The association between miRNA and disease has attracted more and more *** now,existing methods for identifying miRNA related disease mainly rely on top-ranked association model,which may not provide a full landscape o...
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The association between miRNA and disease has attracted more and more *** now,existing methods for identifying miRNA related disease mainly rely on top-ranked association model,which may not provide a full landscape of association between miRNA and *** there is strong need of new computational method to identify the associations from miRNA group *** this paper,we proposed a framework,MDA-TOEPGA,to identify miRNAdisease association based on two-objective evolutionary programming genetic algorithm,which identifies latent miRNAdisease associations from the view of functional *** understand the miRNA functional module in diseases,the case study is *** have been compared MDA-TOEPGA with several state-of-the-art functional module *** results showed that our method cannot only outperform classical algorithms,such as K-means,IK-means,MCODE,HC-PIN,and ClusterONE,but can also achieve an ideal overall performance in terms of a composite score consisting of f1,Sensitivity,and ***,our study showed that MDA-TOEPGA is a promising method to investigate miRNA-disease association from the landscapes of functional module.
Identifying associations between microRNAs(miRNAs)and diseases is very important to understand the occurrence and development of human ***,these existing methods suffer from the following limitation:first,some disease...
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Identifying associations between microRNAs(miRNAs)and diseases is very important to understand the occurrence and development of human ***,these existing methods suffer from the following limitation:first,some disease-related miRNAs are obtained from the miRNA functional similarity networks consisting of heterogeneous data sources,i.e.,disease similarity,protein interaction network,gene ***,little approaches infer disease-related miRNAs depending on the network topological features without the functional similarity of *** this paper,we develop a novel model of Integrating Network Topology Similarity and MicroRNA Function Similarity(INTS-MFS).The integrated miRNA similarities are calculated based on miRNA functional similarity and network topological ***-MFS obtained AUC of 0.872 based on five-fold cross-validation and was applied to three common human diseases in case *** a results,30 out of top 30 predicted Prostatic Neoplasm-related miRNAs were included in the two databases of dbDEMC and PhenomiR2.0.29 out of top 30 predicted Lung Neoplasm-related miRNAs and Breast Neoplasm-related miRNAs were included in dbDEMC,PhenomiR2.0 and experimental ***,INTS-MFS found unknown association with hsa-mir-371a in breast cancer and lung cancer,which have not been *** provides biologists new clues for diagnosing breast and lung cancer.
The distributed clustering method is widely used to extend network lifetime in traditional wireless sensor networks. However, it is difficult to achieve the idea performance of the whole network, such as transmission ...
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The distributed clustering method is widely used to extend network lifetime in traditional wireless sensor networks. However, it is difficult to achieve the idea performance of the whole network, such as transmission rate, energy consumption, and control overhead, neglecting the global stability of the network. To tackle this problem, a centralized mobility-based clustering (CMBC) protocol is proposed in the software defined sensor network. The method of CMBC mainly consists of two aspects: first, CMBC clusters the nodes with the connection time between the mobile nodes (i.e., noncluster head nodes, non-CH) and the cluster head (CH) and establishes stable topological structures between the non-CHs and the CH;second, when emergencies occur, the centralization management control center sends the configuration files to replace the CH. Compared to the distributed network of MBC, WCRA and IMP-MECA protocol, the proposed method can be applied in scenarios with high-speed mobile nodes to improve the network performance in terms of transmission successful rate, average power consumption, and average control overhead.
Targeting mobile vehicle communications, Dedicated Short Range Communications (DSRC) wireless technology has been widely used in Vehicular Ad-hoc Networks (VANETs). Though DSRC can provide reliable and low-latency com...
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Targeting mobile vehicle communications, Dedicated Short Range Communications (DSRC) wireless technology has been widely used in Vehicular Ad-hoc Networks (VANETs). Though DSRC can provide reliable and low-latency communications for various VANET applications, the multi-channel operations standardized by IEEE 802.11p suffer from high contention on control channel, especially in dense traffic scenarios. Meanwhile, as a conventional wireless technology for VANET communications, WiFi is often underutilized when a vehicle is on road. In this paper, we propose an innovative approach that can effectively offload control frames from DSRC to WiFi when the control traffic is dense, resulting in significantly improved throughput of control traffic (about 28.7% under moderate traffic density in simulation).
It is challenging to find an effective license plate detection and recognition method due to the different conditions during the image acquisition phase. This paper aims to develop a new accurate and efficient method ...
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Spectral clustering is one of the most popular clustering approaches. Despite its good performance and strong theoretical supports, it is limited to high complexity of the graph Laplacian similarity matrix constructio...
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Featured with high bandwidth, high reliability, and native IP compatibility, WiFi has been recommended for a wide range of Internet-of-Things (IoT) applications. However, WiFi is inherently energy-hungry and it may im...
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Featured with high bandwidth, high reliability, and native IP compatibility, WiFi has been recommended for a wide range of Internet-of-Things (IoT) applications. However, WiFi is inherently energy-hungry and it may impose high energy consumption on not only IoT devices but also gateways. To reduce gateway's WiFi energy consumption, many energy-efficient solutions for WiFi tethering services can be applied. However, these solutions mainly target the energy optimization of downlink data traffic in WLANs, and they are not suitable for the uplink data traffic of delivering massive IoT data from device to gateway (D2G), which is more common in IoT. When a gateway is powered by batteries, the high energy consumption caused by D2G communications may deplete the gateway quickly and renders the whole system dysfunctional as a result. Toward achieving energy-efficient D2G communications, we propose an innovative Green IoT Gateway (GIG) scheme, which aims at minimizing gateway energy consumption while ensuring the specific delay requirements of devices via cross-interface collaboration. Through utilizing the coexisting low-power ZigBee radios, GIG dynamically schedules the wakeup behaviors of high-power WiFi radios for energy-efficient and delay-bounded D2G communications. GIG has been implemented and evaluated in a prototype system, and the experiment results show that, under the moderate uplink data traffic and delay requirements, the energy consumption of GIG is 38.5% and 12.7% lower than those of a state-of-the-art WiFi tethering scheme and a simple version of the GIG scheme, respectively. Moreover, a great reduction of energy consumption at the device side can also be observed.
Proteins play a vital role in various biological processes and achieve their functions through protein–protein interactions (PPIs). Thus, accurate identification of PPI sites is essential. Traditional biological meth...
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Predicting associations between microRNAs (miRNAs) and diseases from the viewpoint of function modules has become increasingly popular However, existing methods obtained the relations between diseases and miRNAs only ...
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Predicting associations between microRNAs (miRNAs) and diseases from the viewpoint of function modules has become increasingly popular However, existing methods obtained the relations between diseases and miRNAs only through the construction of similarity networks and neglected the complex network characteristic. In this paper, a new method named combining mirNA function similarities and network topology similarities based on module identification in networks (ComSim-MINE) was developed. Combined similarity is calculated from the harmonic mean between miRNA function similarities aid network topology similarities. Experimental results showed that ComSim-MINE can compete with several state-of-the-art weighted function module algorithms, such as ClusterONE, MCODE, NEMO, and SPICi, and achieved the satisfactory results in terms of the composite score of F-measure, sensitivity, and accuracy based on the generated miRNA function interaction network. From the analysis of case studies, some new findings obtained from our proposed method provide clinicians new clues for epidemic diseases, such as COVID-19.
Finding an effective license plate localization (LPL) method is challenging owing to different conditions during the image acquisition phase. Most existing methods do not consider various low-quality image conditions ...
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Finding an effective license plate localization (LPL) method is challenging owing to different conditions during the image acquisition phase. Most existing methods do not consider various low-quality image conditions that exist in real-world situations. Low-quality image conditions mean that an image can have low resolution, plate imperfection effects, variable illumination environments or background objects similar to the license plate (LP). To improve the anti-interference ability and the speed performance of algorithm, this study aims to develop a parallel partial enhancement method based on color differences that demonstrates improved localization performance for blue-white LP images under low-quality conditions. A novel color difference model is exploited to enhance LP areas and filter non-LP areas. Blue-white color ratio and projection analysis are performed to select the exact LP area from the candidates. Moreover, this study develops a parallel version based on a multicore CPU for real-time processing for industrial applications. An image database including 395 low-quality car images captured from various scenes under different conditions is tested for the performance evaluation. The extensive experiments show the effectiveness and efficiency of the proposed approach.
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