bluuebunny/crossref_metadata_2025 huggingface dataset:
Impacts of Climate Change on Lake Fluctuations in the Hindu Kush-Himalaya-Tibetan Plateau
Authors: Yang Xiankun , Lu Xixi , Park Edward , Tarolli Paolo
Published: May 2019

Lakes in the Hindu Kush-Himalaya-Tibetan (HKHT) regions are crucial indicators for the combined impacts of regional climate change and resultant glacier retreat. However, they lack long-term systematic monitoring and thus their responses to recent climatic change still remain only partially understood. This study investigated lake extent fluctuations in the HKHT regions over the past 40 years using Landsat (MSS/TM/ETM+/OLI) images obtained from the 1970s to 2014. Influenced by different regional atmospheric circulation systems, our results show that lake changing patterns are distinct from region to region, with the most intensive lake shrinking observed in northeastern HKHT (HKHT Interior, Tarim, Yellow, Yangtze), while the most extensive expansion was observed in the western and southwestern HKHT (Amu Darya, Ganges Indus and Brahmaputra), largely caused by the proliferation of small lakes in high-altitude regions during 1970s–1995. In the past 20 years, extensive lake expansions (~39.6% in area and ~119.1% in quantity) were observed in all HKHT regions. Climate change, especially precipitation change, is the major driving force to the changing dynamics of the lake fluctuations; however, effects from the glacier melting were also significant, which contributed approximately 31.9–40.5%, 16.5–39.3%, 12.8–29.0%, and 3.3–6.1% of runoff to lakes in the headwaters of the Tarim, Amu Darya, Indus, and Ganges, respectively. We consider that the findings in this paper could have both immediate and long-term implications for dealing with water-related hazards, controlling glacial lake outburst floods, and securing water resources in the HKHT regions, which contain the headwater sources for some of the largest rivers in Asia that sustain 1.3 billion people.
Atmospheric Transmittance Model Validation for CSP Tower Plants
Authors: Hanrieder Natalie , Ghennioui Abdellatif , Alami Merrouni Ahmed , Wilbert Stefan , Wiesinger Florian , Sengupta Manajit , Zarzalejo Luis , Schade Alexander
Published: May 2019

In yield analysis and plant design of concentrated solar power (CSP) tower plants, increased uncertainties are caused by the mostly unknown solar attenuation between the concentrating heliostat field and the receiver on top of the tower. This attenuation is caused mainly by aerosol particles and water vapor. Various on-site measurement methods of atmospheric extinction in solar tower plants have been developed during recent years, but during resource assessment for distinct tower plant projects in-situ measurement data sets are typically not available. To overcome this lack of information, a transmittance model (TM) has been previously developed and enhanced by the authors to derive the atmospheric transmittance between a heliostat and receiver on the basis of common direct normal irradiance (DNI), temperature, relative humidity and barometric pressure measurements. Previously the model was only tested at one site. In this manuscript, the enhanced TM is validated for three sites (CIEMAT’s Plataforma Solar de Almería (PSA), Spain, Missour, Morocco (MIS) and Zagora, Morocco (ZAG)). As the strongest assumption in the TM is the vertical aerosol particle profile, three different approaches to describe the vertical profile are tested in the TM. One approach assumes a homogeneous aerosol profile up to 1 kilometer above ground, the second approach is based on LIVAS profiles obtained from Lidar measurements and the third approach uses boundary layer height (BLH) data of the European Centre for Medium-Range Weather Forecasts (ECMWF). The derived broadband transmittance for a slant range of 1 km ( T 1 k m ) time series is compared with a reference data set of on-site absorption- and broadband corrected T 1 k m derived from meteorological optical range (MOR) measurements for the temporal period between January 2015 and November 2017. The absolute mean bias error (MBE) for the TM’s T 1 k m using the three different aerosol profiles lies below 5% except for ZAG and one profile assumption. The MBE is close to 0 for PSA and MIS assuming a homogeneous extinction coefficient up to 1 km above ground. The root mean square error (RMSE) is around 5–6% for PSA and ZAG and around 7–8% for MIS. The TM performs better during summer months, during which more data points have been evaluated. This validation proves the applicability of the transmittance model for resource assessment at various sites. It enables the identification of a clear site with high T 1 k m with a high accuracy and provides an estimation of the T 1 k m for hazy sites. Thus it facilitates the decision if on-site extinction measurements are necessary. The model can be used to improve the accuracy of yield analysis of tower plants and allows the site adapted design.
Spatially Heterogeneous Land Surface Deformation Data Fusion Method Based on an Enhanced Spatio-Temporal Random Effect Model
Authors: Shi Qiang , Dai Wujiao , Santerre Rock , Li Zhiwei , Liu Ning
Published: May 2019

The spatio-temporal random effect (STRE) model, a type of spatio-temporal Kalman filter model, can be used for the fusion of the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) data to generate high spatio-temporal resolution deformation series, assuming that the land deformation is spatially homogeneous in the monitoring area. However, when there are multiple deformation sources in the monitoring area, complex spatial heterogeneity will appear. To improve the fusion accuracy, we propose an enhanced STRE fusion method (eSTRE) by taking spatial heterogeneity into consideration. This new method integrates the spatial heterogeneity constraints in the STRE model by constructing extra-constrained spatial bases for the heterogeneous area. The effectiveness of this method is verified by using simulated data and real land surface deformation data. The results show that eSTRE can reduce the root mean square (RMS) of InSAR interpolation results by 14% and 23% on average for a simulation experiment and Los Angeles experiment, respectively, indicating that the new proposed method (eSTRE) is substantially better than the previous STRE fusion model.
A Mixed Model Approach to Vegetation Condition Prediction Using Artificial Neural Networks (ANN): Case of Kenya’s Operational Drought Monitoring
Authors: Adede Chrisgone , Oboko Robert , Wagacha Peter Waiganjo , Atzberger Clement
Published: May 2019

Droughts, with their increasing frequency of occurrence, especially in the Greater Horn of Africa (GHA), continue to negatively affect lives and livelihoods. For example, the 2011 drought in East Africa caused massive losses, documented to have cost the Kenyan economy over 12 billion US dollars. Consequently, the demand is ever-increasing for ex-ante drought early warning systems with the ability to offer drought forecasts with sufficient lead times The study uses 10 precipitation and vegetation condition indices that are lagged over 1, 2 and 3-month time-steps to predict future values of vegetation condition index aggregated over a 3-month time period (VCI3M) that is a proxy variable for drought monitoring. The study used data covering the period 2001–2015 at a monthly frequency for four arid northern Kenya counties for model training, with data for 2016–2017 used as out-of-sample data for model testing. The study adopted a model space search approach to obtain the most predictive artificial neural network (ANN) model as opposed to the traditional greedy search approach that is based on optimal variable selection at each model building step. The initial large model-space was reduced using the general additive model (GAM) technique together with a set of assumptions. Even though we built a total of 102 GAM models, only 20 had R2 ≥ 0.7, and together with the model with lag of the predicted variable, were subjected to the ANN modelling process. The ANN process itself uses the brute-force approach that automatically partitions the training data into 10 sub-samples, builds the ANN models in these samples and evaluates their performance using multiple metrics. The results show the superiority of 1-month lag of the variables as compared to longer time lags of 2 and 3 months. The best ANN model recorded an R2 of 0.78 between actual and predicted vegetation conditions 1-month ahead using the out-of-sample data. Investigated as a classifier distinguishing five vegetation deficit classes, the best ANN model had a modest accuracy of 67% and a multi-class area under the receiver operating characteristic curve (AUROC) of 89.99%.
Discrimination of Canopy Structural Types in the Sierra Nevada Mountains in Central California
Authors: Huesca Margarita , Roth Keely L. , García Mariano , Ustin Susan L.
Published: May 2019

Accurate information about ecosystem structure and biogeochemical properties is essential to providing better estimates ecosystem functioning. Airborne LiDAR (light detection and ranging) is the most accurate way to retrieve canopy structure. However, accurately obtaining both biogeochemical traits and structure parameters requires concurrent measurements from imaging spectrometers and LiDARs. Our main objective was to evaluate the use of imaging spectroscopy (IS) to provide vegetation structural information. We developed models to estimate structural variables (i.e., biomass, height, vegetation heterogeneity and clumping) using IS data with a random forests model from three forest ecosystems (i.e., an oak-pine low elevation savanna, a mixed conifer/broadleaf mid-elevation forest, and a high-elevation montane conifer forest) in the Sierra Nevada Mountains, California. We developed and tested general models to estimate the four structural variables with accuracies greater than 75%, for the structurally and ecologically different forest sites, demonstrating their applicability to a diverse range of forest ecosystems. The model R2 for each structural variable was least in the conifer/broadleaf forest than either the low elevation savanna or the montane conifer forest. We then used the structural variables we derived to discriminate site-specific, ecologically meaningful descriptions of canopy structural types (CST). Our CST results demonstrate how IS data can be used to create comprehensive and easily interpretable maps of forest structural types that capture their major structural features and trends across different vegetation types in the Sierra Nevada Mountains. The mixed conifer/broadleaf forest and montane conifer forest had the most complex structures, containing six and five CSTs respectively. The identification of CSTs within a site allowed us to better identify the main drivers of structural variability in each ecosystem. CSTs in open savanna were driven mainly by differences in vegetation cover; in the mid-elevation mixed forest, by the combination of biomass and canopy height; and in the montane conifer forest, by vegetation heterogeneity and clumping.
SST Anomalies in the Mozambique Channel Using Remote Sensing and Numerical Modeling Data
Authors: Han Guoqing , Dong Changming , Li Junde , Yang Jingsong , Wang Qingyue , Liu Yu , Sommeria Joel
Published: May 2019

Based on both satellite remote sensing sea surface temperature (SST) data and numerical model results, SST warming differences in the Mozambique Channel (MC) west of the Madagascar Island (MI) were found with respect to the SST east of the MI along the same latitude. The mean SST west of the MI is up to about 3.0 °C warmer than that east of the MI. The SST differences exist all year round and the maximum value appears in October. The area of the highest SST is located in the northern part of the MC. Potential factors causing the SST anomalies could be sea surface wind, heat flux and oceanic flow advection. The presence of the MI results in weakening wind in the MC and in turn causes weakening of the mixing in the upper oceans, thus the surface mixed layer depth becomes shallower. There is more precipitation on the east of the MI than that inside the MC because of the orographic effects. Different precipitation patterns and types of clouds result in different solar radiant heat fluxes across both sides of the MI. Warm water advected from the equatorial area also contribute to the SST warm anomalies.
Contrast and Homogeneity Feature Analysis for Classifying Tremor Levels in Parkinson’s Disease Patients
Authors: Vivar Guillermina , Almanza-Ojeda Dora-Luz , Cheng Irene , Gomez Juan Carlos , Andrade-Lucio J. A. , Ibarra-Manzano Mario-Alberto
Published: May 2019

Early detection of different levels of tremors helps to obtain a more accurate diagnosis of Parkinson’s disease and to increase the therapy options for a better quality of life for patients. This work proposes a non-invasive strategy to measure the severity of tremors with the aim of diagnosing one of the first three levels of Parkinson’s disease by the Unified Parkinson’s Disease Rating Scale (UPDRS). A tremor being an involuntary motion that mainly appears in the hands; the dataset is acquired using a leap motion controller that measures 3D coordinates of each finger and the palmar region. Texture features are computed using sum and difference of histograms (SDH) to characterize the dataset, varying the window size; however, only the most fundamental elements are used in the classification stage. A machine learning classifier provides the final classification results of the tremor level. The effectiveness of our approach is obtained by a set of performance metrics, which are also used to show a comparison between different proposed designs.
Low-Cost Image Compressive Sensing with Multiple Measurement Rates for Object Detection
Authors: Liao Longlong , Li Kenli , Yang Canqun , Liu Jie
Published: May 2019

When measurement rates grow, most Compressive Sensing (CS) methods suffer from an increase in overheads of transmission and storage of CS measurements, while reconstruction quality degrades appreciably when measurement rates reduce. To solve these problems in real scenarios such as large-scale distributed surveillance systems, we propose a low-cost image CS approach called MRCS for object detection. It predicts key objects using the proposed MYOLO3 detector, and then samples the regions of the key objects as well as other regions using multiple measurement rates to reduce the size of sampled CS measurements. It also stores and transmits half-precision CS measurements to further reduce the required transmission bandwidth and storage space. Comprehensive evaluations demonstrate that MYOLO3 is a smaller and improved object detector for resource-limited hardware devices such as surveillance cameras and aerial drones. They also suggest that MRCS significantly reduces the required transmission bandwidth and storage space by declining the size of CS measurements, e.g., mean Compression Ratios (mCR) achieves 1.43–22.92 on the VOC-pbc dataset. Notably, MRCS further reduces the size of CS measurements by half-precision representations. Subsequently, the required transmission bandwidth and storage space are reduced by one half as compared to the counterparts represented with single-precision floats. Moreover, it also substantially enhances the usability of object detection on reconstructed images with half-precision CS measurements and multiple measurement rates as compared to its counterpart, using a single low measurement rate.
Metal Forming Tool Monitoring Based on a 3D Measuring Endoscope Using CAD Assisted Registration
Authors: Hinz Lennart , Kästner Markus , Reithmeier Eduard
Published: May 2019

In order to provide timely, reliable, and comprehensive data for the maintenance of highly stressed geometries in sheet-bulk metal forming tools, this article features a possible setup by combining a 3D measuring endoscope with a two-stage kinematic. The measurement principle is based on the projection of structured light, allowing time-effective measurements of larger areas. To obtain data of proper quality, several hundred measurements are performed which then have to be registered and finally merged into one single point cloud. Factors such as heavy, unwieldy specimens affecting precise alignment. The rotational axes are therefore possibly misaligned and the kinematics and the hand-eye transformation remain uncalibrated. By the use of computer-aided design (CAD) data, registration can be improved, allowing a detailed examination of local features like gear geometries while reducing the sensitivity to detect shape deviations.
Polarization-Modulated, Goos–Hanchen Shift Sensing for Common Mode Drift Suppression
Authors: Wan Yuhang , Cheng Mengxuan , Zheng Zheng , Liu Kai
Published: May 2019

A polarization-modulation-based Goos–Hanchen (GH) sensing scheme leveraging the polarization-dependence of the Bloch surface wave enhanced GH shift is proposed and experimentally demonstrated. Based on a simple setup utilizing a liquid crystal modulator to switch the polarization state of the input beam periodically, the alternating positions of the reflected beam for both polarizations are monitored by a lock-in amplifier to handily retrieve the GH shift signal. The conventional direct measurement of the beam position for the target state of polarization is vulnerable to instabilities in the optomechanical setup and alignment. Our proposed scheme provides a sensitive yet robust GH shift-sensing setup where the common mode drift and noise could be suppressed to ensure better system stability.
Window-Based Constant Beamwidth Beamformer
Authors: Long Tao , Cohen Israel , Berdugo Baruch , Yang Yan , Chen Jingdong
Published: May 2019

Beamformers have been widely used to enhance signals from a desired direction and suppress noise and interfering signals from other directions. Constant beamwidth beamformers enable a fixed beamwidth over a wide range of frequencies. Most of the existing approaches to design constant beamwidth beamformers are based on optimization algorithms with high computational complexity and are often sensitive to microphone mismatches. Other existing methods are based on adjusting the number of sensors according to the frequency, which simplify the design, but cannot control the sidelobe level. Here, we propose a window-based technique to attain the beamwidth constancy, in which different shapes of standard window functions are applied for different frequency bins as the real weighting coefficients of microphones. Thereby, not only do we keep the beamwidth constant, but we also control the sidelobe level. Simulation results show the advantages of our method compared with existing methods, including lower sidelobe level, higher directivity factor, and higher white noise gain.
Preparation of Selective and Reproducible SERS Sensors of Hg2+ Ions via a Sunlight-Induced Thiol–Yne Reaction on Gold Gratings
Authors: Guselnikova Olga , Svorcik Vaclav , Lyutakov Oleksiy , Chehimi Mohamed M. , Postnikov Pavel S.
Published: May 2019

In this contribution, we propose a novel functional surface-enhanced Raman spectroscopy (SERS) platform for the detection of one of the most hazardous heavy metal ions, Hg2+. The design of the proposed sensor is based on the combination of surface plasmon-polariton (SPP) supporting gold grating with the high homogeneity of the response and enhancement and mercaptosuccinic acid (MSA) based specific recognition layer. For the first time, diazonium grafted 4-ethynylphenyl groups have undergone the sunlight-induced thiol–yne reaction with MSA in the presence of Eosine Y. The developed SERS platform provides an extremely sensitive, selective, and convenient analytical procedure to detect mercury ions with limit of detection (LOD) as low as 10−10 M (0.027 µg/L) with excellent selectivity over other metals. The developed SERS sensor is compatible with a portable SERS spectrophotometer and does not require the expensive equipment for statistical methods of analysis.
Relaxation-Related Piezoelectric and Dielectric Behavior of Bi(Mg,Ti)O3–PbTiO3 Ceramic
Authors: Park Min Young , Ji Jae-Hoon , Koh Jung-Hyuk
Published: May 2019

Piezoelectric and dielectric materials have attracted much attention for their functional device applications. Despite its excellent piezoelectric properties, the content of lead in piezoelectric materials should be restricted to prevent future environmental problems. Therefore, reduced lead content in piezoelectric materials with similar piezoelectric properties is favorable. In our research, piezoelectric materials with decreased lead content will be studied and discussed. Even though the lead content is decreased in Bi(Mg0.5Ti0.5)O3–PbTiO3 ceramics, they show piezoelectric properties similar to that of lead zirconate titanate (PZT)-based materials. We believe this high piezoelectric behavior is related to the relaxation behavior of Bi(Mg0.5Ti0.5)O3–PbTiO3 (BMT–PT) ceramics. In this study, 0.62Bi(Mg0.5Ti0.5)O3–0.38PbTiO3 ceramics were prepared by the conventional sintering process. These piezoelectric ceramics were sintered at varying temperatures of 975–1100 °C. Crystallinity and structural properties were analyzed and discussed. X-ray diffraction pattern analysis demonstrated that the optimal sintering temperature was around 1075 °C. A very high Curie temperature of 447 °C was recorded for 0.62BMT–0.38PT ceramics sintered at 1075 °C. For the first time, we found that the origin of the high Curie temperature, d33, and the dielectric constant is the relaxation behavior of different dipoles in 0.62BMT–0.38PT ceramics.
Fault Identification for a Closed-Loop Control System Based on an Improved Deep Neural Network
Authors: Sun Bowen , Wang Jiongqi , He Zhangming , Zhou Haiyin , Gu Fengshou
Published: May 2019

Fault identification for closed-loop control systems is a future trend in the field of fault diagnosis. Due to the inherent feedback adjustment mechanism, a closed-loop control system is generally very robust to external disturbances and internal noises. Closed-loop control systems often encourage faults to propagate inside the systems, which may lead to the consequence that faults amplitude becomes smaller and fault characteristics difference becomes more inapparent. Hence, it has been challenging to achieve fault identification for such systems. Traditional fault identification methods are not particularly designed for closed-loop control systems and thus cannot be applied directly. In this work, a new fault identification method is proposed, which is based on the deep neural network for closed-loop control systems. Firstly, the fault propagation mechanism in closed-loop control systems is theoretically derived, and the influence of fault propagation on system variables is analyzed. Then deep neural network is applied to find fault characteristics difference between different data modes, and a sliding window is used to amplify the fault-to-noise ratio and characteristics difference, with an aim to increase the identification performance. To verify this method, the simulations that are based on a numerical simulation model, the Tennessee industrial system and the satellite attitude control system are conducted. The results show that the proposed method is more feasible and more effective in fault identification for closed-loop control systems compared with traditional data-driven identification methods, including distance-based and angle-based identification methods.
Evaluation of a Commercial Ballistocardiography Sensor for Sleep Apnea Screening and Sleep Monitoring
Authors: Huysmans Dorien , Borzée Pascal , Testelmans Dries , Buyse Bertien , Willemen Tim , Van Huffel Sabine , Varon Carolina
Published: May 2019

There exists a technological momentum towards the development of unobtrusive, simple, and reliable systems for long-term sleep monitoring. An off-the-shelf commercial pressure sensor meeting these requirements is the Emfit QS. First, the potential for sleep apnea screening was investigated by revealing clusters of contaminated and clean segments. A relationship between the irregularity of the data and the sleep apnea severity class was observed, which was valuable for screening (sensitivity 0.72, specificity 0.70), although the linear relation was limited ( R 2 of 0.16). Secondly, the study explored the suitability of this commercial sensor to be merged with gold standard polysomnography data for future sleep monitoring. As polysomnography (PSG) and Emfit signals originate from different types of sensor modalities, they cannot be regarded as strictly coupled. Therefore, an automated synchronization procedure based on artefact patterns was developed. Additionally, the optimal position of the Emfit for capturing respiratory and cardiac information similar to the PSG was identified, resulting in a position as close as possible to the thorax. The proposed approach demonstrated the potential for unobtrusive screening of sleep apnea patients at home. Furthermore, the synchronization framework enabled supervised analysis of the commercial Emfit sensor for future sleep monitoring, which can be extended to other multi-modal systems that record movements during sleep.
A Novel Distributed State Estimation Algorithm with Consensus Strategy
Authors: Liu Jun , Liu Yu , Dong Kai , Ding Ziran , He You
Published: May 2019

Owing to its high-fault tolerance and scalability, the consensus-based paradigm has attracted immense popularity for distributed state estimation. If a target is neither observed by a certain node nor by its neighbors, this node is naive about the target. Some existing algorithms have considered the presence of naive nodes, but it takes sufficient consensus iterations for these algorithms to achieve a satisfactory performance. In practical applications, because of constrained energy and communication resources, only a limited number of iterations are allowed and thus the performance of these algorithms will be deteriorated. By fusing the measurements as well as the prior estimates of each node and its neighbors, a local optimal estimate is obtained based on the proposed distributed local maximum a posterior (MAP) estimator. With some approximations of the cross-covariance matrices and a consensus protocol incorporated into the estimation framework, a novel distributed hybrid information weighted consensus filter (DHIWCF) is proposed. Then, theoretical analysis on the guaranteed stability of the proposed DHIWCF is performed. Finally, the effectiveness and superiority of the proposed DHIWCF is evaluated. Simulation results indicate that the proposed DHIWCF can achieve an acceptable estimation performance even with a single consensus iteration.
Fully Noncontact Hybrid NDT for 3D Defect Reconstruction Using SAFT Algorithm and 2D Apodization Window
Authors: Selim Hossam , Trull José , Delgado Prieto Miguel , Picó Rubén , Romeral Luis , Cojocaru Crina
Published: May 2019

Nondestructive testing of metallic objects that may contain embedded defects of different sizes is an important application in many industrial branches for quality control. Most of these techniques allow defect detection and its approximate localization, but few methods give enough information for its 3D reconstruction. Here we present a hybrid laser–transducer system that combines remote, laser-generated ultrasound excitation and noncontact ultrasonic transducer detection. This fully noncontact method allows access to scan areas on different object’s faces and defect details from different angles/perspectives. This hybrid system can analyze the object’s volume data and allows a 3D reconstruction image of the embedded defects. As a novelty for signal processing improvement, we use a 2D apodization window filtering technique, applied along with the synthetic aperture focusing algorithm, to remove the undesired effects due to side lobes and wide-angle reflections of propagating ultrasound waves, thus enhancing the resulting 3D image of the defect. Finally, we provide both qualitative and quantitative volumetric results that yield valuable information about defect location and size.
A Robust Noise Mitigation Method for the Mobile RFID Location in Built Environment
Authors: Jing Changfeng , Sun Tiancheng , Chen Qiang , Du Mingyi , Wang Mingshu , Wang Shouqing , Wang Jian
Published: May 2019

The exact location of objects, such as infrastructure, is crucial to the systematic understanding of the built environment. The emergence and development of the Internet of Things (IoT) have attracted growing attention to the low-cost location scheme, which can respond to a dramatic increasing amount of public infrastructure in smart cities. Various Radio Frequency IDentification (RFID)-based locating systems and noise mitigation methods have been developed. However, most of them are impractical for built environments in large areas due to their high cost, computational complexity, and low noise detection capability. In this paper, we proposed a novel noise mitigation solution integrating the low-cost localization scheme with one mobile RFID reader. We designed a filter algorithm to remove the influence of abnormal data. Inspired the sampling concept, a more carefully parameters calibration was carried out for noise data sampling to improve the accuracy and reduce the computational complexity. To achieve robust noise detection results, we employed the powerful noise detection capability of the random sample consensus (RANSAC) algorithm. Our experiments demonstrate the effectiveness and advantages of the proposed method for the localization and noise mitigation in a large area. The proposed scheme has potential applications for location-based services in smart cities.
Improvements in Performance Analysis of Photovoltaic Systems: Array Power Monitoring in Pulse Width Modulation Charge Controllers
Authors: Jiménez-Castillo Gabino , Muñoz-Rodríguez Francisco José , Rus-Casas Catalina , Gómez-Vidal Pedro
Published: May 2019

Various challenges should be considered when measuring photovoltaic array power and energy in pulse width modulation (PWM) charge controllers. These controllers are frequently used not only in stand-alone photovoltaic (SAPV) systems, but may also be found in photovoltaic (PV) self-consumption systems with battery storage connected to the electricity grid. An acceptable solution may be reached using expensive data acquisition systems (DASs), although this could be generally disproportionate to the relatively low cost of SAPV systems. Therefore, the aim of this paper is to develop new and effective monitoring techniques which will provide the PV array direct current (DC), output power (PA,dc), and PV array DC output energy (EA), thus avoiding the use of sophisticated DASs and providing high accuracy for the calculated parameters. Only transducers and electronic circuits that provide the average and true rms values of the PWM signals are needed. The estimation of these parameters through the aforementioned techniques showed high accuracy for both series and shunt PWM battery charge controllers. Normalized root mean square error (NRMSE) was lower than 2.4%, normalized mean bias error (NMBE) was between −1.5% and 1.1%, and mean absolute percentage error (MAPE) was within 1.6%.
Green Practices among Fashion Manufacturers: Relationship with Cultural Innovativeness and Perceived Benefits
Authors: Choi Dooyoung , Han Tae-Im
Published: May 2019

The purpose of this study was to examine green practices implemented among fashion manufacturers and identify factors that drive the adoption of those practices, specifically focusing on a company’s cultural innovativeness and the perceived benefits of green innovations. An online survey was created containing both open-ended and multiple-choice questions using Likert scales. Data were gathered from 29 fashion manufacturers that were identified by the Google search engine and then approached. Qualitative data were analyzed to obtain insights into fashion manufacturers’ green practices and a cluster analysis was conducted to categorize companies into distinct groups based on their level of green product innovations and green process innovations. Our findings suggest that the adoption of green practices was related to a company’s internal characteristics such as cultural innovativeness and social responsibility perceptions. Perceived benefits from green practices were not a sufficient motivator for adopting those practices. It is important to examine manufacturers’ perceptions of becoming more involved in green practices because they have great potential to make a positive impact on the mainstream industry and appeal to a wider market audience.
Identifying Opinion Leaders on Twitter during Sporting Events: Lessons from a Case Study
Authors: Lamirán-Palomares José M. , Baviera Tomás , Baviera-Puig Amparo
Published: May 2019

Social media platforms have had a significant impact on the public image of sports in recent years. Through the relational dynamics of the communication on these networks, many users have emerged whose opinions can exert a great deal of influence on public conversation online. This research aims to identify the influential Twitter users during the 2016 UCI Track Cycling World Championships using different variables which, in turn, represent different dimensions of influence (popularity, activity and authority). Mathematical variables of the social network analysis and variables provided by Twitter and Google are compared. First, we calculated the Spearman’s rank correlation coefficient among all users (n = 20,175) in pairwise comparisons. Next, we performed a qualitative analysis of the top 25 influential users ranked by each variable. As a result, no single variable assessed is sufficient to identify the different kinds of influential Twitter users. The reason that some variables vary so greatly is that the components of influence are very different. Influence is a contextualised phenomenon. Having a certain type of account is not enough to make a user an influencer if they do not engage (actively or passively) in the conversation. Choosing the influencers will depend on the objectives pursued.
Effects of Collaborative Economy: A Reflection
Authors: Menor-Campos Antonio , García-Moreno María de los Baños , López-Guzmán Tomás , Hidalgo-Fernández Amalia
Published: May 2019

Collaborative economy, a practice based on access to goods, is making its way into society, with disruptive effects for traditional economy, which is based on property. Although it is a recent phenomenon, its rapid growth and user acceptance make it possible to predict that in the near future, collaborative economy will be an important pillar of economic growth and employment. The results of this research indicate the existence of other effects of the collaborative economy, not always desirable, among which are changes in mentality or the appearance of new business models.
Mutual Benefit: How Vocational Training Programs Utilize Employer Engagement and Refugee Strengths to Facilitate Integration
Authors: Lumley-Sapanski Audrey , Callahan Nancy Joyce
Published: May 2019

Successful integration of newly arriving refugees requires the engagement of the receiving community and active facilitation of integration through provision of employment, access to housing, and protection of basic rights. Understanding how local entities effectively facilitate integration is important for policymakers and scholars interested in identifying best practices and replicating outcomes. This study examines the integration outcomes of refugees who participated in a vocational hospitality training program in Chicago, Illinois between 2008 and 2012. In particular, we explore the integration experiences—using employment, housing, and homeownership—of Bhutanese origin refugees who represented the largest country of origin group in the hospitality course. We find that the Bhutanese refugees who participated in the course had high rates of homeownership, stable employment, higher wages and experienced socioeconomic upward mobility—positive indicators of integration. In our analysis, we identify three reasons the program is successful in facilitating integration: a practice of selective enrollment, active employer engagement, and informed industry selection. Importantly, our findings suggest a positive benefit for employers in addition to refugee employees.
Out of Sight: Social Control and the Regulation of Public Space in Manchester
Authors: Moss Christopher J. , Moss Kate
Published: May 2019

This paper considers the history and context of the control of public spaces, how this is regulated currently and how it relates to the politics of homelessness and community governance with a specific focus on the regulation of public space in the contemporary city of Manchester.
Recommendations for Measurement and Management of an Elite Athlete
Authors: Sands William , Cardinale Marco , McNeal Jeni , Murray Steven , Sole Christopher , Reed Jacob , Apostolopoulos Nikos , Stone Michael
Published: May 2019

Athletes who merit the title ‘elite’ are rare and differ both quantitatively and qualitatively from athletes of lower qualifications. Serving and studying elite athletes may demand non-traditional approaches. Research involving elite athletes suffers because of the typical nomothetic requirements for large sample sizes and other statistical assumptions that do not apply to this population. Ideographic research uses single-athlete study designs, trend analyses, and statistical process control. Single-athlete designs seek to measure differences in repeated measurements under prescribed conditions, and trend analyses may permit systematic monitoring and prediction of future outcomes. Statistical process control uses control charting and other methods from management systems to assess and modify training processes in near real-time. These methods bring assessment and process control into the real world of elite athletics.
Short-Time β-Alanine Supplementation on the Acute Strength Performance after High-Intensity Intermittent Exercise in Recreationally Trained Men
Authors: Freitas Marcelo Conrado , Cholewa Jason , Panissa Valéria , Quizzini Giovanni , de Oliveira João Vitor , Figueiredo Caique , Gobbo Luis Alberto , Caperuto Erico , Zanchi Nelo Eidy , Lira Fabio , Rossi Fabrício Eduardo
Published: May 2019

(1) Background: We investigated the effects of 28 days of beta-alanine (β-alanine) supplementation on the acute interference effect of high-intensity intermittent exercise (HIIE) on lower-body resistance exercise performance, body composition, and strength when combined with a resistance training program. (2) Methods: Twenty-two males were randomized into: β-alanine supplementation (6.4 g/day) or placebo (6.4 g/day maltodextrin) during 28 days. Total body water, intracellular and extracellular water, fat-free mass (FFM), and fat mass were assessed using bioelectrical impedance. Participants performed 5000-m HIIE (1:1 effort and rest ratio) followed by resistance exercise (four sets of 80% at 45° leg press until muscular failure) at baseline and after 28 days. The resistance training program consisted of three sets of 10 to 12 RM with 90 s of rest, four days per week. (3) Results: For the post-HIIE leg press volume, higher values were observed post-training than pre-training, but no group x time interaction was observed. There was a non-significant trend for an interaction in the FFM change (β-alanine = 2.8% versus placebo = 1.0%, p = 0.072). (4) Conclusion: Twenty-eight days of β-alanine supplementation did not prevent acute strength loss during resistance exercise after high-intensity interval exercise, nor increase strength or hypertrophic adaptations associated with resistance training.
Heart Rate Responses and Exercise Intensity During A Prolonged 4-Hour Individual Cycling Race among Japanese Recreational Cyclists
Authors: Nakagata Takashi , Murade Shinichiro , Katamoto Shizuo , Naito Hisashi
Published: May 2019

Heart rate (HR) during different endurance cycling races and events are investigated for professional cyclist, however, enduro races to compete for total laps and distance covered within a fixed time using a circuit course has not yet been investigated. This study examined the heart rate (HR) and exercise intensity during an enduro cycling race. Ten male Japanese amateur cyclists performed cycling individually for at least 2 consecutive hours. HR was measured using an HR monitor during the race, and we estimated the energy expenditure (EE) during the race using the HR–VO2 relationship in advance. Exercise intensities were defined as percentages of HRmax based on ACSM exercise guideline as follows: moderate intensity, 64–76% HRmax; vigorous intensity, 77–95% HRmax. The HR during the race was 158.9 ± 10.6 bpm (86.4 ± 2.2% HRmax), and exercise intensity is categorized as vigorous intensity. The EE during the race using HR–VO2 relationship were 12.9 ± 1.2 kcal/kg/hr, which would require a large energy expenditure (EE) during the race. However, energy cost was 0.36 ± 0.04 kcal/kg/km regardless of total distance. The findings indicate that enduro cycling racing is categorized as vigorous intensity (>77% HRmax) for healthy male recreational cyclists though, cycling is an efficient form of transportation.
Analysis of the Influence of Dynamic Load on the Work Parameters of a Powered Roof Support’s Hydraulic Leg
Authors: Szurgacz Dawid , Brodny Jarosław
Published: May 2019

One of the basic tasks of powered roof support is to protect the longwall excavation against deformation of the rock mass during the underground exploitation of hard coal. The behavior of the rock mass during mining is difficult to predict. Therefore, the loads acting on the support are diverse in terms of nature, direction and force. The dynamic load resulting from rock bursts, relaxation and tremors may lead to particularly dangerous consequences involving the functionality of the workings and the safety of the crew. The powered roof support will function properly only if the elements dynamically loaded are under control at the moment of impact. The article presents the results of tests of the basic powered roof support’s element − a hydraulic leg impacted by dynamic load. The source of the load was a free falling impact mass dropped from a certain height. The tests covered the actual hydraulic leg with all hydraulic equipment used in the powered roof support. During the tests, the original measurement-recording system developed by the authors was used, in which, among others, a high-speed dynamic camera was used to record movements of the leg’s elements. The original research methodology developed together with the measurement system enabled the registration of many parameters of the leg’s work under dynamic load. In particular, this applies to time series of pressure in the leg and the value of its withdrawal depending on the energy of the impact. The individual phases of the leg’s work were also registered, including the opening and closing of the safety valve protecting the leg against overloading. The obtained results broaden knowledge in the field of hydraulic legs used in the mining support under dynamic load. At the same time, they are a valuable source of information for mine maintenance services and should be applied to the design process, selection and operation of a powered roof support in dynamic conditions. The subject of the article fits in with the philosophy of sustainable development, especially in the field of full use of options of the support and ensuring safe and environmentally friendly mining processes.
Carbon Emission Reduction of Apparel Material Distribution Based on Multi-Objective Genetic Algorithm (NSGA-II)
Authors: Zhang Xujing , Wang Lichuan , Chen Yan
Published: May 2019

Low-carbon production has become one of the top management objectives for every industry. In garment manufacturing, the material distribution process always generates high carbon emissions. In order to reduce carbon emissions and the number of operators to meet enterprises’ requirements to control the cost of production and protect the environment, the paths of material distribution were analyzed to find the optimal solution. In this paper, the model of material distribution to obtain minimum carbon emissions and vehicles (operators) was established to optimize the multi-target management in three different production lines (multi-line, U-shape two-line, and U-shape three-line), while the workstations were organized in three ways: in the order of processes, in the type of machines, and in the components of garment. The NSGA-II algorithm (non-dominated sorting genetic algorithm-II) was applied to obtain the results of this model. The feasibility of the model and algorithm was verified by the practice of men’s shirts manufacture. It could be found that material distribution of multi-line layout produced the least carbon emissions when the machines were arranged in the group of type.
Tourism Impacts Continuity of World Heritage List Inscription and Sustainable Management of Hahoe Village, Korea: A Case Study of Changes in Tourist Perceptions
Authors: Kim Soonki
Published: May 2019

This study examines the World Heritage List inscription’s tourism impact continuity through Hahoe Village’s tourists’ perception changes between 2014 and 2018, and it tries to verify the direction of future management and development plans for a sustainable community. Of all the perceptions verified in this study, two noteworthy issues, such as (1) World Heritage as a tourists’ brand and (2) future management of Hahoe Village as a World Heritage Site for maintaining brand equity, are discussed. In conclusion, the title “World Heritage” has excelled in its role as a tourism brand. Based on this role, the immediate outburst of tourism after the World Heritage List inscription affected Hahoe Village. However, even though the title World Heritage is a powerful brand that has great effect on the tourism industry, it still needs appropriate management to maintain brand equity. In the case of World Heritage, the target object of management is located at a trade-off point of interests between preserving heritage value and improving service convenience for tourists.
The Effect of an Energy Refurbishment Scheme on Adequate Warmth in Low-income Dwellings
Authors: Park Sowoo , Kim Joowook , Song Doosam
Published: May 2019

Many fuel poverty support programs have been implemented in the world. Energy-efficient retrofitting in low-income households is a main aspect of support programs in the context of energy saving, reduction of greenhouse gas emissions, and improvement of the thermal comfort and health of residents. This study analyzed the effects of an energy efficiency program for fuel poverty in Korea on the thermal comfort of residents. A total of 330 households were investigated wherein energy retrofits had been conducted. Indoor temperatures in the main bedroom and in the living room were recorded twice. The results showed that the average indoor air temperature in the surveyed households was 15.1 ± 3.7 °C, indicating that 95.2% of main bedrooms and 80.0% of living rooms did not meet the recommendations of the World Health Organization regarding temperature. These results indicated that the surveyed households did not use energy for heating their rooms, and an energy-saving effect due to the retrofits was difficult to expect. Accordingly, retrofit building or energy policies addressing fuel poverty are shown to be ineffective in the context of energy saving and thermal comfort in Korea. This article highlights issues that need to be analyzed to evaluate how effective the welfare program is. The results of this study alert policymaker to the need to improve the welfare policy; the methods proposed in this article will help them in their decisions.