Dynamic analysis and drilling degrees of freedom

Finite element methods for dynamic analysis employing elements with drilling degrees of freedom are presented. The formulation is based on a variational principle in which displacements and rotations are interpolated independently. The issue of zero masses corresponding to rotational degrees of freedom is addressed and techniques for defining consistent and lumped rotational mass matrices are presented.     

Assessment of the energy and exergy utilization efficiencies in the Turkish agricultural sector

This study deals with evaluating the energy and exergy utilization efficiencies in the Turkish agricultural sector over a 12‐year period from 1990 to 2001. In the energy and exergy analyses, two main energy sources, namely fuels and electricity, are taken into consideration, while the sectoral energy and exergy efficiencies are compared for this period. These main energy sources include diesel for tractors and other vehicles, and electricity for pumps. Overall energy utilization efficiencies are obtained to vary between 29.1 and 41.1%, while overall exergy utilization efficiencies are found to range from 27.9 to 37.4% in the analysed years, respectively. It may be concluded that the present technique proposed here may be used as a useful tool in analysing and evaluating the energy and exergy utilization efficiencies, identifying energy efficiency and/or energy conservation opportunities and dictating the energy strategies of countries. Copyright © 2005 John Wiley & Sons, Ltd.     

Statistically correlated multi-task learning for autonomous driving

Neural Computing and Applications - Autonomous driving research is an emerging area in the machine learning domain. Most existing methods perform single-task learning, while multi-task learning...     

对中国入世后洗涤剂工业形势及相关问题的分析 --国内外业界高层人士访谈

中国加入WTO后，中国洗涤用品行业面临着新的机遇与挑战，中国洗涤用品市场将面临更加激烈的竞争。由于环保的呼声越来越高，中国已开始在部分地区禁磷。中国洗涤用品工业将如何发展，其前景如何，专家的看法又如何，就这些问题本刊专访了有关人士。     

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.

     

Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4 × 10³⁸ unique IP addresses of devices in the network. IPv6 has introduced new features like Neighbour Discovery Protocol (NDP) and Address Auto-configuration Scheme. IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol (ICMPv6). IPv6 is vulnerable to numerous attacks like Denial of Service (DoS) and Distributed Denial of Service (DDoS) which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications. Therefore, an Intrusion Detection System (IDS) is a monitoring system of the security of a network that detects suspicious activities and deals with a massive amount of data comprised of repetitive and inappropriate features which affect the detection rate. A feature selection (FS) technique helps to reduce the computation time and complexity by selecting the optimum subset of features. This paper proposes a method for detecting DDoS flooding attacks (FA) based on ICMPv6 messages using a Binary Flower Pollination Algorithm (BFPA-FA). The proposed method (BFPA-FA) employs FS technology with a support vector machine (SVM) to identify the most relevant, influential features. Moreover, The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios. The results show that the proposed method BFPA-FA achieved the best accuracy rate (97.96%) for the ICMPv6 DDoS detection with a reduced number of features (9) to half the total (19) features. The proven proposed method BFPA-FA is effective in the ICMPv6 DDoS attacks via IDS.     

The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.     

Improved bioavailability and pharmacokinetics of tea polyphenols by encapsulation into gelatin nanoparticles

The authors prepared surface modified (with polyelectrolyte layers), tea polyphenols (TPP) encapsulated, gelatin nanoparticles (TPP‐GNP) and characterised them. The size of the spherical nanoparticles was ∼50 nm. Number of polyelectrolyte layers and incubation time influenced the encapsulation efficiency (EE); highest EE was noted in nanoparticles with six polyelectrolyte layers (TPP‐GNP‐6L) incubated for 4 h. TPP released from TPP‐GNP‐6L in simulated biological fluids indicated protection and controlled release of TPP due to encapsulation. Mathematical modelling indicated anomalous type as a predominant mode of TPP release. TPP‐GNP‐6L exhibited enhanced pharmacokinetics in rabbit model compared with free TPP. The area under the concentration‐time curve and mean residence time were significantly higher in TPP‐GNP‐6L compared with free TPP which provide an evidence of higher bioavailability of TPP due to encapsulation. The authors demonstrated that encapsulation of TPP into GNPs favoured slow and sustained release of TPP with improved pharmacokinetics and bioavailability thereby can prolong the action of TPP.Inspec keywords: gelatin, nanoparticles, encapsulation, biomedical materials, nanomedicine, particle size, polymer electrolytes, polymer films, nanofabricationOther keywords: bioavailability, pharmacokinetics, gelatin nanoparticles, surface modified tea polyphenols, polyelectrolyte layers, spherical nanoparticle size, incubation time, encapsulation efficiency, TPP‐GNP‐6L, simulated biological fluids, mathematical modelling, TPP release, rabbit model, concentration‐time curve, mean residence time, time 4 h     

Prediction-based Iterative Learning Control (PILC) for Uncertain Dynamic Nonlinear Systems Using System Identification Technique

Prediction-based Iterative Learning Control (PILC) is proposed in this paper for a class of time varying nonlinear uncertain systems. Convergence of PILC is analyzed and the uniform boundedness of tracking error is obtained in the presence of uncertainty and disturbances. It is shown that the learning algorithm not only guarantees the robustness, but also improves the learning rate despite the presence of disturbances and slowly varying desired trajectories in succeeding iterations. The effectiveness of the proposed PILC is presented by simulations.