Carbon nanofibers: Synthesis, characterization, and electrochemical properties

Carbon nanofibers (CNFs) have been synthesized by co-catalyst deoxidization process by a reaction between C₂H₅OC₂H₅, Zn and Fe powder at 650 °C for 10 h. These nanofibers exhibit diameters of ∼80 nm and lengths ranging from several micrometers to tens of micrometers. X-ray diffraction, Raman spectroscopy, and high-resolution transmission electron microscopy indicate that as-prepared CNFs possess low graphitic crystallinity. The resultant CNFs as electrode shows capacity of ∼220 mAh/g and high reversibility with little hysteresis in the insertion/deintercalation reactions of lithium-ion. In addition, the possible growth of CNFs is discussed.     

Alcohol consumption detection through behavioural analysis using intelligent systems

We describe in this paper a new methodology for blood alcohol content (BAC) estimation of a subject. Rather than using external devices to determine the BAC value of a subject, we perform a behaviour analysis of this subject using intelligent systems. We monitor the user’s actions in an ordinary task and label those data to various measured BAC values. The obtained data-set is then used to train learning systems to detect alcoholic consumption and perform BAC estimation. We obtain good results on a mono-user base, and lower results with multiple users. We improve the results by combining multiple classifiers and regression algorithms.     

SiO_2对低温液相法制备锐钛型TiO_2/SiO_2纳米复合膜性能的影响

采用浸渍提拉法在玻璃表面制得SiO2/TiO2纳米复合膜,筛选出SiO2∶TiO2优化摩尔比为0.1∶1。结果表明,加入SiO2可有效提高TiO2膜层均匀性,降低晶粒直径,纳米复合膜对甲基橙溶液光催化降解率为38.58%,光照30min后膜接触角为5(°),纳米膜与玻璃之间附着力达到1级,且对各类介质均具有良好的耐蚀性。     

A new core–shell type fluorinated acrylic and siliconated polyurethane hybrid emulsion

A novel core–shell type fluorinated acrylic and siliconated polyurethane (FSiPUA) hybrid emulsion was prepared by seeded emulsion polymerization using siliconated polyurethane (SiPU) as a seed and forming the structure with SiPU as a shell and the copolymer of butyl acrylate (BA) with 2,2,2-trifluoroethylmethacrylate (TFEMA) as a core. SiPU was synthesized using isophorone diisocyanate (IPDI), polytetramethylene ether glycol (PTMG), polypropylene glycol (PPG), dihydroxybutyl-terminated polydimethylsiloxane (PDMS), dimethylol propionic acid (DMPA), 1,6-hexanediol (HDO) and triethylamine (TEA). The contents of siloxane and fluorine were determined according to the feed ratio. Fourier transform infrared spectroscopy (FTIR) was used to identify the chain structure of SiPU and FSiPUA. Investigation of transmission electron microscopy (TEM) confirmed the core–shell structure of FSiPUA emulsion and gave the particle size at about 50 nm. The measurement results of water contact angles and the solvent absorptions in water and n-octane for cured films showed that the water and the oil repellency for FSiPUA had been improved significantly with a suitable content of fluorine and siloxane.     

PVA-based activated carbon fibers with lotus root-like axially porous structure

A novel method was developed for the fabrication of activated carbon fiber (ACF) with wet spinning polyvinyl alcohol (PVA) fibers as the precursors. Through a combination of preoxidation, dehydration, carbonization and activation under a certain tension, PVA-based ACFs (PVA-ACFs) with high yields and good mechanical properties were obtained. The surface and cross-section morphologies, pore structures, surface geometries, surface functional groups and crystal structures of the PVA-ACFs were characterized using field emission scanning electron microscopy, low temperature nitrogen adsorption, Fourier transformed infrared spectrophotometry, X-ray photoelectron spectroscopy and X-ray power diffraction. All the PVA-ACF samples prepared had lotus root-like axially meso- and macroporous structures with the domination of micropores. Fractal geometries of PVA-ACFs deduced from nitrogen adsorption isotherms indicates that capillary force dominated in the interactions between nitrogen and the PVA-ACFs. The surface functional groups of the PVA-ACFs depend on the activating agents. Graphitoidal crystal structures were observed for the PVA-ACFs. The small crystal size and short range ordering between the crystallites ensured a high specific surface area of the PVA-ACFs.     

Multi-scale patch-based sparse appearance model for robust object tracking

When objects undergo large pose change, illumination variation or partial occlusion, most existing visual tracking algorithms tend to drift away from targets and even fail to track them. To address the issue, in this paper we propose a multi-scale patch-based appearance model with sparse representation and provide an efficient scheme involving the collaboration between multi-scale patches encoded by sparse coefficients. The key idea of our method is to model the appearance of an object by different scale patches, which are represented by sparse coefficients with different scale dictionaries. The model exploits both partial and spatial information of targets based on multi-scale patches. Afterwards, a similarity score of one candidate target is input into a particle filter framework to estimate the target state sequentially over time in visual tracking. Additionally, to decrease the visual drift caused by frequently updating model, we present a novel two-step object tracking method which exploits both the ground truth information of the target labeled in the first frame and the target obtained online with the multi-scale patch information. Experiments on some publicly available benchmarks of video sequences showed that the similarity involving complementary information can locate targets more accurately and the proposed tracker is more robust and effective than others.     

A multi-document summarization system based on statistics and linguistic treatment

The massive quantity of data available today in the Internet has reached such a huge volume that it has become humanly unfeasible to efficiently sieve useful information from it. One solution to this problem is offered by using text summarization techniques. Text summarization, the process of automatically creating a shorter version of one or more text documents, is an important way of finding relevant information in large text libraries or in the Internet. This paper presents a multi-document summarization system that concisely extracts the main aspects of a set of documents, trying to avoid the typical problems of this type of summarization: information redundancy and diversity. Such a purpose is achieved through a new sentence clustering algorithm based on a graph model that makes use of statistic similarities and linguistic treatment. The DUC 2002 dataset was used to assess the performance of the proposed system, surpassing DUC competitors by a 50% margin of f-measure, in the best case.     

A new approach of audio emotion recognition

A new architecture of intelligent audio emotion recognition is proposed in this paper. It fully utilizes both prosodic and spectral features in its design. It has two main paths in parallel and can recognize 6 emotions. Path 1 is designed based on intensive analysis of different prosodic features. Significant prosodic features are identified to differentiate emotions. Path 2 is designed based on research analysis on spectral features. Extraction of Mel-Frequency Cepstral Coefficient (MFCC) feature is then followed by Bi-directional Principle Component Analysis (BDPCA), Linear Discriminant Analysis (LDA) and Radial Basis Function (RBF) neural classification. This path has 3 parallel BDPCA + LDA + RBF sub-paths structure and each handles two emotions. Fusion modules are also proposed for weights assignment and decision making. The performance of the proposed architecture is evaluated on eNTERFACE’05 and RML databases. Simulation results and comparison have revealed good performance of the proposed recognizer.     

Research on the measure method of complaint theme influence on online social network

Consumer complaints on online social network quickly become online groups complaints through many people’s aggregation and looking on, interaction and word-of-mouth communication. Therefore, assessing and managing online complain influence has become a new problem for enterprise to listen to and manage online group complaints. This paper analyzed the complaint information feature of consumer group on online social network, from three-dimensional perspective of complaint text’s quality, transmission timeliness and user interaction degree. We built the influence measure model of online complaint theme based on entropy weight model by monitoring and analyzing real-time the static and dynamic properties of complaint information, explored the measure method of complaint theme influence, employed empirical method to verify the validity and provided scientific decision-making tools and methods for enterprise listening to and managing online group complains.