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JFBI -> 2014, Volume 7 Issue 4, 17 December 2014  
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Fabrication and Characterization of Spongy Porous Silk Fibroin Materials Crosslinked by Genipin
Yiyu Wang, Xinyu Wang, Junhua Zhang, Mingzhong Li
JFBI. 2014, 7 (4): 469-478.   DOI: doi:10.3993/jfbi12201401
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The porous Silk Fibroin (SF) scaffolds crosslinked by Genipin (GP) were prepared by freeze-drying. The different amount of GP were added in different concentrations of SF solutions. Compared to the uncross- linked porous SF scaffolds, the GP crosslinked scaffolds were insoluble and showed uniform pores and porosity. The SF scaffolds, with average pore size 39-167 m and porosity 49-71%, could be obtained by changing concentrations of fibroin solution. When the concentration of fibroin increased, the pore size diminished. The fourier transform-infrared (FT-IR) results revealed that GP could react with the -NH2 groups on the side chains of SF macromolecules to form inter- and intro-molecular covalent bonds. The FT-IR, X-ray Diffraction (XRD) and Differential Scanning Calorimetry (DSC) results also showed that the crystallinity of SF scaffold crosslinked by GP was increased slightly while the thermal stability was improved. This new fabrication way provided the basis theory for producing scaffolds with reasonable structure.
Hierarchical Analysis Method and Model Based Data of Controlling Parts of the Body for Clothing
Xiaomei Shang, Xiaoyu Xing, Peipei Gao
JFBI. 2014, 7 (4): 479-494.   DOI: 10.3993/jfbi12201402
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In order to study the accuracy of human measurement data more systematically, the analytic hierarchy model was established to evaluate the degree of measurement diffculty. Based on the manual measurement experiment, we extracted and analyzed the data from different angles, such as the proficiency of work, parts of human body, error correcting frequency and single factor. The three factors, diffculty of recognizing the defined points, dimension of the moving points and measuring path, are used as the standard of criterion level. The results showed that the structure of the body's parts of is the key to producing the measurement di±culty and the diffculty of recognizing the deffned points is the most. Besides, shoulder width is the most diffcult part to measure and the chest circumference is the least.
A Class of P Systems for the Matrix Multiplication
Lisha Han, Laisheng Xiang, Xiyu Liu
JFBI. 2014, 7 (4): 495-505.   DOI: 10.3993/jfbi12201403
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P system is a computing model that imitates a natural process that occurs at a cellular level where all objects evolve in a maximal parallelism and distributed manner. Recent results show that it could be used to solve some problems for less computation time. In this paper, to obtain another new application of P systems, a class of P system for the matrix multiplication with integer numbers is proposed, which provides new ideas and methods for the parallel problem solving in today's big data environment. Firstly, a P system is constructed for matrix multiplication with integer numbers, and it is proven whether it is feasible through a simple example. This is a new attempt in applications of membrane computing, which gives a more effective method to implement the operation than the existing other results.
Performance Comparison of Optimization Methods for Medical Image Registration
Meisen Pan, Jianjun Jiang, Fen Zhang, Xia Fang
JFBI. 2014, 7 (4): 507-516.   DOI: 10.3993/jfbi12201404
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Show Abstract ( 52 )
In the process of medical image registration, the registration function (also so-called similarity metric) was taken as the objective function, and the multi-parameter optimization method as the tool for obtaining the optimal transformation parameters. In this paper, by the use of the mutual information as the registration function, the Powell method and the genetic algorithm were exerted to explore the optimal transformation parameters respectively, and their optimizing performances were evaluated and compared. The experimental results reveal that the Powell method can cater to both the mono- and multi-modality medical image registrations. Unfortunately, however, the genetic algorithm is not adopted for the medical image registration regardless of the registration accuracy or the running time and needs to be significantly improved.
The Research of Molded Bra Cup Inner Surface and Its Capacity
Chao Xing, Bo-an Ying, Xin Zhang, Yan Lu
JFBI. 2014, 7 (4): 517-526.   DOI: 10.3993/jfbi12201405
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Show Abstract ( 75 )
Different bra cup inner surface leads to different capacity and style in dress. As a result, it is important to consider inner surface and its capacity in bra cup designing. In this paper, molded cup with wires is viewed as the research subject: its 3D model is rebuilt in Geomagic Studio, and its capacity is defined and measured in Unigraphics. Then a wearing experiment is conducted where one model wears molded cup bras of same size but different inner surfaces to study bra push-up and upgrade function and by analyzing the difference between cup capacity and breast volume. The research result is that the bigger di®erence between cup capacity and breast, the greater its influence on breasts. Moreover, with similar total bra cup capacity, the push-up and upgrade functions of bra cups in different degrees are presented. Furthermore, molded bra cup is split to blocks and analyzed in order to examine the impact on different functions. There is a certain guiding principle to inner surface shape design of molded bra cup.
Effect of Compression Tights on Performance During Intense Pedalling Exercise
Xiaoqun Dai, Juanjuan Cai, Guodong Wang, A-ming Lu
JFBI. 2014, 7 (4): 527-533.   DOI: 10.3993/jfbi12201406
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The purpose of this study was to investigate the effect of wearing tights on performance while pedalling at high intensity. Eight male undergraduates majored in sports science volunteered to participate in the experiments. Subjects wearing Gradient Compression Tights (GCT) or loose pants as control condition (CONT), pedalled on the power bicycle-ergometer at 180W/60RPM till exhaustion. Surface EMG was recorded at the surface of Rectus Femoris (RF), Vastus Lateralis (VL), Biceps Femoris (BF) belly, Tibialis Anterior (TA) belly and Medial Gastrocnemius (GM) and the heart rate was also monitored. It was confirmed that the GCT exerted gradient pressure distribution on the surface of lower limbs. Such gradient pressure helped to increase the venous return and the heart output, resulted in relatively lower heart rate and longer pedalling duration. The EMG analysis showed significant effect on the average EMG (aEMG) and the Mean Power Frequency (MPF) caused by GCT. Based on a pattern of motor recruitment with the recurrent inhibition, it was speculated that the pressure might enhance the activity of inhibition interneurones, more Motor Units (MU) of low thresholds were inhibited. Due to the less contribution of low-frequency components, the aEMG was lower and the MPF was higher.
Complexity Analysis for Drinkers' EEG via Wavelet Entropy
Jiufu Liu, Guofu Mab, Zaihong Zhou, Zhengqian Wang, Haiyang Liu, Wenliang Liu, Chunsheng Liu, Zhong Yang
JFBI. 2014, 7 (4): 535-548.   DOI: 10.3993/jfbi12201407
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This paper investigates the influence of alcohol on brain complexity. Considering electroencephalogram (EEG) has the nonlinear dynamics characteristic of time-varying and non-stationary, we introduced the Wavelet Entropy (WE) analysis. We denoise EEG signal by using wavelet decomposition, then calculated the wavelet entropy of the denoised signal and analyzed the nonlinear complexity of the signal. The results shows that the EEG wavelet entropy of drinkers' is markedly greater than the EEG wavelet entropy of normal people's. The EEG complexity of drinkers' is higher and the brain of drinkers' is in a more chaotic state. In the case of three kinds of external stimulus, we can get the change rule of the normal people's and alcoholics' EEG, and then analyze the WE and the effects of alcohol on the brain through a long duration of time. The long-time excessive drinking causes damages to the nerve cells, which means the human brain consciousness becomes poor, and response is slow.
Preparation and Characterization of PANI/PVA Electrochromic Membrane
Xiangqin Wang, Binjie Xin, Jian Xu
JFBI. 2014, 7 (4): 549-559.   DOI: 10.3993/jfbi12201408
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A facile strategy for obtaining Polyaniline (PANI) composites was reported wherein the reaction is oxidation polymerization using Dodecylbenzene Sulfonic Acid (DBSA) as the initiator, Polyvinyl Alcohol (PVA) as the emulsifier, and the Ammonium Peroxydisulfate (APS) as the oxidizing agent. The structure and performance of PANI composites were investigated. The results indicated that PANI particles can be dispersed evenly in the PVA matrix, the conductivity and electrochemical properties of the PANI/PVA composites were affected by the protonic acid content, When n(DBSA)/n(AN) = 1.0 under the same condition, the conductivity of PANI membrane is up to 1.28 S/cm. From the FTIR spectrum, the characteristic peaks of PANI at 1459 cm¡1 and 1697 cm¡1 are attributed to the C = C stretching vibration peak of the quinone ring and the benzene ring and the C = N stretching vibration peak of the quinone ring. The asymmetric ECD of PANI/PVA composites with copper and silver fabrics have both three brilliant colors (green - blue - yellow primary colors).
Regression Analysis on Tie-dye Technique and Pattern Feature
Suqiong Liu, Huie Liang, Weidong Gao, Wei Xue, Ming Gu
JFBI. 2014, 7 (4): 561-571.   DOI: 10.3993/jfbi12201409
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Based on computer vision technology, we studied predictive method of tie-dye pattern information. We extracted the average value of HSV (hue, saturation, value) tri-component of valid tie-dye area, proportion of tie-dye white area and coarseness as pattern feature, and designed correlation analysis on tie-dye production process and pattern feature accordingly. The results showed that dye concentration and pattern feature are highly correlated and the speed is also an important indicator of the effect of tie- dye pattern. In view of tie-dye production speed, concentration process parameters and pattern feature linear regression analysis, the findings are as follows: there is a positive correlation between process parameters and H, S component mean; process parameters negatively correlate with V component mean and proportion of tie-dye white area and coarseness; R-Squared values of prediction model are greater than 0.5. The linear regression models can be used to predict tie-dye image pattern effects.
Analysis of Clothing Air Gap in a Protective Suit According to the Body Postures
Jiyoung Choi, Heejin Kim, Bora Kang, Yunja Nama, Min K. Chung, Hyunsook Jung, HaHaewan Lee
JFBI. 2014, 7 (4): 573-581.   DOI: 10.3993/jfbi12201410
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In dangerous working environments such as a Chemical, Biological and Radiological (CBR) exercise, a protective suit plays an important role to increase work efficiency as well as prevent fatal damages. Air gaps entrapped in protective suit play an especially important role in heat transfer. The distribution and size of air gaps depends on body motions. The study developed 8 representative body motions (stretching, walking, crawling, crouching, twisting, climbing and reaching, moving weights and lateral bending) of CBR exercises of which 2-4 static body postures per each motion were derived. 3D body scan was conducted on one male participant for the postures listed. Scanning was performed on both nude and dressed bodies to measure the distribution and size of air gaps between human body and clothing. As a result, curves and volume of the air gaps varied with the different postures. The results serve as the basic data to improve protective performance of current protective suit.
Development and Application of Thermoregulatory Manikin: A Review
Lina Zhai| Jun Li
JFBI. 2014, 7 (4): 583-594.   DOI: 10.3993/jfbi12201411
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Thermoregulatory manikin can simulate complex physiological human behaviors such as sweating, shivering and vasomotion which the human body uses in order to adapt to temperature changes in the environment. Thus, it serves as a better simulation for human responses in the thermal environment than traditional ones. This paper first discusses the limitations of traditional manikins then followed by a summary of suitable thermal physiological models which have been implemented on manikins. A review of the development and application of thermoregulatory manikin is made by comparing research achievements of different research institutes. Currently, the thermal manikin system controlled by thermal physiological model has yet to be matured, which needs further validation before laboratory applications.
Digital Printing of Enzymes on Textile Substrates as Functional Materials
Navdeep Bal, Shadi Houshyar, Yuan Gao, Ilias Louis Kyratzis, Rajiv Padhye, Rajkishore Nayak
JFBI. 2014, 7 (4): 595-602.   DOI: 10.3993/jfbi12201412
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Recently, there have been significant developments in inkjet printing for applications in various fields such as medicine, biomaterials and sensors. In this research, enzymes like horseradish peroxidase (HRP) and glucose oxidase (GOx) were directly printed by inkjet printer onto flexible textile fabric in predefined patterns to produce a functional material. The functionality of the printed enzymes (bioink) was investigated by chemical reaction after printing fresh and stored bio-ink in a digital printer. The results indicated that these enzymes can be effectively printed individually or in combination, which retains their functionality after printing. Furthermore, HRP was coupled and printed with fluorescent group, the result confirmed that the printed enzyme was still active and retained its functionality despite the printing process. Hence, the digital printing technique can be used as a novel method for producing functional textiles for advanced applications in monitoring health and security.
Learning Block Group Sparse Representation Combined with Convolutional Neural Networks for RGB-D Object Recognition
Shuqin Tu, Yueju Xue, Jinfeng Wang, Xiaolin Huang, Xiao Zhang
JFBI. 2014, 7 (4): 603-613.   DOI: 10.3993/jfbi12201413
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RGB-D (Red, Green and Blue-Depth) cameras are novel sensing systems that can improve image recognition by providing high quality color and depth information in computer vision. In this paper we propose a model to study feature representation of combined Convolutional Neural Networks (CNN) and Block Group Sparse Coding (BGSC). Firstly, CNN is used to extract low-level features from raw RGB- D images directly by applying unsupervised algorithm. Then, BGSC is used to obtain higher feature representation for classification by incorporating both the group structure for low-level features and the block structure for the dictionary in subsequent learning processes. Experimental results show that the CNN-BGSC approach has higher accuracy on a household RGB-D object dataset by linear predictive classifier than using Convolutional and Recursive Neural Networks (CNN-RNN), Group Sparse Coding (GSC), and Sparse Representation base Classification (SRC).
Skew Detection and Yarns Density Calculation for Woven Fabric
Junfeng Jing, Shan Liu, Lei Zhang, Pengfei Li
JFBI. 2014, 7 (4): 615-625.   DOI: 10.3993/jfbi12201414
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Automatic identification of fabric structure is a vital research according to the fabric texture. Due to the skewed phenomenon which is inevitable during the scanning process, Hough transform is utilized for skew detection. Then wavelet filter is proposed to separate warps from wefts to enhance the information in vertical and horizontal direction, respectively. Finally, the gray projection curve including peaks and valleys is obtained in warp and weft directions. According to the peaks, the yarns can be located and segmented apparently and the fabric density could be obtained. Experimental results show that the precision of skew detection could be controlled within 2 while the accuracy of yarns density detection can reach up to 100%, which demonstrate that the proposed method is effective in skew detection and fabric density calculation.
A Batch-mode Active Learning Method Based on the Nearest Average-class Distance (NACD) for Multiclass Brain-Computer Interfaces
Minyou Chen, Xuemin Tan, John Q.Gan, Li Zhang, Wenjuan Jian
JFBI. 2014, 7 (4): 627-636.   DOI: 10.3993/jfbi12201415
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In this paper, a novel batch-mode active learning method based on the nearest average-class distance (ALNACD) is proposed to solve multi-class problems with Linear Discriminate Analysis (LDA) classifiers. Using the Nearest Average-class Distance (NACD) query function, the ALNACD algorithm selects a batch of most uncertain samples from unlabeled data to improve gradually pre-trained classifiers' performance. As our method only needs a small set of labeled samples to train initial classifiers, it is very useful in applications like Brain-computer Interface (BCI) design. To verify the effectiveness of the proposed ALNACD method, we test the ALNACD algorithm on the Dataset 2a of BCI Competition IV. The test results show that the ALNACD algorithm offers similar classification results using less sample labeling effort than Random Sampling (RS) method. It also provides competitive results compared with active Support Vector Machine (active SVM), but uses less time than the active SVM in terms of the training.
Table of Content - JFBI 7.4
JFBI. 2014, 7 (4): 63701-63702.
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JFBI 7.4 -Cover page
JFBI. 2014, 7 (4): 63703-63704.
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ISSN 1940-8676
JFBI is Ei Indexed Journal
Editor-in-Chief: Prof. Yi Li
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