ICNCC

With the development of artificial intelligence, the project of using deep learning for molecular property prediction has gained much attention. The current widely used molecular description methods, such as Morgan molecular fingerprinting, need further ...

The rapid development of the information age leads to the mass production and frequent transmission of data, which is difficult to deal with by human alone. With the rise and development of artificial intelligence, the use of data is becoming more ...

Douban has become one of the most popular Chinese film review platforms and has been attacked by various spammers. In our research based on real data from Douban, we found that many spammers spontaneously form different groups, which have different ...

Existing recommendation systems mainly focus on the improvement of accuracy but neglect to involve non-popular items, which leads to the unfairness problem of recommendation results. More specifically, the low exposure rate of non-popular items impairs ...

Automatic Term Extraction is a common upstream task of both natural language and programming language processing tasks. However, most existing domain-specific term extraction methods are designed for natural language, and do not satisfy demand for ...

This paper examines the knowledge capture, play liberation of application-based gambling amongst youth in the U.K. As a growing social phenomenon that is becoming an issue of concern because of the addictive effects on younger consumers, particularly ...

This paper proposed a Internet of things (IoT) malware classification method, which uses a novel visual local feature based on sections of the malware binary. This method filter binary file section of malware samples, then divides the section contents ...

The complexity of human cerebral cortex has important clinical value for the prediction, diagnosis and prevention of certain diseases. In this paper, we mainly used edge extraction and curve fitting to assess the cortical complexity by calculating the ...

The I/Q imbalance of modulator model leads to individual differences in gain and phase mismatch. In this paper, a new method of specific emitter identification is proposed based on these differences. In the method, I/Q signals is decomposed by I/Q ...

Brain image registration is a key part of brain image processing, so the research of brain image registration technology has important value. This paper proposes a brain MR image registration algorithm based on an improved convolutional neural network (...

Chromosome karyotype analysis is an important technique in cytogenetics and plays an important role in modern medical system. Chromosome karyotype analysis is to observe the physical images of chromosomes under a microscope with a high-definition camera,...

In this paper, An end-to-end, pixels-to-pixels deep learning method of signal extraction and parameters estimation for spectrum sensing was developed. A novel spectrum density map was designed for counting signal number at each time, computing signal-to-...

Cognitive radio networks (CRNs) improve spectrum resource utilization rate by providing dynamic spectrum access for second users (SUs) when the spectrum is used by primary users (PUs). When multiple SUs exist in a CRN at the same time, spectrum handoff ...

The particle filter based on particle swarm optimization algorithm has low precision and is easy to fall into local optimization, which is difficult to meet the needs of target tracking. In this paper, a new particle swarm optimization particle filter ...

To improve spectrum utilization efficiency and flexibility in diverse application scenarios, several new multicarrier modulation techniques have been proposed in recent years, and thus accurate recognition of various multicarrier waveforms is critical ...

With the exponential explosion of radio services, spectrum scarcity has become a thorny issue in wireless communications. Cognitive radio networks (CRNs) emerge as the times require. However, choosing the best channel for spectrum handoff becomes a ...

Federated learning protocol provides an applicable solution for large-scale deep learning in distributed scenario. However, existing federated learning system is vulnerable to many attacks and threats. This paper proposes a universal verification ...

Task scheduling is one of the most fundamental technologies in a cloud computing environment. The essence of resource scheduling is to determine the appropriate executor and provide the on-demand resources to meet the task overhead. Due to the ...

Enumerating all routing paths among Autonomous Systems (ASes) at an Internet-scale is an intractable problem. The Border Gateway Protocol (BGP) is the standard exterior gateway protocol through which ASes exchange reachability information. Building an ...

Traditional routing algorithms select the path based on the cost, hop, or other network-related metrics. However, with cloud computing and edge computing development, it is essential to develop a computing-aware routing mechanism to distribute the task ...

Many studies have focused on the impact of Media Access Control (MAC) layer protocols on wireless sensor networks (WSN). In realistic Internet of Things (IoT) scenarios, multiple protocols are used to ensure the efficient operation of the network. IP ...

Smart energy station is a new generation of energy hub infrastructure based on substation, which realizes the multi-station functions of substation, energy storage station, photovoltaic station, charging station and data center station. To improve the ...