bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential Treatment of Retinal Diseases with Iron Chelators
Authors: Shu Wanting , Dunaief Joshua L.
Published: October 2018

Iron is essential for life, while excess iron can be toxic. Iron generates hydroxyl radical, which is the most reactive free radical, causing oxidative stress. Since iron is absorbed through the diet but not excreted from the body, it accumulates with age in tissues, including the retina, consequently leading to age-related toxicity. This accumulation is further promoted by inflammation. Hereditary diseases such as aceruloplasminemia, Friedreich’s ataxia, pantothenate kinase-associated neurodegeneration, and posterior column ataxia with retinitis pigmentosa involve retinal degeneration associated with iron dysregulation. In addition to hereditary causes, dietary or parenteral iron supplementation has been recently reported to elevate iron levels in the retinal pigment epithelium (RPE) and promote retinal degeneration. Ocular siderosis from intraocular foreign bodies or subretinal hemorrhage can also lead to retinopathy. Evidence from mice and humans suggests that iron toxicity may contribute to age-related macular degeneration pathogenesis. Iron chelators can protect photoreceptors and RPE in various mouse models. The therapeutic potential for iron chelators is under investigation.
Grafting Halloysite Nanotubes with Amino or Carboxyl Groups onto Carbon Fiber Surface for Excellent Interfacial Properties of Silicone Resin Composites
Authors: Zhang Xiandong , Wu Guangshun
Published: October 2018

The quality of interphase in carbon fibers (CFs) composites makes a key contribution to overall performance of composites. Here, we achieved for the first time the chemical grafting of halloysite nanotubes (HNTs) with amino or carboxyl groups onto the CFs surface aiming to increase composites interfacial strength. HNTs were grafted using 3-aminopropyltriethoxysilane (APS) followed by succinic anhydride treatment, and HNTs with amino groups (HNT–NH2) or carboxyl groups (HNT–COOH) were separately introduced into the interphase of composites. Functional groups of HNTs and fiber surface structures were characterized, which confirmed the modification success. The wettability between the modified CFs and resin have been enhanced obviously based on the improved fiber polarity and enhanced surface roughness by the introduced two functionalized HNTs with the uniform distributions onto fiber surface. Moreover, interfacial properties and anti-hydrothermal aging behaviors of modified methylphenylsilicone resin (MPSR) composites were improved significantly, especially for HNT–COOH grafting. In addition, the interfacial reinforcement mechanisms for untreated and modified CF composites are discussed and compared.
Preparation and Characterization of Potato Starch Film with Various Size of Nano-SiO2
Authors: Zhang Rongfei , Wang Xiangyou , Cheng Meng
Published: October 2018

The various sizes (15, 30, 80, and 100 nm) of nano-SiO2/potato starch films were synthesized and characterized. The gas permeability, antibacterial properties, and mechanical properties of the films were evaluated to their potential for application as food packaging materials. Results indicated that the 100 nm nano-SiO2 was well dispersed in the starch matrix, which induced an active group on the surface of 100 nm nano-SiO2 adequately combined with starch macromolecule. The water resistance and mechanical properties of the films were improved with the addition of nano-SiO2. Notably, resistance to ultraviolet and thermal aging was also enhanced. The nano-SiO2/potato starch films were more efficient against Escherichia coli (E. coli) than Staphylococcus aureus (S. aureus). Remarkable preservation properties of the films packaging the white mushrooms were obtained, with those of the 100 nm films considered superior. This study can significantly guide the rational choice of the nano-SiO2 size to meet the packaging requirements of various agricultural products.
Reversible Assembly of Terpyridine Incorporated Norbornene-Based Polymer via a Ring-Opening Metathesis Polymerization and Its Self-Healing Property
Authors: Lee Jookyeong , Moon Hwi Hyun , Paeng Keewook , Song Changsik
Published: October 2018

We induced a terpyridine moiety into a norbornene-based polymer to demonstrate its self-healing property, without an external stimulus, such as light, heat, or healing agent, using metal–ligand interactions. We synthesized terpyridine incorporated norbornene-based polymers using a ring-opening metathesis polymerization. The sol state of diluted polymer solutions was converted into supramolecular assembled gels, through the addition of transition metal ions (Ni2+, Co2+, Fe2+, and Zn2+). In particular, a supramolecular complex gel with Zn2+, which is a metal with a lower binding affinity, demonstrated fast self-healing properties, without any additional external stimuli, and its mechanical properties were completely recovered.
Simultaneous Enhancement of Strength and Toughness of PLA Induced by Miscibility Variation with PVA
Authors: Liu Yanping , Wei Hanghang , Wang Zhen , Li Qian , Tian Nan
Published: October 2018

The mechanical properties of poly (lactic acid) (PLA) nanofibers with 0%, 5%, 10%, and 20% (w/w) poly (vinyl alcohol) (PVA) were investigated at the macro- and microscale. The macro-mechanical properties for the fiber membrane revealed that both the modulus and fracture strain could be improved by 100% and 70%, respectively, with a PVA content of 5%. The variation in modulus and fracture strain versus the diameter of a single electrospun fiber presented two opposite trends, while simultaneous enhancement was observed when the content of PVA was 5% and 10%. With a diameter of 1 μm, the strength and toughness of the L95V5 and L90V10 fibers were enhanced to over 3 and 2 times that of pure PLA, respectively. The structural evolution of electrospun nanofiber was analyzed by differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy (FTIR). Although PLA and PVA were still miscible in the concentration range used, the latter could crystallize independently after electrospinning. According to the crystallization behavior of the nanofibers, a double network formed by PLA and PVA—one microcrystal/ordered structure and one amorphous structure—is proposed to contribute to the simultaneous enhancement of strength and toughness, which provides a promising method for preparing biodegradable material with high performance.
Evaluation of the Kou-Modified Lee-Carter Model in Mortality Forecasting: Evidence from French Male Mortality Data
Authors: Alijean Marie Angèle Cathleen , Narsoo Jason
Published: October 2018

Mortality forecasting has always been a target of study by academics and practitioners. Since the introduction and rising significance of securitization of risk in mortality and longevity, more in-depth studies regarding mortality have been carried out to enable the fair pricing of such derivatives. In this article, a comparative analysis is performed on the mortality forecasting accuracy of four mortality models. The methodology employs the Age-Period-Cohort model, the Cairns-Blake-Dowd model, the classical Lee-Carter model and the Kou-Modified Lee-Carter model. The Kou-Modified Lee-Carter model combines the classical Lee-Carter with the Double Exponential Jump Diffusion model. This paper is the first study to employ the Kou model to forecast French mortality data. The dataset comprises death data of French males from age 0 to age 90, available for the years 1900–2015. The paper differentiates between two periods: the 1900–1960 period where extreme mortality events occurred for French males and the 1961–2015 period where no significant jump is observed. The Kou-modified Lee-Carter model turns out to give the best mortality forecasts based on the RMSE, MAE, MPE and MAPE metrics for the period 1900–1960 during which the two World Wars occurred. This confirms that the consideration of jumps and leptokurtic features conveys important information for mortality forecasting.
Modelling the Vertical Distribution of Phytoplankton Biomass in the Mediterranean Sea from Satellite Data: A Neural Network Approach
Authors: Sammartino Michela , Marullo Salvatore , Santoleri Rosalia , Scardi Michele
Published: October 2018

Knowledge of the vertical structure of the bio-chemical properties of the ocean is crucial for the estimation of primary production, phytoplankton distribution, and biological modelling. The vertical profiles of chlorophyll-a (Chla) are available via in situ measurements that are usually quite rare and not uniformly distributed in space and time. Therefore, obtaining estimates of the vertical profile of the Chla field from surface observations is a new challenge. In this study, we employed an Artificial Neural Network (ANN) to reconstruct the 3-Dimensional (3D) Chla field in the Mediterranean Sea from surface satellite estimates. This technique is able to reproduce the highly nonlinear nature of the relationship between different input variables. A large in situ dataset of temperature and Chla calibrated fluorescence profiles, covering almost all Mediterranean Sea seasonal conditions, was used for the training and test of the network. To separate sources of errors due to surface Chla and temperature satellite estimates, from errors due to the ANN itself, the method was first applied using in situ surface data and then using satellite data. In both cases, the validation against in situ observations shows comparable statistical results with respect to the training, highlighting the feasibility of applying an ANN to infer the vertical Chla field from surface in situ and satellite estimates. We also analyzed the usefulness of our approach to resolve the Chla prediction at small temporal scales (e.g., day) by comparing it with the most widely used Mediterranean climatology (MEDATLAS). The results demonstrated that, generally, our method is able to reproduce the most reliable profile of Chla from synoptical satellite observations, thus resolving finer spatial and temporal scales with respect to climatology, which can be crucial for several marine applications. We demonstrated that our 3D reconstructed Chla field could represent a valid alternative to overcome the absence or discontinuity of in situ sampling.
The Global Mangrove Watch—A New 2010 Global Baseline of Mangrove Extent
Authors: Bunting Pete , Rosenqvist Ake , Lucas Richard M. , Rebelo Lisa-Maria , Hilarides Lammert , Thomas Nathan , Hardy Andy , Itoh Takuya , Shimada Masanobu , Finlayson C. Max
Published: October 2018

This study presents a new global baseline of mangrove extent for 2010 and has been released as the first output of the Global Mangrove Watch (GMW) initiative. This is the first study to apply a globally consistent and automated method for mapping mangroves, identifying a global extent of 137,600 km 2 . The overall accuracy for mangrove extent was 94.0% with a 99% likelihood that the true value is between 93.6–94.5%, using 53,878 accuracy points across 20 sites distributed globally. Using the geographic regions of the Ramsar Convention on Wetlands, Asia has the highest proportion of mangroves with 38.7% of the global total, while Latin America and the Caribbean have 20.3%, Africa has 20.0%, Oceania has 11.9%, North America has 8.4% and the European Overseas Territories have 0.7%. The methodology developed is primarily based on the classification of ALOS PALSAR and Landsat sensor data, where a habitat mask was first generated, within which the classification of mangrove was undertaken using the Extremely Randomized Trees classifier. This new globally consistent baseline will also form the basis of a mangrove monitoring system using JAXA JERS-1 SAR, ALOS PALSAR and ALOS-2 PALSAR-2 radar data to assess mangrove change from 1996 to the present. However, when using the product, users should note that a minimum mapping unit of 1 ha is recommended and that the error increases in regions of disturbance and where narrow strips or smaller fragmented areas of mangroves are present. Artefacts due to cloud cover and the Landsat-7 SLC-off error are also present in some areas, particularly regions of West Africa due to the lack of Landsat-5 data and persistence cloud cover. In the future, consideration will be given to the production of a new global baseline based on 10 m Sentinel-2 composites.
Simultaneous Detection of Ammonium and Nitrate in Environmental Samples Using on Ion-Selective Electrode and Comparison with Portable Colorimetric Assays
Authors: Choosang Jittima , Numnuam Apon , Thavarungkul Panote , Kanatharana Proespichaya , Radu Tanja , Ullah Sami , Radu Aleksandar
Published: October 2018

Simple, robust, and low-cost nitrate- and ammonium-selective electrodes were made using substrate prepared from household materials. We explored phosphonium-based ILs and poly (methyl methacrylate)/poly(decyl methacrylate)(MMA-DMA) copolymer as matrix materials alternative to classical PVC-based membranes. IL-based membranes showed suitability only for nitrate-selective electrode exhibiting linear concentration range between 5.0 × 10−6 and 2.5 × 10−3 M with a detection limit of 5.5 × 10−7 M. On the other hand, MMA-DMA—based membranes showed suitability for both ammonium- and nitrate-selective electrodes, and were successfully applied to detect NO3− and NH4+ in water and soil samples. The proposed ISEs exhibited near-Nernstian potentiometric responses to NO3− and NH4+ with the linear range concentration between 5.0 × 10−5 and 5.0 × 10−2 M (LOD = 11.3 µM) and 5.0 × 10−6 and 1.0 × 10−3 M (LOD = 1.2 µM), respectively. The power of ISEs to detect NO3− and NH4+ in water and soils was tested by comparison with traditional, portable colorimetric techniques. Procedures required for analysis by each technique from the perspective of a non-trained person (e.g., farmer) and the convenience of the use on the field are compared and contrasted.
A Joining Procedure and Synchronization for TSCH-RPL Wireless Sensor Networks
Authors: Vera-Pérez Jose , Todolí-Ferrandis David , Santonja-Climent Salvador , Silvestre-Blanes Javier , Sempere-Payá Víctor
Published: October 2018

Wireless Sensor Networks have become a key enabler for Industrial Internet of Things (IoT) applications; however, to adapt to the derived robust communication requirements, deterministic and scheduled medium access should be used, along with other features, such as channel hopping and frequency diversity. Implementing these mechanisms requires a correct synchronization of all devices in the network, a stage in deployment that can lead to non-operational networks. The present article presents an analysis of such situations and possible solutions, including the common current approaches and recommendations, and proposes a new beacon advertising method based on a specific Trickle Timer for the Medium Access Control (MAC) Time-Slotted Channel Hopping (TSCH) layer, decoupling from the timers in the network and routing layers. With this solution, improvements in connection success, time to join, and energy consumption can be obtained for the widely extended IEEE802.15.4e standard.
Distributed Field Estimation Using Sensor Networks Based on H∞ Consensus Filtering
Authors: Yu Haiyang , Zhang Rubo , Wu Junwei , Li Xiuwen
Published: October 2018

This paper is concerned with the distributed field estimation problem using a sensor network, and the main purpose is to design a local filter for each sensor node to estimate a spatially-distributed physical process using the measurements of the whole network. The finite element method is employed to discretize the infinite dimensional process, which is described by a partial differential equation, and an approximate finite dimensional linear system is established. Due to the sparsity on the spatial distribution of the source function, the ℓ 1 -regularized H ∞ filtering is introduced to solve the estimation problem, which attempts to provide better performance than the classical centralized Kalman filtering. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed method.
Resource Management in Energy Harvesting Cooperative IoT Network under QoS Constraints
Authors: Amjad Maliha , Ahmed Ashfaq , Naeem Muhammad , Awais Muhammad , Ejaz Waleed , Anpalagan Alagan
Published: October 2018

Cooperative communication with RF energy harvesting relays has emerged as a promising technique to improve the reliability, coverage, longevity and capacity of future IoT networks. An efficient relay assignment with proper power allocation and splitting is required to satisfy the network’s QoS requirements. This work considers the resource management problem in decode and forward relay based cooperative IoT network. A realistic mathematical model is proposed for joint user admission, relay assignment, power allocation and splitting ratio selection problem. The optimization problem is a mixed integer non-linear problem (MINLP) whose objective is to maximize the overall sum rate (bps) while satisfying the practical network constraints. Further, an outer approximation algorithm is adopted which provides epsilon-optimal solution to the problem with guaranteed convergence and reasonable complexity. Simulations of the proposed solution are carried out for various network scenarios. The simulation results demonstrate that cooperative communication with diversity achieves a better admission of IoT users and increases not only their individual data rates but also the overall sum rate of an IoT network.
A Blockchain-Based Authorization System for Trustworthy Resource Monitoring and Trading in Smart Communities
Authors: Alcarria Ramon , Bordel Borja , Robles Tomás , Martín Diego , Manso-Callejo Miguel-Ángel
Published: October 2018

Resource consumption in residential areas requires novel contributions in the field of consumer information management and collaborative mechanisms for the exchange of resources, in order to optimize the overall consumption of the community. We propose an authorization system to facilitate access to consumer information and resource trading, based on blockchain technology. Our proposal is oriented to the Smart communities, an evolution of Community Energy Management Systems, in which communities are involved in the monitoring and coordination of resource consumption. The proposed environment allows a more reliable management of monitoring and authorization functions, with secure data access and storage and delegation of controller functions among householders. We provide the definition of virtual assets for energy and water resource sharing as an auction, which encourages the optimization of global consumption and saves resources. The proposed solution is implemented and validated in application scenarios that demonstrate the suitability of the defined consensus mechanism, trustworthiness in the level of provided security for resource monitoring and delegation and reduction on resource consumption by the resource trading contribution.
Study on Improved Flight Coefficient Estimation and Trajectory Analysis of a Flying Disc through Onboard Magnetometer Measurements
Authors: Lee Juhwan , Lee Byungjin , Song Jin Woo , Lee Young Jae , Sung Sangkyung
Published: October 2018

This paper proposes a novel and accurate method for estimating the flight coefficient of a flying disc typically operating at a high rotation rate. In particular, the proposed method introduces a new algorithm that takes advantage of magnetic data measured by a miniaturized sensor module onboard a conventional disc. Since the geomagnetic field measured by the magnetic sensor mounted on the rotating body yields a general sinusoidal waveform, a frequency domain analysis is employed in computing the rotational rate. Furthermore, on the basis of the estimated rate during a whole flight period, a yaw damping derivative coefficient is derived, which enables an accurate prediction of the disc’s flight trajectory. For performance verification, both a reference rotation table test and a real flight test are performed, for which a miniaturized embedded sensor module is designed and manufactured for an onboard flight test. A reference rotation test validates the performance of the proposed method. Subsequently, a flight test, in which a simulator-based trajectory is compared with the true reference trajectory, verifies that the proposed method better predicts the flight trajectory by incorporating the estimated coefficient.
Proof of Concept for an Intracochlear Acoustic Receiver for Use in Acute Large Animal Experiments
Authors: Pfiffner Flurin , Prochazka Lukas , Dobrev Ivo , Klein Karina , Sulser Patrizia , Péus Dominik , Sim Jae Hoon , Dalbert Adrian , Röösli Christof , Obrist Dominik , Huber Alexander
Published: October 2018

(1) Background: The measurement of intracochlear sound pressure (ICSP) is relevant to obtain better understanding of the biomechanics of hearing. The goal of this work was a proof of concept of a partially implantable intracochlear acoustic receiver (ICAR) fulfilling all requirements for acute ICSP measurements in a large animal. The ICAR was designed not only to be used in chronic animal experiments but also as a microphone for totally implantable cochlear implants (TICI). (2) Methods: The ICAR concept was based on a commercial MEMS condenser microphone customized with a protective diaphragm that provided a seal and optimized geometry for accessing the cochlea. The ICAR was validated under laboratory conditions and using in-vivo experiments in sheep. (3) Results: For the first time acute ICSP measurements were successfully performed in a live specimen that is representative of the anatomy and physiology of the human. Data obtained are in agreement with published data from cadavers. The surgeons reported high levels of ease of use and satisfaction with the system design. (4) Conclusions: Our results confirm that the developed ICAR can be used to measure ICSP in acute experiments. The next generation of the ICAR will be used in chronic sheep experiments and in TICI.
Photo-Electrochemical Sensing of Dopamine by a Novel Porous TiO2 Array-Modified Screen-Printed Ti Electrode
Authors: Tavella Francesco , Ampelli Claudio , Leonardi Salvatore Gianluca , Neri Giovanni
Published: October 2018

In this paper, the development of a nanoporous TiO2 array-modified Ti electrode for photo-electrochemical (PEC) sensing of dopamine (DA) is reported. A porous TiO2 array-modified electrode was fabricated from the controlled anodic oxidation of a Ti working electrode of commercial screen-printed electrodes (SPE). The anodization process and the related morphological and microstructural transformation of the bare Ti electrode into a TiO2/Ti electrode was followed by scanning electron microscopy (SEM) and UV-visible reflectance spectroscopy (DR-UV-Vis). The modified electrode was irradiated with a low-power (120 mW) UV-Vis LED lamp (λ = 400 nm) and showed good performance for the detection of DA with a large linear response range, a sensitivity of 462 nA mM−1 cm−2, and a limit of detection of 20 µM. Moreover, it showed higher photocurrents in the presence of DA in comparison to some foreign species such as ascorbic acid, uric acid, glucose, K+, Na+, and Cl−. Thus, this proposed low-cost photo-electrochemical sensor, with the advantage of very simple fabrication, demonstrates potential applications for the determination of dopamine in real samples.
Industrial IoT Monitoring: Technologies and Architecture Proposal
Authors: Raposo Duarte , Rodrigues André , Sinche Soraya , Sá Silva Jorge , Boavida Fernando
Published: October 2018

Dependability and standardization are essential to the adoption of Wireless Sensor Networks (WSN) in industrial applications. Standards such as ZigBee, WirelessHART, ISA100.11a and WIA-PA are, nowadays, at the basis of the main process-automation technologies. However, despite the success of these standards, management of WSNs is still an open topic, which clearly is an obstacle to dependability. Existing diagnostic tools are mostly application- or problem-specific, and do not support standard-based multi-network monitoring. This paper proposes a WSN monitoring architecture for process-automation technologies that addresses the mentioned limitations. Specifically, the architecture has low impact on sensor node resources, uses network metrics already available in industrial standards, and takes advantage of widely used management standards to share the monitoring information. The proposed architecture was validated through prototyping, and the obtained performance results are presented and discussed in the final part of the paper. In addition to proposing a monitoring architecture, the paper provides an in-depth insight into metrics, techniques, management protocols, and standards applicable to industrial WSNs.
Flying Ad Hoc Networks: A New Domain for Network Communications
Authors: Guillen-Perez Antonio , Cano Maria-Dolores
Published: October 2018

The advent of flying ad hoc networks (FANETs) has opened an opportunity to create new added-value services. Even though it is clear that these networks share common features with its predecessors, e.g., with mobile ad hoc networks and with vehicular ad hoc networks, there are several unique characteristics that make FANETs different. These distinctive features impose a series of guidelines to be considered for its successful deployment. Particularly, the use of FANETs for telecommunication services presents demanding challenges in terms of quality of service, energy efficiency, scalability, and adaptability. The proper use of models in research activities will undoubtedly assist to solve those challenges. Therefore, in this paper, we review mobility, positioning, and propagation models proposed for FANETs in the related scientific literature. A common limitation that affects these three topics is the lack of studies evaluating the influence that the unmanned aerial vehicles (UAV) may have in the on-board/embedded communication devices, usually just assuming isotropic or omnidirectional radiation patterns. For this reason, we also investigate in this work the radiation pattern of an 802.11 n/ac (WiFi) device embedded in a UAV working on both the 2.4 and 5 GHz bands. Our findings show that the impact of the UAV is not negligible, representing up to a 10 dB drop for some angles of the communication links.
Fast Adaptive RNN Encoder–Decoder for Anomaly Detection in SMD Assembly Machine
Authors: Park YeongHyeon , Yun Il Dong
Published: October 2018

Surface Mounted Device (SMD) assembly machine manufactures various products on a flexible manufacturing line. An anomaly detection model that can adapt to the various manufacturing environments very fast is required. In this paper, we proposed a fast adaptive anomaly detection model based on a Recurrent Neural Network (RNN) Encoder–Decoder with operating machine sounds. RNN Encoder–Decoder has a structure very similar to Auto-Encoder (AE), but the former has significantly reduced parameters compared to the latter because of its rolled structure. Thus, the RNN Encoder–Decoder only requires a short training process for fast adaptation. The anomaly detection model decides abnormality based on Euclidean distance between generated sequences and observed sequence from machine sounds. Experimental evaluation was conducted on a set of dataset from the SMD assembly machine. Results showed cutting-edge performance with fast adaptation.
Smart Contract-Based Review System for an IoT Data Marketplace
Authors: Park Ji-Sun , Youn Taek-Young , Kim Hye-Bin , Rhee Kyung-Hyune , Shin Sang-Uk
Published: October 2018

Internet of Things (IoT)-based devices, especially those used for home automation, consist of their own sensors and generate many logs during a process. Enterprises producing IoT devices convert these log data into more useful data through secondary processing; thus, they require data from the device users. Recently, a platform for data sharing has been developed because the demand for IoT data increases. Several IoT data marketplaces are based on peer-to-peer (P2P) networks, and in this type of marketplace, it is difficult for an enterprise to trust a data owner or the data they want to trade. Therefore, in this study, we propose a review system that can confirm the reputation of a data owner or the data traded in the P2P data marketplace. The traditional server-client review systems have many drawbacks, such as security vulnerability or server administrator’s malicious behavior. However, the review system developed in this study is based on Ethereum smart contracts; thus, this system is running on the P2P network and is more flexible for the network problem. Moreover, the integrity and immutability of the registered reviews are assured because of the blockchain public ledger. In addition, a certain amount of gas is essential for all functions to be processed by Ethereum transactions. Accordingly, we tested and analyzed the performance of our proposed model in terms of gas required.
Voronoi Diagram and Crowdsourcing-Based Radio Map Interpolation for GRNN Fingerprinting Localization Using WLAN
Authors: Sun Yongliang , He Yu , Meng Weixiao , Zhang Xinggan
Published: October 2018

In the last decade, fingerprinting localization using wireless local area network (WLAN) has been paid lots of attention. However, this method needs to establish a database called radio map in the off-line stage, which is a labor-intensive and time-consuming process. To save the radio map establishment cost and improve localization performance, in this paper, we first propose a Voronoi diagram and crowdsourcing-based radio map interpolation method. The interpolation method optimizes propagation model parameters for each Voronoi cell using the received signal strength (RSS) and location coordinates of crowdsourcing points and estimates the RSS samples of interpolation points with the optimized propagation model parameters to establish a new radio map. Then a general regression neural network (GRNN) is employed to fuse the new and original radio maps established through interpolation and manual operation, respectively, and also used as a fingerprinting localization algorithm to compute localization coordinates. The experimental results demonstrate that our proposed GRNN fingerprinting localization system with the fused radio map is able to considerably improve the localization performance.
Design of a Hybrid Indoor Location System Based on Multi-Sensor Fusion for Robot Navigation
Authors: Shi Yongliang , Zhang Weimin , Yao Zhuo , Li Mingzhu , Liang Zhenshuo , Cao Zhongzhong , Zhang Hua , Huang Qiang
Published: October 2018

In the case of a single scene feature, the positioning of an indoor service robot takes a long time, and localization errors are likely to occur. A new method for a hybrid indoor localization system according to multi-sensor fusion is proposed to solve these problems. The localization process is divided in two stages: rough positioning and precise positioning. By virtue of the K nearest neighbors based on possibility (KNNBP) algorithm first created in the present study, the rough position of a robot is determined according to the received signal strength indicator (RSSI) of Wi-Fi. Then, the hybrid particle filter localization (HPFL) algorithm improved on the basis of adaptive Monte Carlo localization (AMCL) is adopted to get the precise localization, which integrates various information, including the rough position and information from Lidar, a compass, an occupancy grid map, and encoders. The experiments indicated that the positioning error was 0.05 m; the success rate of localization was 96% with even 3000 particles, and the global positioning time was 1.9 s. However, under the same conditions, the success rate of AMCL was approximately 40%, the required time was approximately 25.6 s, and the positioning accuracy was the same. This indicates that the hybrid indoor location system is efficient and accurate.
A Low-Light Sensor Image Enhancement Algorithm Based on HSI Color Model
Authors: Ma Shiping , Ma Hongqiang , Xu Yuelei , Li Shuai , Lv Chao , Zhu Mingming
Published: October 2018

Images captured by sensors in unpleasant environment like low illumination condition are usually degraded, which means low visibility, low brightness, and low contrast. In order to improve this kind of images, in this paper, a low-light sensor image enhancement algorithm based on HSI color model is proposed. At first, we propose a dataset generation method based on the Retinex model to overcome the shortage of sample data. Then, the original low-light image is transformed from RGB to HSI color space. The segmentation exponential method is used to process the saturation (S) and the specially designed Deep Convolutional Neural Network is applied to enhance the intensity component (I). At the end, we back into the original RGB space to get the final improved image. Experimental results show that the proposed algorithm not only enhances the image brightness and contrast significantly, but also avoids color distortion and over-enhancement in comparison with some other state-of-the-art research papers. So, it effectively improves the quality of sensor images.
Energy-Balanced Multisensory Scheduling for Target Tracking in Wireless Sensor Networks
Authors: Feng Juan , Zhao Hongwei
Published: October 2018

One important way to extend the lifetime of wireless sensor networks (WSNs) is to manage the sleep scheduling of sensor nodes after they are deployed. Most of the existing works on node scheduling mainly concentrate on nodes which have only one sensor, and they regard a node and its sensor modules as a whole to manage sleep scheduling. Few works involve the sensed modules scheduling of the sensor nodes, which have multiple sensors. However, some of the sensed modules (such as video sensor) consume a lot of energy. Therefore, they have less energy efficiency for multisensory networks. In this paper, we propose a distributed and energy-balanced multisensory scheduling strategy (EBMS), which considers the scheduling of both the communication modules and the sensed modules for each node in target tracking WSNs. In EBMS, the network is organized as clustering structures. Each cluster head adaptively assigns a sleep time to its cluster members according to the position of the members. Energy-balanced multisensory scheduling strategy also proposes an energy balanced parameter to balance the energy consumption of each node in the network. In addition, multi-hop coordination scheme is proposed to find the optimal cooperation among clusters to maximize the energy conservation. Experimental results show that EBMS outperformed the state-of-the-art approaches.
A Combined Ray Tracing Method for Improving the Precision of the USBL Positioning System in Smart Ocean
Authors: Li Jian , Gu Qi , Chen Ying , Sun Guiqing , Huang Haocai
Published: October 2018

The ultra-short baseline positioning system (USBL) has the advantages of flexible application and easy installation, and it plays an extremely important role in the underwater positioning and communication. The error of the USBL in underwater positioning is mainly caused by a ranging error due to ray tracing, a phase difference error of the USBL, and acoustic noise in the underwater communication. Most of these errors are related to the changes in the sound speed during its propagation through the ocean. Therefore, when using the USBL for underwater detection, it is necessary to correct the sound speed profile in the detection area and optimize the ray tracing. Taking into account the actual conditions, this paper aims at correcting the model of underwater sound speed propagation and improving the tracking method of sound lines when the marine environment in the shallow sea area changes. This paper proposes a combined ray tracing method that can adaptively determine whether to use the constant sound speed ray tracing method or the equal gradient ray tracing method. The theoretical analysis and simulation results show that the proposed method can effectively reduce the error of slant distance in USBL compared with the traditional acoustic tracking method and the constant sound speed ray tracing method. The proposed sound ray correction algorithm solves the contradiction between the number of iterations and the reduction of positioning error and has engineering application value.
Cooperative Sensing Data Collection and Distribution with Packet Collision Avoidance in Mobile Long-Thin Networks
Authors: Chen Lien-Wu , Peng Yu-Hao , Tseng Yu-Chee , Tsai Ming-Fong
Published: October 2018

Mobile ad hoc networks (MANETs) have gained a lot of interests in research communities for the infrastructure-less self-organizing nature. A MANET with fleet cyclists using smartphones forms a two-tier mobile long-thin network (MLTN) along a common cycling route, where the high-tier network is composed of 3G/LTE interfaces and the low-tier network is composed of IEEE 802.11 interfaces. The low-tier network may consist of several path-like networks. This work investigates cooperative sensing data collection and distribution with packet collision avoidance in a two-tier MLTN. As numbers of cyclists upload their sensing data and download global fleet information frequently, serious bandwidth and latency problems may result if all members rely on their high-tier interfaces. We designed and analyzed a cooperative framework consisting of a distributed grouping mechanism, a group merging and splitting method, and a sensing data aggregation scheme. Through cooperation between the two tiers, the proposed framework outperforms existing works by significantly reducing the 3G/LTE data transmission and the number of 3G/LTE connections.
A New Disaster Information Sensing Mode: Using Multi-Robot System with Air Dispersal Mode
Authors: Liu Yi , Gao Junyao , Zhao Jingchao , Shi Xuanyang
Published: October 2018

This paper presents a novel sensing mode for using mobile robots to collect disaster ground information when the ground traffic from the rescue center to disaster site is disrupted. Traditional sensing modes which use aerial robots or ground robots independently either have limited ability to access disaster site or are only able to provide a bird’s eye view of the disaster site. To illustrate the proposed sensing mode, the authors have developed a Multi-robot System with Air Dispersal Mode (MSADM) by combining the unimpeded path of aerial robots with the detailed view of ground robots. In the MSADM, an airplane carries some minimal reconnaissance ground robots to overcome the paralyzed traffic problem and deploys them on the ground to collect detailed scene information using parachutes and separation device modules. In addition, the airplane cruises in the sky and relays the control and reported information between the ground robots and the human operator. This means that the proposed sensing mode is able to provide more reliable communication performance when there are obstacles between the human operators and the ground robots. Additionally, the proposed sensing mode can easily make use of different kinds of ground robots, as long as they have a compatible interface with the separation device. Finally, an experimental demonstration of the MSADM is presented to show the effectiveness of the proposed sensing mode.
Application of Nanomaterials in Personal Respiratory Protection Equipment: A Literature Review
Authors: Abbasinia Marzieh , Karimie Safoura , Haghighat Mojtaba , Mohammadfam Iraj
Published: October 2018

Exposure to air pollutants leads to a variety of health effects in humans. Inhalation is one of the most common routs of exposure to poor quality air, mostly in work environments. Respiratory masks are used to prevent breathing in hazardous gases and vapors, especially in the absence of proper controlling measures. This study aims to review the effectiveness of respiratory masks with a nanostructure. The electronic search of the genuine databases, including PubMed, Magiran, Iran Medex, Science Database (SID), Science Direct, Web of Science, and Scopus, was conducted in January and February 2017 in chronological order of publications with the keywords defined in the search strategy. Of all identified papers, nine were collected and included in the study. The results of this study indicated that the use of nanomaterials in the structure of brand new mask filters compared with conventional masks enhances the performance and efficiency of breathing air filtration, improves permeability, increases antimicrobial properties, and offers reasonable comfort to the workers.
Resilience: Examining the Impacts of the Deepwater Horizon Oil Spill on the Gulf Coast Vietnamese American Community
Authors: Patel Megha , Saltzman Leia , Ferreira Regardt , Lesen Amy
Published: October 2018

The 2010 Deepwater Horizon oil spill (DWH) was one of the largest hydrocarbon disasters in US history. The estimated 5 million barrels of oil that poured into the Gulf of Mexico had a devastating impact on the natural environment, as well as on the livelihoods of communities residing along the coastal region. This paper explores resilience in individuals that identify as Vietnamese, presenting findings from a study of three Gulf Coast communities impacted by the DWH oil spill. A 60-min, in-person survey was administered to a total of 326 residents from the Gulf Coast communities of Port Sulphur, LA, Galliano, LA, and Bayou La Batre, AL. Logistic regression outcome and key predictors models were used to determine the probability of having higher levels of resilience. The results of this study highlight the role of age, education, and racial/ethnic identification in fostering resilience following disaster exposure. Identifying as Vietnamese was associated with a decrease in the odds of achieving above-threshold levels of resilience. This study may be viewed as the foundation from which to further explore the unique risk and protective profiles of the Vietnamese population, particularly in regard to those residing in critically vulnerable and disaster-prone areas.
Response of Soil Moisture to Single-Rainfall Events under Three Vegetation Types in the Gully Region of the Loess Plateau
Authors: Hou Guirong , Bi Huaxing , Wei Xi , Kong Lingxiao , Wang Ning , Zhou Qiaozhi
Published: October 2018

Precipitation is the main source of soil moisture recharge in the gully region of the Loess Plateau, and soil moisture is the main and most important water resource for vegetation activities in semiarid regions. To identify the contributions to soil moisture replenishment from rainfall of different intensities, this study conducted a soil moisture monitoring experiment involving continuous measurements at 30-min intervals in areas of Robinia pseudoacacia artificial forestland, Pinus tabulaeformis artificial forestland, and grassland from 1 March to 31 November 2017. The results indicated that there was a positive relationship between the infiltration coefficient and precipitation until the relationship obtained a stable value. When the precipitation was greater than 30 mm, soil moisture was replenished up to the 150 cm soil layer in grassland, and when the precipitation was greater than 40 mm, soil moisture was replenished up to the 150 cm soil layer in P. tabulaeformis artificial forestland. However, only precipitation greater than 50 mm replenished the soil moisture at the 150 cm soil layer in R. pseudoacacia artificial forestland. These three vegetation communities play important roles in soil and water conservation during ecological restoration. The results of this study can guide vegetation configurations in vegetation recovery and reconstruction efforts in the gully region of the Loess Plateau.
Effects of Corporate Life Cycle on Corporate Social Responsibility: Evidence from Korea
Authors: Lee Woo Jae , Choi Seung Uk
Published: October 2018

Few studies examine how firms make strategic decisions over time. In this study, we test whether a firm undertakes corporate social responsibility (CSR) activities as a function of its life-cycle stage. Drawing on prior CSR research that finds ethical concerns and opportunistic behavior to be two key motivations that underpin CSR activities, we hypothesize that firms in their growth stage are positively associated with CSR, while firms in stage of decline are less likely to invest in CSR. The empirical findings of our study—derived by leveraging a sample of South Korean listed firms—are consistent with these predictions. We further find that in the growth stage, group-affiliated firms are more engaged in CSR than are unaffiliated firms. Given that affiliated firms can share the resources of other group-member firms, this evidence supports the slack resource hypothesis. Overall, our results indicate that firms have different CSR strategies, depending on their life-cycle stage.
Effect of Three Husbandry Systems on Environmental Impact of Organic Pigs
Authors: Rudolph Gwendolyn , Hörtenhuber Stefan , Bochicchio Davide , Butler Gillian , Brandhofer Roland , Dippel Sabine , Dourmad Jean Yves , Edwards Sandra , Früh Barbara , Meier Matthias , Prunier Armelle , Winckler Christoph , Zollitsch Werner , Leeb Christine
Published: October 2018

This study examined the environmental impact of the three common organic pig husbandry systems, indoor (n = 24), partly outdoor (n = 30), and outdoor (n = 10), in eight European countries. Global warming (GWP), acidification (AP), and eutrophication potential (EP) was assessed per 1000 kg pig live weight on 64 farrow-to-finish pig production chains (cradle to farm gate). GWP, AP, and EP varied greatly, and the most important source was feed production, followed by housing. GWP did not differ between systems (p = 0.934), but AP in indoor systems and EP in outdoor systems were higher than in partly outdoor systems (p = 0.006 and p = 0.010, respectively). The higher AP in indoor systems can mainly be explained by NH3 arising from manure spreading, while PO4-eq arising from feed consumption and emissions on pasture accounted for the higher EP in outdoor systems. Associations of farm characteristics with (reduced) environmental impacts were mainly found for AP and EP, and included: (Increasing) farm size, numbers of piglets born and weaned per litter, (bought-in) mineral feed, and high-protein by-products, the latter probably connected to beneficial effects of appropriate dietary digestible lysine levels and feed conversion ratio. Increasing carcass weights and dietary cereal proportions were associated with higher environmental impacts. Overall, variation was mostly higher within than between systems, and measures to mitigate environmental impact were identified.
Embedding Higher Education into a Real-World Lab: A Process-Oriented Analysis of Six Transdisciplinary Project Courses
Authors: Beecroft Richard
Published: October 2018

Since the early days of the emerging research format of Real-world Labs (RwLs), higher education plays a vital role in them. Examples have been presented on teaching activities in RwLs, but the reasons for and evidence of their inclusion stays limited. To start a systematic discussion on the embedding of higher education in RwLs, this paper presents the case of six Transdisciplinary Project Courses carried out in the RwL “District Future—Urban Lab” in Karlsruhe/Germany. The paper presents the discourses on the role of learning in RwLs and compares it to those on Transition Labs and Urban Living Labs. To offer a new approach to address this aspect, the paper introduces a social practice perspective to map out the interrelations between an RwL and higher education therein. The detailed analysis of the processes is used to identify the potential of the RwL to support learning. It shows that all dimensions of social practice can be identified in the interplay between Real-world Lab and Transdisciplinary Project Courses, even though to a very different degree and in different phases. The text closes with lessons learned for teaching project courses in RwLs and similar labs.