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- Planning-oriented Autonomous Driving1,690
This work introduces Unified Autonomous Driving (UniAD), a comprehensive framework up-to-date that incorporates full-stack driving tasks in one network and is exquisitely devised to leverage advantages of each module, and provide complementary feature abstractions for agent interaction from a global perspective.
- Vision Transformer Adapter for Dense Predictions938
The ViT-Adapter is proposed, which allows plain ViT to achieve comparable performance to vision-specific transformers and facilitate future research and is verified on multiple dense prediction tasks, including object detection, instance segmentation, and semantic segmentation.
- Shape Robust Text Detection With Progressive Scale Expansion Network860
A novel Progressive Scale Expansion Network (PSENet) is proposed, which can precisely detect text instances with arbitrary shapes and is effective to split the close text instances, making it easier to use segmentation-based methods to detect arbitrary-shaped text instances.
- Efficient and Accurate Arbitrary-Shaped Text Detection With Pixel Aggregation Network632
This paper proposes an efficient and accurate arbitrary-shaped text detector, termed Pixel Aggregation Network (PAN), which is equipped with a low computational-cost segmentation head and a learnable post-processing.
- EmbodiedGPT: Vision-Language Pre-Training via Embodied Chain of Thought459
This work introduces EmbodiedGPT, an end-to-end multi-modal foundation model for embodied AI, empowering embodied agents with multi- modal understanding and execution capabilities, and significantly enhances the success rate of the embodied control task by extracting more effective features.
- Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization270
This work designs an automated preference data construction pipeline to create MMPR, a high-quality, large-scale multimodal reasoning preference dataset and explores integrating PO with MLLMs, developing a simple yet effective method, termed Mixed Preference Optimization (MPO), which boosts multimodal CoT performance.
- Segmenting Transparent Objects in the Wild256
A novel boundary-aware segmentation method, termed TransLab, is proposed, which exploits boundary as the clue to improve segmentation of transparent objects and significantly outperforms 20 recent object segmentation methods based on deep learning.
- Scene Text Image Super-Resolution in the Wild186
A new Text Super-Resolution Network termed TSRN, with three novel modules is developed, which improves the recognition accuracy by over 13% of CRNN, and by nearly 9.0% of ASTER and MORAN compared to synthetic SR data.
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- A novel intrusion detection system based on an optimal hybrid kernel extreme learning machine170
A novel accurate and effective misuse intrusion detection system that relies on specific attack signatures to distinguish between normal and malicious activities is presented to detect various attacks based on an extreme learning machine with a hybrid kernel function (HKELM).
- Vision-RWKV: Efficient and Scalable Visual Perception with RWKV-Like Architectures166
Vision-RWKV (VRWKV), a model adapted from the RWKV model used in the NLP field with necessary modifications for vision tasks, surpasses ViT's performance in image classification and has significantly faster speeds and lower memory usage processing high-resolution inputs.
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- The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World133
The All-Seeing model (ASM), a unified framework for panoptic visual recognition and understanding, is developed with open-ended language prompts and locations, which allows it to generalize to various vision and language tasks with remarkable zero-shot performance.
- InternGPT: Solving Vision-Centric Tasks by Interacting with ChatGPT Beyond Language113
By incorporating pointing instructions, the proposed iGPT significantly improves the efficiency of communication between users and chatbots, as well as the accuracy of chatbots in vision-centric tasks, especially in complicated visual scenarios where the number of objects is greater than 2.
- Performance assessment of extensive green roof runoff flow and quality control capacity based on pilot experiments101
The runoff quantity and quality control capacity of five types of extensive green roofs (EGRs) were analyzed in Beijing for 51 nature rainfall events and 6 simulated events from July 2017 to October 2018 and showed that as the module scale and substrate thickness increased, the retention capacity of the EGRs increased.
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- MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer83
MM-Interleaved is an end-to-end generative model for interleaved image-text data that introduces a multi-scale and multi-image feature synchronizer module, allowing direct access to fine-grained image features in the previous context during the generation process.
- Research advances in traditional Chinese medicine syndromes in cancer patients82
The authors reviewed the presentations of TCM syndromes in seven common malignancies, the objectivity and the standardization of TCm syndrome differentiation, the evaluation ofTCM syndrome modeling in cancer research, and syndrome differentiation-guided TCM treatment of cancers.
- Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks75
This paper proposes Uni-Perceiver v2, which is the first generalist model capable of handling major large-scale vision and vision-language tasks with competitive performance and proposes an effective optimization technique named Task-Balanced Gradient Normalization to ensure stable multi-task learning with an unmixed sampling strategy, helpful for tasks requiring large batch-size training.
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- A Survey of Reasoning with Foundation Models73
This paper introduces seminal foundation models proposed or adaptable for reasoning, highlighting the latest advancements in various reasoning tasks, methods, and benchmarks and discusses the relevance of multimodal learning, autonomous agents, and super alignment in the context of reasoning.
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- Causal augmented ConvNet: A temporal memory dilated convolution model for long-sequence time series prediction68
A causal augmented convolution network (CaConvNet) and its application for long-sequence time series prediction and a comprehensive ablation study is performed to provide insights into the contribution of each sub-structure of the CaConv net model to the observed performance.
- MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents66
This work introduces MMBench-GUI, a hierarchical benchmark for evaluating GUI automation agents across Windows, macOS, Linux, iOS, Android, and Web platforms, and proposes a novel Efficiency-Quality Area (EQA) metric to assess GUI agent execution efficiency in online automation scenarios.
- RoboCodeX: Multimodal Code Generation for Robotic Behavior Synthesis66
A tree-structured multimodal code generation framework for generalized robotic behavior synthesis, termed RoboCodeX, which decomposes high-level human instructions into multiple object-centric manipulation units consisting of physical preferences such as affordance and safety constraints, and applies code generation to introduce generalization ability across various robotics platforms.
- OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text60
This paper introduces OmniCorpus, a 10 billion-scale image-text interleaved dataset that has 15 times larger scales while maintaining good data quality and is more flexible, easily degradable from an image-text interleaved format to pure text corpus and image-text pairs.
- The Use of Finite Element Models to Assist Understanding and Treatment For Scoliosis: A Review Paper59
The current state of the art of FEM related to the biomechanical analysis of scoliosis is discussed in 4 sections: the etiology of adolescent idiopathic scolia, brace treatment, instrumentation treatment, and sensitivity studies of F EM.
- Finite element analysis of the effect of an interphase on toughening of a particle-reinforced polymer composite58
A numerical method was used to study the interaction between a crack and the filler phase in a particle-reinforced polymer composite, providing a framework for the quantitative prediction of the deformation and fracture response of the composite.
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- Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class Representation47
This paper proposes an embedding adaptive-update strategy to avoid feature drift, which maintains old knowledge by hyper-class representation, and adaptively update category embeddings with a class-attention scheme to involve new classes learned in individual sessions to solve IFSS problems.
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- LLMs Meet Multimodal Generation and Editing: A Survey42
This work provides a systematic and insightful overview of multimodal generation and processing, which is expected to advance the development of Artificial Intelligence for Generative Content (AIGC) and world models.
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- SLIME: program-sensitive energy allocation for fuzzing37
A novel program-sensitive solution, named SLIME, to enable adaptive energy allocation on the seed files with various properties for each program, and leverages a customized Upper Confidence Bound Variance-aware (UCB-V) algorithm to statistically select a property queue with the most estimated reward.
- A novel ship classification approach for high resolution SAR images based on the BDA-KELM classification model35
A novel ship classification model combining kernel extreme learning machine (KELM) and dragonfly algorithm in binary space (BDA), named BDA-KelM, is proposed which can achieve a better classification performance than these four widely used models with an classification accuracy as high as 97% and encouraging results of other three multi-class classification evaluation metrics.
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- EchoInk-R1: Exploring Audio-Visual Reasoning in Multimodal LLMs via Reinforcement Learning30
EchoInk-R1 is the first framework to unify audio, visual, and textual modalities for general open-world reasoning via reinforcement learning, and suggests that lightweight reinforcement learning fine-tuning enhances cross-modal reasoning in MLLMs.
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- Mutation grey wolf elite PSO balanced XGBoost for radar emitter individual identification based on measured signals30
Results verify that MGWEPSO-BXGBoost has high accuracy and strong stability even when the sample size of each individual is limited and imbalanced, which is conducive to improving the ability to find the global optimal solution.
- Mini-DALLE3: Interactive Text to Image by Prompting Large Language Models29
This work revisits the existing T2I systems endeavoring to align human intent and introduce a new task - interactive text to image (iT2I), where people can interact with LLM for interleaved high-quality image generation/edit/refinement and question answering with stronger images and text correspondences using natural language.
- Denoising Diffusion Semantic Segmentation with Mask Prior Modeling28
This paper proposes to ameliorate the semantic segmentation quality of existing discriminative approaches with a mask prior modeled by a recently-developed denoising diffusion generative model, and develops a unified architecture that adapts diffusion models for mask prior modeling.
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- Separation and colorimetric detection of Escherichia coli by phage tail fiber protein combined with nano-magnetic beads27
The colorimetric changes determined by visual inspection can be developed as an efficient platform for point-of-care detection of E. coli in resource-limited regions.
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- A new fault detection method for computer networks24
A new fault detection method, whose key is to divide the detection process into multiple stages, which can guarantee that the traffic used by probes during each detection stage is small sufficiently so that the network can operate without severe disturbance from probes.
- SyzTrust: State-aware Fuzzing on Trusted OS Designed for IoT Devices23
SzTrust is presented, the first state-aware fuzzing framework for vetting the security of resource-limited Trusted OSes, and demonstrates significant improvements, including 66% higher code coverage, 651% higher state coverage, and 31% improved vulnerability-finding capability.
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- Biomechanics of high-grade spondylolisthesis with and without reduction23
A comprehensive finite element model was developed to analyze the biomechanics of the spine after spinal fusion at L5–S1 in both types of high-grade spondylolisthesis (balanced and unbalanced pelvis).
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- A robust cutting pattern recognition method for shearer based on Least Square Support Vector Machine equipped with Chaos Modified Particle Swarm Optimization and Online Correcting Strategy19
A novel approach for cutting pattern recognition with an optimal Online Correcting Strategy (OCS) combined with Least Square Support Vector Machine (LSSVM) and Chaos Modified Particle Swarm Optimization (CMPSO) algorithm is proposed, where LSSVM models the functional relationship between input and output of the system, CMPSO optimizes the parameters of L SSVM, and OCS modifies the model to reduce its mismatch as the system runs.
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- LLM4EFFI: Leveraging Large Language Models to Enhance Code Efficiency and Correctness15
This approach, which prioritizes efficiency before ensuring correctness, offers a new paradigm for efficient code generation, and is demonstrated to achieve new state-of-the-art performance in code efficiency benchmarks across various LLM backbones.
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- Comparison between different infiltration models to describe the infiltration of permeable brick pavement system via a laboratory-scale experiment15
The results showed that the fitting accuracy of Kostiakov, Philip, and Green-Ampt models was significantly affected by the monitoring area and hydraulic gradients, and the Horton model is an optimal model to describe the infiltration performance of PBPs, which can also be adopted to evaluate hydrological characterization ofPBPs.
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- How IoT Re-using Threatens Your Sensitive Data: Exploring the User-Data Disposal in Used IoT Devices14
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- Demystify Transformers & Convolutions in Modern Image Deep Networks13
This paper aims to identify the real gains of popular convolution and attention operators through a detailed study, and finds that the key difference among these feature transformation modules, such as attention or convolution, lies in their spatial feature aggregation approach, known as the “spatial token mixer” (STM).
- LuaTaint: A Static Analysis System for Web Configuration Interface Vulnerability of Internet of Things Devices13
LuaTaint combines static taint analysis with a large language model (LLM) to achieve widespread and high-precision detection of vulnerabilities and exhibits a vulnerability detection precision rate of up to 89.29%.
- Remaining useful life prediction for non-stationary degradation processes with shocks13
This article addresses a remaining useful life predictive problem where the considered device suffers from non-stationary degradation with shocks and a novel degradation-shock system model subjected to a hidden degradation state is proposed to characterize the degradation process.
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- Ultrasound-Guided Radiofrequency and Microwave Ablation for the Management of Patients With Benign Thyroid Nodules11
Ultrasound-guided radiofrequency and microwave ablation had better efficacy and safety profile in terms of symptoms, cosmetic relief, complication rate, duration of stay, and operation time when compared with conventional surgery or observation without treatment for patients with benign thyroid nodules.
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- Promoting digital twin technology application for process industry: A novel generation modelling platform and its implementations10
A comprehensive system modelling approach and a closed‐loop industrial control system based on DTs are developed, showcasing advanced control, optimisation, and system security research capabilities.
- Characterizing and Evaluating the Reliability of LLMs against Jailbreak Attacks10
An comprehensive evaluation framework is introduced and an large-scale empirical experiment is conducted to address the need to enhance the security evaluation of LLMs against jailbreak within the domain.
- Visual Robotic Object Grasping Through Combining RGB-D Data and 3D Meshes10
A novel framework to drive automatic robotic grasp by matching camera captured RGB-D data with 3D meshes, on which prior knowledge for grasp is pre-defined for each object type.
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- MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible Cost8
This work introduces MuLan, Multi-Language adapter, a lightweight language adapter with fewer than 20M parameters, trained alongside a frozen text encoder and image diffusion model, to explore a cost-effective framework for multilingual image generation.
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- Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments7
Under feature map dropout, good detectors tend to output bounding boxes whose locations do not change much, while bounding boxes of poor detectors will undergo noticeable position changes, contributing to finding that BoS score has a strong, positive correlation with detection accuracy measured by mean average precision under various test environments.
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- A novel adaptive generic model control strategy for internal thermally coupled air separation columns with multivariable recursive estimation7
An adaptive generic model control (AGMC) with a multivariable recursive estimation is developed and compared control systems show that AGMC can better handle both the system nonlinearity and strong interaction while improving the control performance.
- Hand Pose Estimation with Attention-and-Sequence Network7
This paper presents a novel Attention-and-Sequence Network (ASNet) embedded with finger attention and joint sequence mechanisms, and achieves an average 3D error of 5.6 mm on ICVL, 10.3 mm on NYU, 7.3mm on MSRA, and these competitive results further confirm the great effectiveness of ASNet.
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- Comparison of two methods for endoscopic full-thickness resection of gastrointestinal lesions using OTSC6
EFTR of pre-resection closure are potentially faster compared with the concept of applying closure after EFTR, and larger prospective controlled studies comparing these two techniques are warranted in the future.
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- A Novel 3D Human Action Recognition Framework for Video Content Analysis6
This paper proposes to incorporate temporal patterns of joint positions with currently popular Long Short-Term Memory (LSTM) based learning to improve both accuracy and robustness in 3D human action analysis.
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- Feature Disentangling Autoencoder for Anomaly Detection of Reactor Core Temperature with Feature Increment Strategy5
An incrementally feature disentangling auto-encoder (IDAE), which is the improved version of DAE, and an iterative training framework is designed, which focuses on the parameter training of the newly incremented feature, overcoming the difficulty of model training.
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- Squeeze excitation densely connected residual convolutional networks for specific emitter identification based on measured signals5
A novel convolutional neural network approach, named squeeze excitation densely connected residual Convolutional network (SEDCRN) approach, which can directly recognize signals without complex preprocessing and which outperforms traditional methods and other CNN-based methods in terms of accuracy and parameter efficiency.
- Fair-PP: A Synthetic Dataset for Aligning LLM with Personalized Preferences of Social Equity4
Fair-PP is introduced, a synthetic dataset of personalized preferences targeting social equity, derived from real-world social survey data, which includes 28 social groups, 98 equity topics, and 5 personal preference dimensions.
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- Nanocarrier Based Targeting of Vascular Cell Adhesion Molecule-1 for Diagnosis and Treatment of Atherosclerosis: Current Status and Future Perspectives4
The origin, structure, and function of antibodies, followed by a summary of the VCAM-1 targeted nanosystems, including siRNA targeting carriers, for the therapy and diagnosis of various inflammatory-related pathologies are discussed.
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- Programmable logic controller memory management vulnerability analysis4
This paper proposed five types of attacks on the PLC memory management mechanism, and evaluated the feasibility of the memory attack generation approach on six PLCs from three leading controller vendors.
- Identification and validation of prognostic autophagy-related genes associated with immune microenvironment in human gastric cancer4
Better understanding of the ATGs and their interaction with the immune microenvironment, which would allow the development of novel inhibitors, personalized treatment, and immunotherapy in gastric cancer, is aid in better understanding.
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- False data injection attacks and countermeasures in smart microgrid systems4
This chapter proves that once the attacker knows the bounds of the initial estimation error and measurement noise, he/she can launch nonzero-dynamics stealthy (NDS) attacks in DCmGs, which can affect the detection residuals but remain stealthy.
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- Champion Solution for the WSDM2023 Toloka VQA Challenge3
This report presents the champion solution to the WSDM2023 Toloka Visual Question Answering (VQA) Challenge, and shows that ViT-Adapter is also an effective paradigm for adapting the unified perception model to vision-language downstream tasks.
- A novel radar operating mode identification approach based on variational relevance vector machine with chaotic gravitational search optimization3
An identification approach for radar operating mode identification with variational relevance vector machine (VRVM) as the feature extractor and the basic unit of identification, and an improved chaotic gravity search algorithm (CGSA) is developed to increase the search breadth and optimize the hyperparameters of VRVM.
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- Transformer Based Multi-model Fusion for Medical Image Segmentation3
This work uses the same framework to process the two segmentation tasks of polyps and instruments, and consists of multiple segmentation models, and each model uses a transformer as the backbone network.
- TK-Text: Multi-shaped Scene Text Detection via Instance Segmentation3
This work presents a novel representation, i.e., text kernel, for multi-shaped texts, and proposes a simple yet effective scene text detection method, named as TK-Text, based on this representation.
- Cloud of Line Distribution and Random Forest Based Text Detection from Natural/Video Scene Images3
A new method based on Cloud of Line Distribution (COLD) and Random Forest Classifier for text detection in both natural and video images is presented to show its effectiveness and usefulness compared with the existing methods.
- Cloud of Line Distribution for Arbitrary Text Detection in Scene/Video/License Plate Images3
Experimental results and comparative study show that the proposed method outperforms the existing methods in terms of invariant to rotations, scripts and applications.
- Optimal transmission lines assignment with maximal reliabilities in multi-source multi-sink multi-state computer network3
The experiments result show that the RETLA-NSGA II algorithm can provide efficient solutions in a reasonable time, from which the decision makers can choose the best solution based on their preferences and experiences.
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- FOOLSDEDIT: Deceptively Steering Your Edits Towards Targeted Attribute-Aware Distribution2
The Targeted Attribute Generative Attack (TAGA) is proposed, whose objective is to force SDEdit to generate data distributions aligned with a specified attribute without changing the attribute of the input image, without changing the attribute of the input image.
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- Cuckoo Attack: Stealthy and Persistent Attacks Against AI-IDE2
The Cuckoo Attack is proposed, a novel attack that achieves stealthy and persistent command execution by embedding malicious payloads into configuration files in AI-IDEs and contributes seven actionable checkpoints for vendors to evaluate their product security.
- An analysis of gene expression profiles through machine learning uncovers the new diagnostic signature for diabetic foot ulcers2
DCT, PMEL, and KIT are highlighted as diagnostic biomarkers for DFUs, which are linked to melanin production and the MAPK/PI3K-Akt signaling pathways.
- Contrast-enhanced ultrasonography combined with microbubbles for uterine disorders: Current trends and future perspectives2
The clinical utility of contrast-enhanced ultrasonography with microbubbles with microbubbles in uterine diseases is explored, focusing on its diagnostic accuracy, comparison with traditional imaging techniques, and its potential to improve the management of uterine pathology.
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- Adversarial Malicious Encrypted Traffic Detection Based on Refined Session Analysis2
In this paper, an adversarial malicious encrypted traffic detection method based on refined session analysis (ADRSA) is proposed and the detection performance of ADRSA exceeds that of the most popular detection methods.
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- False Data Injection Attacks and Corresponding Countermeasure in DC Microgrid.2
This paper considers a hierarchical control based DC microgrid equipped with unknown input observer (UIO) based detectors, and proposes a countermeasure against ZTU and NTU attacks by observing the average PCC voltage deviation and performs extensive simulations to validate theoretical results and effectiveness.
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- Research and Implementation of Embedded Modbus/TCP Protocol2
This paper particularly discourses upon how to use LwIP API and multi-thread to implement Modbus client/server model and analyses and discusses the communication model and function of Modbus/TCP components.
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- CONTINUOUS MONITORING SYSTEM FOR ENVIRONMENTALγRADIATION NEAR NUCLEAR FACILITY2
The continuous monitoring system which is used for the environmental routine and accident emergency 1 radiation monitoring near nuclear facility is described and has the functions of alarm over threshold and recorded output signal of detetor and temperature.
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- Exploring the immune landscape of cirrhosis through Weighted Gene Co-expression Network Analysis1
The results demonstrate the effectiveness of WGCNA in uncovering new knowledge regarding the biology of cirrhosis and the function of the immune system in this disease and suggested potential treatment options for this troublesome condition.
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- Data Transmission Reliability of a Two-source Single-sink Computer Network with a Common Arc1
This work considers the case that two source nodes are sending data to the sink node through their own minimal paths (MP), where these two MPs possess a common arc in the computer network, and calculates the reliabilities of the data under their transmission time constraints.
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- An Improved Aprior Algorithm Based on Mining Association Rule1
The improved Apriori algorithm adopts matrix to express database, which can reduce the times of database scanning and use vectors operation to count frequent item sets and get rid of unwanted data simultaneously.
- Overview of Concurrency Control in Real-time Database Systems1
Real-time database system derives its concurrency control mechanisms from traditional ones and results of real-time systems and protocols mixed with the two types or extended from one become more and more popular.
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- IDDF2019-ABS-0043 Comparison of two methods for endoscopic full-thickness resection of gastrointestinal lesions using OTSC–
EFTR of pre-resection closure is potentially faster and safer compared with the concept of applying closure after EFTR, and these two techniques are warranted in the future.
- The current situation and relevant risk factors for disability and dementia in the elderly in urban areas of Jiangsu Province–
The incidence of disability and dementia is high among the elderly in urban areas of Jiangsu Province and comprehensive measures against risk factors should be taken for intervention of disabled people and dementia in the elderly.
- IDDF2018-ABS-0099 Comparison of two methods for endoscopic full-thickness resection of gastrointestinal lesions using over-the-scope clip system–
EFTR for pre-resection closure is potentially faster compared with the concept of applying closure after EFTR, and larger prospective controlled studies comparing those two techniques are warranted in the future.
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- Advances in Traditional Chinese Medical Treatment Research in Liver Cancer Postoperation–
This paper reviewed the advances in TCM treatment research on LC postoperation in recent years and put forward problems and countermeasures, to provide a reference for betterTCM treatment onLC postoperation.
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- High accuracy sequence of event system based on GPS–
This method based on the combination of improved Network Time Protocol(NTP) server synchronization and 1PPS synchronization and1 PPS synchronization is simple, precise and stable, and it has been applied to the turbine protection system in a power plant successfully.
- Usage of Database Connection Pool: A Perspective from"Three Ratios"–
Investigation on how to effectively use the connection pool in order to improve the application efficiency and scalability.
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- PCs communication based on EPL–
This research can be used for reference by people who are interested in improving EPL protocol or using EPL equipment.
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- The Study on MiniGUI Transplantation Based on Embedded Linux–
This paper elaborates the MiniGUI transplanting steps, illustrates the process of establishing cross-compiler environment, transplanting of Mini GUI library and resource files as well as configuration of MiniGUI runtime environment, and porting MiniGUI into S3C2410 development board is realized.
- Design of Knowledge Point Structure and the Reasoning of Teaching Strategies in ITS–
Based on the relationship of intellectual content in the teaching activity, builds reticular structure of ITS knowledge which is represented by adjacency matrix which with the rights.
- Maneuvering target tracking in clutter based on separate bias estimation–
The bias estimation and state estimation covariance are used to confirm gate center and gate region and show that SBE_PDA is superior to strong tracking filter probabilistic data association (STF-PDA) by criterion of track lost ratio.
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- Fuzzy-predictive Control of the Consistency of DO in MBR–
To adjust the consistency of DO, the fuzzy-predictive algorithm was used to get the output which controls the input of the frequency converter that would change the flow of air.
- A New Method for Generating FH Sequences Based on Mixed Map–
A new method for generating chaotic FH sequences based on the Logistic mapping and Tent mapping is proposed, which has not only excellent performances of balance property,Hamming correlation, and so on, but also the properties of quickness and efficiency, making it more suitable for practical FH system.
- A Practical Method of Improving Scene Matching Reliability–
By the suitable-matching area selection, a practical method of improving scene matching reliability is proposed and it is proved by many experiments that it is an effective way.
- Design and Implementation of the Communication between the Remote I/O Station and DCS–
The remote I/O control system which based on DCS and implementation of the communication between the remote I-O station and DCS are introduced and the results of the system test are given.
- The Study of Real-Time Distributed Control System Based on IEC61499–
The architecture and characteristics of IEC 61499 standard function block for distributed industrial process measurement and control system (IPMCS) are introduced and the Real-Time Distributed Control System design method based on IEC61499 is studied.
- Research and Design of Real-time Remote Monitoring System Based on OPC XML-DA–
By analyzing the difference between OPC XML-DA specification and OPC DA specification, an architecture of remote monitoring system is designed and the integrations of automation systems in plant floor with enterprise information management systems is realized.
- Neural Network Fuzzy-PID for a Class of Typical Systems with Large Time-varying Time Delay and its Application–
By use of neural network technique and fuzzy logic theory, a novel intelligent PID controller for a class of typical systems with large time-varying time delay is developed.
- A New Method of Storing and Querying Historical Data in SCADA–
A rapid method to take microsecond to store and query historical data is proposed and has been applied to the commercial SCADA system, which has a good efficiency in storing and querying compared with other products.
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- Realization of CIPS for Pulp and Paper Mill–
System integrating technologies and engineering application schemes are developed and integrated computer network is used to construct the management information system of a large pulp and paper mill that got the economic benifit of 2 millions Yuan.
- The design and implementation of axletree automatic manufacture monitor and control system based on CAN field bus–
Taking the Axletree automatic manufacture pipelining as the object, the real time, high performance and stable monitor and control system is developed.
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- Multiple-model predictive control of uncertain linear systems–
A multiple-model predictive control strategy is studied, which is based on a new model switching method that combines multiple- model switching principle and predictive control method, and can be applied to the linear system with large model uncertainty.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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