bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection and Validation of Tropical Peatland Flaming and Smouldering Using Landsat-8 SWIR and TIRS Bands
Authors: Sofan Parwati , Bruce David , Jones Eriita , Marsden Jackie
Published: February 2019

A Tropical Peatland Combustion Algorithm (ToPeCAl) was first established from Landsat-8 images acquired in 2015, which were used to detect peatland combustion in flaming and smouldering stages. Detection of smouldering combustion from space remains a challenge due to its low temperature and generally small spatial extent. The ToPeCAl consists of the Shortwave Infrared Combustion Index based on reflectance (SICIρ), and Top of Atmosphere (TOA) reflectance in Shortwave Infrared band-7 (SWIR-2), TOA brightness temperature of Thermal Infrared band-10 (TIR-1), and TOA reflectance of band-1, the Landsat-8 aerosol band. The implementation of ToPeCAl was then validated using terrestrial and aerial images (helicopter and drone) collected during fieldwork in Central Kalimantan, Indonesia in the 2018 fire season, on the same day as Landsat-8 overpasses. The overall accuracy of ToPeCAl was found to be 82% with omission errors in a small area (less than 30 m × 30 m) from mixtures of smouldering and vegetation pixels, and commission errors (with minimum area of 30 m x 30 m) on high reflective building rooftops in urban areas. These errors were further reduced by masking and removing urban areas prior to analysis using landuse Geographic Information System (GIS) data; improving the overall mapping accuracy to 93%. For comparison, the day and night-time VIIRS (375 m) active fire product (VNP14IMG) was utilised, obtaining a lower probability of fire detection of 71% compared to ground truth, and 57–72% agreement in a buffer distance of 375 m to 1500 m when compared to the Landsat-8 ToPeCAl results. The night-time data of VNP14IMG was found to have a better correspondence with ToPeCAl results from Landsat 8 than day-time data. This finding could lead to a potential merger of ToPeCAl with VNP14IMG to fill the temporal gaps of peatland fire information when using Landsat. However, the VNP14IMG product exhibited overestimation compared with the results of ToPeCAl applied to Landsat-8.
Photon-Counting Lidar: An Adaptive Signal Detection Method for Different Land Cover Types in Coastal Areas
Authors: Ma Yue , Zhang Wenhao , Sun Jinyan , Li Guoyuan , Wang Xiao Hua , Li Song , Xu Nan
Published: February 2019

Airborne or space-borne photon-counting lidar can provide successive photon clouds of the Earth’s surface. The distribution and density of signal photons are very different because different land cover types have different surface profiles and reflectance, especially in coastal areas where the land cover types are various and complex. A new adaptive signal photon detection method is proposed to extract the signal photons for different land cover types from the raw photons captured by the MABEL (Multiple Altimeter Beam Experimental Lidar) photon-counting lidar in coastal areas. First, the surface types with 30 m resolution are obtained via matching the geographic coordinates of the MABEL trajectory with the NLCD (National Land Cover Database) datasets. Second, in each along-track segment with a specific land cover type, an improved DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm with adaptive thresholds and a JONSWAP (Joint North Sea Wave Project) wave algorithm is proposed and integrated to detect signal photons on different surface types. The result in Pamlico Sound indicates that this new method can effectively detect signal photons and successfully eliminate noise photons below the water level, whereas the MABEL result failed to extract the signal photons in vegetation segments and failed to discard the after-pulsing noise photons. In the Atlantic Ocean and Pamlico Sound, the errors of the RMS (Root Mean Square) wave height between our result and in-situ result are −0.06 m and 0.00 m, respectively. However, between the MABEL and in-situ result, the errors are −0.44 m and −0.37 m, respectively. The mean vegetation height between the East Lake and Pamlico Sound was also calculated as 15.17 m using the detecting signal photons from our method, which agrees well with the results (15.56 m) from the GFCH (Global Forest Canopy Height) dataset. Overall, for different land cover types in coastal areas, our study indicates that the proposed method can significantly improve the performance of the signal photon detection for photon-counting lidar data, and the detected signal photons can further obtain the water levels and vegetation heights. The proposed approach can also be extended for ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) datasets in the future.
Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements
Authors: Yang Huizhang , Chen Chengzhi , Chen Shengyao , Xi Feng
Published: February 2019

This paper presents an efficient sampling system for the acquisition of synthetic aperture radar (SAR) data at sub-Nyquist rate. The system adopts a quadrature compressive sampling architecture, which uses modulation, filtering, sampling and digital quadrature demodulation to produce sub-Nyquist or compressive measurements. In the sequential transmit-receive procedure of SAR, the analog echoes are modulated by random binary chipping sequences to inject randomness into the measurement projection, and the chipping sequences are independent from one observation to another. As a result, the system generates a sequence of independent structured measurement matrices, and then the resulting sensing matrix has better restricted isometry property, as proved by theoretical analysis. As a standard recovery problem in compressive sensing, image formation from the sub-Nyquist measurements has significantly improved performance, which in turn promotes low sampling/data rate. Moreover, the resulting sensing matrix has structures suitable for fast matrix-vector products, based on which we provide a first-order fast image formation algorithm. The performance of the proposed sampling system is assessed by synthetic and real data sets. Simulation results suggest that the proposed system is a valid candidate for sub-Nyquist SAR.
On-Channel Integrated Optofluidic Pressure Sensor with Optically Boosted Sensitivity
Authors: Gaber Noha , Altayyeb Ahmad , Soliman Sherif A. , Sabry Yasser M. , Marty Frédéric , Bourouina Tarik
Published: February 2019

A novel optofluidic sensor that measures the local pressure of the fluid inside a microfluidic channel is presented. It can be integrated directly on-channel and requires no additional layers in fabrication. The detection can be accomplished at a single wavelength; and thereby, only a single laser diode and a single photodetector are required. This renders the sensor to be compact, cheap and easy to fabricate. Basically, the sensor consisted of a Fabry–Pérot microresonator enclosing the fluidic channel. A novel structure of the Fabry–Pérot was employed to achieve high-quality factor, that was essential to facilitate the single wavelength detection. The enhanced performance was attributed to the curved mirrors and cylindrical lenses used to avoid light diffraction loss. The presented sensor was fabricated and tested with deionized water liquid and shown to exhibit a sensitivity up to 12.46 dBm/bar, and a detection limit of 8.2 mbar. Numerical simulations are also presented to evaluate the mechanical–fluidic performance of the device.
A Novel Hierarchical Coding Progressive Transmission Method for WMSN Wildlife Images
Authors: Feng Wenzhao , Hu Chunhe , Wang Yuan , Zhang Junguo , Yan Hao
Published: February 2019

In the wild, wireless multimedia sensor network (WMSN) communication has limited bandwidth and the transmission of wildlife monitoring images always suffers signal interference, which is time-consuming, or sometimes even causes failure. Generally, only part of each wildlife image is valuable, therefore, if we could transmit the images according to the importance of the content, the above issues can be avoided. Inspired by the progressive transmission strategy, we propose a hierarchical coding progressive transmission method in this paper, which can transmit the saliency object region (i.e. the animal) and its background with different coding strategies and priorities. Specifically, we firstly construct a convolution neural network via the MobileNet model for the detection of the saliency object region and obtaining the mask on wildlife. Then, according to the importance of wavelet coefficients, set partitioned in hierarchical tree (SPIHT) lossless coding is utilized to transmit the saliency image which ensures the transmission accuracy of the wildlife region. After that, the background region left over is transmitted via the Embedded Zerotree Wavelets (EZW) lossy coding strategy, to improve the transmission efficiency. To verify the efficiency of our algorithm, a demonstration of the transmission of field-captured wildlife images is presented. Further, comparison of results with existing EZW and discrete cosine transform (DCT) algorithms shows that the proposed algorithm improves the peak signal to noise ratio (PSNR) and structural similarity index (SSIM) by 21.11%, 14.72% and 9.47%, 6.25%, respectively.
Apple Fruit Recognition Algorithm Based on Multi-Spectral Dynamic Image Analysis
Authors: Feng Juan , Zeng Lihua , He Long
Published: February 2019

The ability to accurately recognize fruit on trees is a critical step in robotic harvesting. Many researchers have investigated a variety of image analysis methods based on different imaging technologies for fruit recognition. However, challenges still occur in the implementation of this goal due to various factors, especially variable light and proximal color background. In this study, images with fruit were acquired with a Forward Looking Infrared (FLIR) camera based on the Multi-Spectral Dynamic Imaging (MSX) technology. In view of its imaging mechanism, the optimal timing and shooting angle for image acquisition were pre-analyzed to obtain the maximum contrast between fruit and background. An effective algorithm was developed for locking potential fruit regions, which was based on the pseudo-color and texture information from MSX images. The algorithm was applied to 506 training and 340 evaluating images, including a variety of fruit and complex backgrounds. Recognition precision and sensitivity of these complete fruit regions were both above 92%, and those of incomplete fruit regions were not lower than 72%. The average processing time for each image was less than 1 s. The results indicated that the developed algorithm based on MSX imaging was effective for fruit recognition and could be suggested as a potential method for the automation of orchard production.
Early Visual Detection of Wheat Stripe Rust Using Visible/Near-Infrared Hyperspectral Imaging
Authors: Yao Zhifeng , Lei Yu , He Dongjian
Published: February 2019

Wheat stripe rust is one of the most important and devastating diseases in wheat production. In order to detect wheat stripe rust at an early stage, a visual detection method based on hyperspectral imaging is proposed in this paper. Hyperspectral images of wheat leaves infected by stripe rust for 15 consecutive days were collected, and their corresponding chlorophyll content (SPAD value) were measured using a handheld SPAD-502 chlorophyll meter. The spectral reflectance of the samples were then extracted from the hyperspectral images, using image segmentation based on a leaf mask. The effective wavebands were selected by the loadings of principal component analysis (PCA-loadings) and the successive projections algorithm (SPA). Next, the regression model of the SPAD values in wheat leaves was established, based on the back propagation neural network (BPNN), using the full spectra and the selected effective wavelengths as inputs, respectively. The results showed that the PCA-loadings–BPNN model had the best performance, which modeling accuracy (RC2) and validation accuracy (RP2) were 0.921 and 0.918, respectively, and the RPD was 3.363. The number of effective wavelengths extracted by this model accounted for only 3.12% of the total number of wavelengths, thus simplifying the models and improving the rate of operation greatly. Finally, the optimal models were used to estimate the SPAD of each pixel within the wheat leaf images, to generate spatial distribution maps of chlorophyll content. The visualized distribution map showed that wheat leaves infected by stripe rust could be identified six days after inoculation, and at least three days before the appearance of visible symptoms, which provides a new method for the early detection of wheat stripe rust.
Solving Monocular Visual Odometry Scale Factor with Adaptive Step Length Estimates for Pedestrians Using Handheld Devices
Authors: Antigny Nicolas , Uchiyama Hideaki , Servières Myriam , Renaudin Valérie , Thomas Diego , Taniguchi Rin-ichiro
Published: February 2019

The urban environments represent challenging areas for handheld device pose estimation (i.e., 3D position and 3D orientation) in large displacements. It is even more challenging with low-cost sensors and computational resources that are available in pedestrian mobile devices (i.e., monocular camera and Inertial Measurement Unit). To address these challenges, we propose a continuous pose estimation based on monocular Visual Odometry. To solve the scale ambiguity and suppress the scale drift, an adaptive pedestrian step lengths estimation is used for the displacements on the horizontal plane. To complete the estimation, a handheld equipment height model, with respect to the Digital Terrain Model contained in Geographical Information Systems, is used for the displacement on the vertical axis. In addition, an accurate pose estimation based on the recognition of known objects is punctually used to correct the pose estimate and reset the monocular Visual Odometry. To validate the benefit of our framework, experimental data have been collected on a 0.7 km pedestrian path in an urban environment for various people. Thus, the proposed solution allows to achieve a positioning error of 1.6–7.5% of the walked distance, and confirms the benefit of the use of an adaptive step length compared to the use of a fixed-step length.
Ultrasound Radiation Force for the Assessment of Bone Fracture Healing in Children: An In Vivo Pilot Study
Authors: Ghavami Siavash , Gregory Adriana , Webb Jeremy , Bayat Mahdi , Denis Max , Kumar Viksit , Milbrand Todd A. , Larson A. Noelle , Fatemi Mostafa , Alizad Azra
Published: February 2019

Vibrational characteristics of bone are directly dependent on its physical properties. In this study, a vibrational method for bone evaluation is introduced. We propose a new type of quantitative vibro-acoustic method based on the acoustic radiation force of ultrasound for bone characterization in persons with fracture. Using this method, we excited the clavicle or ulna by an ultrasound radiation force pulse which induces vibrations in the bone, resulting in an acoustic wave that is measured by a hydrophone placed on the skin. The acoustic signals were used for wave velocity estimation based on a cross-correlation technique. To further separate different vibration characteristics, we adopted a variational mode decomposition technique to decompose the received signal into an ensemble of band-limited intrinsic mode functions, allowing analysis of the acoustic signals by their constitutive components. This prospective study included 15 patients: 12 with clavicle fractures and three with ulna fractures. Contralateral intact bones were used as controls. Statistical analysis demonstrated that fractured bones can be differentiated from intact ones with a detection probability of 80%. Additionally, we introduce a “healing factor” to quantify the bone healing progress which successfully tracked the progress of healing in 80% of the clavicle fractures in the study.
Ultra-Low-Power Digital Filtering for Insulated EMG Sensing
Authors: Roland Theresa , Amsuess Sebastian , Russold Michael F. , Baumgartner Werner
Published: February 2019

Myoelectric prostheses help amputees to regain independence and a higher quality of life. These prostheses are controlled by state-of-the-art electromyography sensors, which use a conductive connection to the skin and are therefore sensitive to sweat. They are applied with some pressure to ensure a conductive connection, which may result in pressure marks and can be problematic for patients with circulatory disorders, who constitute a major group of amputees. Here, we present ultra-low-power digital signal processing algorithms for an insulated EMG sensor which couples the EMG signal capacitively. These sensors require neither conductive connection to the skin nor electrolytic paste or skin preparation. Capacitive sensors allow straightforward application. However, they make a sophisticated signal amplification and noise suppression necessary. A low-cost sensor has been developed for real-time myoelectric prostheses control. The major hurdles in measuring the EMG are movement artifacts and external noise. We designed various digital filters to attenuate this noise. Optimal system setup and filter parameters for the trade-off between attenuation of this noise and sufficient EMG signal power for high signal quality were investigated. Additionally, an algorithm for movement artifact suppression, enabling robust application in real-world environments, is presented. The algorithms, which require minimal calculation resources and memory, are implemented on an ultra-low-power microcontroller.
Classification of Lifting Techniques for Application of A Robotic Hip Exoskeleton
Authors: Chen Baojun , Lanotte Francesco , Grazi Lorenzo , Vitiello Nicola , Crea Simona
Published: February 2019

The number of exoskeletons providing load-lifting assistance has significantly increased over the last decade. In this field, to take full advantage of active exoskeletons and provide appropriate assistance to users, it is essential to develop control systems that are able to reliably recognize and classify the users’ movement when performing various lifting tasks. To this end, the movement-decoding algorithm should work robustly with different users and recognize different lifting techniques. Currently, there are no studies presenting methods to classify different lifting techniques in real time for applications with lumbar exoskeletons. We designed a real-time two-step algorithm for a portable hip exoskeleton that can detect the onset of the lifting movement and classify the technique used to accomplish the lift, using only the exoskeleton-embedded sensors. To evaluate the performance of the proposed algorithm, 15 healthy male subjects participated in two experimental sessions in which they were asked to perform lifting tasks using four different techniques (namely, squat lifting, stoop lifting, left-asymmetric lifting, and right-asymmetric lifting) while wearing an active hip exoskeleton. Five classes (the four lifting techniques plus the class “no lift”) were defined for the classification model, which is based on a set of rules (first step) and a pattern recognition algorithm (second step). Leave-one-subject-out cross-validation showed a recognition accuracy of 99.34 ± 0.85%, and the onset of the lift movement was detected within the first 121 to 166 ms of movement.
IKULDAS: An Improved kNN-Based UHF RFID Indoor Localization Algorithm for Directional Radiation Scenario
Authors: Shi Weiguang , Du Jiangxia , Cao Xiaowei , Yu Yang , Cao Yu , Yan Shuxia , Ni Chunya
Published: February 2019

Ultra high frequency radio frequency identification (UHF RFID)-based indoor localization technology has been a competitive candidate for context-awareness services. Previous works mainly utilize a simplified Friis transmission equation for simulating/rectifying received signal strength indicator (RSSI) values, in which the directional radiation of tag antenna and reader antenna was not fully considered, leading to unfavorable performance degradation. Moreover, a k-nearest neighbor (kNN) algorithm is widely used in existing systems, whereas the selection of an appropriate k value remains a critical issue. To solve such problems, this paper presents an improved kNN-based indoor localization algorithm for a directional radiation scenario, IKULDAS. Based on the gain features of dipole antenna and patch antenna, a novel RSSI estimation model is first established. By introducing the inclination angle and rotation angle to characterize the antenna postures, the gains of tag antenna and reader antenna referring to direct path and reflection paths are re-expressed. Then, three strategies are proposed and embedded into typical kNN for improving the localization performance. In IKULDAS, the optimal single fixed rotation angle is introduced for filtering a superior measurement and an NJW-based algorithm is advised for extracting nearest-neighbor reference tags. Furthermore, a dynamic mapping mechanism is proposed to accelerate the tracking process. Simulation results show that IKULDAS achieves a higher positioning accuracy and lower time consumption compared to other typical algorithms.
EffFeu Project: Towards Mission-Guided Application of Drones in Safety and Security Environments
Authors: Hrabia Christopher-Eyk , Hessler Axel , Xu Yuan , Seibert Jacob , Brehmer Jan , Albayrak Sahin
Published: February 2019

The number of unmanned aerial system (UAS) applications for supporting rescue forces is growing in recent years. Nevertheless, the analysis of sensed information and control of unmanned aerial vehicle (UAV) creates an enormous psychological and emotional load for the involved humans especially in critical and hectic situations. The introduced research project EffFeu (Efficient Operation of Unmanned Aerial Vehicle for Industrial Firefighters) especially focuses on a holistic integration of UAS in the daily work of industrial firefighters. This is done by enabling autonomous mission-guided control on top of the presented overall system architecture, goal-oriented high-level task control, comprehensive localisation process combining several approaches to enable the transition from and to GNSS-supported and GNSS-denied environments, as well as a deep-learning based object recognition of relevant entities. This work describes the concepts, current stage, and first evaluation results of the research project.
Parametric Testing of Metasurface Stirrers for Metasurfaced Reverberation Chambers
Authors: Sun Hengyi , Gu Changqing , Li Zhuo , Xu Qian , Wei Mengmeng , Song Jiajia , Xu Baijie , Dong Xiaohang , Wang Kuan , Martín Ferran
Published: February 2019

In this paper, the correlation coefficients and the total scattering cross sections (TSCSs) for different types of metasurfaced stirrers and the traditional metallic stirrer, and the effects on field uniformity when such stirrers are used in reverberation chambers, are analyzed. Three metasurfaced stirrers are considered: A stirrer with two unit cells arranged alternatively (#1), a stirrer with two unit cells arranged in a chessboard-like manner (#2), and a stirrer with two unit cells in random arrangement (#3). From the correlation coefficient and TSCS results obtained in simulations, it follows that metasurfaced stirrer #1 is the best option. Field uniformity analysis of the resulting metasurface reverberation chambers (MRC) equipped with the different stirrers also supports this conclusion.
Monitoring Microwave Ablation Using Ultrasound Echo Decorrelation Imaging: An ex vivo Study
Authors: Zhou Zhuhuang , Wang Yue , Song Shuang , Wu Weiwei , Wu Shuicai , Tsui Po-Hsiang
Published: February 2019

In this study, a microwave-induced ablation zone (thermal lesion) monitoring method based on ultrasound echo decorrelation imaging was proposed. A total of 15 cases of ex vivo porcine liver microwave ablation (MWA) experiments were carried out. Ultrasound radiofrequency (RF) signals at different times during MWA were acquired using a commercial clinical ultrasound scanner with a 7.5-MHz linear-array transducer. Instantaneous and cumulative echo decorrelation images of two adjacent frames of RF data were calculated. Polynomial approximation images were obtained on the basis of the thresholded cumulative echo decorrelation images. Experimental results showed that the instantaneous echo decorrelation images outperformed conventional B-mode images in monitoring microwave-induced thermal lesions. Using gross pathology measurements as the reference standard, the estimation of thermal lesions using the polynomial approximation images yielded an average accuracy of 88.60%. We concluded that instantaneous ultrasound echo decorrelation imaging is capable of monitoring the change of thermal lesions during MWA, and cumulative ultrasound echo decorrelation imaging and polynomial approximation imaging are feasible for quantitatively depicting thermal lesions.
Exploring New Extractive Phases for In-Tube Solid Phase Microextraction Coupled to Miniaturized Liquid Chromatography
Authors: Serra-Mora Pascual , García-Narbona Paola , Verdú-Andrés Jorge , Herráez-Hernández Rosa , Campíns-Falcó Pilar
Published: February 2019

In-tube solid-phase microextraction (IT-SPME) coupled on-line to miniaturized liquid chromatography (LC) has emerged as a powerful tool to address a variety of analytical problems. However, in order to expand its applicability, the development of new sorbents that enhance the efficiency and specificity of the extraction is highly desirable. In this respect, the employment of capillary columns coated with sorbents functionalized with nanoparticles (NPs) replacing the loop of the injection valve (in-valve IT-SPME) is one of the most attractive options. In this work, polymers of tetraethyl orthosilicate (TEOS) and trimethoxyethylsilane (MTEOS) modified with SiO2 and TiO2 NPs have been synthetized and used for the extraction of a variety of water pollutants, using both Capillary-LC and Nano-LC. Compounds with different chemical structures and polarities such as the artificial sweetener saccharine, the polycyclic aromatic hydrocarbons (PAHs) naphthalene and fluoranthene, and some phenylurea and organophosphorous herbicides have been used as target analytes. The extraction efficiencies found with the synthetized capillaries have been compared to those obtained with commercially available capillaries coated with polydiphenyl-polydimethylsiloxane (PDMS), nitroterephthalic acid modified polyetilenglicol (FFAP), and polystyrene-divinylbenzene (PS-DVB) phases. The results obtained in this preliminary study showed that, although PS-DVB phase has the strongest affinity for compounds with two or more aromatic rings, the extraction with TEOS-MTEOS coatings modified with NPs is the best option for a majority of the tested compounds. Examples of application are given.
Investigation of the Exercise Dependence of Athletes Doing Kickboxing, Taekwondo, and Muay Thai
Authors: Orhan Serdar , Yücel Ali Serdar , Sadeq Bootan Jawhar , Orhan Ebru
Published: February 2019

Debates about the conditions in which the frequency and intensity principles of regular exercise, depending on the fact that a sports background can be accepted as extremism, are still a controversial topic. The purpose of this research was to investigate the exercise dependence of athletes who practice Kickboxing, Taekwondo, and Muay Thai. The study included 141 athletes, consisting of 87 men and 54 women. The Exercise Dependence Scale-21 (EDS-21), composed of 21 items developed by Hausenblas and Downs and adapted into the Turkish version by Yeltepe and İkizler, was applied to the athletes. As a result of the research, while athletes showed more sensitivity to the EDS (=71.41), this scale was also defined as symptomatic. It was found that five athletes (3.5%) were asymptomatic-nondependent, 117 athletes (83.0%) were symptomatic-nondependent, and 19 athletes (13.5%) were at risk for exercise dependence. It was determined that athletes were at risk for exercise dependence as follows: Eight athletes were doing Kickboxing, ten athletes were doing Taekwondo, and one athlete was doing Muay Thai. A significant difference was observed according to years of regular training and number of trainings per a day. Other variables presented no significant differences. It was possible to say that years of regular training could be effective in revealing exercise dependence.
Epidemiology of Sports Related Concussion in Brazilian Jiu-Jitsu: A Cross-Sectional Study
Authors: Spano Matthew , Risucci Donald A , Etienne Mill , Petersen Kristina H.
Published: February 2019

Brazilian Jiu-Jitsu (BJJ) is a rapidly growing grappling sport with a wide spectrum of participants. This cross-sectional study examined the lifetime prevalence of concussion in adult BJJ practitioners in the United States using a 17-item survey. A total of 778 (11.4% female) BJJ practitioners with a median age of 31 years completed the survey. Overall, the lifetime prevalence of the self-reported BJJ-related concussion was 25.2%. However, the prevalence was higher among females than males (43.0% versus 22.9%; X2(1,740) = 15.129; p < 0.001). Factors independently associated with significantly increased odds of having sustained a BJJ-related concussion included a prior history of concussion (OR 1.76, 95% CI 1.14–2.74; p = 0.011) and female gender (OR 1.95, 95% CI 1.04–3.65; p = 0.037). The median return to sports time was three days, with 30.3% of participants returning on the same day as being concussed. The present study represents the first epidemiological research examining the concussions in BJJ. The results underscore the need for increased education on concussions and return to sports guidelines among BJJ coaches and practitioners.
Sustainable Supply Chain System Design and Optimization
Authors: Turki Sadok , Rezg Nidhal
Published: February 2019

Due to increasing concerns about the environment, potential economic benefits and legislation pressure; supply chain management has changed to focus on the environmental impacts of production and Earth resource preservation. Therefore, many managers are working hard on improving the sustainability of their supply chain systems. In this paper, we present the themes addressed, and the approaches used in this special issue to investigate the design and optimization of sustainable supply chain systems. Firstly, we introduce the topics under investigation, and then we present the published articles to discuss the benefits of sustainable supply chain systems in raising profits and improving ecology. This issue increases our knowledge of the sustainable supply chain systems design and sustainable strategies.
Does Corporate Social Responsibility Affect the Financial Performance of the Manufacturing Sector? Evidence from an Emerging Economy
Authors: Cherian Jacob , Umar Muhammad , Thu Phung Anh , Nguyen-Trang Thao , Sial Muhammad Safdar , Khuong Nguyen Vinh
Published: February 2019

The present study analyzed the impact of corporate social responsibility (CSR) reporting on the financial performance of Indian companies. It used secondary data from 50 manufacturing companies over the period of fiscal years 2011 to 2017. The results suggested that there exists a significant relationship between the performance of Indian companies and their CSR. The CSR not only improves the firm’s social value and reputation but also improves profitability and performance. According to the results, return on assets is significantly determined by corporate governance, customers, products, number of employees, and board size. The customer has a negative impact on return on assets (ROA). The relationship between return on equity and independent variables is the same as the relationship between ROA and independent variables. Corporate governance and product positively impact ROE, but the relationship between customers, number of employees, and board size are negative. Corporate governance and product positively impact return on capital employed (ROCE), but the relationship between customer and the number of employees is negative. Education has positive impact on profit after tax (PAT) and profit before tax (PBT), but the PAT relationship between environments is negative. Corporate governance and product positively impact PBT. In general, we concluded that in India, socially responsible corporations perform better and vice versa.
Features, Driving Forces and Transition of the Household Energy Consumption in China: A Review
Authors: Jiang Lu , Chen Xingpeng , Xue Bing
Published: February 2019

Household energy consumption has been a major contributor to the increase in global energy demand and carbon emission, and the household sector has also become one of the most crucial factors shaping the management of developments towards sustainability. However, there is still a knowledge gap regarding the household energy consumption in China. Due to the vast territory and the differences among regional conditions, it is critical to conduct a systemic review to illustrate the overall situation as well as the detailed mechanisms of the household energy consumption in China. By employing both qualitative and quantitative methods, two key features of the household energy consumption in China are presented; one is regarding the total amount and the structure of the household energy consumption, and the second is the significant urban-rural gap. The driving forces are investigated from the perspective of external determinants and internal determinants, which consist of seven key factors; finally, the transition roadmap towards the sustainable energy system for the household level are presented based on the text analysis from the four key policy documents. Weaknesses in the current research on the energy geography of household level also exist, such as the lack of single factor research and the lack of integration and comprehensive analysis. Therefore, future studies need to strengthen the research of regional household energy consumption structure, spatial-temporal process, and its motivation mechanism, and sustainable development of energy, so as to explore space-social structure of household energy consumption and spatial-temporal interaction.
How and Why Does Intra-Metropolitan Workplace Location Affect Car Commuting?
Authors: Næss Petter , Tønnesen Anders , Wolday Fitwi
Published: February 2019

This paper illuminates important causal processes that can explain differences between central, semi-central and suburban workplaces in commuting distances and modes. Its empirical base is qualitative interview material on the considerations and conditions underlying commuting behavior among employees of workplaces differently located within Oslo metropolitan area. The interviewees do not necessarily choose local jobs but rather travel a bit farther if this is necessary to find a more relevant job, especially if they have specialized job qualifications. Likewise, employers do not restrict their recruitment to local applicants. Workplaces close to the city center have a large number of potential employees within a short distance from the workplace and are, therefore, more likely to recruit workers locally. The interviewees’ rationales for travel mode choices, such as time-saving, flexibility, convenience and stress avoidance, encourage commuting by transit to central workplaces and by car to peripheral workplaces. For example, transit is often faster and more convenient than car when commuting to central workplaces, while the opposite is often the case for commutes to peripheral workplaces. Rationales of avoidance of stress and frustration and of predictability and control work in similar ways.
Efficiency versus Fairness in the Management of Public Housing Assets in Palermo (Italy)
Authors: Napoli Grazia , Giuffrida Salvatore , Trovato Maria Rosa
Published: February 2019

Public housing policy has been proposing plans of public housing (PH) stock alienation or, as an alternative, property enhancement plans, since administrative and financial commitments have become too heavy for municipalities. This paper deals with one of the current public housing management policy initiatives, undertaken by the Municipality of Palermo (Italy), which aimed at transferring a significant part of the public housing asset to the current tenants, according to some terms and conditions, and applying a politically fixed price. This policy is described in general, focusing on the amount of the assets involved, reporting the terms and conditions for transferring them at an affordable price, and analysing their concentration/distribution in the urban areas. The main aim of the paper is to provide a valuation pattern for defining the trade-off between the efficiency and fairness of such a tool, recognising the conditions for the consistency between the transfer price established by municipality, the merit of the public housing asset, and the market value. A detailed study on two representative neighbourhoods was carried out in order to measure the value of solidarity of this policy and to propose some corrective rules.
Contested Power: American Long-Distance Passenger Rail and the Ambiguities of Energy Intensity Analysis
Authors: Minn Michael
Published: February 2019

This paper is a critical review of research on long-distance passenger rail energy consumption that examines the factors that affect the energy intensity of rail, the comparative energy intensity of alternative modes (auto, air and bus), and the sources of discrepancies between different published energy intensity figures. The ambiguities underlying those discrepancies point to a fundamental question about what phenomenon is being quantified in energy intensity analysis, and whether any transport mode can be said to universally have an energy intensity advantage over other modes at all times, places and scales. This ontological question may be as significant as the epistemic conflicts dominating discourses over competing studies and analytical approaches.
Impact of CARB’s Tailpipe Emission Standard Policy on CO2 Reduction among the U.S. States
Authors: Lim Jaewon , Won DooHwan
Published: February 2019

U.S.Environmental Protection Agency (EPA) set the nationwide emission standard policy, but each state in the U.S. has an option to follow the higher emission standard policy set by CARB (California Air Resources Board) in 2004. There are 14 “CARB states” that follow California’s more restrictive standards. The purpose of this paper is to examine the impact of CARB’s tailpipe emission standard policy. Using the panel dataset for 49 U.S. states over a 28-year study period (1987–2015), this paper found the long-term policy effect in reducing CO2 emission from CARB’s tailpipe standard, and its long-run effect is 5.4 times higher than the short-run effect. The equivalent policy effect of the CARB emission standard in CO2 reduction can be achieved by raising gasoline price by 145.43%. Also, if 26.0% of petroleum consumed for transportation is substituted by alternative clean fuels (natural gas or electricity), it will have a comparable policy effect in CO2 reduction. Findings in this study support to continue the collaborative efforts among the EPA, National Highway Traffic Safety Administration (NHTSA), and California in order to achieve the CO2 reduction goal set by CARB and adopted by the EPA in 2012. The packaged policy approach rooted in persistent public and political support is necessary for successful policy implementation.
A Framework for Ecological Compensation Assessment: A Case Study in the Upper Hun River Basin, Northeast China
Authors: Jiang Xin , Liu Yuyu , Zhao Ranhang
Published: February 2019

With the rapid socio-economic development, human disturbances are believed to have resulted in the degradation of the watershed ecosystem. The ecological damage to and environmental pollution of river basins have caused great losses. It is widely agreed upon that the protection and restoration of river ecosystems should be on the agenda. Ecological compensation, an important tool to prevent the deterioration of water environments and achieve sustainable watershed development, has attracted increasing interest as a research subject. In this study, the upper reach of Hun River basin was selected as a typical study area. The primary purpose was to determine the allocation costs of ecological compensation in different regions for the river basin. The amount of willingness-to-pay (WTP) for the eco-compensation was estimated at 3.2 million dollars by the Contingent Valuation Method (CVM). Based on linear programming techniques, a Data Envelopment Analysis (DEA) created a primary value of the allocation costs. Considering the different weights of each region, a modified coefficient was introduced to correct the primary result on the basis of a questionnaire survey of river ecological protection and construction.
Solar Energy Development in Pakistan: Barriers and Policy Recommendations
Authors: Irfan Muhammad , Zhao Zhen-Yu , Ahmad Munir , Mukeshimana Marie Claire
Published: February 2019

Energy generation is heavily dependent on fossil fuels in Pakistan. Due to the huge population and current progress in industrialization, these sources are not fulfilling the existing energy needs of the country. Meanwhile, they have adverse environmental impacts and are economically unsuitable to electrify remote areas. Consequently, there is a need to look for alternate energy sources. The aim of this paper is to find out the best renewable energy option for Pakistan. For this purpose, we have collected data for solar radiation and wind speed for a period of one year in four major cities of Pakistan. Results indicate that solar energy is the best renewable energy option for Pakistan in terms of price, life span, operation and maintenance cost. Key barriers have been identified over the whole solar energy spectrum through semi-structured interviews with industry professionals. And finally, important policy recommendations have been proposed for institutions and government to overcome these barriers and utilize maximum solar energy in the country.
Key Factors in the Success of Eco-Communities in Taiwan’s Countryside: The Role of Government, Partner, and Community Group
Authors: Sun Chen-Yi , Chen Yen-An , Zhang Xiuzhi
Published: February 2019

The ideals of the successful implementation of an eco-community involve several key elements. This study used a literature review to clarify the key factors for the successful implementation of an eco-community and established the influence of these key elements through expert questionnaires. The results of the study showed that the most crucial part of building a successful eco-community is the community group, followed by the partners who assist the community, and finally the assistance and support of the government. The leader of a community plays the most critical role, followed by the community group, and community self-consciousness. In addition, if the community can establish partnerships with experts, scholars, nongovernmental organizations, and nonprofit organizations, and construct a stable autonomous financial system, the eco-community is guaranteed to continue operating.
Thermal Comfort and Energy Performance of Atrium in Mediterranean Climate
Authors: Aram Reihaneh , Alibaba Halil Zafer
Published: February 2019

This paper aims to determine the optimal single-story office building model with a corner atrium regarding different atrium orientations and office-building window-opening ratios in the Mediterranean climate via EDSL Tas software. When window-opening ratios were 25% and 50% at the northeast and southeast orientations of atriums and office spaces, thermal comfort was achieved according to categories B and C, respectively, within the cold season. Additionally, for the northeast atrium orientation with 25%, 137.2 W and 189.5 W of heat loss and gain in the office zone, and 37.7 W and 204.7 W of heat loss and gain in the atrium zone were recorded. Moreover, for the northeast atrium orientation with 50%, 134.5 W and 134.2 W of heat loss and gain in the office zone, and 40 W and 192 W of heat loss and gain in the atrium zone were recorded. On the other hand, for the southeast atrium orientation with 25%, 108.7 W and 143 W of heat loss and gain in the office zone, and 68.8 W and 130 W of heat loss and gain in the atrium zone were recorded, while, with 50%, 111.7 W and 142.7 W of heat loss and gain in the office zone, and 67.5 W and 121.2 W of heat loss and gain in the atrium zone were recorded. In the warm season, the atrium and office spaces were not thermally comfortable.
Profit Distribution Model for Construction Supply Chain with Cap-and-Trade Policy
Authors: Jiang Wen , Lu Wenfei , Xu Qianwen
Published: February 2019

Cap-and-trade has become one of the most widely used carbon emission limitation methods in the world. Its constraints have a great impact on the carbon emission reduction decisions and production operations of supply chain enterprises, as well as profit distribution. In the construction supply chain, there are few studies on the profit distribution and emission reduction decisions considering cap-and-trade policy. This paper investigates the profit distribution model of a two-echelon construction supply chain consisting of a general contractor and a subcontractor with cap-and-trade policy. Using game theory and Shapley value method, the optimal emission reduction decisions and profit distribution under three cooperation modes of pure competition, co-opetition, and pure cooperation are obtained, respectively. The research shows that the profits of the construction supply chain are increasing in pure competition, co-opetition, and pure cooperation scenarios, and the emission reduction amount of the construction supply chain in the case of pure cooperation is greater than that of pure competition and co-opetition. The carbon emission reduction amount under the co-opetition scenario is not always greater than that under the pure competition scenario, which depends on the emission reduction cost coefficient relationship of general contractor and subcontractor. When the cost coefficient of emission reduction of the general contractor is less than that of the subcontractor, the emission reduction amount under pure competition is larger than that under co-opetition. A numerical study is carried out to verify the conclusions and illustrated the profits of the supply chain decreased with the increase of carbon emission reduction cost coefficient, and had nothing to do with the emission reduction efficiency of enterprises.
Toward Self-Driving Bicycles Using State-of-the-Art Deep Reinforcement Learning Algorithms
Authors: Choi SeungYoon , Le Tuyen P. , Nguyen Quang D. , Layek Md Abu , Lee SeungGwan , Chung TaeChoong
Published: February 2019

In this paper, we propose a controller for a bicycle using the DDPG (Deep Deterministic Policy Gradient) algorithm, which is a state-of-the-art deep reinforcement learning algorithm. We use a reward function and a deep neural network to build the controller. By using the proposed controller, a bicycle can not only be stably balanced but also travel to any specified location. We confirm that the controller with DDPG shows better performance than the other baselines such as Normalized Advantage Function (NAF) and Proximal Policy Optimization (PPO). For the performance evaluation, we implemented the proposed algorithm in various settings such as fixed and random speed, start location, and destination location.
Some General Classes of q-Starlike Functions Associated with the Janowski Functions
Authors: Srivastava Hari M. , Tahir Muhammad , Khan Bilal , Ahmad Qazi Zahoor , Khan Nazar
Published: February 2019

By making use of the concept of basic (or q-) calculus, various families of q-extensions of starlike functions of order α in the open unit disk U were introduced and studied from many different viewpoints and perspectives. In this paper, we first investigate the relationship between various known classes of q-starlike functions that are associated with the Janowski functions. We then introduce and study a new subclass of q-starlike functions that involves the Janowski functions. We also derive several properties of such families of q-starlike functions with negative coefficients including (for example) distortion theorems.