The Efficiency Measurement of Indonesian Universities Based on a Fuzzy Data Envelopment Analysis

The main objective of this study is to measure the relative efficiency of Indonesian universities in 2015. There are twenty five DMUs with four inputs and five outputs that are analyzed. Due to the low number of Indonesian scientific publications, this study analyses the performance of the top 25 universities based on the Webometrics ranking as it has been used as one of the indicators of university achievements by the Higher Education of Indonesia. The Data Envelopment Analysis (DEA) is used to obtain the scores of efficiency, while the Fuzzy approach is applied to address the possibility of errors from the auditor’s assessment in determining the input and output variables correctly. The FDEA can be used in measuring the universities performances under imprecise inputs and outputs. Both the CRS (constant returns to scale) and the VRS (variable returns to scale) models are presented. The empirical results show that 36 percent of universities perform efficiently on the CRS model while 52 percent of universities have efficient performances under the VRS model. Furthermore, the well-known universities have shown relatively low scores, which indicate they need to improve their performances in publishing scientific work, as well as providing useful information to the public through the official websites. Generally, the results of the VRS model are better than the CRS model for both the DEA and the FDEA methods.

Speed Profile as a Tool to Estimate Traffic Calming Measures Efficiency

TCMs （traffic calming measures） are commonly installed in order to reduce speeds and volumes of traffic to acceptable levels and, thus, improve traffic safety as well as environmental impact when designed appropriately as a corridor or aerial implementation with proper spacing. Hence in many previous studies, their impact was mainly evaluated in scope of average and 85th percentile speed reduction. This paper presents and appraises the efficiency of calming measures of various types used in the city of Bialystok, Poland in terms of their influence zone. The assessment is based on speed profiles derived from individual test rides conducted with test vehicle equipped with GPS （global positioning system） data logger to obtain vehicle trajectory data. Speed measurements were conducted in vicinity of most commonly installed calming measures such as speed cameras, raised pedestrian crossing, raised intersection, speed bumps and speed cushion. The results reveal great differences within analysed devices and the usefulness of speed profiles in evaluation of their effectiveness. Speed bumps, most frequently used device in practice due to their low cost installation and speed reduction effectiveness, demonstrate lowest usefulness when influence zone is considered.

Empirical Study on the Measurement of the High-Tech Industry Efficiency in China--Based on the Data of China＇s 31 Provinces （Including Municipalities and Autonomous Regions）

To evaluate the relative effectiveness of the input and output of the high-tech industry in China＇s 31 provinces （including municipalities and autonomous regions）, DEA evaluation model was constructed using data envelopment analysis （DEA）, and DEA evaluation model was solved using Deap2.1 software, for the purpose of obtaining the DEA efficiency and the non-DEA efficiency in all the provinces （including municipalities and autonomous regions）. Then, the comprehensive efficiency, technical efficiency, scale efficiency, scale return, and projection analysis were analyzed. Finally, the provinces of the non-DEA efficiency are sorted according to three efficiencies, and also a goal of improvement is proposed for the purpose of expanding technology investment in the provinces of the DEA efficiency.

How to compare market efficiency? The Sharpe ratio based on the ARMA-GARCH forecast

This paper derives a new method for comparing the weak-form efficiency of markets.The author derives the formula of the Sharpe ratio from the ARMA-GARCH model and finds that the Sharpe ratio just depends on the coefficients of the AR and MA terms and is not affected by the GARCH process.For empirical purposes,the Sharpe ratio can be formulated with a monotonic increasing function of R-squared if the sample size is large enough.One can utilize the Sharpe ratio to compare weak-form efficiency among different markets.The results of stochastic simulation demonstrate the validity of the proposed method.The author also constructs empirical AR-GARCH models and computes the Sharpe ratio for S&P 500 Index and the SSE Composite Index.

Evaluating the energy impact potential of energy efficiency measures for retrofit applications:A case study with U.S.medium office buildings

Quantifying the energy savings of various energy efficiency measures(EEMs)for an energy retrofit project often necessitates an energy audit and detailed whole building energy modeling to evaluate the EEMs;however,this is often cost-prohibitive for small and medium buildings.In order to provide a defined guideline for projects with assumed common baseline characteristics,this paper applies a sensitivity analysis method to evaluate the impact of individual EEMs and groups these into packages to produce deep energy savings for a sample prototype medium office building across 15 climate zones in the United States.We start with one baseline model for each climate zone and nine candidate EEMs with a range of efficiency levels for each EEM.Three energy performance indicators(EPIs)are defined,which are annual electricity use intensity,annual natural gas use intensity,and annual energy cost.Then,a Standard Regression Coefficient(SRC)sensitivity analysis method is applied to determine the sensitivity of each EEM with respect to the three EPIs,and the relative sensitivity of all EEMs are calculated to evaluate their energy impacts.For the selected range of efficiency levels,the results indicate that the EEMs with higher energy impacts(i.e.,higher sensitivity)in most climate zones are high-performance windows,reduced interior lighting power,and reduced interior plug and process loads.However,the sensitivity of the EEMs also vary by climate zone and EPI;for example,improved opaque envelope insulation and efficiency of cooling and heating systems are found to have a high energy impact in cold and hot climates.

Industrial Green Spatial Pattern Evolution of Yangtze River Economic Belt in China

We use the directional slacks-based measure of efficiency and inverse distance weighting method to analyze the spatial pattern evolution of the industrial green total factor productivity of 108 cities in the Yangtze River Economic Belt in 2003–2013.Results show that both the subprime mortgage crisis and ‘the new normal' had significant negative effects on productivity growth,leading to the different spatial patterns between 2003–2008 and 2009–2013.Before 2008,green poles had gathered around some capital cities and formed a tripartite pattern,which was a typical core-periphery pattern.Due to a combination of the polarization and the diffusion effects,capital cities became the growth poles and ‘core' regions,while surrounding areas became the ‘periphery'.This was mainly caused by the innate advantage of capital cities and ‘the rise of central China' strategy.After 2008,the tripartite pattern changed to a multi-poles pattern where green poles continuously and densely spread in the midstream and downstream areas.This is due to the regional difference in the leading effect of green poles.The leading effect of green poles in midstream and downstream areas has changed from polarization to diffusion,while the polarization effect still leads in the upstream area.

A Learning-Based Channel Model for Synergetic Transmission Technology

It is extensively approved that Channel State Information(CSI) plays an important role for synergetic transmission and interference management. However, pilot overhead to obtain CSI with enough precision is a significant issue for wireless communication networks with massive antennas and ultra-dense cell. This paper proposes a learning- based channel model, which can estimate, refine, and manage CSI for a synergetic transmission system. It decomposes the channel impulse response into multiple paths, and uses a learning-based algorithm to estimate paths' parameters without notable degradation caused by sparse pilots. Both indoor measurement and outdoor measurement are conducted to verify the feasibility of the proposed channel model preliminarily.

Efficiency measurement of fertilizer-manufacturing organizations usingFuzzy data envelopment analysis

The aim of the paper is to benchmark the performance of the Indian fertilizermanufacturing organizations based on the ranking of efficiencies using a fuzzy data envelopment analysis(FDEA).FDEA has been used to find the relative efficiency and ranking of the fertilizer-manufacturing organizations.The last few years’data have been converted into the fuzzy inputs and outputs as minimum,mean,and maximum values,respectively.The performance of the fertilizer manufacturing organizations is based on the output maximization model of DEA.The frontier organizations set the benchmark for the lagging organizations for further improvement in the performance.This method can also be used to incorporate the data of the several years for multiple inputs and outputs instead of consideration of data of only one year.The proposed approach in this study may help organizations to improve its efficiency to fulfill its goal.

A New Method to Measure the Coupling Efficiency of Waveguide Photodetector

In this paper, a new method is outlined for the estimation of coupling efficiency between a source laser and a WGPD. Internal quantum efficiencies as high as 72% (for 0.15μm device) and 86.5% (for 0.5μm device) are achieved.

Decomposition of China＇s Industrial Environmental Total Factor Productivity Sources： Analysis Based on Factor Input and Pollution Treatment

Following slack-based inefficiency measurement method and Luenberger productivity index, this paper decomposes industrial environmental TFP index by input factors and output to estimate the sources of China＇s industrial environmental TFP. Results indicate that （1） China＇s industrial environmental TFP increased between 2001 and 2007 but declined in 2008 under the effect of global financial crisis; （2） input utilization productivity contributes 1/3 to industrial environmental TFP and pollution treatment productivity contributes about 2/3, which means that pollution treatment will effectively increase industrial environmental TFP; （3） capital utilization productivity contributes I/6 to input productivity and labor utilization productivity contributes about 5/6, which means that progress of labor production technologies is an effective means to increase industrial environmental TFP; （4） COD treatment productivity contributes roughly 2/3 to pollution treatment productivity, and S02 treatment productivity contributes about 1/3, which shows that priority on COD treatment will more effectively increase industrial environmental TFP.

Performance Assessment of European Football Teams： Using Stochastic Data Envelopment Analysis Model

Data Envelopment Analysis （DEA） is a powerful mathematical optimization method widely used for measuring, evaluating and improving the performance of Decision Making Units （DMUs）. These used in the various forms, such as hospitals, government agencies, educational institutions, air force, bank branches, business finns, sport teams and even people including the performance of countries, regions, etc. Recently DEA has been extended to examine the performance through the different sport types. In this paper, a Stochastic Input Oriented Data Envelopment Analysis （SIODEA） Model is conducted for measuring and evaluating the relative efficiency scores of football teams selected from different European countries during 2014/2015 season each with some of inputs are stochastic with normally distributed and recent inputs are deterministic and outputs, to shed light on the professional football teams performance.

Coupling and coordinated evolution characteristics of regional economy-energy-carbon emission multiple systems:A case study of main China's Basin

Comprehensive analysis of the Economy-Energy-Carbon Emission(EECE)system is beneficial for promoting sustainable social development.This study analyzes the system development of major watersheds in China from 2010 to 2019.The research fully considers the system’s internal and external inputs and outputs and proposes an evaluation index system for regional EECE coupling and coordinated development.Then,using the difference in system weight allocation to improve the coupling and coordination model,the study explores the dynamic system’s coupling and coordination.The results show that(1)The development of the system structure is relatively stable,but the overall development status is not ideal;(2)The downstream of China’s main river basins has obvious economic advantages,while the energy system fluctuates greatly.The efficiency of the carbon emission system will decrease in areas with rapid economic development.The coupling and coordination level of the EECE system is better in the Yangtze River Basin than in the Yellow River Basin;(3)From the perspective of dynamic coordinated development,the main river basins have been divided into two states since 2012,but it is relatively stable overall.Regional dynamic coordination is often at a disadvantage in regions with rapid economic and energy development;(4)The coupling coordination degree of the two river basins has significant positive spatial autocorrelation.Most provinces’significant spatial clustering characteristics of the coupling coordination degree are High-High type.Low-Low type provinces are mainly concentrated downstream.The research process has certain reference significance for the collaborative governance of complex regional systems.

Measuring efficiency of crop cleaners by image analysis

The purity of product from agricultural cleaners(such as chile,cotton,bean,wheat and other crop cleaners)is needed to be measured under various conditions in order to adjust and optimize the machine at the design and improvement stages.The traditional weight-based method of measuring purity is time consuming,and requires much labor.In this study,we used image analysis to measure percent crop cover for the product output to infer the purity.Chile cleaner was used as one example machine to compare between Photoshop©and Arcview©software for the analysis of fresh and dry harvest pictures.The data collection process is more reproducible and less labor and time consuming than the traditional technique.Both software packages provided accurate estimations of purity for both fresh and dry harvest pictures.Photoshop©had better accuracy than Arcview©(mean error ratio of 0.016 vs.0.081 for fresh harvest;and 0.035 vs.0.114 for dry harvest).

An Analysis of Energy and Environment Efficiency of China＇s Iron and Steel Industry

Due to heavy energy consumption and low technical efficiency, China＇s iron and steel industry is trapped in the dilemma ＂large but not strong＂. This situation not only exerts enormous pressure on energy security but also on increased carbon emission and environmental pollution. The contribution of this study is to calculate the energy and environment efficiency of China＇s iron and steel industry and to analyze the factors affecting this efficiency. An index of energy and environment efficiency is introduced based on Directional Slacks-based Distance Measure Model. This index is adopted to measure the energy and environment efficiency of China＇s iron and steel industry using 2,382 firm observations during 2001 to 2005. In addition, Hierarchy Linear Model （HLM） is applied to analyze the factors which can influence the efficiency with both firm-level and province-level data. The conclusions are as follows： The energy and environment efficiency of China＇s iron and steel industry did not have a significant change during the research period. A firm＇s age, size, ownership, product category and the economy of its province have significant influence on its energy and environment efficiency.

A point-wise minimization model for data envelopment analysis considering environmental variables

Environmental variables are widely recognized as a cause of differences in efficiency measurement.However,the existing literature on data envelopment analysis(DEA)in environmental factors ignores the impact of demand on output.To address this gap,we propose the Point-wise Minimization DEA model(PWMDEA),which considers contextual variables that affect demand and lead to differences in efficiency.The model obtains efficiency value by considering the minimum of virtual inputs and virtual demand.Then,efficiency is evaluated by minimizing the ratio of above minimum to virtual output.This one-step model avoids issues of multi-stage assumptions and requires less data,making it more applicable.Moreover,we demonstrate the accuracy of our new model by conducting simulations with given true efficiency values.The simulation results demonstrate that our model has the lowest ranking error when the output is affected by multiple inputs or when demand has a significant impact.In addition,we evaluate the efficiency of healthcare in 31 Chinese provinces by considering two environmental factors.The results suggest that provinces with lower financial investments or population loss received higher rankings from our proposed model.These findings provide plausible explanations and demonstrate the practical usefulness of our model.

On the thrust performance of an ionic polymer-metal composite actuated robotic fish: Modeling and experimental investigation

In this paper, we theoretically predict and experimentally measure the thrust efficiency of a biomimetic robotic fish, which is propelled by an ionic polymer-metal composite （IPMC） actuator. A physics-based model that consists of IPMC dynamics and hydrodynamics was proposed, and simulation was conducted. In order to test the thrust performance of the robotic fish, a novel experimental apparatus was developed for hydrodynamic experiments. Under a servo towing system, the IPMC fish swam at a self-propelled speed where external force is averagely zero. Experimental results demonstrated that the theoretical model can well predict the thrust efficiency of the robotic fish. A maximum thrust efficiency of 2.3x10-3 at 1 Hz was recorded experi- mentally, the maximum thrust force was 0.0253 N, recorded at 1.2 Hz, while the maximum speed was 0.021 m/s, recorded at 1.5 Hz, and a peak power of 0.36 W was recorded at 2.6 Hz. Additionally, the optimal actuation frequency for the thrust efficiency was also recorded at the maximum self-propelled speed. The present method of examining the thrust efficiency may also be applied to the studies of other types of smart material actuated underwater robots.