bluuebunny/crossref_metadata_2025 huggingface dataset:
Transungual Delivery of Ciclopirox Is Increased 3–4-Fold by Mechanical Fenestration of Human Nail Plate in an In Vitro Model
Authors: Cordoba Díaz Damian , Losa Iglesias Marta Elena , Becerro de Bengoa Vallejo Ricardo , Cordoba Diaz Manuel
Published: January 2019

Onychomycosis is a fungal infection of nails that is widespread and difficult to treat because of the impermeable nature of human nails. Topically applied anti-fungal agents cannot penetrate this structure, and treatment regimens often resort to systemic antifungals with concomitant side effects. One recent clinical study suggested that mechanical fenestration of the nail using an intelligent nail drill might be a possible solution to this problem. In this work, an in vitro model of the transungual delivery of antifungal agents is presented, which utilizes real nail tissue and an inline flow system. This system was deployed to measure transungual delivery of ciclopirox and determined that nail fenestration improved drug delivery by 3–4-fold after 42 days. This study bolsters the argument that nail fenestration should be accepted as a pretreatment for onychomycosis and offers a way of evaluating new drugs or formulations designed to combat this condition.
Preparation and Study of the Antibacterial Applications and Oxidative Stress Induction of Copper Maleamate-Functionalized Mesoporous Silica Nanoparticles
Authors: Díaz-García Diana , Ardiles Perla R. , Prashar Sanjiv , Rodríguez-Diéguez Antonio , Páez Paulina L. , Gómez-Ruiz Santiago
Published: January 2019

Mesoporous silica nanoparticles (MSNs) are an interesting class of nanomaterials with potential applications in different therapeutic areas and that have been extensively used as drug carriers in different fields of medicine. The present work is focused on the synthesis of MSNs containing a maleamato ligand (MSN-maleamic) and the subsequent coordination of copper(II) ions (MSN-maleamic-Cu) for the exploration of their potential application as antibacterial agents. The Cu-containing nanomaterials have been characterized by different techniques and the preliminary antibacterial effect of the supported maleamato-copper(II) complexes has been tested against two types of bacteria (Gram positive and Gram negative) in different assays to determine the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). The biological results showed a moderate antibacterial activity against Escherichia coli which motivated a more detailed study of the antibacterial mechanism of action of the synthesized maleamate-containing nanosystems and whose findings showed oxidative stress generation in bacterial cells. All the prepared nanomaterials were also tested as catalysts in the “solvent free” selective oxidation of benzyl alcohol, to observe if there is a potential correlation between the catalytic oxidation capacity of the materials and the observed oxidative stress in bacteria. This may help in the future, for a more accurate rational design of antibacterial nanosystems, based on their observed catalytic oxidation activity.
Non-Isothermal Crystallization Behavior of PEEK/Graphene Nanoplatelets Composites from Melt and Glass States
Authors: Alvaredo Ángel , Martín María Isabel , Castell Pere , Guzmán de Villoria Roberto , Fernández-Blázquez Juan P.
Published: January 2019

The effect of the graphene nanoplateletets (GNP), at concentration of 1, 5 and 10 wt %, in Poly ether ether ketone (PEEK) composite crystallization from melt and during cold crystallization were investigated by differential scanning calorimetry (DSC) and real time X-ray diffraction experiments. DSC results revealed a double effect of GNP: (a) nucleating effect crystallization from melt started at higher temperatures and (b) longer global crystallization time due to the restriction in the polymer chain mobility. This hindered mobility were proved by rheological behavior of nanocomposites, because to the increase of complex viscosity, G′, G″ with the GNP content, as well as the non-Newtonian behavior found in composites with high GNP content. Finally, real time wide and small angle synchrotron X-ray radiation (WAXS/SAXS) X-ray measurements showed that GNP has not affected the orthorhombic phase of PEEK nor the evolution of the crystal phase during the crystallization processes. However, the correlation length of the crystal obtained by WAXS and the long period (L) by SAXS varied depending on the GNP content.
Synthesis, Structures and Electrochemical Properties of Lithium 1,3,5-Benzenetricarboxylate Complexes
Authors: Cheng Pei-Chi , Li Bing-Han , Tseng Feng-Shuen , Liang Po-Ching , Lin Chia-Her , Liu Wei-Ren
Published: January 2019

Four lithium coordination polymers, [Li3(BTC)(H2O)6] (1), [Li3(BTC)(H2O)5] (2), [Li3(BTC)(μ2-H2O)] (3), and [Li(H2BTC)(H2O)] (4) (H3BTC = 1,3,5-benzenetricarboxylatic acid), have been synthesized and characterized. All the structures have been determined using single crystal X-ray diffraction studies. Complexes 1 and 2 have two-dimensional (2-D) sheets, whereas complex 3 has three-dimensional (3-D) frameworks and complex 4 has one-dimensional (1-D) tubular chains. The crystal-to-crystal transformation was observed in 1–3 upon removal of water molecules, which accompanied the changes in structures and ligand bridging modes. Furthermore, the electrochemical properties of complexes 3 and 4 have been studied to evaluate these compounds as electrode materials in lithium ion batteries with the discharge capacities of 120 and 257 mAhg−1 in the first thirty cycles, respectively.
Characterization of Solvent-Treated PEDOT:PSS Thin Films with Enhanced Conductivities
Authors: Rwei Syang-Peng , Lee Yi-Huan , Shiu Jia-Wei , Sasikumar Ragu , Shyr Uin-Ting
Published: January 2019

The conducting polymer of poly(3,4-ethylenedioxythiophene):poly(4-styrenesulfonate) (PEDOT:PSS) is one of the most important and intensively investigated organic conducting materials. The PEDOT:PSS water dispersions with various concentrations of poly (4-styrenesulfonic acid) solution (PSSAS) were synthesized by 3,4-ethylenedioxythiophene (EDOT) in the presence of water. The fabrication of the solvent-treated PEDOT:PSS films through spin coating and solvent treatment processes was achieved with a solvent of pure water mixed with acetone (or MeOH, EtOH) in a ratio of 50:50. Moreover, both the organic solvent and water have synergetic effects while the PSS and PEDOT-attached PSS segments will form a coil-like and a linear (or extended-coil) structure, respectively. That may induce a stacking of the linear and planar PEDOT-attached PSS segments, which favors the formation of a crystalline phase. Finally, the maximum electrical conductivity of the PEDOT:PSS thin films with solvent treatment was investigated by means of X-ray diffraction (XRD) patterns and scanning electron microscope (SEM) images. Furthermore, we aimed to explain the synergetic effects of phase separation of the PEDOT:PSS thin films by both the organic solvent and water.
A Study on the Modified Arrhenius Equation Using the Oxygen Permeation Block Model of Crosslink Structure
Authors: Moon Byungwoo , Jun Namgyu , Park Soo , Seok Chang-Sung , Hong Ui Seok
Published: January 2019

Polymers are widely used in various industries because of their characteristics such as elasticity, abrasion resistance, fatigue resistance and low temperature. In particular, the tensile characteristic of rubber composites is important for the stability of industrial equipment because it determines the energy absorption rates and vibration damping. However, when a product is used for a long period of time, polymers become hardened owing to the changes in characteristics because of aging, thereby reducing the performance and increasing the possibility of accidents. Therefore, accurately predicting the mechanical properties of polymers is important for preventing industrial accidents while operating a machine. In general reactions, the linear Arrhenius equation is used to predict the aging characteristics; however, for rubber composites, it is more accurate to predict the aging characteristics using nonlinear equations rather than linear equations. However, the reason that the characteristic equation of the polymer appears nonlinear is not well known, and studies on the change in the characteristics of the natural and butadiene rubber owing to degradation are still lacking. In this study, a tensile test is performed with different aging temperatures and aging time to evaluate the aging characteristics of rubber composites using strain energy density. We propose a block effect of crosslink structure to express the nonlinear aging characteristics, assuming that a limited reaction can occur owing to the blocking of reactants in the rubber composites. Consequently, we found that a relationship exists between the crosslink structure and aging characteristics when the reduction in crosslink space owing to aging is represented stochastically. In addition, a modified Arrhenius equation, which is expressed as a function of time, is proposed to predict the degradation rate for all aging temperatures and aging times, and the formula is validated by comparing the degradation rate obtained experimentally with the degradation rate predicted by the modified Arrhenius equation.
Hyaluronic Acid-Decorated Laponite® Nanocomposites for Targeted Anticancer Drug Delivery
Authors: Jiang Tingting , Chen Guangxiang , Shi Xiangyang , Guo Rui
Published: January 2019

In this study, hyaluronic acid (HA), a natural polysaccharide that can specifically bind to CD44 receptors, was conjugated onto laponite® (LAP) nanodisks for the encapsulation and specific delivery of the anti-cancer drug doxorubicin (DOX) to CD44-overexpressed cancer cells. The prepared LM-HA could encapsulate DOX efficiently and release drug in a continuous manner with pH-responsiveness. In vitro cell viability assay proved that LM-HA had good biocompatibility, and drug-loaded LM-HA/DOX exhibited targeted anti-tumor effects against HeLa cells with CD44 receptors overexpressed. In addition, the flow cytometric detection and confocal laser scanning microscope results confirmed that LM-HA/DOX could be specifically internalized by HeLa cells via CD44-mediated endocytosis. Therefore, the HA-modified LAP nanodisks with high drug loading efficiency, pH-sensitive drug release properties and CD44 targetability might be an efficient nanoplatform for cancer chemotherapy.
The Perceived Role of Financial Incentives in Promoting Waste Recycling—Empirical Evidence from Finland
Authors: Abila Beatrice , Kantola Jussi
Published: January 2019

Placing emphasis on promoting the reduction, reuse, recycling, recovery and repair of waste has been a critical aspect of the sustainable waste management agenda. Considering recycling, an environmentally friendly and sustainable waste management option, monetary rewards are in place for certain recyclable municipal waste materials in Finland. The study investigates consumers’ perception about the role of financial incentives in effecting the recycling of municipal solid waste materials in Finland. The study also considers drivers for recycling municipal solid waste on the basis of behavioural change factors, such as environmental risk, behavioural economics, resource value, economic benefit, convenience, knowledge, legislation and belief. It further determines the association between income-earning consumers and non-income-earning consumers in their perception of financial incentives for recycling. The empirical results from the study confirm that the role of financial incentive is important in accelerating the recycling of municipal solid waste. A weak-to-positive relationship exists between drivers for recycling municipal solid waste and recycling behaviour. There exists no statistically significant difference in the means of the perceived role of financial incentives for recycling in the two groups. The introduction of financial incentives for other recyclable wastes is required in order to boost consumers’ participation in the recycling of municipal solid waste. The need to pay more attention to intrinsic and extrinsic factors, as they affect the participation members of the society in the recycling of municipal solid waste, is paramount. This has become necessary in ensuring sustainable waste management in Finland.
“Where Are We Going?” Dante’s Inferno or Richard Rorty’s “Liberal Ironist”
Authors: Sansom Dennis
Published: January 2019

This paper elucidates the structure of moral action by arguing that Dante’s explanation in the Inferno of why people end up in their respective circles of hell is superior in terms of accounting for the structure of moral reasoning to Richard Rorty’s promotion of the “liberal ironist.” The latter suffers an internal contradiction—it wants a well-lived life without any overriding aims, but such a life is understandable only in light of affirming life-aims. The former convincingly shows that the structure of action reveals the truth of the well-known apothegm—“we reap what we sow.” The main point for Dante is not who is rational (for even the rational can be vicious, as depicted in the Inferno), but whose aims actually fulfill the practical life. This comparison of Dante and Rorty can have larger pedagogical aims, helping students to understand better what Albert William Levi calls “the moral imagination” and deepening their appreciation of how metaphors and paradigms of moral excellence provide, or fail to provide, an overriding unity and purpose to our actions.
Observation of CO2 Regional Distribution Using an Airborne Infrared Remote Sensing Spectrometer (Air-IRSS) in the North China Plain
Authors: Wang Ruwen , Xie Pinhua , Xu Jin , Li Ang , Sun Youwen
Published: January 2019

Carbon dioxide (CO2) is one of the most important anthropogenic greenhouse gases (GHG) and significantly affects the energy balance of atmospheric systems. Larger coverage and higher spatial resolution of CO2 measurements can complement the existing in situ network and satellite measurements and thus improve our understanding of the global carbon cycle. In this study, we present a self-made airborne infrared remote sensing spectrometer (Air-IRSS) designed to determine the regional distribution of CO2. The Air-IRSS measured CO2 in the spectral range between 1590 and 1620 nm at a spectral resolution of 0.45 nm and an exposure time of 1 s. It was operated onboard an aircraft at a height of 3 km with a velocity of 180 km/h, and a spatial resolution of 50.00 m × 62.80 m. Weighting function modified differential optical absorption spectroscopy (WFM-DOAS) was used to analyze the measured spectra. The results show that the total uncertainty estimated for the retrieval of the CO2 column was 1.26% for airborne measurements over a large region, and 0.30% for a fixed point, such as power points or factories. Under vibration-free static conditions, the on-ground Air-IRSS observations can adequately reproduce the variations observed by Greenhouse Gases Observing Satellite (GOSAT) with a correlation coefficient (r) of 0.72. Finally, we conducted an airborne field campaign to determine the regional distribution of CO2 over the North China Plain. The regional distribution of CO2 columns over four cities of Xing-tai, Hengshui, Shijiazhuang, and Baoding were obtained with the GPS information, which ranged from 2.00 × 1021 molec cm−2 to 3.00 × 1021 molec cm−2. The CO2 vertical distributions were almost uniform below a height of 3 km in the area without CO2 emission sources, and the highest values were found over Baoding City.
Walker: Continuous and Precise Navigation by Fusing GNSS and MEMS in Smartphone Chipsets for Pedestrians
Authors: Zhu Feng , Tao Xianlu , Liu Wanke , Shi Xiang , Wang Fuhong , Zhang Xiaohong
Published: January 2019

The continual miniaturization of mass-market sensors built in mobile intelligent terminals has inspired the development of accurate and continuous navigation solution for portable devices. With the release of Global Navigation Satellite System (GNSS) observations from the Android Nougat system, smartphones can provide pseudorange, Doppler, and carrier phase observations of GNSS. However, it is still a challenge to achieve the seamless positioning of consumer applications, especially in environments where GNSS signals suffer from a low signal-to-noise ratio and severe multipath. This paper introduces a dedicated android smartphone application called Walker that integrates the GNSS navigation solution and MEMS (micro-electromechanical systems) sensors to enable continuous and precise pedestrian navigation. Firstly, we introduce the generation of GNSS and MEMS observations, in addition to the architecture of Walker application. Then the core algorithm in Walker is given, including the time-differenced carrier phase improved GNSS single-point positioning and the integration of GNSS and Pedestrian Dead Reckoning (PDR). Finally, the Walker application is tested and the observations of GNSS and MEMS are assessed. The static experiment shows that, with GNSS observations, the RMS (root mean square) values of east, north, and up positioning error are 0.49 m, 0.37 m, and 1.01 m, respectively. Furthermore, the kinematic experiment verifies that the proposed method is capable of obtaining accuracy within 1–3 m for smooth and continuous navigation.
MFA-Net: Motion Feature Augmented Network for Dynamic Hand Gesture Recognition from Skeletal Data
Authors: Chen Xinghao , Wang Guijin , Guo Hengkai , Zhang Cairong , Wang Hang , Zhang Li
Published: January 2019

Dynamic hand gesture recognition has attracted increasing attention because of its importance for human–computer interaction. In this paper, we propose a novel motion feature augmented network (MFA-Net) for dynamic hand gesture recognition from skeletal data. MFA-Net exploits motion features of finger and global movements to augment features of deep network for gesture recognition. To describe finger articulated movements, finger motion features are extracted from the hand skeleton sequence via a variational autoencoder. Global motion features are utilized to represent the global movements of hand skeleton. These motion features along with the skeleton sequence are then fed into three branches of a recurrent neural network (RNN), which augment the motion features for RNN and improve the classification performance. The proposed MFA-Net is evaluated on two challenging skeleton-based dynamic hand gesture datasets, including DHG-14/28 dataset and SHREC’17 dataset. Experimental results demonstrate that our proposed method achieves comparable performance on DHG-14/28 dataset and better performance on SHREC’17 dataset when compared with start-of-the-art methods.
Intelligent Spectroscopy System Used for Physicochemical Variables Estimation in Sugar Cane Soils
Authors: Landeta-Escamilla Ofelia , Sandoval-Gonzalez Oscar , Martínez-Sibaja Albino , Flores-Cuautle José de Jesús Agustín , Posada-Gómez Rubén , Alvarado-Lassman Alejandro
Published: January 2019

The current condition of soils is a major area of interest due to the lack of certainty in their physicochemical properties, which can guarantee the quality and the production of a specific crop. Additionally, methodologies to improve land management must be implemented in order to address the consequences of many environmental issues. To date, many techniques have been implemented to improve the accuracy—and more recently the speed—of analysis, in order to obtain results while in the field. Among those, Near Infrared (NIR) spectroscopy has been widely used to achieve the objectives mentioned above. Nevertheless, it requires particular knowledge, and the cost might be high for farmers who own the fields and crops. Thus, the present work uses a system that implements capacitance spectroscopy plus artificial intelligence algorithms to estimate the physicochemical variables of soil used to grow sugar cane. The device uses the frequency response of the soil to determine its magnitude and phase values, which are used by artificial intelligence algorithms that are capable of estimating the soil properties. The obtained results show errors below 8% in the estimation of the variables compared to the analysis results of the soil in laboratories. Additionally, it is a portable system, with low cost, that is easy to use and could be implemented to test other types of soils after evaluating the necessary algorithms or proposing alternatives to restore soil properties.
Non-Local Based Denoising Framework for In Vivo Contrast-Free Ultrasound Microvessel Imaging
Authors: Adabi Saba , Ghavami Siavash , Fatemi Mostafa , Alizad Azra
Published: January 2019

Vascular networks can provide invaluable information about tumor angiogenesis. Ultrafast Doppler imaging enables ultrasound to image microvessels by applying tissue clutter filtering methods on the spatio-temporal data obtained from plane-wave imaging. However, the resultant vessel images suffer from background noise that degrades image quality and restricts vessel visibilities. In this paper, we addressed microvessel visualization and the associated noise problem in the power Doppler images with the goal of achieving enhanced vessel-background separation. We proposed a combination of patch-based non-local mean filtering and top-hat morphological filtering to improve vessel outline and background noise suppression. We tested the proposed method on a flow phantom, as well as in vivo breast lesions, thyroid nodules, and pathologic liver from human subjects. The proposed non-local-based framework provided a remarkable gain of more than 15 dB, on average, in terms of contrast-to-noise and signal-to-noise ratios. In addition to improving visualization of microvessels, the proposed method provided high quality images suitable for microvessel morphology quantification that may be used for diagnostic applications.
Camera Calibration Using Gray Code
Authors: Sels Seppe , Ribbens Bart , Vanlanduit Steve , Penne Rudi
Published: January 2019

In order to determine camera parameters, a calibration procedure involving the camera recordings of a checkerboard is usually performed. In this paper, we propose an alternative approach that uses Gray-code patterns displayed on an LCD screen. Gray-code patterns allow us to decode 3D location information of points of the LCD screen at every pixel in the camera image. This is in contrast to checkerboard patterns where the number of corresponding locations is limited to the number of checkerboard corners. We show that, for the case of a UEye CMOS camera, the precision of focal-length estimation is 1.5 times more precise than when using a standard calibration with a checkerboard pattern.
A Robust Indoor Localization System Integrating Visual Localization Aided by CNN-Based Image Retrieval with Monte Carlo Localization
Authors: Xu Song , Chou Wusheng , Dong Hongyi
Published: January 2019

This paper proposes a novel multi-sensor-based indoor global localization system integrating visual localization aided by CNN-based image retrieval with a probabilistic localization approach. The global localization system consists of three parts: coarse place recognition, fine localization and re-localization from kidnapping. Coarse place recognition exploits a monocular camera to realize the initial localization based on image retrieval, in which off-the-shelf features extracted from a pre-trained Convolutional Neural Network (CNN) are adopted to determine the candidate locations of the robot. In the fine localization, a laser range finder is equipped to estimate the accurate pose of a mobile robot by means of an adaptive Monte Carlo localization, in which the candidate locations obtained by image retrieval are considered as seeds for initial random sampling. Additionally, to address the problem of robot kidnapping, we present a closed-loop localization mechanism to monitor the state of the robot in real time and make adaptive adjustments when the robot is kidnapped. The closed-loop mechanism effectively exploits the correlation of image sequences to realize the re-localization based on Long-Short Term Memory (LSTM) network. Extensive experiments were conducted and the results indicate that the proposed method not only exhibits great improvement on accuracy and speed, but also can recover from localization failures compared to two conventional localization methods.
A Multi-Camera Rig with Non-Overlapping Views for Dynamic Six-Degree-of-Freedom Measurement
Authors: Niu Zhiyuan , Ren Yongjie , Yang Linghui , Lin Jiarui , Zhu Jigui
Published: January 2019

Large-scale measurement plays an increasingly important role in intelligent manufacturing. However, existing instruments have problems with immersive experiences. In this paper, an immersive positioning and measuring method based on augmented reality is introduced. An inside-out vision measurement approach using a multi-camera rig with non-overlapping views is presented for dynamic six-degree-of-freedom measurement. By using active LED markers, a flexible and robust solution is delivered to deal with complex manufacturing sites. The space resection adjustment principle is addressed and measurement errors are simulated. The improved Nearest Neighbor method is employed for feature correspondence. The proposed tracking method is verified by experiments and results with good performance are obtained.
Optimal Resource Management and Binary Power Control in Network-Assisted D2D Communications for Higher Frequency Reuse Factor
Authors: Ningombam Devarani Devi , Shin Seokjoo
Published: January 2019

Device-to-device (D2D) communications can be adopted as a promising solution to attain high quality of service (QoS) for a network. However, D2D communications generates harmful interference when available resources are shared with traditional cellular users (CUs). In this paper, network architecture for the uplink resource management issue for D2D communications underlaying uplink cellular networks is proposed. We develop a fractional frequency reuse (FFR) technique to mitigate interference induced by D2D pairs (DPs) to CUs and mutual interference among DPs in a cell. Then, we formulate a sum throughput optimization problem to achieve the QoS requirements of the system. However, the computational complexity of the optimization problem is very high due to the exhaustive search for a global optimal solution. In order to reduce the complexity, we propose a greedy heuristic search algorithm for D2D communications so as to find a sub-optimal solution. Moreover, a binary power control scheme is proposed to enhance the system throughput by reducing overall interference. The performance of our proposed scheme is analyzed through extensive numerical analysis using Monte Carlo simulation. The results demonstrate that our proposed scheme provides significant improvement in system throughput with the lowest computational complexity.
Gradient-Based Multi-Objective Feature Selection for Gait Mode Recognition of Transfemoral Amputees
Authors: Khademi Gholamreza , Mohammadi Hanieh , Simon Dan
Published: January 2019

One control challenge in prosthetic legs is seamless transition from one gait mode to another. User intent recognition (UIR) is a high-level controller that tells a low-level controller to switch to the identified activity mode, depending on the user’s intent and environment. We propose a new framework to design an optimal UIR system with simultaneous maximum performance and minimum complexity for gait mode recognition. We use multi-objective optimization (MOO) to find an optimal feature subset that creates a trade-off between these two conflicting objectives. The main contribution of this paper is two-fold: (1) a new gradient-based multi-objective feature selection (GMOFS) method for optimal UIR design; and (2) the application of advanced evolutionary MOO methods for UIR. GMOFS is an embedded method that simultaneously performs feature selection and classification by incorporating an elastic net in multilayer perceptron neural network training. Experimental data are collected from six subjects, including three able-bodied subjects and three transfemoral amputees. We implement GMOFS and four variants of multi-objective biogeography-based optimization (MOBBO) for optimal feature subset selection, and we compare their performances using normalized hypervolume and relative coverage. GMOFS demonstrates competitive performance compared to the four MOBBO methods. We achieve a mean classification accuracy of 97.14 % ± 1.51 % and 98.45 % ± 1.22 % with the optimal selected subset for able-bodied and amputee subjects, respectively, while using only 23% of the available features. Results thus indicate the potential of advanced optimization methods to simultaneously achieve accurate, reliable, and compact UIR for locomotion mode detection of lower-limb amputees with prostheses.
Rate-Distortion Performance and Incremental Transmission Scheme of Compressive Sensed Measurements in Wireless Sensor Networks
Authors: Da Rocha Henriques Felipe , Lovisolo Lisandro , Barros da Silva Eduardo Antônio
Published: January 2019

We consider a Wireless Sensor Network (WSN) monitoring environmental data. Compressive Sensing (CS) is explored to reduce the number of coefficients to transmit and consequently save the energy of sensor nodes. Each sensor node collects N samples of environmental data, these are CS coded to transmit M < N values to a sink node. The M CS coefficients are uniformly quantized and entropy coded. We investigate the rate-distortion performance of this approach even under CS coefficient losses. The results show the robustness of the CS coding framework against packet loss. We devise a simple strategy to successively approximate/quantize CS coefficients, allowing for an efficient incremental transmission of CS coded data. Tests show that the proposed successive approximation scheme provides rate allocation adaptivity and flexibility with a minimum rate-distortion performance penalty.
Rapid Measurement of Soybean Seed Viability Using Kernel-Based Multispectral Image Analysis
Authors: Baek Insuck , Kusumaningrum Dewi , Kandpal Lalit Mohan , Lohumi Santosh , Mo Changyeun , Kim Moon S. , Cho Byoung-Kwan
Published: January 2019

Viability is an important quality factor influencing seed germination and crop yield. Current seed-viability testing methods rely on conventional manual inspections, which use destructive, labor-intensive and time-consuming measurements. The aim of this study is to distinguish between viable and nonviable soybean seeds, using a near-infrared (NIR) hyperspectral imaging (HSI) technique in a rapid and nondestructive manner. The data extracted from the NIR–HSI of viable and nonviable soybean seeds were analyzed using a partial least-squares discrimination analysis (PLS-DA) technique for classifying the viable and nonviable soybean seeds. Variable importance in projection (VIP) was used as a waveband selection method to develop a multispectral imaging model. Initially, the spectral profile of each pixel in the soybean seed images was subjected to PLS-DA analysis, which yielded a reasonable classification accuracy; however, the pixel-based classification method was not successful for high accuracy detection for nonviable seeds. Another viability detection method was then investigated: a kernel image threshold method with an optimum-detection-rate strategy. The kernel-based classification of seeds showed over 95% accuracy even when using only seven optimal wavebands selected through VIP. The results show that the proposed multispectral NIR imaging method is an effective and accurate nondestructive technique for the discrimination of soybean seed viability.
A Self-Adaptive 1D Convolutional Neural Network for Flight-State Identification
Authors: Chen Xi , Kopsaftopoulos Fotis , Wu Qi , Ren He , Chang Fu-Kuo
Published: January 2019

The vibration of a wing structure in the air reflects coupled aerodynamic–mechanical responses under varying flight states that are defined by the angle of attack and airspeed. It is of great challenge to identify the flight state from the complex vibration signals. In this paper, a novel one-dimension convolutional neural network (CNN) is developed, which is able to automatically extract useful features from the structural vibration of a recently fabricated self-sensing wing through wind-tunnel experiments. The obtained signals are firstly decomposed into various subsignals with different frequency bands via dual-tree complex-wavelet packet transformation. Then, the reconstructed subsignals are selected to form the best combination for multichannel inputs of the CNN. A swarm-based evolutionary algorithm called grey-wolf optimizer is utilized to optimize a set of key parameters of the CNN, which saves considerable human efforts. Two case studies demonstrate the high identification accuracy and robustness of the proposed method over standard deep-learning methods in flight-state identification, thus providing new perspectives in self-awareness toward the next generation of intelligent air vehicles.
Deep RetinaNet-Based Detection and Classification of Road Markings by Visible Light Camera Sensors
Authors: Hoang Toan , Nguyen Phong , Truong Noi , Lee Young , Park Kang
Published: January 2019

Detection and classification of road markings are a prerequisite for operating autonomous vehicles. Although most studies have focused on the detection of road lane markings, the detection and classification of other road markings, such as arrows and bike markings, have not received much attention. Therefore, we propose a detection and classification method for various types of arrow markings and bike markings on the road in various complex environments using a one-stage deep convolutional neural network (CNN), called RetinaNet. We tested the proposed method in complex road scenarios with three open datasets captured by visible light camera sensors, namely the Malaga urban dataset, the Cambridge dataset, and the Daimler dataset on both a desktop computer and an NVIDIA Jetson TX2 embedded system. Experimental results obtained using the three open databases showed that the proposed RetinaNet-based method outperformed other methods for detection and classification of road markings in terms of both accuracy and processing time.
DeepMoCap: Deep Optical Motion Capture Using Multiple Depth Sensors and Retro-Reflectors
Authors: Chatzitofis Anargyros , Zarpalas Dimitrios , Kollias Stefanos , Daras Petros
Published: January 2019

In this paper, a marker-based, single-person optical motion capture method (DeepMoCap) is proposed using multiple spatio-temporally aligned infrared-depth sensors and retro-reflective straps and patches (reflectors). DeepMoCap explores motion capture by automatically localizing and labeling reflectors on depth images and, subsequently, on 3D space. Introducing a non-parametric representation to encode the temporal correlation among pairs of colorized depthmaps and 3D optical flow frames, a multi-stage Fully Convolutional Network (FCN) architecture is proposed to jointly learn reflector locations and their temporal dependency among sequential frames. The extracted reflector 2D locations are spatially mapped in 3D space, resulting in robust 3D optical data extraction. The subject’s motion is efficiently captured by applying a template-based fitting technique on the extracted optical data. Two datasets have been created and made publicly available for evaluation purposes; one comprising multi-view depth and 3D optical flow annotated images (DMC2.5D), and a second, consisting of spatio-temporally aligned multi-view depth images along with skeleton, inertial and ground truth MoCap data (DMC3D). The FCN model outperforms its competitors on the DMC2.5D dataset using 2D Percentage of Correct Keypoints (PCK) metric, while the motion capture outcome is evaluated against RGB-D and inertial data fusion approaches on DMC3D, outperforming the next best method by 4.5 % in total 3D PCK accuracy.
Visual-Acoustic Sensor-Aided Sorting Efficiency Optimization of Automotive Shredder Polymer Residues Using Circularity Determination
Authors: Huang Jiu , Xu Chaorong , Zhu Zhuangzhuang , Xing Longfei
Published: January 2019

To reduce the emissions and weight of vehicles, manufacturers are incorporating polymer materials into vehicles, and this has increased the difficulty in recycling End-of-Life vehicles (ELVs). About 25–30% (mass) of an ELV crushed mixture is the unrecyclable material known as automotive shredder residues (ASRs), and most of the vehicle polymers are concentrated in this fraction. Thus, these vehicle polymers are conventionally disposed of in landfills at a high risk to the environment. The only way to solve this problem is through the development of a novel separation and recycling mechanism for ASRs. Our previous research reported a novel sensor-aided single-scrap-oriented sorting method that uses laser-triangulation imaging combined with impact acoustic frequency recognition for sorting crushed ASR plastics, and we proved its feasibility. However, the sorting efficiencies were still limited, since, in previous studies, the method used for scrap size determination was mechanical sieving, resulting in many deviations. In this paper, a new method based on three-dimensional (3D) imaging and circularity analysis is proposed to determine the equivalent particle size with much greater accuracy by avoiding the issues that are presented by the irregularity of crushed scraps. In this research, two kinds of commonly used vehicle plastics, acrylonitrile-butadiene-styrene (ABS) and polypropylene (PP), and their corresponding composite materials, acrylonitrile-butadiene-styrene/polycarbonate (ABS/PC) and polypropylene/ethylene-propylene-diene-monomer (PP/EPDM), were studied. When compared with our previous study, with this new method, the sorting efficiency increased, with PP and PP/EPDM and ABS and ABS/PC achieving about 15% and 20% and 70% and 90%, respectively. The sorting efficiency of ASR polymer scraps can be optimized significantly by using sensor-aided 3D image measurement and circularity analysis.
City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts
Authors: Elbery Ahmed , Rakha Hesham
Published: January 2019

Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS technology, which is expected to reduce vehicle fuel/energy consumption and pollutant emissions by routing drivers through the most environmentally friendly routes. To compute these routes, the FB-ECO utilizes VANET communication to update link costs in real-time, based on the experiences of other vehicles in the system. In this paper, we study the impact of vehicular communication on FB-ECO navigation performance in a large-scale real network with realistic calibrated traffic demand data. We conduct this study at different market penetration rates and different congestion levels. We start by conducting a sensitivity analysis of the market penetration rate on the FB-ECO system performance, and its network-wide impacts considering ideal communication. Subsequently, we study the impact of the communication network on system performance for different market penetration levels, considering the communication system. The results demonstrate that, for market penetration levels less than 30%, the eco-routing system performs adequately in both the ideal and realistic communication scenarios. It also shows that, for realistic communication, increasing the market penetration rate results in a network-wide degradation of the system performance.
Autonomous Exploration for Radioactive Hotspots Localization Taking Account of Sensor Limitations
Authors: Ardiny Hadi , Witwicki Stefan , Mondada Francesco
Published: January 2019

Effective radioactive hotspot localization and detection is limited by sensor characteristics (i.e., the long acquisition time and poor angular resolution AR of a gamma camera) that significantly degrade the performance of autonomous exploration in terms of the completion time and accuracy. The goal of this research is to study effective exploration algorithms that take into account these specific sensor limitations. These exploration algorithms are adapted and implemented based on behaviour-based and multi-criteria decision making MCDM approaches on an autonomous robot. The algorithms were also tested in simulation and validated by experiments performed on a real robot. According to the results, the algorithms demonstrate the ability to mitigate the unfavourable effects of the limitations.
SDVL: Efficient and Accurate Semi-Direct Visual Localization
Authors: Perdices Eduardo , Cañas José María
Published: January 2019

Visual Simultaneous Localization and Mapping (SLAM) approaches have achieved a major breakthrough in recent years. This paper presents a new monocular visual odometry algorithm able to localize in 3D a robot or a camera inside an unknown environment in real time, even on slow processors such as those used in unmanned aerial vehicles (UAVs) or cell phones. The so-called semi-direct visual localization (SDVL) approach is focused on localization accuracy and uses semi-direct methods to increase feature-matching efficiency. It uses inverse-depth 3D point parameterization. The tracking thread includes a motion model, direct image alignment, and optimized feature matching. Additionally, an outlier rejection mechanism (ORM) has been implemented to rule out misplaced features, improving accuracy especially in partially dynamic environments. A relocalization module is also included but keeping the real-time operation. The mapping thread performs an automatic map initialization with homography, a sampled integration of new points and a selective map optimization. The proposed algorithm was experimentally tested with international datasets and compared to state-of-the-art algorithms.
Dynamic Load Balancing of Software-Defined Networking Based on Genetic-Ant Colony Optimization
Authors: Xue Hai , Kim Kyung Tae , Youn Hee Yong
Published: January 2019

Load Balancing (LB) is one of the most important tasks required to maximize network performance, scalability and robustness. Nowadays, with the emergence of Software-Defined Networking (SDN), LB for SDN has become a very important issue. SDN decouples the control plane from the data forwarding plane to implement centralized control of the whole network. LB assigns the network traffic to the resources in such a way that no one resource is overloaded and therefore the overall performance is maximized. The Ant Colony Optimization (ACO) algorithm has been recognized to be effective for LB of SDN among several existing optimization algorithms. The convergence latency and searching optimal solution are the key criteria of ACO. In this paper, a novel dynamic LB scheme that integrates genetic algorithm (GA) with ACO for further enhancing the performance of SDN is proposed. It capitalizes the merit of fast global search of GA and efficient search of an optimal solution of ACO. Computer simulation results show that the proposed scheme substantially improves the Round Robin and ACO algorithm in terms of the rate of searching optimal path, round trip time, and packet loss rate.
Preliminary Phytochemical Analysis of Berberis goudotii Triana & Planch. ex Wedd. (Berberidaceae) with Anticariogenic and Antiperiodontal Activities
Authors: Sequeda-Castañeda Luis , Muñoz-Realpe Camila , Celis-Zambrano Crispín , Gutiérrez-Prieto Sandra , Luengas-Caicedo Pilar , Gamboa Fredy
Published: January 2019

Berberis goudotii is an endemic Colombian plant found in the paramo ecosystem. It has been used in food preparation and as a medicinal plant for diverse treatments. Additionally, it is used as a mouthwash to strengthen the gums and combat throat irritations and periodontitis. The present research evaluated Berberis goudotii aerial parts extract and fractions antimicrobial activities. Ultrasonic-assisted extraction was used to attain total ethanol-water extract. Solid-liquid fractionation was used to obtain hexane fraction. The residue was dispersed in water and liquid-liquid fractionation was carried-out to acquire dichloromethane, butanol and water fractions. Preliminary phytochemical analysis was performed on total extract and phenol, polyphenol, flavonoid, and proanthocyanidin, while tannin content was quantified. Antimicrobial activity assessment was performed by agar diffusion method using disks and wells employing Ceftazidime as a positive control against Streptococcus mutans, Streptococcus sobrinus, Lactobacillus acidophilus, Lactobacillus casei, Porphyromonas gingivalis, Prevotella intermedia and Fusobacterium nucleatum. Antimicrobial activity was determined as relative percentage inhibition (RPI), minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Phenols (92.5 ± 7.7 mg GA/10 g), polyphenols (87.7 ± 8.1 mg PG/10 g) and tannins (44.1 ± 4.3 mg PG/10 g) were among the highest secondary metabolites observed. Total extract presented an MBC of 1.0 µg/µL against cariogenic bacteria (Streptococcus mutans and Streptococcus sobrinus) and 0.12 µg/µL against bacteria associated with periodontal disease (Porphyromonas gingivalis, Prevotella intermedia and Fusobacterium nucleatum). Butanol and hexane fractions showed antiperiodontal activity with MBC of 0.12 and 1.0 µg/µL, respectively. In conclusion, Berberis goudotii total extract demonstrated antimicrobial activity against cariogenic and periodontal microorganisms, on the other hand, hexane and butanol fractions displayed antiperiodontal activity.
On the Road to Sustainability: Implementation of the 2030 Agenda Sustainable Development Goals (SDG) in Poland
Authors: Raszkowski Andrzej , Bartniczak Bartosz
Published: January 2019

The purpose of the study is to determine the implementation status of the 2030 Agenda sustainable development goals (SDG) in Poland. The current situation in the country is characterized in the introduction, with particular emphasis on the socio-economic situation, economic growth, sustainable development, crucial strategic documents, development policies, non-governmental organizations and good governance. The next part of the article presents the selected for analyses indicators, which monitor the implementation of SDG at the national level (National SDG indicators). The study covers the period 2010–2016. In terms of the research methodology, the dynamic analysis methods were used, i.e., individual dynamics indexes (fixed-base and chain type). The average rate of particular phenomena changes over time was also determined. The data for calculations were retrieved from Statistics Poland resources. The article provides recommendations regarding the effective implementation of SDG in Poland in the years to come. The research results showed that the implementation status of SDG is satisfactory. In the case of 57 indicators out of the 73 analysed, the direction of expected changes was positive; thus the country remains on the right path towards sustainable development. Among the diagnosed problems the following can be listed: obesity, civilization diseases, lower income, government expenditure and R&D outlays in agriculture, fewer adults participating in education, gender pay gap, lower revenues from selling innovative products, unfavourable ratio of disposable income in rural areas against the city, unsatisfactory quality of the law-making, relatively low percentage of energy from renewable sources in transport and land requiring reclamation.