This paper describes automation methods for device driver development in IP-based embedded systems order to achieve high reliability, productivity, reusability and fast time market. We formally specify behaviors using event driven finite state machines, communication channels, declaratively described rules, constraints synthesis patterns. A is synthesized from this specification a virtual environment that platform (processor, operating system other hardware) independent. The mapped specific...

This paper presents a correct-by-construction synthesis method for generating operating system based device drivers from formally specified behavior model. Existing driver development is largely manual using an ad-hoc design methodology. Consequently, this task error prone and becomes bottleneck in embedded methodology.Our solution to problem starts by accurately specifying access with formal model, viz. extended event driven finite state machines. We easy check soundness conditions on the...

Expectation maximization (EM) algorithm is to find maximum likelihood solution for models having latent variables. A typical example Gaussian Mixture Model (GMM) which requires assumption, however, natural images are highly non-Gaussian so that GMM cannot be applied perform image clustering task on pixel space. To overcome such limitation, we propose a GAN based EM learning framework can maximize the of and estimate We call this model GAN-EM, clustering, semi-supervised classification...

We experimentally study the robustness of deep camera-LiDAR fusion architectures for 2D object detection in autonomous driving. First, we find that model is usually both more accurate, and robust against single-source attacks than single-sensor neural networks. Furthermore, show without adversarial training, early late fusion, whereas two perform similarly after training. However, note single-channel training often detrimental even to robustness. Moreover, observe cross-channel...

Many projects have tried to analyze the structure and dynamics of application overlay networks on Internet using packet analysis network flow data. While such is essential for a variety management security tasks, it difficult many networks: either volume data so large as make inspection intractable, or privacy concerns forbid capture require dissociation flows from users' actual IP addresses. In this paper, an algorithm mining preserving item sets proposed. On one hand, only maximal set...

This paper describes automation methods for device driver development in IP-based embedded systems order to achieve high reliability, productivity, reusability and fast time market. We formally specify behaviors using event driven finite state machines, communication channels, declaratively described rules, constraints synthesis patterns. A is synthesized from this specification a virtual environment that platform (processor, operating system other hardware) independent. The mapped specific...

Conference key agreement is one of the important issues in cryptography. In this paper, we propose a novel conference scheme. Without adopting authenticated broadcasting channel model, use an intermediary node to ensure correctness transmitted messages. A passive adversary or active obtains zero knowledge about common established by all honest participants who follow proposed Keywords: key, Diffie-Hellman, adversary, cryptography

Underwater optical imaging is a highly challenging task owing to the intricate underwater environment. This often plagued by issues such as image blur, color distortion, and low contrast, which pose significant obstacles target detection tasks. Traditional methods depend on manually designed features, may not accurately characterize targets can also be impacted factors occlusion sediment burial. paper presents novel baseline for object based YOLOv7 algorithm, an end-to-end algorithm with...

Human hand detection is still a challenging problem in real world setting because the appearance features are less and varied form. So it very important to make good use of context enhance feature through each other. In this paper, we propose Context Attention Feature Pyramid Networks CA-FPN for human detection, where Module (CAM) introduced as new component pyramid architecture. The CAM aims to: (1) capture information reserve local edge feature, (2) figure out relative hands. proposed...

Understanding web instructional videos is an essential branch of video understanding in two aspects. First, most existing methods focus on short-term actions for a-few-second-long clips; these are not directly applicable to long videos. Second, unlike unconstrained videos, e.g., movies, more structured that they have step-by-step procedures constraining the task. In this work, we study problem-solving via Visual Question Answering (VQA). Surprisingly, it has been emphasis community despite...

Camouflaged objects are typically assimilated into their backgrounds and exhibit fuzzy boundaries. The complex environmental conditions the high intrinsic similarity between camouflaged targets surroundings pose significant challenges in accurately locating segmenting these entirety. While existing methods have demonstrated remarkable performance various real-world scenarios, they still face limitations when confronted with difficult cases, such as small targets, thin structures, indistinct...

We propose an instance segmentation model, named CoMask, that effectively alleviates the scale variation issue and addresses precise localization. Specifically, we develop a multi-scale feature extraction module (MSFEM) to exploit spatial cues. Besides, channel attention mechanism is also adopted further enhance discriminating ability. Equipped with MSFEMs, multi-level features can be extracted better characterize objects of various sizes provide affluent high-level semantic information. For...