Abstract
In this paper the role of Plug-In Electric Vehicles' (PIEVs) parking lot in operating Smart Multi-Energy System (SMES) has been investigated. SMES in this paper has been modeled as a multi-input multi-output model which consists of some storage and energy converters. In the proposed framework, the PIEV's parking lot behaves like an energy storage with selling energy price less than upstream network price and as manageable load when its purchase price is more than upstream network. On the other hand, traffic pattern of PIEVs in parking lot has an uncertain behavior and is modeled based on stochastic approach. In the stochastic model, two branches of scenarios for total state of charge and total capacity of parking lot in each hour are produced. The considered case studies show the effectiveness of the proposed model and the impact of PIEVs' parking lot in operation of SMES elements.

Abstract
Within network measurement context, traffic sampling has been targeted as a promising solution to cope with the huge amount of traffic traversing network devices as only a subset of packets is elected for analysis. Although this brings an evident advantage to measurement overhead, the computational burden of performing sampling tasks in network equipment may overshadow the potential benefits of sampling. Attending that sampling techniques evince distinct temporal and spatial characteristics in handling traffic, this paper is focused on studying the computational weight of current and emerging techniques in terms of memory consumption, CPU load and data volume. Furthermore, the accuracy of these techniques in estimating network parameters such as throughput is evaluated. A sampling framework has also been implemented in order to provide a versatile and fair platform for carrying out the testing and comparison process.

Abstract
In this paper three highly birefringent (HiBi) spun photonic crystal fibers (PCF) are fabricated and their performance are characterized for electrical current measurement. These fibers are tested by coiling them around an electric conductor using three distinct winding diameters with different turns. The results present a very good linear relation with the current and its sensitivity depends on the winding diameter and on the number of turns. For the larger winding diameter, the fiber with lower circular pitch had higher sensitivity and for the smaller winding diameter the best sensitivity result was for the fiber with higher circular pitch.

Abstract
In this work a simultaneous strain and temperature sensor based on a suspended core fiber is proposed. The sensor comprises a 3mm suspended core PCF between SMFs and is based on the combination of two multimodal interferences with different frequency fringe patterns. The interference of the both signal has different sensitivity responses to strain and temperature. Thought a low-pass frequency filtering of the detected spectrum, the wavelength shift of the two interferences can be measured allowing the discrimination of strain and temperature simultaneously. The resolutions of this sensor are 0.45 degrees C and 4.02 mu epsilon.

Abstract
The problem of cross-modal retrieval from multimedia repositories is considered. This problem addresses the design of retrieval systems that support queries across content modalities, for example, using an image to search for texts. A mathematical formulation is proposed, equating the design of cross-modal retrieval systems to that of isomorphic feature spaces for different content modalities. Two hypotheses are then investigated regarding the fundamental attributes of these spaces. The first is that low-level cross-modal correlations should be accounted for. The second is that the space should enable semantic abstraction. Three new solutions to the cross-modal retrieval problem are then derived from these hypotheses: correlation matching (CM), an unsupervised method which models cross-modal correlations, semantic matching (SM), a supervised technique that relies on semantic representation, and semantic correlation matching (SCM), which combines both. An extensive evaluation of retrieval performance is conducted to test the validity of the hypotheses. All approaches are shown successful for text retrieval in response to image queries and vice versa. It is concluded that both hypotheses hold, in a complementary form, although evidence in favor of the abstraction hypothesis is stronger than that for correlation.

Abstract