RF MEMS continuous reversible variable inductor based on a microfluidic network

In this work, RF MEMS continuous reversible variable inductor has been fabricated by using microelectronic technology and lamination process. We review, evaluate and compare this variable inductor with other work. The proposed inductor is a dual circular coil and has an inductance of few nH. The fundamental idea is to place a liquid droplet between the metal turns of a coil in order to modify the capacitive/resistive coupling between metal tracks and hence to change the stored magnetic energy. The SU-8 resin was used to realize the microfluidic channels and Au as metallic tracks. To prove the reversibility of the inductor, two cases were studied: filling and emptying of channels. The tuning range of the inductance is approximately 107 % at 1.6 GHz, making these devices very suitable as building blocks in many RF applications.     

Speech driven photo realistic facial animation based on an articulatory DBN model and AAM features

This paper presents a photo realistic facial animation synthesis approach based on an audio visual articulatory dynamic Bayesian network model (AF_AVDBN), in which the maximum asynchronies between the articulatory features, such as lips, tongue and glottis/velum, can be controlled. Perceptual Linear Prediction (PLP) features from audio speech, as well as active appearance model (AAM) features from face images of an audio visual continuous speech database, are adopted to train the AF_AVDBN model parameters. Based on the trained model, given an input audio speech, the optimal AAM visual features are estimated via a maximum likelihood estimation (MLE) criterion, which are then used to construct face images for the animation. In our experiments, facial animations are synthesized for 20 continuous audio speech sentences, using the proposed AF_AVDBN model, as well as the state-of-art methods, being the audio visual state synchronous DBN model (SS_DBN) implementing a multi-stream Hidden Markov Model, and the state asynchronous DBN model (SA_DBN). Objective evaluations on the learned AAM features show that much more accurate visual features can be learned from the AF_AVDBN model. Subjective evaluations show that the synthesized facial animations using AF_AVDBN are better than those using the state based SA_DBN and SS_DBN models, in the overall naturalness and matching accuracy of the mouth movements to the speech content.     

Fuzzy clustering with learnable cluster-dependent kernels

We propose a new relational clustering approach, called Fuzzy clustering with Learnable Cluster-dependent Kernels (FLeCK), that learns the underlying cluster-dependent dissimilarity measure while seeking compact clusters. The learned dissimilarity is based on a Gaussian kernel function with cluster-dependent parameters. Each cluster’s parameter learned by FLeCK reflects the relative intra-cluster and inter-cluster characteristics. These parameters are learned by optimizing both the intra-cluster and the inter-cluster distances. This optimization is achieved iteratively by dynamically updating the partition and the local kernel. This makes the kernel learning task takes advantages of the available unlabeled data and reciprocally, the categorization task takes advantages of the learned local kernels. Another key advantage of FLeCK is that it is formulated to work on relational data. This makes it applicable to data where objects cannot be represented by vectors or when clusters of similar objects cannot be represented efficiently by a single prototype. Using synthetic and real data sets, we show that FLeCK learns meaningful parameters and outperforms several other algorithms. In particular, we show that when data include clusters with various inter- and intra-cluster distances, learning cluster-dependent parameters is crucial in obtaining a good partition.     

Virtual-water content of agricultural production and food trade balance of Tunisia

This article is devoted to the assessment of Tunisian agricultural production and food trade balance water-equivalent. A linear regression model relating annual rainfall to crop yields is developed to estimate the agricultural production water-equivalent. Its implementation is based on national data for crop and animal production, leading to food demand water-equivalent quantification. Results highlight the relationship between agricultural and water policies and provide a picture of food security in the country in relation to local agricultural production, and to virtual water fluxes related to foodstuffs trade balance.     

Local feature selection for multiple instance learning

Journal of Intelligent Information Systems - We propose a local feature selection method for the Multiple Instance Learning (MIL) framework. Unlike conventional feature selection algorithms that...     

A hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating transportation service quality

Managing service quality is vital to retain customer satisfaction and augment revenues for any business organization. Often it is difficult to assess service quality due to lack of quantifiable measures and limited data. In this paper, we present a hybrid approach based on SERVQUAL and fuzzy TOPSIS for evaluating service quality of urban transportation systems. The proposed approach consists of three steps. The first step involves development of a SERVQUAL based questionnaire to collect data for measuring transportation service quality. The participants provide linguistic assessments to rate the service quality criteria and the alternatives. In step 2, the linguistic ratings are combined through fuzzy TOPSIS to generate an overall performance score for each alternative. The alternative with the highest score is finally chosen. In step 3, sensitivity analysis is conducted to evaluate the influence of criteria weights on the decision making process.The strength of the proposed approach is its practical applicability and ability to provide solution under partial or lack of quantitative information. An application of the proposed approach for evaluation of service quality of metro in Montreal is provided.     

Synthesis and characterization of radiation cross-linked PVP hydrogels and investigation of its potential as an antileishmanial drug carrier

Polymer Bulletin - The aim of this study was to elaborate a suitable hydrogel to be used as drug carrier for antileishmanial treatment. Therefore, a PVP hydrogel was synthesized using gamma...     

Osmotic Dehydration Kinetics of Pomegranate Seeds Using Date Juice as an Immersion Solution Base

Pomegranate seeds were osmodehydrated using date juice added with sucrose (final °Brix, 55) as immersion solution. The kinetics of osmotic dehydration showed that the most significant changes of mass transfer took place during the first 20 min of the process, regardless of date juice varieties. During this time, seed water loss and solid gain were estimated to be ∼39% and ∼6%, respectively. After 20 min of the process, the percentage of water loss and solid gain varied slightly and ranged on average close to ∼40% and ∼9%, respectively. During osmotic dehydration, there was a leaching of natural solutes from seeds into the solution, which is quantitatively not negligible, and might have an important impact on the sensorial and nutritional value of seeds and date juices. Both scanning electron microscopy and texture (compression) analysis revealed that osmotic dehydration process induced modifications of seed texture and cell structure. Sucrose was found to be the essential element which influences the texture of seed and the viscosity of date juice. Additionally, natural sugar present in date juice permits substituting 35% of the total quantity of sucrose added to the osmotic solution.