bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Machine Vision System For Estimation Of Theaflavins And Thearubigins In Orthodox Black Tea
Authors: Akuli Amitava , Pal Abhra , Bej Gopinath , Dey Tamal , Ghosh Arunangshu , Tudu Bipan , Bhattacharyya Nabarun , Bandyopadhyay Rajib 
Published: February 2018

Abstract
Orthodox black tea quality depends upon the amount of certain organic compounds present and out of these, theaflavins (TF) and thearubigins (TR) are the most important ones While TF is responsible for attractive golden colour, increased brightness and astringency in tea liquor, TR is reddish brown, reduces the brightness of tea liquor and contribute mostly for the ashy taste of the liquor with minor improvement in astringency. The rapid estimation of TF and TR thus may resolve the problem of certain uncertainty or ambiguity that may arise during quality assessment of tea by the tea tasters. In this paper, a new method for rapid measurement of concentration of TF and TR is described using a machine vision system taking images of tea liquor and employing artificial neural networks (ANN). The results show good correlation of estimated values of TF and TR with the actual concentrations obtained using ultraviolet-visible spectrophotometer (UV-VIS)
Acoustic Emission Based Defects Monitoring Of Threedimensional Braided Composites Using Wavelet Network
Authors: Hua Su , Tianyuan Zhang , Ning Zhang 
Published: February 2018

Abstract
In order to effectively differentiate all kinds of defects inside the composites, this paper carries out testing on the internal defects of three-dimensional (3d) braided composites by use of acoustic emission nondestructive detecting technology. It puts forward the processing method for acoustic emission signals for the internal defects of three-dimensional braided composites based on wavelet neural network (WNN). This method does wavelet transformation on real-time collected acoustic emission signals, takes the characteristics of internal defect energy to be obtained as network input, selects the wavelet neural network (WNN) with “compact” type and realizes the recognition on the classification of micro cracks and pores of 3d braided composites
Design Of Smart Robot For Wrist Rehabilitation
Authors: Aabdallah Ismail Ben , Bouteraa Yassine , Rekik Chokri 
Published: February 2018

Abstract
Generally, the rehabilitation process needs a physical interactions between patients and therapists. Based on the principles governing such human-human interactions (HHI), the design of rehabilitation robots received several attempts in order to abstract the HHI in human-robot interaction (HRI). To achieve this goal, the rehabilitation robot should be smart and provides a useful and comprehensive platform to track the patient status. In this paper, a biofeedback-based high fidelity smart robot for wrist rehabilitation is designed. This robot is intended for repetitive exercises without therapist intervention. Hold the two sets of wrist movement: flexion/extension and radial/ulnar derivation. Distinguished by its compact mechanism design, the developed wrist rehabilitation robot (HRR) offers high stiffness with a total absence of any friction and backlash. Based on EMG signal, the smart robot can understand the patient pain degree. Two features extractions are used to estimate the pain level. A fuzzy logic controller is implemented in the LabVIEW-based human-machine interface (HMI) to determine the desired angle and velocity in real time. Parameters and results of each exercise can be stored and operated later in analysis and evolution of patient progress
Measurement and Control System for Thermosolar Plant and Performance Comparison Between Traditional and Nanofluid Solar Thermal Collectors
Authors: Visconti P. , Primiceri P. , Costantini P. , Colangelo G. , Cavalera G. 
Published: February 2018

Abstract
Aim of this work is the design of a programmable electronic system for monitoring the environmental parameters and managing the electrical functions of a thermo-solar plant. The designed control unit detects data from temperature and light sensors, processes acquired information and commands external equipments (pumps, electric valves and power supplies) in order to optimize plant performances and maximize efficiency and energy savings. Recently several researches, in the field of solar thermal energy production, have demonstrated that nanofluid-based solar collectors present higher conversion efficiency. In this context, the designed control unit can be used to detect their operation parameters in order to compare the performances of nanofluidbased solar collector with those of traditional one. The electronic experimental setup is capable to monitor, at the same time, the two different types of solar collector in similar environmental conditions and to show on touch screen display the detected performances. In order to have reference data, experimental measurements have been carried out by using traditional water and Al2O3-based nanofluid thermo solar collectors. The obtained experimental data showed the benefit in terms of efficiency in the use of nanofluid as heat transfer fluid in such a system.
Evaluation of Hybrid Trust Models Using Ant Colony Optimization in Wireless Sensor Networks
Authors: Kumar G. Edwin Prem , Baskaran K. , Blessing R. Elijah , Lydia M. 
Published: February 2018

Abstract
Wireless sensor networks (WSNs) are prone to various kinds of threats and are subjected to several constraints like energy, communication overhead and lifetime. Application of bio-inspired algorithms based trust models has shown significant improvement in the security mechanism of the wireless sensor networks. This paper presents a brief survey on application of Ant Colony Optimization (ACO) and significance of trust models in WSNs. ACO application in routing, increase in lifetime, energy efficiency, intrusion detection and security has been presented. The performance of three hybrid trust models is evaluated based on the path length, trust calculation and energy consumption using ACO.
Structural Desigh and Motion Analysis of Universal Mobile Quadruped Robot
Authors: Xiong Wang 
Published: February 2018

Abstract
According to bionics and simplified octopus structure, this paper designed a universal mobile quadruped robot and adopted Denavit-Hartenberg system to analyze the single leg kinematics of a robot, obtaining its kinematics equation. Also, through the method of separating variables, this paper solved its inverse kinematics and got the joint angle. A walking gait is planned and the joint angle of vertical pendulum stance phase and swing phase of the robot in walking are calculated. MATLAB is used to simulate the relevant joint angles of the robot, so as to analyze its movement change. Experimental results further verified the universal motion of robots.
A Novel Hybrid Localization Method for Wireless Sensor Network
Authors: Jun Wang , Fu Zhang , Tiansi Ren , Xun Chen , Gang Liu 
Published: February 2018

Abstract
Wireless sensor network is a kind of brand-new information acquisition platform, which is realized by the introduction of self-organizing and auto-configuration mechanisms. Node localization technology represents a crucial component of wireless sensor network. In this paper, a localization method based on kernel principal component analysis and particle swarm optimization back propagation algorithm is carefully discussed. First of all, taking KPCA as the front-end system to extract the main components of the localization information, and then regarding the nonlinear principal components extracted from distance vectors as the input samples, and meanwhile taking the coordinates of vertices in addition to the region boundary as the output samples, the PSO-BP neural network is trained to achieve the localization model. Finally the localization of unknown nodes can be estimated. The simulation experiment result showed that the method has high ability of stability and precision, and meets the practical need of localization.
A Real-time Pedestrian Detection System in Street Scene
Authors: Guo Ai-ying , Xu Mei-hua , Ran Feng , Wang Qi 
Published: February 2018

Abstract
Pedestrian detection is the key technology in Advanced Driver Assistant System (ADAS).Until recently, pedestrian detection, which is realized as the vehicle equipment, still doesn’t have the mature product. So, this thesis proposes a novel pedestrian detection system on board with the E-HOG (Histogram of Gradient) IP (intellectual property), can be used as the real time vehicle equipment. Three contributions are made in this thesis. Firstly, Sobel operator cascaded Uniform Local Binary Pattern (LBP) and E-HOG is the novel structure of pedestrian detection system. The Sobel operator gives the sliding step of Uniform LBP detection window, without using the results of LBP detection window. Through this operation, the detection speed will be improved. Second, the vehicle equipment of pedestrian detection is self-developed using FPGA as core devices. Third, E-HOG IP, which is promoted based on the HOG, can extract pedestrian or other objects feature. Without sacrifice of accuracy, this pedestrian detection on board deals with 30 fps (640x480 pixels) and can be used as the real-time detection system.
Research on Distributed Data Storage based on Information Processing Cloud
Authors: Qing-Yun LUO , Ling-Zhi ZHU , Yun-Jie CHAGN , Jin-Guo ZHAO , Wei-Sheng LIAO , Rui HE 
Published: February 2018

Abstract
Sensor network is a data-centric network, which provides data collection, storage and query services. Data storage and query is one of the hot spot in the research of sensor networks. In order to solve the problem of low efficiency of storage and query, high energy consumption in sensor networks, we put forward a scheme that storing distributed data of wireless sensor network based on information processing cloud. Information processing cloud is made up of a group of sensor nodes around the network center, which have the ability to absorb and process data from other nodes of sensor network which do not belong to the information processing cloud. The group of sensor nodes around the network center respond data query requests from anywhere of the network, and sensor nodes can be adjusted dynamically according to real situation, the cloud of nodes and non-cloud of nodes can be dynamically transformed as well. When non-cloud of sensor nodes store data or send query request, they only need to do centripetal movement, centrifugal movement or circumfusing movement. The analysis shows that the proposed scheme can simplify route algorithm of data storage and data query, and it also has less computation cost and storage cost than the existing schemes.
Quantitative Feedback Theory-Based Robust Control for a Spindle of Lathe Machine
Authors: Khairudin M. 
Published: February 2018

Abstract
This paper presents theoritical and experimental design of a robust control based on quantitative feedback theory (QFT) approach to control deepness variations on cutting process for a spindle of lathe machine. The dynamics of a spindle is uncertain and varying due to deepness variation on cutting process. Practical design steps are explained in which QFT based conditions are assembled to obtain a compensator and pre-filter gain to control a spindle. The robust controller show an advantage control the system under various cutting conditions. The performances of the proposed controller are evaluated in terms of input tracking capability of the spindle responses and speed responses of a spindle incorporating deepness on cutting process. Experimental results show that QFT based robust control provides the improvement of robustness and performances.
An Intelligent Feature Selection and Classification Method Based on Hybrid ABC–SVM
Authors: Li Jie , Zhang Qiuwen , Yongzhi Zhang , Chang Li , Jian Xiao 
Published: February 2018

Abstract
This paper presents a new approach to feature selection and classifcation based on support vector machine and hybrid artificial bee colony. The approach consists of two stages. At the first stage, this paper presented a hybrid artificial bee colony-based classifier model that combines artificial bee colony to improve classification accuracy with the most superior model parameter and features were selected from the original feature set. The classification accuracy and the feature subset provided by the SVM classifier are both considered to update the food source. Finally, the most superior features and optimal model parameter are fed into SVM to identify different class. The testing results verify the effectiveness of the method in extracting feature subset and pattern classification
AMI Based Sensing Architecture for Smart Grid in IPV6 Networks
Authors: Peng Wang , Fei Su , bohong Hu , wenpeng Luan 
Published: February 2018

Abstract
Advanced Metering Infrastructure (AMI) is a key part in the development of the smart grid, which integrates automatic meter reading, distribution automation, user data analysis, as well as realtime price adjustment functions. Existing AMI can offer good support for smart grid backbone. However, it still has some shortages when sensing the electric meter data acquisition, electric devices, and etc. Due to the vast number of meters, the use of IPv6 technology in AMI is an inevitable trend. Sensing architecture based on IPv6 can help AMI be aware of communication network topology and the access time of electrical devices, and calculate real-time electricity billing. Smart meter data is collected using cognitive architecture so that it would be more accurate and meaningful. In this paper, we firstly introduce the basic architecture of AMI, including master station system, smart meters and the key technologies of communication network. And then, for the existing AMI architecture, we analyze the current situation and challenges in the aspect of perception. Finally an AMI sensing architecture based on 6LowPAN and Mesh is proposed. Experiments show that the architecture can not only improve the accuracy of the meter data, but also sense the temporary access devices. As a result, the structure is feasible and could earn more commercial benifit.
A Blind Assessment Method of Image Compression Quality Based on Image Variance
Authors: Zhou Qun , Liu Xiongwei 
Published: February 2018

Abstract
The assessment of image compression result can not only evaluate the quality of image compression results and to a certain extent, can also find the advantages and drawbacks of various compression methods. At the same time, it can provide a reference for the compressed image restoration. Firstly, the classification and shortages of image quality assessment methods are presented. Then, several objective assessment methods usually used for image compression quality are introduced and the recent research progresses are shown. Finally, in view of the shortages of traditional image assessment methods and the existing blind assessment methods, based on image invariance, we propose a blind assessment method of image compression quality by considering the edge detail recovery and artifact removing. Compared with the traditional blind assessment methods, our method is simple in form and evaluation system is easily implemented. The experimental results also show that it is reasonable and effective.
Research of Dual Watermarking Technology for Digital Image
Authors: Yinglan Fang , Bing Han , Yongmei Zhang , Lin Tian 
Published: February 2018

Abstract
Digital image watermark has been studied as object. It analyzed the typical digital watermark algorithms based on the space domain and transform domain and key researched watermarking algorithm based on discrete wavelet transform. It has designed and improved blind watermarking algorithm and color image watermarking algorithm. Finally, based on the two improved watermarking algorithm, it has designed a dual watermarking algorithm. Both are separated but related. It authenticates dual watermarking algorithm in addition to subjective visual evaluation, but also use numerical objective evaluation and quantitative analysis. Experimental results show that this dual watermarking algorithm combines with robustness and concealment.
The Mesostigmatid Mite Protogamasellus mica, an Effective Predator of Free-Living and Plant-Parasitic Nematodes
Authors: Stirling Graham R. , Stirling A. Marcelle , Walter David E. 
Published: February 2018

Abstract

Protogamasellus mica was extracted from a sugarcane field in Australia and cultured on bacterial-feeding nematodes. Studies with various nematodes in laboratory arenas showed that one mite and its progeny reduced nematode numbers by between 26 and 50 nematodes/day. A bacterivore (Mesorhabditis sp.), a fungivore (Aphelenchus avenae), and two plant parasites (root-knot nematode, Meloidogyne javanica and root-lesion nematode, Pratylenchus zeae) were all reduced at much the same rate despite the fact that the nematodes are quite different in size and motility and belong to different trophic groups. When sugarcane was grown in the greenhouse for 8 wk, stunt nematode (Tylenchorhynchus annulatus), a plant parasite that feeds ectoparasitically on roots, was almost eliminated from pots inoculated with the mite, and numbers of microbivores and root-lesion nematode were markedly reduced. Huge reductions in nematode populations were also observed when mites were added to microcosms containing small quantities of defaunated soil. These results show that P. mica multiplies rapidly when nematodes are available as a food source and has the capacity to play a role in regulating populations of both plant-parasitic and free-living nematodes. Future research should focus on understanding the crop and soil management practices required to enable this mite and other predatory species to thrive.
Türkiye’deki Üstün Yetenekli Öğrencilerin Psikolojik Danışma ve Rehberlik İhtiyaçları
Authors: ALTUN Fatma , YAZICI Hikmet 
Published: February 2018

Bu çalışmanın temel amacı üstün
yetenekli tanısı alan öğrencilerin psikolojik danışma ve rehberlik (PDR)
alanında yaşadıkları sorunların ebeveyn görüşlerine dayalı olarak
belirlenmesidir. Ayrıca üstün yeteneklilerin PDR ihtiyaçlarında çocuğun yaş ve
cinsiyetinin etkileşiminin etkisi, ebeveynlerin cinsiyetleri ve eğitim
durumlarına göre algılanan problem durumlarında farklılaşma olup olmadığı da bu
çalışmanın alt amaçları arasındadır. Araştırma grubunu, Türkiye’nin 12
bölgesinde yer alan 24 BİLSEM’e kayıtlı öğrencilerin ebeveynleri arasından
seçilen 606 kişi (320 Anne, 286 Baba) oluşturmaktadır. Araştırmanın verileri
Üstün Yetenekliler İçin Problem Tarama Envanteri ve Bilgi Formu ile
toplanmıştır. Elde edilen bulgulara göre; ebeveynler çocuklarının kişisel
özellikleri, okul yaşantıları ve aile ilişkileri alanlarında belirgin sorunlar
yaşadıklarını ifade etmişlerdir. Öğrencilerin PDR hizmetlerine duydukları
ihtiyaçlar yaş ve cinsiyet etkileşimine
bağlı olarak farklılaşmaktadır. İhtiyaçların türü konusunda ebeveyn cinsiyetine
bağlı anlamlı farka rastlanmamışken, eğitim düzeyine dayalı fark tespit
edilmiştir. Bu çalışma ile
Türkiye’deki üstün yetenekli öğrencilerin PDR alanındaki öncelikli ihtiyaçları
tespit edilmiş ve bunların bazı değişkenlerde göre farklılaştığı saptanmıştır.
Spatio-temporal changes in evapotranspiration over China using GLEAM_V3.0a products (1980–2014)
Authors: Yang Xiuqin , Yong Bin , Yin Yixing , Zhang Yuqing 
Published: February 2018

Abstract
This study used land evapotranspiration (ET) values from 61 ChinaFLUX eddy covariance (EC) sites and water-balanced derived ET in ten basins to investigate the performance of Global Land Evaporation Amsterdam Model (GLEAM) V3.0a ET estimates (i.e., ETG) over China. We quantified the spatio-temporal characteristics of ETG and the impact of precipitation (P) and potential ET (ETP) on ETG. ETG was appropriate for estimating daily, seasonal, and annual ET rates. The mean annual ETG increased progressively from the northwest to southeast of China. Domain-averaged annual ETG over China was 421.90 mm year−1 during 1980 to 2014. The spatial patterns of ETG were in accordance with those of annual precipitation. Low ETG values occurred in the Northwest River Basin, and relatively high ET values were found across southern China. ETG showed the highest annual variation in the Northwest River Basin and low variation in the southwest region, which captured seasonal variations with maxima in summer and minima in winter. The inter-annual variation of annual ETG and ETP differed significantly from 1980 to 2014, yielding prominent spatial variability around −16.50 to 9.10 mm year−2 and −1.90 to 4.70 mm year−2, respectively. Annual ETG is correlated well with P and ETP at each site.
Comparative study on long term climate data sources over South Korea
Authors: Kim Dong-Ik , Han Dawei 
Published: February 2018

Abstract
Long term climate data are vitally important in reliably assessing water resources and water related hazards, but in-situ observations are generally sparse in space and limited in time. Although there are several global datasets available as substitutes, there is a lack of comparative studies about their suitability in different parts of the world. In this study, to find out the reliable century-long climate dataset in South Korea, we first evaluate multi-decadal reanalyses (ERA-20 cm, ERA-20c, ERA-40 and NOAA 20th century reanalysis (20CR)) and gridded observations (CRUv3.23 and GPCCv7) for monthly mean precipitation and temperature. In the temporal and statistical comparisons, CRUv3.23 and GPCCv7 for precipitation and ERA-40 for temperature perform the best, and ERA-20c and 20CR also indicate meaningful agreements. For ERA-20 cm, it has only a statistical agreement, but the mean has the difficulty in representing its ensemble. This paper also shows that the applicability of each dataset may vary by region and all products should be locally adjusted before being applied in climate impact assessments. These findings not only help to fill in the knowledge gaps about these datasets in South Korea but also provide a useful guideline for the applicability of the global datasets in different parts of the world.
Flakes Size-Dependent Optical and Electrochemical Properties of MoS2
Authors: Abdelaziz Aboelazm Eslam Atef , Mohammed Ali Gomaa Abdelgawad , Algarni Hamed , Chong Kwok Feng 
Published: February 2018

Background:
Molybdenum disulfide (MoS2) is a transition metal dichalcogenides and has
some interesting and promising properties. MoS2 has direct and indirect band gaps depending on its
crystalline structure. In addition, its sheets morphology makes it a good candidate for supercapacitor
applications.

Objective:
The aim of this work is to study the effect of MoS2 flakes size on its optical and electrochemical
properties.

Method:
MoS2 with different flakes sizes were prepared by exfoliation method. The exfoliation was
performed by sonication of MoS2 powder in N,N-Dimethylformamide followed by different centrifugation
speeds. UV-Vis spectra illustrated the optical energy gap was inversely proportional to
the MoS2 flakes size.

Results:
Absorption coefficient values indicated that the exfoliation reduced the number of layers.
Symmetric supercapacitor was made from two MoS2 electrodes and tested in 6 M KOH electrolyte.
The specific capacitance was found to be dramatically increased with decreasing flakes size (9.5 and
4.5 mF/cm2 for 0.26 and 0.98 µm flakes size, respectively).

Conclusion:
These findings recommend that MoS2 can be the excellent electrode material for supercapacitor.