Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion features.Therefore,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis task.Secondly,the LLM generates a global attention map based on localization.Finally,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion details.This paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.

Deep neural network based on multi-level wavelet and attention for structured illumination microscopy

Structured illumination microscopy(SIM)is a popular and powerful super-resolution(SR)technique in biomedical research.However,the conventional reconstruction algorithm for SIM heavily relies on the accurate prior knowledge of illumination patterns and signal-to-noise ratio(SNR)of raw images.To obtain high-quality SR images,several raw images need to be captured under high fluorescence level,which further restricts SIM’s temporal resolution and its applications.Deep learning(DL)is a data-driven technology that has been used to expand the limits of optical microscopy.In this study,we propose a deep neural network based on multi-level wavelet and attention mechanism(MWAM)for SIM.Our results show that the MWAM network can extract high-frequency information contained in SIM raw images and accurately integrate it into the output image,resulting in superior SR images compared to those generated using wide-field images as input data.We also demonstrate that the number of SIM raw images can be reduced to three,with one image in each illumination orientation,to achieve the optimal tradeoff between temporal and spatial resolution.Furthermore,our MWAM network exhibits superior reconstruction ability on low-SNR images compared to conventional SIM algorithms.We have also analyzed the adaptability of this network on other biological samples and successfully applied the pretrained model to other SIM systems.

Construction of a Multi-Level Strategic System for Cultivating Cultural Industry Management Talents in Colleges and Universities

Through SWOT(strengths,weaknesses,opportunities,and threats)and PEST(political,economic,social,and technological)analysis,this study discusses the construction of a multi-level strategic system for the cultivation of cultural industry management talents in colleges and universities.First of all,based on SWOT analysis,it is found that colleges and universities have rich educational resources and policy support,but they face challenges such as insufficient practical teaching and intensified international competition.External opportunities come from the rapid development of the cultivation of cultural industry management talents and policy promotion,while threats come from global market competition and talent flow.Secondly,PEST analysis reveals the key factors in the macro-environment:at the political level,the state vigorously supports the cultivation of cultural industry management talents;at the economic level,the market demand for cultural industries is strong;at the social level,the public cultural consumption is upgraded;at the technological level,digital transformation promotes industry innovation.On this basis,this paper puts forward a multi-level strategic system covering theoretical education,practical skill improvement,interdisciplinary integration,and international vision training.The system aims to solve the problems existing in talent training in colleges and universities and cultivate high-quality cultural industry management talents with theoretical knowledge,practical skills,and global vision,so as to adapt to the increasingly complex and diversified cultural industry management talents market demand and promote the long-term development of the industry.

Multi-level access control model for tree-like hierarchical organizations

An access control model is proposed based on the famous Bell-LaPadula （BLP） model.In the proposed model,hierarchical relationships among departments are built,a new concept named post is proposed,and assigning security tags to subjects and objects is greatly simplified.The interoperation among different departments is implemented through assigning multiple security tags to one post, and the more departments are closed on the organization tree,the more secret objects can be exchanged by the staff of the departments.The access control matrices of the department,post and staff are defined.By using the three access control matrices,a multi granularity and flexible discretionary access control policy is implemented.The outstanding merit of the BLP model is inherited,and the new model can guarantee that all the information flow is under control.Finally,our study shows that compared to the BLP model,the proposed model is more flexible.

Shape retrieval using multi-level included angle functions-based Fourier descriptor

An effective shape signature namely multi-level included angle functions MIAFs is proposed to describe the hierarchy information ranging from global information to local variations of shape.Invariance to rotation translation and scaling are the intrinsic properties of the MIAFs.For each contour point the multi-level included angles are obtained based on the paired line segments derived from unequal-arc-length partitions of contour.And a Fourier descriptor derived from multi-level included angle functions MIAFD is presented for efficient shape retrieval.The proposed descriptor is evaluated with the standard performance evaluation method on three shape image databases the MPEG-7 database the Kimia-99 database and the Swedish leaf database. The experimental results of shape retrieval indicate that the MIAFD outperforms the existing Fourier descriptors and has low computational complexity.And the comparison of the MIAFD with other shape description methods also shows that the proposed descriptor has the highest precision at the same recall value which verifies its effectiveness.

Seasonal Dynamics of Nitrogen and Phosphorus in Water and Sediment of A Multi-level Ditch System in Sanjiang Plain,Northeast China

The multi-level ditch system developed in the Sanjiang Plain,Northeast China has sped up water drainage process hence transferred more pollutants from farmlands into the rivers of this region.Understanding the seasonal dynamics of nitrogen (N) and phosphorus (P) transportation in the ditch system and the role of different ditch size is thus crucial for water pollution control of the rivers in the Sanjiang Plain.In this study,an investigation was conducted in the Nongjiang watershed of the Sanjiang Plain to study the nutrient variation and the correlation between water and sediments in the ditch system in terms of ditch level.Water and sediments samples were collected in each ditch level in growing season at regular intervals (once per month),and TN,NO 3--N,NH 4+-N,TP,and PO 4 3--P were analyzed.The results show that nutrient contents in water were higher in June and July,especially in July,the contents of TN and TP were 3.21mg/L and 0.84mg/L in field ditch,4.04mg/L and 1.06mg/L in lateral ditch,2.46mg/L and 0.70mg/L in branch ditch,1.92mg/L and 0.63mg/L in main ditch,respectively.In August and September,the nutrient contents in the water were relatively lower.The peak value of nutrient in ditch water had been moving from the field ditch to the main ditch over time,showing a remarkable impact of ditch system on river water environment.The nutrient transfer in ditch sediments could only be found in rainfall season.Nutrient contents in ditch sediment had effect on that in ditch water,but nutrients in ditch water and sediments had different origination.Ditch management in terms of the key fac-tors is hence very important for protecting river water environment.

A Mandatory Access Control Framework in Virtual Machine System with Respect to Multi-level Security Ⅱ:Implementation

This paper is a continuation of our last paper [1] which describes the theory of Virt-BLP model. Based on Virt-BLP model,this paper implements a mandatory access control(MAC) framework applicable to multi-level security(MLS) in Xen. The Virt-BLP model is the theoretical basis of this MAC framework,and this MAC framework is the implementation of Virt-BLP model. Our last paper focuses on Virt-BLP model,while this paper concentrates on the design and implementation of MAC framework. For there is no MAC framework applicable to MLS in virtual machine system at present,our MAC framework fills the blank by applying Virt-BLP model to Xen,which is better than current researches to guarantee the security of communication between virtual machines(VMs) . The experimental results show that our MAC framework is effective to manage the communication between VMs.

A Multi-level Approach for Complex Fault Isolation Based on Structured Residuals

In industrial processes,there exist faults that have complex effect on process variables.Complex and simple faults are defined according to their effect dimensions.The conventional approaches based on structured residuals cannot isolate complex faults.This paper presents a multi-level strategy for complex fault isolation.An extraction procedure is employed to reduce the complex faults to simple ones and assign them to several levels.On each level,faults are isolated by their different responses in the structured residuals.Each residual is obtained insensitive to one fault but more sensitive to others.The faults on different levels are verified to have different residual responses and will not be confused.An entire incidence matrix containing residual response characteristics of all faults is obtained,based on which faults can be isolated.The proposed method is applied in the Tennessee Eastman process example,and the effectiveness and advantage are demonstrated.

A New Rational-based Optimal Design Strategy of Ship Structure Based on Multi-level Analysis and Super-element Modeling Method

A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore,the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship,suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.

BC-BLPM:A Multi-Level Security Access Control Model Based on Blockchain Technology

Traditional multi-level security(MLS)systems have the defect of centralizing authorized facilities,which is difficult to meet the security requirements of modern distributed peer-to-peer network architecture.Blockchain is widely used in the field of access control with its decentralization,traceability and non-defective modification.Combining the blockchain technology and the Bell-LaPadula model,we propose a new access control model,named BCBLPM,for MLS environment.The“multi-chain”blockchain architecture is used for dividing resources into isolated access domains,providing a fine-grained data protection mechanism.The access control policies are implemented by smart contracts deployed in each access domain,so that the side chains of different access domains storage access records from outside and maintain the integrity of the records.Finally,we implement the BC-BLPM prototype system using the Hyperledger Fabric.The experimental and analytical results show that the model can adapt well to the needs of multi-level security environment,and it has the feasibility of application in actual scenarios.

An effective multi-level algorithm based on ant colony optimization for graph bipartitioning

Partitioning is a fundamental problem with applications to many areas including data mining, parellel processing and Very-large-scale integration （VLSI） design. An effective multi-level algorithm for bisecting graph is proposed. During its coarsening phase, an improved matching approach based on the global information of the graph core is developed with its guidance function. During the refinement phase, the vertex gain is exploited as ant＇s heuristic information and a positive feedback method based on pheromone trails is used to find the global approximate bipartitioning. It is implemented with American National Standards Institute （ANSI） C and compared to MeTiS. The experimental evaluation shows that it performs well and produces encouraging solutions on 18 different graphs benchmarks.

Fatigue Properties of RPC under Cyclic Loads of Single-stage and Multi-level Amplitude

Fatigue properties of Reactive Powder Concrete （RPC） under axial compression of single-stage and multi-level amplitude in cycles were studied. The tests reveal the fatigue life, the strain and residual life of the RPC samples. Through the analysis of the test results under cyclic loads of single amplitude, the S-N curve of RPC and the evolution rule of macro-damage of RPC were presented, which can be divided into latency stage, stable development stage and instability development stage according to the evolution pattern of the fatigue crack. Accordingly, the development of longitudinal deformation presents the similar three-stage-model, and the proportion of each stage is 15%, 75%, and 10%. According to test results, the fatigue strength reduction factor is 0.564. We brought forward an empirical formula to predict the life of RPC via total longitudinal strain and got the evolving rule for the residual strength of the RPC. The analysis of the test results under cyclic loads of multi-level amplitude shows that the strain under this loading pattern experiences three stages. The characteristic value for the residual strain was obtained. The irreversible damage and non-linear evolution of RPC was described by the development of the residual plastic strain.

Competitive location problem of multi-level pickup point considering cooperative coverage

To occupy a greater market share in terminal distribution, companies are urged to make full use of cooperative coverage formed with brand effect and information sharing in the layout of pickup points. Based on the diversity of pickup points, the piecewise function, signal intensity function and probability function are introduced. Meanwhile, considering the effect of distance satisfaction and cooperation coverage on customer behavior, the location model of the pickup point under competitive environments is established. The genetic algorithm is used to solve the problem, and the effectiveness of the model and algorithm is verified by a case. The results show that the sensitivity of weighted demand coverages to budget decreases gradually. The maximum weighted demand coverage increases at first and then decreases with the increase of the signal threshold, and there is a positive correlation with the change of the actual demand coverage to the senior customers, but it is negatively related to the intermediate and primary customers. When the number of high-level pickup points in a competitive enterprise is small, the advantage of the target enterprise is more significant. Through comparison, the cooperative coverage model is better than the non-cooperative coverage model, in terms of the weighted demand coverage, the construction cost and the attention paid to the important customers.

Multi-level fuzzy comprehensive appraisal on social effects of projects

The application of multi-level fuzzy comprehensive appraisal on social effects of projects has been studied. The principles for setting up an index system have been analyzed and the index system has been set up according to projects of construction. Models for multi-level fuzzy comprehensive appraisal have been offered and relative calculation steps have been given according to project instances.

Design of Irregular QC-LDPC Code Based Multi-Level Coded Modulation Scheme for High Speed Optical Communication Systems

In this paper, we focus on the design of irregular QC-LDPC code based multi-level coded modulation(MLCM) scheme by jointly optimizing the component code rate and the degree distribution of the irregular QC-LDPC component code. Firstly, the sub-channel capacities of MLCM systems is analyzed and discussed, based on which the optimal component code rate can be obtained. Secondly, an extrinsic information transfer chart based two-stage searching algorithm is proposed to find the good irregular QC-LDPC code ensembles with optimal component code rates for their corresponding sub-channels. Finally, by constructing the irregular QC-LDPC component codes from the designed ensembles with the aim of possibly enlarging the girth and reducing the number of the shortest cycles, the designed irregular QC-LDPC code based 16QAM and 64QAM MLCM systems can achieve 0.4 dB and 1.2 dB net coding gain, respectively, compared with the recently proposed regular QC-LDPC code based 16QAM and 64QAM MLCM systems.

A Parameterization of Cooling Rate Calculation under the Non-LTE Condition: Multi-Level Model

Calculations of cooling rate by CO2 15 μm band in the earth's upper mesosphere and lower thermosphere be-come very difficult because of the non-LTE. This is primarily due to the nonlinear vibration-vibrational (VV) transition processes between CO, molecules in different states. This paper suggests that the non-LTE source function be parameterized as a linear combination of two limiting source functions. One limiting source function neglects the VV transitions while the other limiting source function assumes VV transitions being dominant. These two limiting source functions can be derived by linear models. The parameterization schemes proposed here can be applied to the general circulation models including those non-LTE regions.

A Mandatory Access Control Framework in Virtual Machine System with Respect to Multi-level Security I： Theory

At present,there are few security models which control the communication between virtual machines (VMs).Moreover,these models are not applicable to multi-level security (MLS).In order to implement mandatory access control (MAC) and MLS in virtual machine system,this paper designs Virt-BLP model,which is based on BLP model.For the distinction between virtual machine system and non-virtualized system,we build elements and security axioms of Virt-BLP model by modifying those of BLP.Moreover,comparing with BLP,the number of state transition rules of Virt-BLP is reduced accordingly and some rules can only be enforced by trusted subject.As a result,Virt-BLP model supports MAC and partial discretionary access control (DAC),well satisfying the requirement of MLS in virtual machine system.As space is limited,the implementation of our MAC framework will be shown in a continuation.

A new tracking error detection method using amplitude difference detection for signal waveform modulation multi-level discs

The sub-land/sub-pit affects the characteristic of the tracking error signal which is generated by the conventional differential phase detection （DPD） method in the signal waveform modulation multi-level （SWML） read-only disc. To solve this problem, this paper proposes a new tracking error detection method using amplitude difference. Based on the diffraction theory, the amplitude difference is proportional to the tracking error and is feasible to be used for obtaining the off-track information. The experimental system of the amplitude difference detection method is developed. The experimental results show that the tracking error signal derived from the new method has better performance in uniformity and signal-to-noise ratio than that derived from the conventional DPD method in the SWML read-only disc.

Improved Fibroblast Adhesion and Proliferation by Controlling Multi-level Structure of Polycaprolactone Microfiber

Improving wound healing efficiency is a key issue for high performance dressings.The surface topology of fibers in wound dressings plays an important role in regulating cell behaviors during the regeneration.Herein,a polycaprolactone(PCL)scaffold with a shish-kebab structure was prepared by electrospinning and solution-induced crystallization.L929 cells were used to investigate the behavior of fibroblasts on the multi-level microfiber.The results showed that the shish-kebab fiber-based scaffold enhanced the cell proliferation when compared with the normal fiber and the fiber with a porous structure.Protein absorption,cell adhesive force,and cell modulus also increased by the shish-kebab fiber.The shish-kebab fiber-based scaffold with improved fibroblast-regulation ability can be applied in rapid wound healing.

A Multi-Level Threshold Method for Edge Detection and Segmentation Based on Entropy

The essential tool in image processing,computer vision and machine vision is edge detection,especially in the fields of feature extraction and feature detection.Entropy is a basic area in information theory.The entropy,in image processing field has a role associated with image settings.As an initial step in image processing,the entropy is always used the image’s segmentation to determine the regions of image which is used to separate the background and objects in image.Image segmentation known as the process which divides the image into multiple regions or sets of pixels.Many applications have been development to enhance the image processing.This paper utilizes the Shannon entropy to achieve edge detection process and segmentation of the image.It introduces a new method of edge detection for 2-D histogram and Shannon entropy based on multilevel threshold.The method utilizes the gray value and the average gray value of the pixels to achieve the two dimensional histogram.The current method has apriority in comparison to some upper classical methods.The experimental results exhibited that the proposed method could capture a moderate quality and execution time better than other comparative methods,particularly in the largest images size.The proposed method offers good results when applied with images of different sizes from the civilization of ancient Egyptians.