scholarly journals Improving the Return Loading Rate Problem in Northwest China Based on the Theory of Constraints

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1397
Author(s):  
Wen-Tso Huang ◽  
Cheng-Chang Lu ◽  
Jr-Fong Dang
Keyword(s):  
Loading Rate ◽  
Phase 1 ◽  
Model Performance ◽  
Optimal Solution ◽  
Northwest China ◽  
Theory Of Constraints ◽  
Simulation Data ◽  
Original Distribution ◽  
Proposed Model ◽  
Transportation Distance

This paper introduces how to improve the return loading rate problem by integrating the Sub-Tour reversal approach with the method of the Theory of Constraints (TOC). The proposed model generates the initial solution derived by the Sub-Tour reversal approach in phase 1 and then applies TOC to obtain the optimal solution, meeting the goal of improving the return loading rate to more than 50% and then lowering the total transportation distance in phase 2. To see our model capability, this study establishes an original distribution layout to compare the performance of the Sub-Tour reversal approach with our model, based on the simulation data generated by the Monte Carlo simulation. We also conduct the pair t-test to verify our model performance. The results show that our proposed model outperforms the Sub-Tour reversal approach in a significant manner. By utilizing the available data, our model can be easily implemented in the real world and efficiently seeks the optimal solutions.

scholarly journals Wind Farm Cable Connection Layout Optimization with Several Substations

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3615
Author(s):  
Adelaide Cerveira ◽  
Eduardo J. Solteiro Pires ◽  
José Baptista
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Programming Model ◽  
Optimal Solution ◽  
Wind Farms ◽  
Green Energy ◽  
Fossil Energy ◽  
Proposed Model ◽  
Short Time ◽  
Cable Connection

Green energy has become a media issue due to climate changes, and consequently, the population has become more aware of pollution. Wind farms are an essential energy production alternative to fossil energy. The incentive to produce wind energy was a government policy some decades ago to decrease carbon emissions. In recent decades, wind farms were formed by a substation and a couple of turbines. Nowadays, wind farms are designed with hundreds of turbines requiring more than one substation. This paper formulates an integer linear programming model to design wind farms’ cable layout with several turbines. The proposed model obtains the optimal solution considering different cable types, infrastructure costs, and energy losses. An additional constraint was considered to limit the number of cables that cross a walkway, i.e., the number of connections between a set of wind turbines and the remaining wind farm. Furthermore, considering a discrete set of possible turbine locations, the model allows identifying those that should be present in the optimal solution, thereby addressing the optimal location of the substation(s) in the wind farm. The paper illustrates solutions and the associated costs of two wind farms, with up to 102 turbines and three substations in the optimal solution, selected among sixteen possible places. The optimal solutions are obtained in a short time.

scholarly journals Nodule Detection with Convolutional Neural Network Using Apache Spark and GPU Frameworks

2021 ◽  
Vol 11 (6) ◽  
pp. 2838
Author(s):  
Nikitha Johnsirani Venkatesan ◽  
Dong Ryeol Shin ◽  
Choon Sung Nam
Keyword(s):  
Neural Network ◽  
Radiation Dose ◽  
Convolutional Neural Network ◽  
Model Performance ◽  
Performance Comparison ◽  
Apache Spark ◽  
Training Time ◽  
Learning Framework ◽  
Proposed Model

In the pharmaceutical field, early detection of lung nodules is indispensable for increasing patient survival. We can enhance the quality of the medical images by intensifying the radiation dose. High radiation dose provokes cancer, which forces experts to use limited radiation. Using abrupt radiation generates noise in CT scans. We propose an optimal Convolutional Neural Network model in which Gaussian noise is removed for better classification and increased training accuracy. Experimental demonstration on the LUNA16 dataset of size 160 GB shows that our proposed method exhibit superior results. Classification accuracy, specificity, sensitivity, Precision, Recall, F1 measurement, and area under the ROC curve (AUC) of the model performance are taken as evaluation metrics. We conducted a performance comparison of our proposed model on numerous platforms, like Apache Spark, GPU, and CPU, to depreciate the training time without compromising the accuracy percentage. Our results show that Apache Spark, integrated with a deep learning framework, is suitable for parallel training computation with high accuracy.

A Novel Cloud-Assisted Secure Deep Feature Classification Framework for Cancer Histopathology Images

2021 ◽  
Vol 21 (2) ◽  
pp. 1-22
Author(s):  
Abhinav Kumar ◽  
Sanjay Kumar Singh ◽  
K Lakshmanan ◽  
Sonal Saxena ◽  
Sameer Shrivastava
Keyword(s):  
Differential Privacy ◽  
Model Performance ◽  
Healthcare Services ◽  
Cloud Services ◽  
Efficient Computation ◽  
Sensitive Data ◽  
Classification Framework ◽  
Proposed Model ◽  
Diagnostic Framework ◽  
Histopathological Image Classification

The advancements in the Internet of Things (IoT) and cloud services have enabled the availability of smart e-healthcare services in a distant and distributed environment. However, this has also raised major privacy and efficiency concerns that need to be addressed. While sharing clinical data across the cloud that often consists of sensitive patient-related information, privacy is a major challenge. Adequate protection of patients’ privacy helps to increase public trust in medical research. Additionally, DL-based models are complex, and in a cloud-based approach, efficient data processing in such models is complicated. To address these challenges, we propose an efficient and secure cancer diagnostic framework for histopathological image classification by utilizing both differential privacy and secure multi-party computation. For efficient computation, instead of performing the whole operation on the cloud, we decouple the layers into two modules: one for feature extraction using the VGGNet module at the user side and the remaining layers for private prediction over the cloud. The efficacy of the framework is validated on two datasets composed of histopathological images of the canine mammary tumor and human breast cancer. The application of differential privacy preserving to the proposed model makes the model secure and capable of preserving the privacy of sensitive data from any adversary, without significantly compromising the model accuracy. Extensive experiments show that the proposed model efficiently achieves the trade-off between privacy and model performance.

scholarly journals Distilling Deep Structural Facial Relationships for FAU Intensity Estimation

2021 ◽  
Author(s):  
Yingruo Fan ◽  
Jacqueline CK Lam ◽  
Victor On Kwok Li
Keyword(s):  
Structural Characteristics ◽  
Model Performance ◽  
Training Model ◽  
Model Parameters ◽  
Intensity Estimation ◽  
Structural Relationships ◽  
Proposed Model ◽  
Comparable Performance ◽  
Knowledge Distillation ◽  
The Difference

<div> <div> <div> <p>Facial emotions are expressed through a combination of facial muscle movements, namely, the Facial Action Units (FAUs). FAU intensity estimation aims to estimate the intensity of a set of structurally dependent FAUs. Contrary to the existing works that focus on improving FAU intensity estimation, this study investigates how knowledge distillation (KD) incorporated into a training model can improve FAU intensity estimation efficiency while achieving the same level of performance. Given the intrinsic structural characteristics of FAU, it is desirable to distill deep structural relationships, namely, DSR-FAU, using heatmap regression. Our methodology is as follows: First, a feature map-level distillation loss was applied to ensure that the student network and the teacher network share similar feature distributions. Second, the region-wise and channel-wise relationship distillation loss functions were introduced to penalize the difference in structural relationships. Specifically, the region-wise relationship can be represented by the structural correlations across the facial features, whereas the channel-wise relationship is represented by the implicit FAU co-occurrence dependencies. Third, we compared the model performance of DSR-FAU with the state-of-the-art models, based on two benchmarking datasets. Our proposed model achieves comparable performance with other baseline models, though requiring a lower number of model parameters and lower computation complexities. </p> </div> </div> </div>

scholarly journals An Updated Analytical Structural Pounding Force Model Based on Viscoelasticity of Materials

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Qichao Xue ◽  
Chunwei Zhang ◽  
Jian He ◽  
Guangping Zou ◽  
Jingcai Zhang
Keyword(s):  
Vibration Control ◽  
Viscoelastic Model ◽  
Control Process ◽  
Model Performance ◽  
Analytical Models ◽  
Model Parameters ◽  
Force Model ◽  
Control Analysis ◽  
Proposed Model ◽  
Force Calculation

Based on the summary of existing pounding force analytical models, an updated pounding force analysis method is proposed by introducing viscoelastic constitutive model and contact mechanics method. Traditional Kelvin viscoelastic pounding force model can be expanded to 3-parameter linear viscoelastic model by separating classic pounding model parameters into geometry parameters and viscoelastic material parameters. Two existing pounding examples, the poundings of steel-to-steel and concrete-to-concrete, are recalculated by utilizing the proposed method. Afterwards, the calculation results are compared with other pounding force models. The results show certain accuracy in proposed model. The relative normalized errors of steel-to-steel and concrete-to-concrete experiments are 19.8% and 12.5%, respectively. Furthermore, a steel-to-polymer pounding example is calculated, and the application of the proposed method in vibration control analysis for pounding tuned mass damper (TMD) is simulated consequently. However, due to insufficient experiment details, the proposed model can only give a rough trend for both single pounding process and vibration control process. Regardless of the cheerful prospect, the study in this paper is only the first step of pounding force calculation. It still needs a more careful assessment of the model performance, especially in the presence of inelastic response.

Decision-making approach for complex problems management in a scarce human resources environment

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Marcilio Andrade ◽  
Dermeval Carinhana Jr
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Theoretical Perspective ◽  
Optimal Solution ◽  
Complex Problem ◽  
Theory Of Constraints ◽  
Content Type ◽  
Physical Constraints ◽  
Complex Problems ◽  
The Relationship

Purpose This purpose of this study is to structure complex problems to be solved with greater efficiency, optimising the relationship between root causes (RC) relevance of the problem and utilisation of human resources to treat them, minimising the use of manpower in problem-solving activity and thus contributing to greater productivity within organisations. Design/methodology/approach The authors built an approach under the concepts of theory of constraints and multiattribute and multiobjective decision-making methods that were applied in a real complex problem of the low development of Brazilian space industry, by theoretical perspective. Also, the authors submitted it in a simulation environment to assess in which situations it is successful considering number of problem’s RC, system complexity and number of people in the system. Findings The approach was successful on the real case, finding the optimal relationship between the RC relevance and the number of people involved to treat them. For certain complex problem inputs configurations, simulation results reveal that the approach is reliable obtaining more than 95% chance of success in finding the optimal relationship, when comparing with traditional prioritising methods. Originality/value This approach introduces an unprecedented way to locate and evaluate non-physical constraints within a system, which is used to determine RC relevance, as well as an unprecedented way of defining a single optimal solution for structuring a problem, considering the relevance of RC and the use of human resources. The approach is useful for organisations in general which often need managing complex problems with few resources.

An Integrated Methodology for Evaluation of Electric Vehicles Under Sustainable Automotive Environment

2019 ◽  
pp. 41-62 ◽  
Author(s):  
Tapas Kumar Biswas ◽  
Željko Stević ◽  
Prasenjit Chatterjee ◽  
Morteza Yazdani
Keyword(s):  
Electric Vehicles ◽  
Sustainability Assessment ◽  
Model Performance ◽  
Compromise Solution ◽  
Holistic Model ◽  
Proposed Model ◽  
Criteria Importance ◽  
Assessment Problems ◽  
Selection Of

In this chapter, a holistic model based on a newly developed combined compromise solution (CoCoSo) and criteria importance through intercriteria correlation (CRITIC) method for selection of battery-operated electric vehicles (BEVs) has been propounded. A sensitivity analysis has been performed to verify the robustness of the proposed model. Performance of the proposed model has also been compared with some of the popular MCDM methods. It is observed that the model has the competency of precisely ranking the BEV alternatives for the considered case study and can be applied to other sustainability assessment problems.

Simulating E-business Innovation Process Improvement with Virtual Teams Across Europe and Asia

2011 ◽  
pp. 1023-1043
Author(s):  
Kenneth D. Strang ◽  
Cliff E.L. Chan
Keyword(s):  
Virtual Teams ◽  
New Product Development ◽  
Quality Function Deployment ◽  
Phase 1 ◽  
Innovation Process ◽  
New Product ◽  
Geographically Dispersed ◽  
Proposed Model ◽  
The Voice

In this article, E-business new product development innovation processes were studied at four enterprises across Europe and Asia. E-entrepreneurship innovation was improved using a quality of idea priority model. The conventional quality function deployment phase 1 matrix was revised to increase the voice of customers and engineer quality of idea decision-making. The proposed model was simulated with geographically dispersed virtual teams (based on production data). Statistical analyses were applied to test the hypothesis that an improved innovation process could better discriminate between new product return on investment pass or fail probability.

Simulating E-business Innovation Process Improvement with Virtual Teams Across Europe and Asia

2010 ◽  
Vol 1 (1) ◽  
pp. 22-41 ◽  
Author(s):  
Kenneth D. Strang ◽  
Cliff E.L. Chan
Keyword(s):  
Virtual Teams ◽  
New Product Development ◽  
Quality Function Deployment ◽  
Phase 1 ◽  
Innovation Process ◽  
New Product ◽  
Geographically Dispersed ◽  
Proposed Model ◽  
The Voice

In this article, E-business new product development innovation processes were studied at four enterprises across Europe and Asia. E-entrepreneurship innovation was improved using a quality of idea priority model. The conventional quality function deployment phase 1 matrix was revised to increase the voice of customers and engineer quality of idea decision-making. The proposed model was simulated with geographically dispersed virtual teams (based on production data). Statistical analyses were applied to test the hypothesis that an improved innovation process could better discriminate between new product return on investment pass or fail probability.

scholarly journals Hedging Long-Term Exposures of a Well-Diversified Portfolio with Short-Term Stock Index Futures Contracts

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Yufang Liu ◽  
Wei-Guo Zhang ◽  
Rongda Chen ◽  
Junhui Fu
Keyword(s):  
Optimal Solution ◽  
Optimal Number ◽  
Stock Index ◽  
Futures Contracts ◽  
Equivalent Transformation ◽  
Stock Index Futures ◽  
Index Futures ◽  
Proposed Model ◽  
Diversified Portfolio

It is difficult for passive portfolio strategy to manage the long-term exposure of a well-diversified portfolio because stock index futures contracts have a finite life limited by their maturity. In this paper, we investigate the problem of the rollover hedge strategy for the long-term exposure of a well-diversified portfolio. First, we consider the rollover hedge strategy for the well-diversified portfolio when the portfolio is not adjusted during the period. In order to obtain the optimal solution of the proposed model, the auxiliary models are constructed using the equivalent transformation technique. Moreover, dynamic programming is employed to derive the optimal positions of stock index futures contracts for the long-term exposure of the well-diversified portfolio. In addition, we extend the result to the case of the rollover hedge strategy with transaction costs and derive the optimal number of stock index futures contracts.

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