CT引导下Hook-wire定位辅助胸腔镜手术对早期肺癌患者的疗效分析

目的探讨CT引导下Hook-wire定位辅助胸腔镜手术对早期肺癌患者的疗效。方法选取92例早期肺癌患者,按随机数字表法分为两组,各46例。对照组行常规胸腔镜手术治疗,观察组行CT引导下Hook-wire定位辅助胸腔镜手术治疗。比较两组手术情况、创伤应激指标、肿瘤标志物水平及并发症。结果观察组手术时间、术后引流时间及住院时间为(138.52±10.52)min、(3.12±0.45)d、(10.35±1.25)d,短于对照组,术中出血量为(105.41±12.36)ml,少于对照组,差异有统计学意义(P<0.05);观察组术后皮质醇(Cor)、去甲肾上腺素(NE)、C反应蛋白(CRP)水平分别为(118.52±8.36)ng/ml、(185.93±14.52)ng/L、(32.41±4.25)mg/L,低于对照组,差异有统计学意义(P<0.05);观察组术后癌胚抗原(CEA)、细胞角蛋白19片段抗原21-1(CYFRA21-1)、糖类抗原125(CA125)水平为(8.96±1.15)ng/ml、(3.88±0.42)ng/ml、(12.63±1.54)U/ml,低于对照组,并发症少于对照组,差异有统计学意义(P<0.05)。结论CT引导下Hook-wire定位辅助胸腔镜手术治疗早期肺癌效果更佳,可减轻手术创伤,降低创伤应激反应,加快肿瘤标志物复常,减少并发症发生。

Collaborative positioning for swarms:A brief survey of vision,LiDAR and wireless sensors based methods

As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.

术前运用Hook-wire与医用胶定位行胸腔镜手术切除孤立性肺小结节的效果

目的探讨术前运用Hook-wire与医用胶定位方式行胸腔镜手术(VATS)切除孤立性肺小结节(SPN)的效果。方法选取2020年1月至2022年2月福州市长乐区医院收治的81例行VATS切除SPN的患者作为研究对象,按照随机数字表法分为观察组(n=41)与对照组(n=40)。对照组术前予以Hook-wire定位,观察组术前予以医用胶定位,比较两组定位和手术情况、定位相关并发症发生率及病理结果。结果两组定位时间、穿刺深度比较差异无统计学意义;观察组定位成功率高于对照组,术中结节切除时间短于对照组,定位费用少于对照组,差异有统计学意义(P<0.05)。观察组定位相关并发症发生率为24.39%,低于对照组的47.50%,差异有统计学意义(P<0.05)。两组良性、非典型增生、微浸润癌、浸润性癌、原位癌、转移瘤病理结果比较差异无统计学意义。结论对VATS切除SPN术前运用医用胶定位可提高定位成功率,缩短手术时间,节省手术费用,降低定位相关并发症发生率,且不影响病理诊断结果。

Adaptive H_(∞)Filtering Algorithm for Train Positioning Based on Prior Combination Constraints

To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

An improved particle filter indoor fusion positioning approach based on Wi-Fi/PDR/geomagnetic field

The existing indoor fusion positioning methods based on Pedestrian Dead Reckoning(PDR)and geomagnetic technology have the problems of large initial position error,low sensor accuracy,and geomagnetic mismatch.In this study,a novel indoor fusion positioning approach based on the improved particle filter algorithm by geomagnetic iterative matching is proposed,where Wi-Fi,PDR,and geomagnetic signals are integrated to improve indoor positioning performances.One important contribution is that geomagnetic iterative matching is firstly proposed based on the particle filter algorithm.During the positioning process,an iterative window and a constraint window are introduced to limit the particle generation range and the geomagnetic matching range respectively.The position is corrected several times based on geomagnetic iterative matching in the location correction stage when the pedestrian movement is detected,which made up for the shortage of only one time of geomagnetic correction in the existing particle filter algorithm.In addition,this study also proposes a real-time step detection algorithm based on multi-threshold constraints to judge whether pedestrians are moving,which satisfies the real-time requirement of our fusion positioning approach.Through experimental verification,the average positioning accuracy of the proposed approach reaches 1.59 m,which improves 33.2%compared with the existing particle filter fusion positioning algorithms.

Synthetic Aperture Positioning: A Review

Obtaining precise position of interested emitters passively has wide applications in both civilian and military fields.Different from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been proposed.The method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted signals.The SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise ratio.This paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope analysis.Besides,the possible future outlook of SAP is considered.

Wireless Positioning:Technologies,Applications,Challenges,and Future Development Trends

The development of the fifth-generation(5G)mobile communication systems has entered the commercialization stage.5G has a high data rate,low latency,and high reliability that can meet the basic demands of most industries and daily life,such as the Internet of Things(IoT),intelligent transportation systems,positioning,and navigation.The continuous progress and development of society have aroused wide concern.Positioning accuracy is the core demand for the applications,especially in complex environments such as airports,warehouses,supermarkets,and basements.However,many factors also affect the accuracy of positioning in those environments,for example,multipath effects,non-line-of-sight,and clock synchronization errors.This paper provides a comprehensive review of the existing works about positioning for the future wireless network and discusses its key techniques and algorithms,as well as the current development and future directions.We first outline the current traditional positioning technologies and algorithms,which are discussed and analyzed with the relevant literature.In addition,we also discuss application scenarios for wireless localization.By comparing different positioning systems,the challenges and future development directions of existing wireless positioning systems are prospected.

Hybrid pedestrian positioning system using wearable inertial sensors and ultrasonic ranging

Pedestrian positioning system(PPS)using wearable inertial sensors has wide applications towards various emerging fields such as smart healthcare,emergency rescue,soldier positioning,etc.The performance of traditional PPS is limited by the cumulative error of inertial sensors,complex motion modes of pedestrians,and the low robustness of the multi-sensor collaboration structure.This paper presents a hybrid pedestrian positioning system using the combination of wearable inertial sensors and ultrasonic ranging(H-PPS).A robust two nodes integration structure is developed to adaptively combine the motion data acquired from the single waist-mounted and foot-mounted node,and enhanced by a novel ellipsoid constraint model.In addition,a deep-learning-based walking speed estimator is proposed by considering all the motion features provided by different nodes,which effectively reduces the cumulative error originating from inertial sensors.Finally,a comprehensive data and model dual-driven model is presented to effectively combine the motion data provided by different sensor nodes and walking speed estimator,and multi-level constraints are extracted to further improve the performance of the overall system.Experimental results indicate that the proposed H-PPS significantly improves the performance of the single PPS and outperforms existing algorithms in accuracy index under complex indoor scenarios.

A Combined Antenna Array Deployment with High Positioning Accuracy and Low Angular Measurement Error

In this paper,an antenna array composed of circular array and orthogonal linear array is proposed by using the design of long and short baseline“orthogonal linear array”and the circular array ambiguity resolution design of multi-group baseline clustering.The effectiveness of the antenna array in this paper is verified by sufficient simulation and experiment.After the system deviation correction work,it is found that in the L/S/C/X frequency bands,the ambiguity resolution probability is high,and the phase difference system error between each channel is basically the same.The angle measurement error is less than 0.5°,and the positioning error is less than 2.5 km.Notably,as the center frequency increases,calibration consistency improves,and the calibration frequency points become applicable over a wider frequency range.At a center frequency of 11.5 GHz,the calibration frequency point bandwidth extends to 1200 MHz.This combined antenna array deployment holds significant promise for a wide range of applications in contemporary wireless communication systems.

Accurate Source-Receiver Positioning Method for a High-Resolution Deep-Towed Multichannel Seismic Exploration System

The near-seabed multichannel seismic exploration systems have yielded remarkable successes in marine geological disaster assessment,marine gas hydrate investigation,and deep-sea mineral exploration owing to their high vertical and horizontal resolution.However,the quality of deep-towed seismic imaging hinges on accurate source-receiver positioning information.In light of existing technical problems,we propose a novel array geometry inversion method tailored for high-resolution deep-towed multichannel seismic exploration systems.This method is independent of the attitude and depth sensors along a deep-towed seismic streamer,accounting for variations in seawater velocity and seabed slope angle.Our approach decomposes the towed line array into multiline segments and characterizes its geometric shape using the line segment distance and pitch angle.Introducing optimization parameters for seawater velocity and seabed slope angle,we establish an objective function based on the model,yielding results that align with objective reality.Employing the particle swarm optimization algorithm enables synchronous acquisition of optimized inversion results for array geometry and seawater velocity.Experimental validation using theoretical models and practical data verifies that our approach effectively enhances source and receiver positioning inversion accuracy.The algorithm exhibits robust stability and reliability,addressing uncertainties in seismic traveltime picking and complex seabed topography conditions.

An improved positioning model of deep-seafloor datum point at large incidence angle

The inhomogeneous sound speed in seawater causes refraction of sound waves,and the elimination of the refraction effect is essential to the accuracy of underwater acoustic positioning.The raytracing method is an indispensable tool for effectively handling problems.However,this method has a conflict between localization accuracy and computational quantity.The equivalent sound speed profile(ESSP)method uses a simple sound speed profile(SSP)instead of the actual complex SSP,which can improve positioning precision but with residual error.The residual error is especially non-negligible in deep water and at large beam incidence angles.By analyzing the residual error of the ESSP method through a simulation,an empirical formula of error is presented.The data collected in the sailing circle mode(large incidence angle)of the South China Sea are used for verification.The experiments show that compared to the ESSP method,the improved algorithm has higher positioning precision and is more efficient than the ray-tracing method.

WiFi Indoor Positioning and Tracking Algorithm Based on Compressive Sensing and Sage-Husa Adaptive Kalman Filter

Aiming at the problem that the positioning accuracy of WiFi indoor positioning technology based on location fingerprint has not reached the requirements of practical application, a WiFi indoor positioning and tracking algorithm combining adaptive affine propagation (AAPC), compressed sensing (CS) and Kalman filter is proposed. In the off-line phase, AAPC algorithm is used to generate clustering fingerprints with optimal clustering effect performance;In the online phase, CS and nearest neighbor algorithm are used for position estimation;Finally, the Kalman filter and physical constraints are combined to perform positioning and tracking. By collecting a large number of real experimental data, it is proved that the developed algorithm has higher positioning accuracy and more accurate trajectory tracking effect.

Market Positioning Analysis of CJ Brand Fitness Equipment

CJ Health Technology Co.has been an export-oriented supplier of fitness equipment,boasting leading technology innovation and manufacturing capabilities.However,in the process of expanding into the domestic market,the challenges of unclear market positioning and lack of brand awareness have emerged as major obstacles.To address these issues,a SWOT analysis was conducted to explore a suitable market positioning strategy for the CJ brand.The analysis reveals that the market demand for commercial fitness equipment is relatively saturated,with fierce competition.In contrast,the home fitness market represents a new blue ocean with promising development opportunities for the CJ brand.Leveraging excellent product quality,stringent quality control measures,and innovation-driven cutting-edge technology,it is recommended that CJ brand fitness equipment target young customers aged between 25 and 35 years old.Additionally,vigorously developing the home fitness product line is proposed to capitalize on this burgeoning market segment.

CT引导下Hook-wire穿刺定位在肺部小结节胸腔镜手术中的应用效果

目的研究术前CT引导下肺部小结节Hook-wire穿刺定位在基层医院运用中的可行性、安全性。方法回顾性分析2021年1月1日至2022年12月31日在我院因肺部小结行术前CT引导穿刺定位行手术的患者,共计70例。对所有患者均实施CT引导下Hook-wire穿刺定位开展胸腔镜手术,对患者的手术穿刺情况、手术方式及相关手术指标变化情况进行观察与记录。结果70例患者中,69例术前定位在小结节附近2 cm内,1例因穿刺针从叶裂经过而出现偏差,70例穿刺定位均未穿刺入小结节内,部位穿刺深度(5 mm~2 cm),穿刺时间(4~8 min),气胸(7例),血胸(2例),穿刺部位略感胀痛;手术方式(胸腔镜下肺楔形切除48例,胸腔镜下肺段切除15例,胸腔镜下肺叶切除术7例),术中发现定位针均位于肺组织中未发现脱落,牵引线未发现断裂,术后病理(原位癌15例,微浸润腺癌42例,浸润腺癌13例),术后随访中穿刺部位无疼痛等不适。结论术前CT引导Hook-wire穿刺定位技术在基层医院胸腔镜手术中的运用安全、有效,完全满足基层医院胸外科医师开展肺部小结节的手术要求,对定位精度要求相对低、并发症少、患者疼痛轻、定位时间短、费用低,适合在基层医院中开展。

定位丝与Hook-wire在肺小结节胸腔镜术前定位中的应用比较

目的:比较定位丝与Hook-wire两种定位技术在肺小结节患者胸腔镜术前定位中的有效性和安全性。方法:回顾并分析119例胸腔镜术前计算机体层成像(computed tomography,CT)引导下经皮穿刺定位的肺小结节患者的临床资料,根据不同定位方法分为定位丝组(50例)和Hook-wire组(69例),比较两组间的结节位置、结节直径、结节至胸膜的距离、定位时间、定位成功率及并发症发生率的差异,对定位后并发症的相关因素进行logistic回归分析。结果:两组间的结节位置、结节直径、结节至胸膜的距离差异无统计学意义。定位丝组与Hook-wire组定位时间相近[16(14,19)min vs 16(14,18.5)min,t=-0.416,P=0.677]。定位丝组与Hook-wire组定位成功率相近(98.0%vs 94.2%,χ^(2)=1.038,P=0.397)。定位丝组总体并发症发生率低于Hook-wire组(16.0%vs 47.8%,χ^(2)=13.003,P<0.001),亚组分析中定位丝组的气胸(12.0%vs 27.5%,χ^(2)=4.217,P=0.044)、肺出血(4.0%vs 18.8%,χ^(2)=5.796,P=0.016)、局部疼痛(0.0%vs 8.7%,χ^(2)=4.579,P<0.001)的发生率均低于Hook-wire组。Logistic回归分析结果显示,不同的定位方法是本研究中肺小结节患者胸腔镜术前定位后是否有并发症的独立危险因素(OR=0.208,95%CI 0.085~0.507,P<0.001)。结论:定位丝法定位时间、定位成功率与Hook-wire法相近,但定位丝法较Hook-wire法并发症少,值得推广。

术前CT引导下Hook-wire定位与医用胶定位在磨玻璃结节为主的早期肺癌术中的应用效果比较

目的 对比术前CT引导下Hook-wire与医用胶定位在磨玻璃结节为主的早期肺癌手术切除中的应用效果。方法 回顾性分析83例以磨玻璃结节为主的早期肺癌切除术患者的临床资料,根据其术前结节定位方法将其分为Hook-wire组(CT引导下Hook-wire定位,n=30)与医用胶组(CT引导下医用胶定位,n=53),比较两组定位成功率、平均定位耗时、病灶精确切除率、病灶平均切除时间、定位相关并发症、术后住院时间等。结果 医用胶组与Hook-wire组平均定位耗时、结节切除耗时、术后住院时间及手术相关并发症发生率比较,差异无统计学意义(P>0.05),医用胶组定位成功率高于Hook-wire组,定位相关并发症发生率低于Hook-wire组,结节精准切除率高于Hook-wire组,差异均有统计学意义(P<0.05)。结论 相比于Hookwire,CT引导下医用胶定位GGN的效果更好,安全性更高。

肺结节定位针和Hook-wire在肺结节术前定位中的应用比较

目的:探讨术前CT引导下新型肺结节定位针和Hook-wire定位针在肺小结节胸腔镜切除术中的应用价值,为术前定位方法的选择提供更多循证证据。方法:回顾性分析2022年1月—2022年10月于天津医科大学总医院心胸外科接受胸腔镜手术治疗肺结节,并在术前接受肺结节定位的80例患者的临床资料,根据定位针种类不同分为Hook-wire组和新型肺结节定位针组。Hook-wire定位针组患者接受术前CT引导下肺结节Hook-wire定位,新型肺结节定位针组患者接受术前CT引导下肺结节定位,比较两组定位效果及患者预后情况。结果:新型肺结节定位针组的定位后疼痛评分和移位或脱钩发生率均明显低于Hook-wire组,差异有统计学意义(χ^(2)=-6.671;t=3.914,P<0.05)。结论:肺小结节胸腔镜切除术前采用CT引导新型肺结节定位针定位能有效降低钩丝移位或脱钩风险并减轻定位后疼痛。

5G Ultra-Dense Network Fingerprint Positioning Method Based on Matrix Completion

The problem of high-precision indoor positioning in the 5G era has attracted more and more attention.A fingerprint location method based on matrix completion(MC-FPL)is proposed for 5G ultradense networks to overcome the high costs of traditional fingerprint database construction and matching algorithms.First,a partial fingerprint database constructed and the accelerated proximal gradient algorithm is used to fill the partial fingerprint database to construct a full fingerprint database.Second,a fingerprint database division method based on the strongest received signal strength indicator is proposed,which divides the original fingerprint database into several sub-fingerprint databases.Finally,a classification weighted K-nearest neighbor fingerprint matching algorithm is proposed.The estimated coordinates of the point to be located can be obtained by fingerprint matching in a sub-fingerprint database.The simulation results show that the MC-FPL algorithm can reduce the complexity of database construction and fingerprint matching and has higher positioning accuracy compared with the traditional fingerprint algorithm.

Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

Electric vehicle charging identification and positioning is critically important to achieving automatic charging.In terms of the problem of automatic charging for electric vehicles,a dual recognition and positioning method based on deep learning is proposed.The method is divided into two parts:global recognition and localization and local recognition and localization.In the specific implementation process,the collected pictures of electric vehicle charging attitude are classified and labeled.It is trained with the improved YOLOv4 networkmodel and the corresponding detectionmodel is obtained.The contour of the electric vehicle is extracted by the BiSeNet semantic segmentation algorithm.The minimum external rectangle is used for positioning of the electric vehicle.Based on the location relationship between the charging port and the electric vehicle,the rough location information of the charging port is obtained.The automatic charging equipment moves to the vicinity of the charging port,and the camera near the charging gun collects pictures of the charging port.The model is detected by the Hough circle,the KM algorithmis used for featurematching,and the homography matrix is used to solve the attitude.The results show that the dual identification and location method based on the improved YOLOv4 algorithm proposed in this paper can accurately locate the charging port.The accuracy of the charging connection can reach 80%.It provides an effective way to solve the problems of automatic charging identification and positioning of electric vehicles and has strong engineering practical value.