Coordination Model Research Articles

A Proactive Telephonic Outreach Program to Address Unmet Social Needs of Children in Immigrant and Refugee Families at a Federally Qualified Health Center.

We developed a telephonic outreach and care coordination program for children in immigrant and refugee families (CIRF) at a federally qualified health center (FQHC) in North Carolina to address unmet health-related social needs (HRSN). Participants were recruited between December 2020 and October 2021. Eligible children were ages 0-5, non-English speaking, and were seen at the FQHC in the 2years prior. A bicultural/bilingual case manager completed telephonic outreach to caregivers of participants with HRSN screening. Bilingual patient navigators made follow-up calls to assess connection to resources and to develop strategies for addressing unmet needs. Three hundred forty-two families received outreach; 212 (62.0%) completed the baseline questionnaire. The majority (N = 160, 75.5%) completed at least one follow-up. The majority (N = 186, 88.1%) were Spanish-speaking, and over two-thirds (N = 149, 70.3%) were uninsured. Most participants had between 3-5 HRSNs identified (N = 121, 57.1%); "employment" (n = 158, 74.5%) and "food" (n = 138, 65.1%) were the most common. Despite repeated assistance, the majority of participants struggled to link to a community resource for their highest priority need (N = 123, 78.3%). Proactive phone-based HRSN screening may be a feasible and effective intervention to facilitate the identification of social needs for CIRF. The delivery of the intervention in languages other than English may have further contributed to program acceptability. Despite program feasibility and acceptability, community-level barriers to the resolution of HRSNs persist. While similar care coordination models can be considered to identify the high burden of unmet HRSN among CIRF, addressing the limited capacity of community-based resources for this population will be a critical component to ensuring the sustainability of such programs.

Response Coordination Model for Real Time Decision Making in Coastal Search and Rescue Operation Using Fuzzy Logic Technique

Coastal search and rescue (SAR) operations are complex, involving dynamic and uncertain conditions that demand real-time, effective decision-making. This paper aimed to analyze response coordination for real- time decision-making in coastal SAR operations using the fuzzy logic technique. The main aims of this study were to identify the key parameters and linguistic variables critical for effective decision-making in SAR operations and finally to design a fuzzy logic model tailored to the dynamic and uncertain conditions inherent in coastal SAR operations. The proposed fuzzy logic model demonstrated improved responsiveness and adaptability to changing conditions, offering a more robust framework for decision-making in SAR operations. However, this study contributes to enhancing the efficiency and effectiveness of real time decision making in SAR operations in coastal environments, with broader implications for maritime safety.

New urbanization; Urban resilience; Coupled coordination model; Huaihe River Basin

Contemporary China's pension system revolves around the allocation and acquisition of pension resources, relying on the enforcement of political power as a guarantee, and is closely integrated with the formulation of laws to form a normative system. This system is composed of a variety of specific systems, and the sub-systems are interconnected and complementary in function, forming a comprehensive pension security network. In the process of promoting the modernization of the national governance system and governance capacity, the pension field needs to achieve a benign governance model, which requires a complete pension system as a support. Under the framework of the existing political system and constitutional system, the basic governance logic remains unchanged. To further promote the development of the pension system, the key lies in optimizing the pension legal system and establishing an effective coordination mechanism between laws and systems. Specifically, it is necessary to start from the following aspects: first, reconstruct the pension legal system with a coordinated and development approach, enhance the fairness of the pension legal system on the basis of objectively analyzing the social situation, and ensure the sustainability of social pension security; second, optimize the pension legal system from the perspective of national strategic layout, including improving the form of family pension responsibility and accelerating the legalization of social pension security; finally, strengthen the development of pension laws by giving full play to the leading role of the National People's Congress in legislation and improving the review mechanism of administrative normative documents. Only in this way can we form a modern system to deal with the issue of elderly care under the increasingly severe aging situation.

Study on the Coupled Coordinated Development of New Urbanization and Urban Resilience in Huaihe River Basin

The coupled and coordinated development of new urbanization and urban resilience can promote the disaster response, disaster resistance and high-quality development of urban agglomerations in the Huaihe River Basin. The article constructs a new urbanization system and a chain-type urban resilience evaluation system with the mechanism of "pressure-feedback", selects the central city of Huaihe River Basin as the research object, and measures the new urbanization and urban resilience level and change trend of the central city of Huaihe River Basin in 2012-2021 with the help of the coupling coordination model. Using the entropy value method, we measured the new urbanization and urban toughness level and the trend of change of the central cities in Huaihe River Basin from 2012 to 2021, measured the type of city cluster coupling coordination and its internal factors with the help of the coupling coordination model, and analyzed the coupling coordination relationship between the two.

Chinese women's years of education and subjective well-being: an empirical analysis based on ordered Logit model and coupling coordination model.

In modern society, the improvement of women's education level has become one of the important indicators of national development and social progress. Although there are many useful explorations on the relationship between education and subjective well-being, the research on women's years of education and subjective well-being is very limited. The article focuses on women's years of education to determine whether and how to affect subjective well-being. This study is based on the China general social survey in 2021. The ordered Logit model was used to analyze the impact of women's years of education on subjective well-being, and a binary coupling coordination model was constructed to test the above two variables. The results show that the longer the education years of women, the stronger the subjective well-being. The benchmark regression results show that women's years of education have positive and negative effects on subjective well-being through economic status, physical and mental health, ecological environment, social cognition and personal cognition. The analysis of coupling coordination degree shows that the coupling between the years of education and subjective well-being of women in coastal areas and economically developed areas is the strongest, and the subjective well-being is better realized by increasing the years of education. Based on the above research results, this paper provides some practical suggestions for improving women's subjective well-being, and provides some valuable references for women to effectively balance husband-wife relationship, family relationship and work relationship, improve women's years of education and better obtain happiness.

Determining What’s Next: Visual Analytics for Evaluating Human-Automation Coordination

As advanced automated systems become more complex, there is a greater need to analyze the difficulty of human-automation coordination. We developed a novel visual analytics tool to evaluate human-automation coordination by examining the relationship between projection, explanation (retrojection), and the understanding of current events through time. The What’s Next Diagram visualizes demands on human sensemaking as operators answer Wiener’s key automation surprise question: what will automation do next. The tool can assess whether operators can answer the question directly and quickly given the design and architecture of human-automation systems. It can be used as a model of multi-agent coordination, as a tool for post-mortem analysis, or an aid for design. We illustrate how the tool can be used to identify system requirements for anomaly response in the aviation domain.

Car-following model based on artificial potential field with consideration of horizontal curvature in connected vehicles environment

Connected vehicles (CVs) will gradually replace traditional vehicles to become the main components of traffic flow. Studying the car-following behavior characteristics is crucial for improving traffic flow stability and safety in CVs environment. Additionally, the radius of road curvature significantly impacts vehicle driving behavior, making it necessary to consider it for the car-following models of CVs. The artificial potential field (APF) theory can more accurately and comprehensively depict various microscopic driving behaviors, offering a new approach for modeling vehicle microscopic behavior. Firstly, this paper constructs the attractive and repulsive potential fields considering horizontal curve curvature based on a road coordinate transformation model. Secondly, an Artificial Potential Field-Based Car-Following Model Considering Curvature (APFCCM) in connected vehicles environment is proposed. Finally, the model is calibrated and validated using the Hangzhou - Xifu Freeway dataset from the Tongji Road Trajectory Sharing (TJRD TS) platform, and compared with the full velocity difference model(FVDM), the Intelligent Driver Model (IDM) and the Driving Risk Potential Field Model (DRPFM). The results show that the APFCCM performs well in trajectory simulation, model accuracy, and scenario adaptability, and it has the lowest mean absolute error(MAE) and root mean square error(RMSE) in position, speed, and acceleration metrics.

Voyage charterparty arrangement for river tramp shipping: Green and traditional vessels comparison

Voyage charterparty arrangement (VCA) for river shipping is a common agreement between a shipowner and a charterer regarding the transportation of specific cargoes from one port to another via a tramp vessel. Optimizing VCA with the essential terms such as laytime and sailing speed of the vessel, is a crucial task for both parties to reduce potential disputes and achieve win-win outcomes. This paper models the problem from two perspectives: the VCA negotiation stage and execution stage. Firstly, according to the given probability distribution of port time, the theoretically optimal laytime is obtained by using textbook formulation of newsvendor problems (NVP). On this basis, considering the concerns about the inaccuracy of the given probability distribution and the adjustment measures taken by charterers and shipowners in reality, an integrated adjustment model is constructed to determine the optimal laytime in the VCA negotiation stage. Secondly, taking into account the vessel's uncertain lock crossing time, an operations coordination model with information sharing of the berth plan is established to obtain the optimal sailing speed under a certain confidence level in the VCA execution stage. Finally, a case study of chartering tramp vessels on the Yangtze River validates the applicability and effectiveness of the models proposed in this paper, and some important management insights are derived. The results show that establishing lower optimal speed limits and relatively shorter laytime when signing a contract with the shipowner of green river vessels is reasonable for the charterer. By notifying the shipowner of the berth plan after the green river vessel crosses through the lock, the charterer can avoid higher demurrage costs due to speeding-up. Operations coordination would be mutually beneficial without abusing the contract terms. Compared to traditional river vessels, it's more reasonable to reduce the benefits allocated to charterers from the deceleration of green river vessels by shipowners.

Spatiotemporal Characteristics and Influencing Factors of the Synergistic Effect of Pollution Reduction and Carbon Reduction in China

Based on the use of the coupling coordination model to calculate the coupling coordination degree of carbon emission and pollutant control, the national, regional, and provincial spatiotemporal characteristics of the synergistic effect of pollution control and carbon emissions reduction in China were further analyzed, facilitating the crucial to identification of key areas. The fixed effects regression models and provincial panel data from 2006 to 2020 were used to explore factors contributing to better synergizing the reduction of pollution and carbon emissions in China. On this basis, the adjustment variable of R&D investment intensity was introduced, and the regulation effect model was constructed to further explore the influence mechanism of the synergistic effect of pollution reduction and carbon reduction. The results showed that： synergy exists between carbon emission reduction and the air pollution control system, the evolution of the synergistic effect of pollution reduction and carbon reduction in China presented an inverted "U"-shaped trend from 2006 to 2020, and there was spatial aggregation and a spatial spillover effect in pollution reduction and carbon reduction. The synergistic governance of carbon emission and pollutant control was still at a relatively low level. The carbon emission and air pollutant emission systems were still in an unstable and uncoordinated state. The results showed that： The degree of coordination of eastern China, central China, and western China decreased in turn. At the national level, energy consumption structure, per capita GDP, and the proportion of green investment were the main factors affecting the synergistic effect of pollution reduction and carbon. The heterogeneity of the influencing factors existed in the central, eastern, and western regions on industrial structure, energy consumption structure, energy utilization efficiency, per capita GDP, urbanization rate, the proportion of green investment, and transportation structure. The intensity of R&D played a significant moderating effect in the whole country, eastern, and central regions. However, no significant moderating effect was identified in the western region. In the eastern region, the urbanization rate, the proportion of green investment, and the transportation structure could not have a significant effect on the synergistic effect of pollution reduction and carbon reduction alone, and it must be coordinated with the intensity of R&D.

The Coupling and Coordination Between Digital Economy and Green Economy: Evidence from China

ABSTRACT This paper tries to empirically calculate the coupling and coordinate degree between digital economy and green economy by utilizing the data for 28 Chinese provinces from 2015 to 2020 via coupling coordination model. Specifically, we measure the development level of digital economy and green economy by utilizing the entropy weight method, which supports that while the digital economy and green economy increases quickly among all sample provinces, there exists problem of digital divide among different regions and the speed of digital economy is higher than that of green economy. Additionally, we calculated the degree of coupling and coordination between digital economy and green economy, which suggests that coordination and coupling between digital economy and green economy experiences sharp increase. Finally, we also investigated the regional heterogeneity for the coupling and coordination between such two factors and offered that while the absolute level of coupling and coordination between digital economy and green economy in western and eastern regions is lower than that in eastern regions, its growth rate is higher in western and eastern regions than that in eastern regions.

Striking a balance between water use and environmental protection in an oasis—A case study of Ganzhou District, China

AbstractArid regions in Northwestern China, such as Ganzhou District, are crucial for agriculture but face challenges due to water scarcity. This study employs a coupling coordination model to analyse the environmental impact of agricultural water use in Ganzhou District and dissect the tension between agricultural development and ecological concerns. Despite an overall positive trend, the study reveals relatively poor coordination between water use and environmental protection, along with uneven spatial distribution. Examining the tension between agricultural expansion and its environmental repercussions, this study offers a reference for efforts to promote sustainable practices in agriculture and environmental management in oases.

A study on the spatial correlation network structure and its influencing factors of coupling coordination between FDI flow network and carbon transfer network in the belt and road initiative countries

Clarifying the spatial correlation characteristics and influencing factors of coupling coordination between Foreign Direct Investment (FDI) flow networks and carbon transfer networks in countries along the Belt and Road Initiative is of utmost importance for the formulation of regional carbon governance strategies and the establishment of a high-quality Green Silk Road. This study used a comprehensive approach combining social network analysis and coupling coordination model to measure the coupling coordination degree of FDI flow networks and carbon transfer networks of 67 Belt and Road countries from 2010 to 2016. In addition, a modified gravity model is used to characterize the spatial correlation network structure of coupling coordination between the two networks, and the QAP regression analysis method is applied to investigate the factors influencing the spatial association network. The results are as follows: 1) The spatial correlation network of coupling coordination between the two networks has good accessibility and relatively high overall network stability. 2) Countries such as Qatar and the United Arab Emirates occupy central positions in the network, while Bahrain and Jordan are positioned on the periphery of the network. 3) The spatial correlation network can be divided into three sectors: net outflow, net inflow, and bidirectional overflow sectors. 4) Spatial adjacency, bilateral investment treaties, economic development, and institutional quality have significant positive effects on the spatial association network, while the industrial structure and the level of infrastructure development have a significant negative impact. This study proposes an indicator system for the coupling coordination between FDI flow networks and carbon transfer networks. The aim is to investigate the coupling coordination relationship between FDI flow networks and carbon emission transfer networks in countries along the Belt and Road Initiative, providing important guidance for the formulation of regional cooperative carbon emission reduction strategies in other regions.

Research on the coupling coordination of digital economy and urban green development in the Yangtze River Delta of China

Digital economy has become an important engine for promoting green development.The existing literature mainly analyzed the impact of digital economy on green development, but rarely examines the coordinated development relationship between the two. This study contributes to the literature by constructing a research framework for the coupling coordination of digital economy and urban green development, using entropy method, coupling coordination model, and spatial auto-correlation to examine the coordinated development relationship between the two.The results show that:(1) During the research period, the comprehensive level of digital economy and urban green development in the Yangtze River Delta (YRD) both showed an upward and consistent trend. The level of digital economy was significantly lower than that of green development, but the gap between the two continued to narrow. (2) The overall coupling coordination level between digital economy and green development in the 41 cities of YRD was relatively low but showing a continuous upward trend. It has undergone a transition from near imbalance to primary coordination, still with a long way to realize high-quality coordination. (3) The coupling coordination level of digital economy and urban green development in different regions of YRD showed spatial differences, the order from high to low was Shanghai, Zhejiang, Jiangsu and Anhui province respectively. (4) The coupling coordination of digital economy and urban green development in the YRD exhibited significant spatial positive correlation and spatial dependence characteristics. The research results can provide a new perspective to promote the positive interaction between green development and digital economy.

Detection of Road Risk Sources Based on Multi-Scale Lightweight Networks.

Timely discovery and disposal of road risk sources constitute the cornerstone of road operation safety. Presently, the detection of road risk sources frequently relies on manual inspections via inspection vehicles, a process that is both inefficient and time-consuming. To tackle this challenge, this paper introduces a novel automated approach for detecting road risk sources, termed the multi-scale lightweight network (MSLN). This method primarily focuses on identifying road surfaces, potholes, and scattered objects. To mitigate the influence of real-world factors such as noise and uneven brightness on test results, pavement images were carefully collected. Initially, the collected images underwent grayscale processing. Subsequently, the median filtering algorithm was employed to filter out noise interference. Furthermore, adaptive histogram equalization techniques were utilized to enhance the visibility of cracks and the road background. Following these preprocessing steps, the MSLN model was deployed for the detection of road risk sources. Addressing the challenges associated with two-stage network models, such as prolonged training and testing times, as well as deployment difficulties, this study adopted the lightweight feature extraction network MobileNetV2. Additionally, transfer learning was incorporated to elevate the model's training efficiency. Moreover, this paper established a mapping relationship model that transitions from the world coordinate system to the pixel coordinate system. This model enables the calculation of risk source dimensions based on detection outcomes. Experimental results reveal that the MSLN model exhibits a notably faster convergence rate. This enhanced convergence not only boosts training speed but also elevates the precision of risk source detection. Furthermore, the proposed mapping relationship coordinate transformation model proves highly effective in determining the scale of risk sources.

Electric vehicles coordination for grid balancing using multi-objective Harris Hawks Optimization

The rise of renewables coincides with the shift towards Electrical Vehicles (EVs) posing technical and operational challenges for the energy balance of the local grid. Nowadays, the energy grid cannot deal with a spike in EVs usage leading to a need for more coordinated and grid aware EVs charging and discharging strategies. However, coordinating power flow from multiple EVs into the grid requires sophisticated algorithms and load-balancing strategies as the complexity increases with more control variables and EVs, necessitating large optimization and decision search spaces. In this paper, we propose an EVs fleet coordination model for the day ahead aiming to ensure a reliable energy supply and maintain a stable local grid, by utilizing EVs to store surplus energy and discharge it during periods of energy deficit. The optimization problem is addressed using Harris Hawks Optimization (HHO) considering criteria related to energy grid balancing, time usage preference, and the location of EV drivers. The EVs schedules, associated with the position of individuals from the population, are adjusted through exploration and exploitation operations, and their technical and operational feasibility is ensured, while the rabbit individual is updated with a non-dominated EV schedule selected per iteration using a roulette wheel algorithm. The solution is evaluated within the framework of an e-mobility service in Terni city. The results indicate that coordinated charging and discharging of EVs not only meet balancing service requirements but also align with user preferences with minimal deviations. The assessment of the determined solutions’ quality and efficacy shows promising outcomes, with convergence after 100 iterations reflected in a generational distance of 0.35 and a Pareto front error of 1.01, while the distribution of solutions exhibits strong hypervolume thus covering a significant portion of the objective space.

An inter-provincial coordinate model under Renewable Portfolio Standards policy based on tradable green certificate options trading

The current territorial management model under Renewable Portfolio Standards in China cannot fully develop renewable energy due to the mismatch between high energy-consumption regions and renewable energy-rich regions. Therefore, we proposed an inter-provincial coordinate model based on tradable green certificate options trading (CMTOT), which includes four components: (1) A dual-objective optimization model is established to minimize the RPS target realization cost and maximize the pollutant emission reduction based on Blacke-Scholes option pricing model. (2) The identification of buyer and seller provinces of tradable green certificate (TGC) options based on the above model. (3) An optimization model in buyers' or sellers' cooperation alliance is established. (4) The cost allocation models by Shapley value and Nucleolus are established to ensure the fairness in different scenarios. A case study of Tianjin, Shandong, Shanxi and Inner Mongolia shows that the CMTOT can effectively reduce the RPS target realization cost by 16.79 % and increase the pollutant emission reduction by 4.32 %. A sensitivity analysis confirms the robustness of the CMTOT. The results show that the CMTOT can both fully develop renewable energy and effectively reduce pollutant emission. Therefore, we proposed some policy recommendations to support the implementation of the CMTOT.

Spatial and temporal heterogeneity of soil salinity and ionic coupling relationship under the water-saving renovation of a typical irrigation district in arid and semi-arid areas

Soil salinization is a global environmental problem. To investigate the spatiotemporal heterogeneity of soil salinity and the coupling relationship of soil salinity ions under water-saving renovation conditions, we chose Shenwu Irrigation Area, where water-saving renovation projects are being conducted comprehensively. Specifically, for our field experiments, we chose 46 soil sampling points. Specifically, we used different spatial interpolation methods and coupling coordination models were applied to study the spatial and temporal distribution of soil salinity and soil salt-based ion coupling relationship changes during different water-saving periods in the irrigation area between 2015 and 2022. The results showed that (1) the emergence of soil salinity extremes after water-saving renovation project led to an increase in the variability of soil salinity. (2) Compared with the Inverse Distance Weighted, Radial Basis Function, and Universal Kriging interpolations, the Mean Absolute Error of the Ordinary Kriging interpolation was reduced by 12.68 %, 43.96 %, and 38.77 %, the Root Mean Square Error was reduced by 14.34 %, 60.85 %, and 36.53 %, reflective of a significant improvement in accuracy, and thus confirming this method to be optimal for elucidating soil salinity. (3) Compared with pre-water-saving renovation project, the average soil desalination rates in the 0–50 cm soil layer during and after project implementation were 5.71 % and 35.67 %. The impact of the water-saving renovation project was highest in channelside areas, followed by croplands, and lowest in lakeside areas. (4) The growth rates of soil salt-based ion coupling degree and coupling coordination degree after project implementation, compared with before implementation, were 17.07 % and 10.81 %. The implementation of water-saving renovation project improved soil quality. This study provides scientific support for the prevention and control of soil salinization in irrigation areas.

Role of a holo-insertase complex in the biogenesis of biophysically diverse ER membrane proteins

Mammalian membrane proteins perform essential physiologic functions that rely on their accurate insertion and folding at the endoplasmic reticulum (ER). Using forward and arrayed genetic screens, we systematically studied the biogenesis of a panel of membrane proteins, including several G-protein-coupled receptors (GPCRs). We observed a central role for the insertase, the ER membrane protein complex (EMC), and developed a dual-guide approach to identify genetic modifiers of the EMC. We found that the back of Sec61 (BOS) complex, a component of the multipass translocon, was a physical and genetic interactor of the EMC. Functional and structural analysis of the EMC⋅BOS holocomplex showed that characteristics ofa GPCR's soluble domain determine its biogenesis pathway. In contrast to prevailing models, no single insertase handles all substrates. We instead propose a unifying model for coordination between the EMC, the multipass translocon, and Sec61 for the biogenesis of diverse membrane proteins in human cells.

A Study of Improved Two-Stage Dual-Conv Coordinate Attention Model for Sound Event Detection and Localization.

Sound Event Detection and Localization (SELD) is a comprehensive task that aims to solve the subtasks of Sound Event Detection (SED) and Sound Source Localization (SSL) simultaneously. The task of SELD lies in the need to solve both sound recognition and spatial localization problems, and different categories of sound events may overlap in time and space, making it more difficult for the model to distinguish between different events occurring at the same time and to locate the sound source. In this study, the Dual-conv Coordinate Attention Module (DCAM) combines dual convolutional blocks and Coordinate Attention, and based on this, the network architecture based on the two-stage strategy is improved to form the SELD-oriented Two-Stage Dual-conv Coordinate Attention Model (TDCAM) for SELD. TDCAM draws on the concepts of Visual Geometry Group (VGG) networks and Coordinate Attention to effectively capture critical local information by focusing on the coordinate space information of the feature map and dealing with the relationship between the feature map channels to enhance the feature selection capability of the model. To address the limitation of a single-layer Bi-directional Gated Recurrent Unit (Bi-GRU) in the two-stage network in terms of timing processing, we add to the structure of the two-layer Bi-GRU and introduce the data enhancement techniques of the frequency mask and time mask to improve the modeling and generalization ability of the model for timing features. Through experimental validation on the TAU Spatial Sound Events 2019 development dataset, our approach significantly improves the performance of SELD compared to the two-stage network baseline model. Furthermore, the effectiveness of DCAM and the two-layer Bi-GRU structure is confirmed by performing ablation experiments.

An efficient colorectal cancer detection network using atrous convolution with coordinate attention transformer and histopathological images

The second most common type of malignant tumor worldwide is colorectal cancer. Histopathology image analysis offers crucial data for the clinical diagnosis of colorectal cancer. Currently, deep learning techniques are applied to enhance cancer classification and tumor localization in histopathological image analysis. Moreover, traditional deep learning techniques might loss integrated information in the image while evaluating thousands of patches recovered from whole slide images (WSIs). This research proposes a novel colorectal cancer detection network (CCDNet) that combines coordinate attention transformer with atrous convolution. CCDNet first denoises the input histopathological image using a Wiener based Midpoint weighted non-local means filter (WMW-NLM) for guaranteeing precise diagnoses and maintain image features. Also, a novel atrous convolution with coordinate attention transformer (AConvCAT) is introduced, which successfully combines the advantages of two networks to classify colorectal tissue at various scales by capturing local and global information. Further, coordinate attention model is integrated with a Cross-shaped window (CrSWin) transformer for capturing tiny changes in colorectal tissue from multiple angles. The proposed CCDNet achieved accuracy rates of 98.61% and 98.96%, on the colorectal histological image and NCT-CRC-HE-100 K datasets correspondingly. The comparison analysis demonstrates that the suggested framework performed better than the most advanced methods already in use. In hospitals, clinicians can use the proposed CCDNet to verify the diagnosis.