Computer vision-based identification of different tissue categories in histological images is a critical application of the computer-assisted diagnosis (CAD). Computer-assisted diagnosis systems... Show More

Computer vision-based identification of different tissue categories in histological images is a critical application of the computer-assisted diagnosis (CAD). Computer-assisted diagnosis systems support to reduce the cost and increase the efficiency of this process. Traditional image classification approaches depend on feature extraction methods designed for a specific problem based on domain information. Deep learning approaches are becoming important alternatives with advance of machine learning technologies to overcome the numerous difficulties of the feature-based approaches. A method for the classification of histological images of human colorectal cancer containing seven different types of tissue using convolutional neural network (CNN) is proposed in this article. The method is evaluated using four different colour models in absence and presence of Gaussian noise. The highest classification accuracies are achieved with HVI colour model, which is 95.8% in nonexistence and 78.5% in existence of noise respectively.

In order to solve the problems occurring in the current donation systems, the methodologies of blockchain include decentralized data storage, transaction hash, digital signature, blocks connection... Show More

In order to solve the problems occurring in the current donation systems, the methodologies of blockchain include decentralized data storage, transaction hash, digital signature, blocks connection within the chain are adopted to the donation model, called blockchain donation model (BDM). In BDM, all donation transactions are recorded in detail and stored permanently; they are not allowed to change, modify, or delete. In addition, donors could indicate the specific groups for donating directly because of the peer-to-peer transmission method. All the information is sealed through the secure mechanism; only donors and donees could decrypt it with their own keys. BDM records transaction flows starting from receiving to spending the donation in detail. BDM is not only a place for listing details of donations but also a secured transaction storage. The blocks are connected together with a strong chain which is maintained by all nodes in the blockchain network. Thus, BDM is a platform dealing with the donation issue under a well secure mechanism, no intermediaries, and a permanent storage.

The process model matching is a critical step in many business process management activities. Process model matching consists of finding correspondences between activities of process models. This... Show More

The process model matching is a critical step in many business process management activities. Process model matching consists of finding correspondences between activities of process models. This article presents a method for matching process model. The proposed method matches (i.e., aligns) two process models in three sequential steps. First, activities in the two process models are extracted. Second, the extracted activities are expanded using synonyms, hypernyms, and hyponyms of its composing words. These synonyms, hypernyms, and hyponyms are extracted from the WordNet thesaurus. Third, the expanded activities are compared using the Monge-Elkan similarity metric to detect matches. An empirical study was conducted on three well known datasets to evaluate the proposed method. The results of the experiment showed that the proposed method has the potential to match business process models in an effective manner when step two of the method is based on synonyms and hypernyms.

Power consumption mainly takes place in three stages: processing the data, receiving the data, and transmitting the data. Power consumption in data transmitting is one of the most important... Show More

Power consumption mainly takes place in three stages: processing the data, receiving the data, and transmitting the data. Power consumption in data transmitting is one of the most important phenomena in wireless sensor networks (WSNs). In this article, authors analyze the power transmission in three scenarios with 100 and 500 nodes for 100 and 1000 sq. meters of area respectively and design a network which should be more efficient in power saving. Results analysis section presents different data aggregation techniques and their impact on the power transmission in WSNs. Three different scenarios have been used during simulation of network in Matlab. After that, the authors find that the proposed approach has outperformed in the first two scenarios. However, in the third scenario, results are partially better as compared to the existing approaches (tree-based, cluster-based, chain-based, and grid-based). The proposed approach, PLBDA, is 10.30%, 18.55%, 37.11%, and 55.67% better for transmission power save in comparison to tree-based, cluster-based, grid-based, and chain-based approaches respectively.