Random 3-SAT: The Plot Thickens

This paper presents an experimental investigation of the following questions: how does the average-case complexity of random 3-SAT, understood as a function of the order (number of variables) for fixed density (ratio of number of clauses to order) instances, depend on the density? Is there a phase transition in which the complexity shifts from polynomial to exponential in the order? Is the transition dependent or independent of the solver? Our experiment design uses three complete SAT solvers embodying different algorithms: GRASP, CPLEX, and CUDD. We observe new phase transitions for all three solvers, where the median running time shifts from polynomial in the order to exponential. The location of the phase transition appears to be solver-dependent. GRASP shifts from polynomial to exponential complexity near the density of 3.8, CPLEX shifts near density 3, while CUDD exhibits this transition between densities of 0.1 and 0.5. This experimental result underscores the dependence between the solver and the complexity phase transition, and challenges the widely held belief that random 3-SAT exhibits a phase transition in computational complexity very close to the crossover point.     

Design of a compact orthogonal fed self‐diplexing bowtie‐ring slot antenna based on substrate integrated waveguide

In this article, a novel design of compact cavity‐backed slot antenna based on substrate integrated waveguide (SIW) technology is presented for dual‐frequency communication services. A single layer printed circuit board is applied to implement the proposed antenna. The bowtie‐ring slot engraved on the SIW square cavity is excited using two orthogonal microstrip feed lines to operate at two distinct frequencies (6.62 GHz and 11.18 GHz). The proposed antenna allows each of these frequencies to be designed independently. A prototype of the proposed cavity‐backed antenna that radiates at both 6.62 GHz and 11.18 GHz is fabricated and measured. The port isolation better than 29.3 dB is achieved by utilizing the transmission zeros (TZs), which are produced due to the orthogonal feed lines, TE₁₁₀ mode and coupling between the TE₁₂₀ and TE₂₁₀ modes. The measured peak gains of the proposed diplexing antenna are 5.77 dBi and 5.81 dBi at lower and upper resonating frequencies, respectively. The proposed dual‐frequency antenna exhibits the front‐to‐back‐ratio (FTBR) and cross‐polarization level greater than 26 dB and 21 dB, respectively, at both resonating frequencies.     

Segmentation and range sensing using a moving-aperture lens

The use of a novel motorized lens to perform segmentation of image sequences is presented in this paper. The lens has the effect of introducing small, repeating movements of the camera center so that objects appear to translate in the image by an amount that depends on the distance from the plane of focus. For a stationary scene, optical flow magnitudes are therefore directly related to three-dimensional object distance from the observer. We describe a segmentation procedure that exploits these controlled observer movements and present experimental results that demonstrate the successful extraction of objects at different depths. Potential applications of our approach include image compositing, teleconferencing, and range estimation.Received: 4 July 2002, Accepted: 16 December 2002, Published online: 23 July 2003 Correspondence to: Amy E. Bell     

Effects of situational demand upon social enjoyment and preference in schizotypy.

The socioemotional functioning of schizophrenic and schizotypic individuals is marked by withdrawal, poor organization, and limited emotional displays. Such behavioral tendencies and lack of social enjoyment in schizotypy could be linked to the relative situational demands or role ambiguity inherent in specific social activities. To determine whether high-schizotypy individuals prefer more clearly role-defined social activities (e.g., visiting relatives) to more ambiguous, novel situations (e.g., going alone to a party), the authors gathered reports from 52 high-schizotypy and 60 low-schizotypy individuals on their enjoyment and frequency of engaging in social situations varying in relative situational demand. Parallel reports were obtained from knowledgeable others. Group × Situational Demand interactions revealed the hypothesized pattern of reduced frequency and enjoyment ratings for ambiguous or novel situations by the high-schizotypy participants in both self and others' reports. Groups were more comparable in their reported frequency and enjoyment of less ambiguous situations. Results suggest the importance of situational demands in the socioemotional experience and behavioral withdrawal in schizotypy. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Improved bounds for large scale capacitated arc routing problem

The Capacitated Arc Routing Problem (CARP) stands among the hardest combinatorial problems to solve or to find high quality solutions. This becomes even more true when dealing with large instances. This paper investigates methods to improve on lower and upper bounds of instances on graphs with over 200 vertices and 300 edges, dimensions that, today, can be considered of large scale. On the lower bound side, we propose to explore the speed of a dual ascent heuristic to generate capacity cuts. These cuts are next improved with a new exact separation enchained to the linear program resolution that follows the dual heuristic. On the upper bound, we implement a modified Iterated Local Search procedure to Capacitated Vehicle Routing Problem (CVRP) instances obtained by applying a transformation from the CARP original instances. Computational experiments were carried out on the set of large instances generated by Brandão and Eglese and also on the regular size sets. The experiments on the latter allow for evaluating the quality of the proposed solution approaches, while those on the former present improved lower and upper bounds for all instances of the corresponding set.     

Cost Effective Optimal Task Scheduling Model in Hybrid Cloud Environment

In today’s world, Cloud Computing (CC) enables the users to access computing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located in remote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and task scheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud is employed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the current research work develops a Cost-Effective Optimal Task Scheduling Model (CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) model is used in the proposed work for hybrid clouds. Moreover, the algorithm works on the basis of multi-intentional task completion process with optimal resource allocation. The model was successfully simulated to validate its effectiveness based on factors such as processing time, make span and efficient utilization of virtual machines. The results infer that the proposed model outperformed the existing works and can be relied in future for real-time applications.     

Watch to Edit: Video Retargeting using Gaze

We present a novel approach to optimally retarget videos for varied displays with differing aspect ratios by preserving salient scene content discovered via eye tracking. Our algorithm performs editing with cut, pan and zoom operations by optimizing the path of a cropping window within the original video while seeking to (i) preserve salient regions, and (ii) adhere to the principles of cinematography. Our approach is (a) content agnostic as the same methodology is employed to re‐edit a wide‐angle video recording or a close‐up movie sequence captured with a static or moving camera, and (b) independent of video length and can in principle re‐edit an entire movie in one shot. Our algorithm consists of two steps. The first step employs gaze transition cues to detect time stamps where new cuts are to be introduced in the original video via dynamic programming. A subsequent step optimizes the cropping window path (to create pan and zoom effects), while accounting for the original and new cuts. The cropping window path is designed to include maximum gaze information, and is composed of piecewise constant, linear and parabolic segments. It is obtained via L(1) regularized convex optimization which ensures a smooth viewing experience. We test our approach on a wide variety of videos and demonstrate significant improvement over the state‐of‐the‐art, both in terms of computational complexity and qualitative aspects. A study performed with 16 users confirms that our approach results in a superior viewing experience as compared to gaze driven re‐editing [ JSSH15 ] and letterboxing methods, especially for wide‐angle static camera recordings.     

Modeling basal ganglia for understanding Parkinsonian reaching movements

We present a computational model that highlights the role of basal ganglia (BG) in generating simple reaching movements. The model is cast within the reinforcement learning (RL) framework with correspondence between RL components and neuroanatomy as follows: dopamine signal of substantia nigra pars compacta as the temporal difference error, striatum as the substrate for the critic, and the motor cortex as the actor. A key feature of this neurobiological interpretation is our hypothesis that the indirect pathway is the explorer. Chaotic activity, originating from the indirect pathway part of the model, drives the wandering, exploratory movements of the arm. Thus, the direct pathway subserves exploitation, while the indirect pathway subserves exploration. The motor cortex becomes more and more independent of the corrective influence of BG as training progresses. Reaching trajectories show diminishing variability with training. Reaching movements associated with Parkinson's disease (PD) are simulated by reducing dopamine and degrading the complexity of indirect pathway dynamics by switching it from chaotic to periodic behavior. Under the simulated PD conditions, the arm exhibits PD motor symptoms like tremor, bradykinesia and undershooting. The model echoes the notion that PD is a dynamical disease.