modeling framework, students can be characterized by both their location on a continuous latent variable and by their latent class membership according to Students’ responses. It is important to identify anchor items for constructing a common scale between latent classes beforehand under the (...) class='Hi'>mixture IRT framework. Then, all model parameters across latent classes can be estimated on the common scale. In the study, we proposed Q-matrix anchored mixture Rasch model, including a Q-matrix and the traditional mixture Rasch model. The Q-matrix in QAMRM can use class invariant items to place all model parameter estimates from different latent classes on a common scale regardless of the ability distribution. A simulation study was conducted, and it was found that the estimated parameters of the QAMRM recovered fairly well. A real dataset from the Certificate of Proficiency in English was analyzed with the QAMRM, LCDM. It was found the QAMRM outperformed the LCDM in terms of model fit indices. (shrink)

Galen’s elemental mixture of fire, air, water and earth (and of the corresponding primary qualities, hot, cold, dry and wet) is primarily a physical process, in which primary elements mix and give rise to all compounded physical bodies, inanimate and animate. As such, the concrete, physical process of mixture is an essential basis for a thorough understanding of Galen’s physical system. In this article I pursued a twofold aim. First, I showed Galen’s syncretic approach while expounding his theory (...) of mixture (insofar as he attributes that theory equally to ‘Hippocrates’, Aristotle and the Stoics) and illustrated the reasons behind this approach. Second, and more importantly, I addressed Galen’s epistemological position concerning mixture’s constituents and answered the question of whether, according to Galen, are the qualities alone, conceived more Aristotelico as conceptually distinct from the body itself, to mix or if Galen viewed mixture, as the Stoics did, as a coextension of bodies. As we argue, Galen assigns the epistemological status of πιθανόν to the Aristotelian and Peripatetic doctrines. This indicates that, to a certain extent, he joins this historical debate and is more closely aligned with Aristotle and the Peripatetics than with the Stoics. By resorting to what is πιθανόν Galen obtains two results: (1) does not expose himself to accusations of dogmatism but, at the same time and in his method, enters the ongoing controversy about qualities and bodies without taking a definitive position, and (2) he preserves his syncretic theoretical structure which finds its linchpin in the defence of a medical-cum-philosophical continuism. (shrink)

In this work, the significance of combining the evidence from multitaper mel-frequency cepstral coefficients, linear prediction residual, and linear prediction residual phase features for multilingual speaker identification with the constraint of limited data condition is demonstrated. The LPR is derived from linear prediction analysis, and LPRP is obtained by dividing the LPR using its Hilbert envelope. The sine-weighted cepstrum estimators with six tapers are considered for multitaper MFCC feature extraction. The Gaussian mixture model–universal background model is used for modeling (...) each speaker for different evidence. The evidence is then combined at scoring level to improve the performance. The monolingual, crosslingual, and multilingual speaker identification studies were conducted using 30 randomly selected speakers from the IITG multivariability speaker recognition database. The experimental results show that the combined evidence improves the performance by nearly 8–10% compared with individual evidence. (shrink)

Understanding and solving the psychological health problems of college students have become a focus of social attention. Complex networks have become important tools to study the factors affecting psychological health, and the Gaussian graphical model is often used to estimate psychological networks. However, previous studies leave some gaps to overcome, including the following aspects. When studying networks of subpopulations, the estimation neglects the intrinsic relationships among subpopulations, leading to a large difference between the estimated network and the real network. Because (...) of the high cost, previous psychological surveys often have a small sample size, and the psychological description is insufficient. Here, the intrinsic connections among multiple tasks are used, and multitask machine learning is applied to develop a multitask Gaussian graphical model. The psychological networks of the population and subpopulations are estimated based on psychological questionnaire data. This study is the first to apply a psychological network to such a large-scale college student psychological analysis, and we obtain some interesting results. The model presented here is a dynamic model based on complex networks which predicts individual behavior and provides insight into the intrinsic links among various symptoms. (shrink)

Intentional weight loss can increase health risk in the long‐term, despite short‐term benefits, because human adipose tissue is widely contaminated with various lipophilic environmental contaminants, especially persistent organic pollutants (POPs). Recently, chronic exposure to low POPs has emerged as a new risk factor for common metabolic diseases and cardiovascular diseases. The amount of POPs released from adipocytes to the circulation increases during weight loss, thereby increasing POPs exposure of other critical organs. Possible harmful effects due to release of POPs during (...) weight loss are opposite to those usually expected from losing weight. It is speculated that this tradeoff can explain recent puzzling findings on intensive weight loss. The presence of POPs in adipose tissue adds a challenge to weight management and an optimal strategy of weight management needs to consider both fat mass and dynamics of POPs. (shrink)

In this paper, we propose a person verification scheme using a novel combination of palmprint and speech. The crucial aspect of biometric based verification lies in its use of features in verification. Thus, in this paper, we propose two novel feature extraction methods for palmprint verification. The proposed methods are based on the Gaussian mixture model followed by subspace based approaches such as ICA I and ICA II, called independent component analysis I mixture model and independent component analysis (...) II mixture model for palmprint verification. The speech verification system uses sphericity based measurement for person verification. The proposed multimodal biometric system uses a fairly large database of 150 users. The robustness of the proposed methods is validated by introducing six different types of noises on palmprint images and Gaussian white noise with two different signal-to-noise ratios on speech samples. Then, fusion of palmprint and speech are carried out at match score level using the weighted SUM rule for both clean and noisy conditions. Finally, we compare the results of combined biometric with the results of individual biometric and also the results of the proposed methods against conventional subspace methods. (shrink)

Robert Deltete and Anastasios Brenner have provided a thorough examination of my translation of Duhem’s Le mixte et la combinaison chimique (1902) and associated essays. I am very grateful for their efforts and gratified that such competent reviewers should be generally positive. They provide an overview of relevant aspects of Duhem’s life and work, which may serve to introduce him to readers of this journal and promote interest in Duhem studies. They also raise and answer some questions about the interpretation (...) and evaluation of Duhem’s work, make some points of criticism of my choice of material and question certain points of translation. The editor has suggested that I make a response, and I shall take up some issues in these three areas. Since Duhem’s views play a central role in the development of the concept of chemical substance which I have worked on in recent years, I will make several references to my own publications. (shrink)