We refer to human-robot relationships as Lovotics. In this paper a design process for Lovotics is presented. In order to invoke these relationships, technological solutions can only take us so far. Design played an important role in order to engage users to explore the possibilities of bi-directional, human-robot love. We conducted a user-centric study in order to understand these factors and i...

In this paper, we propose a new approach for offline signature verification based on score level fusion of distance and orientation features of centroids. The proposed method employs symbolic representation of offline signatures using bi-interval valued feature vector. Distance and orientation features of centroids of offline signatures are used to form bi-interval valued symbolic feature vecto...

We propose and test a BI Success model, based on DeLone and McLean’s IS Success model, that incorporates comprehensive data that is needed for decision-making and computer systems that allow integration and analysis of that data as dimensions of BI success. Our model also includes organizational support structure for BI and the users’ involvement in the ongoing development of BI systems as cont...

Biomedical data sets often have mixed categorical and numerical types, where the former represent semantic information on the objects and the latter represent experimental results. We present the BILCOM algorithm for 'Bi-Level Clustering of Mixed categorical and numerical data types'. BILCOM performs a pseudo-Bayesian process, where the prior is categorical clustering. BILCOM partitions biomedi...

Code-Smells represent design situations that can affect the maintenance and evolution of software. They make a system difficult to evolve. Code-smells are detected, in general, using quality metrics that represent some symptoms. However, the selection of suitable quality metrics is challenging due to the absence of consensus to identify some code-smells based on a set of symptoms and also the h...

Exact Bi-Level image expansion techniques are required for a wide range of applications such as cartography, calligraphy, medical images, remote sensing, and satellite imagery [1,2,5]. Among the methods proposed in the literature are (a) pixel replication; (b) area sizing; (c) interpolation and spline methods; and (d) DCT-based techniques. All these methods generate distortion and noticeable de...

Mathematical programmes with equilibrium constraints (MPECs) constitute important modelling tools for network flow problems, as they place 'what-if' analyses in a proper mathematical framework. We consider a class of stochastic MPEC traffic models that explicitly incorporate possible uncertainties in travel costs and demands. In stochastic programming terminology, we consider 'here-and-now' mod...

The paper presents an approach to bi-level programming using a duality gap-penalty function format. A new exact penalty function exists for obtaining a global optimal solution for the linear case, and an algorithm is given for doing this, making use of some new theoretical properties. For each penalty parameter value, the central optimisation problem is one of maximising a convex function over ...

In this paper, bi-level linear programming problem with multiple objectives at each level in intuitionistic fuzzy environment is studied and solved. In this problem, technological coefficients and resources are characterized by intuitionistic fuzzy numbers having linear membership and non-membership function. Intuitionistic fuzzy efficient solution is computed for the upper level by the propose...

Many traditional approaches to statistical analysis cease to be useful when the number of variables is large in comparison with the sample size. Penalized regression methods have proved to be an attractive approach, both theoretically and empirically, for dealing with these problems. This thesis focuses on the development of penalized regression methods for high-dimensional variable selection. ...