DNA fragment assembly is a critical and essential early task in a genome project. This task leads to an NP-hard combinatorial optimization problem, and thus, efficient approximate algorithms are required to tackle large problem instances. The Problem Aware Local Search (PALS) is one of the most efficient heuristics for this problem in the literature. PALS gives fairly good solutions but the probability of premature convergence to local optima is significant. In this paper, we propose two modifications to the PALS heuristic in order to ameliorate its performance. The first modification enables the algorithm to improve the tentative solutions in a more appropriate and beneficial way. The second modification permits a significant reduction in the computational demands of the algorithm without significant accuracy loss. Computational experiments confirm that our proposals lead to a more efficient and robust assembler, improving both accuracy and efficiency.
Dissimilarity or distance metrics are the cornerstone of shape matching and retrieval algorithms. As there is no unique dissimilarity measure that gives good performances in all possible configurations, these metrics are usually combined to provide reliable results. In this paper we propose to compute the best linear convex, or weighted, combination of any set of measured shape distances to enhance shape matching algorithms. To do so, a database is represented as a graph, where nodes are shapes and the edges carry the convex combination of dissimilarity measures. Weights are chosen to maximize the weighted distances between the query shape and shapes in the database. The optimal weights are solutions of a linear programming problem. This fully unsupervised method improves the outcomes of any set of shape similarity measures as shown in our experimental results performed on several popular 3D shape benchmarks.
The majority of shape matching and retrieval methods use only one single shape descriptor. Unfortunately, no shape descriptor is sufficient to provide suitable results for all kinds of shapes. The most common way to improve the performance of shape descriptors is to fuse them. In this paper, we propose a new 3D matching and retrieval approach based on a fully unsupervised fusion of curvature and geometric diffusion descriptors. In fact, to improve retrieval precision, we use two descriptors based on local and global features extracted from a shape, and automatically combine these features using a fusion method called Product rule. The Product rule combines values assigned to vertices by the two descriptors. This fusion rule gives better results compared to other well-known fusion schemes such as Max, Min and Linear rules. The proposed approach improves considerably the retrieval precision even with pose changes. This is shown through the retrieval results obtained on several popular 3D shape benchmarks.
The interest shown by some community of researchers to autonomous drones or UAVs (Unmanned Aerial Vehicles) has increased with the advent of wireless communication networks. These networks allow UAVs to cooperate more efficiently in an ad hoc manner in order to achieve specific tasks in specific environments. To do so, each drone navigates autonomously while staying connected with other nodes in its group via radio links. This connectivity can deliberately be maintained for a while constraining the mobility of the drones. This will be suitable for the drones involved in a given path of a given transmission between a source and a destination. This constraint could be removed at the end of the transmission process and the mobility of each concerned drone becomes again independent from the others. In this work, we have proposed a bio-inspired routing protocol for UAVs called BR- AODV. The protocol takes advantage of a well known ad hoc routing protocol for on-demand route computation, and the Boids of Reynolds mechanism for connectivity and route maintaining while data is being transmitted. The performances of BR-AODV were evaluated and compared to those of classical AODV routing protocol and the results show that BR-AODV outperforms AODV in terms of delay, throughput and packet loss.
The interest shown by some community of researchers to autonomous drones or UAVs (Unmanned Aerial Vehicles) has increased with the advent of wireless communication networks. These networks allow UAVs to cooperate more efficiently in an ad hoc manner in order to achieve specific tasks in specific environments. To do so, each drone navigates autonomously while staying connected with other nodes in its group via radio links. This connectivity can deliberately be maintained for a while constraining the mobility of the drones. This will be suitable for the drones involved in a given path of a given transmission between a source and a destination. This constraint could be removed at the end of the transmission process and the mobility of each concerned drone becomes again independent from the others. In this work, we have proposed a bio-inspired routing protocol for UAVs called BR- AODV. The protocol takes advantage of a well known ad hoc routing protocol for on-demand route computation, and the Boids of Reynolds mechanism for connectivity and route maintaining while data is being transmitted. The performances of BR-AODV were evaluated and compared to those of classical AODV routing protocol and the results show that BR-AODV outperforms AODV in terms of delay, throughput and packet loss.
The aim of this paper is to examine a premature breakage of two compression plates for fixing broken bones with different patients for the period of their recovery. Each compression plate's breakage can induce grave consequences such as a new surgery, unexpected undesired complications and a prolonged healing time. The investigation of the compression plate breakage causes required an examination of the chemical composition and steel hardness, metallographic examination as well as that of the compression plate breakage surface by means of macroscopic and microscopic observations using microscope. On the origin of the results it can be established that the breakage was caused by high static load.
In spite the fact that Emily Elizabeth Dickinson lived during the 19thcentury Amherst among conservative community that gave less chance to female voice to gain a share in social and political life, she paved the way for the coming female thinkers to obtain more freedom of thought and expression. In other words, since she was convient that ‘Abdiction of Belief makes the Behaviour Small’ she undercut social conventions and moved under gradual shift from Orthodox Trinitarianism into new thoughts of liberalism. However, in good deal of her work, she still pertains to religious conservatism in wider sense than Amhest Church had been dectated.
Boron Phosphorus and Arsenic atoms used as doping for the polysilicon gate they can cause crucial problem of metal-oxide- Semiconductor (MOS) devices. In this work, in order to improve the electrical parameters of MOS transistor such as, threshold voltage and flat band voltage, we have simulated Boron, Phosphorus and Arsenic Diffusion profiles in three dimensions in a polysilicon layer using the simulator Athena based on Pearson type IV models. We have study profile of dopant in 3-D before and after thermal annealing in a highly doped polysilicon film. The model takes into account the distribution of vacancy mechanism by associating parameters and effects related to high concentrations, such as the formation of clusters by trapping and exceeding the solid solubility limit. Based on the literature the model is solved under windows seven, following a well-defined algorithm. also We have studied the influence of some parameters, like concentration, temperature, time, dose and energy on implantation profiles of Boron, Phosphorus and Arsenic. The results have analyzed and discussed in order to extract depth of doping (Phosphorus Arsenic and boron) and it has been able to optimize the silicon oxide thickness, to reduce the penetration of doping. This theoretical analyses show that technological conditions preserve the quality of the silicon oxide structure studied. The model is validated with the help of simulation results obtained from Matlab
The purpose of this paper is to improve data gathering from oilfield wells (GEA: Gassi El Agreb oilfield case study) by the integration of deported autonomous flowmeters installed on these wells in a DCS control system. Indeed, oil and gas industry is very much linked to technological progress of electronics and informatics; this has allowed a considerable evolution of production processes control. This evolution is translated by process control techniques change: from pneumatic systems to electronic systems, from analog to digital ones and then from centralized control to distributed one which we commonly call DCS (Distributed Control System).
