Search

Past studies used the network data envelopment analysis approach from a two-stage perspective (the production stage and waste/pollutant treatment stage) to evaluate industrial eco-efficiency and assess internal ineffective sources. However, these studies did not consider the dynamic features, i.e., capital investments in the current period are used to establish fixed assets for two stages, which can also be used in the later period, thus affecting its two-stage eco-efficiency. A dynamic network data envelopment analysis approach is adopted to fill this research gap and evaluate Chinese industrial two-stage eco-efficiency during 2010–2015, reflecting the practical production context and achieving comparable efficiencies among different periods. The major results of our study are: Firstly, not considering the dynamic features leads to an underestimation of the two-stage eco-efficiency. Secondly, the production efficiency was higher than the treatment efficiency, and the two-stage eco-efficiency was between the two during the study period. Furthermore, eastern China performed best with respect to the two-stage eco-efficiency, including production and treatment efficiencies, followed by the central and the western areas. Finally, a fifth of the 30 regions had a relatively low value of the input and output efficiencies of both production and treatment stages based on the clustering analysis.

Ranking of efficient decision-making units (DMUs) using data envelopment analysis (DEA) results is very important for various purposes. We propose a new comprehensive ranking method using network analysis for efficient DMUs to improve the discriminating power of DEA. This ranking method uses a measure, namely dominance value, which is a network centrality-based indicator. Thus far, existing methods exploiting DMU&rsquo, s positional features use either the superiority, which considers the efficient DMUs&rsquo, relative position on the frontier compared to other DMUs, or the influence, which captures the importance of the DMUs&rsquo, role as benchmarking targets for inefficient DMUs. However, in this research, the dominance value is the compounded measure of both core positional features of DMUs. Moreover, a network representation technique has been used to ensure the performance of the dominance value compared to the superiority and influence. To demonstrate the proposed ranking method, we present two examples, research and development (R&amp, D) efficiency of small and medium-sized enterprises (SMEs) and technical efficiency of plug-in hybrid electric vehicles (HEVs). Through these two examples, we can see how the known weaknesses and the unobserved points in the existing method differ in this new method. Hence, it is expected that the proposed method provides another new meaningful ranking result that can show different implications.

Falls are the leading cause of fatal injuries in the elderly such as fractures, and secondary damage from falls can lead to death. As such, fall detection is a crucial topic. However, due to the trade-off relationship between privacy preservation, user convenience, and fall detection performance, it is generally difficult to develop a fall detection system that simultaneously satisfies all conditions. The main goal of this study is to build a practical fall detection framework that can effectively classify the various behavior types into &ldquo, Fall&rdquo, and &ldquo, Activities of daily living (ADL)&rdquo, while securing privacy preservation and user convenience. For this purpose, signal data containing the motion information of objects was collected using a non-contact, unobtrusive, and non-restraint impulse-radio ultra wideband (IR-UWB) radar. These data were then applied to a convolutional neural network (CNN) algorithm to create an object behavior type classifier that can classify the behavior types of objects into &ldquo, ADL.&rdquo, The data were collected by actually performing various activities of daily living, including falling. The performance of the classifier yielded satisfactory results. By combining an IR-UWB and CNN algorithm, this study demonstrates the feasibility of building a practical fall detection system that exceeds a certain level of detection accuracy while also ensuring privacy preservation and user convenience.

In this paper, we present a new mathematical model of line balancing for processing time and physical workload at the same time. Line balancing is the problem to assign tasks to stations while satisfying some managerial viewpoints. Most researches about the line balancing problems are focused on the conventional industrial measures that minimizing total processing time and/or number of workstations. Also, independently, some research reports insist some industrial ergonomic issues to be considered for balancing. So, we propose a zero-one integer program model that combines the overload of processing time and physical workload with various risk elements. For the solution techniques, we adopt the goal programming approach and design an appropriate algorithm process. Various computational test runs are performed on the processing time only model, the physical workload only model, and the integrated model. Comparing the pay-offs between the two overloads, test results show us that well balanced job allocation is able to be obtained through the proposed model. And we conclude that the model may be very useful for the operation managers to make decisions on their job scheduling efforts.

Subgradient optimization methods provide a valuable tool for obtaining a lower bound of specially structured linear programming or linear programming relaxation of discrete optimization problems. However, there is no practical rule for obtaining primal optimal solutions from subgradient-based approach other than the lower bounds. This paper presents a class of procedures to recover primal solutions directly from the information generated in the process of using subgradient optimization methods to solve such Lagrangian dual formulations. We also present a hybrid primal dual algorithm based on these methods and some computational results.