bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimation of Handgrip Force from SEMG Based on Wavelet Scale Selection
Authors: Wang Kai , Zhang Xianmin , Ota Jun , Huang Yanjiang
Published: February 2018

This paper proposes a nonlinear correlation-based wavelet scale selection technology to select the effective wavelet scales for the estimation of handgrip force from surface electromyograms (SEMG). The SEMG signal corresponding to gripping force was collected from extensor and flexor forearm muscles during the force-varying analysis task. We performed a computational sensitivity analysis on the initial nonlinear SEMG-handgrip force model. To explore the nonlinear correlation between ten wavelet scales and handgrip force, a large-scale iteration based on the Monte Carlo simulation was conducted. To choose a suitable combination of scales, we proposed a rule to combine wavelet scales based on the sensitivity of each scale and selected the appropriate combination of wavelet scales based on sequence combination analysis (SCA). The results of SCA indicated that the scale combination VI is suitable for estimating force from the extensors and the combination V is suitable for the flexors. The proposed method was compared to two former methods through prolonged static and force-varying contraction tasks. The experiment results showed that the root mean square errors derived by the proposed method for both static and force-varying contraction tasks were less than 20%. The accuracy and robustness of the handgrip force derived by the proposed method is better than that obtained by the former methods.
Second Generation Small Pixel Technology Using Hybrid Bond Stacking
Authors: Venezia Vincent , Hsiung Alan , Yang Wu-Zang , Zhang Yuying , Zhao Cheng , Lin Zhiqiang , Grant Lindsay
Published: February 2018

In this work, OmniVision’s second generation (Gen2) of small-pixel BSI stacking technologies is reviewed. The key features of this technology are hybrid-bond stacking, deeper back-side, deep-trench isolation, new back-side composite metal-oxide grid, and improved gate oxide quality. This Gen2 technology achieves state-of-the-art low-light image-sensor performance for 1.1, 1.0, and 0.9 µm pixel products. Additional improvements on this technology include less than 100 ppm white-pixel process and a high near-infrared (NIR) QE technology.
Mn4+-Doped Magnesium Titanate—A Promising Phosphor for Self-Referenced Optical Temperature Sensing
Authors: Venturini Francesca , Baumgartner Michael , Borisov Sergey
Published: February 2018

Phosphors based on magnesium titanate activated with Mn 4 + ions are of great interest because, when excited with blue light, they display a strong red-emitting luminescence. They are characterized by a luminescence decay which is strongly temperature dependent in the range from −50 ∘ C to 150 ∘ C, making these materials very promising for temperature sensing in the biochemical field. In this work, the optical and thermal properties of the luminescence of Mg 2 TiO 4 are investigated for different Mn 4 + doping concentrations. The potential of this material for temperature sensing is demonstrated by fabricating a fiber optic temperature microsensor and by comparing its performance against a standard resistance thermometer. The response of the fiber optic sensor is exceptionally fast, with a response time below 1 s in the liquid phase and below 1.1 s in the gas phase.
The Design of a Single-Bit CMOS Image Sensor for Iris Recognition Applications
Authors: Park Keunyeol , Song Minkyu , Kim Soo
Published: February 2018

This paper presents a single-bit CMOS image sensor (CIS) that uses a data processing technique with an edge detection block for simple iris segmentation. In order to recognize the iris image, the image sensor conventionally captures high-resolution image data in digital code, extracts the iris data, and then compares it with a reference image through a recognition algorithm. However, in this case, the frame rate decreases by the time required for digital signal conversion of multi-bit digital data through the analog-to-digital converter (ADC) in the CIS. In order to reduce the overall processing time as well as the power consumption, we propose a data processing technique with an exclusive OR (XOR) logic gate to obtain single-bit and edge detection image data instead of multi-bit image data through the ADC. In addition, we propose a logarithmic counter to efficiently measure single-bit image data that can be applied to the iris recognition algorithm. The effective area of the proposed single-bit image sensor (174 × 144 pixel) is 2.84 mm2 with a 0.18 μm 1-poly 4-metal CMOS image sensor process. The power consumption of the proposed single-bit CIS is 2.8 mW with a 3.3 V of supply voltage and 520 frame/s of the maximum frame rates. The error rate of the ADC is 0.24 least significant bit (LSB) on an 8-bit ADC basis at a 50 MHz sampling frequency.
An Automatic Gait Feature Extraction Method for Identifying Gait Asymmetry Using Wearable Sensors
Authors: Anwary Arif , Yu Hongnian , Vassallo Michael
Published: February 2018

This paper aims to assess the use of Inertial Measurement Unit (IMU) sensors to identify gait asymmetry by extracting automatic gait features. We design and develop an android app to collect real time synchronous IMU data from legs. The results from our method are validated using a Qualisys Motion Capture System. The data are collected from 10 young and 10 older subjects. Each performed a trial in a straight corridor comprising 15 strides of normal walking, a turn around and another 15 strides. We analyse the data for total distance, total time, total velocity, stride, step, cadence, step ratio, stance, and swing. The accuracy of detecting the stride number using the proposed method is 100% for young and 92.67% for older subjects. The accuracy of estimating travelled distance using the proposed method for young subjects is 97.73% and 98.82% for right and left legs; and for the older, is 88.71% and 89.88% for right and left legs. The average travelled distance is 37.77 (95% CI ± 3.57) meters for young subjects and is 22.50 (95% CI ± 2.34) meters for older subjects. The average travelled time for young subjects is 51.85 (95% CI ± 3.08) seconds and for older subjects is 84.02 (95% CI ± 9.98) seconds. The results show that wearable sensors can be used for identifying gait asymmetry without the requirement and expense of an elaborate laboratory setup. This can serve as a tool in diagnosing gait abnormalities in individuals and opens the possibilities for home based self-gait asymmetry assessment.
Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time
Authors: Zhang Yeqing , Wang Meiling , Li Yafeng
Published: February 2018

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully.
Comparison of Feature Learning Methods for Human Activity Recognition Using Wearable Sensors
Authors: Li Frédéric , Shirahama Kimiaki , Nisar Muhammad , Köping Lukas , Grzegorzek Marcin
Published: February 2018

Getting a good feature representation of data is paramount for Human Activity Recognition (HAR) using wearable sensors. An increasing number of feature learning approaches—in particular deep-learning based—have been proposed to extract an effective feature representation by analyzing large amounts of data. However, getting an objective interpretation of their performances faces two problems: the lack of a baseline evaluation setup, which makes a strict comparison between them impossible, and the insufficiency of implementation details, which can hinder their use. In this paper, we attempt to address both issues: we firstly propose an evaluation framework allowing a rigorous comparison of features extracted by different methods, and use it to carry out extensive experiments with state-of-the-art feature learning approaches. We then provide all the codes and implementation details to make both the reproduction of the results reported in this paper and the re-use of our framework easier for other researchers. Our studies carried out on the OPPORTUNITY and UniMiB-SHAR datasets highlight the effectiveness of hybrid deep-learning architectures involving convolutional and Long-Short-Term-Memory (LSTM) to obtain features characterising both short- and long-term time dependencies in the data.
An Unsupervised Deep Hyperspectral Anomaly Detector
Authors: Ma Ning , Peng Yu , Wang Shaojun , Leong Philip
Published: February 2018

Hyperspectral image (HSI) based detection has attracted considerable attention recently in agriculture, environmental protection and military applications as different wavelengths of light can be advantageously used to discriminate different types of objects. Unfortunately, estimating the background distribution and the detection of interesting local objects is not straightforward, and anomaly detectors may give false alarms. In this paper, a Deep Belief Network (DBN) based anomaly detector is proposed. The high-level features and reconstruction errors are learned through the network in a manner which is not affected by previous background distribution assumption. To reduce contamination by local anomalies, adaptive weights are constructed from reconstruction errors and statistical information. By using the code image which is generated during the inference of DBN and modified by adaptively updated weights, a local Euclidean distance between under test pixels and their neighboring pixels is used to determine the anomaly targets. Experimental results on synthetic and recorded HSI datasets show the performance of proposed method outperforms the classic global Reed-Xiaoli detector (RXD), local RX detector (LRXD) and the-state-of-the-art Collaborative Representation detector (CRD).
Analysis of Resonance Asymmetry Phenomenon in Resonant Fiber Optic Gyro
Authors: Li Zhuoyan , He Nie , Sun Xuqiang , Jin Chao , Liu Chengxiang , Wu Xu
Published: February 2018

This experiment demonstrated the resonance asymmetry phenomenon in the resonant fiber optic gyro. The asymmetry of resonant curve affects the system open-loop bias and its stability, which directly affects the accuracy of angular velocity measurement. In this paper, a new mathematic model is established. The influence of the coupler normal mode loss difference (the phase difference between the coupler cross port output optical field and direct port is less than the ideal π/2) on the symmetry of resonant curve, the resonant signal modulated by the triangular wave, and the demodulation curve are analyzed. Moreover, the asymmetry of the resonant curve leads to the asymmetry of the resonant signal, as modulated by the triangular wave and the demodulation curve from the theoretical simulation and the experiment.
Auto-Calibration and Fault Detection and Isolation of Skewed Redundant Accelerometers in Measurement While Drilling Systems
Authors: Seyed Moosavi Seyed , Moaveni Bijan , Moshiri Behzad , Arvan Mohammad
Published: February 2018

The present study designed skewed redundant accelerometers for a Measurement While Drilling (MWD) tool and executed auto-calibration, fault diagnosis and isolation of accelerometers in this tool. The optimal structure includes four accelerometers was selected and designed precisely in accordance with the physical shape of the existing MWD tool. A new four-accelerometer structure was designed, implemented and installed on the current system, replacing the conventional orthogonal structure. Auto-calibration operation of skewed redundant accelerometers and all combinations of three accelerometers have been done. Consequently, biases, scale factors, and misalignment factors of accelerometers have been successfully estimated. By defecting the sensors in the new optimal skewed redundant structure, the fault was detected using the proposed FDI method and the faulty sensor was diagnosed and isolated. The results indicate that the system can continue to operate with at least three correct sensors.
An Affordable Insole-Sensor-Based Trans-Femoral Prosthesis for Normal Gait
Authors: Pandit Srinivas , Godiyal Anoop , Vimal Amit , Singh Upinderpal , Joshi Deepak , Kalyanasundaram Dinesh
Published: February 2018

This paper proposes a novel and an affordable lower limb prosthesis to enable normal gait kinematics for trans-femoral amputees. The paper details the design of a passive prosthesis with magneto-rheological (MR) damping system and electronic control. A new control approach based on plantar insole feedback was employed here. Strategically placed sensors on the plantar insole provide required information about gait cycle to a finite state controller for suitable action. A proportional integral (PI) based current controller controls the required current for necessary damping during gait. The prosthesis was designed and developed locally in India keeping in view the cost, functionality, socio-economic, and aesthetic requirements. The prototype was experimentally tested on a trans-femoral amputee and the results are presented in this work. The implementation of the proposed design and control scheme in the prototype successfully realizes the notion that normal gait kinematics can be achieved at a low cost comparable to passive prostheses. The incurring cost and power expenditure of the proposed prosthesis are evaluated against passive and active prostheses, respectively. The commercial implications for the prosthesis were explored on the basis of recommendations of ISPO Consensus Conference on Appropriate Prosthetic Technology in Developing Countries. The key objective of this work is to enable lucid design for development of an affordable prosthesis in a low-resource setting.
Temporal Noise Analysis of Charge-Domain Sampling Readout Circuits for CMOS Image Sensors
Authors: Ge Xiaoliang , Theuwissen Albert
Published: February 2018

This paper presents a temporal noise analysis of charge-domain sampling readout circuits for Complementary Metal-Oxide Semiconductor (CMOS) image sensors. In order to address the trade-off between the low input-referred noise and high dynamic range, a Gm-cell-based pixel together with a charge-domain correlated-double sampling (CDS) technique has been proposed to provide a way to efficiently embed a tunable conversion gain along the read-out path. Such readout topology, however, operates in a non-stationery large-signal behavior, and the statistical properties of its temporal noise are a function of time. Conventional noise analysis methods for CMOS image sensors are based on steady-state signal models, and therefore cannot be readily applied for Gm-cell-based pixels. In this paper, we develop analysis models for both thermal noise and flicker noise in Gm-cell-based pixels by employing the time-domain linear analysis approach and the non-stationary noise analysis theory, which help to quantitatively evaluate the temporal noise characteristic of Gm-cell-based pixels. Both models were numerically computed in MATLAB using design parameters of a prototype chip, and compared with both simulation and experimental results. The good agreement between the theoretical and measurement results verifies the effectiveness of the proposed noise analysis models.
Comments on “A New Elliptical Model for Device-Free Localization”
Authors: Yuan Yanan , Ke Wei , Jin Jie , Lu Jun , Shao Jianhua
Published: February 2018

A recent paper “A New Elliptical Model for Device-Free Localization” (Sensors 2016, 16, 577) presents a new geometry-based elliptical model for Device-free localization (DFL). In this comment, we point out some problems of the original paper and exploit the same data used in the original paper to demonstrate the existence of these problems. Then, we give a modified formula to correct their model. Meanwhile, a real experiment is performed to verify our conclusion.
Ion Chromatography Applications in Wastewater Analysis
Authors: Michalski Rajmund
Published: February 2018

Wastewater analysis is an important area in analytical and environmental chemistry. It can be performed with both the classic wet methods and instrumental techniques. The development of new methods, and modification of the existing ones, constitute a major task for researchers. Ion chromatography plays a predominant role in ion determinations with the instrumental methods. It offers several advantages over the conventional methods, such as simultaneous determinations of alkali and alkaline earth cations and ammonia. Ammonium ions cannot be determined by spectroscopic methods. Ion chromatography has been accepted world-wide as a reference method for analyzing anions and cations in water and wastewater due to the fact that it enables the replacement of several individual wet chemistry methods for common ions with one instrumental technique. The following article describes the principles of ion chromatography, such as stationary phases, eluents, detectors, and sample preparation methods. Moreover, the applications of ion chromatography in wastewater analyses and international standards are presented.
Sustainability, Transformational Leadership, and Social Entrepreneurship
Authors: Muralidharan Etayankara , Pathak Saurav
Published: February 2018

This article examines the extent to which culturally endorsed transformational leadership theories (CLTs) and the sustainability of society, both considered societal level institutional indicators, impact the emergence of social entrepreneurship. Using 107,738 individual-level responses from 27 countries for the year 2009 obtained from the Global Entrepreneurship Monitor (GEM) survey, and supplementing with country-level data obtained from Global Leadership and Organizational Behavior Effectiveness (GLOBE) and Sustainability Society Foundation (SSF), our findings from multilevel analysis show that transformational CLTs and sustainability conditions of society positively influence the likelihood of individuals becoming social entrepreneurs. Further, the effectiveness of transformational CLTs matters more for social entrepreneurship when the sustainability of society is low, which suggests the interaction between cultural leadership styles and societal sustainability. This article contributes to comparative entrepreneurship research by introducing strong cultural antecedents of social entrepreneurship in transformational CLTs and societal sustainability. We discuss various implications and limitations of our study, and we suggest directions for future research.
Social Network Analysis of Scientific Articles Published by Food Policy
Authors: Popp József , Balogh Péter , Oláh Judit , Kot Sebastian , Harangi Rákos Mónika , Lengyel Péter
Published: February 2018

The article analyses co-authorship and co-citation networks in Food Policy, which is the most important agricultural policy journal in the field of agricultural economics. The paper highlights the principal researchers in this field together with their authorship and citation networks on the basis of 714 articles written between 2006 and 2015. Results suggest that the majority of the articles were written by a small number of researchers, indicating that groups and central authors play an important role in scientific advances. It also turns out that the number of articles and the central role played in the network are not related, contrary to expectations. Results also suggest that groups cite themselves more often than average, thereby boosting the scientific advancement of their own members.
Analysis of Carbon Emission Reduction in a Dual-Channel Supply Chain with Cap-And-Trade Regulation and Low-Carbon Preference
Authors: Wang Xiaoyan , Xue Minggao , Xing Lu
Published: February 2018

This paper focuses on the reduction of carbon emissions driven by cap-and-trade regulation and consumers’ low-carbon preference in a dual-channel supply chain. Under the low-carbon environment, we also discuss the pricing strategies and the profits for the supply chain members using the Stackelberg game model in two cases. In the first (second) case where the initial proportion of consumers who prefer the online direct channel (traditional retail channel) is “larger”, the direct sale price of low-carbon products could be set higher than (equal to) the wholesale price. And it is shown that in both cases, tighter cap-and-trade regulation and higher low-carbon preference stimulate the manufacturer to cut carbon emissions in its production process. However, improving consumers’ low-carbon preference is more acceptable to the supply chain members. It always benefits the manufacturer and the retailer. In comparison, the firm’s profit increases with carbon price only when the clean production level is relatively high. Our findings can provide useful managerial insights for policy-makers and firms in the development of low-carbon sustainability.
Does a Board Chairman’s Political Connection Affect Green Investment?—From a Sustainable Perspective
Authors: Wang Kai , Zhang Hao-Min , Tsai Sang-Bing , Wu Li-Dong , Xue Kun-Kun , Fan He-Jun , Zhou Jie , Chen Quan
Published: February 2018

Using a sample consisting of China’s listed manufacturing companies which issue A-shares on the Shenzhen and Shanghai stock exchanges from 2008–2014, this study empirically tests the relationship between board chairman’s political connections and the amount of energy conservation and emission reduction investment. The results show that the existence of politically-connected board chairmen positively affects green investment. In addition, marketization degrees negatively moderate the relationship between political connection and green investment, which supports an institutional logic perspective. The amount of redundant resources also has the same moderating effect, which is consistent with the resource exchange perspective.
Green Roof for Stormwater Management in a Highly Urbanized Area: The Case of Seoul, Korea
Authors: Shafique Muhammad , Kim Reeho , Kyung-Ho Kwon
Published: February 2018

Urbanization changes natural pervious surfaces to hard, impervious surfaces such as roads, buildings and roofs. These modifications significantly affect the natural hydrologic cycle by increasing stormwater runoff rates and volume. Under these circumstances, green roofs offer multiple benefits including on-site stormwater management that mimics the natural hydrologic conditions in an urban area. It can retain a large amount of rainwater for a longer time and delay the peak discharge. However, there is very limited research that has been carried out on the retrofitted green roof for stormwater management for South Korean conditions. This study has investigated the performance of retrofitted green roofs for stormwater management in a highly urbanized area of Seoul, the capital city of Korea. In this study, various storm events were monitored and the research results were analyzed to check the performance of the green roof with controlling the runoff in urban areas. Results also allowed us to conclude that the retention mainly depends on the intensity and duration of the rain events. From the analysis, average runoff retention on the green roof was 10% to 60% in different rain events. The application of an extensive green roof provides promising results for stormwater management in the highly urbanized area of Seoul.
Sustainability Biogas Production from Ensiled Plants Consisting of the Transformation of the Digestate into a Valuable Organic-Mineral Granular Fertilizer
Authors: Prask Hubert , Szlachta Józef , Fugol Małgorzata , Kordas Leszek , Lejman Agnieszka , Tużnik Franciszek , Tużnik Filip
Published: February 2018

The research concerned the elaborate of non-waste biogas production technology based on the development of digestate from anaerobic digestion. In the anaerobic digestion process, the substrates of plant origin in the form of silage were used. The digestate obtained after biogas production was processed using the ORTWED method into a valuable granulated organic-mineral fertilizer, which contains a solid fraction of digestate, calcium and biogenic elements. This method can be successfully applied in agriculture in the context of its sustainable development due to the growing problem of utilization of digestate forming in agricultural biogas plants.
Curve Number Applications for Restoration the Zarqa River Basin
Authors: Shammout Maisa’a , Shatanawi Muhammad , Nelson Jim
Published: February 2018

The great demand for water resources from the Zarqa River Basin (ZRB) has resulted in a base-flow reduction of the River from 5 m3/s to less than 1 m3/s. This paper aims to predict Curve Numbers (CNs) as a baseline scenario and propose restoration scenarios for the ZRB. The method includes classifying the soil type and land use, predicting CNs, and proposing CN restoration scenarios. The prediction of existing CNs will be in parallel with the runoff prediction by using the US Army Corps of Engineers HEC-1 Model, and the Rainfall–Runoff Model (RRM). The models have been set up at the land use distribution of 0.3% water body, 9.3% forest and orchard, 71% mixture of grass, weeds, and desert shrubs, 7.0% crops, 4.0% urban areas, and 8.4% bare soil. The results show that CNs are 59, 78 and 89 under dry, normal and wet conditions, respectively. During the vegetation period, CNs are 52, 72 and 86 for dry, normal and wet conditions respectively. The restoration scenarios include how CNs decrease the runoff and increase the soil moisture when using the contours, terraces and crop residues. Analyzing the results of CN scenarios will be a fundamental tool in achieving watershed restoration targets.
An Investigation of the Influence of the Worldwide Governance and Competitiveness on Accounting Fraud Cases: A Cross-Country Perspective
Authors: Sadaf Rabeea , Oláh Judit , Popp József , Máté Domicián
Published: February 2018

This article examines how worldwide governance, global competiveness, and other institutional determinants have influenced the number of accounting fraud cases in several countries. The researchers have focused more closely on the importance of ‘good governance’ as one of the indicators of development objectives in itself. The institutional perspective is employed to explain the complexity of frauds in different societies which can be compatible for the purposes of international judgments in order to increase the effectiveness of previous forensic accounting theories. In this paper, a linear regression model is tested where governance, competitiveness, and other institutional variables are associated with a measure of accounting fraud cases. From our results, we can merely claim that an increased level of controlled corruption and political stability might reduce the number of fraud cases in various countries, while more effective and independent governance services with a higher freedom of expression seemed to increase them. The existence of accounting crimes also appeared to be a suitable proxy of better competitiveness. Anglo-Saxon countries have more stated fraud cases than other countries, attributed, perhaps, to the finest commercial courts with the most professional and least corrupt judges in the world, with centuries of precedent cases and experience in dealing with fraud. Moreover, we believe that a better understanding of fraud detection is a potentially important element in forensic accounting analytics in the success of governance policies to enhance development and reduce the risk of bankruptcies related to the reported fraud cases of enterprises.
Spatiotemporal Patterns of Desertification Dynamics and Desertification Effects on Ecosystem Services in the Mu Us Desert in China
Authors: Liu Qingfu , Zhao Yanyun , Zhang Xuefeng , Buyantuev Alexander , Niu Jianming , Wang Xiaojiang
Published: February 2018

Degradation of semi-arid and arid ecosystems due to desertification is arguably one of the main obstacles for sustainability in those regions. In recent decades, the Mu Us Desert in China has experienced such ecological degradation making quantification of spatial patterns of desertification in this area an important research topic. We analyzed desertification dynamics for seven periods from 1986 to 2015 and focused on five ecosystem services including soil conservation, water retention, net primary productivity (NPP), crop productivity, and livestock productivity, all assessed for 2015. Furthermore, we examined how ecosystem services relate to each other and are impacted by desertification. Three major conclusions are drawn from the study. First, the eastern part of the study area experienced overall improvement while desertification in the west first increased and then reversed its trend during those periods between 1986 and 2015. Second, significant synergistic relationships are observed for three regulating services (soil conservation, water retention, NPP) and two provisioning services (crop productivity and livestock productivity). Strong relationships across different types of ecosystem services were found only between crop productivity and NPP. Third, in response to increasing desertification, the three regulating services exhibit a monotonically decreasing trend, while the two provisioning services follow a hump-shaped response.
Sustainable Global Sourcing: A Systematic Literature Review and Bibliometric Analysis
Authors: Jia Fu , Jiang Yan
Published: February 2018

Sustainable Global Sourcing (SGS) is a rapidly emerging field with a geometric growth that is evidenced by the number of articles published within this field. The aim of this paper is to develop a systematic study quantitatively depicting the knowledge structure of the SGS field. A bibliometric analysis in conjunction with citation analysis and co-citation analysis is adopted to evaluate a total of 287 journal articles identified from systematic selection of influential work. A further content analysis is performed to obtain the detailed insights on the results of bibliometric analysis. Findings show five research clusters that constitute the SGS field, i.e., (i) Global Sourcing (GS) practice and environmental performance; (ii) Social sustainability/ethical sourcing practice in GS; (iii) Environmental evaluation criteria and certification; (iv) Fuzzy modelling of environmental practice in GS; (v) Effects of environmental and social sustainability practice on economic performance. On this basis, eight research directions are outlined for future research. This study provides an innovative method for systematic literature review work and robust indications for future investigations in the SGS field.
Mapping the Landscape and Evolutions of Green Supply Chain Management
Authors: Shan Wei , Wang Jingyi
Published: February 2018

There is a growing need to integrate environmental considerations into supply chain management research and practice. Conceptual papers are being updated all the time to gain a systematic view of the framework in green supply chain management. The purpose of this paper is to visualize the research to-date on green supply chain management according to the intellectual framework and hot topics. Using bibliometric analysis, our paper will present a comprehensive summary of previous research on the knowledge domain. Exploring 1145 papers mainly published from 2000 to May 2017 in international peer-reviewed journals from social sciences citation index (SSCI), the basic distribution of publications are analyzed, and nine prominent research clusters in green supply chain management are visualized by a co-citation network. Key issues are highlighted and analyzed. As for future inquiries, there are numerous opportunities for more advanced theoretically-grounded research and exploration of more multi-functional and systematic approaches. In order to gain broader views of research, a triple bottom line approach can be widely applied to evaluation, impact mechanisms, decision making, drivers, risks and carrier analysis, as well as system contributions. This also provides an integrated point of view to understand the landscape of green supply chain management both for researchers and practitioners.
Use Cases with Economics and Simulation for Thermo-Chemical District Networks
Authors: Geyer Philipp , Delwati Muhannad , Buchholz Martin , Giampieri Alessandro , Smallbone Andrew , Roskilly Anthony P. , Buchholz Reiner , Provost Mathieu
Published: February 2018

Thermo-chemical networks using absorption and desorption to capture and valorise the potential of very low-grade residual heat (20 °C to 60 °C) to offer a reduction of end user costs and increased primary energy efficiency. The paper demonstrates the technical and economic potential of thermo-chemical networks by defining use cases and their related level of energy efficiency and technological feasibility. Furthermore, specific economic scenarios, including estimations on investment and operation costs, demonstrate the economic benefit of the technology. Simple payback periods between about 0.5 and 7.5 years indicate a good economic feasibility with end user costs below 4 €ct/kWh-equivalent and refunds of 0.5 to 1 €ct/kWh for the required residual heat. Due to the low-temperature characteristics of the relevant systems and services, detailed simulations are required to approve the functioning and viability of the new technology. For this purpose, the paper demonstrates the simulation outline using the example of space heating based on a low-temperature air heating system partially driven with thermo-chemical fuel.
Promoting Sustainability through Investment in Building Information Modeling (BIM) Technologies: A Design Company Perspective
Authors: Reizgevičius Marius , Ustinovičius Leonas , Cibulskienė Diana , Kutut Vladislavas , Nazarko Lukasz
Published: February 2018

The aim of this article is to enhance the understanding of how design companies perceive the benefits of Building Information Modeling (BIM) technologies application. BIM is recognized in the literature as a (potentially) powerful driver leading the construction sector towards sustainability. However, for design companies, the choice to invest in BIM technologies is basically an economic one. Specifically, a design company assesses economic benefits and efficiency improvements thanks to the application of BIM technologies. The article discusses the return on investments (ROI) in BIM technologies and reviews ROI calculation methodologies proposed by other authors. In order to evaluate BIM return on investment correctly practical ROI calculations are carried out. Appropriate methods, together with the relevant variables for ROI calculation, are developed. The study allows for adjusting the calculation method making it more accurate and understandable using the Autodesk Revit based ROI calculation of the first year.
From Uncertainties to Successful Start Ups: A Data Analytic Approach to Predict Success in Technological Entrepreneurship
Authors: Tomy Sarath , Pardede Eric
Published: February 2018

Understanding uncertainties and assessing the risks surrounding business opportunities is essential to support the success of sustainable entrepreneurial initiatives launched on a daily basis. The contribution of this study is the identification of uncertainties surrounding opportunities in the opportunity evaluation stage of the entrepreneurial process and the examination of how the analysis and evaluation of uncertainty factors, with the help of data, can predict the future success of an organization. In the first phase, the uncertainty factors are classified based on their sources and we discuss the likely implications towards new venture success with the help of existing literatures. In the second phase, a success prediction model is implemented using machine learning techniques and strategic analysis. The model is trained in such a way that, when new data emerges, the qualitative data is transformed into quantitative data and the probability of success or failure is calculated as the result output in the pre-start-up phase. The method and findings would be relevant for nascent entrepreneurs and researchers focusing on sustainable technology entrepreneurship.
Rheological Behaviour of a Bitumen Modified with Metal Oxides Obtained by Regeneration Processes
Authors: Giuffrè Tullio , Morreale Marco , Tesoriere Giovanni , Trubia Salvatore
Published: February 2018

Nowadays, one important challenge is to demonstrate an innovative and integrated approach for the sustainable construction of roads considering the whole life cycle of the infrastructure. Road pavements with multiple asphalt layers generally undergo prolonged environmental exposure and the alternation between solar irradiation and low temperatures. As a result, relaxation or progressive removal of the material with a negative impact on the resistance to plastic deformation occur, also leading to the formation of slits and to dimensional variations, which are commonly defined as thermal cracking. This suggests the use of suitable bitumen modifiers. For these, important parameters are the optimal mixing time and mixing temperature, in order to reduce problems related to the stability of the bitumen. Therefore, the behaviour, upon changing the temperature, of bituminous mixtures containing (as fillers) a series of metal oxides coming, as secondary products, from spent acid solutions regeneration processes, was investigated. This is intended in order to recover and reuse those otherwise dangerous wastes coming from several industrial (especially, metallurgical) processes. The study was aimed at evaluating the properties of bituminous blends by performing rheological tests under dynamic shear regime. More specifically, five different bitumen matrices were prepared (70/100 bitumen and blends with metal oxides and/or SBS copolymer). Results showed that the addition of iron oxides leads to an increase of the softening point and the complex modulus. The increase is even more emphasized when SBS is added to the blend.
How Will Policies of China’s CO2 ETS Affect its Carbon Price: Evidence from Chinese Pilot Regions
Authors: Yang Baochen , Liu Chuanze , Gou Zehao , Man Jiacheng , Su Yunpeng
Published: February 2018

CO2 Emissions Trading Scheme is a key policy instrument for dealing with increasing greenhouse gas emissions. This work aims at giving some policy recommendations on the design of China’s National Emissions Trading Scheme. The experience accumulated in China’s Carbon Emissions Trading Pilots is quite valuable for China’s National Emissions Trading Scheme, so it is important to analyze the determinants of the prices in these pilots. We use the difference-in-differences model to study various policies respectively, including auction, investment access of individual and institutional traders, and carbon forward. Principal components of economy, energy, climate and allowance characteristic are respectively extracted from alternative variables, such as CPI, energy price, extreme temperature, in four categories. These principal components are set as control variables. Results show that these policies play a big role in the price discovery and stabilization. Auction drives the market price to approach the auction completion price. Carbon price exhibits a positive sensitivity to non-regulated entities’ participation and carbon forward. All the significant variables together can reflect most of the pilots’ price information. Policies have heterogeneous impacts on carbon price. The finding is robust to alternative specifications.
Management Strategies and Innovations: Important Roles to Sustainable Construction
Authors: Hwang Bon-Gang , Shan Ming
Published: February 2018

While sustainable construction has gained rapid growth worldwide in recent years, it is confronting various challenges and problems, particularly those from a management perspective. This Special Issue collects 16 original research articles relating to management strategies and innovations of sustainable construction, which are mainly concentrated in three areas: the adoption of sustainable construction technologies and products, the development of sustainable built environment, and the organization studies associated with sustainable construction.
Can Next-Generation Vehicles Sustainably Survive in the Automobile Market? Evidence from Ex-Ante Market Simulation and Segmentation
Authors: Shin Jungwoo , Lim Taehoon , Kim Moo , Choi Jae
Published: February 2018

Introduced autonomous and connected vehicles equipped with emerging technologies are expected to change the automotive market. In this study, using stated preference (SP) data collected from choice experiments conducted in Korea with a mixed multiple discrete-continuous extreme value model (MDCEV), we analyzed how the advent of next-generation of vehicles with advanced vehicle technologies would affect consumer vehicle choices and usage patterns. Additionally, ex-ante market simulations and market segmentation analyses were conducted to provide specific management strategies for next-generation vehicles. The results showed that consumer preference structures of conventional and alternative fuel types primarily differed depending on whether they were drivers or non-drivers. Additionally, although the introduction of electric vehicles to the automobile market is expected to negatively affect the choice probability and mileage of other vehicles, it could have a positive influence on the probability of purchasing an existing conventional vehicle if advanced vehicle technologies are available.
Optimal Investment Planning of Bulk Energy Storage Systems
Authors: Khastieva Dina , Dimoulkas Ilias , Amelin Mikael
Published: February 2018

Many countries have the ambition to increase the share of renewable sources in electricity generation. However, continuously varying renewable sources, such as wind power or solar energy, require that the power system can manage the variability and uncertainty of the power generation. One solution to increase flexibility of the system is to use various forms of energy storage, which can provide flexibility to the system at different time ranges and smooth the effect of variability of the renewable generation. In this paper, we investigate three questions connected to investment planning of energy storage systems. First, how the existing flexibility in the system will affect the need for energy storage investments. Second, how presence of energy storage will affect renewable generation expansion and affect electricity prices. Third, who should be responsible for energy storage investments planning. This paper proposes to assess these questions through two different mathematical models. The first model is designed for centralized investment planning and the second model deals with a decentralized investment approach where a single independent profit maximizing utility is responsible for energy storage investments. The models have been applied in various case studies with different generation mixes and flexibility levels. The results show that energy storage system is beneficial for power system operation. However, additional regulation should be considered to achieve optimal investment and allocation of energy storage.
Towards the Handling Demand Response Optimization Model for Home Appliances
Authors: Veras Jaclason , Silva Igor , Pinheiro Plácido , Rabêlo Ricardo
Published: February 2018

The Demand Response (DR) is used by public electric utilities to encourage consumers to change their consumption profiles to improve the reliability and efficiency of the electric power system (EPS) and at the same time to minimize the electricity costs for the final consumers. Normally, DR optimization models only aim to reduce the energy consumption and reduce the final cost. However, this disregards the needs of the consumer. Therefore, proposals which appear excellent in theory are usually impracticable and non-commercial. This paper proposes a real-time Demand Response (DR) optimization model to minimize the electricity costs associated with consumption without compromising the satisfaction or comfort of residential consumers. The proposed DR here considered the different home appliance categories and level of consumer satisfaction for the new load scheduling of the appliances and is much more comprehensive than the other models analyzed. Moreover, it can be applied in any country, under any energy scenario. This model was developed as a nonlinear programming problem subject to a set of constraints. An energy consumption analysis of 10 families for 2015 from five geographic and climatic regions of Brazil was carried out. A computational validation of the model was performed using a genetic algorithm (GA) to determine the programming of residential devices for the time horizon. The computational simulations showed a decrease in the cost of the electricity. Moreover, the results showed that there was no impairment to consumer satisfaction and comfort due to the scheduling of appliances.
Evolving and Strengthening the Cooperative Approach for Agroforestry Farmers in Bangladesh: Lessons Learned from the Shimogo Cooperative in Japan
Authors: Islam Kazi , Fujiwara Takahiro , Sato Noriko , Hyakumura Kimihiko
Published: February 2018

Although an agro-based country, the farmers of Bangladesh do not receive significant returns from their products, due to some obstacles blocking the achievement of this ultimate goal. This study tries to identify the major challenges of the agroforestry product supply chains in Bangladesh, and offer an alternative solution through the involvement and experiences of farmer cooperatives within a Japanese cooperative model. The objectives were outfitted by two case studies, and the Bangladesh case clearly showed that the involvement of many intermediaries in agroforestry product supply chains was one of the main obstacles that stunted the outcomes of the agroforestry programs. The intermediaries have maximized their profit by buying the farmer products at low prices and selling them back at higher prices, which resulted in high marketing margins. Meanwhile, the Japanese case study had articulated that the farmer-driven cooperative approach, with its good marketing strategies and service functions, could successfully eliminate the intermediaries’ involvement in farmer products, and make a cooperative a strong economic organization. Despite a few challenges, the farmer-driven Japanese cooperative approach would be a good solution that could tackle the middleman problem, and make agroforestry a sustainable production system in Bangladesh.