bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of the Fluidity of the Ultrasonic Plasticized Polymer Melt by Spiral Flow Testing under Micro-Scale
Authors: Jiang Bingyan , Zou Yang , Liu Tao , Wu Wangqing
Published: February 2019

The fluidity of a molten polymer plasticized by ultrasonic vibration was characterized by spiral flow testing based on an Archimedes spiral mold with microchannels. Mold inserts with various channel depths from 250 to 750 µm were designed and fabricated to represent the size effect under micro-scale. The effect of ultrasonic plasticizing parameters and the mold temperature on the flow length was studied to determine the rheological nature of polymers and control parameters. The results showed that the flow length decreased with reduced channel depth due to the size effect. By increasing ultrasonic amplitude, ultrasonic action time, plasticizing pressure, and mold temperature, the flow length could be significantly increased for both the amorphous polymer polymethyl methacrylate (PMMA) and the semi-crystalline polymers polypropylene (PP) and polyamide 66 (PA66). The enhanced fluidity of the ultrasonic plasticized polymer melt could be attributed to the significantly reduced shear viscosity.
Study on Soy-Based Adhesives Enhanced by Phenol Formaldehyde Cross-Linker
Authors: Wu Zhigang , Xi Xuedong , Lei Hong , Liang Jiankun , Liao Jingjing , Du Guanben
Published: February 2019

To find the effects of cross-linker phenol-formaldehyde (PF) resin on the performance of soy-based adhesives, the reaction between model compounds hydroxymethyl phenol (HPF) and glutamic acid were studied in this paper. HPF prepared in laboratory conditions showed higher content of hydroxymethyl groups than normal PF resin, which was proved by the results of Electrospray Ionization Mass Spectrometry (ESI-MS) and 13C Nuclear Magnetic Resonance (13C-NMR). The results of ESI-MS, Fourier transform infrared spectroscopy (FT-IR), and 13C-NMR based on resultant products obtained from model compounds showed better water resistance of the soy protein-based adhesive modified by PF-based resin, which indicated the reaction between PF resin and soy protein. However, it seemed that the soy-based adhesive cross-linked by HPF with the maximum content of hydroxymethyl groups did not show the best water resistance.
Contraction of Entangled Polymers After Large Step Shear Deformations in Slip-Link Simulations
Authors: Masubuchi Yuichi
Published: February 2019

Although the tube framework has achieved remarkable success to describe entangled polymer dynamics, the chain motion assumed in tube theories is still a matter of discussion. Recently, Xu et al. [ACS Macro Lett. 2018, 7, 190–195] performed a molecular dynamics simulation for entangled bead-spring chains under a step uniaxial deformation and reported that the relaxation of gyration radii cannot be reproduced by the elaborated single-chain tube model called GLaMM. On the basis of this result, they criticized the tube framework, in which it is assumed that the chain contraction occurs after the deformation before the orientational relaxation. In the present study, as a test of their argument, two different slip-link simulations developed by Doi and Takimoto and by Masubuchi et al. were performed and compared to the results of Xu et al. In spite of the modeling being based on the tube framework, the slip-link simulations excellently reproduced the bead-spring simulation result. Besides, the chain contraction was observed in the simulations as with the tube picture. The obtained results imply that the bead-spring results are within the scope of the tube framework whereas the failure of the GLaMM model is possibly due to the homogeneous assumption along the chain for the fluctuations induced by convective constraint release.
Tablet of Ximenia Americana L. Developed from Mucoadhesive Polymers for Future Use in Oral Treatment of Fungal Infections
Authors: Almeida Lucas , Oshiro Júnior João Augusto , Silva Milena , Nóbrega Fernanda , Andrade Jéssica , Santos Widson , Ribeiro Angélica , Conceição Marta , Veras Germano , Medeiros Ana Cláudia
Published: February 2019

The use of biocompatible polymers such as Hydroxypropylmethylcellulose (HPMC), Hydroxyethylcellulose (HEC), Carboxymethylcellulose (CMC), and Carbopol in solid formulations results in mucoadhesive systems capable of promoting the prolonged and localized release of Active Pharmaceutical Ingredients (APIs). This strategy represents a technological innovation that can be applied to improving the treatment of oral infections, such as oral candidiasis. Therefore, the aim of this study was to develop a tablet of Ximenia americana L. from mucoadhesive polymers for use in the treatment of oral candidiasis. An X. americana extract (MIC of 125 μg·mL−1) was obtained by turbolysis at 50% of ethanol, a level that demonstrated activity against Candida albicans. Differential Thermal Analysis and Fourier Transform Infrared Spectroscopy techniques allowed the choice of HPMC as a mucoadhesive agent, besides polyvinylpyrrolidone, magnesium stearate, and mannitol to integrate the formulation of X. americana. These excipients were granulated with an ethanolic solution 70% v/v at PVP 5%, and a mucoadhesive tablet was obtained by compression. Finally, mucoadhesive strength was evaluated, and the results demonstrated good mucoadhesive forces in mucin disk and pig buccal mucosa. Therefore, the study allowed a new alternative to be developed for the treatment of buccal candidiasis, one which overcomes the inconveniences of common treatments, costs little, and facilitates patients’ adhesion.
3D Shape Analysis of Powder for Laser Beam Melting by Synchrotron X-ray CT
Authors: Thiede Tobias , Mishurova Tatiana , Evsevleev Sergei , Serrano-Munoz Itziar , Gollwitzer Christian , Bruno Giovanni
Published: February 2019

The quality of components made by laser beam melting (LBM) additive manufacturing is naturally influenced by the quality of the powder bed. A packing density <1 and porosity inside the powder particles lead to intrinsic voids in the powder bed. Since the packing density is determined by the particle size and shape distribution, the determination of these properties is of significant interest to assess the printing process. In this work, the size and shape distribution, the amount of the particle’s intrinsic porosity, as well as the packing density of micrometric powder used for LBM, have been investigated by means of synchrotron X-ray computed tomography (CT). Two different powder batches were investigated: Ti–6Al–4V produced by plasma atomization and stainless steel 316L produced by gas atomization. Plasma atomization particles were observed to be more spherical in terms of the mean anisotropy compared to particles produced by gas atomization. The two kinds of particles were comparable in size according to the equivalent diameter. The packing density was lower (i.e., the powder bed contained more voids in between particles) for the Ti–6Al–4V particles. The comparison of the tomographic results with laser diffraction, as another particle size measurement technique, proved to be in agreement.
Error Analysis on Indoor Localization with Visible Light Communication
Authors: Yan Jun , Zhu Bingcheng , Chen Liang , Wang Jin , Liu Jingbin
Published: February 2019

Affected by the complexity of the indoor environment, accurate indoor positioning is challenging in many localization based services (LBS). Recently, it has been recognized that, visible light communication (VLC) is promising for indoor navigation and positioning, due to the low implementation cost with marginal modification to the existing infrastructure and the possibility to achieve high accurate positioning results. Provided that the positions of the light emitting diodes (LEDs) are known to the receiver, the angle of arrival (AOA) of the light signal is able to be estimated by a camera embedded in a smart phone, and thus the position of the smart phone can be derived based on the triangulation. In this paper, the performance of the positioning accuracy is analyzed based on indoor positioning with VLC, and the analytical upper bound of location error is derived. Extensive simulation results have verified the theoretical analysis on the VLC-based localization approach in different indoor scenarios. In order to obtain better location performance, the principles of choosing reference LED and localization LED are also given.
Local Deep Descriptor for Remote Sensing Image Feature Matching
Authors: Dong Yunyun , Jiao Weili , Long Tengfei , Liu Lanfa , He Guojin , Gong Chengjuan , Guo Yantao
Published: February 2019

Feature matching via local descriptors is one of the most fundamental problems in many computer vision tasks, as well as in the remote sensing image processing community. For example, in terms of remote sensing image registration based on the feature, feature matching is a vital process to determine the quality of transform model. While in the process of feature matching, the quality of feature descriptor determines the matching result directly. At present, the most commonly used descriptor is hand-crafted by the designer’s expertise or intuition. However, it is hard to cover all the different cases, especially for remote sensing images with nonlinear grayscale deformation. Recently, deep learning shows explosive growth and improves the performance of tasks in various fields, especially in the computer vision community. Here, we created remote sensing image training patch samples, named Invar-Dataset in a novel and automatic way, then trained a deep learning convolutional neural network, named DescNet to generate a robust feature descriptor for feature matching. A special experiment was carried out to illustrate that our created training dataset was more helpful to train a network to generate a good feature descriptor. A qualitative experiment was then performed to show that feature descriptor vector learned by the DescNet could be used to register remote sensing images with large gray scale difference successfully. A quantitative experiment was then carried out to illustrate that the feature vector generated by the DescNet could acquire more matched points than those generated by hand-crafted feature Scale Invariant Feature Transform (SIFT) descriptor and other networks. On average, the matched points acquired by DescNet was almost twice those acquired by other methods. Finally, we analyzed the advantages of our created training dataset Invar-Dataset and DescNet and gave the possible development of training deep descriptor network.
Relation between Changes in Photosynthetic Rate and Changes in Canopy Level Chlorophyll Fluorescence Generated by Light Excitation of Different Led Colours in Various Background Light
Authors: Ahlman Linnéa , Bånkestad Daniel , Wik Torsten
Published: February 2019

Using light emitting diodes (LEDs) for greenhouse illumination enables the use of automatic control, since both light quality and quantity can be tuned. Potential candidate signals when using biological feedback for light optimisation are steady-state chlorophyll a fluorescence gains at 740 nm, defined as the difference in steady-state fluorescence at 740 nm divided by the difference in incident light quanta caused by (a small) excitation of different LED colours. In this study, experiments were conducted under various background light (quality and quantity) to evaluate if these fluorescence gains change relative to each other. The light regimes investigated were intensities in the range 160–1000 μ mol   m − 2   s − 1 , and a spectral distribution ranging from 50% to 100% red light. No significant changes in the mutual relation of the fluorescence gains for the investigated LED colours (400, 420, 450, 530, 630 and 660 nm), could be observed when the background light quality was changed. However, changes were noticed as function of light quantity. When passing the photosynthesis saturate intensity level, no further changes in the mutual fluorescence gains could be observed.
Comparison of Satellite and UAV-Based Multispectral Imagery for Vineyard Variability Assessment
Authors: Khaliq Aleem , Comba Lorenzo , Biglia Alessandro , Ricauda Aimonino Davide , Chiaberge Marcello , Gay Paolo
Published: February 2019

In agriculture, remotely sensed data play a crucial role in providing valuable information on crop and soil status to perform effective management. Several spectral indices have proven to be valuable tools in describing crop spatial and temporal variability. In this paper, a detailed analysis and comparison of vineyard multispectral imagery, provided by decametric resolution satellite and low altitude Unmanned Aerial Vehicle (UAV) platforms, is presented. The effectiveness of Sentinel-2 imagery and of high-resolution UAV aerial images was evaluated by considering the well-known relation between the Normalised Difference Vegetation Index (NDVI) and crop vigour. After being pre-processed, the data from UAV was compared with the satellite imagery by computing three different NDVI indices to properly analyse the unbundled spectral contribution of the different elements in the vineyard environment considering: (i) the whole cropland surface; (ii) only the vine canopies; and (iii) only the inter-row terrain. The results show that the raw s resolution satellite imagery could not be directly used to reliably describe vineyard variability. Indeed, the contribution of inter-row surfaces to the remotely sensed dataset may affect the NDVI computation, leading to biased crop descriptors. On the contrary, vigour maps computed from the UAV imagery, considering only the pixels representing crop canopies, resulted to be more related to the in-field assessment compared to the satellite imagery. The proposed method may be extended to other crop typologies grown in rows or without intensive layout, where crop canopies do not extend to the whole surface or where the presence of weeds is significant.
Global 15-Meter Mosaic Derived from Simulated True-Color ASTER Imagery
Authors: Gonzalez Louis , Vallet Valérie , Yamamoto Hirokazu
Published: February 2019

This work proposes a new methodology to build an Earth-wide mosaic using high-spatial resolution (15 m) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images in pseudo-true color. As ASTER originally misses a blue visible band, we have designed a cloud of artificial neural networks to estimate the ASTER blue reflectance from Level-1 data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same satellite Terra platform. Next, the granules are radiometrically harmonized with a novel color-balancing method and seamlessly blended into a mosaic. We demonstrate that the proposed algorithms are robust enough to process several thousands of scenes acquired under very different temporal, spatial, and atmospheric conditions. Furthermore, the created mosaic fully preserves the ASTER fine structures across the various building steps. The proposed methodology and protocol are modular so that they can easily be adapted to similar sensors with enormous image libraries.
Modelling Impulse Response Function of Functional Infrared Imaging for General Linear Model Analysis of Autonomic Activity
Authors: Perpetuini David , Cardone Daniela , Filippini Chiara , Chiarelli Antonio Maria , Merla Arcangelo
Published: February 2019

Functional infrared imaging (fIRI) is a validated procedure to infer autonomic arousal. Currently, fIRI signals are analysed through descriptive metrics, such as average temperature changes in a region of interest (ROI). However, the employment of mathematical models could provide a powerful tool for the accurate identification of autonomic activity and investigation of the mechanisms underlying autonomic arousal. A linear temporal statistical model such as the general linear model (GLM) is particularly suited for its simplicity and direct interpretation. In order to apply the GLM, the thermal response linearity and time-invariance of fIRI have to be demonstrated, and the thermal impulse response (TIR) needs to be characterized. In this study, the linearity and time-invariance of the thermal response to sympathetic activating stimulation were demonstrated, and the TIR for employment of the GLM was characterized. The performance of the GLM-fIRI was evaluated by comparison with the GLM applied on synchronous measurements of the skin conductance response (SCR). In fact, the GLM-SCR is a validated procedure to estimate autonomic arousal. Assuming the GLM-SCR as the gold standard approach, a GLM-fIRI sensitivity and specificity of 86.4% and 75.9% were obtained. The GLM-fIRI may allow increased performances in the evaluation of autonomic activity and a broader range of application of fIRI in both research and clinical settings for the assessment of psychophysiological and psychopathological states.
Multi-Pig Part Detection and Association with a Fully-Convolutional Network
Authors: Psota Eric T. , Mittek Mateusz , Pérez Lance C. , Schmidt Ty , Mote Benny
Published: February 2019

Computer vision systems have the potential to provide automated, non-invasive monitoring of livestock animals, however, the lack of public datasets with well-defined targets and evaluation metrics presents a significant challenge for researchers. Consequently, existing solutions often focus on achieving task-specific objectives using relatively small, private datasets. This work introduces a new dataset and method for instance-level detection of multiple pigs in group-housed environments. The method uses a single fully-convolutional neural network to detect the location and orientation of each animal, where both body part locations and pairwise associations are represented in the image space. Accompanying this method is a new dataset containing 2000 annotated images with 24,842 individually annotated pigs from 17 different locations. The proposed method achieves over 99% precision and over 96% recall when detecting pigs in environments previously seen by the network during training. To evaluate the robustness of the trained network, it is also tested on environments and lighting conditions unseen in the training set, where it achieves 91% precision and 67% recall. The dataset is publicly available for download.
An Intelligent Failure Detection on a Wireless Sensor Network for Indoor Climate Conditions
Authors: Gutiérrez Sebastián , Ponce Hiram
Published: February 2019

Wireless sensor networks (WSN) involve large number of sensor nodes distributed at diverse locations. The collected data are prone to be inaccurate and faulty due to internal or external influences, such as, environmental interference or sensor aging. Intelligent failure detection is necessary for the effective functioning of the sensor network. In this paper, we propose a supervised learning method that is named artificial hydrocarbon networks (AHN), to predict temperature in a remote location and detect failures in sensors. It allows predicting the temperature and detecting failure in sensor node of remote locations using information from a web service comparing it with field temperature sensors. For experimentation, we implemented a small WSN to test our sensor in order to measure failure detection, identification and accommodation proposal. In our experiments, 94.18% of the testing data were recovered and accommodated allowing of validation our proposed approach that is based on AHN, which detects, identify and accommodate sensor failures accurately.
A Highlight-Generation Method for Rendering Translucent Objects
Authors: Yu Hui , Liu Peter X. , Hu Lingyan
Published: February 2019

The acquisition of translucent objects has become a very common task thanks to the progress of 3D scanning technology. Since the characteristic soft appearance of translucent objects is due to subsurface scattering, the details are naturally left out in this appearance. For objects that have complex shapes, this lack of detail is obviously more prominent. In this paper, we propose a method to preserve the details of surface geometry by adding highlight effects. In generating highlight effects, our method employs a local orthonormal frame and combines, in a novel way, the incoming and outgoing light in approximating the subsurface scattering process. When the incident illuminant direction changes from nearly overhead to nearly horizontal, our method effectively preserves complex surface geometry details in the appearance of translucent materials. Through experiments, we show that our method can store surface features as well as maintain the translucency of the original materials and even enhance the perception of translucency. By numerically comparing the generated highlight effects with those generated by the traditional Bidirectional Reflectance Distribution Function (BRDF) models with different bandwidth parameters, we demonstrate the validity of our proposed method.
A Short Review on the Role of the Metal-Graphene Hybrid Nanostructure in Promoting the Localized Surface Plasmon Resonance Sensor Performance
Authors: Alharbi Raed , Irannejad Mehrdad , Yavuz Mustafa
Published: February 2019

Localized Surface Plasmon Resonance (LSPR) sensors have potential applications in essential and important areas such as bio-sensor technology, especially in medical applications and gas sensors in environmental monitoring applications. Figure of Merit (FOM) and Sensitivity (S) measurements are two ways to assess the performance of an LSPR sensor. However, LSPR sensors suffer low FOM compared to the conventional Surface Plasmon Resonance (SPR) sensor due to high losses resulting from radiative damping of LSPs waves. Different methodologies have been utilized to enhance the performance of LSPR sensors, including various geometrical and material parameters, plasmonic wave coupling from different structures, and integration of noble metals with graphene, which is the focus of this report. Recent studies of metal-graphene hybrid plasmonic systems have shown its capability of promoting the performance of the LSPR sensor to a level that enhances its chance for commercialization. In this review, fundamental physics, the operation principle, and performance assessment of the LSPR sensor are presented followed by a discussion of plasmonic materials and a summary of methods used to optimize the sensor’s performance. A focused review on metal-graphene hybrid nanostructure and a discussion of its role in promoting the performance of the LSPR sensor follow.
Laterally Movable Triple Electrodes Actuator toward Low Voltage and Fast Response RF-MEMS Switches
Authors: Naito Yasuyuki , Nakamura Kunihiko , Uenishi Keisuke
Published: February 2019

A novel actuator toward a low voltage actuation and fast response in RF-MEMS (radio frequency micro-electro-mechanical systems) switches is reported in this paper. The switch is comprised of laterally movable triple electrodes, which are bistable by electrostatic forces applied for not only the on-state, but also the off-state. The bistable triple electrodes enable the implementation of capacitive series and shunt type switches on a single switch, which leads to high isolation in spite of the small gap between the electrodes on the series switch. These features of the actuator are effective for a low voltage and fast response actuation in both the on- and off-state. The structure was designed in RF from a mechanical point of view. The laterally movable electrodes were achieved using a simple, low-cost two-mask process with 2.0 µm thick sputtered aluminum. The characteristics of switching response time and actuation voltage were 5.0 µs and 9.0 V, respectively.
A Semantic-Enabled Platform for Realizing an Interoperable Web of Things
Authors: Lanza Jorge , Sánchez Luis , Gómez David , Santana Juan Ramón , Sotres Pablo
Published: February 2019

Nowadays, the Internet of Things (IoT) ecosystem is experiencing a lack of interoperability across the multiple competing platforms that are available. Consequently, service providers can only access vertical data silos that imply high costs and jeopardize their solutions market potential. It is necessary to transform the current situation with competing non-interoperable IoT platforms into a common ecosystem enabling the emergence of cross-platform, cross-standard, and cross-domain IoT services and applications. This paper presents a platform that has been implemented for realizing this vision. It leverages semantic web technologies to address the two key challenges in expanding the IoT beyond product silos into web-scale open ecosystems: data interoperability and resources identification and discovery. The paper provides extensive description of the proposed solution and its implementation details. Regarding the implementation details, it is important to highlight that the platform described in this paper is currently supporting the federation of eleven IoT deployments (from heterogeneous application domains) with over 10,000 IoT devices overall which produce hundreds of thousands of observations per day.
Compensation for Process and Temperature Dependency in a CMOS Image Sensor
Authors: Xie Shuang , Theuwissen Albert
Published: February 2019

This paper analyzes and compensates for process and temperature dependency among a (Complementary Metal Oxide Semiconductor) CMOS image sensor (CIS) array. Both the analysis and compensation are supported with experimental results on the CIS’s dark current, dark signal non-uniformity (DSNU), and conversion gain (CG). To model and to compensate for process variations, process sensors based on pixel source follower (SF)’s transconductance gm,SF have been proposed to model and to be compared against the measurement results of SF gain ASF. In addition, ASF’s thermal dependency has been analyzed in detail. To provide thermal information required for temperature compensation, six scattered bipolar junction transistor (BJT)-based temperature sensors replace six image pixels inside the array. They are measured to have an untrimmed inaccuracy within ±0.5 °C. Dark signal and CG’s thermal dependencies are compensated using the on-chip temperature sensors by at least 79% and 87%, respectively.
Parallel Connected Generative Adversarial Network with Quadratic Operation for SAR Image Generation and Application for Classification
Authors: He Chu , Xiong Dehui , Zhang Qingyi , Liao Mingsheng
Published: February 2019

Thanks to the availability of large-scale data, deep Convolutional Neural Networks (CNNs) have witnessed success in various applications of computer vision. However, the performance of CNNs on Synthetic Aperture Radar (SAR) image classification is unsatisfactory due to the lack of well-labeled SAR data, as well as the differences in imaging mechanisms between SAR images and optical images. Therefore, this paper addresses the problem of SAR image classification by employing the Generative Adversarial Network (GAN) to produce more labeled SAR data. We propose special GANs for generating SAR images to be used in the training process. First, we incorporate the quadratic operation into the GAN, extending the convolution to make the discriminator better represent the SAR data; second, the statistical characteristics of SAR images are integrated into the GAN to make its value function more reasonable; finally, two types of parallel connected GANs are designed, one of which we call PWGAN, combining the Deep Convolutional GAN (DCGAN) and Wasserstein GAN with Gradient Penalty (WGAN-GP) together in the structure, and the other, which we call CNN-PGAN, applying a pre-trained CNN as a discriminator to the parallel GAN. Both PWGAN and CNN-PGAN consist of a number of discriminators and generators according to the number of target categories. Experimental results on the TerraSAR-X single polarization dataset demonstrate the effectiveness of the proposed method.
Flexural Capacity and Deflection of Fiber-Reinforced Lightweight Aggregate Concrete Beams Reinforced with GFRP Bars
Authors: Liu Xi , Sun Yijia , Wu Tao
Published: February 2019

Adding fibers is highly effective to enhance the deflection and ductility of fiber-reinforced polymer (FRP)-reinforced beams. In this study, the stress and strain conditions of FRP-reinforced lightweight aggregate concrete (LWC) beams with and without fibers at ultimate load level were specified. Based on the sectional analyses, alternative equations to predict the balanced reinforcement ratio and flexural capacity for beams failed by balanced failure and concrete crushing were established. A rational equation for estimating the short-term stiffness of FRP–LWC beams at service-load levels was suggested based on Zhu’s model. In addition, the contribution of the steel fibers on the short-term stiffness was quantified incorporating the effects of FRP reinforcement ratio. The proposed short-term stiffness model was validated with measured deflections from an experimental database for fiber-reinforced normal weight concrete (FNWC) beams reinforced with FRP bars. Furthermore, six glass fiber-reinforced polymer (GFRP)-reinforced LWC beams with and without steel fibers were tested under four-point bending. Based on the test results, the proposed models and procedures according to current design codes ACI 440.1R, ISIS-M03, GB 50608, and CSA S806 were linked together by comparing their predictions. The results showed that increasing the reinforcement ratio and adding steel fibers decreased the strain of the FRP bars. The flexural capacity of the LWC beams with and without steel fibers was generally underestimated by the design codes, while the proposed model provided accurate ultimate moment predictions. Moreover, the proposed short-term stiffness model yielded reasonable estimations of deflection for both steel fiber-reinforced lightweight aggregate concrete (SFLWC) and FNWC beams.
A Novel Passive Indoor Localization Method by Fusion CSI Amplitude and Phase Information
Authors: Dang Xiaochao , Si Xiong , Hao Zhanjun , Huang Yaning
Published: February 2019

With the rapid development of wireless network technology, wireless passive indoor localization has become an increasingly important technique that is widely used in indoor location-based services. Channel state information (CSI) can provide more detailed and specific subcarrier information, which has gained the attention of researchers and has become an emphasis in indoor localization technology. However, existing research has generally adopted amplitude information for eigenvalue calculations. There are few research studies that have used phase information from CSI signals for localization purposes. To eliminate the signal interference existing in indoor environments, we present a passive human indoor localization method named FapFi, which fuses CSI amplitude and phase information to fully utilize richer signal characteristics to find location. In the offline stage, we filter out redundant values and outliers in the CSI amplitude information and then process the CSI phase information. A fusion method is utilized to store the processed amplitude and phase information as a fingerprint database. The experimental data from two typical laboratory and conference room environments were gathered and analyzed. The extensive experimental results demonstrate that the proposed algorithm is more efficient than other algorithms in data processing and achieves decimeter-level localization accuracy.
Automated Chemical Sensing Unit Integration for Parallel Optical Interrogation
Authors: Hernandez Ana L , Dortu Fabian , Veenstra Theo , Ciaurriz Paula , Casquel Rafael , Cornago Iñaki , Horsten Hendrik V , Tellechea Edurne , Maigler María V , Fernández Fátima , Holgado Miguel
Published: February 2019

We report the integration of an automated chemical optical sensing unit for the parallel interrogation of 12 BICELLs in a sensing chip. The work was accomplished under the European Project Enviguard (FP7-OCEAN-2013-614057) with the aim of demonstrating an optical nano-biosensing unit for the in-situ detection of various chemical pollutants simultaneously in oceanic waters. In this context, we designed an optical sensing chip based on resonant nanopillars (R-NPs) transducers organized in a layout of twelve biophotonic sensing cells (BICELLs). The sensing chip is interrogated in reflection with a 12-channels optical spectrometer equipped with an embedded computer-on-chip performing image processing for the simultaneous acquisition and analysis (resonant mode fitting) of the 12 spectra. A microfluidic chip and an automated flow control system composed of four pumps and a multi-path micro-valve makes it possible to drive different complex protocols. A rack was designed ad-hoc for the integration of all the modules. As a proof of concept, fluids of different refractive index (RI) were flowed in the system in order to measure the time response (sensogram) of the R-NPs under optical reflectance, and assess the sensors’ bulk sensitivity (285.9 ± 16.4 nm/RIU) and Limit of Detection (LoD) (2.95 × 10−6 RIUS). The real-time response under continuous flow of a sensor chip based on R-NP is showed for the first time, obtaining 12 sensograms simultaneously, featuring the unit as a potential excellent multiplexed detection system. These results indicate the high potential of the developed chemical sensing unit to be used for in-situ, multiplex and automatic optical biosensing.
Orthogonal Chirp Coded Excitation in a Capacitive Micro-machined Ultrasonic Transducer Array for Ultrasound Imaging: A Feasibility Study
Authors: Kim Bae-Hyung , Lee Seungheun , Kim Kang-Sik
Published: February 2019

It has been reported that the frequency bandwidth of capacitive micro-machined ultrasonic transducers (CMUTs) is relatively broader than that of other ceramic-based conventional ultrasonic transducers. In this paper, a feasibility study for orthogonal chirp coded excitation to efficiently make use of the wide bandwidth characteristic of CMUT array is presented. The experimental result shows that the two orthogonal chirps mixed and simultaneously fired in CMUT array can be perfectly separated in decoding process of the received echo signal without sacrificing the frequency bandwidth each chirp. The experimental study also shows that frequency band-divided orthogonal chirps are successfully compressed to two short pulses having the −6 dB axial beam-width of 0.26- and 0.31-micro second for high frequency and low frequency chirp, respectively. B-mode image simulations are performed using Field II to estimate the improvement of image quality assuming that the orthogonal chirps designed for the experiments are used for simultaneous transmission multiple-zone focusing (STMF) technique. The simulation results show that the STMF technique used in CMUT array can improve the lateral resolution up to 77.1% and the contrast resolution up to 74.7%, respectively. It is shown that the penetration depth also increases by more than 3 cm.
Virtual Touch Sensor Using a Depth Camera
Authors: Lee Dong-seok , Kwon Soon-kak
Published: February 2019

In this paper, a virtual touch sensor using a depth camera is proposed. Touch regions are detected by finding each region that consists of pixels within a certain distance from a touch surface. Touch points are detected by finding a pixel in each touch region whose neighboring pixels are closest to surfaces. A touch path error due to noise in the depth picture is corrected through a filter that introduces a weight parameter in order to respond quickly even with sudden changes. The virtual touch sensor is implemented by using the proposed methods for the touch point detection and the touch path correction. In the virtual touch sensor, a touch surface and pixels of a depth picture can be regarded as a virtual touch panel and virtual touch units, respectively. The virtual touch sensor can be applied to wide fields of touch interfaces. Results of simulations show the implementation of the touch-pen interface using the virtual touch sensor.
A New Model and Its Application for the Dynamic Response of RGO Resistive Gas Sensor
Authors: Du Hongfei , Xie Guangzhong , Su Yuanjie , Tai Huiling , Du Xiaosong , Yu He , Zhang Qiuping
Published: February 2019

An reduced graphene oxide (RGO) resistive gas sensor was prepared to detect ammonia at room temperature, the result indicated that the desorption of gas (NH 3 ) molecules from a graphene-based sensor was difficult, which lead to a baseline drift. The responses of different concentrations were compared and studied. It was found that both the response rate and its acceleration were affected by the gas concentration. An Intermolecular Forces Based Model was established to explain the adsorption and desorption dynamic response curves. A new method was proposed based on this model. The first and second derivative extrema (FSDE) of the response curve can be attained quickly to calibrate the gas concentrations. The experiment results demonstrated that this new method could eliminate the baseline drift and was capable of increasing the efficiency of gas calibration significantly.
Farmers’ Bargaining Power and Input Prices: What Can We Learn from Self-Reported Assessments?1
Authors: Malak-Rawlikowska Agata , Milczarek-Andrzejewska Dominika , Fałkowski Jan
Published: February 2019

One of the key challenges in improving our understanding of farmers’ relations with input suppliers is that we do not have direct information about farmers’ bargaining power vis-à-vis their input providers. To overcome this problem, this study used farmers’ self-reported assessments of their position in the supply chain. Using unique micro-survey data from the dairy sector in Poland, we constructed a proxy of farmers’ bargaining power and showed that it helps to explain discounts at which farmers buy feed from input suppliers, in addition to what is explained by the standard variables.
Supporting Children, Blaming Parents: Frontline Providers’ Perception of Childhood’s Adversity and Parenthood in Indonesia
Authors: Siagian Clara , Arifiani Sandra , Amanda Putri , Kusumaningrum Santi
Published: February 2019

This article explores the construction of childhood and parenthood in rural communities in Indonesia based on a series of focus group discussions with service providers, community decision makers, and paraprofessionals; a group that we refer to as “frontline providers”. By examining the providers’ definition of successful children and their perception of factors that could undermine a child’s success, we provide insights into how frontline providers understand the role of parents, and how parenthood is constructed accordingly. We found that the providers’ definition of successful children reflects a strong neoliberal logic and that education is seen as the primary mechanism of such investment, an evolution of the idea of a modern nation under the previous regime that has permeated into an individual assessment. The paternalistic culture has further cemented the tendency among the frontline providers to problematize parents as the main risk factor for children’s educational achievement and to ignore the structural and ecological factors. We traced this paradigm in Indonesia’s educational and child protection policy framework, prompting a myriad of parenting programs that put parents from the underprivileged group as the main subject of intervention. Informed by studies in different countries, we argue that without changes in structural factors, any intervention on parenting will be deemed ineffective.
Land Use/Cover Change Effects on River Basin Hydrological Processes Based on a Modified Soil and Water Assessment Tool: A Case Study of the Heihe River Basin in Northwest China’s Arid Region
Authors: Jin Xin , Jin Yanxiang , Mao Xufeng
Published: February 2019

Land use/cover change (LUCC) affects canopy interception, soil infiltration, land-surface evapotranspiration (ET), and other hydrological parameters during rainfall, which in turn affects the hydrological regimes and runoff mechanisms of river basins. Physically based distributed (or semi-distributed) models play an important role in interpreting and predicting the effects of LUCC on the hydrological processes of river basins. However, conventional distributed (or semi-distributed) models, such as the soil and water assessment tool (SWAT), generally assume that no LUCC takes place during the simulation period to simplify the computation process. When applying the SWAT, the subject river basin is subdivided into multiple hydrologic response units (HRUs) based on the land use/cover type, soil type, and surface slope. The land use/cover type is assumed to remain constant throughout the simulation period, which limits the ability to interpret and predict the effects of LUCC on hydrological processes in the subject river basin. To overcome this limitation, a modified SWAT (LU-SWAT) was developed that incorporates annual land use/cover data to simulate LUCC effects on hydrological processes under different climatic conditions. To validate this approach, this modified model and two other models (one model based on the 2000 land use map, called SWAT 1; one model based on the 2009 land use map, called SWAT 2) were applied to the middle reaches of the Heihe River in northwest China; this region is most affected by human activity. Study results indicated that from 1990 to 2009, farmland, forest, and urban areas all showed increasing trends, while grassland and bare land areas showed decreasing trends. Primary land use changes in the study area were from grassland to farmland and from bare land to forest. During this same period, surface runoff, groundwater runoff, and total water yield showed decreasing trends, while lateral flow and ET volume showed increasing trends under dry, wet, and normal conditions. Changes in the various hydrological parameters were most evident under dry and normal climatic conditions. Based on the existing research of the middle reaches of the Heihe River, and a comparison of the other two models from this study, the modified LU-SWAT developed in this study outperformed the conventional SWAT when predicting the effects of LUCC on the hydrological processes of river basins.
Sustainable and De-Stressed International Supply-Chains Through the SYNCHRO-NET Approach
Authors: Giusti Riccardo , Iorfida Chiara , Li Yuanyuan , Manerba Daniele , Musso Stefano , Perboli Guido , Tadei Roberto , Yuan Shuai
Published: February 2019

Synchro-modal supply chain eco-NET (SYNCHRO-NET) is a Horizon 2020 European research project aimed at overcoming the stress due to the increasing transportation distances, the higher complexity, and the vulnerability of international supply chains. In order to foster sustainability, quality, and reliability of such supply chains, SYNCHRO-NET mainly exploits the impact and the possible benefits coming from slow/smart-steaming and synchro-modality transportation strategies, and the related business models. The aim of this paper is to summarize and disseminate the main developments and scientific contributions coming from the project. In particular, the working core of the SYNCHRO-NET solution is an integrated and cloud-based eco-system of optimization and simulation software modules that supports stakeholders’ decisions in freight transportation and logistics management at strategic, operational, and real-time levels. The platform has achieved a high grade of automation in several processes to overcome all the issues related to human-based operations. The efficiency and effectiveness of the overall platform have been tested on three case studies considering pan-European and regional trade lanes, as well as commercial activities between the Far East and European ports. The project results and outputs also allow us to analyze barriers and opportunities of the approach, industrial and academic developments, and relations with emerging technologies.
Utilities: Innovation and Sustainability
Authors: Loredo Enrique , Lopez-Mielgo Nuria , Pineiro-Villaverde Gustavo , García-Álvarez María Teresa
Published: February 2019

Pro-market reforms have disrupted the playing field and strongly affected the innovative behavior of electricity, gas and water utilities. Beyond a significant reduction in sectoral R&D investments, very little is known about how these firms accomplish their innovation strategies in this new scenario. Given this gap in the literature, the first aim of this paper is to identify the internal determinants of both the product and process innovation of utilities in a liberalized environment. Additionally, there is another external force that is also disrupting the specific landscape of utilities: the sustainability challenge. Therefore, the second aim of this paper is establishing whether sustainability-orientation is a driver of innovation in the utilities industries. The empirical study is carried out on a panel of 82 Spanish electricity, gas and water utilities over the period 2005–2012 (Technological Innovation Panel dataset (PITEC)). The main findings are: (i) the acquisition of disembodied knowledge does not play a relevant role for utilities; (ii) non-formal search processes are central to product innovation; (iii) some markets for technology –external R&D and technology embedded in equipment—are determinant factors for process innovation; (iv) sustainability orientation increases the likelihood of generating both, product and process innovations. These firm-level results are novel contributions to the field of utility management.
Social Entrepreneurship as a Path for Social Change and Driver of Sustainable Development: A Systematic Review and Research Agenda
Authors: Bansal Sanchita , Garg Isha , Sharma Gagan Deep
Published: February 2019

Social entrepreneurship has been recognized as a tool to attain sustainable development. This paper highlights the role of social entrepreneurship in triggering social change and attaining sustainable development. The paper contributes significantly to the existing literature by conducting a systematic review of extant works. To this end, we analyzed and reviewed 173 research papers from the Web of Science database. The results are presented in the form of descriptive findings and thematic discussion. The paper concludes by setting up the agenda for future researchers in the field.
Applicability of Transaction Cost Economics to Understanding Organizational Structures in Solidarity-Based Food Systems in Germany
Authors: Carlson Laura A. , Bitsch Vera
Published: February 2019

In response to consumer concerns about sustainability of food production and distribution systems, and the difficulties many agricultural producers face to self-sustain while providing the quality of products consumers desire, alternatives to market-based exchange are developing. Solidarity-based food systems (SFS) based on relationships of mutual trust, dependency and support between consumers and producers are an example. SFS are designed to insulate producers from market pressures and alleviate consumers’ mistrust in market-based mechanisms. A network of SFS has formed in Germany under the name Solidarische Landwirtschaft (Solawi). Theories based on economic principles that help explain the way alternatives to market-based transactions in agriculture are organized are still lacking. The article suggests Transaction Cost Economics (TCE) as helpful to gain a better understanding of how these organizations form and function. The governance structures Solawis create are considered hybrid organizations according to TCE. Qualitative research methods are used to generate detailed accounts of the governance structures of four Solawis and the reasons behind the decisions of individual actors to participate. Effectiveness of TCE in evaluating these structures is analyzed. Based on the results, the concept of transaction benefits is suggested as a potential augmentation of TCE to improve its applicability to SFS.