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Article
Open AccessIn vivo evaluation of CD38 and CD138 as targets for nanoparticle-based drug delivery in multiple myeloma
Drug-loaded nanoparticles have established their benefits in the fight against multiple myeloma; however, ligand-targeted nanomedicine has yet to successfully translate to the clinic due to insufficient effica...
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Chapter and Conference Paper
Research on the English Teaching Resource Library Management System Based on the Computer Technology
With the continuous development of the computer network technology and the network education, colleges and universities have gradually carried out the construction of the college English multimedia network tea...
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Article
Open AccessDeath effector domain-containing protein induces vulnerability to cell cycle inhibition in triple-negative breast cancer
Lacking targetable molecular drivers, triple-negative breast cancer (TNBC) is the most clinically challenging subtype of breast cancer. In this study, we reveal that Death Effector Domain-containing DNA-bindin...
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Chapter and Conference Paper
Correction to: Efficient Processing of Convolutional Neural Networks on SW26010
In the originally published version of this chapter, in section 2.2 and 3.3, in the second to last sentence “swDGEMM” was corrected to “swDNN”. Furthermore, in the last sentence of 3.3, “16” was corrected to “...
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Chapter and Conference Paper
An Empirical Study and Analysis of the Performance Model for the Foreign Language Learning
In the definition of the learning performance, it can be seen that the definitions of the learning performance in China and the foreign countries can be attributed to two aspects. One is from the learning effi...
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Chapter and Conference Paper
Efficient Processing of Convolutional Neural Networks on SW26010
Artificial intelligence has developed rapidly in recent years. Deep neural networks are the basis of many artificial intelligence applications. How to accelerate the computational processing of deep neural net...
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Chapter and Conference Paper
SATB-Nets: Training Deep Neural Networks with Segmented Asymmetric Ternary and Binary Weights
Deep convolutional neural networks (CNNs) are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources efficiently. To address th...
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Chapter and Conference Paper
Three-Means Ternary Quantization
Deep Convolution Neural Networks (DCNNs) have achieved state-of-the-art results in a wide range of tasks, especially in image recognition and object detection. However, millions of parameters make it difficul...
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Chapter and Conference Paper
Fissionable Deep Neural Network
Model combination nearly always improves the performance of machine learning methods. Averaging the predictions of multi-model further decreases the error rate. In order to obtain multi high quality models mor...
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Chapter and Conference Paper
Accelerate K-means Algorithm by Using GPU in the Hadoop Framework
Cluster analysis, such as k-means algorithm, plays a critical role in data mining area, but now it is facing the computational challenge due to the continuously increasing data volume. Parallel computing becom...
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Chapter and Conference Paper
Priority-Based Live Migration of Virtual Machine
Live migration of Virtual Machines (VMs) has been a powerful tool to facilitate system maintenance, load balancing, fault tolerance, and power saving. In this paper, we describe the design and implementation o...
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Chapter and Conference Paper
The Impact of Cache on Memory Test
In order to ensure the reliability of embedded systems, test of the embedded system memory is particularly important. Among the different types of algorithms proposed for testing memories, March test is the mo...
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Chapter and Conference Paper
Self-organization Data Gathering for Wireless Sensor Networks
Sensor networks have attracted much attention in the recent years for its wide applications in biology, medicine, security and battlefield, etc. Data gathering is one of the most important operations in wirele...
