TWO-STAGE EFFICIENCY MEASUREMENT AND TECHNOLOGICAL HETEROGENEITY: EVIDENCE FROM THE BIOTECHNOLOGICAL INDUSTRY IN TAIWAN

2014 ◽  
Vol 31 (01) ◽  
pp. 1450007
Author(s):  
YUNG-HSIANG LU ◽  
YUNG-HO CHIU ◽  
CHING-REN CHIU ◽  
YU-CHIAO HUNG
Keyword(s):  
Time Lag ◽  
Listed Companies ◽  
Two Stage ◽  
Listed Firms ◽  
Second Stage ◽  
Business Operations ◽  
Efficiency Assessment ◽  
Operating Process ◽  
Gap Ratio ◽  
Stage Efficiency

This paper explores the operational and market efficiencies of various biotechnological company formats in Taiwan during the period 2006 to 2008 by adopting the two-stage directional distance function and the meta-frontier concept. It conducts an efficiency assessment by taking into account a five-year time lag between R&D investments and actually obtaining a patent in order to better reflect the actual business operating process and thus more accurately gauge the efficiency of business operations in biotechnological companies. The empirical results show that non-listed companies registered better operational efficiency in the first stage, whereas their market efficiency in the second stage is inferior to that of listed companies when the meta-technology set is used as a basis. The average operation gap ratio and market gap ratio of non-listed companies exceeded those of listed firms, indicating that the technological heterogeneity (i.e., the gap) of non-listed companies is smaller than that of listed ones.

scholarly journals Research on Efficiency of Animation Enterprises Based on Two-Stage DEA Network System Model of Sharing Input Resources

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Shuo Zhang ◽  
Xuemei Yang ◽  
Jian Zhang ◽  
Mengjie Liao ◽  
Lin Qi
Keyword(s):  
Production Quality ◽  
System Model ◽  
Network System ◽  
Research Model ◽  
Two Stage ◽  
Second Stage ◽  
Production Quantity ◽  
Overall Efficiency ◽  
Stage Efficiency

This research constructs a two-stage DEA network system model of shared input resources to evaluate the efficiency of animation companies: the first-stage efficiency to reflect the production quantity and the second-stage efficiency to reflect the production quality of animation products, where the quality of animation products is judged based on the market recognition of the animation products. The overall efficiency in the research model is used to describe the development of animation enterprises. According to the result, it is concluded that the overall efficiency of the surveyed animation companies and the efficiency of each sub-stage have shown an upward trend, which is in line with the growth of the company's development.

Effects of Multiblocking and Axial Gap Distance on Performance of Partial Admission Turbines: A Numerical Analysis

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
Narmin Baagherzadeh Hushmandi ◽  
Torsten H. Fransson
Keyword(s):  
Rotor Blades ◽  
Test Case ◽  
Two Stage ◽  
Second Stage ◽  
Partial Admission ◽  
Flow Interactions ◽  
Single Arc ◽  
And Performance ◽  
Stage Efficiency ◽  
Better Than

In this paper, the effects of axial gap distance between the first stage stator and rotor blades and multiblocking on aerodynamics and performance of partial admission turbines are analyzed numerically. The selected test case is a two stage axial steam turbine with low reaction blades operating with compressed air. The multiblocking effect is studied by blocking the inlet annulus of the turbine in a single arc and in two opposing blocked arcs, each having the same admission degree. The effect of axial gap distance between the first stage stator and rotor blades is studied while varying the axial gap by 20% compared with the design gap distance. Finally, full admission turbine is modeled numerically for comparison. Performance of various computational cases showed that the first stage efficiency of the two stage partial admission turbine with double blockage was better than that of the single blockage turbine; however, the extra mixing losses of the double blockage turbine caused the efficiency to deteriorate in the downstream stage. It was shown that the two stage partial admission turbine with smaller axial gap than the design value had better efficiency of the first stage due to lower main flow and leakage flow interactions; however, the efficiency at the second stage decreased faster compared with the other cases. Numerical computations showed that the parameters, which increased the axial force of the first stage rotor wheel for the partial admission turbine, were longer blocked arc, single blocked arc, and reduced axial gap distance between the first stage stator and rotor blades.

An Enhanced Two Stage MMSE Equalizer for Coded FBMC/OQAM Systems

2019 ◽  
Vol 10 (1) ◽  
pp. 69-82 ◽  
Author(s):  
Mohammad Rizk Assaf ◽  
Abdel-Nasser Assimi
Keyword(s):  
Error Propagation ◽  
Channel Model ◽  
Error Correcting Codes ◽  
Two Stage ◽  
Probability Of Error ◽  
Second Stage ◽  
Different Types ◽  
Mmse Equalizer ◽  
And Performance ◽  
Ici Cancellation

In this article, the authors investigate the enhanced two stage MMSE (TS-MMSE) equalizer in bit-interleaved coded FBMC/OQAM system which gives a tradeoff between complexity and performance, since error correcting codes limits error propagation, so this allows the equalizer to remove not only ICI but also ISI in the second stage. The proposed equalizer has shown less design complexity compared to the other MMSE equalizers. The obtained results show that the probability of error is improved where SNR gain reaches 2 dB measured at BER compared with ICI cancellation for different types of modulation schemes and ITU Vehicular B channel model. Some simulation results are provided to illustrate the effectiveness of the proposed equalizer.

Personalised attraction recommendation for enhancing topic diversity and accuracy

2021 ◽  
pp. 016555152199980
Author(s):  
Yuanyuan Lin ◽  
Chao Huang ◽  
Wei Yao ◽  
Yifei Shao
Keyword(s):  
Real World ◽  
Information Overload ◽  
Two Stage ◽  
Misclassification Cost ◽  
Second Stage ◽  
Low Visibility ◽  
Recommendation Diversity ◽  
Optimisation Model ◽  
Definition Of ◽  
Improved Methods

Attraction recommendation plays an important role in tourism, such as solving information overload problems and recommending proper attractions to users. Currently, most recommendation methods are dedicated to improving the accuracy of recommendations. However, recommendation methods only focusing on accuracy tend to recommend popular items that are often purchased by users, which results in a lack of diversity and low visibility of non-popular items. Hence, many studies have suggested the importance of recommendation diversity and proposed improved methods, but there is room for improvement. First, the definition of diversity for different items requires consideration for domain characteristics. Second, the existing algorithms for improving diversity sacrifice the accuracy of recommendations. Therefore, the article utilises the topic ‘features of attractions’ to define the calculation method of recommendation diversity. We developed a two-stage optimisation model to enhance recommendation diversity while maintaining the accuracy of recommendations. In the first stage, an optimisation model considering topic diversity is proposed to increase recommendation diversity and generate candidate attractions. In the second stage, we propose a minimisation misclassification cost optimisation model to balance recommendation diversity and accuracy. To assess the performance of the proposed method, experiments are conducted with real-world travel data. The results indicate that the proposed two-stage optimisation model can significantly improve the diversity and accuracy of recommendations.

scholarly journals Two-stage multi-tasking transform framework for large-scale many-objective optimization problems

2021 ◽  
Author(s):  
Lu Chen ◽  
Handing Wang ◽  
Wenping Ma
Keyword(s):  
Large Scale ◽  
Original Problem ◽  
Optimization Problems ◽  
Reference Points ◽  
Optimization Strategy ◽  
Two Stage ◽  
Decision Space ◽  
Second Stage ◽  
Decision Variables ◽  
Objective Space

AbstractReal-world optimization applications in complex systems always contain multiple factors to be optimized, which can be formulated as multi-objective optimization problems. These problems have been solved by many evolutionary algorithms like MOEA/D, NSGA-III, and KnEA. However, when the numbers of decision variables and objectives increase, the computation costs of those mentioned algorithms will be unaffordable. To reduce such high computation cost on large-scale many-objective optimization problems, we proposed a two-stage framework. The first stage of the proposed algorithm combines with a multi-tasking optimization strategy and a bi-directional search strategy, where the original problem is reformulated as a multi-tasking optimization problem in the decision space to enhance the convergence. To improve the diversity, in the second stage, the proposed algorithm applies multi-tasking optimization to a number of sub-problems based on reference points in the objective space. In this paper, to show the effectiveness of the proposed algorithm, we test the algorithm on the DTLZ and LSMOP problems and compare it with existing algorithms, and it outperforms other compared algorithms in most cases and shows disadvantage on both convergence and diversity.

scholarly journals A Two-Stage Mono- and Multi-Objective Method for the Optimization of General UPS Parallel Manipulators

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 543
Author(s):  
Alejandra Ríos ◽  
Eusebio E. Hernández ◽  
S. Ivvan Valdez
Keyword(s):  
Genetic Algorithm ◽  
Performance Metrics ◽  
Tracking Error ◽  
Parallel Manipulators ◽  
Optimization Method ◽  
Statistical Hypothesis ◽  
Two Stage ◽  
Multi Objective ◽  
Second Stage ◽  
Conflicting Objectives

This paper introduces a two-stage method based on bio-inspired algorithms for the design optimization of a class of general Stewart platforms. The first stage performs a mono-objective optimization in order to reach, with sufficient dexterity, a regular target workspace while minimizing the elements’ lengths. For this optimization problem, we compare three bio-inspired algorithms: the Genetic Algorithm (GA), the Particle Swarm Optimization (PSO), and the Boltzman Univariate Marginal Distribution Algorithm (BUMDA). The second stage looks for the most suitable gains of a Proportional Integral Derivative (PID) control via the minimization of two conflicting objectives: one based on energy consumption and the tracking error of a target trajectory. To this effect, we compare two multi-objective algorithms: the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) and Non-dominated Sorting Genetic Algorithm-III (NSGA-III). The main contributions lie in the optimization model, the proposal of a two-stage optimization method, and the findings of the performance of different bio-inspired algorithms for each stage. Furthermore, we show optimized designs delivered by the proposed method and provide directions for the best-performing algorithms through performance metrics and statistical hypothesis tests.

scholarly journals Fast Two-Stage Computation of an Index Policy for Multi-Armed Bandits with Setup Delays

Mathematics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 52
Author(s):  
José Niño-Mora
Keyword(s):  
Numerical Study ◽  
Arithmetic Operation ◽  
Bandit Problem ◽  
Index Policy ◽  
Two Stage ◽  
Second Stage ◽  
Whittle Index ◽  
Set Up ◽  
Computing Method ◽  
Special Case

We consider the multi-armed bandit problem with penalties for switching that include setup delays and costs, extending the former results of the author for the special case with no switching delays. A priority index for projects with setup delays that characterizes, in part, optimal policies was introduced by Asawa and Teneketzis in 1996, yet without giving a means of computing it. We present a fast two-stage index computing method, which computes the continuation index (which applies when the project has been set up) in a first stage and certain extra quantities with cubic (arithmetic-operation) complexity in the number of project states and then computes the switching index (which applies when the project is not set up), in a second stage, with quadratic complexity. The approach is based on new methodological advances on restless bandit indexation, which are introduced and deployed herein, being motivated by the limitations of previous results, exploiting the fact that the aforementioned index is the Whittle index of the project in its restless reformulation. A numerical study demonstrates substantial runtime speed-ups of the new two-stage index algorithm versus a general one-stage Whittle index algorithm. The study further gives evidence that, in a multi-project setting, the index policy is consistently nearly optimal.

scholarly journals Multiple Sclerosis: Assessment of Disease Progression and Effects of Treatment

1987 ◽  
Vol 14 (S3) ◽  
pp. 518-520 ◽  
Author(s):  
D.W. Paty
Keyword(s):  
Multiple Sclerosis ◽  
Disease Progression ◽  
Treatment Effects ◽  
Two Stage ◽  
Second Stage ◽  
Sequential Development ◽  
Stage Disease

ABSTRACT:MS could well be a two stage disease. The first stage involves the sequential development of multiple small lesions, mostly inflammatory, that accumulate at a given rate. The second stage could be that of consolidation and confluence of lesions that involves not only demyelination but gliosis. MRI now gives us an opportunity to watch the evolution of these processes and also to monitor treatment effects. It is only after the evolution of this process is understood that we can design rational therapies directed toward the prevention of spasticity in MS.

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