Analysis of the joint detection capability of the SMILE satellite and EISCAT-3D radar

The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter Sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.

Target Detection on Water Surfaces Using Fusion of Camera and LiDAR Based Information

To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle(USV)perception,this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection.Firstly,the visual recognition component employs an improved YOLOv7 algorithmbased on a self-built dataset for the detection of water surface targets.This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure,addressing the problemof excessive redundant information during feature extraction in the original YOLOv7 network model.Simultaneously,this modification simplifies the computational burden of the detector,reduces inference time,and maintains accuracy.Secondly,to tackle the issue of sample imbalance in the self-built dataset,slide loss function is introduced.Finally,this paper replaces the original Complete Intersection over Union(CIoU)loss function with the Minimum Point Distance Intersection over Union(MPDIoU)loss function in the YOLOv7 algorithm,which accelerates model learning and enhances robustness.To mitigate the problem of missed recognitions caused by complex water surface conditions in purely visual algorithms,this paper further adopts the fusion of LiDAR and camera data,projecting the threedimensional point-cloud data from LiDAR onto a two-dimensional pixel plane.This significantly reduces the rate of missed detections for water surface targets.

Microwave-induced thermoacoustic imaging of joints

Due to the complexity of joint structures and the diversity of disorders in the joints,the diagnosis of joint diseases is challenging.Current clinical diagnostic techniques for evaluating joint diseases,such as arthritis,have strengths and weaknesses.New imaging techniques need to be developed for the diagnosis or auxiliary diagnosis of arthritis.As an emerging nonintrusive low-cost imaging method,microwave-induced thermoacoustic imaging(TAI)can present tissue morphology while providing the tissue microwave energy absorption density distribution related to dielectric properties.TAI is currently in development to potentially visualize joint anatomic structures and to detect arthritis.Here,we offer a mini review to summarize the status of research on TAI of joints and present an outlook to the future development of TAI in the detection of joint diseases.

Low-Complexity Joint Channel Estimation and Symbol Detection for OFDMA Systems

In this paper,we propose a joint channel estimation and symbol detection(JCESD)algorithm relying on message-passing algorithms(MPA)for orthogonal frequency division multiple access(OFDMA)systems.The channel estimation and symbol detection leverage the framework of expectation propagation(EP)and belief propagation(BP)with the aid of Gaussian approximation,respectively.Furthermore,to reduce the computation complexity involved in channel estimation,the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula.Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%,compared with the traditional linear minimum mean square error(LMMSE)algorithm,and can approach to the bit error rate(BER)performance bound of perfectly known channel state information within 0.1 dB.

End-to-End Joint Multi-Object Detection and Tracking for Intelligent Transportation Systems

Environment perception is one of the most critical technology of intelligent transportation systems(ITS).Motion interaction between multiple vehicles in ITS makes it important to perform multi-object tracking(MOT).However,most existing MOT algorithms follow the tracking-by-detection framework,which separates detection and tracking into two independent segments and limit the global efciency.Recently,a few algorithms have combined feature extraction into one network;however,the tracking portion continues to rely on data association,and requires com‑plex post-processing for life cycle management.Those methods do not combine detection and tracking efciently.This paper presents a novel network to realize joint multi-object detection and tracking in an end-to-end manner for ITS,named as global correlation network(GCNet).Unlike most object detection methods,GCNet introduces a global correlation layer for regression of absolute size and coordinates of bounding boxes,instead of ofsetting predictions.The pipeline of detection and tracking in GCNet is conceptually simple,and does not require compli‑cated tracking strategies such as non-maximum suppression and data association.GCNet was evaluated on a multivehicle tracking dataset,UA-DETRAC,demonstrating promising performance compared to state-of-the-art detectors and trackers.

Digital image processing-based automatic detection algorithm of cross joint trace and its application in mining roadway excavation practice

This paper proposes a digital image processing-based detection algorithm for cross joint traces of coal roadway heading face.Initially,the acquired images were preprocessed,i.e.,adaptive correction was conducted for non-uniform illumination images based on the 2D gamma function.The edge detection algorithm was then applied to extract the edges of the structural plane,followed by the filtration of the non-structural plane noises.Moreover,the Hough transform algorithm was applied to extract the linear edges;finally,the edges were locally connected in accordance with the angle and distance criteria.The experimental results show that this algorithm can be used to reduce the noise caused by non-uniform illumination and avoid the mutual interference of multi-scale edges,so as to effectively extract the traces of the cross joint.Furthermore,Q-system and rock mass rating(RMR),were applied to conduct a quantitative evaluation on the stand-up time of unsupported roof in the four test images.The Q-system quality scores are 26.7,43.3,3.1,and 6.7,and the RMR quality scores are 56.84,58.73,48.42,and 51.42,respectively.The stand-up time of unsupported roofs with a span of 4.6 m are 30,36,7.7 and 14 d,respectively.

VMMAO-YOLO:an ultra-lightweight and scale-aware detector for real-time defect detection of avionics thermistor wire solder joints

The quality of the exposed avionics solder joints has a significant impact on the stable operation of the inorbit spacecrafts.Nevertheless,the previously reported inspection methods for multi-scale solder joint defects generally suffer low accuracy and slow detection speed.Herein,a novel real-time detector VMMAO-YOLO is demonstrated based on variable multi-scale concurrency and multi-depth aggregation network(VMMANet)backbone and“one-stop”global information gather-distribute(OS-GD)module.Combined with infrared thermography technology,it can achieve fast and high-precision detection of both internal and external solder joint defects.Specifically,VMMANet is designed for efficient multi-scale feature extraction,which mainly comprises variable multi-scale feature concurrency(VMC)and multi-depth feature aggregation-alignment(MAA)modules.VMC can extract multi-scale features via multiple fix-sized and deformable convolutions,while MAA can aggregate and align multi-depth features on the same order for feature inference.This allows the low-level features with more spatial details to be transmitted in depth-wise,enabling the deeper network to selectively utilize the preceding inference information.The VMMANet replaces inefficient highdensity deep convolution by increasing the width of intermediate feature levels,leading to a salient decline in parameters.The OS-GD is developed for efficacious feature extraction,aggregation and distribution,further enhancing the global information gather and deployment capability of the network.On a self-made solder joint image data set,the VMMAOYOLO achieves a mean average precision mAP@0.5 of 91.6%,surpassing all the mainstream YOLO-series models.Moreover,the VMMAO-YOLO has a body size of merely 19.3 MB and a detection speed up to 119 frame per second,far superior to the prevalent YOLO-series detectors.

Oil Spill Management in Nigeria: SWOT Analysis of the Joint Investigation Visit (JIV) Process

The Joint Investigation Visit (JIV) process of the National Oil Spill Detection and Response Agency (NOSDRA) have been analysed using the Strength, Weakness, Opportunity and Threat (SWOT) methodology. The oil spill Joint Investigation Visit (JIV) is empowered by the Oil Spill Recovery, Clean-up, Remediation and Damage Assessment Reulations, 2011 Section 5. The strength of the JIV process lies within its participatory nature and the well defined legal structure of the process. The oil spill Joint Investigation Visit process in Nigeria has several weaknesses—lack of independence and oversight, lack of technical competence on the part of regulatory bodies, lack of technical competence on the part of community representative, lack of transparency on the part of oil companies, lack of general procedure for determining the actual cause of spill, lack of general procedure for determining the actual volume of oil spilled, determination on the size of the impacted area and exclusion of women from the JIV Process. The JIV process for oil spill presents a number of opportunities such as;increasing community awareness, growing consciousness through Non Governmental Organisations (NGOs) and capacity building of stakeholders. Possible threats to the JIV process include;poor governance and corruption, manipulation of the Process by the spiller through the start date of an oilspill and obvious lack of transparency. Improved effectiveness of the JIV process will depend on strengthening of government agency coordination, integrated decision-making adequate training to various stakeholders and supporting infrastructure for purposeful monitoring and enforcement.

Significance of combined detection of serum 25(OH)D3, hsa-miR-17-5p and HCV-RNA in the diagnosis of hepatitis C disease

Objective: Significance of combined detection of serum 25(OH)D3, hsa-miR-17-5p and HCV-RNA in diagnosis of hepatitis C disease. Methods: A total of 52 patients with benign ovarian tumor resection were selected from April 2016 to April 2018 in our hospital. We paid attention to the implementation of perioperative nursing intervention, and observed the prognosis and the occurrence of adverse reactions. Results: The expression of hsa-mir-17-5p in the observation group was significantly higher than that in the control group, the expression of 25(OH)D3 was lower than that in the control group, the expression of hsa-mir-17-5p in the HCV-RNA positive group was higher than that in the HCV-RNA negative group, and the expression of 25(OH) D3 was lower than that in the HCV-RNA negative group. The expression of HCV-RNA in the observation group was positively and negatively correlated with the expression of 25(OH) D3 and hsa-mir-17-5p in the 25(OH)D3 and the critical values of serum 25 (OH)D3, hsa-mir-17-5p and HCV-RNA were 24.23 ug/L, 1.89 relative expression and 1.22 × 103 IU/mL, respectively. The area of AUC detected by hsa-miR-17-5p+ 25 (OH) D3+25(OH)D3 is larger than that detected separately. Conclusion: The combined detection of serum 25(OH)D3, hsa-mir-17-5p and HCV-RNA has high diagnostic efficiency and sensitivity for hepatitis C. It is suggested that they be used in clinical practice.

Automatic Feature Point Detection and Tracking of Human Actions in Time-of-flight Videos

Detecting feature points on the human body in video frames is a key step for tracking human movements. There have been methods developed that leverage models of human pose and classification of pixels of the body image. Yet, occlusion and robustness are still open challenges. In this paper, we present an automatic, model-free feature point detection and action tracking method using a time-of-flight camera. Our method automatically detects feature points for movement abstraction. To overcome errors caused by miss-detection and occlusion, a refinement method is devised that uses the trajectory of the feature points to correct the erroneous detections. Experiments were conducted using videos acquired with a Microsoft Kinect camera and a publicly available video set and comparisons were conducted with the state-of-the-art methods. The results demonstrated that our proposed method delivered improved and reliable performance with an average accuracy in the range of 90 %.The trajectorybased refinement also demonstrated satisfactory effectiveness that recovers the detection with a success rate of 93.7 %. Our method processed a frame in an average time of 71.1 ms.

Establishing minimum clinically important difference values for the Patient-Reported Outcomes Measurement Information System Physical Function, hip disability and osteoarthritis outcome score for joint reconstruction, and knee injury and osteoarthritis out

AIM To establish minimum clinically important difference(MCID) for measurements in an orthopaedic patient population with joint disorders.METHODS Adult patients aged 18 years and older seeking care for joint conditions at an orthopaedic clinic took the Patient-Reported Outcomes Measurement Information System Physical Function(PROMIS~? PF) computerized adaptive test(CAT), hip disability and osteoarthritis outcome score for joint reconstruction(HOOS JR), and the knee injury and osteoarthritis outcome score for joint reconstruction(KOOS JR) from February 2014 to April 2017. MCIDs were calculated using anchorbased and distribution-based methods. Patient reports of meaningful change in function since their first clinic encounter were used as an anchor.RESULTS There were 2226 patients who participated with a mean age of 61.16(SD = 12.84) years, 41.6% male, and 89.7% Caucasian. Mean change ranged from 7.29 to 8.41 for the PROMIS~? PF CAT, from 14.81 to 19.68 for the HOOS JR, and from 14.51 to 18.85 for the KOOS JR. ROC cut-offs ranged from 1.97-8.18 for the PF CAT, 6.33-43.36 for the HOOS JR, and 2.21-8.16 for the KOOS JR. Distribution-based methods estimated MCID values ranging from 2.45 to 21.55 for the PROMIS~? PF CAT; from 3.90 to 43.61 for the HOOS JR, and from 3.98 to 40.67 for the KOOS JR. The median MCID value in the range was similar to the mean change score for each measure and was 7.9 for the PF CAT, 18.0 for the HOOS JR, and 15.1 for the KOOS JR.CONCLUSION This is the first comprehensive study providing a wide range of MCIDs for the PROMIS? PF, HOOS JR, and KOOS JR in orthopaedic patients with joint ailments.

Test analysis of detection of damage to a complicated spatial model structure

A two-stage damage detection approach is proposed and experimentally demonstrated on a complicated spatial model structure with a limited number of measurements. In the experiment,five known damage patterns,including 3 brace damage cases and 2 joint damage cases,were simulated by removing braces and weakening beam鈥揷olumn connections in the structure. The limited acceleration response data generated by hammer impact were used for system identification,and modal parameters were extracted by using the eigensystem realization algorithm. In the first stage,the possible damaged locations are determined by using the damage index and the characteristics of the analytical model itself,and the extent of damage for those substructures identified at stage I is estimated in the second stage by using a second-order eigen-sensitivity approximation method. The main contribution of this paper is to test the two-stage method by using the real dynamic data of a complicated spatial model structure with limited sensors. The analysis results indicate that the two-stage approach is ableto detect the location of both damage cases,only the severity of brace damage cases can be assessed,and the reasonable analytical model is critical for successful damage detection.

An adaptive waveform-detection threshold joint optimization method for target tracking

The joint optimization of detection threshold and waveform parameters for target tracking which comes from the idea of cognitive radar is investigated for the modified probabilistic data association(MPDA)filter.The transmitted waveforms and detection threshold are adaptively selected to enhance the tracking performance.The modified Riccati equation is adopted to predict the error covariance which is used as the criterion function,while the optimization problem is solved through the genetic algorithm(GA).The detection probability,false alarm probability and measurement noise covariance are all considered together,which significantly improves the tracking performance of the joint detection and tracking system.Simulation results show that the proposed adaptive waveform-detection threshold joint optimization method outperforms the adaptive threshold method and the fixed parameters method,which will reduce the tracking error.The average reduction of range error between the adaptive joint method and the fixed parameters method is about 0.6 m,while that between the adaptive joint method and the adaptive threshold only method is about 0.3 m.Similar error reduction occurs for the velocity error and acceleration error.

Ping-pong effects study in PIC turbo joint detection for TDD CDMA

A kind of turbo joint detection scheme based on parallel interference cancellation （PIC） is studied; then, the eigenvalues of iteration matrix is deeply analyzed for studying the ping-pong effects in PIC JD and the corresponding compensation approach is introduced. Finally, the proposed algorithm is validated through computer simulation in TDD CDMA uplink transmission. The result shows that the ping-pong effects are almost avoided completely in the presence of the compensation scheme, and system performance is greatly improved.

Symbols detection for frequency-selective V-BLAST OFDM systems

As the combining form of the orthogonal frequency-division multiplexing (OFDM) technique and the vertical Bell Labs layered space-time (V-BLAST) architecture, the V-BLAST OFDM system can better meet the demand of next-generation (NextG) broadband mobile wireless multimedia communications. The symbols detection problem of the V-BLAST OFDM system is investigated under the frequency-selective fading environment. The joint space-frequency demultiplexing operation is proposed in the V-BLAST OFDM system. Successively, one novel half-rate rotational invariance joint space-frequency coding scheme for the V-BLAST OFDM system is proposed. By elegantly exploiting the above rotational invariance property, we derive one direct symbols detection scheme without knowing channels state information (CSI) for the frequency-selective V-BLAST OFDM system. Extensive simulation results demonstrate the validity of the novel half-rate rotational invariance joint space-frequency coding scheme and the performance of the direct symbols detection scheme.

Joint Detection for Image Transmission Based on Schur Algorithm over Wireless Sensor Network

To achieve much efficient multimedia transmission over an error-prone wireless network, there are still some problem must to be solved, especially in energy limited wireless sensor network. In this paper, we propose a joint detection based on Schur Algorithm for image wireless transmission over wireless sensor network. To eliminate error transmissions and save transmission energy, we combine Schur algorithm with joint dynamic detection for wireless transmission of JPEG 2000 encoded image which we proposed in [1]. Schur algorithm is used to computing the decomposition of system matrix to decrease the computational complexity. We de-scribe our transmission protocol, and report on its performance evaluation using a simulation testbed we have designed for this purpose. Our results clearly indicate that our method could approach efficient images transmission in wireless sensor network and the transmission errors are significantly reduced when compared to regular transmissions.

Diagnostic efficacy of combined detection of different tumor markers for primary hepatic carcinoma

Objective:To explore the clinical diagnostic value of combined detection of different tumor markers for primary hepatic carcinoma, and to provide the reference for the clinical diagnosis. Methods: 72 patients who were diagnosed with primary hepatic carcinoma were collected as observation group, 65 patients with benign liver disease as benign liver disease group and 80 cases of health examination as healthy control group, the contents of tumor markers alpha fetoprotein(AFP), carcinoembryonic antigen(CEA), carbohydrate antigen-199(CA199), carbohydrate antigen-125(CA125) and carbohydrate antigen-153(CA153) were determined by electrochemiluminescence in all subjects, then the results of five kinds of tumor markers and the positive rates of each index between the two groups were compared, the diagnostic value of separate and combined detection of different tumor markers in primary hepatic carcinoma were analyzed.Results: The values of AFP, CA199 and CA153 in the observation group were higher than the benign liver disease group, the values of AFP, CEA, CA199, CA125 and CA153 in the observation group were higher than the control group, the values of CA199 and CA125 in the benign liver disease group were higher than the control group, the differences were statistically significant (P<0.05). The positive rates of AFP, CEA, CA199 and CA153 in the observation group were higher than the benign liver disease group, the positive rates of AFP, CEA, CA199 and CA125 in the observation group were higher than the control group, the positive rates of AFP, CEA, CA199 and CA125 in the benign liver disease group were higher than the control group, the differences were statistically significant (P<0.05). The sensitivity of combined detection of all indicators for primary hepatic carcinoma was 86.4%, specificity, correct index, misdiagnosis rate and missed diagnosis rate were 86.4%, 89.2%, 75.6%, 13.6% and 10.8% respectively, and the combined detection was higher than the correct index of each index.Conclusion: Combined detection of serum tumor markers AFP, CEA, CA199, CA125 and CA153 can improve the sensitivity and specificity of diagnosis of primary hepatic carcinoma, it has better diagnostic value for primary hepatic carcinoma.

LDPC Coding Scheme for Improving the Reliability of Multi-Level-Cell NAND Flash Memory in Radiation Environments

Utilizing commercial off-the-shelf(COTS) components in satellites has received much attention due to the low cost. However, commercial memories suffer severe reliability problems in radiation environments. This paper studies the low-density parity-check(LDPC) coding scheme for improving the reliability of multi-level-cell(MLC) NAND Flash memory in radiation environments. Firstly, based on existing physical experiment works, we introduce a new error model for heavyion irradiations; secondly, we explore the optimization of writing voltage allocation to maximize the capacity of the storage channel; thirdly, we design the degree distribution of LDPC codes that is specially suitable for the proposed model; finally, we propose a joint detection-decoding scheme based on LDPC codes, which estimates the storage channel state and executes an adaptive log-likelihood ratio(LLR) calculation to achieve better performance. Simulation results show that, compared with the conventional LDPC coding scheme, the proposed scheme may almost double the lifetime of the MLC NAND Flash memory in radiation environments.

Delivery Invoice Information Classification System for Joint Courier Logistics Infrastructure

With the growth of the online market,demand for logistics and courier cargo is increasing rapidly.Accordingly,in the case of urban areas,road congestion and environmental problems due to cargo vehicles are mainly occurring.The joint courier logistics system,a plan to solve this problem,aims to establish an efficient logistics transportation system by utilizing one joint logistics delivery terminal by several logistics and delivery companies.However,several courier companies use different types of courier invoices.Such a system has a problem of information data transmission interruption.Therefore,the data processing process was systematically analyzed,a practically feasible methodology was devised,and delivery invoice information processing standards were established for this.In addition,the importance of this paper can be emphasized in terms of data processing in the logistics sector,which is expected to grow rapidly in the future.The results of this study can be used as basic data for the implementation of the logistics joint delivery terminal system in the future.And it can be used as a basis for securing the operational reliability of the joint courier logistics system.