Positive vectors clustering using inverted Dirichlet finite mixture models

In this work we present an unsupervised algorithm for learning finite mixture models from multivariate positive data. Indeed, this kind of data appears naturally in many applications, yet it has not been adequately addressed in the past. This mixture model is based on the inverted Dirichlet distribution, which offers a good representation and modeling of positive non-Gaussian data. The proposed approach for estimating the parameters of an inverted Dirichlet mixture is based on the maximum likelihood (ML) using Newton Raphson method. We also develop an approach, based on the minimum message length (MML) criterion, to select the optimal number of clusters to represent the data using such a mixture. Experimental results are presented using artificial histograms and real data sets. The challenging problem of software modules classification is investigated within the proposed statistical framework, also.     

Novel approaches for synthesizing video textures

Video texture, a novel type of medium, can produce a new video with a continuously varying stream of images from a recorded video. A classic approach to generate video textures is to apply principal components analysis (PCA) for dimensionality reduction (i.e. extraction of frame signatures) and autoregressive (AR) process for prediction purposes. In this paper we investigate the use of other dimensionality reduction techniques to generate accurate video textures. Based on our experiments, the quality of video textures can be improved further. We also propose a new approach for generating video textures using probabilistic principal components analysis (PPCA) and Gaussian process dynamical model (GPDM) to synthesize video textures which contain frames that never appeared before and with similar motions as original videos. Furthermore, we propose two ways of generating online video textures by applying the incremental Isomap and incremental Spatio-temporal Isomap (IST-Isomap). Both approaches can produce good online video texture results. In particular, IST-Isomap, that we propose, is more suitable for sparse video data (e.g. cartoon).     

Optimization of friction stir welding process using NSGA-II and DEMO

In welding processes, the selection of optimal process parameter settings is very important to achieve best weld qualities. In this work, neuro-multi-objective evolutionary algorithms (EAs) are proposed to optimize the process parameters in friction stir welding process. Artificial neural network (ANN) models are developed for the simulation of the correlation between process parameters and mechanical properties of the weld using back-propagation algorithm. The weld qualities of the weld joint, such as ultimate tensile strength, yield stress, elongation, bending angle and hardness of the nugget zone, are considered. In order to optimize those quality characteristics, two multi-objective EAs that are non-dominated sorting genetic algorithm II and differential evolution for multi-objective are coupled with the developed ANN models. In the end, multi-criteria decision-making method which is technique for order preference by similarity to the ideal solution is applied on the Pareto front to extract the best solutions. Comparisons are conducted between results obtained from the proposed techniques, and confirmation experiments are performed to verify the simulated results.

     

An inverse Black–Scholes problem

Optimization and Engineering - In this work, we provide a new Black–Scholes model, where the weak formulation at stake is done in the case of a general class of finite Radon measures. A...     

A heuristic to solve the synchronized log-truck scheduling problem

We present a synchronized routing and scheduling problem that arises in the forest industry, as a variation of the log-truck scheduling problem. It combines routing and scheduling of trucks with specific constraints related to the Canadian forestry context. This problem includes aspects such as pick-up and delivery, multiple products, inventory stock, multiple supply points and multiple demand points. We developed a decomposition approach to solve the weekly problem in two phases. In the first phase we use a MIP solver to solve a tactical model that determines the destinations of full truckloads from forest areas to woodmills. In the second phase, we make use of two different methods to route and schedule the daily transportation of logs: the first one consists in using a constraint-based local search approach while the second one is a hybrid approach involving a constraint programming based model and a constraint-based local search model. These approaches have been implemented using COMET2.0. The method, was tested on two industrial cases from forest companies in Canada.     

Unexploited Thapsia garganica,Orlaya maritima,and Retama raetam Seeds: Potential Sources of Unsaturated Fatty Acid and Natural Antioxidants

Total lipid contents, fatty acid compositions, phenolic profiles and antioxidants activities of seeds from Thapsia garganica, Orlaya maritima, and Retama raetam were investigated. The oil values were more than 26 %, except seeds of R. raetam (ca. 3 %). Unsaturated fatty acids accounted for the majority of the fatty acids (more than 75 %). Oleic and linoleic acid were the predominant fatty acids. Total phenolic compounds (24–104 mg GAE g^?1 DR), total flavonoids (4–102 mg QE g^?1g DR), total tannins (28–85 mg GAE g^?1 DR) and condensed tannins (0.62–131 mg CE g^?1 DR) were also determined. The antioxidant activities using different assays were evaluated. The predominant detected classes were the phenolic acids (42–85 %) and the flavonoids (11–48 %). The major phenolic acids were caffeic, trans‐4‐hydroxy‐3‐methoxycinnamic, p‐coumaric, and gallic acid. The predominant flavonoids were quercetin, luteolin, naringin, apigenin, and kaempferol. This study brings attention to the medicinal importance of these species as a source of oil and antioxidant molecules.     

A GIS Database for Sustainable Management of Shallow Water Resources in the Tulul al Ashaqif Region, NE Jordan

The Tulul al Ashaqif region is an arid area in northeastern Jordan that contains renewable shallow perched aquifer water. The study of these aquifers has led to better understanding of the recharge process as well as other hydrological issues related to management of water resources in similar areas. The use of geographic information system (GIS)-based predictive mapping to locate areas of high potential for shallow perched aquifer sites is explored in this paper. Knowledge of the hydrologic, geologic and geomorphic variables influencing the development of shallow aquifer formation is used to produce GIS layers representing the spatial distribution of those variables. The GIS layers are then analyzed to identify locations where combinations of environmental variables match patterns observed at known sites. In addition, information can be deduced on the volume of water that is available and the best locations to site recharge facilities. Moreover, future development of these resources requires consideration of possible adverse affects of usage on these resources. The database developed can be used for this purpose as well.     

Treatment of electroplating wastewater containing Cu2+, Zn2+ and Cr(VI) by electrocoagulation

The performance of electrocoagulation, with aluminium sacrificial anode, in the treatment of metal ions (Cu2+, Zn2+ and Cr(VI)) containing wastewater, has been investigated. Several working parameters, such as pH, current density and metal ion concentrations were studied in an attempt to achieve a higher removal capacity. Results obtained with synthetic wastewater revealed that the most effective removal capacities of studied metals could be achieved when the pH was kept between 4 and 8. In addition, the increase of current density, in the range 0.8-4.8 A dm(-2), enhanced the treatment rate without affecting the charge loading, required to reduce metal ion concentrations under the admissible legal levels. The removal rates of copper and zinc were found to be five times quicker than chromium because of a difference in the removal mechanisms. The process was successfully applied to the treatment of an electroplating wastewater where an effective reduction of (Cu2+, Zn2+ and Cr(VI)) concentrations under legal limits was obtained, just after 20 min. The electrode and electricity consumptions were found to be 1 g l(-1) and 32 A h l(-1), respectively. The method was found to be highly efficient and relatively fast compared to conventional existing techniques.     

Simple N‐Heterocyclic Carbenes as Ligands in Ullmann‐Type Ether and Thioether Formations

A simple N‐heterocyclic carbene (NHC) derived from 1‐methyl‐3‐ethylimidazolium tetrafluoroborate was found to be an efficient ligand for a range of copper‐catalyzed cross‐coupling reactions, leading to the formation of aromatic ethers and thioethers.