Using cross-layer metrics to improve the performance of end-to-end handover mechanisms

Network centric handover solutions for all IP wireless networks usually require modifications to network infrastructure which can stifle any potential rollout. This has led researchers to begin looking at alternative approaches. Endpoint centric handover solutions do not require network infrastructure modification, thereby alleviating a large barrier to deployment. Current endpoint centric solutions capable of meeting the delay requirements of Voice over Internet Protocol (VoIP) fail to consider the Quality of Service (QoS) that will be achieved after handoff. The main contribution of this paper is to demonstrate that QoS aware handover mechanisms which do not require network support are possible. This work proposes a Stream Control Transmission Protocol (SCTP) based handover solution for VoIP called Endpoint Centric Handover (ECHO). ECHO incorporates cross-layer metrics and the ITU-T E-Model for voice quality assessment to accurately estimate the QoS of candidate handover networks, thus facilitating a more intelligent handoff decision. An experimental testbed was developed to analyse the performance of the ECHO scheme. Results are presented showing both the accuracy of ECHO at estimating the QoS and that the addition of the QoS capabilities significantly improves the handover decisions that are made.     

Complexity classes for self-assembling flexible tiles

We present a theoretical model for self-assembling DNA tiles with flexible branches. We encode an instance of a “problem” as a pot of such tiles for which a “solution” is an assembled complete complex without any free sticky ends. Using the number of tiles in an assembled complex as a measure of complexity we show how NTIME classes (such as NP and NEXP) can be represented with corresponding classes of the model.     

Betriebsinformatik und Wirtschaftsinformatik als notwendige anwendungsbezogene Ergänzung einer allgemeinen Informatik – Vorschläge zur Verbesserung der akademischen Ausbildung auf dem Gebiet der automatisierten Datenverarbeitung in der Bundesrepublik Deutschland

Zusammenfassung  Nachdruck eines Aufsatzes aus elektronische datenverarbeitung 11(11)1969:544–548. This article is also available in English via and : Grochla E (2008) Corporate Information Systems Engineering and Business and Information Systems Engineering as a Necessary Application-Oriented Extension of General Computer Science – Proposals for Enhancing Academic Education in the Field of Automated Data Processing in the Federal Republic of Germany. Bus Inf Syst Eng. doi .

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The use of data-derived label hierarchies in multi-label classification

Instead of traditional (multi-class) learning approaches that assume label independency, multi-label learning approaches must deal with the existing label dependencies and relations. Many approaches try to model these dependencies in the process of learning and integrate them in the final predictive model, without making a clear difference between the learning process and the process of modeling the label dependencies. Also, the label relations incorporated in the learned model are not directly visible and can not be (re)used in conjunction with other learning approaches. In this paper, we investigate the use of label hierarchies in multi-label classification, constructed in a data-driven manner. We first consider flat label sets and construct label hierarchies from the label sets that appear in the annotations of the training data by using a hierarchical clustering approach. The obtained hierarchies are then used in conjunction with hierarchical multi-label classification (HMC) approaches (two local model approaches for HMC, based on SVMs and PCTs, and two global model approaches, based on PCTs for HMC and ensembles thereof). The experimental results reveal that the use of the data-derived label hierarchy can significantly improve the performance of single predictive models in multi-label classification as compared to the use of a flat label set, while this is not preserved for the ensemble models.     

3D‐vision based detection,localization, and sizing of broccoli heads in the field

This paper describes a 3D vision system for robotic harvesting of broccoli using low‐cost RGB‐D sensors, which was developed and evaluated using sensory data collected under real‐world field conditions in both the UK and Spain. The presented method addresses the tasks of detecting mature broccoli heads in the field and providing their 3D locations relative to the vehicle. The paper evaluates different 3D features, machine learning, and temporal filtering methods for detection of broccoli heads. Our experiments show that a combination of Viewpoint Feature Histograms, Support Vector Machine classifier, and a temporal filter to track the detected heads results in a system that detects broccoli heads with high precision. We also show that the temporal filtering can be used to generate a 3D map of the broccoli head positions in the field. Additionally, we present methods for automatically estimating the size of the broccoli heads, to determine when a head is ready for harvest. All of the methods were evaluated using ground‐truth data from both the UK and Spain, which we also make available to the research community for subsequent algorithm development and result comparison. Cross‐validation of the system trained on the UK dataset on the Spanish dataset, and vice versa, indicated good generalization capabilities of the system, confirming the strong potential of low‐cost 3D imaging for commercial broccoli harvesting.     

Using meta‐modeling in design and implementation of component‐based systems: the SOFA case study

To allow efficient and user‐friendly development of a component‐based application, component systems have to provide a rather complex development infrastructure, including a tool for component composition, component repository, and a run‐time infrastructure. In this paper, we present and evaluate benefits of using meta‐modeling during the process of defining a component system and also during creation of the development and run‐time infrastructures. Most of the presented arguments are based on a broad practical experience with designing the component systems SOFA and SOFA 2; the former designed in a classical ad hoc ‘manual’ way, whereas the latter with the help of meta‐modeling. Copyright © 2010 John Wiley & Sons, Ltd.     

Discrimination of quarry blasts and earthquakes in the vicinity of Istanbul using soft computing techniques

The purpose of this article is to demonstrate the use of feedforward neural networks (FFNNs), adaptive neural fuzzy inference systems (ANFIS), and probabilistic neural networks (PNNs) to discriminate between earthquakes and quarry blasts in Istanbul and vicinity (the Marmara region). The tectonically active Marmara region is affected by the Thrace-Eski?ehir fault zone and especially the North Anatolian fault zone (NAFZ). Local MARNET stations, which were established in 1976 and are operated by the Kandilli Observatory and Earthquake Research Institute (KOERI), record not only earthquakes that occur in the region, but also quarry blasts. There are a few quarry-blasting areas in the Gaziosmanpa?a, Çatalca, Ömerli, and Hereke regions. Analytical methods were applied to a set of 175 seismic events (2001-2004) recorded by the stations of the local seismic network (ISK, HRT, and CTT stations) operated by the KOERI National Earthquake Monitoring Center (NEMC). Out of a total of 175 records, 148 are related to quarry blasts and 27 to earthquakes. The data sets were divided into training and testing sets for each region. In all the models developed, the input vectors consist of the peak amplitude ratio (S/P ratio) and the complexity value, and the output is a determination of either earthquake or quarry blast. The success of the developed models on regional test data varies between 97.67% and 100%.     

The State of the Art in Topology‐Based Visualization of Unsteady Flow

Vector fields are a common concept for the representation of many different kinds of flow phenomena in science and engineering. Methods based on vector field topology are known for their convenience for visualizing and analysing steady flows, but a counterpart for unsteady flows is still missing. However, a lot of good and relevant work aiming at such a solution is available. We give an overview of previous research leading towards topology‐based and topology‐inspired visualization of unsteady flow, pointing out the different approaches and methodologies involved as well as their relation to each other, taking classical (i.e. steady) vector field topology as our starting point. Particularly, we focus on Lagrangian methods, space–time domain approaches, local methods and stochastic and multifield approaches. Furthermore, we illustrate our review with practical examples for the different approaches.     

RSA算法在DSP芯片上的加速实现

RSA是一种应用广泛的公钥算法,其原理简单,安全性好,但加密速度较慢。用硬件实现数据保护在安全性和速度上都能得到更好的性能。该文介绍了一种有效实现硬件数据加密的方案--基于TMS320C54x芯片的PC安全卡,并通过分析TMS320C54x芯片的特点,提出了一种在PC安全卡上加速实现RSA算法的方法,取得了良好的加速效果。