bluuebunny/crossref_metadata_2025 huggingface dataset:
Assemblages of fish along a mangrove - mudflat gradient in temperate Australia
Authors: Payne Nicholas Leslie , Gillanders Bronwyn May
Published: January 2009

Mangroves are considered to support rich assemblages of fish and invertebrates. Fishes inhabiting mangrove habitats and at various distances from mangroves across mudflats were sampled to: (1) compare fish assemblages between habitats; and (2) determine the influence of mangrove proximity on fish abundance and diversity in three southern Australian estuaries between November 2005 and January 2006. Based on their distribution, fish species were classified as mangrove residents, mudflat residents, generalists or rare species. The assemblage structure of fish in mangroves differed from assemblages 500 m away; however, neither total abundance nor species richness differed significantly between mangroves and mudflats. Mangrove residents and Aldrichetta forsteri (yellow-eyed mullet) displayed strong associations with mangrove habitats, whereas mudflat residents were associated with mudflat habitats. No other fish groups or individual species occurred in higher abundances in either habitat. Total fish abundance, mangrove residents and A. forsteri were positively correlated with pneumatophore density, indicating that the structural complexity of the mangroves might influence the distributions of certain fish species. The current study demonstrated that mangrove habitats in temperate Australia support no greater abundance or diversity of fish than adjacent mudflat habitats and that mangrove proximity does not influence fish distribution at a habitat scale.
β
1
integrins differentially control extravasation of inflammatory cell subsets into the CNS during autoimmunity
Authors: Bauer Martina , Brakebusch Cord , Coisne Caroline , Sixt Michael , Wekerle Hartmut , Engelhardt Britta , Fässler Reinhard
Published: January 2009

Inhibiting the α
4
subunit of the integrin heterodimers α
4
β
1
and α
4
β
7
with the monoclonal antibody natalizumab is an effective treatment for multiple sclerosis (MS). However, the pharmacological action of natalizumab is not understood conclusively. Previous studies suggested that natalizumab inhibits activation, proliferation, or extravasation of inflammatory cells. To specify which mechanisms, cell types, and α
4
heterodimers are affected by the antibody treatment, we studied MS-like experimental autoimmune encephalomyelitis (EAE) in mice lacking the β
1
-integrin gene either in all hematopoietic cells or selectively in T lymphocytes. Our results show that T cells critically rely on β
1
integrins to accumulate in the central nervous system (CNS) during EAE, whereas CNS infiltration of β
1
-deficient myeloid cells remains unaffected, suggesting that T cells are the main target of anti-α
4
-antibody blockade. We demonstrate that β
1
-integrin expression on encephalitogenic T cells is critical for EAE development, and we therefore exclude α
4
β
7
as a target integrin of the antibody treatment. T cells lacking β
1
integrin are unable to firmly adhere to CNS endothelium in vivo, whereas their priming and expansion remain unaffected. Collectively, these results suggest that the primary action of natalizumab is interference with T cell extravasation via inhibition of α
4
β
1
integrins.
Interference in acetylene intersystem crossing acts as the molecular analog of Young's double-slit experiment
Authors: de Groot Mattijs , Field Robert W. , Buma Wybren J.
Published: January 2009

We report on an experimental approach that reveals crucial details of the composition of singlet-triplet mixed eigenstates in acetylene. Intersystem crossing in this prototypical polyatomic molecule embodies the mixing of the lowest excited singlet state (
S
1
) with 3 triplet states (
T
1
,
T
2
, and
T
3
). Using high-energy (157-nm) photons from an F
2
laser to record excited-state photoelectron spectra, we have decomposed the mixed eigenstates into their
S
1
,
T
3
,
T
2
, and
T
1
constituent parts. One example of the interpretive power that ensues from the selective sensitivity of the experiment to the individual electronic state characters is the discovery and examination of destructive interference between two doorway-mediated intersystem crossing pathways. This observation of an interference effect in nonradiative decay opens up possibilities for rational coherent control over molecular excited state dynamics.
Irreversible climate change due to carbon dioxide emissions
Authors: Solomon Susan , Plattner Gian-Kasper , Knutti Reto , Friedlingstein Pierre
Published: January 2009

The severity of damaging human-induced climate change depends not only on the magnitude of the change but also on the potential for irreversibility. This paper shows that the climate change that takes place due to increases in carbon dioxide concentration is largely irreversible for 1,000 years after emissions stop. Following cessation of emissions, removal of atmospheric carbon dioxide decreases radiative forcing, but is largely compensated by slower loss of heat to the ocean, so that atmospheric temperatures do not drop significantly for at least 1,000 years. Among illustrative irreversible impacts that should be expected if atmospheric carbon dioxide concentrations increase from current levels near 385 parts per million by volume (ppmv) to a peak of 450–600 ppmv over the coming century are irreversible dry-season rainfall reductions in several regions comparable to those of the “dust bowl” era and inexorable sea level rise. Thermal expansion of the warming ocean provides a conservative lower limit to irreversible global average sea level rise of at least 0.4–1.0 m if 21st century CO
2
concentrations exceed 600 ppmv and 0.6–1.9 m for peak CO
2
concentrations exceeding ≈1,000 ppmv. Additional contributions from glaciers and ice sheet contributions to future sea level rise are uncertain but may equal or exceed several meters over the next millennium or longer.
The δ isoform of CaM kinase II is required for pathological cardiac hypertrophy and remodeling after pressure overload
Authors: Backs Johannes , Backs Thea , Neef Stefan , Kreusser Michael M. , Lehmann Lorenz H. , Patrick David M. , Grueter Chad E. , Qi Xiaoxia , Richardson James A. , Hill Joseph A. , Katus Hugo A. , Bassel-Duby Rhonda , Maier Lars S. , Olson Eric N.
Published: January 2009

Acute and chronic injuries to the heart result in perturbation of intracellular calcium signaling, which leads to pathological cardiac hypertrophy and remodeling. Calcium/calmodulin-dependent protein kinase II (CaMKII) has been implicated in the transduction of calcium signals in the heart, but the specific isoforms of CaMKII that mediate pathological cardiac signaling have not been fully defined. To investigate the potential involvement in heart disease of CaMKIIδ, the major CaMKII isoform expressed in the heart, we generated CaMKIIδ-null mice. These mice are viable and display no overt abnormalities in cardiac structure or function in the absence of stress. However, pathological cardiac hypertrophy and remodeling are attenuated in response to pressure overload in these animals. Cardiac extracts from CaMKIIδ-null mice showed diminished kinase activity toward histone deacetylase 4 (HDAC4), a substrate of stress-responsive protein kinases and suppressor of stress-dependent cardiac remodeling. In contrast, phosphorylation of the closely related HDAC5 was unaffected in hearts of CaMKIIδ-null mice, underscoring the specificity of the CaMKIIδ signaling pathway for HDAC4 phosphorylation. We conclude that CaMKIIδ functions as an important transducer of stress stimuli involved in pathological cardiac remodeling in vivo, which is mediated, at least in part, by the phosphorylation of HDAC4. These findings point to CaMKIIδ as a potential therapeutic target for the maintenance of cardiac function in the setting of pressure overload.
Evaluating and Training Substance Abuse Counselors: A Pilot Study Assessing Standardized Patients as Authentic Clients
Authors: Fussell Holly E. , Lewy Colleen S. , McFarland Bentson H.
Published: January 2009

Clinician training and supervision are needed to transfer evidence-based practices to community-based treatment organizations. Standardized patients (SPs) are used for clinician training and evaluating. However, to be effective for substance abuse counselors, SPs must realistically portray substance abuse treatment clients. The current study assessed authenticity of SPs as substance abuse treatment clients. Twenty-one substance abuse counselors interviewed SP(s) with differing profiles. Counselors provided quantitative and qualitative ratings of SP authenticity. Counselor responses to the study procedures were analyzed as well. Quantitative results include high-authenticity ratings for the SPs but counselors’ subjective responses varied. Counselor's rated the experience of participating in the study positively and provided constructive comments for future applications of this methodology. Results support future work on SPs as teaching and evaluation tools in substance abuse counseling. Findings also illustrate the need to refine definitions of authenticity for SPs as substance abuse clients.
Sixteen-Year Predictors of Substance Use Disorder Diagnoses for Patients with Mental Health Disorders
Authors: Irmiter Cheryl , Barry Kristen L. , Cohen Kenneth , Blow Fredrick C.
Published: January 2009

Individuals with substance use disorders (SUDs). including co-occurring disorders, are among the highest-risk populations for medical and psychiatric rehospitalizations, and are often underdiagnosed at initial hospitalization. This study examined predictors for these individuals at baseline hospitalization and subsequent rehospitalizations. Three groups were compared from a sample of individuals admitted to inpatient psychiatry (1982 to 1987) with at least one rehospitalization within a 16-year period. Multivariate logistical regressions were used to determine associations with predictor variables. The data showed that individuals’ diagnosed with a SUD after baseline hospitalization were more likely to have more medical hospitalizations and to be diagnosed with schizophrenia compared to those who were diagnosed with a SUD, including co-occurring disorders, at baseline. The results of this study indicate the importance of substance use screening to enhance service resources and treatment outcomes for medically and psychiatrically complex populations.
Complexity Analysis of Pipeline Mapping Problems in Distributed Heterogeneous Networks
Authors: Gu Yi , Wu Qishi , Zhu Mengxia , Rao Nageswara S. V.
Published: January 2009

Largescale scientific applications require using various system resources to execute complex computing pipelines in distributed networks to support collaborative research. System resources are typically shared in the Internet or over dedicated connections based on their location, availability, capability, and capacity. Optimizing the network performance of computing pipelines in such distributed environments is critical to the success of these applications.

We consider two types of largescale distributed applications: (i) interactive applications where a single dataset is sequentially processed along a pipeline; and (ii) streaming applications where a series of datasets continuously flow through a pipeline.

The computing pipelines of these applications consist of a number of modules executed in a linear order in network environments with heterogeneous resources under different constraints. Our goal is to find an efficient mapping scheme that allocates the modules of a pipeline to network nodes for minimum endtoend delay or maximum frame rate.

We formulate the pipeline mappings in distributed environments as optimization problems and categorize them into six classes with different optimization goals and mapping constraints: (i) Minimum Endtoend Delay with No Node Reuse (MEDNNR), (ii) Minimum Endtoend Delay with Contiguous Node Reuse (MEDCNR), (iii) Minimum Endtoend Delay with Arbitrary Node Reuse (MEDANR), (iv) Maximum Frame Rate with No Node Reuse or Share (MFRNNRS), (v) Maximum Frame Rate with Contiguous Node Reuse and Share (MFRCNRS), and (vi) Maximum Frame Rate with Arbitrary Node Reuse and Share (MFRANRS).

Here, “contiguous node reuse” means that multiple contiguous modules along the pipeline may run on the same node and “arbitrary node reuse” imposes no restriction on node reuse. Note that in interactive applications, a node can be reused but its resource is not shared.

We prove that MEDANR is polynomially solvable and the rest are NP-complete. MEDANR, where either contiguous or noncontiguous modules in the pipeline can be mapped onto the same node, is essentially the Maximum n-hop Shortest Path problem, and can be solved using a dynamic programming method. In MEDNNR and MFRNNRS, any network node can be used only once, which requires selecting the same number of nodes for onetoone onto mapping. We show its NP-completeness by reducing from the Hamiltonian Path problem. Node reuse is allowed in MEDCNR, MFRCNRS and MFRANRS, which are similar to the Maximum n-hop Shortest Path problem that considers resource sharing. We prove their NP-completeness by reducing from the Disjoint-Connecting-Path Problem and Widest path with the Linear Capacity Constraints problem, respectively.
A Perspective on Information Fusion Problems
Authors: Madan Rabinder N. , Rao Nageswara S. V.
Published: January 2009

Information fusion problems have a rich history spanning four centuries and several disciplines as diverse as political economy, reliability engineering, target tracking, bioinformatics, forecasting, distributed detection, robotics, cyber security, nuclear engineering, distributed sensor networks, and others. Over the past decade, the area of information fusion has been established as a discipline by itself with several contributions to its foundations as well as applications. In a basic formulation of the information fusion problem, each component is characterized by a probability distribution. The goal is to estimate a fusion rule for combining the outputs of components to achieve a specified objective such as better performance or functionality compared to the components. If the sensor error distributions are known, several fusion rule estimation problems have been formulated and solved using deterministic methods.

In the area of pattern recognition a weighted majority fuser was shown to be optimal in combining outputs from pattern recognizers under statistical independence conditions. A simpler version of this problem corresponds to the Condorcet Jury theorem proposed in 1786. This result was rediscovered since then in other disciplines including by von Neumann in 1959 in building reliable computing devices. The distributed detection problem, studied extensively in the target tracking area, can be viewed as a generalization of the above two problems. In these works, the underlying distributions are assumed to be known, which is quite reasonable in the areas these methods are applied.

In a different formulation, we consider estimating the fuser based on empirical data when no information is available about the underlying distributions of components. Using the empirical estimation methods, this problem is shown to be solvable in principle, and the fuser performance may be sharpened based on the specific formulation. The isolation fusers perform at least as good as best component, and the projective fusers perform as good as best combination of components. In a special case of function estimation, each component could be a potential function estimator, radial basis function, nearest neighbor estimator, regressogram, kernel estimator, regression tree or another estimator.

A projective fuser based on a nearest neighbor concept has been proposed based on Voronoi regions in this case. Under fairly general smoothness and non-smoothness conditions on the individual estimators, the expected fuser error is close to optimal with a specified probability. This result is purely sample-based and distribution-free in that it does not require the knowledge of underlying distributions and can be computed only using measurements.
AHLSS: A Hierarchical, Adaptive, Extendable P2P Live Streaming System
Authors: Li Runzhi , Guo Chunyi , Fan Ming , Wang Zongmin
Published: January 2009

With the development of P2P streaming technology, various live streaming systems have been designed. Some measurement studies recently have shown that the most important issue exposed by previous systems is how to balance the benefits between the internet service provider, the internet content provider, and P2P users. This issue is induced by little consideration on management and control. Other problems include how to resolve peers churn and make full use of network bandwidth and apply incentive mechanism among peers.

In this work we introduce AHLSS, a P2P system for live streaming which is hierarchical, adaptive, and extendable. We present the architecture of AHLSS which is divided into three layers. The top layer named AP (Administrator Peer) overlay consisted of some authentic servers, which are arranged by ICP (Internet Content Provider) to provide enrollment and authentication for peers to join P2P overlay and start to watch a media channel. Every AP locates in an alliance alone. The middle layer is SP overlay. AHLSS divides peers that participate in data transmission into two classes, including SP and NP, which base on the capability of peers. SP is elected by AP. SP has responsibility to route media packets quickly and reply peers' channel request within the cluster. The under layer consists of many clusters. A cluster is formed by uniting peers which have poor capability and little stability near SP. SP is named cluster-head with the responsibility for management of members in the cluster.

Our system's innovative features are the following: It provides the function of enrollment and authentication; AP look up peer's EnrollInfo (a list, which keeps the register information of peers) periodically and apply a decision-tree approach to elect SP. It resolves problems which are associated with the dynamics and heterogeneity of peers; to cope with the problem of topology-mismatch, we design Alliance and Cluster to partition the physical location of peers and make use of the Two-hop Detection Algorithm which belongs to LTM technology to optimize the connection of SP among alliances; different transmission modes are designed on SP overlay and within cluster. Native mesh-pull is adopted in SP overlay and the hybrid mode includes tree-push and mesh-pull which are applied in NP (Normal Peer) overlay. It reduces the delay in chunks transmitted through SP to NP and makes full use of the upload bandwidth of peers; Approach of K degree redundancy cluster-head is adopted by NP, it is used to avoid the inorganized status for NPs which resulted from SP's failure.

In this paper, we describe in detail the main algorithms that stand behind the design of AHLSS and present the analysis of architecture for various aspects including adaptability, scalability, efficiency, and robustness.
IAM: An Effective and Robust Protocol for P2P Live Streaming System
Authors: Guo Hongfang , Lin Yusong , Wang Zongmin
Published: January 2009

The phenomenal success and popularity of peer-to-peer (p2p) streaming over the last decade took many providers, researchers, as well as the mass, by surprise. It would become the dominant type of traffic over the Internet in the very near future. The released Windows Vista contains its own P2P networking system. Though P2P streaming has become one of the most attractive network applications, it is still awaiting some technological breakthroughs. P2P streaming faces very different challenges from other P2P applications, such as file download. In live P2P streaming, the stringent real-time performance requirement in terms of bandwidth and latency is one of the challenges it faces. In addition, frequent joining and leaving of the autonomous end-hosts have more significant impact on the system performance. So the churn problem and reconstruction due to uncertainty are key challenges of P2P streaming. A number of solutions were proposed which did not take all the factors into account. This paper presents IAM (IP Address Matching), a novel protocol for P2P live streaming system.

For overlay structure, neighbor selection algorithm-FAMM (Forward Address Maximum Matching), which allows the peer choose the close peers as neighbors, is proposed. In this mechanism peer selects neighbors by matching IP address in regular expression. IP address is assigned by area basically, so the closer the peers are, the more the same bits of IP address they have. Peer chooses the first m (m > 0) peers whose IP address has same bits with it as the neighbors. Meanwhile, the latency is generally low. FAMM just likes the DHT routing.

As managing peer failures and proper recovery are of critical importance for a robust P2P streaming system, a new peer exception mechanism is also proposed which is the other central issue of the IAM. According to the different error information which the peer receives, it detects the departure or failure of the neighbor intelligently and recovers from an unstable state promptly.

To evaluate the performance of the IAM, we have conducted extensive simulations and real-network experiment. The results indicate that IAM shortens the latency and is robust to the dynamic peers. It achieves superior comprehensive performance over Random scheme. It is proved effective in the real-network environment, and the latency of recovery is shortened significantly which is only 25% of that with the usual mechanism, as well.
P2PMP2: A Peer-to-Peer Leveraged Mobile Streaming System Based on Push and Pull
Authors: Jianwei Niu , Yunqi Tang , Jian Ma , Bing Zhou
Published: January 2009

In a traditional mobile streaming system, all users pull streams from the server. This model would cause users a high communication cost and heavy burden to the base station. At the same time, the low bandwidth of the cellular network cannot meet the requirements of high quality video, which greatly limits the large-scale deployment of the mobile multimedia streaming service.
Fast Inter Mode Decision Based on RD Costs and Frequencies of Modes
Authors: Li Wei , Zhou Bing , Huang Xueli
Published: January 2009

The new video coding standard H.264/AVC achieves higher coding efficiency than previous standards. However, the efficiency arises at the cost of significant complexity. In this paper, an efficient intermode decision algorithm is proposed to cut down the complexity of an exhaustively full mode decision algorithm in the reference software. Statistical variables including RD (Rate Distortion) costs and frequencies of various modes, correlation of modes between current MB (Macroblock), and their spatial and temporal neighbor MBs are utilized to achieve fast mode decision in the algorithm.

The proposed algorithm is composed of three primary steps: The characteristics information of video content, RD cost, and frequency of each mode, are obtained by statistics to assist the decision of the best coding mode for the MB. Because the accuracy of the statistical results will affect the succedent mode decision process, FMD (Full Mode Decision) algorithm are used to get the statistical values from several training frames. In addition, considering the above statistical variables change with video content's changes, they are updated at regular intervals. The best coding modes of current MBs and their neighbor MBs (both spatial and temporal) are highly correlated, so the coding mode of these neighbor MBs are used as an indication to that of current MBs. The difference of RD costs between MB mode (16×16, 16×8 and 8×16) and non-MB modes is used to decide the possible modes class for current MB. Furthermore, the possible modes are prioritized based on their occurring probabilities such that the highest probable mode will be tried first. During this process, the computed RD cost is checked against a content adaptive RD cost threshold to decide if the mode decision process should be terminated before trying the remaining modes in the class. In this way many unlikely coding modes are skipped, and the computational time is significantly reduced.

Experimental results show that the proposed algorithm performs well on both the low motion sequences and the high motion sequences due to utilizing the sequence-dependent statistical variables as adaptive threshold to decide the best coding modes. On average, the algorithm reduces the total encoding time by 66.3% while image quality (PSNR) degradation is only 0.154dB with bitrate increase about 0.21%.
An Efficient Worm Defense System Based Signature Extraction
Authors: Tu Hao , Li Zhitang , Liu Bin , Zhang Yejiang
Published: January 2009

The fast spread of a worm is a great challenge to Internet security. Most current defense systems use a signature matching approach while most signatures are developed manually. It is difficult to catch a variety of new worms promptly. An efficient worm defense system is designed and implemented to provide early warning at the moment the worms start to spread in the network and to contain or slow down the spread of the worm by automatically extracting a signature that could be used by firewalls or Intrusion Prevention Systems. Several recent efforts to automatically extract worm signatures from Internet traffic have been done, but the efficiency is an unsolved problem especially in real high-speed network. In this paper, we proposed an efficient worm defense system based signature extraction. The input of the system is all traffic crossing an edge network and its output is a database of worm signatures which can be used by content-based defense. There are three main stages to extract signatures from network traffic. First, a clustering stage uses multidimensional traffic mining based IP header to identify significant traffic volume. We propose a binary clustering algorithm and this leaves a preferred policy to improve the front traffic filter, which can reduce the traffic to be processed and enhance its purity. After clustering, nonsignificant traffic volume is stored in an innocuous packet pool and significant traffic volume is further classified using address dispersion as suspicious or innocuous. After this stage, only a small portion of the packets captured from the edge network are analyzed in third stage, signature extraction. A position-aware signature generation method based bloom filter is proposed to extract more accurate signatures with less CPU time and memory consumption. To minimize false positives, the signatures will be verified based on the innocuous packet pool. Both trace data and tcpdump data are used to test the prototype system. Experiment results show that the system can efficiently filter through suspicious traffic with high purity and extract more accurate signature, which can well support popular content-based defense system such as Snort.
Designated-Verifier Chameleon Proxy Signature
Authors: Zhang Jianhong , Ji Cheng , Geng Qin
Published: January 2009

With the development of computer technology, the requirement of the methods to verify the authenticity, the validity, and the integrity of information is becoming much bigger. For this purpose, many methods have been generated, such as digital signature, digital watermarking, steganography, and so on. Digital signature is a hot topic in cryptography and it plays a very important role in many fields. A normal digital signature allows a signer to generate a signature of the message with his secret key and the generated signature can be verified by anyone with the signer's public key. Chameleon signature is a non-interactive signature based on the well-established hash-and-sign paradigm, in which the receiver cannot convince the third party of the identity of the signer. Designated-verifier signature is a very useful tool for protecting the privacy of the valid verifier. Motivated by above statements, we construct a new chameleon hash scheme and construct a new DVICPS scheme. Our chameleon hash scheme satisfies all the properties of the normal chameleon hash function. In our hash function the owner of a public key does not need to retrieve the associated secret key. We prove that our new chameleon hash scheme satisfies all the attributes defined in [1] and our chameleon hash scheme is secure assuming Weak Computational Diffie-Hellman (WCDH) assumption is difficult. And we show our chameleon hash scheme is secure based on the difficulty of solving WCDHP assumption. Moreover, we use the proposed chameleon hash function to design a designated-verifier ID-based chameleon proxy signature (DVICPS) scheme. Furthermore, we analyze the security of our DVICPS scheme and prove that our DVICPS scheme is secure in the random oracle model. In our signature scheme, only the receiver who owns the corresponding secret key can verify the validity of the signature which efficiently protects the benefit of the verifier. We also prove that our signature scheme is secure in random oracle model. The success probability of forging our DVICPS scheme is equivalent to solving Computational Diffie-Hellman Problem (CDHP). Thus, our DVICPS scheme is secure and efficient.
The Aide Diagnosis of Cardiac Heart Diseases Using a Deoxyribonucleic Acid Based Backpropagation Neural Network
Authors: Shi Li , Wang Zhizhong , Wang Lijia , Zhang Jinying
Published: January 2009

In this paper, a novel diagnostic scheme of cardiac heart diseases is presented using a Deoxyribonucleic Acid (DNA)-based BP(DNA-BP) Neural Network by distinguishing the shapes of ST segments automatically. First, wavelet transform is applied to extract the ST segments by identifying the characteristic points in the ECG. ECG signals are decomposed by aTrous Algorithm using dyadic spline wavelets. The relationship between the feature points of ECG signals and the modulus maximum pairs of the signals' wavelet transform is established, and the R-wave and ST segment's fiducial points are extracted at different wavelet scales. Second, in order to overcome the disadvantages of the BP neural network, a DNA optimization method is adopted to optimize the original weights and bias of a BP neural network. The BP algorithm is used to find the most optimal values of the weights and bias of the BP network. At last the effectiveness of the proposed aided diagnostic scheme is demonstrated via the experiments which the data are from the clinical study and MIT/BIH ECG data base. In order to validate the advantages of the DNA-based BP (DNA-BP) network and determine the best application conditions of the network, two types of experiments were conducted. In each experiment, 30 samples were selected as the training data and testing data respectively. In the first type of experiments, the data were obtained from the ECG of different people. While in the second type of experiments, the data were obtained from the ECG of one person at different times. The same data and the conditions were used in both BP and GA-based BP (GA-BP) networks to illustrate the advantages of the proposed DNA-based BP network. The experiment results illustrate that the proposed DNA-based BP network overcomes the limitation of the sloping method in identifying straight line ST segments and the limitation of function fitting method in fitting accuracy. It also surmounts the disadvantages of a BP network in terms of the local minimum, slow convergence, and the shortcomings of GA-BP in terms of its limitation in algorithm coding and evolution ways.

In conclusion, the neural network is used to supply an invaluable aid for physicians to diagnose cardiac heart diseases and myocardial infarction.
A Reputation-Based Trust Evaluation Model for P2P E-Commerce
Authors: Liang Wang , Yajun Guo , Mei Qi
Published: January 2009

P2P e-commerce as a new shopping pattern is developing rapidly, and users can transact with anybody anytime and anywhere in the P2P e-commerce system, but as users often interact with strangers, hence building trust among the users, make the users know each other well, estimate the risk of participating in a transaction, and enable to transact securely in the P2P e-commerce system is an urgent problem to be solved for P2P e-commerce nowadays. In order to settle the problem, this paper provides a novel reputation-based trust model in P2P e-commerce system. The main thought of the proposed trust model is that a node has two types of reputation: local reputation and global reputation. In the local reputation computing, we take the calculation of factors including the amount of transaction money and transaction time and so on, and in the global reputation computing, there are three factors introduced—the number of neighbor nodes, the direct trust level of neighbor nodes, and the trust evaluation weight of neighbor nodes, and finally the object node's trust level can be obtained by using the local reputation weight coefficient and the global reputation weight coefficient to integrate the node's local reputation with global reputation. We have conducted two experiments that show that our trust model contrast with the present typical trust models EigenRep and Beta in the aspects of the computing load and the successful transaction rate. The first experiment shows that the trust model has a lower computing load compared to the EigenRep and Beta, because we do not compute the node's reputation through the transitive recommending of the intermediate nodes; the second experiment shows that the trust model has a higher successful transaction rate when the malicious nodes exist in the system, and even the number of malicious nodes proportion is larger, the trust model also has a higher successful transaction rate. In conclusion, the trust model more roundly takes into account the factors affecting the local reputation and global reputation and can greatly improve their computing methods. The experiment results show that the trust model can reduce the trust level computing load, and have more improvements on the successful transaction rate and anti-attack capability compared to the existing trust models. But the trust model does not introduce the risk factor, and the logic of the trust mode is relatively simple, so our trust model still needs to be improved constantly.
A Novel Filter Bank Design Method with CEM FRM Technique
Authors: Zhang Li-Zhi , Luo Wen-Yu
Published: January 2009

Modulation filter banks can be obtained by modulating one or two prototype filters, which reduce the design complexity of the filter banks. Furthermore, this kind of filter can be realized by using DFT or FFT with very high computationally efficiency. The proposition of a modulation filter bank reduces the computation complexity of designing the filter bank consumedly, which has very high computation efficiency. However, with the increasing of channels, the request for transition of the prototype filter is very high. This makes the length of the prototype filter longer, which decreases the computation efficiency.

Frequency-response masking technique, which was proposed by Lim in 1986, is a very efficient way for designing the sharp transition filter. It is composed of three sub-filters and a delay chain. The basic thought is designing a low complexity filter before compressing its frequency response, and then eliminating the useless periodic images of the prototype filter and its compensation filter by two masking filters. The complexity of the FRM filter can also be reduced by modifying its architecture. According to it, the paper deduces a Novel FRM low-pass filter based on Complex Exponential Modulation (CEM). The deduced filter is very suitable to the multi-rate digital signal process, apart from applying a single rate digital signal process.

In the application of software defined radio, the most bandwidth needs to be separated because it may has many narrowband channels. The need is very stringent for the filter to attenuate the closer channels. The filter banks encounter a main problem when it is used to separate channels, which is that the prototype filter must be a sharp transition bandwidth filter. Furthermore, the length of the prototype filter becomes longer in the DFT filter banks when the number of sub-filters is large and the transition band is very sharp. So it is very important to use a high efficiency digital filter, which can reduce the number of coefficient observably.

Based on the advantage of deduced novel low-pass filter, the paper proposes a new analysis filter bank architecture, which makes use of the high efficiency low-pass filter as a prototype filter. So it can decrease the computation complexity consumedly when the transition bandwidth of prototype filter is especially very sharp. It is the same with the alterable bandwidth system. At last, an eight channels filter bank design example is used to illustrate its feasibility. It reduces the computationally complexity of the sharp transition filter by using a CEM FRM prototype filter. At last, an application example has been given to illustrate the design of analysis filter banks, showing that the resulting filter bank reduces the computation complexity, which adapt to use in engineering implementation.
Performance Analysis of Blind Multiuser Detector with Fuzzy Kalman Filter in IR-UWB
Authors: Jian Peng , Li-yun Su
Published: January 2009

With on-going widespread deployment of UWB systems, multi-user detection has received increasing attention. In order to successfully decode the users in a UWB system, the most important issue is to be solved, apart from the multi-path and multiple-access channel. Most existing approaches employ correlators to correlate the received signal with a template signal. This technique appears very powerful, but not so satisfactory in a multi-path and multiple-access channel. A novel multi-user detection algorithm relying on the theory of canonical representation of multi-user receivers and fuzzy Kalman filtering (FKF) is proposed for impulse radio ultra-wideband systems. Dynamical systems of time-hopping BPSK in ultra-wideband are developed separately in the paper. Although the Kalman filtering algorithm is conditioned on perfect knowledge of some system parameters, we have used the fuzzy technique to overcome the difficulties. It is presumed that both, the process noise and the measurement noise, are zero-mean white sequences with their known covariance. If the Kalman filter is based on a complete and perfect model, the innovation should be a zero-mean white noise process, otherwise there is something erroneous with the design and the filter is not performing optimally, thus making the filter to diverge or coverage to a large bound. In practice, it is difficult to know the exact values for covariance. In order to reduce computation, we have to ignore some errors, but sometimes those unmodeled errors will remain significant. The adaptation of the filter uses a fuzzy inference system based on a covariance matching scheme that adjusts the measurement noise covariance matrix online. The basic idea behind this technique is to make the residual consistent with their theoretical covariance. The fuzzy Kalman filter method is proposed in the previous subsection is related to many existing algorithms for adaptive multiuser detector. Now, some performances are given to compare the differences from other prior algorithms. Since the Kalman filter scheme and the RLS one are similar, it is necessary to compare the proposed algorithm with the before RLS algorithms. Theoretical analysis and numerical results show that the new scheme has a better bit error rate performance compared with the conventional detector, and the effectiveness of the novel Kalman filtering algorithm.
On the Approximation of Fuzzy System
Authors: Yue Shihong , Chen Wei , Wang Jin , Wang Huaxiang
Published: January 2009

The choice of fuzzy set function affects how well the fuzzy systems approximate an unknown function. We first examine several popular fuzzy systems, based on which we generalize the error of the fuzzy system by the mathematical functional. Two classes of extended fuzzy systems with special set function are proposed respectively in one-dimensional and two-dimensional reproducing kernel spaces, and they are in fact the best interpolation operators in the sense of classical mathematical approximation. The extended fuzzy system can be used as easily as any typical fuzzy system but has better characters. Our major contributions are as follows. We prove that the existing fuzzy system with a triangle-shaped set function is by no means the best choice for an uncertain system. On the contrary, the reproducing kernel-shaped set function can give the best approximation in the sense of mathematical functional. According to the result, overlapped symmetric triangles or trapezoid set functions reduce fuzzy systems to piecewise linear systems. Universal Gaussian bell-curve set functions can work well but its learning cost is too expensive to apply under online condition. We explain what our proposed extended fuzzy system is useful for a given uncertain system. This solution is associated with another problem: Is the reproducing kernel condition too specific to limit its applications? We must stress that the reproducing kernel function is easily found in any continuous function space. Consequently, the extended fuzzy system can approximate any continuous function with arbitrary accuracy.

Furthermore one may question why we do not directly use an optimal approximation functional instead of the extended fuzzy system. Here we answer this problem by the following point of views: The two methods face different applicable conditions. The optimal approximation functional is used to interpolate those accurate data. These data are needed under certain conditions such as distributions and quantity, etc. When little information is available, an optimal approximation functional will do nothing. But the extended fuzzy system gives a good approximation to an uncertain system and can work efficiently under the condition of vague or poor information. Consequently, the two methods have different optimal criteria and different input and output descriptions. Furthermore, the extended fuzzy systems can be created flexibly by artificial experiences or other ways. Two experiments are used to verify the effectiveness and efficiency of our proposed extended fuzzy systems.
Using Dempster-Shafer Evidence Theory and Choquet Integral for Image Segmentation in Gas-Liquid Two-Phase Flow
Authors: Yue Shihong , Wang Jin , Li Beibei , Wang Huaxiang
Published: January 2009

Data fusion technique, essentially the Dempster-Shafer evidence theory, has widely been applied in image processing and significantly improving the image segmentation quality. The mass function determination in Dempster-Shafer evidence theory plays a crucial role in data fusion process. The purpose of this paper is to propose a method of automatically determining mass functions by Choquet integral and its identification algorithm. Different from the existing versions of determining the mass function values, the obtained mass function values in fact are the fuzzy measures in Choquet integral, which can be globally and accurately determined by the parameter identification algorithm of Choquet integral. Thus our proposed method is a very general and accurate one to handle the ambiguity connected with pixel classification in image segmentation, reducing the subjectivity of the existing methods. Results on real images from the two-phase flow are presented in order to verify the usefulness of our proposed method. Within this framework, we essentially investigate the possibility of determining mass functions using the concept of fuzzy clustering algorithm and the fuzzy measure in Choquet integral. Besides, in the calculation of mass functions, we have also introduced fuzzy measure information in order to fully utilize a feasible and efficient determination method that has widely succeeded in the Choquet integral application. The obtained results show the efficient and robust characters of our proposed method. The comparison research has also illustrated that the performances in image segmentation were significantly improved when using several images representing the same object. We have presented a data fusion approach to two-phase flow image segmentation based on the Dempster-Shafer evidence theory and Choquet integral tool. The electrical CT (Computed Tomography) techniques applied in the two-phase flow measurement have been becoming more and more popular, and ECT (Electrical Capacitance Tomography) and ERT (Electrical Resistivity Tomography) both are the most useful CT techniques. Comparing the real images with the reconstructed images in our experiments the fused image based on our proposed method clearly provides a better approximation than the singleton of ECT or ERT. The experimental results show that the Choquet integral tool helps improve the image segmentation quality of flow regimes greatly.
A Rule-Based Prefetching Approach for Object-Based Storage Device
Authors: He Shuibing , Feng Dan , Li Chunhua , Yuan Yanli
Published: January 2009

Capturing the advantages of NAS and SAN, Object-based Storage System (OBSS) is becoming an active research area. OBSS is composed of clients, metadata server, and Object-based Storage Devices (OSDs). Similar to the prefetching of file and block, object prefetching is also an effective method to reduce the object access latency in OSD. However, the existing methods focus on intra-object prefetching [ 1 ] and they limit the prefetching capability among objects to a certain extent.

In this paper, we present a novel inter-object prefetching approach which considers the characteristics of the object access in OSD. This approach adopts a kind of data mining technique called sequential pattern mining to find the object access sequential patterns [ 2 ], then produces the object sequential rules according to the patterns, and finally prefetches objects according to the rules and the object access context. The whole process includes the following three modules: Object Request Service Module. It maintains a current object access context, which is a l-length recently accessed object sequence. Furthermore, it appends new object information to the historic object access stream when an object is accessed. Sequential Rules Mining Module. It is composed of the object sequences preprocessing, the sequential pattern mining and the sequential rules producing modules. The preprocessing module divides the object access stream into many subsequences. Base on the discovered object sequential patterns gained by the sequential pattern mining module, object access sequential rules table is constructed. Prefetching Engine Module. When the current requested object is not in the object cache, the prefetching engine selects a matched rule with the highest confidence from the rules table according to the context, then chooses the corresponding objects and preloads them into the object cache.

Simulated experimental results show that both prediction accuracy and object hit rate can be improved comparing with the Group-based prefetching method [ 3 ] which can also be used for object prefetching.
Multisignature Scheme Based on the Generalized Conic Curve
Authors: Lin Song , Wang Biao , Li Zhoujun
Published: January 2009

We propose a multisignature scheme based on the generalized conic curve. This scheme makes use of the difficulties in factorizing large integer and computing discrete logarithm on the Abelian group, is convenient to, plaintext. Furthermore, the numeric Simulation of the multisignature is designed.