Hao lu

Chinese Academy of Sciences | CAS · Institute of Automation

Traffic situation awareness and alerting assisted by adverse weather conditions contributes to improve traffic safety, disaster coping mechanisms, and route planning for government agencies, business sectors, and individual travelers. However, at the city level, the physical sensor-generated data are partly held by different transportation and mete...

Social sensors perceive the real world through social media and online web services, which have the advantages of low cost and large coverage over traditional physical sensors. In intelligent transportation researches, sensing and analyzing such social signals provide a new path to monitor, control and optimize transportation systems. However, curr...

The widespread communication of academic ideas and research achievements through literature and media has generated massive academic big data. Analyzing such academic big data and discovering knowledge can discover comprehensive and predictive academic intelligence and provide corresponding services, which are valuable for scholars, journals, insti...

Urban transportation systems are shaped by factors that include people, vehicles, roads, and the environment, forming a complex and giant system with dynamics, diversity, and uncertainty. Physical signal-driven intelligent transportation systems (ITSs) typically lack the ability to capture social behaviors or crowd willingness, and they achieve onl...

Nowadays, automation science and technology based on automatic control and information processing has become an essential impetus to productive forces and human life. So a comprehensive understanding of the latest research progress in this discipline is essential for its significant reference value to scholars and research institutions. In this pap...

Autonomous driving (AD), including single-vehicle intelligent AD and vehicle–infrastructure cooperative AD, has become a current research hot spot in academia and industry, and multi-sensor fusion is a fundamental task for AD system perception. However, the multi-sensor fusion process faces the problem of differences in the type and dimensionality...

Digital human in cyberspace can help provide humanized services in specific applications, such as question & answer systems, recommender systems, chatter robots, and intelligent assistants. While most researches focus on behavior analytics, few of them integrate the personality that is also a closely related factor. As a classic indicator for perso...

Frequent meteorological disasters present new challenges for decision-making in disaster response. As a timely and effective source of intelligent information, social media plays a vital role in detecting and monitoring these situations. Meteorological social briefings summarize valuable information from numerous social media posts, providing essen...

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (T-ITS) has become a leading international journal in the field of ITS since its first issue published in 2000. To obtain a structural overview as well as the evolution of T-ITS in the last decade (2010–2019), we present a comprehensive bibliometric analysis from multiple perspectives based on...

Current evidence indicates that the semantic representation of question and answer sentences is better generated by deep neural network-based sentence models than traditional methods in community answer selection tasks. In particular, as a widely recognized language model, the self-attention model computes the similarity between the specific word a...

The evolution of modern mobile terminals, social networks, and other intelligent services makes everyone become a ubiquitous information perceiver, producer, and propagator. Also known as “social sensor” and “social IoT”, these individuals and communities generate a huge volume of social signals, which has shown prominent value for mining. These un...

Natural disasters are public emergencies characterized by suddenness, universality, and nonconventionality. Realizing the early warning, monitoring, and intervention of natural disasters and their derivative social impacts is significant for reducing the disasters’ damage and benefits the maintenance of social stability. Social sensors are ubiquito...

Massive Open Online Courses (MOOCs) have received unprecedented attention, in which learners can obtain a large number of learning objects anytime. However, the increasing information overload on MOOCs inhibits the appropriate choice of learning objects by learners, leading to a low efficiency and high dropout rates in the learning process. E-learn...

With the frequent occurrence of extreme natural phenomena, news about meteorological disasters has increased. As a timely and effective social sensor, social networks have gradually become an important data source for the perception of extreme meteorological events. Meteorological briefing refers to screening valuable knowledge from massive data to...

University faculties generate a large amount of heterogeneous data in e-learning environments that online systems and toolkits have made widely available in all aspects of teaching and scientific researching activities. How to use the data efficiently and scientifically for faculty evaluations has recently become an important issue in university pe...

Tremendous academic information causes serious information overload problems while supporting scientific research. Scientific paper and citation recommendation systems have been developed to relieve this problem and work as a filter to furnish only relevant papers to researchers. Although previous studies have made comparative progress, this proble...

Compilation of users' avatars together with associated online activities strengthens the ability to discover user connections which focuses on understanding users online behaviours. This paper made an initial attempt to identify special type of SNS users by incorporating users avatar information, which proposes a multi-modal user profiling method t...

[Objective] This paper proposes a citation prediction model for scholarly articles, which could identify potential research hot spots and optimize journal editing.[Methods] First, we used graph convolution to extract literature features, which include keywords, authors, institutions, countries, and citations. Then, we used recurrent neural network...

Course recommendation systems are applied to help students with different needs select courses in a large range of course resources. However, a student’s needs are not always determined by their personal interests, they are also influenced by teachers, peers etc. Unlike online courses, user behavior and user satisfaction of offline courses often ha...

Abstract Crowdsourcing has significantly motivated the development of meteorological services. Starting from the beginning of 2010s and highly motivating after 2014, crowdsourcing‐driven meteorological services have evolved from a single collection and observation of data to the systematic acquisition, analysis and application of these data. In thi...

Based on ACP ( artificial systems, computing experiments, and parallel execution ) methodology, parallel control and management has become a popularly systematic and complete solution for the control and management of complex systems. This paper focuses on summarizing comprehensive review of the research literature of parallel control and managemen...

In recent years, frequent meteorological disasters have brought great suffering to people. The meteorological briefing is an effective way to realize the real-time perception of extreme meteorological events, which is of great significance for decision-makers to formulate plans and provide timely assistance. Traditional meteorological briefings pri...

In recent years, frequent meteorological disasters have caused great concern to people. It is particularly important to timely detect the meteorological events and release early warning information. Most traditional meteorological event detection methods rely on physical sensors, but such practice is usually costly and inflexible. As a new form of...

Meteorological events, such as typhoons, rainstorms, and floods, are correctly forecasted, observed and reported by meteorological stations. However, the impacts of such events are widely shared and discussed over social network sites (SNS), such as online news outlets, Sina microblogs and WeChat public posts. Social media provides a platform where...

The current existing data in online music service platforms is heterogeneous, extensive, and disorganized. Finding an effective method to use these data in recommending appropriate music to users during a short-term session is a significant challenge. Another serious problem is that most of data, in reality, obey the long-tailed distribution, which...

We present a bibliographic and authorship-based collaboration analysis of papers published in the IEEE Transactions on Intelligent Transportation Systems (T-ITS) between 2014 and 2016 from the aspects of productivity, topics, citations, usage, and authorship networks. The most productive authors, institutions, countries/regions, and the most cited...

In traditional Web-based learning systems, due to insufficient learning behaviors analysis and personalized study guides, a few user clustering algorithms are introduced. While analyzing the behaviors with these algorithms, researchers generally focus on continuous data but easily neglect discrete data, each of which is generated from online learni...

In the age of big data, Open Source intelligence (OSint) is hard to grasp. This paper proposes an ASKE engine based framework to acquire and analyzes open source intelligence. To validate the utility of this framework, the latest five years papers which were published in 19 domestic core journals as a data set to make a test is used. Not surprisingl...

Nowadays, automation science and technology based on automatic control and information processing has become an essential impetus to productive forces and human life. So a comprehensive understanding of the latest research progress in this discipline is essential for its significant reference value to scholars and research institutions. In this pape...

The most time-consuming operation in the Elliptic Curve Cryptography (ECC) calculation is scalar multiplication. Scalar multiplication plays a major role in ECC. Currently, there are several optimization algorithms for point scalar multiplication which have either high computational complexity or additional storage requirement. They are all unsuita...

This paper aims at discovering latent cyber organizations in rich social media, through analysis sentiment dimension of individual's social attribute. From a sociology perspective, people who have the same point of views will have great probabilities and opportunities to aggression together. Monitoring these latent cyber organizations can help us u...

Since the first peer-reviewed journal appeared in the late 17th century, journals have been the most important platform for scientists to publish articles. Over the last decade, the fast growth of online social networking and media services has brought us numerous valuable data and several applications to track the topic trends in a held and facili...

Currently, the research issues are becoming increasingly global and complex. In order to master more and more professional and comprehensive ability to solve problems, it is proposed in this paper that academic intelligence, journal intelligence, conference intelligence, paper intelligence and so on are integrated together to establish intelligent...

The micro-blogs, as a new social media, possesses big differences with other social media on the aspect of information updating frequency, organization structure, user connection and etc, which have astonishing power of convergence and penetration. Based on this, it is proposed in this paper that Micro-Blog Public Opinion Index (MBPOI), which consi...

In the past two decades, many branches of science have shifted from individually oriented research toward team-based scientific collaboration. 1-3 Teams of researchers representing different disciplines are often brought together to better solve large-scale and often urgent problems of scientific, societal, and environmental relevance. In addition...

The news filtering and summarization (NFAS) system can automatically recognize Web news pages, retrieve each news page's title and news content, and extract key phrases. This extraction method substantially outperforms methods based on term frequency and lexical chains.