Perception, as the information input module of automatic driving system, determines lower limit entire system. Both autonomous perception and robot are constantly approaching real physical world through digital methods, this is only limited to scope human perception, such lane lines, traffic lights, obstacles, so on. The main premise process that humans already know categories or properties world, allow machines systems replicate responses. Whether it a pure visual route multi-source fusion...

Swift is a new, principled approach to building web applications that are secure by construction. In modern applications, some application functionality usually implemented as client-side code written in JavaScript. Moving and data the client can create security vulnerabilities, but currently there no good methods for deciding when it do so. automatically partitions while providing assurance resulting placement efficient. Application Java-like annotated with information flow policies specify...

In order to perform some types of complex tasks, the principles crowdsourcing have been applied in constructing a mobile network with huge amount human involvement and powerful devices. addition, through social Internet Things (SIoT) paradigm, capability humans devices discover exploit objects their services is augmented. Thus, SIoT has become promising for service discovery composition. By introducing SIoT, we can expand traditional achieve broader application. However, threats are also...

Affective computing is one of the key technologies to achieve advanced brain-machine interfacing. It increasingly concerning research orientation in field artificial intelligence. Emotion recognition closely related affective computing. Although emotion based on electroencephalogram (EEG) has attracted more and attention at home abroad, subject-independent still faces enormous challenges. We proposed a algorithm dynamic empirical convolutional neural network (DECNN) view Combining advantages...

As a kind of non-invasive, low-cost, and readily available brain examination, EEG has attached significance to the means clinical diagnosis epilepsy. However, reading long-term records brought heavy burden neurologists experts. Therefore, automatic classification for epileptic patients plays an essential role in epilepsy treatment. This paper proposes Attention Mechanism-based Wavelet Convolution Neural Network classification. firstly uses multi-scale wavelet analysis decompose input EEGs...

Attention deficit/Hyperactivity disorder (ADHD) is a complex, universal and heterogeneous neurodevelopmental disease. The traditional diagnosis of ADHD relies on the long-term analysis complex information such as clinical data (electroencephalogram, etc.), patients' behavior psychological tests by professional doctors. In recent years, functional magnetic resonance imaging (fMRI) has been developing rapidly widely employed in study brain cognition due to its non-invasive non-radiation...

Detecting ancient Chinese characters in various media, including stone inscriptions, calligraphy, and couplets, is challenging due to the complex backgrounds diverse styles. This study proposes an advanced deep-learning framework for detecting scenes improve detection accuracy. First, introduces Ancient Character Haar Wavelet Transform downsampling block (ACHaar), effectively reducing feature maps' spatial resolution while preserving key character features. Second, a Glyph Focus Module (GFM)...

In recent years, substantial research has focused on emotion recognition using multi-stream speech representations. existing (SER) approaches, effectively extracting and fusing features is crucial. To overcome the bottleneck in SER caused by fusion of inter-feature information, including challenges like modeling complex feature relations inefficiency methods, this paper proposes an framework based multi-task learning, named AFEA-Net. The consists a alignment learning (SEAL), acoustic...

Swift is a new, principled approach to building web applications that are secure by construction . In modern applications, some application functionality usually implemented as client-side code written in JavaScript. Moving and data the client can create security vulnerabilities, but currently there no good methods for deciding when it do so. automatically partitions while providing assurance resulting placement efficient. Application Java-like annotated with information flow policies...

Virtual machines hosted in virtualized data centers are important providers of computational resources the era cloud computing. Efficient scheduling centers' virtual can reduce number physical servers needed to host and, turn, energy and other capital costs for maintaining centre. In this paper, we propose an innovative approach achieve efficient pro-active VM scheduling. Our uses a multi-capacity bin packing technique that efficiently places VMs onto servers. We use time-series analysis...

Cloud computing is experiencing a rapid development since large amount of data need to be addressed. How carry on the reasonable task scheduling plays vital role in efficiency cloud computing. This paper proposes green task-scheduling algorithm (GCTA) based improved binary particle swarm optimization(BPSO). The main contribution our work avoiding matrix operations by using pipelined number for virtual machines and redefining position velocity particle. Simulation shows that proposed GCTA has...

Swift is a new, principled approach to building Web applications that are secure by construction. Modern typically implement some functionality as client-side JavaScript code, for improved interactivity. Moving code and data the client can create security vulnerabilities, but currently there no good methods deciding when it do so. automatically partitions application while providing assurance resulting placement efficient. Application written Java-like annotated with information flow...

Breast cancer is one of the leading cancers worldwide.Precision medicine a new trend that systematically examines molecular and functional genomic information within each patient's to identify patterns may affect treatment decisions potential outcomes.As part precision medicine, computer-aided diagnosis enables joint analysis image from pathological images.In this paper we propose an integrated framework for breast staging using image-omics information.The entire biomedical imaging...

As one of the important tools epilepsy diagnosis, electroencephalogram (EEG) is noninvasive and presents no traumatic injury to patients. It contains a lot physiological pathological information that easy obtain. The automatic classification epileptic EEG in diagnosis therapeutic efficacy epileptics. In this article, an explainable graph feature convolutional neural network named WTRPNet proposed for classification. Since constructed by recurrence plot wavelet domain, it can fully obtain...

Maintenance plays an important role in system reliability enhancement which is essential requirement for computer systems service critical applications. This paper presents a failure number m based maintenance policy k-out-of-n:G load- sharing with goal of maximizing the long-run expected reward per unit time. Compared to previous study, we take load-sharing into account and employ tampered rate (TFR) model describe change caused by sharing. With some typical numeral examples, analyzed under...

Complex network clustering problems have been gained great popularity and widespread researches recently, plentiful optimization algorithms are aimed at this problem. Among these methods, the methods aiming multiple objectives can break limitations (e.g., instability) of those optimizing single objective. However, one shortcoming stands out that cannot balance exploration exploitation well. In another sentence, it fails to optimize solutions on basis good obtained so far. Inspired by nature,...

Clinical Electroencephalogram (EEG) data is of great significance to realize automatable detection, recognition and diagnosis reduce the valuable time. To make a classification epilepsy, we constructed convolution support vector machine (CSVM) by integrating advantages convolutional neural networks (CNN) (SVM). distinguish focal non-focal epilepsy EEG signals, firstly reduced dimensionality signals using principal component analysis (PCA). After that, classified CSVM. The accuracy,...