ICMLT

The CO2-brine interfacial tension (IFT) is key to designing the CO2 injection into underground saline aquifers in order to reduce CO2 and slow global temperature increase. Laboratory measurement of CO2-brine IFT is usually time-consuming and requires an ...

Linear classification has demonstrated success in many areas of applications. Modern algorithms for linear classification can train reasonably good models while going through the data in only tens of rounds. However, large data often does not fit in the ...

With the advance of Bitcoin technology, money laundering has been incentivised as a den of Bitcoin blockchain, in which the user's identity is hidden behind a pseudonym known as address. Although this trait permits concealing in the plain sight, the ...

In this paper, we describe an intelligent teaching assistant system using deep learning technologies. A few works had been done on building intelligent assistant for teachers before and our job is novel. The main challenge in this area is the ...

Graph networks are extensively used as an essential framework to analyse the interconnections between transactions and capture illicit behaviour in Bitcoin blockchain. Due to the complexity of Bitcoin transaction graph, the prediction of illicit ...

In recent years, we have become increasingly dependent on smart devices. Android is an operating system mainly used on mobile devices, where hundreds of millions of users can download various apps through many application stores. Under these ...

Thermal management system of data center continuously face a lot of challenges, because data center industry has seen a boom growth in power density. In this paper we proposed the Tilted Active Tiles (TATs) to improve the local cold air supply and ...

Most existing machine learning (ML) based solutions for anomaly detection in sensory data rely on carefully hand-crafted features. This approach has a fundamental limitation since it is often application-specific and requires considerable human effort ...

Recently, network attacks with complex types have occurred more frequently than before, and traditional detection algorithms cannot meet current needs. For this reason, an intrusion detection method based on Attention- Long Short Term Memory (LSTM) ...

Nowadays, agriculture around the world is facing severe challenges because of global warming and rapid population growth. In order to maximize the agricultural production and minimize the environmental degradation at the same time, careful land-use ...

Convolutional neural networks (CNNs) have made great success in computer vision tasks. But the computational complexity of CNNs is huge, which makes CNNs run slowly especially when computational resources are limited. In this paper, we propose a scheme ...

In this paper, artificial neural network(ANN) are introduced to data assimilation for WRF model, which is a mesoscale complex model. A particle swarm optimization optimized Multilayer Perception data assimilation (MLP-PSO-DA) model is proposed in order ...

With the availability of large-scale data set of X-ray images and development of CNNs(Convolutional Neural Networks), using CNNs assist diagnose become more and more popular. But training CNNs using global image may be affected by the excessive ...

The emergence of deep neural networks and full convolutional neural networks has brought great progress to salient object detection. In this paper, we propose a new type of deep full convolutional neural network structure, named top-down feature ...

Face anti-spoofing technology is indispensable for the face recognition system, which is vulnerable to malicious spoofing attacks such as printed attacks and replayed video attacks. In this paper, we focus on more challenging cross-database ...

Intent detection and slot filling are the two main tasks in natural language understanding module in goal oriented conversational agents. Models which optimize these two objectives simultaneously within a single network (joint models) have proven ...

Ulaanbaatar is considered as one of the most congested cities in the world. The public transport system of a city is a great indicator of its relative level of development. This article applies a combined model composed of the Analytic Hierarchy Process ...

This paper introduces the concept of computer war chess system and the JTLS war chess system of the U.S. Army. Starting from the application of the current war chess system in the military demand, it puts forward the concept of the war chess simulation ...

With the progress and development of technology, virtual machine gradually appears in people's vision and is widely used in various fields. Based on the analysis of a series of problems in Quartermaster training, this paper puts forward a comprehensive ...

Customer churn prediction is a pivotal issue in business marketing. Many researches have been pursuing more efficient features and techniques for it. Rapid growth of mobile Internet devices has generated large amounts of customer trajectory data, which ...

Energy-harvesting IoT nodes need to conserve their energy to remain operating without interrupting. By predicting input power supply, IoT nodes could appropriately schedule or adjust data transmission interval to match available energy for lasting ...

The success of blockchain technology makes more and more applications begin to use distributed anonymous network. However, the decentralized, anonymous, and distributed features of the distributed anonymous network also create conditions for many ...

Text classification is an elementary task in Natural Language Processing (NLP). Existing methods, such as Long Short-Term Memory Networks (LSTM) and Attention Mechanism have recently achieved strong performance on multiple NLP related tasks. However, in ...

The exponential increase in the number of malware stems from the fact that attackers often create malware variants with automated tools. And automated tools generally tend to reuse similar function modules. It is essential, therefore, that security ...