bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surface Following With An Rgb-D Vision-Guided Robotic System For Automated And Rapid Vehicle Inspection
Authors: Nakhaeinia Danial , Payeur Pierre , Chávez-Aragón Alberto , Cretu Ana-Maria , Laganière Robert , Macknojia Rizwan 
Published: February 2018

Abstract
This paper presents the design and integration of a vision-guided robotic system for automated and rapid vehicle inspection. The main goal of this work is to scan and explore regions of interest over an automotive vehicle while a manipulator’s end effector operates in close proximity of the vehicle and safely accommodates its curves and inherent surface obstacles, such as outside mirrors or door handles, in order to perform a series of close inspection tasks. The project is motivated by applications in automated vehicle inspection, cleaning, and security screening. In order to efficiently navigate the robotic manipulator along the vehicle’s surface within regions of interest that are selectively identified, an efficient and accurate integration of information from multiple RGB-D sensors and robotic components is proposed. The main components of the proposed approach include: automated vehicle category recognition from visual information; RGB-D sensors calibration; extraction of specific areas to inspect over the vehicle body, and path planning from an efficiently reconstructed 3D surface mesh to move the robotic arm along and in close proximity of the vehicle. The proposed multi-stage system developed merges all components to achieve rapid 3D profiling over a complex surface in order to fully automate the process of surface following for vehicles of various types and shapes. To validate the feasibility and effectiveness of the proposed method experiments are carried out with a 7-DOF manipulator navigating over automotive body panels
Non Invasive Estimation Of Blood Urea Concentration Using Near Infrared Spectroscopy
Authors: Ramasahayam Swathi , Chowdhury Shubhajit Roy 
Published: February 2018

Abstract
This paper details about the noninvasive estimation of Urea concentration in blood using near infrared spectroscopy (NIRS) and Artificial neural network based prediction model. The absorption spectrum of the urea has been studied experimentally in order to choose the wavelengths of peak absorption. For this purpose, IR absorption spectrum of 0.1M aqueous urea solution has been collected and analyzed in second overtone region of the near-infra red spectra using the Bruker tensor 27 FTIR spectrometer. Based on the theoretical analysis the optimal wavelength of sensor is found to be 995nm for obtaining proper Photo plethysmograph (PPG). The regression analysis has been carried out on PPG signal with the artificial neural networks for obtaining a prediction model for estimating the blood urea concentration. The mean square error ofprediction is found to be ± 2.23mg/dL.
Multi-Scale Compressed Sensing Based On Split Augmented Lagrangian Shrinkage Algorithm For Image Super-Resolution Reconstruction
Authors: Shu-yao Tian , Chun-hai Hu 
Published: February 2018

Abstract
This paper proposes a multi-scale compressed sensing algorithm in shearlet domain by exploiting discrete Shearlet transform which can optimally represent the images with edges. An image is decomposed by shearlet. The compressed sensing is deployed in each of the directional sub-bands of high frequency scales. And inverse measurement matrix is modified by the upsampling operator to enhance the resolution of image. In addition, the original image reconstructed by compressed sensing based on super-resolution can produce the low subbands with high frequency. And an split augmented lagrangian shrinkage algorithm is exploited for compressed sensing image reconstruction, which can improve reconstruction image quality and convergence rate. Experimental results has shown that the proposed method can reconstruct the image with less iterative time by using fewer samples, improve the computational efficiency as well as achieve the images with high quality
Iot-1-Pass-Security: L(One)-Pass Authenticated Key Agreement Protocol For Energy Constraint Iot Applications
Authors: Aliasgari Mehrdad , Chan Garrett , Mozumdar Mohammad 
Published: February 2018

Abstract
IoT data security is one of the core unresolved challenges in IoT community. Lack of resource-efficient authenticated secure key exchange methods among resource-constrained IoT devices makes man-in-the-middle attacks a serious vulnerability. In this regard, we propose 1(One) pass Authenticated Key Agreement (AKA) protocol for IoT applications. This protocol requires only one round of communication among the sender and receiver to establish a secure session, providing a balance between security (data confidentiality with integrity) and performance. We implemented and performed comprehensive power consumption and timing analysis of our implementation on Contiki platform to demonstrate the efficiency of the proposed protocol
Characterization Of Photodectors Using A Monochromator And A Broadband Light Source In The Xyz Color Space
Authors: V. J.-S. Botero , G. F.-E. López , B. J.-F. Vargas 
Published: February 2018

Abstract
Photodetectors are sensors, which respond to the electromagnetic radiation of the spectrum. Their spectral response depends on many factors of the manufacturing process, e.g. the type of diode that is used or, in some cases, the optical elements that are added to limit the response band. In this paper, we propose an experimental methodology to obtain the spectral response of a photodetector by constructing the characteristic curve using the monochromatic response. For this purpose, we use a broadband source as input of the monochromator to vary the wavelength each five nm. The characteristic curves of one commercial color sensor were obtained (including the loss) using the output ratio of the monochromator. Via the numerical expression of the response curve, it is possible to model the actual response of the photodetectors to known or simulated spectra of electromagnetic radiation, and thus to generalize photometric measurements. Previously we have demonstrated the importance of obtaining such measurements to study light sources. Finally, this newly developed method helps studying the behavior of a photodetector in detail; hence, it enables the derivation of photometric measurements from known data or simulations
Semantic Collaboration And Sensing As A Service In Semantic Web Of Things
Authors: Chen X. Y. , Li G. Y. 
Published: February 2018

Abstract
The intrinsic contradiction hidden in the Internet of things, which is the mismatching between the diversification of forms expressing the thing’s information and the insufficiency of understanding ability of the agents using the thing’s information, hinders its intelligent development. Adding a semantic annotation for the expression of thing’s information based on ontology will improve the ability to understand, to reason and to obtain information for the agents, and will essentially promote the Internet of things to “semantic web of things”. For semantic web of things, its open and dynamic natures inevitably determine it is an open service ecosystem, and whether the hyper world itself and the individual in their sub worlds are in continuous development and evolution, so the semantic web of things must be self-adaptive to provide semantic collaboration services. To achieve all, this is based on “sensing as a service”. From different points of view, such as dynamic space, service collaboration and web-based context management services, we analyze semantic collaboration mechanism. Respectively put forward self-adaptiveness formulas and self-adaptive support framework of semantic web of things, propose the definition and architecture of semantic web of things and present sensing as a service model. This paper discusses semantic coordination mechanism and key support technologies for semantic web of things, which lay a theory and technology foundation for subsequent semantic collaboration application schemas, and the application experiments, validation and evaluation of semantic collaboration support system
Novel Svdd-Based Algorithm For Moving Object Detecting And Tracking Under Dynamic Scenes
Authors: Wang Chunxiang , Xu Dongfang , Wang Yongqing 
Published: February 2018

Abstract
Object detecting and tracking is an important technique used in diverse applications of machine vision, and has made great progress with the prevalence of artificial intelligence technology, among which the detecting and tracking moving object under dynamic scenes is more challenging for high requirements on real-time performance and reliability. Essentially analyzing, object detecting and tracking need to classify the objects and background into two different categories according to different features, where the detecting and tracking drift caused by noisy background can be effectively handled by robust maximum margin classifier, such as one-class SVM. But the time and space complexities of traditional one-class SVM methods tend to be high, which limits its wide applications to various fields. Inspired by the idea proposed by Support Vector Data Description (SVDD), in this paper we present a novel SVDD-based algorithm to efficiently deal with detecting and tracking moving object under dynamic scenes. The experimental results on synthetic, benchmark data and real-world videos demonstrate the competitive performances of the proposed method
Weak GPS Acquisition Via Compressed Differential Detection Using Structured Measurement Matrix
Authors: Elango G.Arul , Sudha Gnanou Florence 
Published: February 2018

Abstract
Quality of the acquisition algorithm is the main criteria for assessment of the GPS receiver. Compressed sensing has been used recently in the GPS signal acquisition process to improve the acquisition sensitivity and find visible satellites in the two dimensional search space. In this paper, strategies for constructing the GPS Dictionary matrix using different measurement matrices are analyzed for weak signal conditions. Conventional acquisition methods use pure random or Bernoulli measurement matrices requiring huge storage memory and resulting in high computational cost for faithful sparse signal representation. Based on the restricted isometry and coherence properties, the Kronecker product of hybrid ‘L’ deterministic measurement matrix has been proposed for fast calculation and easy hardware implementation of the GPS acquisition module. Simulation results for weak signals of C/N0 25 dB-Hz show that the compressed sensing combined with post-correlation differential detection scheme has the ability to determine more number of visible satellites. It is inferred that using this approach, 92% probability of obtaining 1.2 times more visible satellites than the uncompressed data length of 8 msec is achieved with lower computation time and significant improvement in average post correlation SNR value of 0.84 dB is obtained for four visible satellites.
Selective Sensing Using Nanostructured Gas Sensors: A Review
Authors: Castelino Roshan , G Pramod N 
Published: February 2018

Abstract
Fabricating a sensor for a toxic gas like carbon monoxide has been a constant need in many domestic and industrial applications. Although many sensors are commercially available, research is focused on developing a selective sensor with higher sensitivity, selectivity and low operating temperature. This paper reviews the fabrication, comparison and evaluation of different nanostructured titanium dioxide sensors used in detection. After a brief description of the structural properties of, the article presents sensing mechanism in semiconductor metal oxide sensors. For a reducing agent like, the surface reactions result in the reduction of sensor resistance. The parameters associated with sensor performance are discussed. The article presents a summary of main research findings in this field. Nanostructured morphologies offer better sensing performance and selectivity. The improved performance due to nanostructured is highlighted. The review clarifies the specific role of for the future research.
Chemical Signals of Vector Beetle Facilitate the Prevalence of a Native Fungus and the Invasive Pinewood Nematode
Authors: ZHANG BIN , ZHANG WEI , LU MIN , AHMAD FAHEEM , TIAN HAOKAI , NING JING , LIU XIAOLONG , ZHAO LILIN , SUN JIANGHUA 
Published: February 2018

Abstract
In China, the invasive Bursaphelenchus xylophilus, the vector Monochamus alternatus beetle, and associated fungi exhibit a symbiotic relationship causing serious losses to pine forests. Although this complex system has been intensively investigated, the role of vector beetles on the development of associated fungi and their indirect contribution to the prevalence of pinewood nematode (PWN) is yet unknown. Here, three of the highly prevalent fungal species, viz., Sporothrix sp. 1, Ophiostoma ips, and Sporothrix sp. 2 were isolated from beetle chambers in diseased trees in Guangdong province, southeast China. Pairwise cultivation of isolated fungi demonstrated the dominance of Sporothrix sp. 1 over O. ips and Sporothrix sp. 2. On the other hand, two fatty acid ethyl esters (FAEE), ethyl palmitate (EP) and ethyl linoleate (EL), isolated from the body surface of the vector beetle enhanced the growth of Sporothrix sp. 1. When PWN were cultured on Sporothrix sp. 1, the fecundity and the body length were increased significantly as compared with when cultured on O. ips and Sporothrix sp. 1. Our results suggest that the vector beetles promote Sporothrix sp. 1 to occupy more niches by rapid growth and spread, which in turn better support PWN population, hence facilitate PWN pathogenicity in the invasive regions.
Mapping Poverty at the Level of Subregions in Poland Using Indirect Estimation
Authors: Szymkowiak Marcin , Młodak Andrzej , Wawrowski Łukasz 
Published: February 2018

AbstractThe European Survey on Income and Living Conditions (EU-SILC) is the basic source of information published by CSO (the Central Statistical Office of Poland) about the relative poverty indicator, both for the country as a whole and at the regional level (NUTS 1). Estimates at lower levels of the territorial division than regions (NUTS 1) or provinces (NUTS 2, also called ’voivodships’) have not been published so far. These estimates can be calculated by means of indirect estimation methods, which rely on information from outside the subpopulation of interest, which usually increases estimation precision. The main aim of this paper is to show results of estimation of the poverty indicator at a lower level of spatial aggregation than the one used so far, that is at the level of subregions in Poland (NUTS 3) using the small area estimation methodology (SAE), i.e. a model–based technique – the EBLUP estimator based on the Fay–Herriot model. By optimally choosing covariates derived from sources unaffected by random errors we can obtain results with adequate precision. A territorial analysis of the scope of poverty in Poland at NUTS 3 level will be also presented in detail4. The article extends the approach presented by Wawrowski (2014).
A New Estimator of Mean Using Double Sampling
Authors: Vadlamudi Kalyan Rao , Sedory Stephen A. , Singh Sarjinder 
Published: February 2018

Abstract
In this paper, we consider the problem of estimation of population mean of a study variable by making use of first-phase sample mean and first-phase sample median of the auxiliary variable at the estimation stage. The proposed new estimator of the population mean is compared to the sample mean estimator, ratio estimator and the difference type estimator for the fixed cost of the survey by using the concept of two-phase sampling. The magnitude of the relative efficiency of the proposed new estimator has been investigated through simulation study.
Relations for Moments of Progressively Type-II Right Censored Order Statistics From Erlang-Truncated Exponential Distribution
Authors: Malik Mansoor Rashid , Kumar Devendra 
Published: February 2018

Abstract
In this paper, we establish some new recurrence relations for the single and product moments of progressively Type-II right censored order statistics from the Erlang-truncated exponential distribution. These relations generalize those established by Aggarwala and Balakrishnan (1996) for standard exponential distribution. These recurrence relations enable computation of mean, variances and covariances of all progressively Type-II right censored order statistics for all sample sizes in a simple and efficient manner. Further an algorithm is discussed which enable us to compute all the means, variances and covariances of Erlang-truncated exponential progressive Type-II right censored order statistics for all sample sizes n and all censoring schemes (R
1, R
2,…, R
m), m < n. By using these relations, we tabulate the means and variances of progressively Type-II right censored order statistics of the Erlang-truncated exponential distribution.
Evaluation of COX-2 expression in renal cell carcinoma and its correlation with clinicopathological factors: a tissue microarray study
Authors: Ashour G.A.R , Said W 
Published: February 2018

AbstractObjectives: This study, aimed to evaluate the expression of COX-2 in renal cell carcinoma, and correlate it with different patient clinicopathological data, emphasizing on the role of COX-2 as a prognostic factor for renal cell carcinoma and to decide which cases more likely benefit from the targeted therapy later on.
Patients and Methods: The present series consisted of tissue samples obtained from 47 patients (30 patients were males and 17 were females). All the tumor samples were collected from the Pathology Department, Faculty of Medicine, Alexandria University during the period from July 2009 to November 2010. Archival paraffin-embedded renal cell carcinoma tissue samples were used to prepare tissue microarray blocks for immunohistochemical staining with COX-2 antibody. Marker expression was categorized for statistical analysis then correlated to clinicopathological variables.
Results: The histological types was significantly associated with COX-2 expression, with higher expression being more common in papillary and chromophobe renal cell carcinoma, the majority of these two types were in score 1 and 2 while majority of clear cell renal cell carcinoma had score 0 and 1.
Conclusion: The association of COX-2 marker was related to the histologic type of tumor; COX-2 expression study might provide prognostic information regarding tumor aggressiveness. These findings suggested a potential impact of COX-2 targeted therapy in the treatment of renal cell carcinoma with overexpressed COX-2 that needs further investigation.
Removal of humic acid from aqueous solution using polyacrylamide/chitosan semi-IPN hydrogel
Authors: Liu Zejun , Zhou Shaoqi 
Published: February 2018

Abstract
In this study, we provide the first documented removal of humic acid (HA) from aqueous solution using polyacrylamide/chitosan (PAAm/CS) semi-IPN hydrogel. The prepared semi-IPN hydrogel was characterized by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FT-IR). The factors effecting HA adsorption performance were individually tested, including initial pH, ionic strength, contact time, initial HA concentration, and temperature. The results indicated that semi-IPN hydrogel was successfully fabricated and can be applied in a wide pH range, from 3 to 9. Low ionic strength effectively enhanced the adsorption capacity. As the ionic strength increased, this enhancement was less obvious but still positive. The adsorption kinetics were fitted to a pseudo-first-order kinetic model, and the adsorption isotherm was described using the Sips isotherm model. The HA adsorption capacity increased with increasing temperature. The maximum adsorption capacity has the potential to attain 166.30 mg g−1, based on the Sips isotherm at 25 °C. Experiments demonstrated that the HA adsorption process can be primarily attributed to electrostatic interactions, and hydrogen bonding was also involved. Facile synthesis and good adsorptive performance indicate that semi-IPN hydrogel can be used for removing HA from water.
Modified powder activated carbon-catalyzed ozonation of humic acid: influences of chemical and textural properties
Authors: Feng Jing , Yang Yang , Chen Honglin , Zhang Xiaoming 
Published: February 2018

Abstract
A modification method that combines thermal and oxidation treatments was used to improve catalytic activity of activated carbon (AC) which catalyzed ozonation of the aquatic contaminant humic acid (HA). As a consequence of modifying virgin AC, modified AC (ACN2O2N2) had good catalytic performance for ozonation of HA. Apparent first-order rate constants (kapp) were ACN2O2N2 (7.88 × 10−3 s−1) &gt; virgin AC (3.28 × 10−3 s−1). This change was discussed in terms of three factors: textural property, graphitization degree, and surface chemical property. From analysis results, it was deduced that the surface chemical property (the concentration of surface groups) was the main factor that influenced catalytic activity. An increase in the concentration of hydroxyl groups on AC enhanced catalytic activity of AC in ozonation of HA. Effects of phosphate (both a ligand and a strong Lewis base) further confirmed that Lewis acid sites (hydroxyl groups) were the active centers for free radical reaction in catalytic ozonation of AC.
Microalgae cultivation for wastewater treatment and biogas production at Moscow wastewater treatment plant
Authors: Shchegolkova N. , Shurshin K. , Pogosyan S. , Voronova E. , Matorin D. , Karyakin D. 
Published: February 2018

Abstract
The process of cultivation of microalgae on purified and clarified wastewater of Kuryanovo wastewater treatment plants (KWWTP) was studied. The studies were conducted on monoculture (Scenedesmus quadricauda and Chlorella sorokiniana) and on polyculture, the composition of which was formed from microalgae present in the wastewater. The authors created and investigated the columnar photobioreactor (PBR), which acted as a pilot project on the purified and clarified water of KWWTP and allowed the removal of total nitrogen and phosphorus phosphates with an efficiency of up to 90%. The formation of a stable biocenosis from 22 species of algae (with 3–4 dominant species) and 31 species of zooplankton organisms belonging to six systematic subdivisions was recorded. The optimal retention time of the microalgae polyculture for the most effective wastewater treatment has been determined. The conducted studies have shown that the depth of decomposition of ashless matter and the ultimate biogas potential of untreated microalgae biomass is 15% lower than the corresponding values obtained with digestion of activated sludge, which necessitates studies in the field of pretreatment of algal biomass. The paper shows: connections between chlorophyll-a content, algal biomass and fluorescence index F0 and between biomass increment and Fv/Fm value.