Recent Patents on Computer Science - Volume 12, Issue 3, 2019

Background: In making the deep neural network, activation functions play an important role. But the choice of activation functions also affects the network in term of optimization and to retrieve the better results. Several activation functions have been introduced in machine learning for many practical applications. But which activation function should use at hidden layer of deep neural networks was not identified. Objective: Th Read More

Background: This paper renders a classification and retrieval of image achievements in the search area of image retrieval, especially content-based image retrieval, an area that has been very active and successful in the past few years. Objective: Primarily the features extracted established on the bag of visual words (BOW) can be arranged by utilizing Scaling Invariant Feature Transform (SIFT) and developed K-M Read More

Background: The increased variability in production or procurement with respect to less increase of variability in demand or sales is considered as bullwhip effect. Bullwhip effect is considered as an encumbrance in optimization of supply chain as it causes inadequacy in the supply chain. Various operations and supply chain management consultants, managers and researchers are doing a rigorous study to find the causes behind t Read More

Background: The scaling up of the MANETs is an important criterion to consider since the nodes have to maintain the updated routing information. Generally, agents are deployed to balance the load. However, a single agent performance may not be satisfactory, if the network has a large set of nodes. Hence, the agents are necessary once the network size increases, but the launching of Agents in the network involves computati Read More

Background: Data integrity protection in Cloud Computing becomes very challenging since the user no longer has the possession of their own data. This makes cloud data storage security of critical importance. The users can resort to legal action against the cloud provider if the provider fails to maintain the integrity of the shared data, but it also raises a need to secure users' private data across the public cloud. Methods: In this Read More

Background: With the rapid development of the Internet, the number of web spam has increased dramatically in recent years, which has wasted search engine storage and computing power on a massive scale. To identify the web spam effectively, the content features, link features, hidden features and quality features of web page are integrated to establish the corresponding web spam identification index system. However Read More

Background: Active Queue Management (AQM) is a TCP congestion avoidance approach that predicts congestion before sources overwhelm the buffers of routers. Random Early Detection (RED) is an AQM strategy that keeps history of queue dynamics by estimating an average queue size parameter avg and drops packets when this average exceeds preset thresholds. The parameter configuration in RED is problematic and Read More

Background: In recent years, the cost is becoming one of the biggest obstacles for the effective operation of supply chain. It is increasingly urgent to minimize the cost and optimize the supply chain system. However, importance measures have been little used in it as a research focus in solving the optimization problems. Methods: With respect to the foregoing, this paper combines the reliability, importance measures and cost is Read More

Background: With an exponential increase in software online as well as offline, through each passing day, the task of digging out precise and relevant software components has become the need of the hour. There is no dearth of techniques used for the retrieval of software component from the available online and offline repositories in the conceptual as well as the empirical literature. However each of these techniques Read More

Background: Most of the common multi-user detection techniques have the shortcomings of large computation and slow operation. For Hopfield neural networks, there are some problems such as high-speed searching ability and parallel processing, but there are local convergence problems. Objective: The stochastic Hopfield neural network avoids local convergence by introducing noise into the state variables and then achiev Read More