bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultrathin Photonic Polymer Gel Films Templated by Non-Close-Packed Monolayer Colloidal Crystals to Enhance Colorimetric Sensing
Authors: Yu Shimo , Dong Shun , Jiao Xiuling , Li Cheng , Chen Dairong
Published: March 2019

Responsive polymer-based sensors have attracted considerable attention due to their ability to detect the presence of analytes and convert the detected signal into a physical and/or chemical change. High responsiveness, fast response speed, good linearity, strong stability, and small hysteresis are ideal, but to gain these properties at the same time remains challenging. This paper presents a facile and efficient method to improve the photonic sensing properties of polymeric gels by using non-close-packed monolayer colloidal crystals (ncp MCCs) as the template. Poly-(2-vinyl pyridine) (P2VP), a weak electrolyte, was selected to form the pH-responsive gel material, which was deposited onto ncp MCCs obtained by controlled O2 plasma etching of close-packed (cp) MCCs. The resultant ultrathin photonic polymer gel film (UPPGF) exhibited significant improvement in responsiveness and linearity towards pH sensing compared to those prepared using cp MCCs template, achieving fast visualized monitoring of pH changes with excellent cyclic stability and small hysteresis loop. The responsiveness and linearity were found to depend on the volume and filling fraction of the polymer gel. Based on a simple geometric model, we established that the volume increased first and then decreased with the decrease of template size, but the filling fraction increased all the time, which was verified by microscopy observations. Therefore, the responsiveness and linearity of UPPGF to pH can be improved by simply adjusting the etching time of oxygen plasma. The well-designed UPPGF is reliable for visualized monitoring of analytes and their concentrations, and can easily be combined in sensor arrays for more accurate detection.
Improving an Extreme Rainfall Detection System with GPM IMERG data
Authors: Mazzoglio Paola , Laio Francesco , Balbo Simone , Boccardo Piero , Disabato Franca
Published: March 2019

Many studies have shown a growing trend in terms of frequency and severity of extreme events. As never before, having tools capable to monitor the amount of rain that reaches the Earth’s surface has become a key point for the identification of areas potentially affected by floods. In order to guarantee an almost global spatial coverage, NASA Global Precipitation Measurement (GPM) IMERG products proved to be the most appropriate source of information for precipitation retrievement by satellite. This study is aimed at defining the IMERG accuracy in representing extreme rainfall events for varying time aggregation intervals. This is performed by comparing the IMERG data with the rain gauge ones. The outcomes demonstrate that precipitation satellite data guarantee good results when the rainfall aggregation interval is equal to or greater than 12 h. More specifically, a 24-h aggregation interval ensures a probability of detection (defined as the number of hits divided by the total number of observed events) greater than 80%. The outcomes of this analysis supported the development of the updated version of the ITHACA Extreme Rainfall Detection System (ERDS: erds.ithacaweb.org). This system is now able to provide near real-time alerts about extreme rainfall events using a threshold methodology based on the mean annual precipitation.
Wide Field of View Microwave Interferometric Radiometer Imaging
Authors: Corbella Ignasi , Torres Francesc , Duffo Nuria , Duran Israel , Gonzalez-Gambau Veronica , Martin-Neira Manuel
Published: March 2019

In microwave interferometric radiometers with a large field of view, as for example the Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) onboard the Soil Moisture and Ocean Salinity (SMOS) satellite, one of the major causes of reconstruction error is the contribution to the visibility of the brightness temperature outside the fundamental period, defined on the basis of reciprocal grids. A mitigation method consisting of estimating this contribution through the application of a brightness temperature model outside the fundamental period is proposed. The main advantage is that it does not require any a posteriori addition of artificial scenes to the reconstructed image. Additionally, a method to avoid the sophisticated matrix regularization and inversion techniques usually applied in microwave interferometry is presented. Image reconstruction algorithms are implemented on a minimum grid size in order to maximize their numerical efficiency. An improved method to apply an apodization window to the reconstructed image for reducing Gibbs oscillations is also proposed. All procedures are generally described considering the single polarization case and successively implemented applying the MIRAS layout in both its single polarization and full polarimetric modes. Results show similar performance of the proposed algorithm with respect to the nominal one applied by SMOS. All algorithms are implemented in the MIRAS Testing Software and have been successfully used for scientific studies by other teams.
Rebuilding a Microwave Soil Moisture Product Using Random Forest Adopting AMSR-E/AMSR2 Brightness Temperature and SMAP over the Qinghai–Tibet Plateau, China
Authors: Qu Yuquan , Zhu Zhongli , Chai Linna , Liu Shaomin , Montzka Carsten , Liu Jin , Yang Xiaofan , Lu Zheng , Jin Rui , Li Xiang , Guo Zhixia , Zheng Jie
Published: March 2019

Time series of soil moisture (SM) data in the Qinghai–Tibet plateau (QTP) covering a period longer than one decade are important for understanding the dynamics of land surface–atmosphere feedbacks in the global climate system. However, most existing SM products have a relatively short time series or show low performance over the challenging terrain of the QTP. In order to improve the spaceborne monitoring in this area, this study presents a random forest (RF) method to rebuild a high-accuracy SM product over the QTP from 19 June 2002 to 31 March 2015 by adopting the advanced microwave scanning radiometer for earth observing system (AMSR-E), and the advanced microwave scanning radiometer 2 (AMSR2), and tracking brightness temperatures with latitude and longitude using the International Geosphere–Biospheres Programme (IGBP) classification data, the digital elevation model (DEM) and the day of the year (DOY) as spatial predictors. Brightness temperature products (from frequencies 10.7 GHz, 18.7 GHz and 36.5 GHz) of AMSR2 were used to train the random forest model on two years of Soil Moisture Active Passive (SMAP) SM data. The simulated SM values were compared with third year SMAP data and in situ stations. The results show that the RF model has high reliability as compared to SMAP, with a high correlation (R = 0.95) and low values of root mean square error (RMSE = 0.03 m3/m3) and mean absolute percent error (MAPE = 19%). Moreover, the random forest soil moisture (RFSM) results agree well with the data from five in situ networks, with mean values of R = 0.75, RMSE = 0.06 m3/m3, and bias = −0.03 m3/m3 over the whole year and R = 0.70, RMSE = 0.07 m3/m3, and bias = −0.05 m3/m3 during the unfrozen seasons. In order to test its performance throughout the whole region of QTP, the three-cornered hat (TCH) method based on removing common signals from observations and then calculating the uncertainties is applied. The results indicate that RFSM has the smallest relative error in 56% of the region, and it performs best relative to the Japan Aerospace Exploration Agency (JAXA), Global Land Data Assimilation System (GLDAS), and European Space Agency’s Climate Change Initiative (ESA CCI) project. The spatial distribution shows that RFSM has a similar spatial trend as GLDAS and ESA CCI, but RFSM exhibits a more distinct spatial distribution and responds to precipitation more effectively than GLDAS and ESA CCI. Moreover, a trend analysis shows that the temporal variation of RFSM agrees well with precipitation and LST (land surface temperature), with a dry trend in most regions of QTP and a wet trend in few north, southeast and southwest regions of QTP. In conclusion, a spatiotemporally continuous SM product with a high accuracy over the QTP was obtained.
Shallow-Water Habitat Mapping using Underwater Hyperspectral Imaging from an Unmanned Surface Vehicle: A Pilot Study
Authors: Mogstad Aksel Alstad , Johnsen Geir , Ludvigsen Martin
Published: March 2019

The impacts of human activity on coastal ecosystems are becoming increasingly evident across the world. Consequently, there is a growing need to map, monitor, and manage these regions in a sustainable manner. In this pilot study, we present what we believe to be a novel mapping technique for shallow-water seafloor habitats: Underwater hyperspectral imaging (UHI) from an unmanned surface vehicle (USV). A USV-based UHI survey was carried out in a sheltered bay close to Trondheim, Norway. In the survey, an area of 176 m2 was covered, and the depth of the surveyed area was approximately 1.5 m. UHI data were initially recorded at a 1-nm spectral resolution within the range of 380–800 nm, but this was reduced to 86 spectral bands between 400-700 nm (3.5-nm spectral resolution) during post-processing. The hyperspectral image acquisition was synchronized with navigation data from the USV, which permitted georeferencing and mosaicking of the imagery at a 0.5-cm spatial resolution. Six spectral classes, including coralline algae, the wrack Fucus serratus, green algal films, and invertebrates, were identified in the georeferenced imagery, and chosen as targets for support vector machine (SVM) classification. Based on confusion matrix analyses, the overall classification accuracy was estimated to be 89%–91%, which suggests that USV-based UHI may serve as a useful tool for high-resolution mapping of shallow-water habitats in the future.
Plant Microbial Fuel Cells–Based Energy Harvester System for Self-powered IoT Applications
Authors: Osorio de la Rosa Edith , Vázquez Castillo Javier , Carmona Campos Mario , Barbosa Pool Gliserio Romeli , Becerra Nuñez Guillermo , Castillo Atoche Alejandro , Ortegón Aguilar Jaime
Published: March 2019

The emergence of modern technologies, such as Wireless Sensor Networks (WSNs), the Internet-of-Things (IoT), and Machine-to-Machine (M2M) communications, involves the use of batteries, which pose a serious environmental risk, with billions of batteries disposed of every year. However, the combination of sensors and wireless communication devices is extremely power-hungry. Energy Harvesting (EH) is fundamental in enabling the use of low-power electronic devices that derive their energy from external sources, such as Microbial Fuel Cells (MFC), solar power, thermal and kinetic energy, among others. Plant Microbial Fuel Cell (PMFC) is a prominent clean energy source and a step towards the development of self-powered systems in indoor and outdoor environments. One of the main challenges with PMFCs is the dynamic power supply, dynamic charging rates and low-energy supply. In this paper, a PMFC-based energy harvester system is proposed for the implementation of autonomous self-powered sensor nodes with IoT and cloud-based service communication protocols. The PMFC design is specifically adapted with the proposed EH circuit for the implementation of IoT-WSN based applications. The PMFC-EH system has a maximum power point at 0.71 V, a current density of 5 mA cm − 2 , and a power density of 3.5 mW cm − 2 with a single plant. Considering a sensor node with a current consumption of 0.35 mA, the PMFC-EH green energy system allows a power autonomy for real-time data processing of IoT-based low-power WSN systems.
A Distributed Architecture for Human-Drone Teaming: Timing Challenges and Interaction Opportunities
Authors: Hummel Karin Anna , Pollak Manuela , Krahofer Johannes
Published: March 2019

Drones are expected to operate autonomously, yet they will also interact with humans to solve tasks together. To support civilian human-drone teams, we propose a distributed architecture where sophisticated operations such as image recognition, coordination with humans, and flight-control decisions are made, not on-board the drone, but remotely. The benefits of such an architecture are the increased computational power available for image recognition and the possibility to integrate interfaces for humans. On the downside, communication is necessary, resulting in the delayed reception of commands. In this article, we discuss the design considerations of the distributed approach, a sample implementation on a smartphone, and an application to the concrete use case of bookshelf inventory. Further, we report experimentally-derived first insights into messaging and command response delays with a custom drone connected through Wi-Fi.
Consensus-Based Track Association with Multistatic Sensors under a Nested Probabilistic-Numerical Linguistic Environment
Authors: Wang Xinxin , Xu Zeshui , Gou Xunjie
Published: March 2019

Track association is an important technology in military and civilian fields. Due to the increasingly complex environment and the diversity of the sensors, it is a key factor to separate the corresponding track from multiple maneuvering targets by multisensors with a consensus. In this paper, we first transform the track association problem to multiattribute group decision making (MAGDM), and describe the MAGDM with nested probabilistic-numerical linguistic term sets (NPNLTSs). Then, a consensus model with NPNLTSs is constructed which has two key processes. One is a consensus checking process, and the other is a consensus modifying process. Based on which, a track association algorithm with automatic modification is put forward based on the consensus model. After that, the solution of a case study in practice is given to obtain the corresponding track by the proposed method, and it provides technical support for the track association problems. Finally, we make comparisons with other methods from three aspects, and the results show that the proposed method is effective, feasible, and applicable. Moreover, some discussions about the situation where there is only one echo point at a time are provided, and we give a discriminant analysis method.
Contextual Action Cues from Camera Sensor for Multi-Stream Action Recognition
Authors: Hong Jongkwang , Cho Bora , Hong Yong Won , Byun Hyeran
Published: March 2019

In action recognition research, two primary types of information are appearance and motion information that is learned from RGB images through visual sensors. However, depending on the action characteristics, contextual information, such as the existence of specific objects or globally-shared information in the image, becomes vital information to define the action. For example, the existence of the ball is vital information distinguishing “kicking” from “running”. Furthermore, some actions share typical global abstract poses, which can be used as a key to classify actions. Based on these observations, we propose the multi-stream network model, which incorporates spatial, temporal, and contextual cues in the image for action recognition. We experimented on the proposed method using C3D or inflated 3D ConvNet (I3D) as a backbone network, regarding two different action recognition datasets. As a result, we observed overall improvement in accuracy, demonstrating the effectiveness of our proposed method.
Low-Cost Curb Detection and Localization System Using Multiple Ultrasonic Sensors
Authors: Rhee Joon Hyo , Seo Jiwon
Published: March 2019

Curb detection and localization systems constitute an important aspect of environmental recognition systems of autonomous driving vehicles. This is because detecting curbs can provide information about the boundary of a road, which can be used as a safety system to prevent unexpected intrusions into pedestrian walkways. Moreover, curb detection and localization systems enable the autonomous vehicle to recognize the surrounding environment and the lane in which the vehicle is driving. Most existing curb detection and localization systems use multichannel light detection and ranging (lidar) as a primary sensor. However, although lidar demonstrates high performance, it is too expensive to be used for commercial vehicles. In this paper, we use ultrasonic sensors to implement a practical, low-cost curb detection and localization system. To compensate for the relatively lower performance of ultrasonic sensors as compared to other higher-cost sensors, we used multiple ultrasonic sensors and applied a series of novel processing algorithms that overcome the limitations of a single ultrasonic sensor and conventional algorithms. The proposed algorithms consisted of a ground reflection elimination filter, a measurement reliability calculation, and distance estimation algorithms corresponding to the reliability of the obtained measurements. The performance of the proposed processing algorithms was demonstrated by a field test under four representative curb scenarios. The availability of reliable distance estimates from the proposed methods with three ultrasonic sensors was significantly higher than that from the other methods, e.g., 92.08% vs. 66.34%, when the test vehicle passed a trapezoidal-shaped road shoulder. When four ultrasonic sensors were used, 96.04% availability and 13.50 cm accuracy (root mean square error) were achieved.
Controlled Lighting and Illumination-Independent Target Detection for Real-Time Cost-Efficient Applications. The Case Study of Sweet Pepper Robotic Harvesting
Authors: Arad Boaz , Kurtser Polina , Barnea Ehud , Harel Ben , Edan Yael , Ben-Shahar Ohad
Published: March 2019

Current harvesting robots are limited by low detection rates due to the unstructured and dynamic nature of both the objects and the environment. State-of-the-art algorithms include color- and texture-based detection, which are highly sensitive to the illumination conditions. Deep learning algorithms promise robustness at the cost of significant computational resources and the requirement for intensive databases. In this paper we present a Flash-No-Flash (FNF) controlled illumination acquisition protocol that frees the system from most ambient illumination effects and facilitates robust target detection while using only modest computational resources and no supervised training. The approach relies on the simultaneous acquisition of two images—with/without strong artificial lighting (“Flash”/“no-Flash”). The difference between these images represents the appearance of the target scene as if only the artificial light was present, allowing a tight control over ambient light for color-based detection. A performance evaluation database was acquired in greenhouse conditions using an eye-in-hand RGB camera mounted on a robotic manipulator. The database includes 156 scenes with 468 images containing a total of 344 yellow sweet peppers. Performance of both color blob and deep-learning detection algorithms are compared on Flash-only and FNF images. The collected database is made public.
On the Use of Oblique Acoustic Leakage to Measure the Wavenumber Spectrum of Propagating Lamb Waves
Authors: Hakoda Christopher , Hasanian Mostafa , Lissenden Cliff J.
Published: March 2019

Lamb waves propagating within a waveguide often have similar frequency content. If there are multiple Lamb wave modes with the same frequency content, the wavenumber spectrum can be used to distinguish between them. As a result, the wavenumber spectrum is an important tool for determining the modal content of signals. In this paper, we propose a new method for measuring wavenumber spectra that uses an air-coupled transducer for reception and Snell’s law instead of a fast-Fourier transform. The method employs an angular scan rather than a translational scan. The advantages and disadvantages of the method are discussed along with some suggestions for potential improvements. Finally, experimental results comparing the proposed method to a more conventional method, which used a PVDF transducer, demonstrate the feasibility of the proposed method.
Variability of the UHF Signals Generated by Partial Discharges in Mineral Oil
Authors: Kunicki Michal
Published: March 2019

The paper presents the results of the analysis on the variability of the ultra-high frequency (UHF) signals generated by partial discharges (PD) under the long-term AC voltage. Surface PD (SD) are generated by model PD source (PDS) immersed in brand new mineral oil. Three scenarios are compared and investigated, where different solid dielectrics are applied: pressboard paper (PBP), polytetrafluoroethylene (PTFE) and glass-ceramic (GLS). The PDS is powered continuously by the AC voltage with its relative level of 1.3 of the inception voltage (Ui) within 168 h. UHF signals generated by the continuously occurred SD within 168 h are registered. Various indicators describing the variability of the UHF signals emitted by SD are assigned and analyzed in order to discover if there are any relevant trends presented. Furthermore, some long-term characteristics of the UHF signals emitted by the applied PDS are also announced. As a result, some relevant trends are discovered and related to the properties of the applied dielectric materials, thus the variability of the UHF signals emitted by SD is confirmed. The highest variability of the UHF signals is associated with PBP and the first 48 h after PD inception. Moreover achieved results may be potentially applied for modeling of the PD variability in time, which may be useful for works that concern the development of the UHF method.
An Effective Spectrum Handoff Based on Reinforcement Learning for Target Channel Selection in the Industrial Internet of Things
Authors: Oyewobi Stephen S. , Hancke Gerhard P. , Abu-Mahfouz Adnan M. , Onumanyi Adeiza J.
Published: March 2019

The overcrowding of the wireless space has triggered a strict competition for scare network resources. Therefore, there is a need for a dynamic spectrum access (DSA) technique that will ensure fair allocation of the available network resources for diverse network elements competing for the network resources. Spectrum handoff (SH) is a DSA technique through which cognitive radio (CR) promises to provide effective channel utilization, fair resource allocation, as well as reliable and uninterrupted real-time connection. However, SH may consume extra network resources, increase latency, and degrade network performance if the spectrum sensing technique used is ineffective and the channel selection strategy (CSS) is poorly implemented. Therefore, it is necessary to develop an SH policy that holistically considers the implementation of effective CSS, and spectrum sensing technique, as well as minimizes communication delays. In this work, two reinforcement learning (RL) algorithms are integrated into the CSS to perform channel selection. The first algorithm is used to evaluate the channel future occupancy, whereas the second algorithm is used to determine the channel quality in order to sort and rank the channels in candidate channel list (CCL). A method of masking linearly dependent and useless state elements is implemented to improve the convergence of the learning. Our approach showed a significant reduction in terms of latency and a remarkable improvement in throughput performance in comparison to conventional approaches.
In-Situ Monitoring of a Filament Wound Pressure Vessel by the MWCNT Sensor under Hydraulic Fatigue Cycling and Pressurization
Authors: Xiao Biao , Yang Bin , Xuan Fu-Zhen , Wan Yun , Hu Chaojie , Jin Pengcheng , Lei Hongshuai , Xiang Yanxun , Yang Kang
Published: March 2019

As a result of the high specific strength/stiffness to mass ratio, filament wound composite pressure vessels are extensively used to contain gas or fluid under pressure. The ability to in-situ monitor the composite pressure vessels for possible damage is important for high-pressure medium storage industries. This paper describes an in-situ monitoring method to permanently monitor composite pressure vessels for their structural integrity. The sensor is made of a multi-walled carbon nanotube (MWCNT) that can be embedded in the composite skin of the pressure vessels. The sensing ability of the sensor is firstly evaluated in various mechanical tests, and in-situ monitoring experiments of a full-scale composite pressure vessel during hydraulic fatigue cycling and pressurization are performed. The monitoring results of the MWCNT sensor are compared with the strains measured by the strain gauges. The results show that the measured signal by the developed sensor matches the mechanical behavior of the composite laminates under various load conditions. In the hydraulic fatigue test, the relationship between the resistance and the strain is built, and could be used to quantitative monitor the filament wound pressure vessel. The bursting of the pressure vessel can be detected by the sharp increase of the MWCNT sensor resistance. Embedding the MWCNT sensor into the composite pressure vessel is successfully demonstrated as a promising method for structural health monitoring.
Development and Characterization of Thermal Flow Sensors for Non-Invasive Measurements in HVAC Systems
Authors: Cerimovic Samir , Treytl Albert , Glatzl Thomas , Beigelbeck Roman , Keplinger Franz , Sauter Thilo
Published: March 2019

We investigated non-invasive flow rate measurements in heating, ventilation, and air conditioning (HVAC) systems utilizing thermal transduction instead of commonly used ultrasonic techniques. The proposed thermal flow transduction comprises two temperature sensors and a heater, all mounted non-invasively on the outer surface of metal-pipes and, therefore, not disturbing the fluid flow inside. One temperature sensor measures the heater temperature, whereas the other one, mounted upstream of the heater, follows the fluid temperature for reference. The temperature difference (i.e., the heater excess temperature) depends on the fluid flow velocity and can be used to derive the mean volume flow inside the pipe. Experimental characterizations were conducted using two sensor prototypes. Beside output characteristics, other main issues such as dynamic behavior and noise density were investigated in detail. Special attention was paid to error compensation allowing measurements within a large range of fluid temperatures. Measurement results confirm the feasibility of this approach, however with some constraints regarding response time.
A Combined Approach of Field Data and Earth Observation for Coastal Risk Assessment
Authors: Bruno Maria Francesca , Molfetta Matteo Gianluca , Pratola Luigi , Mossa Michele , Nutricato Raffaele , Morea Alberto , Nitti Davide Oscar , Chiaradia Maria Teresa
Published: March 2019

The traditional approach for coastal monitoring consists in ground investigations that are burdensome both in terms of logistics and costs, on a national or even regional scale. Earth Observation (EO) techniques can represent a cost-effective alternative for a wide scale coastal monitoring. Thanks to the all-weather day/night radar imaging capability and to the nationwide acquisition plan named MapItaly, devised by the Italian Space Agency and active since 2010, COSMO-SkyMed (CSK) constellation is able to provide X-band images covering the Italian territory. However, any remote sensing approach must be accurately calibrated and corrected taking into account the marine conditions. Therefore, in situ data are essential for proper EO data selection, geocoding, tidal corrections and validation of EO products. A combined semi-automatic technique for coastal risk assessment and monitoring, named COSMO-Beach, is presented here, integrating ground truths with EO data, as well as its application on two different test sites in Apulia Region (South Italy). The research has shown that CSK data for coastal monitoring ensure a shoreline detection accuracy lower than image pixel resolution, and also providing several advantages: low-cost data, a short revisit period, operational continuity and a low computational time.
An Integrated Approach to Goal Selection in Mobile Robot Exploration
Authors: Kulich Miroslav , Kubalík Jiří , Přeučil Libor
Published: March 2019

This paper deals with the problem of autonomous navigation of a mobile robot in an unknown 2D environment to fully explore the environment as efficiently as possible. We assume a terrestrial mobile robot equipped with a ranging sensor with a limited range and 360 ° field of view. The key part of the exploration process is formulated as the d-Watchman Route Problem which consists of two coupled tasks—candidate goals generation and finding an optimal path through a subset of goals—which are solved in each exploration step. The latter has been defined as a constrained variant of the Generalized Traveling Salesman Problem and solved using an evolutionary algorithm. An evolutionary algorithm that uses an indirect representation and the nearest neighbor based constructive procedure was proposed to solve this problem. Individuals evolved in this evolutionary algorithm do not directly code the solutions to the problem. Instead, they represent sequences of instructions to construct a feasible solution. The problems with efficiently generating feasible solutions typically arising when applying traditional evolutionary algorithms to constrained optimization problems are eliminated this way. The proposed exploration framework was evaluated in a simulated environment on three maps and the time needed to explore the whole environment was compared to state-of-the-art exploration methods. Experimental results show that our method outperforms the compared ones in environments with a low density of obstacles by up to 12.5 % , while it is slightly worse in office-like environments by 4.5 % at maximum. The framework has also been deployed on a real robot to demonstrate the applicability of the proposed solution with real hardware.
Electromechanical Dynamics Model of Ultrasonic Transducer in Ultrasonic Machining Based on Equivalent Circuit Approach
Authors: Zhang Jian-Guo , Long Zhi-Li , Ma Wen-Ju , Hu Guang-Hao , Li Yang-Min
Published: March 2019

Ultrasonic transducer is a piezoelectric actuator that converts AC electrical energy into ultrasonic mechanical vibration to accelerate the material removal rate of workpiece in rotary ultrasonic machining (RUM). In this study, an impedance model of the ultrasonic transducer is established by the electromechanical equivalent approach. The impedance model not only facilitates the structure design of the ultrasonic transducer, but also predicts the effects of different mechanical structural dimensions on the impedance characteristics of the ultrasonic transducer. Moreover, the effects of extension length of the machining tool and the tightening torque of the clamping nut on the impedance characteristics of the ultrasonic transducer are investigated. Finally, through experimental analysis, the impedance transfer function with external force is established to analyze the dynamic characteristics of machining process.
Accurate Multiple Ocean Bottom Seismometer Positioning in Shallow Water Using GNSS/Acoustic Technique
Authors: Liu Huimin , Wang Zhenjie , Zhao Shuang , He Kaifei
Published: March 2019

The Global Navigation Satellite System combined with acoustic technique has achieved great economic benefits in positioning of ocean bottom seismometers, with hundreds of underwater transponders attached to seismometers typically being deployed during oil exploration. The previous single transponder positioning method ignored the similar underwater environments between the transponders. Due to the refraction effect of sound, the technique usually showed poor positioning accuracy in shallow water when the incidence angles are large. In this paper, the effect of sound ray bending is analyzed based on the sound ray tracing method in shallow water, and a new piecewise incidence angle model is proposed to improve the positioning accuracy of multiple objects in order to estimate the sound ray bending correction. The parameters of the new model are divided into groups and estimated by sequential least squares method, together with all of the transponders. The observability analysis is discussed in simulation and testing experiments in the South China Sea. The results show that the newly proposed method is able to make full use of the acoustic observation data of hundreds of transponders to accurately estimate the SRB correction, which could also significantly improve the positioning accuracy of multiple transponders.
Food Safety Satisfaction in China and Its Influencing Factors: Empirical Study with a Hierarchical Linear Model
Authors: He Chunhua , Han Guanghua , Liu Yihong
Published: March 2019

Food safety is one of the residents’ initial demands in daily life, and the negative perception of food safety potentially leads to public panic and dissatisfaction with government performance. Existing literature only focused on certain regions in China by using different indicators, and their results varied and lacked comparability. This paper explores influencing factors of the public’s satisfaction with food safety by conducting a nationwide survey in China. Factors cover several demographic variables while considering the nature of governments to reveal the difference among provinces. The results show that demographic factors such as gender, age, type of residence, education, and census register are positively correlated with food safety satisfaction, while annual income is not significant. Evaluation of government regulation efforts has a positive correlation with food safety satisfaction. People with higher trust in the government show higher satisfaction with the food safety situation. On the province level, per capita GDP, per capita food safety fiscal expenditure, and food safety fiscal expenditure level are positively correlated with food safety satisfaction. The empirical findings are helpful for government regulations; we thereby discuss our analytical results and suggest some governmental policies.
Bio-Based Foamed Cushioning Materials Using Polypropylene and Wheat Bran
Authors: Sohn Joo Seong , Kim Hyun Keun , Cha Sung Woon
Published: March 2019

This study investigated bio-based plastic cushioning materials foamed through water phase-change characteristics using the natural by-product wheat bran. Experiments were carried out while increasing the wheat bran content from 20% to 70% in a blended composite material of polypropylene (PP) and wheat bran (WB). From the experimental results, we were able to prepare a bio-based plastic cushion that contained a high amount of natural materials, with a bran content of over 50%. This indicates the possibility of meeting the criteria for biodegradable plastics, as well as bio-based plastics. In this study, by inducing a foaming ratio of 95% or more, a volume-expansion ratio from 16 times to over 62 times was achieved. In addition, the optimal mixing condition for inducing a high-expansion foam was when the mixing ratio of PP and WB was 50/50, and the water content of the foaming agent was 25 parts per hundred resin. Finally, dynamic cushioning characteristics of PP50/WB50 composite foam prepared in this study and Polystyrene (PS) bead based commercial products were compared. The composite foam of this study showed comparable values, confirming commercialization possibility.
Above-Ground Biomass Models of Caragana korshinskii and Sophora viciifolia in the Loess Plateau, China
Authors: Dou Yanxing , Yang Yang , An Shaoshan
Published: March 2019

The quantification of above-ground biomass is based on the calculation of carbon storage, which is important for the balance of carbon cycling. However, the allometric models of shrubs for calculating the above-ground biomass of shrubs in the Loess Plateau are scarce. In order to solve this issue, this study analyzed some highly correlated variables, including height (H), branch diameters (D), canopy volume (Cv), canopy area (Ca), and then built a regression model to predict the above-ground biomass in two common shrubs (Caragana korshinskii and Sophora viciifolia) in the Loess Plateau, China. The results show that the above-ground biomass of these two shrubs can be accurately predicted by H and D, and then we can use allometric model (y = axb) to calculate shrub above-ground biomass (including leaf biomass and branch biomass). Furthermore, the correlation between leaf biomass and branch biomass in Caragana korshinskii and Sophora viciifolia indicates that the components of above-ground biomass are closely related to each other. In addition, there is a strong linear relationship (p < 0.01) between the observed and estimated biomass values, which confirms the data accuracy of the above-ground biomass estimation models. In summary, these two biomass estimation models provide an accurate way to estimate the quantification of carbon for shrubs in the Loess Plateau.
Translating Sustainability into Action: A Management Challenge in FabLabs
Authors: Galuppo Laura , Kajamaa Anu , Ivaldi Silvia , Scaratti Giuseppe
Published: March 2019

In recent years, the number of new organizations aiming to accomplish principles of sustainability has rapidly grown, leading analysts and scholars to announce almost a new industrial revolution. An example of this is the proliferation of the so-called fabrication laboratories (FabLabs) that nowadays are perceived as being forerunners in innovative and sustainable high-tech production through peer-to-peer collaborative practices and sharing. However, the challenges managers face in translating these promotional aims into organizational action is vastly understudied. To address this research gap, we have studied the management of two FabLabs, in Italy and Finland. In this study, we draw from a psycho-sociological framework applying cultural-historical activity theory, and especially from the concepts of activity system and contradiction. According to this perspective, a sustainable organization is based on promotion, enrichment, regeneration, and flexible change efforts, and it is related to the managerial and ability to bring internal and external stakeholders together to recognize and solve tensions and contradictions collectively. Through our case studies, we have provided new research knowledge on how managers make an effort to translate sustainability into action in the complex context of FabLabs, involving multiple, often competing stakeholders and activity systems. Our analysis reveals multiple tensions in the collective activity, stemming from system level contradictions, which represent a challenge for the daily work of the FabLab managers. In the paper we also suggest how an engaged management orientation towards sustainably can be promoted, and we discuss future research topics.
Additive Effects of Performance- and Commitment-Oriented Human Resource Management Systems on Organizational Outcomes
Authors: Kim KonShik , Shin Tack-Hyun
Published: March 2019

Exploring the duality and balance research on human resource management (HRM), this study established two different HRM systems or bundles based on distinct guiding principles—the performance-oriented HRM system and the commitment-oriented HRM system. This study investigated whether the performance- and commitment-oriented HRM systems or bundles with different philosophical backgrounds have their own independent and additive effects on organizational outcomes. The relationships between these HRM systems and organizational outcomes were examined with 1735 firm-period samples in the longitudinal setting. The empirical results show that the commitment-oriented HRM systems have independent and additive effects on organizational commitment and human capital. However, the performance-oriented HRM systems have no independent and additive effect on organizational outcomes. Our study also indicates that increasing the performance-oriented HRM practices can be redundant and unnecessary unless firms have sufficiently high levels of the commitment-oriented HRM practices. Given that the definition and measures of commitment-oriented HRM bundles nearly match the characteristics of sustainable HRM, we thus argue that the commitment-oriented HRM systems have more potential to improve not only organizational outcomes and performance, but also human and social sustainability, than the performance-oriented HRM systems.
Estimating the Impact of Air Pollution on Inbound Tourism in China: An Analysis Based on Regression Discontinuity Design
Authors: Dong Daxin , Xu Xiaowei , Wong Yat Fung
Published: March 2019

Prior studies have suggested the existence of a reverse causality relationship between air quality and tourism development: while air quality influences tourism, dynamic segments of the tourism industry (e.g., cruising, airline, foodservice) have impacts on air quality. This reverse causality hinders a precise estimate on the effect of air pollution on tourism development within a conventional econometric framework, since the variable of air pollution is endogenous. This study estimates the impact of air pollution on the inbound tourism industry in China, by controlling for endogeneity based on a regression discontinuity design (RDD). The estimate is derived from a quasi-experiment generated by China’s Huai River Policy, which subsidizes coal for winter heating in northern Chinese cities. By analyzing data from 274 Chinese cities during the period 2009–2012, it is found that air pollution significantly reduces the international inbound tourism: an increase of PM 10 (particulate matter smaller than 10 μ m) by 0.1 mg/m 3 will cause a decline in the tourism receipts-to-local gross domestic product (GDP) ratio by 0.45 percentage points. This study also highlights the importance of controlling for endogeneity, since the detrimental impact of air pollution would otherwise be considerably underestimated. This study further demonstrates that, although air pollution is positively correlated with the average expenditure of each tourist, it substantially depresses the number of inbound tourists. The results imply that air quality could potentially influence inbound tourists’ city destination choices. However, it is interesting to note that travelers in air polluted cities in China tend to spend more money.
The Impact of Social Media on Learning Behavior for Sustainable Education: Evidence of Students from Selected Universities in Pakistan
Authors: Abbas Jaffar , Aman Jaffar , Nurunnabi Mohammad , Bano Shaher
Published: March 2019

In today’s world, social media is playing an indispensable role on the learning behavior of university students to achieve sustainable education. The impact of social media on sustainable education is becoming an essential and impelling factor. The world has become a global village and technology use has made it a smaller world through social media and how it is changing instruction. This original study is amongst the few to perform a focalized investigation on revealing the relationship between positive and negative characteristics of social media and the learning attitude of university students for sustainable education. However, this study aims to examine the constructive and adverse factors that impact on students’ minds and how these helped students to share positive and negative aspects with others. It is increasingly noticeable that social networking sites and their applications present enormous benefits for as well as risks to university students and their implications on students’ psychological adjustment or learning behaviors are not well understood. This study adapted the cluster sampling method, and respondents participated from five selected regions. Researchers distributed 1013 questionnaires among the targeted sample of university students with an age range of 16 to 35 years, and they collected 831 complete/valid responses. This study applied the social gratification theory to examine students’ behavior practicing social media usage. This study specifically identified 18 adversarial and constructive factors of social media from the previous literature. The findings revealed that the usage of social media in Pakistan has a negative influence on a student’s behavior as compared to positive aspects. Results may not be generalized to the entire student community as findings are specific to the specific respondents only. This study presents a relationship between antithetical and creative characteristics of social media and exhibits avenues for future studies by facilitating a better understanding of web-based social network use.
Technology Spillover Effect in China: The Spatiotemporal Evolution and Its Drivers
Authors: Liu Chengliang , Guo Qingbin
Published: March 2019

Under the background of global economic integration, the technology spillover effect is playing a more and more important role in the technological progress of developing countries. In this circumstance, this paper conducted an in-depth analysis on the 12-year spatial-temporal evolution of the international technology spillover effect and its driving determinants in China during the period of 2003 to 2014. Analytical results highlighted that: (1) As a whole, the international technology spillover effect in general has shown an upward trend in China, except in 2008 and 2012, which are observed as deep-V plunge variations. The plunge in 2008 was more dramatic. After 2011, the growth rate of international technology spillover effect from international import trade and foreign direct investment (FDI) respects slowed obviously down. (2) The spatial distribution of the international technology spillover effect from FDI in China transferred from the ribbon-like pattern to the flake-like pattern, while the effect from import trade held steady with little difference in regional spatial distribution. (3) From the drivers, human capital, economic development, trade openness, and institutional factors promoted the technological spillover effect of import trade channels positively, and financial development, human capital, economic development, and institutional factors promoted the technological spillover effect of FDI channels positively.
After COP21: Contested Transformations in the Energy/Agri-Food Nexus
Authors: Marsden Terry , Rucinska Karolina
Published: March 2019

To what extent are we witnessing real transformatory change towards a low- or zero-carbon economy following the optimism surrounding the COP21 Paris agreements? Taking the energy/agri-food nexus as a major focus, the paper examines what it regards as highly contested co-evolutionary trends associated both with carbonised and geo-politically motivated ‘lock-in’ on the one hand, but nevertheless, the rise of significant post-carbon strategies and practices on the other. The latter may be significantly encouraged by the rise of what are termed as ‘stranded assets’ and disinvestments in the financial investment sector, and the opportunities for more distributed systems of production in the energy/agri-food nexus. These shifts suggest a more polyvalent set of post-carbonised capitalist and post-capitalist processes which demand a renewed political- ecological approach by scholars in understanding these multiple resources and transformatory processes. Overall, this would suggest that the transformations before us will not assume a ‘business as usual’ model of conventional (and concentrated) capitalist development.