ppxscal/embedding_network huggingface dataset:
Using a hybrid fuzzy classifier (HFC) to map typical grassland vegetation in Xilin River Basin, Inner Mongolia, China
Authors: Z. Sha, Y. Bai, Y. Xie, M. Yu, L. Zhang
Venue: International Journal of Remote Sensing (2008)

Community ecologists and vegetation scientists in grassland research have a strong interest in quantifying biotic communities in detail. However, a satisfactory classification with fine biotic details has been challenged by the coarse resolutions of Landsat images, although they are easily accessible. In this paper, a hybrid fuzzy classifier (HFC) for vegetation classification with Landsat ETM+ imagery on the typical grassland in Xilinhe River Basin, Inner Mongolia, China has been developed. Three vegetation classification systems were created from different aspects: the botanical system (Bio-classes, also as the final mapping units for vegetation cover), the combined botanical and spectral system (Bio-S classes), and the spectral system (Spec-classes). The HFC designed a fuzzy logic to measure the similarity between Spec-classes, extracted by the unsupervised classification, and Bio-S classes, built from the field samples, when considering the spectral variations of samples within the same Bio-class. Then, Bio-S classes, which served as a bridge for assigning Spec-classes to the target Bio-classes, were merged to restore Bio-classes for the final mapping. To assess the classification accuracy, the HFC was compared with a conventional supervised classification (CSC). The overall result of the HFC was much better than that of the CSC, with an accuracy percentage of 80.2% as compared to 69.0% for the CSC.
Robust fuzzy clustering-based image segmentation
Authors: Zhang Yang, Fu-Lai Chung, Wang Shitong
Venue: Applied Soft Computing (2009)

The fuzzy clustering algorithm fuzzy c-means (FCM) is often used for image segmentation. When noisy image segmentation is required, FCM should be modified such that it can be less sensitive to noise in an image. In this correspondence, a robust fuzzy clustering-based segmentation method for noisy images is developed. The contribution of the study here is twofold: (1) we derive a robust modified FCM in the sense of a novel objective function. The proposed modified FCM here is proved to be equivalent to the modified FCM given by Hoppner and Klawonn [F. Hoppner, F. Klawonn, Improved fuzzy partitions for fuzzy regression models, Int. J. Approx. Reason. 32 (2) (2003) 85-102]. (2) We explore the very applicability of the proposed modified FCM for noisy image segmentation. Our experimental results indicate that the proposed modified FCM here is very suitable for noisy image segmentation.
Is there an acceleration of the CpG transition rate during the mammalian radiation?
Authors: M. Peifer, J. E. Karro, H. H. von Grünberg
Venue: Bioinformatics (2008)

Motivation: In this article we build a model of the CpG dinucleotide substitution rate and use it to challenge the claim that, that rate underwent a sudden mammalian-specific increase approximately 90 million years ago. The evidence supporting this hypothesis comes from the application of a model of neutral substitution rates able to account for elevated CpG dinucleotide substitution rates. With the initial goal of improving that model's accuracy, we introduced a modification enabling us to account for boundary effects arising by the truncation of the Markov field, as well as improving the optimization procedure required for estimating the substitution rates. Results: When using this modified method to reproduce the supporting analysis, the evidence of the rate shift vanished. Our analysis suggests that the CpG-specific rate has been constant over the relevant time period and that the asserted acceleration of the CpG rate is likely an artifact of the original model. Contact: peifer@uni-graz.at Supplementary information: Supplementary data are available at Bioinformatics online.
An integrative model with subject weight based on neural network learning for bankruptcy prediction
Authors: Sungbin Cho, Jinhwa Kim, Jae Kwon Bae
Venue: Expert Systems with Applications: An International Journal (2009)

This study proposes an integration strategy regarding how to efficiently combine the currently-in-use statistical and artificial intelligence techniques. In particular, by combining multiple discriminant analysis, logistic regression, neural networks, and decision trees induction, we introduce an integrative model with subject weight based on neural network learning for bankruptcy prediction. The strength of the proposed model stems from differentiating the weights of the source methods for each subject in the testing data set. That is, the relative weights consist of N by I matrix, where N denotes the number of subjects and I denotes the number of the source methods. The experiments using a real world financial data indicate that the proposed model can marginally increase the prediction accuracy compared to the source methods. The integration strategy can be useful for a dichotomous classification problem like bankruptcy prediction since prediction can be improved by taking advantage of existing and newly emerging techniques in the future.
On workload merging and filtering effects in hierarchical wireless media streaming
Authors: Jean Cao, Carey Williamson
Venue: Proceedings of the 4th ACM workshop on Wireless multimedia networking and performance modeling (2008)

In wireless networks, bandwidth is relatively scarce, especially for supporting on-demand media streaming. In wired networks, multicast stream merging is a well-known technique for scalable on-demand streaming. Also, caching proxies are widely used on the Internet to offload servers and reduce network traffic. This paper uses simulation to examine a caching hierarchy for wireless streaming video distribution, in combination with multicast stream merging. The main purpose is to gain insight into the filtering effects caused by caching and merging. Using request frequencies, entropy, and inter-reference times as metrics, we illustrate how merging, caching, and traffic aggregation affect the traffic characteristics at each level. The simulation results provide useful insights into caching performance in a video streaming hierarchy.
Fuzzy hierarchical TOPSIS for supplier selection
Authors: Jia-Wen Wang, Ching-Hsue Cheng, Kun-Cheng Huang
Venue: Applied Soft Computing (2009)

This study simplifies the complicated metric distance method [L.S. Chen, C.H. Cheng, Selecting IS personnel using ranking fuzzy number by metric distance method, Eur. J. Operational Res. 160 (3) 2005 803-820], and proposes an algorithm to modify Chen's Fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) [C.T. Chen, Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy Sets Syst., 114 (2000) 1-9]. From experimental verification, Chen directly assigned the fuzzy numbers 1@? and 0@? as fuzzy positive ideal solution (PIS) and negative ideal solution (NIS). Chen's method sometimes violates the basic concepts of traditional TOPSIS. This study thus proposes fuzzy hierarchical TOPSIS, which not only is well suited for evaluating fuzziness and uncertainty problems, but also can provide more objective and accurate criterion weights, while simultaneously avoiding the problem of Chen's Fuzzy TOPSIS. For application and verification, this study presents a numerical example and build a practical supplier selection problem to verify our proposed method and compare it with other methods.
Scalable Dynamic User Preferences for Recommender Systems through the Use of the Well-Founded Semantics
Authors: Manoela Ilic, João Leite, Martin Slota
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01 (2008)

User modeling and personalisation are the key aspects of recommender systems in terms of recommendation quality. ERASP is an add-on to existing recommender systems which uses dynamic logic programming -- an extension of answer set programming -- as a means for users to specify and update their models and preferences, with the purpose of enhancing recommendations. While being an excellent solution in recommender systems limited to a few thousand products, ERASP does not scale well beyond that point. In this paper we present a major theoretical redesign of ERASP which entails a significant improvement in the performance of its implementation, making it usable in domains with hundreds of thousands of products.
Balance control by weighting and tensiometric measurements of bucket wheel excavators
Authors: Marin Silviu Nan, Iosif Kovacs, Florin Dumitru Popescu
Venue: WSEAS Transactions on Systems and Control (2008)

An essential element when establishing the balance of a bucket wheel excavator is the determination of the barycentre, the best results being thus obtained by weighting after having installed all the components. The problem, on which emphasis is laid, is how to maintain the stability and equilibrium of bucket wheel excavators or any other extraction machinery during operation, the main machinery of a technological extracting system employed for coal mining. The balance survey, respectively that of the stability of these machineries is compulsory because the bearing surface is rather small compared to the other building sub-systems outside the range of the surface, onto which much higher forces operate. The lack of correct balance for bucket wheel excavators determines their operation in an inadequate dynamic mode, or in extreme cases, there is the danger of losing stability by tilting over the excavator respectively suffering huge material and human loss. It is compulsory to verify for the correctness of the position and mass value of balance because there might be substantial error sources leading to compromise the operation. One of the most popular methods is that of weighting the entire equipment from the superior platform of the excavator. The weighting process implies the lifting of the excavators in three spots with hydraulic cylinders, the measurement of the forces, as well as the measurement of pressure inside the cylinders and of the stroke of each cylinder. The data measurement and rehashing installation is destined to determine the dimensions that finally define the weighting process of excavators or other operating machineries to which the balancing and control of stability is imposed. Thus, two types of data measurement and rehashing installations depending on the nature and type of the transducer used will be presented. For the first type, only analogical signals are transmitted to a numerical computer, and for the second type only digital signals are transmitted.
Integration of Multiple Classifiers for Chinese Semantic Dependency Analysis
Authors: Jiajun Yan, David B. Bracewell, Fuji Ren, Shingo Kuroiwa
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Semantic Dependency Analysis (SDA) has extensive applications in Natural Language Processing (NLP). In this paper, an integration of multiple classifiers is presented for SDA of Chinese. A Naive Bayesian Classifier, a Decision Tree and a Maximum Entropy classifier are used in a majority wins voting scheme. A portion of the Penn Chinese Treebank was manually annotated with semantic dependency structure. Then each of the three classifiers was trained on the same training data. All three of the classifiers were used to produce candidate relations for test data and the candidate relation that had the majority vote was chosen. The proposed approach achieved an accuracy of 86% in experimentation, which shows that the proposed approach is a promising one for semantic dependency analysis of Chinese.
System implications of information privacy
Authors: H. E. Petersen, R. Turn
Venue: Proceedings of the April 18-20, 1967, spring joint computer conference (1967)

Recent advances in computer time-sharing technology promise information systems which will permit simultaneous on-line access to many users at remotely located terminals. In such systems, the question naturally arises of protecting one user's stored programs and data against unauthorized access by others. Considerable work has already been done in providing protection against accidental access due to hardware malfunctions or undebugged programs. Protection against deliberate attempts to gain access to private information, although recently discussed from a philosophical point of view, has attracted only fragmentary technical attention. This paper presents a discussion of the threat to information privacy in non-military information systems, applicable countermeasures, and system implications of providing privacy protection.
A new approach of secret key management lifecycle for military applications
Authors: Nikolaos Bardis, Nikolaos Doukas, Konstantinos Ntaikos
Venue: WSEAS Transactions on Computers (2008)

In this paper a new approach is presented for key management access and sharing secret keys between certified users of a group. Such schemes are referred to as Symmetric Key Management Systems. The concept of information lifecycle management is first presented and analysed in the context of data storage efficiency. This concept is then extended for use with the management of symmetric secret keys. The need for a standard in symmetric secret key management is presented and founded on software engineering principles. A novel scheme contributing in this direction is hence presented. Specifically, access controls processes are presented that are based on passwords. These passwords, with the additional use of the AES cryptographic algorithm and nonces can be used to provide not only authentication for the access control in the system but additionally for the access in the encrypted file that stores all the symmetrical secret keys of each user of certified group. Following this, a new approach for the lifecycle management of secret keys is presented in order to achieve the secure communication based on encryption - decryption of all the messages in real time with the simultaneous use of two symmetrical secret keys for each transmission of information between the users. It is finally concluded that this innovative technology guarantees the automatic password and secret keys management lifecycle irrespective of the actions of the users and provides secure communication between certified group of users in local network and in internet.
Modeling vibration frequencies of annular plates by regression based neural network
Authors: V. P. Singh, S. Chakraverty, R. K. Sharma, G. K. Sharma
Venue: Applied Soft Computing (2009)

In this paper, a regression based artificial neural network model for multi input single output (MISO) systems has been developed. The time devoted in training this model is considerably less in comparison with the traditional ANN model and the number of neurons in the hidden layer can be fixed by choosing a regression polynomial of desired degree. The proposed model has been used and simulated for an example problem of transverse vibrations of plates viz. vibration of circular and elliptic annular plates. There exist nine different boundary conditions for the present example problem which are all simulated using the model. The training and testing with unseen patterns show the efficacy and reliability of the proposed technique for the MISO systems. Comparison of the proposed model with the traditional ANN model shows the former to be better and much efficient.
A network performance recommendation process for advanced internet applications users
Authors: Leobino Nascimento Sampaio
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

Advanced applications have caused end-users to show a new interest in accessing network measurement and status data across multiple domains, in order to detect occasional network problems. Diversity of network technologies, technical solutions and network managers add to the complexity of providing such information, which, when available, includes technical details that are meaningful only to specialists. However, context awareness can ease the recommendation process underlying a monitoring infrastructure. This research investigates a novel approach for traffic monitoring in view of the context information used to provide network performance recommendations in the most productive way.
Long range mutual information
Authors: Nahur Fonseca, Mark Crovella, Kavé Salamatian
Venue: ACM SIGMETRICS Performance Evaluation Review (2008)

Network traffic modeling generally views traffic as a superposition of flows that creates a timeseries of volume counts (e.g. of bytes or packets). What is omitted from this view of traffic is the contents of packets. Packet contents (e.g. header fields) contain considerable information that can be useful in many applications such as change and anomaly detection, and router performance evaluation. The goal of this paper is to draw attention to the problem of modeling traffic with respect to the contents of packets. In this regard, we identify a new phenomenon: long range mutual information (LRMI), which means that the dependence of the contents of a pair of packets decays as a power of the lag between them. We demonstrate that although LRMI is hard to measure, and hard to model using the mathematical tools at hand, its effects are easy to identify in real traffic, and it may have a considerable impact on a number of applications. We believe that work in modeling this phenomenon will open doors to new kinds of traffic models, and new advances in a number of applications.
Convergence of the collocation methods for singular integro-differential equations in Lebesgue spaces
Authors: Iurie Caraus, Nikos E. Mastorakis
Venue: WSEAS Transactions on Mathematics (2007)

In this article, the numerical schemes of collocation methods for an approximate solution of singular integro- differential equations with kernels of Cauchy type are explained. The equations are defined on arbitrary smooth closed contours. The theoretical background of collocations methods in Lebesgue spaces is obtained.
ITFP
Authors: Guangyong Zheng, Kang Tu, Qing Yang, Yun Xiong, Chaochun Wei, Lu Xie, Yangyong Zhu, Yixue Li
Venue: Bioinformatics (2008)

Summary: Investigation of transcription factors (TFs) and their downstream regulated genes (targets) is a significant issue in post-genome era, which can provide a brand new vision for some vital biological process. However, information of TFs and their targets in mammalian is far from sufficient. Here, we developed an integrated TF platform (ITFP), which included abundant TFs and their targets of mammalian. In current release, ITFP includes 4105 putative TFs and 69 496 potential TF-target pairs for human, 3134 putative TFs and 37 040 potential TF-target pairs for mouse, and 1114 putative TFs and 18 055 potential TF-target pairs for rat. In short, ITFP will serve as an important resource for the research community of transcription and provide strong support for regulatory network study. Availability: ITFP can be accessed at http://itfp.biosino.org/itfp Contact:yyzhu@fudan.edu.cn; yxli@sibs.ac.cn
Superconvergence of finite element method for the Signorini problem
Authors: Ming-xia Li, Qun Lin, Shu-hua Zhang
Venue: Journal of Computational and Applied Mathematics (2008)

In this paper, we study the superconvergence of the frictionless Signorini problem. When approximated by bilinear finite elements, by virtue of the information on the contact zone, we can derive a superconvergence rate of O(h^3^2) under a proper regularity assumption. Finally, a numerical test is given to verify our result.
Some lower bounds on the algebraic immunity of functions given by their trace forms
Authors: V. V. Bayev
Venue: Problems of Information Transmission (2008)

The algebraic immunity of a Boolean function is a parameter that characterizes the possibility to bound this function from above or below by a nonconstant Boolean function of a low algebraic degree. We obtain lower bounds on the algebraic immunity for a class of functions expressed through the inversion operation in the field GF(2 n ), as well as for larger classes of functions defined by their trace forms. In particular, for n ¿ 5, the algebraic immunity of the function Tr n (x ¿1) has a lower bound ¿2¿n + 4¿ ¿ 4, which is close enough to the previously obtained upper bound ¿¿n¿ + ¿n/¿¿n¿¿ ¿ 2. We obtain a polynomial algorithm which, give a trace form of a Boolean function f, computes generating sets of functions of degree ¿ d for the following pair of spaces. Each function of the first (linear) space bounds f from below, and each function of the second (affine) space bounds f from above. Moreover, at the output of the algorithm, each function of a generating set is represented both as its trace form and as a polynomial of Boolean variables.
Vehicular urban sensing: efficiency and privacy
Authors: Mario Gerla
Venue: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems (2008)

There has been growing interest in urban surveillance using vehicles that monitor the environment, classify the events, e.g., license plate reading, and exchange metadata with neighbors in a peer-to-peer fashion. The idea is to create a totally distributed index of all the events, to be accessed by users. For instance, the Department of Transportation extracts traffic congestion statistics; the Department of Health monitors pollutants, and; the Police carries out forensic investigations. Mobile, vehicular sensing differs significantly from fixed (wireless) sensing. The vehicles have no strict limits on battery life, processing power and storage capabilities. Moreover they can generate an enormous volume of data, making current sensor harvesting solutions inadequate. In this talk we describes MobEyes, a middleware solution that diffuses data summaries to create a distributed index of the massive sensed data base. We discuss the challenges of designing and maintain such a system, from information dissemination to harvesting, routing and security.
Future scenarios of mixed reality: the INTUITION roadmap scenarios
Authors: Angelos Amditis, Ioannis Karaseitanidis, Matthaios Bimpas, Roland Blach
Venue: The Visual Computer: International Journal of Computer Graphics (2008)

INTUITION is a Network of Excellence that aims to integrate the European research efforts on the scientific and technological field of Virtual and Mixed Reality. To perform that, a series of activities have taken place in order to gather knowledge regarding actors and research profiles, projects and research results, products and patents. Having a clear view of research needs and technology trends the Network has envisioned the research goals that need to be pursued within the years to come. The starting point is a set of visionary scenarios which set out the picture for the technological and scientific advances that need to take place. Within this paper a set of indicative scenarios on a higher and descriptive level are provided and the way they contribute to the roadmap definition is explained. With this report we want to share these scenarios and our initial thoughts to stimulate a broader discussion and invite people from all relevant backgrounds to enter the knowledge creation process. The paper is a collective production of the INTUITION Consortium.