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Optimal Building Frame Column Design Based on the Genetic Algorithm
Get PDFBuilding structure is like the skeleton of the building, it bears the effects of various forces and forms a supporting system, which is the material basis on which the building depends. Hence building structure design is a vital part in architecture design, architects often explore novel applications of their technologies for building structure innovation. However, such searches relied on experiences, expertise or gut feeling. In this paper, a new design method for the optimal building frame column design based on the genetic algorithm is proposed. First of all, in order to construct the optimal model of the building frame column, building units are divided into three categories in general: building bottom, main building and building roof. Secondly, the genetic algorithm is introduced to optimize the building frame column. In the meantime, a PGA-Skeleton based concurrent genetic algorithm design plan is proposed to improve the optimization efficiency of the genetic algorithm. Finally, effectiveness of the mentioned algorithm is verified through the simulation experiment
Localization Based Evolutionary Routing (LOBER) for Efficient Aggregation in Wireless Multimedia Sensor Networks
Get PDFEfficient aggregation in wireless sensor nodes helps reduce network traffic and reduce energy consumption. The objective of this work Localization Based Evolutionary Routing (LOBER) is to achieve global optimization for aggregation and WMSN lifetime. Improved localization is achieved by a novel Centroid Based Octant Localization (CBOL) technique considering an arbitrary hexagonal region. Geometric principles of hexagon are used to locate the unknown nodes in the centroid positions of partitioned regions. Flower pollination algorithm, a meta heuristic evolutionary algorithm that is extensively applied in solving real life, complex and nonlinear optimization problems in engineering and industry is modified as Enhanced Flower Pollination Algorithm (EFPA) to fit into WMSN and enhance routing mechanism and ensure efficiency in data aggregation. The system is simulated using MATLAB and found to have a considerable improvement in the optimization process
An Adaptive Superpixel Tracker Using Multiple Features
Get PDFVisual tracking is a challenging issue in the field of computer vision due to the objects’ intricate appearance variation. To adapt the change of the appearance, multiple channel features which could provide more information are used. However, the low level feature could not represent the structure of the object. In this paper, a superpixel-based adaptive tracking algorithm by using color histogram and haar-like feature is proposed, whose feature is classified into the middle level. Based on the superpixel representation of video frames, the haar-like feature is extracted at the superpixel level as the local feature, and the color histogram feature is applied with the combination of background subtraction method as the frame feature. Then, local features are clustered and weighted according to the target label and the location center. Superpixel-based appearance model is measured by using the sum of the voting map, and the candidate with the highest score is selected as the tracking result. Finally, an efficient template updating scheme is introduced to obtain the robust results and improve the computational efficiency. The proposed algorithm is evaluated on eight challenging video sequences and experimental results demonstrate that the proposed method can get better performance on occlusion, illumination variation and transformation
GFCache: A Greedy Failure Cache Considering Failure Recency and Failure Frequency for an Erasure-Coded Storage System
Get PDFIn the big data era, data unavailability, either temporary or permanent, becomes a normal occurrence on a daily basis. Unlike the permanent data failure, which is fixed through a background job, temporarily unavailable data is recovered on-the-fly to serve the ongoing read request. However, those newly revived data is discarded after serving the request, due to the assumption that data experiencing temporary failures could come back alive later. Such disposal of failure data prevents the sharing of failure information among clients, and leads to many unnecessary data recovery processes, (e.g. caused by either recurring unavailability of a data or multiple data failures in one stripe), thereby straining system performance.
To this end, this paper proposes GFCache to cache corrupted data for the dual purposes of failure information sharing and eliminating unnecessary data recovery processes. GFCache employs a greedy caching approach of opportunism to promote not only the failed data, but also sequential failure-likely data in the same stripe. Additionally, GFCache includes a FARC (Failure ARC) catch replacement algorithm, which features a balanced consideration of failure recency, frequency to accommodate data corruption with good hit ratio. The stored data in GFCache is able to support fast read of the normal data access. Furthermore, since GFCache is a generic failure cache, it can be used anywhere erasure coding is deployed with any specific coding schemes and parameters. Evaluations show that GFCache achieves good hit ratio with our sophisticated caching algorithm and manages to significantly boost system performance by reducing unnecessary data recoveries with vulnerable data in the cache
High Capacity Data Hiding in Encrypted Image Based on Compressive Sensing for Nonequivalent Resources
Get PDFTo fulfill the requirements of data security in environments with nonequivalent resources, a high capacity data hiding scheme in encrypted image based on compressive sensing (CS) is proposed by fully utilizing the adaptability of CS to nonequivalent resources. The original image is divided into two parts: one part is encrypted with traditional stream cipher; the other part is turned to the prediction error and then encrypted based on CS to vacate room simultaneously. The collected non-image data is firstly encrypted with simple stream cipher. For data security management, the encrypted non-image data is then embedded into the encrypted image, and the scrambling operation is used to further improve security. Finally, the original image and non-image data can be separably recovered and extracted according to the request from the valid users with different access rights. Experimental results demonstrate that the proposed scheme outperforms other data hiding methods based on CS, and is more suitable for nonequivalent resources
Adaptive Median Filtering Algorithm Based on Divide and Conquer and Its Application in CAPTCHA Recognition
Get PDFAs the first barrier to protect cyberspace, the CAPTCHA has made significant contributions to maintaining Internet security and preventing malicious attacks. By researching the CAPTCHA, we can find its vulnerability and improve the security of CAPTCHA. Recently, many studies have shown that improving the image preprocessing effect of the CAPTCHA, which can achieve a better recognition rate by the state-of-the-art machine learning algorithms. There are many kinds of noise and distortion in the CAPTCHA images of this experiment. We propose an adaptive median filtering algorithm based on divide and conquer in this paper. Firstly, the filtering window data quickly sorted by the data correlation, which can greatly improve the filtering efficiency. Secondly, the size of the filtering window is adaptively adjusted according to the noise density. As demonstrated in the experimental results, the proposed scheme can achieve superior performance compared with the conventional median filter. The algorithm can not only effectively detect the noise and remove it, but also has a good effect in preservation details. Therefore, this algorithm can be one of the most strong tools for various CAPTCHA image recognition and related applications
An Improved End-to-End Memory Network for QA Tasks
Get PDFAt present, End-to-End trainable Memory Networks (MemN2N) has proven to be promising in many deep learning fields, especially on simple natural language-based reasoning question and answer (QA) tasks. However, when solving some subtasks such as basic induction, path finding or time reasoning tasks, it remains challenging because of limited ability to learn useful information between memory and query. In this paper, we propose a novel gated linear units (GLU) and local-attention based end-to-end memory networks (MemN2N-GL) motivated by the success of attention mechanism theory in the field of neural machine translation, it shows an improved possibility to develop the ability of capturing complex memory-query relations and works better on some subtasks. It is an improved end-to-end memory network for QA tasks. We demonstrate the effectiveness of these approaches on the 20 bAbI dataset which includes 20 challenging tasks, without the use of any domain knowledge. Our project is open source on github4
The Effect of the Fin Length on the Solidification Process in a Rectangular Enclosure with Internal Fins
Get PDFThe aim of the proposed work is to study the solidification process within a rectangular enclosure provided with three internal rectangular fins attached to the left vertical wall of the cavity. This latest is filled with a phase change material (PCM), initially liquid, at a temperature above its melting temperature. The solidification process was initiated by cooling the left wall and fins to a temperature lower than the melting temperature. In order to study and examine the thermal behavior and thermal performance of the proposed system, a mathematical model, based on the conservation equations of mass, momentum and energy was developed. The governing equations and their associated boundary and initial conditions were next adimensionalyzed. Therefore, several controlling parameters were appeared. The volume control method was used to discretize the equations. The resulting algebraic equations were solved iteratively. Numerical investigations were carried out to study and examine the effect of the dimensionless fin length on the hydrodynamic and thermal fields of the flow, the dimensionless heat flux, the solidified mass fraction and the dimensionless time of complete solidification
A Correct Smoothed Particle Method to Model Structure-Ice Interaction
Get PDFThis paper studies the effect of ice resistance on the icebreaking capacity and speed of an icebreaking vessel. We combine an improved Correct Smoothed Particle Method (CSPM) with a material low-speed collision fracture model to numerically simulate the continuous icebreaking and rolling process of crushed. Using this model, we investigate the icebreaking resistance and immersion resistance during the icebreaking process, taking into account the fluid (water) as the elastic boundary support and the fluid-solid coupling interaction. We compare the icebreaking resistance and broken ice fracture shapes obtained by the numerical calculation with the theoretical analytical results, and thus validate the improved CSPM method. Further, we compare the immersion resistance results from our simulation against that from Puntigliano [Puntigliano, Hamburgische Schiffbau-Versuchsanstalt GmbH (1995)], and demonstrate that the proposed method can accurately predict ice resistance
Simulation of Damage Evolution and Study of Multi-Fatigue Source Fracture of Steel Wire in Bridge Cables under the Action of Pre-Corrosion and Fatigue
Get PDFA numerical simulation method for the damage evolution of high-strength steel wire in a bridge cable under the action of pre-corrosion and fatigue is presented in this paper. Based on pitting accelerated crack nucleation theory in combination with continuum mechanics, cellular automata technology (CA) and finite element (FE) analysis, the damage evolution process of steel wire under pre-corrosion and fatigue is simulated. This method automatically generates a high-strength steel wire model with initial random pitting defects, and on the basis of this model, the fatigue damage evolution process is simulated; thus, the fatigue life and fatigue performance of the corroded steel wire can be evaluated. A comparison of the numerical simulation results with the experimental results shows that this method has strong reliability and practicability in predicting the fatigue life of corroded steel wire and simulating the damage evolution process. Based on the method proposed in this paper, the fatigue life of steel wires with different degrees of corrosion under the action of different stress levels is predicted. The results show that as the degree of corrosion increases, the fatigue properties of steel wire gradually decrease, and the influence of existing pitting corrosion on fatigue life is far greater than that on mass loss.Stress concentration is the main cause of fatigue life of corroded steel wire in advance attenuation. In addition, the fracture process of steel wire with multi-fatigue sources and the effect of the number and distribution of pits on the fatigue life of steel wire are studied. The results show that, compared with a stepped pitting distribution, a planar pitting distribution has a greater impact on the damage evolution process. The fatigue life of steel wire is positively correlated with the number of pits and the angle and distance between pits