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Multi-Level Parallel Network for Brain Tumor Segmentation

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 741-757页

作者： Juhong tie Hui Peng School of Software Engineering Chengdu University of Information TechnologyChengdu610225China

Accurate automatic segmentation of gliomas in various sub-regions,including peritumoral edema,necrotic core,and enhancing and non-enhancing tumor core from 3D multimodal MRI images,is challenging because of its highly heterogeneous appearance and *** convolution neural networks(CNNs)have recently improved glioma segmentation ***,extensive down-sampling such as pooling or stridden convolution in CNNs significantly decreases the initial image resolution,resulting in the loss of accurate spatial and object parts information,especially information on the small sub-region tumors,affecting segmentation ***,this paper proposes a novel multi-level parallel network comprising three different level parallel subnetworks to fully use low-level,mid-level,and high-level information and improve the performance of brain tumor *** also introduce the Combo loss function to address input class imbalance and false positives and negatives imbalance in deep *** proposed method is trained and validated on the BraTS 2020 training and validation *** the validation dataset,ourmethod achieved a mean Dice score of 0.907,0.830,and 0.787 for the whole tumor,tumor core,and enhancing tumor core,*** with state-of-the-art methods,the multi-level parallel network has achieved competitive results on the validation dataset.

关键词： Convolution neural network brain tumor segmentation parallel network

Rupture of a giant jejunal mesenteric cystic lymphangioma misdiagnosed as ovarian torsion: A case report

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World Journal of Clinical Cases 2024年第4期12卷 847-852页

作者： Jing Xu tie-Feng Lv Department of Hepatopathy Hangzhou Xixi HospitalHangzhou 310023Zhejiang ProvinceChina

BACKGROUND Cystic lymphangioma is a rare benign tumor that affects the lymphatic *** lymphangiomas in the small bowel are extremely *** SUMMARY We present a 21-year-old female patient who complained of abdominal *** diagnosis of ovarian torsion was suspected after abdominopelvic unenhanced computed tomography and ultrasound revealed a large cyst in contact with the bladder,ovary,and *** patient underwent emergency laparotomy per-formed by gynecologists,but it was discovered that the cystic tumor originated from the *** surgeons were then called in to perform a *** examination confirmed the diagnosis of cystic lymphangioma of the *** patient had an uneventful postoperative *** Mesenteric lymphangiomas can cause abdominal pain,and imaging techniques can help determine their characteristics,location,and *** surgical excision and pathological examination are considered the standard treatment and diagnostic method.

关键词： Rupture Jejunum Mesenteric cystic lymphangioma Ovarian torsion Surgical excision Pathological examination Case report

Characteristics of Particulate Matter Emissions for Low-Sulfur Heavy Oil Used in Low-Speed Two-Stroke Diesel Engines of Ocean-Going Ships

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Journal of Thermal Science 2024年第2期33卷 739-750页

作者： WU Gang MA Qianli WEI Lijiang JIANG Guohe WANG Tengfei LI tie Merchant Marine College Shanghai Maritime UniversityShanghai201306China State Key Laboratory of Ocean Engineering Shanghai Jiao Tong UniversityShanghai200240China

In this work,particulate matter(PM) emissions from a large two-stroke,low-speed marine diesel engine were investigated when the engine was operated with low-sulfur heavy fuel oil(HFO) at various *** samples were collected in situ from the engine exhaust to determine the detailed physical and chemical *** nanostructure and morphology of the nanoparticles were analyzed using transmission electron microscopy images(TEM).The results show that volatile organic carbon(OC) accounts for more than 80% in the HFO particles and leads to an increase in particle *** thermodynamic conditions of a low-speed engine favor the behavior of capturing the soluble organic components.A large number of spherical char HFO particles with aerodynamic diameters of 0.2 μm-0.5 μm and a suspected inner metal core were *** two peak aerodynamic diameters of the HFO nanoparticles are 15 nm and 86 *** morphological differences among the HFO nanoparticles in varied engine conditions represent the formation process from primary nascent particles to mature graphitized particles caused by *** above study will be valuable for understanding the characteristics of PM emissions from low-sulfur HFO to achieve the ship PM emissions reduction target.

关键词： low-speed diesel engine maritime regulations heavy fuel oil TEM particles size and distribution

Pushing the frontiers: Chip-based detection based on micro-and nano-structures

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Chinese Chemical Letters 2024年第4期35卷 86-98页

作者： Meihui Liu Xinyuan Zhou Xiao Li Zhenjie Xue tie Wang Tianjin Key Laboratory of Life and Health Detection Life and Health Intelligent Research InstituteTianjin University of TechnologyTianjin 300384China

Changes in trace substances in human metabolites, which are related to disease processes and health status, can serve as chemical markers for disease diagnosis and symptom monitoring. Real-time online detection is an inevitable trend for the future of health monitoring, and the construction of chips for detection faces major challenges. The response of sensors often fails to meet the requirements for chipbased detection of trace substances due to the low efficiency of interfacial heterogeneous reactions, necessitating a rational design approach for micro-and nano-structures to improve sensor performance with respect to sensitivity and detection limits. This review focuses on the influence of micro-and nanostructures that used in chip on sensing. Firstly, this review categorizes sensors into chemiresistors, electrochemical sensors, fluorescence sensors, and surface enhanced Raman scattering(SERS) sensors based on their sensing principle, which have significant applications in disease diagnosis. Subsequently, commencing from the application requirements in the field of sensing, this review focuses on the different structures of nanoparticle(NP) assemblies, including wire, layered, core-shell, hollow, concave and deformable structures. These structures change in the size, shape, and morphology of conventional structures to achieve characteristics such as ordered alignment, high specific surface area, space limitation,vertical diffusion, and swaying behavior with fluid, thereby addressing issues such as poor signal transmission efficiency, inadequate adsorption and capture capacity, and slow mass transfer speed during sensing. Finally, the design direction of micro-and nano-structures, and possible obstacles and solutions to promote chip-based detection have been discussed. It is hope that this article will inspire the exploration of interface micro-and nano-structures modulated sensing methods.

关键词： Chip-based detection Micro-and nano-structures Real-time online detection Sensing Health monitoring

Cognitive Jammers Assisted Covert Communication in Cognitive Radio Networks

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China Communications 2024年第9期21卷 75-89页

作者： Liu Changjun Shi Jia tie Zhuangzhuang Wang Yongchao The State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071China

In this work,we investigate the covert communication in cognitive radio(CR)networks with the existence of multiple cognitive jammers(CJs).Specifically,the secondary transmitter(ST)helps the primary transmitter(PT)to relay information to primary receiver(PR),as a reward,the ST can use PT's spectrum to transmit private information against the eavesdropper(Eve)under the help of one selected cognitive jammer(CJ).Meanwhile,we propose three jammer-selection schemes,namely,link-oriented jammer selection(LJS),min-max jammer selection(MMJS)and random jammer selection(RJS).For each scheme,we analyze the average covert throughput(ACT)and covert outage probability(COP).Our simulation results show that CJ is helpful to ST's covert communication,the expected minimum detection error probability and ACT can be significantly improved with the increase of false alarm of ***,the LJS scheme achieves best performance in ACT and COP,followed by RJS scheme,and MMJS scheme shows the worst performance.

关键词： cognitive jammer cognitive radio covert communication performance analysis

A real-time intelligent lithology identification method based on a dynamic felling strategy weighted random forest algorithm

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Petroleum Science 2024年第2期21卷 1135-1148页

作者： tie Yan Rui Xu Shi-Hui Sun Zhao-Kai Hou Jin-Yu Feng School of Petroleum Engineering Northeast Petroleum UniversityDaqing163318HeilongjiangChina Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya572025HainanChina

Real-time intelligent lithology identification while drilling is vital to realizing downhole closed-loop drilling. The complex and changeable geological environment in the drilling makes lithology identification face many challenges. This paper studies the problems of difficult feature information extraction,low precision of thin-layer identification and limited applicability of the model in intelligent lithologic identification. The author tries to improve the comprehensive performance of the lithology identification model from three aspects: data feature extraction, class balance, and model design. A new real-time intelligent lithology identification model of dynamic felling strategy weighted random forest algorithm(DFW-RF) is proposed. According to the feature selection results, gamma ray and 2 MHz phase resistivity are the logging while drilling(LWD) parameters that significantly influence lithology identification. The comprehensive performance of the DFW-RF lithology identification model has been verified in the application of 3 wells in different areas. By comparing the prediction results of five typical lithology identification algorithms, the DFW-RF model has a higher lithology identification accuracy rate and F1 score. This model improves the identification accuracy of thin-layer lithology and is effective and feasible in different geological environments. The DFW-RF model plays a truly efficient role in the realtime intelligent identification of lithologic information in closed-loop drilling and has greater applicability, which is worthy of being widely used in logging interpretation.

关键词： Intelligent drilling Closed-loop drilling Lithology identification Random forest algorithm Feature extraction

Machine learning-based performance predictions for steels considering manufacturing process parameters:a review

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Journal of Iron and Steel Research International 2024年第7期31卷 1555-1581页

作者： Wei Fang Jia-xin Huang tie-xu Peng Yang Long Fu-xing Yin Tianjin Key Laboratory of Materials Laminating Fabrication and Interface Control Technology School of Materials Science and EngineeringHebei University of TechnologyTianjin 300132China Institute of New Materials Guangdong Academy of ScienceGuangzhou 510651GuangdongChina

Steels are widely used as structural materials,making them essential for supporting our lives and ***,further improving the comprehensive properties of steel through traditional trial-and-error methods becomes challenging due to the continuous development and numerous processing parameters involved in steel *** address this challenge,the application of machine learning methods becomes crucial in establishing complex relationships between manufacturing processes and steel *** review begins with a general overview of machine learning methods and subsequently introduces various performance predictions in steel *** classification of performance pre-diction was used to assess the current application of machine learning model-assisted *** important issues,such as data source and characteristics,intermediate features,algorithm optimization,key feature analysis,and the role of environmental factors,were summarized and *** insights will be beneficial and enlightening to future research endeavors in this field.

关键词： Steel Manufacturing process Machine learning Performance prediction Algorithm

Determination of ice jam thickness—A new approach

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Journal of Hydrodynamics 2024年第3期36卷 570-581页

作者： Jun Wang Lian-sheng Sang Fei-hu Song tie-jie Cheng Jueyi Sui School of Civil and Water Engineering Hefei University of TechnologyHefei230009China School of Engineering University of Northern British ColumbiaPrince GeorgeCanada

In winter,rivers in cold regions often experience flood disasters resulted from ice jams or ice *** of the variation of ice jam thickness and water level during an ice jammed period are not only a practical need for ice prevention to avoid disaster and plan water resource,but also essential for the development of any mathematical model for predicting the evolution of ice *** far,some equations based on the energy equation have been proposed to describe the relationship between ice jam thickness and water ***,in the derivation of these equations,the local head loss coefficient at the ice jam head and the riverbed slope factor were ***,those reported equations cannot be used to preciously describe the flow energy equation with ice jams and accurately calculate the ice jam thickness and water *** the present study,a more comprehensive theoretical model for hydraulic calculation of ice jam thickness has been derived by considering important and essential factors including riverbed slope and local head loss coefficient at the ice jam ***,based on the data collected from laboratory experiments of ice jam accumulation,the local head loss coefficient at the ice jam head has been calculated,and the empirical equation for calculating the local head loss coefficient has been established by considering flow Froude number and the ratio of ice discharge to flow *** results of this study not only provide a new reference for calculating ice jam thickness and water level,but also present a theoretical basis for accurate CFD simulation of ice jams.

关键词： Energy equation ice jam thickness local head loss coefficient ice jam head riverbed slope

Covert LEO Satellite Communication Aided by Generative Adversarial Network Based Cooperative UAV Jamming

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China Communications 2024年第9期21卷 27-39页

作者： Shi Jia Li Xiaomeng Liao Xiaomin tie Zhuangzhuang Hu Junfan School of Communication Engineering Xidian UniversityXi’an 710071China School of Information and Communications National University of Defense TechnologyWuhan 410073China

In this paper,we study the covert performance of the downlink low earth orbit(LEO)satellite communication,where the unmanned aerial vehicle(UAV)is employed as a cooperative *** maximize the covert rate of the LEO satellite transmission,a multi-objective problem is formulated to jointly optimize the UAV’s jamming power and *** practical consideration,we assume that the UAV can only have partial environmental information,and can’t know the detection threshold and exact location of the eavesdropper on the *** solve the multiobjective problem,we propose the data-driven generative adversarial network(DD-GAN)based method to optimize the power and trajectory of the UAV,in which the sample data is collected by using genetic algorithm(GA).Simulation results show that the jamming solution of UAV generated by DD-GAN can achieve an effective trade-off between covert rate and probability of detection errors when only limited prior information is obtained.

关键词： covert communication generative adversarial network LEO satellite UAV jammer