Novel Application of Neutrosophic Logic in Classifiers Evaluated under Region-Based Image Categorization System

Neutrosophic logic is a relatively new logic that is a generalization of fuzzy logic. In this dissertation, for the first time, neutrosophic logic is applied to the field of classifiers where a support vector machine (SVM) is adopted as the example to validate the feasibility and effectiveness of neutrosophic logic. The proposed neutrosophic set is integrated into a reformulated SVM, and the performance of the achieved classifier N-SVM is evaluated under an image categorization system. Image categorization is an important yet challenging research topic in computer vision. In this dissertation, images are first segmented by a hierarchical two-stage self organizing map (HSOM), using color and texture features. A novel approach is proposed to select the training samples of HSOM based on homogeneity properties. A diverse density support vector machine (DD-SVM) framework that extends the multiple-instance learning (MIL) technique is then applied to the image categorization problem by viewing an image as a bag of instances corresponding to the regions obtained from the image segmentation. Using the instance prototype, every bag is mapped to a point in the new bag space, and the categorization is transformed to a classification problem. Then, the proposed N-SVM based on the neutrosophic set is used as the classifier in the new bag space. N-SVM treats samples differently according to the weighting function, and it helps reduce the effects of outliers. Experimental results on a COREL dataset of 1000 general purpose images and a Caltech 101 dataset of 9000 images demonstrate the validity and effectiveness of the proposed method

Pedagogical Translanguaging. Cenoz, J., & Gorter, D. (2022). Cambridge University Press, 68 pages, ISBN: 978-1-009-01440-3.

Translanguaging generally refers to the use of two or more languages consciously or unconsciously at the same time for communicative purposes in a multilingual context (Conteh, 2018). Pedagogical translanguaging is the teaching practice that utilizes various teacher-planned activities to foster language and content learning in classroom settings by activating all the linguistic knowledge students already possess (Cenoz & Gorter, 2022). In this connection, pedagogical translanguaging provides a theoretical and instructional approach to support the development of all the languages used by multilingual learners. More importantly, the strength of pedagogical translanguaging lies in its potential to inspire confidence and encourage participation in language classrooms. Because learners are allowed to take advantage of their entire linguistic repertoire to be fully engaged in the learning of a target language (Hirsu, Zacharias, & Futro, 2021). However, there are more things to consider than meets the eye for the implementation of pedagogical translanguaging

Characteristics of Postural Muscle Activity in Response to A Motor-Motor Task in Elderly

The purpose of the current study was to evaluate postural muscle performance of older adults in response to a combination of two motor tasks perturbations. Fifteen older participants were instructed to perform a pushing task as an upper limb perturbation while standing on a fixed or sliding board as a lower limb perturbation. Postural responses were characterized by onsets and magnitudes of muscle activities as well as onsets of segment movements. (Please see full abstract article

Randomized Search of Graphs in Log Space and Probabilistic Computation

Reingold has shown that L = SL, that s-t connectivity in a poly-mixing digraph is complete for promise-RL, and that s-t connectivity for a poly-mixing out-regular digraph with known stationary distribution is in L. Several properties that bound the mixing times of random walks on digraphs have been identified, including the digraph conductance and the digraph spectral expansion. However, rapidly mixing digraphs can still have exponential cover time, thus it is important to specifically identify structural properties of digraphs that effect cover times. We examine the complexity of random walks on a basic parameterized family of unbalanced digraphs called Strong Chains (which model weakly symmetric logspace computations), and a special family of Strong Chains called Harps. We show that the worst case hitting times of Strong Chain families vary smoothly with the number of asymmetric vertices and identify the necessary condition for non-polynomial cover time. This analysis also yields bounds on the cover times of general digraphs. Next we relate random walks on graphs to the random walks that arise in Monte Carlo methods applied to optimization problems. We introduce the notion of the asymmetric states of Markov chains and use this definition to obtain some results about Markov chains. We also obtain some results on the mixing times for Markov Chain Monte Carlo Methods. Finally, we consider the question of whether a single long random walk or many short walks is a better strategy for exploration. These are walks which reset to the start after a fixed number of steps. We exhibit digraph families for which a few short walks are far superior to a single long walk. We introduce an iterative deepening random search. We use this strategy estimate the cover time for poly-mixing subgraphs. Finally we discuss complexity theoretic implications and future work

イオン移動度質量分析法による５族金属酸化物クラスターイオンの構造と組成に関する研究

要約のみTohoku University美齊津文典課

イオン移動度質量分析法による５族金属酸化物クラスターイオンの構造と組成に関する研究

要約のみTohoku University美齊津文典課