Semisupervised dimensionality reduction for hyperspectral images based on the combination of semisupervised learning and metric learning

This paper presents a semisupervised dimensionality reduction (DR) method based on the combination of semisupervised learning (SSL) and metric learning (ML) (CSSLML-DR) in order to overcome some existing limitations in HSIs analysis. Specifically, CSSML focuses on the difficulties of high dimensionality of hyperspectral images (HSIs) data, the insufficient number of labelled samples and inappropriate distance metric. CSSLML aims to learn a local metrics under which the similar samples are pushed as close as possible, and simultaneously, the different samples are pulled away as far as possible. CSSLML constructs two local-reweighted dynamic graphs in an iterative two-steps approach: L-step and V-step. In L-step, the local between-class and within-class graphs are updated. In V-step, the transformation matrix and the reduced space are updated. The algorithm is repeated until a stopping criterion is satisfied. Experimental results on two well-known hyperspectral image data sets demonstrate the superiority of CSSLML algorithm compared to some traditional DR methods.     

Cancer patients psychological adjustment and perception of illness: cultural differences between Belgium and Turkey

Little is known about cultural differences in psychological adjustment and perception of illness (PI) during medical procedures in general and radiotherapy in particular. This study compares a Turkish (TP) and a French speaking Belgian (BP) population. A group of 296 consecutive patients attending the radiotherapy clinic of Institut Jules Bordet, Brussels, (n = 172) and Oncology Institute, Capa-Istanbul, (n = 124) were interviewed and assessed by a symptom checklist, the SCL-90-R, at the beginning and at the end of the radiotherapy. PI, derived from a semi-structured interview, was assessed at the beginning of radiotherapy by a five-point observer-rating scale derived from the Omega Vulnerability Rating Scale. Differences in SCL-90-R scores, taking into account country, age, gender, level of education and PI as potential explanatory variables, have been tested by a multivariate analysis of variance with a design of repeated measures using the SCL-90-R scores as dependent variables. Mainly a time effect and a country effect have been found. Some interactions between both effects have also been found. Globally, all the SCL-90-R scores decrease between the beginning and the end of the radiotherapy. The effect of country is noticeable for most of the SCL-90-R components, with higher scores in the BP, except for the positive symptom total score where the TP showed higher scores. The interaction between country and time is not significant, the scores of both the BP and TP decreasing over time, except for somatization scores (P < 0.001) where the scores of the BP were stable over time while the scores of the TP decreased considerably, and for paranoid ideation scores (P = 0.001) where the scores of the BP decreased while the scores of the TP increased. Results showed a higher rate of correct perception in the BP compared to the TP (P = 0.0001). A PI effect has been found for somatization (P = 0.02), anxiety (P = 0.01) and Global Severity Index scores (P = 0.05), with higher mean scores for the "correct perception" category. No interaction with time was found. A significant interaction effect between country and PI has been found for anxiety scores with higher scores in the correct perception category in the BP and in the "denial of implications" category in the TP (P < 0.001). Results highlight cultural differences in psychological adjustment and/or in the responses to self-report questionnaires: greater weight was given to items by the BP, more numerous items were scored by the TP, and greater weight was given to the somatization subscale compared to the psychological subscales by the TP. This study suggests that psychosocial distress is expressed differently in Belgium and Turkey, where patients express mostly somatic complaints. Finally PI, a culture-dependent factor, appears to influence psychological adjustment very differently, a correct perception of illness leading to more anxiety in the BP compared to the TP.     

The triangular pyramid: Routing and topological properties

In this paper, a new topology for multicomputer interconnection networks, based on triangular mesh, is proposed. The new network, referred to as the triangular pyramid (or tripy for short), has L levels of triangular mesh. We study some basic important properties of the proposed network as well as introduce a routing algorithm for the tripy network based on the routing of triangular meshes. We prove that this form of pyramidal network is Hamiltonian, Hamiltonian-connected, and pancyclic. We also prove that the proposed network is 6-colorable and conduct a brief comparison of the tripy and its traditional pyramid counterpart. Our results show that the proposed network has higher scalability, connectivity, and total network bandwidth while preserving the important properties of the traditional pyramid network.     

Exploring creative thinking in graphically mediated synchronous dialogues

This paper reports on an aspect of the EC funded Argunaut project which researched and developed awareness tools for moderators of online dialogues. In this study we report on an investigation into the nature of creative thinking in online dialogues and whether or not this creative thinking can be coded for and recognized automatically such that moderators can be alerted when creative thinking is occurring or when it has not occurred after a period of time. We outline a dialogic theory of creativity, as the emergence of new perspectives from the interplay of voices, and the testing of this theory using a range of methods including a coding scheme which combined coding for creative thinking with more established codes for critical thinking, artificial intelligence pattern-matching techniques to see if our codes could be read automatically from maps and ‘key event recall’ interviews to explore the experience of participants. Our findings are that: (1) the emergence of new perspectives in a graphical dialogue map can be recognized by our coding scheme supported by a machine pattern-matching algorithm in a way that can be used to provide awareness indicators for moderators; (2) that the trigger events leading to the emergence of new perspectives in the online dialogues studied were most commonly disagreements and (3) the spatial representation of messages in a graphically mediated synchronous dialogue environment such as Digalo may offer more affordance for creativity than the much more common scrolling text chat environments. All these findings support the usefulness of our new account of creativity in online dialogues based on dialogic theory and demonstrate that this account can be operationalised through machine coding in a way that can be turned into alerts for moderators.     

Optimum design of electromagnetic shielding rooms with minimum usage of absorbing materials

In this article, a novel method has been proposed to optimize the electromagnetic shielding rooms. This method is based on using minimum electromagnetic absorbing materials on the inner surface of the rooms. The positions of the absorbing materials are found optimally to produce a “best” performance for the shielding rooms. The ray‐tracing method is used to predict the shielding effectiveness (SE) of the electromagnetic shielding rooms with apertures. The performance of the proposed method is verified by a comprehensive example. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE 2010.     

Scatter search technique for exam timetabling

At universities where students enjoy flexibility in selecting courses, the Registrar’s office aims to generate an appropriate exam timetable for numerous courses and large number of students. An appropriate, real-world exam timetable should show fairness towards all students, respecting the following constraints: (a) eliminating or minimizing the number of simultaneous exams; (b) minimizing the number of consecutive exams; (c) minimizing the number of students with two or three exams per day (d) eliminating the possibility of more than three exams per day (e) exams should fit in rooms with predefined capacity; and (f) the number of exam periods is limited. These constraints are conflicting, which makes exam timetabling intractable. Hence, solving this problem in realistic time requires the use of heuristic approaches. In this work, we develop an evolutionary heuristic technique based on the scatter search approach for finding good suboptimal solutions for exam timetabling. This approach is based on maintaining and evolving a population of solutions. We evaluate our suggested technique on real-world university data and compare our results with the registrar’s manual timetable in addition to the timetables of other heuristic optimization algorithms. The experimental results show that our adapted scatter search technique generates better timetables than those produced by the registrar, manually, and by other meta-heuristics.     

Problems of spatial linkage of a geo-referenced Demographic and Health Survey (DHS) dataset to a population census: A case study of Egypt

GPS coordinates are increasingly available as spatial references on population surveys in the developing world, where high-resolution address and street mapping are absent. This potentially offers opportunities to enhance national census data by spatial linkage with survey sources. The paper explores the use of GPS-referenced Demographic and Health Survey (DHS) data in combination with census data in Egypt and identifies errors in coordinate referencing. The study develops a practical approach to the measurement of spatial uncertainty in this situation and assessment of its impact on data linkage. The analysis specifically addresses the analytical implications at three different spatial scales and is internationally relevant to the handling of GPS-referenced DHS data in GIS.     

Classification of non-alcoholic beer based on aftertaste sensory evaluation by chemometric tools

Sensory evaluation is the application of knowledge and skills derived from several different scientific and technical disciplines, physiology, chemistry, mathematics and statistics, human behavior, and knowledge about product preparation practices. This research was aimed to evaluate aftertaste sensory attributes of commercial non-alcoholic beer brands (P1, P2, P3, P4, P5, P6, P7) by several chemometric tools. These attributes were bitter, sour, sweet, fruity, liquorice, artificial, body, intensity and duration. The results showed that the data are in a good consistency. Therefore, the brands were statistically classified in several categories. Linear techniques as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were performed over the data that revealed all types of beer are well separated except a partial overlapping between zones corresponding to P4, P6 and P7. In this research, for the confirmation of the groups observed in PCA and in order to calculate the errors in calibration and in validation, PLS-DA technique was used. Based on the quantitative data of PLS-DA, the classification accuracy values were ranked within 49-86%. Moreover, it was found that the classification accuracy of LDA was much better than PCA. It shows that this trained sensory panel can discriminate among the samples except an overlapping between two types of beer. Also, two types of artificial networks were used: Probabilistic Neural Networks (PNN) with Radial Basis Functions (RBF) and FeedForward Networks with Back Propagation (BP) learning method. The highest classification success rate (correct predicted number over total number of measurements) of about 97% was obtained for RBF followed by 94% for BP. The results obtained in this study could be used as a reference for electronic nose and electronic tongue in beer quality control.     

An Experimental and Theoretical Comparison of Model Selection Methods

Machine Learning - We investigate the problem of model selection in the setting of supervised learning of boolean functions from independent random examples. More precisely, we compare methods for...     

A generalization of the Chebyshev type inequalities for Sugeno integrals

In this paper, we give a generalization of the Chebyshev type inequalities for Sugeno integral with respect to non-additive measures. The main results of this paper generalize most of the inequalities for Sugeno integral obtained by many researchers. Also, some conclusions are drawn and some problems for further investigations are given.