Silhouette-based human action recognition using SAX-Shapes

Human action recognition is an important problem in Computer Vision. Although most of the existing solutions provide good accuracy results, the methods are often overly complex and computationally expensive, hindering practical applications. In this regard, we introduce the combination of time-series representation for the silhouette and Symbolic Aggregate approXimation (SAX), which we refer to as SAX-Shapes, to address the problem of human action recognition. Given an action sequence, the extracted silhouettes of an actor from every frame are transformed into time series. Each of these time series is then efficiently converted into the symbolic vector: SAX. The set of all these SAX vectors (SAX-Shape) represents the action. We propose a rotation invariant distance function to be used by a random forest algorithm to perform the human action recognition. Requiring only silhouettes of actors, the proposed method is validated on two public datasets. It has an accuracy comparable to the related works and it performs well even in varying rotation.     

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes.     

Attitudes towards mobile banking: are there any differences between users and non-users?

Extant research has focused on monitoring the behaviour of people who use mobile banking (MB) but it has paid little attention to understanding the impact of information technology usage behaviour due to cultural differences. Humans are the weakest link in information technology adoption; past research has shown that not all users are predisposed to change their behaviour radically and adopt new channels of banking. This paper examines the demographic patterns of users and non-users of MB. The paper also investigates the attitudinal influences of users and non-users of MB based on innovation attributes. Using empirical research, the study identifies constructs of innovation attributes that were perceived to be significantly different among the users and non-users of MB. The study provides valuable insights into MB in Saudi Arabia that have not been previously investigated. From a practical point, findings of this study will be particularly useful to banks, financial institutions and telecommunication service providers.     

Light weight model for intra mode selection in HEVC

Multimedia Tools and Applications - The High Efficiency Video Coding (HEVC) efficiently reduces the size of the multimedia contents, but at the cost of high computation complexity. In order to make...     

Role of situational method engineering to improve visual information systems in agile distributed environment

Software product prone to continuous evolution due to increase in the use of technology. Therefore, more stakeholders are involved in software evolution increases the cost and complexity. This required optimization of resources and cost to handle evolution with Global Software Development (GSD) to utilize time zones efficiently. The significance challenge of GSD reports: time zone difference, geographical location, communication delays, knowledge sharing, control among stakeholders and development team. Because of these challenges, the requirements for development in GSD environment are also challenge as compared to on site development. Different requirement engineering methods have been used to improve the requirements analysis to deal with ambiguities and inconsistency in large set of requirements. The customization and tailoring of requirements according to changing project’s situations required to improve project development with reusing existing agile methods during requirement engineering phase. Moreover, complex information systems where heterogeneity is inevitable that implies the involvement of divergent stakeholders and necessitate a comprehensive framework to capture multidimensional viewpoints and fulfill aforementioned issues. Therefore, a situational multi-dimensional agile requirement engineering method has been proposed to support team and stakeholders’ viewpoints. The schema of the proposed method is based on challenges recognized by performing Literature Review. Then proposed method has been evaluated via experimental approach and statistical analysis conducted to validated reliability of data collected. This result is significant approved both practically and statistically that the proposed approach ease to use, implement, trained and increased productivity and performance. Hence, the experimental study for the evaluation of the proposed approach results concluded that, proposed approach is the important multimedia tool for supporting organization and distributed development team for information sharing, collaboration, product development.

     

哈尔滨地区汛期径流量变化趋势与复杂性分析

区域水文要素复杂性研究是当今的热点问题,为了研究哈尔滨地区汛期径流量的复杂性特征及变化趋势,将R/S分析法和等概率粗粒化LZC算法引入到区域径流复杂性分析与变化趋势预测中,对地区内10个水文站点的汛期径流序列的复杂性进行诊断并对其变化趋势进行分析。研究结果表明:哈尔滨、通河、阿城、依兰、烟囱山各站未来的汛期径流量呈减少趋势,岔林河、莲花、西北河、延寿、四平山各站未来的汛期径流量呈增长趋势;各站点汛期径流序列的复杂度由高到低依次为:四平山、烟囱山、岔林河、阿城、西北河、依兰、莲花、通河、哈尔滨、延寿;从河流集水面积对其径流长程相关性和复杂性的影响可以看出,站点的河流集水面积越大,其径流量的长程相关性越强,复杂性指数越小。研究成果揭示了本地区汛期径流量的变化趋势以及复杂性演变特征,该特征可为区域径流预测及水资源优化配置提供科学依据。     

Biomathematical study of time-dependent flow of a Carreau nanofluid through inclined catheterized arteries with overlapping stenosis

Journal of Central South University - This work is concerned with the analysis of blood flow through inclined catheterized arteries having a balloon (angioplasty) with time-variant overlapping...     

Molecular dynamics simulations of enantiomeric separations as an interfacial process in HPLC

Since chromatographic separation is a dynamic process, with the interactions between the drug and the chiral stationary phase mediated by the solvent, no single interacting structure, such as could be found by minimizing the energy, could possibly describe and account for the ratio of residence times in the chromatographic column for the enantiomeric pair. We describe the use of explicit-solvent fully atomistic molecular dynamics simulations, permitting all the interactions between the atoms constituting the chiral stationary phase, solvent molecules and the drug molecule. This allows us to better understand the molecular dynamic chiral recognition that provides the discrimination, which results in the separation of enantiomers by high performance liquid chromatography. It also provides a means of predicting, for a given set of conditions, which enantiomer elutes first and an estimate of the expected separation factor. In this review, we consider the use of molecular dynamics toward this understanding and prediction.     

Single phase multi color emitting Ca2LuTaO6: Dy3+/Eu3+ double perovskite oxide phosphors

The trivalent rare-earth (RE³⁺) doped phosphors show tremendous achievement in narrow band multicolor line emission for various applications. However, the 4f–4f absorption transition of these ions is forbidden in UV and blue light excitation. Usually, a sensitizer having spin allowed transition was used as a co-dopant to excite these ions via the energy transfer phenomenon. Another approach promisingly using to excite these ions by efficient energy transfer from the intrinsic emission of the Ca₂LuTaO₆ double perovskite phosphors host lattice. Phosphors of Ca₂LuTaO₆ with double perovskite structure were synthesized by using a high-temperature solid-state reaction method. The produced Ca₂LuTaO₆ double perovskite phosphors show an intrinsic broad band emission centered at 424 nm under the excitation of 313 nm UV light. The origin of this broad band blue emission was deeply investigated by using computation and experimental approaches. The trivalent activator Dy³⁺ and Eu³⁺ were doped is a single and co-dopant in the produced Ca₂LuTaO₆ phosphors to check their excitation in UV and near-UV spectral region. X-ray diffraction and scanning electron microscopy were used to investigate the structure and phase analysis. Various characterizations such as photoluminescence excitation, emission, and CIE chromaticity coordinates were measured which illustrate the potential of Dy³⁺ and Eu³⁺ activated Ca₂LuTaO₆ double perovskite phosphors for narrow band multicolor line emission for various applications.     

Your comments matter: incorporating viewers’ comments for ranking online video content using bibliometrics

ABSTRACT

The quality of user-generated content over World Wide Web media is a matter of serious concern for both creators and users. To measure the quality of content, webometric techniques are commonly used. In recent times, bibliometric techniques have been introduced to good effect for evaluation of the quality of user-generated content, which were originally used for scholarly data. However, the application of bibliometric techniques to evaluate the quality of YouTube content is limited to h-index and g-index considering only views. This paper advocates for and demonstrates the adaptation of existing Bibliometric indices including h-index, g-index and M-index exploiting both views and comments and proposes three indices h_vc, g_vc and m_vc for YouTube video channel ranking. The empirical results prove that the proposed indices using views along with the comments outperform the existing approaches on a real-world dataset of YouTube.