ppxscal/embedding_network huggingface dataset:
Webservices oriented data mining in knowledge architecture
Authors: Richard Olejnik, Teodor-Florin Fortiş, Bernard Toursel
Venue: Future Generation Computer Systems (2009)

Massive parallelism is required for an efficient solution to data mining tasks, considering the proliferation of data and the need for high computational effort. The DisDaMin (Distributed Data Mining) project addressed distributed discovery and knowledge discovery through parallelization of data mining tasks. DisDaMin algorithms are based on the DG-ADAJ (Desktop-Grid Adaptive Application in Java), a middleware platform for Desktop Grid used as a deployment mechanism for DisDaMin algorithms. On the top of DG-ADAJ, SOA specific components could be employed to provide additional features and to improve current operation. An ESB (Enterprise Service Bus) built on the top of DG-ADAJ is going to provide improved availability, solve interoperability issues by exposing services through well established interfaces, and offer a loosely coupled infrastructure. An additional enactment layer is going to improve the performance of intelligent fragmentation of data, offering at the same time the necessary support for the execution of data workflows.
An entropy clustering analysis based on genetic algorithm
Authors: Liang-Ying Wei, Ching-Hsue Cheng
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2008)

Clustering analysis quantifies similarities (dissimilarities) between objects in a given dataset and discovers the hidden characteristics of each cluster. However, researchers often have difficulty in setting optimal parameters for clustering analysis when they attempt to obtain the optimal clustering. This work presents an entropy-based efficient clustering technique utilizing principles of genetic algorithm (GA), unlike previous clustering method [24] which employs parameter setting. The proposed method considers the data spread to determine the adaptive threshold within parameters optimized by genetic algorithm. The fitness function of genetic algorithm is defined as clustering accuracy. Four datasets in the UCI database are selected as the experimental data to compare the accuracy of the proposed algorithm with the three clustering methods. Results of this study demonstrate that the proposed algorithm outperforms listing methods.
Mathematical modelling of processes of reject water treatment in moving bed bioreactor
Authors: Viola Somogyi, Bence Fazekas, Endre Domokos, Ákos Rédey
Venue: WSEAS TRANSACTIONS on SYSTEMS (2008)

Efficient treatment of reject water originating from sludge digestion process was achieved by implementing a moving bed bioreactor. Since the ongoing processes in the reactor were unclear, model development was chosen in order to map them. To describe biofilm processes a newly presented zero-dimensional biofilm model [27] was chosen. Simulation data in the study of Plattes et al. [28] were promising for municipal wastewater but it did not meet the expectations in case of wastewater with high ammonia content. Therefore four step nitrogen removal was implemented in the OD biofilm model. Steady-state simulation showed that processes over nitrite were of great importance in the system. The results also indicated that to a certain degree ANAMMOX (anaerobic ammonia oxidation) reaction took place as well. The special structure of the moving bed bioreactor with protected microorganism colonies was assumed to be the reason for that.
Absence seizures as resetting mechanisms of brain dynamics
Authors: S. P. Nair, P. I. Jukkola, M. Quigley, A. Wilberger, D. S. Shiau, J. C. Sackellares, P. M. Pardalos, K. M. Kelly
Venue: Cybernetics and Systems Analysis (2008)

To understand the increase in age-related incidence and frequency of absence seizures in the rat brain, we investigated the effect of these seizures on brain dynamics. This paper puts forward the hypothesis that age-related differences in the expression of absence seizures are associated with the ability of the seizures to reset brain dynamics.
Application note: USDA UV-B monitoring system: An application of centralized architecture
Authors: Xinli Wang, Wei Gao, Jim R. Slusser, John Davis, Becky Olson, Scott Janssen, George Janson, Bill Durham, Roger Tree, Rita Deike
Venue: Computers and Electronics in Agriculture (2008)

In order to determine the spatial and temporal variations of solar ultraviolet-B (UV-B) radiation reaching the Earth's surface and their effects on agriculture and environment due to the depletion of atmospheric ozone, the U.S. Department of Agriculture (USDA) UV-B monitoring system has been established to provide essential information of ground UV-B levels, along with other variables, to research communities, decision makers, and the public. This monitoring network of 39 sites was designed as a centralized system covering the U.S. domain with collaborating sites in Canada and New Zealand. Programmed data loggers and a central data server are employed to automate the work. The centralized architecture allows centrally processing the data from all sites on a 3min basis and making daily updates available for the users. The system architecture, algorithms for data collection and data flow in the data processing procedures are presented in this article. Statistics show that the system is rather reliable with an overall data completeness of 98.14% since it began running in 1994. Main damages to the instruments are caused by the static electricity associated with severe thunderstorms, which result in a lower data completeness in summer months than in the others. The drawbacks of the centralized architecture, the possible remedies for the network failures, and our experiences with the system are discussed.
Optimal RSS threshold selection in connectivity-based localization schemes
Authors: Gianni Giorgetti, Sandee K.S. Gupta, Gianfranco Manes
Venue: Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems (2008)

Connectivity-based localization schemes compute the node positions using proximity information collected within the network. In many cases of practical interest, Received Signal Strength (RSS) measurements are available, and connectivity data can be obtained by comparing the RSS against a threshold. We use the Cramér-Rao bound (CRB) analysis to determine the threshold value that minimizes the localization error. The CRB is based on knowledge of the propagation model's parameters and the true node positions. Since this information is not available to a localization scheme, we approximate the optimal threshold value using a function that depends only on the number of nodes in the network. We use extensive simulations and RSS data from in-field experiments to validate the results of the proposed approach.
Study of the potential of alternative crops by integration of multisource data using a neuro-fuzzy technique
Authors: Anjan Sarkar, Arka Majumdar, Shaunak Chatterjee, Debapriya Chatterjee, Shibendu S. Ray, B. Kartikeyan
Venue: International Journal of Remote Sensing (2008)

This work proposes a neuro-fuzzy method for suggesting alternative crop production over a region using integrated data obtained from land-survey maps as well as satellite imagery. The methodology proposed here uses an artificial neural network (multilayer perceptron, MLP) to predict alternative crop production. For each pixel, the MLP takes vector input comprising elevation, rainfall and goodness values of different existing crops. The first two components of the aforementioned input, that is, elevation and rainfall, are determined from contour information of land-survey maps. The other components, such as goodness values of different existing crops, are based on the productivity estimates of soil determined by fuzzyfication and expert opinion (on soil) along with production quality by the Normalized Difference Vegetation Index (NDVI) obtained from satellite imagery. The methodology attempts to ensure that the suggested crop will also be a high productivity crop for that region.
Efficient prediction of exchange rates with low complexity artificial neural network models
Authors: Ritanjali Majhi, G. Panda, G. Sahoo
Venue: Expert Systems with Applications: An International Journal (2009)

In recent years forecasting of financial data such as interest rate, exchange rate, stock market and bankruptcy has been observed to be a potential field of research due to its importance in financial and managerial decision making. Survey of existing literature reveals that there is a need to develop efficient forecasting models involving less computational load and fast forecasting capability. The present paper aims to fulfill this objective by developing two novel ANN models involving nonlinear inputs and simple ANN structure with one or two neurons. These are: functional link artificial neural network (FLANN) and cascaded functional link artificial neural network (CFLANN). These have been employed to predict currency exchange rate between US$ to British Pound, Indian Rupees and Japanese Yen. The performance of the proposed models have been evaluated through simulation and have been compared with those obtained from standard LMS based forecasting model. It is observed that the CFLANN model performs the best followed by the FLANN and the LMS models.
Cooperative caching for grid-enabled OLAP
Authors: F. Dehne, M. Lawrence, A. Rau-Chaplin
Venue: International Journal of Grid and Utility Computing (2009)

In this paper, we propose a grid-based On-Line Analytical Processing (OLAP) application which distributes query computation across an enterprise grid. Our application follows a two-tiered process for answering queries based on sharing Cached OLAP data between the users at the local grid site and using grid scheduling approaches to execute the remaining parts of a query amongst a distributed set of OLAP Servers. A new technique for extraction and aggregation of shared Cached OLAP data is proposed, along with an efficient, aggregate-aware Cache controller. An experimental evaluation of the proposed query processing and cooperative Caching methods shows a significant reduction in query times compared to previously proposed methods.
Any time, any place: online advanced placement courses for high school students
Authors: Carol M. Shepherd
Venue: Universal Access in the Information Society (2008)

Increasingly, high school students in USA are participating in advanced placement courses. Unfortunately, this opportunity is not equitable across the country, as many students are unable to take these classes. By effectively utilizing technology, advanced placement courses could be offered to all students, in all countries, from all socio-economic groups. This paper discusses the benefits and possible disadvantages of students taking AP courses online. However, little research has been conducted in this area. There is a need for further research in the positive and negative aspects of online learning among high school students, particularly those taking AP courses.
Exploiting shared correlations in probabilistic databases
Authors: Prithviraj Sen, Amol Deshpande, Lise Getoor
Venue: Proceedings of the VLDB Endowment (2008)

There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources --- from sensor data, experimental data, data from uncurated sources, and many others. There is a growing need for database management systems that can efficiently represent and query such data. In this work, we show how data characteristics can be leveraged to make the query evaluation process more efficient. In particular, we exploit what we refer to as shared correlations where the same uncertainties and correlations occur repeatedly in the data. Shared correlations occur mainly due to two reasons: (1) Uncertainty and correlations usually come from general statistics and rarely vary on a tuple-to-tuple basis; (2) The query evaluation procedure itself tends to re-introduce the same correlations. Prior work has shown that the query evaluation problem on probabilistic databases is equivalent to a probabilistic inference problem on an appropriately constructed probabilistic graphical model (PGM). We leverage this by introducing a new data structure, called the random variable elimination graph (rv-elim graph) that can be built from the PGM obtained from query evaluation. We develop techniques based on bisimulation that can be used to compress the rv-elim graph exploiting the presence of shared correlations in the PGM, the compressed rv-elim graph can then be used to run inference. We validate our methods by evaluating them empirically and show that even with a few shared correlations significant speed-ups are possible.
Spatial scaling and information fractal dimension of surface parameters used in quantitative remote sensing
Authors: Renhua Zhang, Jing Tian, Zhaoliang Li, Xiaomin Sun, Xiaoguang Jiang
Venue: International Journal of Remote Sensing (2008)

In this paper, a general formula has been modified, proving that the scaling difference of a surface parameter depends not only on the variance of the surface parameter itself but also on the function structure of the surface parameter. Through quantitatively describing the relationship between scaling differences and measuring scale, in terms of the concept of information fractal dimension and topological dimension, a definition of information fractal dimension used in remote sensing was proposed. By computing the information fractal dimension of Leaf Area Index and surface temperature, we found that the method describes not only the information on spatial texture and spatial structure of remotely sensed data as the traditional methods did, but also illustrates the connection between the scaling difference and measuring scale. Where the information fractal dimension of a surface parameter in some areas is known, the scaling difference can be obtained according to the measuring scale, then it can be eliminated and more accurate results could be achieved after scaling transform. At last, the problems about the relativity of true values of surface parameters were discussed.
Link-load balance aware mapping and routing for NoC
Authors: Zhou Wenbiao, Yan Zhang, Zhigang Mao
Venue: WSEAS Transactions on Circuits and Systems (2007)

The paper presents a novel mapping and routing technique for the mesh based NoC design problem with an objective of minimizing the energy consumption and normalized worst link-load. The proposed algorithm PLBMR is a particle swarm optimization (PSO) based two phases process, one is mapping core onto NoC to minimize the NoC communication energy consumption, and another is the allocation of routing path for keeping the link-load balance. and the paper presents the detail implementation of the PLBMR algorithm. Experimental results show that the proposed technique can reduce the normalized worst link-load by 20% on average while guarantee a low energy consumption.
Investigating data preprocessing methods for circuit complexity models
Authors: P. W. Chandana Prasad, Azam Beg
Venue: Expert Systems with Applications: An International Journal (2009)

Preprocessing the data is an important step while creating neural network (NN) applications because this step usually has a significant effect on the prediction performance of the model. This paper compares different data processing strategies for NNs for prediction of Boolean function complexity (BFC). We compare NNs' predictive capabilities with (1) no preprocessing (2) scaling the values in different curves based on every curve's own peak and then normalizing to [0,1] range (3) applying z-score to values in all curves and then normalizing to [0,1] range, and (4) logarithmically scaling all curves and then normalizing to [0,1] range. The efficiency of these methods was measured by comparing RMS errors in NN-made BFC predictions for numerous ISCAS benchmark circuits. Logarithmic preprocessing method resulted in the best prediction statistics as compared to other techniques.
A realtime multimodal system for analyzing group meetings by combining face pose tracking and speaker diarization
Authors: Kazuhiro Otsuka, Shoko Araki, Kentaro Ishizuka, Masakiyo Fujimoto, Martin Heinrich, Junji Yamato
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

This paper presents a realtime system for analyzing group meetings that uses a novel omnidirectional camera-microphone system. The goal is to automatically discover the visual focus of attention (VFOA), i.e. "who is looking at whom", in addition to speaker diarization, i.e. "who is speaking and when". First, a novel tabletop sensing device for round-table meetings is presented; it consists of two cameras with two fisheye lenses and a triangular microphone array. Second, from high-resolution omnidirectional images captured with the cameras, the position and pose of people's faces are estimated by STCTracker (Sparse Template Condensation Tracker); it realizes realtime robust tracking of multiple faces by utilizing GPUs (Graphics Processing Units). The face position/pose data output by the face tracker is used to estimate the focus of attention in the group. Using the microphone array, robust speaker diarization is carried out by a VAD (Voice Activity Detection) and a DOA (Direction of Arrival) estimation followed by sound source clustering. This paper also presents new 3-D visualization schemes for meeting scenes and the results of an analysis. Using two PCs, one for vision and one for audio processing, the system runs at about 20 frames per second for 5-person meetings.
Proceedings of the 6th ACM international symposium on Mobility management and wireless access
Venue: MOBIWAC (2008)

It is our great pleasure to welcome you to the 6th ACM International Symposium on Mobility Management and Wireless Access - MobiWac '08 in Vancouver, Canada. Following the successful previous events in Fort Worth (TX), Philadelphia (PA), Maui (Hawaii), Torremolinos (Spain) and Chania (Greece), this year's symposium continues the tradition of being a premier forum for presentation of research results and experience reports on leading edge issues of mobility and wireless access, including models, systems, applications, and theory. The mission of the symposium is to share novel mobility management and wireless network solutions and identify new directions for future research and development. MobiWac gives researchers and practitioners a unique opportunity to share their perspectives with others interested in the various aspects of Mobile and Wireless Systems. The call for papers attracted 50 submissions from Asia, North America, Europe, Central America and Australia. The program committee accepted 18 regular papers which represents an acceptance rate of 36%. These papers cover a variety of topics, including next generation access control models, engineering and analysis techniques for access control policies and models, and security administration. The program committee further accepted 9 papers as short papers. All submissions were fully peer reviewed. We hope that these proceedings will serve as a valuable reference for mobile and wireless systems researchers and developers. Based upon the MobiWac TPC recommendations, the following three papers have been selected as candidates for the MobiWac 2008 Best Paper Award: "The Problem of Placing Mobility Anchor Points in Wireless Mesh Networks" Lei Wu and Bjorn Landfeldt "Efficient Multimedia Call Delivery over IP-Based Heterogeneous Wireless Access Networks" Peyman TalebiFard and Victor Leung "QoS Routing Mechanism using Mobility Prediction of Node in Ad-hoc Network" Hyun-Jong Cha, Insung Han and Hwang Bin Ryou. These papers were reviewed by a committee consisting of the General Chair, Professor Luciano Bononi and Professor Albert Zomaya who made the final decision on the best paper award. We thank the committee for their work.
Impact of denial of service attacks on ad hoc networks
Authors: Imad Aad, Jean-Pierre Hubaux, Edward W. Knightly
Venue: IEEE/ACM Transactions on Networking (TON) (2008)

Significant progress has been made towards making ad hoc networks secure and DoS resilient. However, little attention has been focused on quantifying DoS resilience: Do ad hoc networks have sufficiently redundant paths and counter-DoS mechanisms to make DoS attacks largely ineffective? Or are there attack and system factors that can lead to devastating effects? In this paper, we design and study DoS attacks in order to assess the damage that difficult-to-detect attackers can cause. The first attack we study, called the JellyFish attack, is targeted against closed-loop flows such as TCP; although protocol compliant, it has devastating effects. The second is the Black Hole attack, which has effects similar to the JellyFish, but on open-loop flows. We quantify via simulations and analytical modeling the scalability of DoS attacks as a function of key performance parameters such as mobility, system size, node density, and counter-DoS strategy. One perhaps surprising result is that such DoS attacks can increase the capacity of ad hoc networks, as they starve multi-hop flows and only allow one-hop communication, a capacity-maximizing, yet clearly undesirable situation.
A cross-cultural user evaluation of product recommender interfaces
Authors: Li Chen, Pearl Pu
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

We present a cross-cultural user evaluation of an organization-based product recommender interface, by comparing it with the traditional list view. The results show that it performed significantly better, for all study participants, in improving on their competence perceptions, including perceived recommendation quality, perceived ease of use and perceived usefulness, and positively impacting users' behavioral intentions such as intention to save effort in the next visit. Additionally, oriental users were observed reacting more significantly strongly to the organization interface regarding some subjective aspects, compared to western subjects. Through this user study, we also identified the dominating role of the recommender system's decision-aiding competence in stimulating both oriental and western users' return intention to an e-commerce website where the system is applied.
Evaluation of an ontology-content based filtering method for a personalized newspaper
Authors: Veronica Maidel, Peretz Shoval, Bracha Shapira, Meirav Taieb-Maimon
Venue: Proceedings of the 2008 ACM conference on Recommender systems (2008)

A new ontological-content-based method for ranking the relevancy of items in the electronic newspapers domain is proposed. The method is being implemented in ePaper, a personalized electronic newspaper research project. The content-based part of the filtering method of ePaper utilizes a hierarchical ontology of news items. The method considers common and "close" ontology concepts appearing in the user's profile and in the item's profile, measuring the hierarchical distance between concepts in the two profiles. Based on the number of common and related concepts, and their distances from each other, the filtering algorithm computes the similarity between items and users, and rank-orders the news items according to their relevancy to each user, thus providing a personalized newspaper. We have conducted evaluations of the filtering method, examining various parameters. A group of subjects, each having defined an initial content-based profile using the news ontology concepts, read news items from a certain electronic newspaper and expressed the relevancy of each item to them. In different runs of the algorithm on the same data, we changed several parameters of the algorithm, and compared the results with the users' ratings. We discovered that the filtering method, which considers not only common concepts but also hierarchically related concepts, yields significantly better quality of filtering compared to using only common concepts. Moreover, we were able to find optimal values of similarity scores according to the hierarchical distance between related concepts.