A Cell Based Dynamic Spectrum Management Scheme with Interference Mitigation for Cognitive Networks

Future wireless systems are expected to be characterized by the coexistence of different radio access technologies (RATs) resulting in complex heterogeneous wireless environments. In parallel with this, the tremendous demand for spectrum has inspired the requirement of dynamic spectrum management (DSM). This paper aims at designing a cell based dynamic spectrum management (CBDSM) scheme to enhance the spectrum utilization and maximize the profit of operators in wireless heterogeneous networks. The system architecture and the functional modules supporting the CBDSM scheme are designed. As a fundamental issue in spectrum management, the inter-system interference issue is solved in the proposed CBDSM scheme. Furthermore, game theory, which is a potential tool for studying the distributed autonomous resource optimization algorithms, is applied to design a spectrum trading algorithm enabling the heterogeneous wireless networks to dynamically trade spectrum and to share the profit. In the algorithm, we take into account the economic value of the spectrum of wireless systems in order to guarantee the rationality for the spectrum trading. The simulation results show that the proposed CBDSM scheme effectively improves the spectrum utilization and the profit of operators while it reduces the mutual interference between wireless networks to a tolerable level.

Composition analysis of coherent nanoinsertions of solid solutions on the basis of high-resolution electron micrographs

A program package is presented, ensuring fast direct and inverse Fourier transformations of images, various methods of noise filtration and use of spectral windows, and determination of local interplanar spacings (LIS) from cross-sectional high-resolution electron micrographs. The algorithm for determining the LIS consists in obtaining, by double fast Fourier transformation, a high-resolution image filtered by selecting an appropriate combination of reflections and using this image to find the characteristic LIS. A specific feature of this algorithm is that it employs weighting with correction of the integration domain. The resulting maps of LIS can be used to determine the chemical composition, e.g., in substitutional solid solutions, such as A_xB_1?x , A_xB_1?x C. The method is applied to process a high-resolution electron micrograph of a heterostructure with a submonolayer InGaAs/GaAs lattice.     

A location‐aware peer‐to‐peer overlay network

This work describes a novel location‐aware, self‐organizing, fault‐tolerant peer‐to‐peer (P2P) overlay network, referred to as Laptop. Network locality‐aware considerations are a very important metric for designing a P2P overlay network. Several network proximity schemes have been proposed to enhance the routing efficiency of existing DHT‐based overlay networks. However, these schemes have some drawbacks such as high overlay network and routing table maintenance overhead, or not being completely self‐organizing. As a result, they may result in poor scalability as the number of nodes in the system grows. Laptop constructs a location‐aware overlay network without pre‐determined landmarks and adopts a routing cache scheme to avoid maintaining the routing table periodically. In addition, Laptop significantly reduces the overlay maintenance overhead by making each node maintain only the connectivity between parent and itself. Mathematical analysis and simulations are conducted to evaluate the efficiency, scalability, and robustness of Laptop. Our mathematical analysis shows that the routing path length is bounded by log_d N, and the joining and leaving overhead is bounded by d log_d N, where N is the number of nodes in the system, and d is the maximum degree of each node on the overlay tree. Our simulation results show that the average latency stretch is 1.6 and the average routing path length is only about three in 10 000 Laptop nodes, and the maximum degree of a node is bounded by 32. Copyright © 2006 John Wiley & Sons, Ltd.     

Semantic Knowledge Management for Education

ldquoSemantic technologiesrdquo are touted as the next big wave in educational technology and as the solution to many problems in this arena. Interdisciplinary work between the fields of knowledge management (KM) and educational technology (ET) is booming. But the crop of actual systems and semantically enhanced learning objects is still meager, maybe because KM and EL are lacking a consensus on the underlying notions, e.g., of ldquosemantics,rdquo yielding specific problems in their interplay. In this paper, we look at semantic educational technologies and draw conclusions for their approach in KM. In particular, we (re)evaluate the notions of semantics, knowledge, and learning; their role for learning materials in ET; and how they interact with the contexts involved in the learning/teaching process. Based on this, we distill a list of conditions the underlying knowledge representation format must fulfil to support these. As these conditions are still rather abstract, we show how they can be realized in a concrete language design, taking in our open mathematical documents format OMDoc as a point of departure.     

Smart Manufacturing Through Digital Shop Floor Management Boards

Smart manufacturing, an offspring from Industry 4.0 (I4.0), defines the future for the manufacturing industry. Smart manufacturing leads to digitalization of the shop floor, which is automated, computerized and complex. To stay competitive, digitalization of the shop floor management (SFM) boards will be instrumental in improving performance management and continuous improvement. The purpose of this paper is to improve the understanding of SFM board meetings in the era of I4.0. The paper explores the current adaptation level of digital SFM boards, and identifies influencing forces for and forces against a further transition from analogue to digital SFM boards. Based on a survey and a subsequent workshop with practitioners, this paper reveals that digital SFM boards have not yet been adapted at shop floor level, and currently, practitioners are stuck to the standardized procedures and manual processes. The forces against a further adaptation are a managerial mindset stuck in an Industry 2.0 era and immature technologies to digitize the visualization of real-time data. The forces for are the need of enhancing data transparency within and across teams, which means elimination of information silos and time-consuming manual updates of SFM boards.

     

Using key performance indicators as knowledge-management tools at a regional health-care authority level.

The advantages of the introduction of information and communication technologies in the complex health-care sector are already well-known and well-stated in the past. It is, nevertheless, paradoxical that although the medical community has embraced with satisfaction most of the technological discoveries allowing the improvement in patient care, this has not happened when talking about health-care informatics. Taking the above issue of concern, our work proposes an information model for knowledge management (KM) based upon the use of key performance indicators (KPIs) in health-care systems. Based upon the use of the balanced scorecard (BSC) framework (Kaplan/Norton) and quality assurance techniques in health care (Donabedian), this paper is proposing a patient journey centered approach that drives information flow at all levels of the day-to-day process of delivering effective and managed care, toward information assessment and knowledge discovery. In order to persuade health-care decision-makers to assess the added value of KM tools, those should be used to propose new performance measurement and performance management techniques at all levels of a health-care system. The proposed KPIs are forming a complete set of metrics that enable the performance management of a regional health-care system. In addition, the performance framework established is technically applied by the use of state-of-the-art KM tools such as data warehouses and business intelligence information systems. In that sense, the proposed infrastructure is, technologically speaking, an important KM tool that enables knowledge sharing amongst various health-care stakeholders and between different health-care groups. The use of BSC is an enabling framework toward a KM strategy in health care.     

A smart spectrum utilization approach using multiantenna‐based cognitive relays in cognitive radio network

Efficient spectrum utilization is a promising technique for a prolonged unused radio frequency (RF) spectrum in a wireless network. In this paper, an adaptive spectrum sharing cognitive radio (CR) network has been proposed consisting of a primary user (PU) and secondary user transmitter (SU ? Tx) that communicates with secondary user receiver (SU ? Rx) via multiantenna‐based proactive decode‐and‐forward (DF) relay selection scheme. In our model, strategically an adaptable joint venture on underlay/overlay protocol is defined based on channel occupancy using spectrum sensing technique. Here, secondary transmitters (i.e., source transmitter) continuously sense the PU activities by energy detector and can simultaneously transmit to secondary receivers. Depending on sensing result secondary transmitters automatically switches in underlay mode if PU is active otherwise operates in overlay mode. The advantage of this scheme is that the joint mode of transmission allows the SUs to maximize their transmission rate. The outage performance at SU ? Rx and closed‐form expressions of joint underlay/overlay protocol has been evaluated. The power control policies at different transmitter nodes are taken care of. With the same diversity order, a trade‐off between multiantenna and multirelay is shown. This comparison shows improvement in outage behavior when the count in relays surpasses the number of antennas. Finally, the analytical model of smart efficient spectrum utilization without harming license users in CR is validated by MATLAB simulation.     

LOMM:移动网格中的移动性管理机制

基于移动网格的覆盖网体系结构,本文提出基于分层覆盖网络的移动性管理机制LOMM.移动节点在入网和移动时,动态的将其位置信息向固定节点构成的核心覆盖网络中进行注册和更新;通信节点则通过核心覆盖网络的结构化路由方式来解析移动节点的当前位置.最后对移动性管理机制的性能进行理论分析和仿真分析.     

How Do Knowledge Management Announcements Affect Firm Value? A Study of Firms Pursuing Different Business Strategies

The importance of knowledge management (KM) efforts is well recognized in the popular and academic press. However, KM efforts do not always lead to improved firm performance. This paper argues that different kinds of KM efforts may be appropriate for firms pursuing different business strategies, and the impact of a KM effort on firm performance would depend on whether the effort is aligned with the firm's business strategy. Prior literature on organizational learning, KM, and business strategy is used to develop these arguments, and also to identify the nature of KM efforts that would be most appropriate for firms pursuing Defender, Analyzer, and Prospector business strategies. An event study is used to evaluate the stock market reaction to a firm's public announcement of the KM effort. The empirical results, based on 103 KM announcements from 1995 to 2002, are consistent with the theory-based expectations, showing alignment between the KM effort and business strategy to be positively associated with impact on firm value. Some of the implications of these results for practice and future research are examined.     

Microwave permittivity of leaf using an Ag thick-film microstrip resonator

The X-band microwave dielectric constant, dielectric loss and the conductivity of the leaves of four different plants were measured from even and odd mode resonance characteristics of an Ag thick-film microstrip straight resonator, due to the perturbation caused by leafy vegetation as an overlay. Using the changes in the frequency response, the moisture-dependent X-band microwave properties of the leaves of Ficus Bengalensis, Ficus Religiosa, Acalypha Wilkensiana, and Acalypha Hispidia have been calculated. The permittivity obtained depends on the position of the overlay and moisture content. A partial overlay method might be a low-cost alternative for dielectric characterisation of biomaterials since a very small size of leaf is needed.     

A Neural Network-Based Connectivity Management for Mobile Computing Environment

The mobile computing environment experiences wireless problems and suffers from limited bandwidth, which leads to frequent disconnections. This has posed a challenge in maintaining user-to-user connectivity in the mobile computing environment. In this paper, we propose a neural network (NN) based connectivity management for mobile computing environment to maintain the mobile user-to-user connectivity throughout the transaction. Here the connectivity management maintains the status information of mobile hosts at the base station to handle frequent disconnection of mobile hosts (MHs), which occur because of hand-offs and interruptions. The disconnection of an MH because of wireless problems is called interruption, and the disconnection due to MH crossing the cell boundary is called hand-off. The neural networks are trained with respect to the status information to provide an intelligent decision for the connectivity management. The simulation results demonstrate that the proposed technique performs well in terms of percentage acceptance of disconnections and resource utilization (bandwidth and buffer) for the volatile mobile computing environment. It is also observed that the intelligent decision by neural network has improved the performance of the system.     

Low-field current transport mechanisms in rf magnetron sputter deposited boron carbide (B5C)/p-type crystalline silicon junctions in the dark

Measurements of the forward and reverse currents in an undoped rf magnetron sputter deposited boron carbide (B₅C)/p-type Si(111) junction have been made in the dark in the temperature range 120–300K at low-bias voltages (0–0.3V). A diode-like behaviour of the junction current has been observed in this low-bias region at all temperatures but with a rather large reverse (leakage) current I _R, particularly at high temperatures (I _R≈2 μA at V = ?0:3V and T = 290 K). The forward ‘voltage factor’ A (T) was found to decrease with increasing temperature as A (T)≈q/ηk _B T, with relatively high values of the ‘ideality factor’ η(about 3.5–4), probably due to the existence of an interfacial layer. The temperature dependence of the measured junction current (forward and reverse) flowing at low bias voltages and of the forward ‘current factor’ I _0F can be described satisfactorily by a model of the tunnelling of thermally excited carriers, including tunnelling via impurity localized levels, of the form I (T) ∝ exp [?C/T ^1/3] over the entire temperature range studied (120–300K). A high density of ‘localized’ energy states as large as 10¹⁸ cm^?3 eV^?1 was estimated, which can be attributed in part to ‘extrinsic’ interface states that could have been formed throughout the fabrication procedures of the rf sputter deposited B₅C/p-crystalline silicon junction studied. Another possible cause of such large concentration of ‘localized’ states is the ‘intrinsic’ interface states produced by the lattice mismatch between the polycrystalline boron carbide and crystalline silicon semiconductors as well as of the high intrinsic defect concentration caused by structural imperfections that often exist in boron carbide compounds.     

Indexing Techniques for Power Management in Multi-Attribute Data Broadcast

In this paper, we discuss the power conservative indexing techniques for managing multi-attribute data broadcast on wireless channels. These indexing techniques, namely, index tree, signature and hybrid, aim at improving the battery power consumption of mobile clients. By taking into account the broadcast management factors such as clustering and scheduling, these three indexing schemes may significantly reduce tune-in time while maintaining a reasonable access time. Cost models for single and multi-attribute query processing are developed. Our performance evaluation shows that the signature and hybrid methods are superior to the index tree method.     

The impact of knowledge management practices on the acceptance of Massive Open Online Courses (MOOCs) by engineering students: A cross-cultural comparison

This study conducted a cross-cultural analysis of the impact of knowledge management (KM) practices on the acceptance of Massive Open Online Courses (MOOCs). The study extended the Technology Acceptance Model (TAM) with KM practices. A structural equation modeling (SEM) was employed to test the hypothesized relationships based on data collected from 540 engineering students in Malaysia and Turkey. The results indicated that KM practices, including knowledge access, knowledge storage, and knowledge application have a positive and significant impact on perceived usefulness (PU) of MOOCs. However, knowledge sharing has a positive and significant impact on perceived ease of use (PEOU) of MOOCs. Further, a SEM-based multi-group analysis was employed to identify the moderating role of culture in examining the impact of KM practices on MOOCs acceptance. The findings suggested cultural differences in patterns between acceptance behaviors of engineering students in Malaysia and Turkey.     

An overlay approach to data security in ad-hoc networks

While it has been argued that application-layer overlay protocols can enhance services in mobile ad-hoc networks, hardly any empirical data is available on the throughput and delay performance achievable in this fashion. This paper presents performance measurements of an application-layer overlay approach that ensures integrity and confidentiality of application data in an ad-hoc environment. A key management and encryption scheme, called neighborhood key method, is presented where each node shares secrets only with authenticated neighbors in the ad-hoc network, thus avoiding global re-keying operations. All proposed solutions have been implemented and empirically evaluated in an existing software system for application-layer overlay networking. Results from indoor and outdoor measurement experiments with mobile handheld devices provide insight into the performance and overhead of overlay networking and application-layer security services in ad-hoc networks.     

Burstiness and resource management in ATM networks

Networks based upon the asynchronous transfer mode (ATM) provide for high flexibility to cope with a wide range of applications, some of them producing highly sporadic traffic. Therefore, the problem of burstiness has become in the last few years a key issue for such networks. A basic question is how to dimension network buffers in the presence of bursty traffic? In this paper we investigate the concept of burstiness and its impact on resource management. In burstiness characterization encountered in the literature, special attention has been given to the squared coefficient of variation of inter-arrival time Cv² in a cell arrival process. In order to observe the impact of bursty traffic on a queue, we develop in the present paper a ‘bursty’ traffic model, namely the two-stage hyper-Bernoulli cell arrival process, HBP₂, for short. We numerically solve the HBP₂/D/1/K queue. We especially derive the rejection probability P_loss. Numerical results are then thoroughly studied and we discuss the relevance for burstiness characterization of Cv² and peak to mean rate ratio B. We draw attention to the concept of local overload, i.e. when the arrival rate is greater than the server rate. This seems to be the most relevant phenomenon in the impact of a bursty traffic on a queue. These results are finally applied to the problem of resource management in ATM networks.     

面向情感倾向性分类的特征表达研究

Online reviews and comments are important information resources for people. A new model, called Sentiment Vector Space Model (SVSM), for feature selection and weighting is proposed to predict the sentiment orientation of comments and reviews, e.g., sorting out positive reviews from negative ones. Different from that of topic oriented classification, feature selection of sentiment orientation prediction focuses on language characteristics. Different from traditional algorithms for sentiment classification, this model integrates grammatical knowledge and takes topic correlations into account. Features are extracted, and the similarity between these features and the topic are also computed. The feature similarity is taken as a factor when evaluating the polarity of opinions. The experimental results show that the proposed model is more effective in identifying sentiment orientation than most of the traditional techniques.     

PCB企业知识管理实施浅析

分析了PCB企业知识管理的必要性,它是PCB企业迎接挑战、提升竞争力的必然选择。进而分析了PCB企业知识的特点和PCB企业知识管理现状,在此基础上提出了PCB企业知识管理实施的关键因素包括领导、文化与制度三个方面,同时对PCB企业知识管理实施的步骤做了初步的探讨。