bluuebunny/crossref_metadata_2025 huggingface dataset:
Accuracy Improvements to Pixel-Based and Object-Based LULC Classification with Auxiliary Datasets from Google Earth Engine
Authors: Qu Le’an , Chen Zhenjie , Li Manchun , Zhi Junjun , Wang Huiming
Published: January 2021

The monitoring and assessment of land use/land cover (LULC) change over large areas are significantly important in numerous research areas, such as natural resource protection, sustainable development, and climate change. However, accurately extracting LULC only using the spectral features of satellite images is difficult owing to landscape heterogeneities over large areas. To improve the accuracy of LULC classification, numerous studies have introduced other auxiliary features to the classification model. The Google Earth Engine (GEE) not only provides powerful computing capabilities, but also provides a large amount of remote sensing data and various auxiliary datasets. However, the different effects of various auxiliary datasets in the GEE on the improvement of the LULC classification accuracy need to be elucidated along with methods that can optimize combinations of auxiliary datasets for pixel- and object-based classification. Herein, we comprehensively analyze the performance of different auxiliary features in improving the accuracy of pixel- and object-based LULC classification models with medium resolution. We select the Yangtze River Delta in China as the study area and Landsat-8 OLI data as the main dataset. Six types of features, including spectral features, remote sensing multi-indices, topographic features, soil features, distance to the water source, and phenological features, are derived from auxiliary open-source datasets in GEE. We then examine the effect of auxiliary datasets on the improvement of the accuracy of seven pixels-based and seven object-based random forest classification models. The results show that regardless of the types of auxiliary features, the overall accuracy of the classification can be improved. The results further show that the object-based classification achieves higher overall accuracy compared to that obtained by the pixel-based classification. The best overall accuracy from the pixel-based (object-based) classification model is 94.20% (96.01%). The topographic features play the most important role in improving the overall accuracy of classification in the pixel- and object-based models comprising all features. Although a higher accuracy is achieved when the object-based method is used with only spectral data, small objects on the ground cannot be monitored. However, combined with many types of auxiliary features, the object-based method can identify small objects while also achieving greater accuracy. Thus, when applying object-based classification models to mid-resolution remote sensing images, different types of auxiliary features are required. Our research results improve the accuracy of LULC classification in the Yangtze River Delta and further provide a benchmark for other regions with large landscape heterogeneity.
Machine Learning Based Algorithms for Global Dust Aerosol Detection from Satellite Images: Inter-Comparisons and Evaluation
Authors: Lee Jangho , Shi Yingxi Rona , Cai Changjie , Ciren Pubu , Wang Jianwu , Gangopadhyay Aryya , Zhang Zhibo
Published: January 2021

Identifying dust aerosols from passive satellite images is of great interest for many applications. In this study, we developed five different machine-learning (ML) based algorithms, including Logistic Regression, K Nearest Neighbor, Random Forest (RF), Feed Forward Neural Network (FFNN), and Convolutional Neural Network (CNN), to identify dust aerosols in the daytime satellite images from the Visible Infrared Imaging Radiometer Suite (VIIRS) under cloud-free conditions on a global scale. In order to train the ML algorithms, we collocated the state-of-the-art dust detection product from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) with the VIIRS observations along the CALIOP track. The 16 VIIRS M-band observations with the center wavelength ranging from deep blue to thermal infrared, together with solar-viewing geometries and pixel time and locations, are used as the predictor variables. Four different sets of training input data are constructed based on different combinations of VIIRS pixel and predictor variables. The validation and comparison results based on the collocated CALIOP data indicate that the FFNN method based on all available predictor variables is the best performing one among all methods. It has an averaged dust detection accuracy of about 81%, 89%, and 85% over land, ocean and whole globe, respectively, compared with collocated CALIOP. When applied to off-track VIIRS pixels, the FFNN method retrieves geographical distributions of dust that are in good agreement with on-track results as well as CALIOP statistics. For further evaluation, we compared our results based on the ML algorithms to NOAA’s Aerosol Detection Product (ADP), which is a product that classifies dust, smoke, and ash using physical-based methods. The comparison reveals both similarity and differences. Overall, this study demonstrates the great potential of ML methods for dust detection and proves that these methods can be trained on the CALIOP track and then applied to the whole granule of VIIRS granule.
Radiometric Calibration Evaluation for FY3D MERSI-II Thermal Infrared Channels at Lake Qinghai
Authors: Yan Lin , Hu Yonghong , Zhang Yong , Li Xiao-Ming , Dou Changyong , Li Jun , Si Yidan , Zhang Lijun
Published: January 2021

The absolute radiometric accuracy of the Fengyun 3D advanced Medium Resolution Spectral Imager (FY3D MERSI-II) thermal infrared bands was evaluated using the collected field measurements and atmospheric transfer simulations during 16–22 August 2019 at Lake Qinghai. A thermal infrared radiometer equipped on an unmanned surface vehicle was used to continuously collect the water temperature. Atmospheric conditions, surface emissivity, and aerosol optical depth measured near the field experiment site were adopted by the atmospheric transfer code to calculate the parameters about the influence of atmosphere on long-wave radiation, including the path radiance and the transmittance propagated from land surface to the satellite. The radiometric calibration accuracy analysis suggests that the differences between the simulated brightness temperature and satellite-based brightness temperature are −0.346 K and −0.722 K for channel 24 on 18 and 20 August, respectively, while it reaches −0.460 K and −1.036 K for channel 25 on 18 and 20 August, respectively. The vicarious calibration coefficients were found to be in good agreement with the internal onboard calibration coefficient in channel 24 and 25 of the FY3D MERSI-II according to the validation analysis in selected regions. The thermal infrared bands of the FY3D have a good in-orbit operational status according to our vicarious calibration experiments.
SDR Proof-of-Concept of Full-Duplex Jamming for Enhanced Physical Layer Security
Authors: Silva André , Gomes Marco , Vilela João P. , Harrison Willie K.
Published: January 2021

In order to secure wireless communications, we consider the usage of physical-layer security (PLS) mechanisms (i.e., coding for secrecy mechanisms) combined with self-interference generation. We present a prototype implementation of a scrambled coding for secrecy mechanisms with interference generation by the legitimate receiver and the cancellation of the effect of self-interference (SI). Regarding the SI cancellation, four state-of-the-art algorithms were considered: Least mean square (LMS), normalized least mean square (NLMS), recursive least squares (RLS) and QR decomposition recursive least squares (QRDRLS). The prototype implementation is performed in real-world software-defined radio (SDR) devices using GNU-Radio, showing that the LMS outperforms all other algorithms considered (NLMS, RLS and QRDRLS), being the best choice to use in this situation (SI cancellation). It was also shown that it is possible to secure communication using only noise generation by the legitimate receiver, though a variation of the packet loss rate (PLR) and the bit error rate (BER) gaps is observed when moving from the fairest to an advantageous or a disadvantageous scenario. Finally, when noise generation was combined with the adapted scrambled coding for secrecy with a hidden key scheme, a noteworthy security improvement was observed resulting in an increased BER for Eve with minor interference to Bob.
Preparation and Performance Analysis of Ag/ZnO Humidity Sensor
Authors: Li Peng , Yu Shuguo , Zhang Hongyan
Published: January 2021

Highly sensitive silver (Ag) modified zinc oxide (ZnO) humidity sensors were prepared by hydrothermal synthesis and the mechanism was studied. Experimental results show that Ag-modified ZnO can effectively enhance the performance of a humidity sensor. Large number of oxygen vacancies and many active sites are generated on the surface when molar ratio of Ag+ to Zn2+ is 1:100, which can accelerate the decomposition of water molecules on surface of the material, thereby improving the response of humidity sensor. Moreover, the linearity of ZnO humidity sensor is greatly improved by silver nanoparticles. Compared with previously reported ZnO-based humidity sensors, Ag/ZnO humidity sensors have a better response (151,700%), good linearity, low hysteresis (3%), and short response/recovery time (36/6 s). At the same time, it is found that the light had little effect on the performance of Ag/ZnO. Therefore, this kind of ZnO sensor with stable performance and excellent performance is expected to be used in the detection of relative humidity in conventional environments.
Beacons and Blockchains in the Mobile Gaming Ecosystem: A Feasibility Analysis
Authors: Pittaras Iakovos , Fotiou Nikos , Siris Vasilios A. , Polyzos George C.
Published: January 2021

We explore the adoption of the Internet of Things (IoT) and Distributed Ledger Technologies (DLTs), such as blockchains, in mobile gaming, focusing on ecosystem expansion and diversification, customer attraction and retention, exploitation of context sensitive and personalized advertisements, and improved monetization of in-game assets. We evaluate the cost and transaction delay of DLTs in a location-based mobile game ecosystem using two types of blockchains (permissioned and permissionless or public), based on defined Key Performance Indicators (KPIs). Our evaluation shows the advantages of using both types of blockchains as well as interledger technologies that combine them. Permissioned blockchains enable high performance, e.g., in terms of throughput and delay, and low cost, while permissionless (public) blockchains, through their transparency, immutability, and openness, support trust and facilitate interactions among unrelated parties. Finally, we show that the combination of IoT devices and DLTs in mobile gaming offers new business opportunities and enables innovative business models for both traditional mobile gaming companies and other participants in the ecosystem, e.g., game players, cafes, malls, and similar establishments, advertising companies, and independent programmers.
Fast Multi-Focus Fusion Based on Deep Learning for Early-Stage Embryo Image Enhancement
Authors: Raudonis Vidas , Paulauskaite-Taraseviciene Agne , Sutiene Kristina
Published: January 2021

Background: Cell detection and counting is of essential importance in evaluating the quality of early-stage embryo. Full automation of this process remains a challenging task due to different cell size, shape, the presence of incomplete cell boundaries, partially or fully overlapping cells. Moreover, the algorithm to be developed should process a large number of image data of different quality in a reasonable amount of time. Methods: Multi-focus image fusion approach based on deep learning U-Net architecture is proposed in the paper, which allows reducing the amount of data up to 7 times without losing spectral information required for embryo enhancement in the microscopic image. Results: The experiment includes the visual and quantitative analysis by estimating the image similarity metrics and processing times, which is compared to the results achieved by two wellknown techniques—Inverse Laplacian Pyramid Transform and Enhanced Correlation Coefficient Maximization. Conclusion: Comparatively, the image fusion time is substantially improved for different image resolutions, whilst ensuring the high quality of the fused image.
Unobtrusive Health Monitoring in Private Spaces: The Smart Home
Authors: Wang Ju , Spicher Nicolai , Warnecke Joana M. , Haghi Mostafa , Schwartze Jonas , Deserno Thomas M.
Published: January 2021

With the advances in sensor technology, big data, and artificial intelligence, unobtrusive in-home health monitoring has been a research focus for decades. Following up our research on smart vehicles, within the framework of unobtrusive health monitoring in private spaces, this work attempts to provide a guide to current sensor technology for unobtrusive in-home monitoring by a literature review of the state of the art and to answer, in particular, the questions: (1) What types of sensors can be used for unobtrusive in-home health data acquisition? (2) Where should the sensors be placed? (3) What data can be monitored in a smart home? (4) How can the obtained data support the monitoring functions? We conducted a retrospective literature review and summarized the state-of-the-art research on leveraging sensor technology for unobtrusive in-home health monitoring. For structured analysis, we developed a four-category terminology (location, unobtrusive sensor, data, and monitoring functions). We acquired 912 unique articles from four relevant databases (ACM Digital Lib, IEEE Xplore, PubMed, and Scopus) and screened them for relevance, resulting in n=55 papers analyzed in a structured manner using the terminology. The results delivered 25 types of sensors (motion sensor, contact sensor, pressure sensor, electrical current sensor, etc.) that can be deployed within rooms, static facilities, or electric appliances in an ambient way. While behavioral data (e.g., presence (n=38), time spent on activities (n=18)) can be acquired effortlessly, physiological parameters (e.g., heart rate, respiratory rate) are measurable on a limited scale (n=5). Behavioral data contribute to functional monitoring. Emergency monitoring can be built up on behavioral and environmental data. Acquired physiological parameters allow reasonable monitoring of physiological functions to a limited extent. Environmental data and behavioral data also detect safety and security abnormalities. Social interaction monitoring relies mainly on direct monitoring of tools of communication (smartphone; computer). In summary, convincing proof of a clear effect of these monitoring functions on clinical outcome with a large sample size and long-term monitoring is still lacking.
Suboptimal Omnidirectional Wheel Design and Implementation
Authors: Palacín Jordi , Martínez David , Rubies Elena , Clotet Eduard
Published: January 2021

The optimal design of an omnidirectional wheel is usually focused on the minimization of the gap between the free rollers of the wheel in order to minimize contact discontinuities with the floor in order to minimize the generation of vibrations. However, in practice, a fast, tall, and heavy-weighted mobile robot using optimal omnidirectional wheels may also need a suspension system in order to reduce the presence of vibrations and oscillations in the upper part of the mobile robot. This paper empirically evaluates whether a heavy-weighted omnidirectional mobile robot can take advantage of its passive suspension system in order to also use non-optimal or suboptimal omnidirectional wheels with a non-optimized inner gap. The main comparative advantages of the proposed suboptimal omnidirectional wheel are its low manufacturing cost and the possibility of taking advantage of the gap to operate outdoors. The experimental part of this paper compares the vibrations generated by the motion system of a versatile mobile robot using optimal and suboptimal omnidirectional wheels. The final conclusion is that a suboptimal wheel with a large gap produces comparable on-board vibration patterns while maintaining the traction and increasing the grip on non-perfect planar surfaces.
Evaluation of Accelerometer-Derived Data in the Context of Cycling Cadence and Saddle Height Changes in Triathlon
Authors: Evans Stuart A. , James Daniel A. , Rowlands David , Lee James B.
Published: January 2021

In the multisport of triathlon cycling is the longest of the three sequential disciplines. Triathlon bicycles differ from road bicycles with steeper seat tube angles with a change to saddle height altering the seat tube angle. This study evaluated the effectiveness of a tri axial accelerometer to determine acceleration magnitudes of the trunk in outdoor cycling in two saddle positions. Interpretation of data was evaluated based on cadence changes whilst triathletes cycled in an aerodynamic position in two saddle positions. The evaluation of accelerometer derived data within a characteristic overground setting suggests a significant reduction in mediolateral acceleration of the trunk, yielding a 25.1% decrease when saddle height was altered alongside reduced rate of perceived exertion (3.9%). Minimal differences were observed in anteroposterior and longitudinal acceleration. Evaluation of sensor data revealed a polynomial expression of the subtle changes between both saddle positions. This study shows that a triaxial accelerometer has capability to continuously measure acceleration magnitude of trunk movements during an in-the-field, varied cadence cycle protocol. Accessible and practical sensor technology could be relevant for postural considerations when exploring saddle position in dynamic settings.
A Distributed Multi-Hop Intra-Clustering Approach Based on Neighbors Two-Hop Connectivity for IoT Networks
Authors: Batta Mohamed Sofiane , Mabed Hakim , Aliouat Zibouda , Harous Saad
Published: January 2021

Under a dense and large IoT network, a star topology where each device is directly connected to the Internet gateway may cause serious waste of energy and congestion issues. Grouping network devices into clusters provides a suitable architecture to reduce the energy consumption and allows an effective management of communication channels. Although several clustering approaches were proposed in the literature, most of them use the single-hop intra-clustering model. In a large network, the number of clusters increases and the energy draining remains almost the same as in un-clustered architecture. To solve the problem, several approaches use the k-hop intra-clustering to generate a reduced number of large clusters. However, k-hop proposed schemes are, generally, centralized and only assume the node direct neighbors information which lack of robustness. In this regard, the present work proposes a distributed approach for the k-hop intra-clustering called Distributed Clustering based 2-Hop Connectivity (DC2HC). The algorithm uses the two-hop neighbors connectivity to elect the appropriate set of cluster heads and strengthen the clusters connectivity. The objective is to optimize the set of representative cluster heads to minimize the number of long range communication channels and expand the network lifetime. The paper provides the convergence proof of the proposed solution. Simulation results show that our proposed protocol outperforms similar approaches available in the literature by reducing the number of generated cluster heads and achieving longer network lifetime.
EUV and Hard X-ray Hartmann Wavefront Sensing for Optical Metrology, Alignment and Phase Imaging
Authors: de La Rochefoucauld Ombeline , Dovillaire Guillaume , Harms Fabrice , Idir Mourad , Huang Lei , Levecq Xavier , Piponnier Martin , Zeitoun Philippe
Published: January 2021

For more than 15 years, Imagine Optic have developed Extreme Ultra Violet (EUV) and X-ray Hartmann wavefront sensors for metrology and imaging applications. These sensors are compatible with a wide range of X-ray sources: from synchrotrons, Free Electron Lasers, laser-driven betatron and plasma-based EUV lasers to High Harmonic Generation. In this paper, we first describe the principle of a Hartmann sensor and give some key parameters to design a high-performance sensor. We also present different applications from metrology (for manual or automatic alignment of optics), to soft X-ray source optimization and X-ray imaging.
A Possible World-Based Fusion Estimation Model for Uncertain Data Clustering in WBNs
Authors: Li Chao , Zhang Zhenjiang , Wei Wei , Chao Han-Chieh , Liu Xuejun
Published: January 2021

In data clustering, the measured data are usually regarded as uncertain data. As a probability-based clustering technique, possible world can easily cluster the uncertain data. However, the method of possible world needs to satisfy two conditions: determine the data of different possible worlds and determine the corresponding probability of occurrence. The existing methods mostly make multiple measurements and treat each measurement as deterministic data of a possible world. In this paper, a possible world-based fusion estimation model is proposed, which changes the deterministic data into probability distribution according to the estimation algorithm, and the corresponding probability can be confirmed naturally. Further, in the clustering stage, the Kullback–Leibler divergence is introduced to describe the relationships of probability distributions among different possible worlds. Then, an application in wearable body networks (WBNs) is given, and some interesting conclusions are shown. Finally, simulations show better performance when the relationships between features in measured data are more complex.
NFC-Based Wearable Optoelectronics Working with Smartphone Application for Untact Healthcare
Authors: Kang Min Hyung , Lee Gil Ju , Yun Joo Ho , Song Young Min
Published: January 2021

With growing interest in healthcare, wearable healthcare devices have been developed and researched. In particular, near-field communication (NFC) based wearable devices have been actively studied for device miniaturization. Herein, this article proposes a low-cost and convenient healthcare system, which can monitor heart rate and temperature using a wireless/battery-free sensor and the customized smartphone application. The authors designed and fabricated a customized healthcare device based on the NFC system, and developed a smartphone application for real-time data acquisition and processing. In order to achieve compact size without performance degradation, a dual-layered layout is applied to the device. The authors demonstrate that the device can operate as attached on various body sites such as wrist, fingertip, temple, and neck due to outstanding flexibility of device and adhesive strength between the device and the skin. In addition, the data processing flow and processing result are presented for offering heart rate and skin temperature. Therefore, this work provides an affordable and practical pathway for the popularization of wireless wearable healthcare system. Moreover, the proposed platform can easily delivery the measured health information to experts for contactless/personal health consultation.
Analysis of the Influence of Different Bionic Structures on the Noise Reduction Performance of the Centrifugal Pump
Authors: Dai Cui , Guo Chao , Chen Yiping , Dong Liang , Liu Houlin
Published: January 2021

The strong noise generated during the operation of the centrifugal pump harms the pump group and people. In order to decrease the noise of the centrifugal pump, a specific speed of 117.3 of the centrifugal pump is chosen as a research object. The bionic modification of centrifugal pump blades is carried out to explore the influence of different bionic structures on the noise reduction performance of centrifugal pumps. The internal flow field and internal sound field of bionic blades are studied by numerical calculation and test methods. The test is carried out on a closed pump test platform which includes external characteristics and a flow noise test system. The effects of two different bionic structures on the external characteristics, acoustic amplitude–frequency characteristics and flow field structure of a centrifugal pump, are analyzed. The results show that the pit structure has little influence on the external characteristic parameters, while the sawtooth structure has a relatively great influence. The noise reduction effect of the pit structure is aimed at the wide-band noise, while the sawtooth structure is aimed at the discrete noise of the blade-passing frequency (BPF) and its frequency doubling. The noise reduction ability of the sawtooth structure is not suitable for high-frequency bands.
Blockchain Security and Privacy for the Internet of Things
Authors: Picone Marco , Cirani Simone , Veltri Luca
Published: January 2021

The Internet of Things (IoT) is of continuously growing interest for research and industry [...]
Examining the Driving Factors of the Direct Carbon Emissions of Households in the Ebinur Lake Basin Using the Extended STIRPAT Model
Authors: Chai Ziyuan , Simayi Zibibula , Yang Zhihan , Yang Shengtian
Published: January 2021

In order to achieve the carbon emission reduction targets in Xinjiang, it has become a necessary condition to study the carbon emission of households in small and medium-sized cities in Xinjiang. This paper studies the direct carbon emissions of households (DCEH) in the Ebinur Lake Basin, and based on the extended STIRPAT model, using the 1987–2017 annual time series data of the Ebinur Lake Basin in Xinjiang to analyze the driving factors. The results indicate that DCEH in the Ebinur Lake Basin during the 31 years from 1987 to 2017 has generally increased and the energy structure of DCEH has undergone tremendous changes. The proportion of coal continues to decline, while the proportion of natural gas, gasoline and diesel is growing rapidly. The main positive driving factors affecting its carbon emissions are urbanization, vehicle ownership and GDP per capita, while the secondary driving factor is residents’ year-end savings. Population, carbon intensity and energy consumption structure have negative effects on carbon emissions, of which energy consumption structure is the main factor. In addition, there is an environmental Kuznets curve between DCEH and economic development, but it has not yet reached the inflection point.
Driver Distraction Recognition Using Wearable IMU Sensor Data
Authors: Sun Wencai , Si Yihao , Guo Mengzhu , Li Shiwu
Published: January 2021

Distracted driving has become a major cause of road traffic accidents. There are generally four different types of distractions: manual, visual, auditory, and cognitive. Manual distractions are the most common. Previous studies have used physiological indicators, vehicle behavior parameters, or machine-visual features to support research. However, these technologies are not suitable for an in-vehicle environment. To address this need, this study examined a non-intrusive method for detecting in-transit manual distractions. Wrist kinematics data from 20 drivers were collected using wearable inertial measurement units (IMU) to detect four common gestures made while driving: dialing a hand-held cellular phone, adjusting the audio or climate controls, reaching for an object in the back seat, and maneuvering the steering wheel to stay in the lane. The study proposed a progressive classification model for gesture recognition, including two major time-based sequencing components and a Hidden Markov Model (HMM). Results show that the accuracy for detecting disturbances was 95.52%. The accuracy associated with recognizing manual distractions reached 96.63%, using the proposed model. The overall model has the advantages of being sensitive to perceptions of motion, effectively solving the problem of a fall-off in recognition performance due to excessive disturbances in motion samples.
Test-Retest Reliability of Isokinetic Knee Strength Measurements in Type 2 Diabetes Mellitus Patients
Authors: Adsuar José Carmelo , Parraca Jose , Raimundo Armando , Garcia-Gordillo Miguel Angel , Polero Patricia , Tomas-Carus Pablo
Published: January 2021

Background: Reliability studies are used to verify the evaluation accuracy of a given device. Strength is an important factor for the development of daily activities and its correct management is fundamental. The objective of this study was to examine the reliability of a concentric strength test in people with type 2 diabetes mellitus (T2DM). Methods: Twenty-seven individuals with T2DM performed three repetitions of extension-flexion in concentric-concentric action at 60°/s, for both legs, using an isokinetic dynamometer. For the reliability analysis, we performed an intra-session test retest. Results: The total sample and men sub-group intra-class correlation coefficient (ICC) values were excellent for peak torque and work. In the women sub-group, ICC values were excellent for extensors in both peak torque and work; however, concerning flexor, the ICC values were good for peak torque while, for work, they were good for the right leg and moderate for the left leg. Standard error of measurement (SEM) percentage oscillated from 3.85% to 6.80%, with the smallest real difference (SRD) percentage being from 10.66% to 18.86% for peak torque. Furthermore, the SEM (%) was around 5.5% and SRD (%) was around 15% for work. Conclusions: The isokinetic dynamometry had “good” to “excellent” relative reliability for peak torque (0.862–0.983) and work (0.744–0.982) of extension-flexion in concentric-concentric action at 60°/s. In addition, our study showed that, in general, an SRD < 20% could indicate a true change in strength regarding this protocol in T2DM.
Unsettled Belonging in Complex Geopolitics: Refugees, NGOs, and Rural Communities in Northern Colorado
Authors: Hausermann Heidi , Lundy Morgan , Mitchell Jill , Ipsen Annabel , Zorn Quentin , Vasquez-Romero Karen , DeMorrow Lynch Riley
Published: January 2021

In Colorado, meat processing and packing industries profit from the low-wage labor of foreign born workers and refugees in particular. Scholars and journalists have examined the hazardous and environmentally unjust workplace conditions in meatpacking, and detailed refugee struggles in North American resettlement geographies. Our research builds from this work to examine how multi-scalar geopolitical processes shape processes of refugee resettlement and refugee labor in Colorado’s meatpacking industries. Methods for this work include analysis of secondary data and twenty-two semi-structured interviews with various actors knowledgeable about refugee resettlement and/or agricultural production in Colorado. We argue various intersecting geopolitical processes—from immigration raids of meatpacking plants to presidential-level xenophobic discourses and ensuing immigration policies—interact to impact refugee resettlement and participation in the meat production sector. Moreover, while the U.S.’s neoliberal model of outsourcing resettlement to non-governmental organizations (NGOs) has been widely critiqued, we argue NGO employees, many of whom identify as foreign-born and/or refugees, work to build connection and belonging among refugees in challenging resettlement environments. We suggest a feminist geopolitics approach, which examines how the “global” and the “intimate” are deeply intertwined, is a useful perspective for understanding complicated racialized spaces in the rural United States, including efforts to build connections and empower refugee identities.
Does a Pro-Environmental Firm Attract Future Cash Flow? With an Impact of Sustainable Advertisement on Firms’ Financial Performance
Authors: Lee Jaehong , Kim Suyon
Published: January 2021

This study investigates the future existence of firms that are engaged in environment-oriented activities. Recently, strategic activities for firms’ sustainable growth has been critical for the environment. We use regression analysis to examine the relationship using firms listed in the Korea Stock Exchange market from 2014 to 2018. We use five aspects of environment-oriented activities: organization, management, strategy, performance, and shareholders, provided by the Korea Corporate Governance Service. The empirical results indicate that the firms participating in environment-oriented activities are likely to predict future cash flow, implying firms’ sustainability. We also claim that firms engaged in environment-oriented activities are likely to advertise their pro-environmental engagements, resulting in firms’ sustainable existence in the future. These findings are robust when we use the aggregate value as an alternative measurement. Our finding provides useful information for corporate practice. Active involvement in environmental activities can be used as a strategy that leads to superior performance. These efforts will contribute to enhancing the public image and improving green competitiveness. From the perspective of regulators, the non-financial information assessment supports the government’s eco-friendly policy that emphasizes environment-oriented activities. The results indicate that transparent information for external investors seeking to invest in firms are engaged in environment-oriented activities.
Future Work Self and Employee Creativity: The Mediating Role of Informal Field-Based Learning for High Innovation Performance
Authors: Zhang Qichao , Ma Zhenzhong , Ye Long , Guo Ming , Liu Shuzhen
Published: January 2021

In today’s highly uncertain environment, the value of creativity and innovation are increasingly critical. How individuals could improve their creativity and innovation performance has become the focus of attention. Future work self as an intrinsic motivation factor plays an important role in creativity and innovation. Based on the self-consistency theory, this study integrated proactive personality and informal field-based learning (IFBL) to explore the relationship between future work self and employee creativity to increase innovation performance. It used data from 201 R&D department employees in China’s high-tech companies. The results show that future work self has a positive effect on employee creativity and that IFBL mediates the relationship between future work self and employee creativity. This process is then positively moderated by a proactive personality. This study’s results help clarify the formation mechanism of creativity from the perspective of intrinsic motivation and indicate that future work self can drive individuals’ creativity and innovation efforts, especially under the consistency of self-concept, motivation and personality. This research also emphasizes the importance of IFBL in improving individual creativity and further organizational innovation performance. Implications for theory and management to help improve creativity and innovation performance are then discussed in detail.
Green Packaging from Consumer and Business Perspectives
Authors: Wandosell Gonzalo , Parra-Meroño María C. , Alcayde Alfredo , Baños Raúl
Published: January 2021

Sustainable development is a global objective that aims to address the societal challenge of climate action, the environment, resource efficiency, and raw materials. In this sense, an important strategy is the promotion of green packaging, that is, the use of sustainable materials and designs for the packaging of goods. In recent years, many research works have been published in the specialised area covering the different perspectives and dimensions of green packaging. However, to our knowledge, no previous investigations have analysed the research activity on green packaging from business and consumer perspectives. The present study intends to fill this gap by analysing all of the publications found in the Scopus database with the help of visual analytic tools, including word clouds and Gephi network visualization software. More specifically, our study analyses the impact of green packaging from business and consumer viewpoints, including some specific issues such as the design and materials used in green packaging, green packaging costs, marketing strategies and corporate social responsibility related to green packaging, and the impact of green packaging in waste management, the circular economy, logistics, and supply chain management. The results obtained reveal the growing interest of scholars and researchers in all of these dimensions, as is made patently clear by the increasing number of journal publications in recent years. The practical implications of this study are significant, given the growing awareness among companies and consumers about the importance of the promotion of sustainable development through green packaging alternatives. More specifically, the results of this research could be very useful for all of those agents who are interested in learning about the main lines of research being developed in the field of green packaging.
Measuring Historical Urban Neighborhood Sustainability: America’s Grand Avenues
Authors: Greenberg Michael R.
Published: January 2021

From 1850 through approximately 1920, wealthy entrepreneurs and elected officials created “grand avenues” lined by mansions in New York City, Chicago, Detroit, and other developing US cities. This paper examines the birthplaces of grand avenues to determine whether they have remained sustainable as magnets for healthy and wealthy people. Using data from the US EPA’s EJSCREEN system and the CDC’s 500 cities study across 11 cities, the research finds that almost every place where a grand avenue began has healthier and wealthier people than their host cities. Ward Parkway in Kansas City and New York’s Fifth Avenue have continued to be grand. Massachusetts Avenue in Washington, D.C., Richmond’s Monument Avenue, St. Charles Avenue in New Orleans, and Los Angeles’s Wilshire Boulevard are national and regional symbols of political power, culture and entertainment, leading to sustainable urban grand avenues, albeit several are challenged by their identification with white supremacy. Among Midwest industrial cities, Chicago’s Prairie Avenue birthplace has been the most successful, whereas the grand avenues of St. Louis, Cleveland, Detroit, and Buffalo have struggled, trying to use higher education, medical care, and entertainment to try to rebirth their once pre-eminent roles in their cities.
Air Pollution Prediction Using an Ensemble of Dynamic Transfer Models for Multivariate Time Series
Authors: Kong Taewoon , Choi Dongguen , Lee Geonseok , Lee Kichun
Published: January 2021

Entering a new era of big data, analysis of large amounts of real-time data is important, and air quality data as streaming time series are measured by several different sensors. To this end, numerous methods for time-series forecasting and deep-learning approaches based on neural networks have been used. However, they usually rely on a certain model with a stationary condition, and there are few studies of real-time prediction of dynamic massive multivariate data. Use of a variety of independent variables included in the data is important to improve forecasting performance. In this paper, we proposed a real-time prediction approach based on an ensemble method for multivariate time-series data. The suggested method can select multivariate time-series variables and incorporate real-time updatable autoregressive models in terms of performance. We verified the proposed model using simulated data and applied it to predict air quality measured by five sensors and failures based on real-time performance log data in server systems. We found that the proposed method for air pollution prediction showed effective and stable performance for both short- and long-term prediction tasks. In addition, traditional methods for abnormality detection have focused on present status of objects as either normal or abnormal based on provided data, we protectively predict expected statuses of objects with provided real-time data and implement effective system management in cloud environments through the proposed method.
Resident-Tourist Value Co-Creation in the Intangible Cultural Heritage Tourism Context: The Role of Residents’ Perception of Tourism Development and Emotional Solidarity
Authors: Lan Tianning , Zheng Zhiyue , Tian Di , Zhang Rui , Law Rob , Zhang Mu
Published: January 2021

The value co-creation behavior of residents can contribute to the sustainable development of intangible cultural heritage (ICH) tourism. This paper aims to provide a theoretical framework that uses “cognition–affection–behavior” theory to explain how the two variables of tourism development perception and emotional solidarity affect the value co-creation participation behavior of the local residents in the context of intangible cultural heritage tourism while considering the mediating role of emotional solidarity. This study empirically investigates Meizhou Island in Fujian Province, China as an example by using a structural equation model (SEM). Results show that the perception of local residents toward the benefits of tourism development has a significant positive impact on their emotional solidarity and value co-creation participation behavior, whereas their perception toward the costs of tourism development has a significant negative impact. In addition, the emotional solidarity of these residents has a significant positive impact on their value co-creation participation and plays a mediating role in the relationship between the tourism development perceptions of local residents and their value co-creation participation behavior. This study has important theoretical and practical significance for the management of ICH tourist destinations.
Detecting All Non-Dominated Points for Multi-Objective Multi-Index Transportation Problems
Authors: Abd Elazeem Abd Elazeem M. , Mousa Abd Allah A. , El-Shorbagy Mohammed A. , Elagan Sayed K. , Abo-Elnaga Yousria
Published: January 2021

Multi-dimensional transportation problems denoted as multi-index are considered as the extension of classical transportation problems and are appropriate practical modeling for solving real–world problems with multiple supply, multiple demand, as well as different modes of transportation demands or delivering different kinds of commodities. This paper presents a method for detecting the complete nondominated set (efficient solutions) of multi-objective four-index transportation problems. The proposed approach implements weighted sum method to convert multi-objective four-index transportation problem into a single objective four-index transportation problem, that can then be decomposed into a set of two-index transportation sub-problems. For each two-index sub-problem, parametric analysis was investigated to determine the range of the weights values that keep the efficient solution unchanged, which enable the decision maker to detect the set of all nondominated solutions for the original multi-objective multi-index transportation problem, and also to find the stability set of the first kind for each efficient solution. Finally, an illustrative example is presented to illustrate the efficiency and robustness of the proposed approach. The results demonstrate the effectiveness and robustness for the proposed approach to detect the set of all nondominated solutions.
Enhancement of the Concrete Durability with Hybrid Nano Materials
Authors: Gamal Heba A. , El-Feky M. S. , Alharbi Yousef R. , Abadel Aref A. , Kohail Mohamed
Published: January 2021

The importance of the incorporation of nanomaterials in concrete has emerged as a promising research interest due to the outstanding functionalized properties of the materials at that size level. This study aims to investigate the engineering and durability properties of concrete incorporated with hybrid nanomaterials. In this study, the influence of carbon nanotube (CNT) on microstructure, mechanical, and corrosion characteristics of nano-clay-based (NC) concrete has been evaluated. The cement was replaced with CNT at different percentages of 0.01%, 0.02%, and 0.04% by weight, while NC was replaced at a constant percentage of 5%. A scanning electron microscope (SEM) was used to examine the microstructural characterization of the samples. To investigate the influence of carbon nanotubes in the fresh properties, slump and air content tests were carried out. The compressive strength, tensile strength, flexural strength, and bond strength of the hardened concrete was evaluated according to ASTM standards. The porosity of specimens was determined by carrying out the sorptivity and water penetration tests. The corrosion resistance of the steel bar embedded in concrete was assessed. The results of SEM examinations showed that incorporating CNT into the nano-clay-based concrete remarkably achieved a denser structure at all studied contents. Further, significant enhancements in the mechanical properties, durability, and chloride penetration resistance were attained when incorporating CNT in the NC concrete. Further, adding CNTs improves the corrosion resistance and has proven useful resistance to crack propagation within the concrete matrix as compared to the control mix without CNT. Results of this study prove that the incorporation of hybrid nano CNT and NC gives better performance for mechanical strength and durability properties.
Harvesting Waste Thermal Energy Using a Surface-Modified Carbon Fiber-Based Thermo-Electrochemical Cell
Authors: Artyukhov Denis , Kiselev Nikolay , Gorshkov Nikolay , Kovyneva Natalya , Ganzha Olga , Vikulova Maria , Gorokhovsky Alexander , Offor Peter , Boychenko Elena , Burmistrov Igor
Published: January 2021

An important direction in the development of energy saving policy is harvesting and conversion into electricity of low-grade waste heat. The present paper is devoted to the improvement of the efficiency of thermo-electrochemical cells based on carbon fiber electrodes and potassium ferri-/ferrocyanide redox electrolyte. The influence of the carbon fiber electrode surface modification (magnetron deposition of silver and titanium or infiltration implantation of nanoscale titanium oxide) on the output power and parameters of the impedance equivalent scheme of a thermo-electrochemical cell has been studied. Two kinds of cell designs (a conventional electrochemical cell with a salt bridge and a coin cell-type body) were investigated. It was found that the nature of the surface modification of electrodes can change the internal resistance of the cell by three orders of magnitude. The dependence of the equivalent scheme parameters and output power density of the thermoelectric cell on the type of electrode materials was presented. It was observed that the maximum power for carbon fiber modified with titanium metal and titanium oxide was 25.2 mW/m2 and the efficiency was 1.37%.