As a key mission of the modern traffic management, crowd flow prediction (CFP) benefits in many tasks intelligent transportation services. However, most existing techniques focus solely on forecasting entrance and exit flows metro stations that do not provide enough useful knowledge for management. In practical applications, managers desperately want to solve problem getting potential passenger distributions help authorities improve transport services, termed as distribution (CFD) forecasts....

Public urban transit offers a convenient, affordable, and sustainable mode of transportation for many. However, limited subsidies revenue collected from bus fares place restrictions on the number lines that can operate; these in turn limit individuals who benefit public transit. To make well-informed operational decisions planning operations, understanding origin destination patterns riders is crucial. traditional methods data collection are labor-intensive costly. Although some agencies use...

People's daily information sharing and acquisition through the Internet has become more popular. The comprehensive multimodal marketing advertorial generated by 'We Media' accounts besides normal social news is gaining its importance on media platforms. In order to achieve effective advertising, intent understanding a key step towards generating targeted advertising strategies (push advertorials specific people at time). However, in real are usually designed pretend as with wide range of...

Crowd Flow Prediction (CFP) is one major challenge in the intelligent transportation systems of Sydney Trains Network. However, most advanced CFP methods only focus on entrance and exit flows at stations or a few subway lines, neglecting Distribution (CFD) forecasting problem across entire city network. CFD prediction plays an irreplaceable role metro management as tool that can help authorities plan route schedules avoid congestion. In this paper, we propose three online non-negative matrix...

In recent years, it is a difficult issue to integrate the deep cross-fertilization and interpretable cognitive modeling methods from basic theory of emotional psychology with learning other algorithms. To address this problem, model that integrates VGG-facial action coding system (FACS)-OCC based on fer2013 expression features OCC-pleasure-arousal-dominance (PAD)-openness, conscientiousness, extraversion, agreeableness, neuroticism (OCEAN) fusion psychology, namely, computational...

Change address identification is one of the difficulties in bitcoin clustering as an emerging social computing problem. Most current-related research only applies to certain specific types transactions and faces problems low recognition rate high false positive rate. We innovatively propose a method based on multiconditional one-time change addresses conduct experiments with on-chain transaction data. The results show that proposed identifies at least 12.3% more than other heuristics. On top...

Recently, practical applications for passenger flow prediction have brought many benefits to urban transportation development. With the development of urbanization, a real-world demand from managers is construct new metro station in one city area that never planned before. Authorities are interested picture future volume commuters before constructing station, and estimate how would it affect other areas. In this paper, specific problem termed as potential (PPF) prediction, which novel...

As a developing trend of urbanization, massive amounts urban statistical data with multiple views (e.g., Population and Economy) are increasingly collected benefited to diverse domains, including transportation service, regional analysis, etc.Unfortunately, these that divided into fine-grained regions usually suffer from missing value problem during the acquisition storage processes.It is mianly caused by some inevitable circumstances, e.g., document defacement, difficulty in remote...

The audio-video based multimodal emotion recognition has attracted a lot of attention due to its robust performance. Most the existing methods focus on proposing different cross-modal fusion strategies. However, these strategies introduce redundancy in features modalities without fully considering complementary properties between modal information, and approaches do not guarantee non-loss original semantic information during intra- inter-modal interactions. In this paper, we propose novel...

Fusion technology is crucial for multimodal sentiment analysis. Recent attention-based fusion methods demonstrate high performance and strong robustness. However, these approaches ignore the difference in information density among three modalities, i.e., visual audio have low-level signal features conversely text has high-level semantic features. To this end, we propose a non-homogeneous network (NHFNet) to achieve interaction. Specifically, module with attention aggregation designed handle...

Abstract With the rapid growth of Internet Vehicles (IoV) technology, performance and privacy IoV terminals (IoVT) have become increasingly important. This paper proposes a federated learning model for IoVT classification using connection records (FLM-ICR) to address concerns poor computational in analyzing users' private data IoV. FLM-ICR, horizontally client-server architecture, utilizes an improved multi-layer perceptron logistic regression network as backbone, employs momentum gradient...

To distinguish the subtle differences among fine-grained categories, a large amount of well-labeled images are typically required. However, manual annotations for categories is an extremely difficult task as it usually has high demand professional knowledge. this end, we propose to directly leverage web visual recognition. Our work mainly focuses on two critical issues including "label noise" and "domain mismatch" in images. Specifically, end-to-end deep denoising network (DDN) model jointly...

Large volumes of urban statistical data with multiple views imply rich knowledge about the development degree cities. These present crucial statistics which play an irreplaceable role in regional analysis and computing. In reality, however, divided into fine-grained regions usually suffer from missing problems. Those values hide useful information that may result a distorted analysis. Thus, this paper, we propose spatial imputation method for multi-view data. To address problem, exploit...

Traumatic brain injury (TBI) remains a growing significant public health problem and prognosis of outcome is difficult due to the multitude factors that underlie heterogeneity TBI. Prognosis aims forecast likely development disease significantly affects patient's recovery healthcare. Traditionally, TBI relies on physician's insights their empirical knowledge which makes it infeasible for large-scale implementation. Existing methods utilize single modality (i.e., either clinical data or...

Wang and Yu proposed a block cipher scheme based on dynamic sequences generated by multiple chaotic systems, which overcomes the problem of periodical degradation random due to computational precision. Their has feature that plaintext is encrypted keystream created from several one‐dimensional maps. However, this results in some weaknesses encryption algorithm. We show three kinds attacks paper, through one can recover given ciphertext without secret key. also present an improvement their...

Establishing the tolerance limits of patient-specific quality assurance (PSQA) processes based on gamma passing rate (GPR) by using normal statistical process control (SPC) methods involves certain problems. The aim this study was threefold: (a) to show that heuristic SPC method can replace quantile for establishing in PSQA and is more robust, (b) introduce an iterative procedure "Identify-Eliminate-Recalculate" with unknown states retrospective GPRs, (c) recommend a workflow define actual...

Railway points are among the key components of railway infrastructure. As a part signal equipment, control routes trains at junctions, having significant impact on reliability, capacity, and punctuality rail transport. Meanwhile, they also one most fragile parts in systems. Points failures cause large portion incidents. Traditionally, maintenance is based fixed time interval or raised after equipment failures. Instead, it would be great value if we could forecast points' take action...

Biodetoxification fungus selectively degrades toxic inhibitors generated from pretreatment of lignocellulose without consuming fermentable sugars. However, one barrier for practical application is the sustained cell viability in consequent fermentation step to compete sugars with fermenting strains, resulting sugar loss and reduced target product yield. This study investigated competitive growth property between biodetoxification Paecilomyces variotii FN89 L-lactic acid bacterium Pediococcus...

With the continuous process of urbanization, regional integration has become an inevitable trend future social development. Accurate prediction passenger volume is essential prerequisite for understanding extent integration, which one most fundamental elements enhancement intercity transportation systems. This study proposes a two-phase approach in effort to predict highway volume. The datasets subsume and impact factors urban attributes. In Phase I, correlation analysis conducted remove...