ppxscal/embedding_network huggingface dataset:
A content-driven access control system
Authors: Jessica Staddon, Philippe Golle, Martin Gagné, Paul Rasmussen
Venue: Proceedings of the 7th symposium on Identity and trust on the Internet (2008)

Protecting identity in the Internet age requires the ability to go beyond the identification of explicitly identifying information like social security numbers, to also find the broadly-held attributes that, when taken together, are identifying. We present a system that can work in conjunction with natural language processing algorithms or user-generated tags, to protect identifying attributes in text. The system uses a new attribute-based encryption protocol to control access to such identifying attributes and thus protects identity. The system supports the definition of user access rights based on role or identity. We extend the existing model of attribute-based encryption to support threshold access rights and provide a heuristic instantiation of revocation.
Introduction to Microsystem Technology: A Guide for Students (Wiley Microsystem and Nanotechnology)
Authors: Gerald Gerlach, Wolfram Dotzel
Venue:  (2008)

Over half a century after the discovery of the piezoresistive effect, microsystem technology has experienced considerable developments. Expanding the opportunities of microelectronics to non-electronic systems, its number of application fields continues to increase. Microsensors are one of the most important fields, used in medical applications and micromechanics. Microfluidic systems are also a significant area, most commonly used in ink-jet printer heads. This textbook focuses on the essentials of microsystems technology, providing a knowledgeable grounding and a clear path through this well-established scientific dicipline. With a methodical, student-orientated approach, Introduction to Microsystem Technology covers the following: microsystem materials (including silicon, polymers and thin films), and the scaling effects of going micro; fabrication techniques based on different material properties, descriptions of their limitations and functional and shape elements produced by these techniques; sensors and actuators based on elements such as mechanical, fluidic, and thermal (yaw rate sensor components are described); the influence of technology parameters on microsystem properties, asking, for example, when is the function of a microsystem device robust and safe? The book presents problems at the end of each chapter so that you may test your understanding of the key concepts (full solutions for these are given on an accompanying website). Practical examples are included also, as well as case studies that enable a better understanding of the technology as a whole. With its extensive treatment on the fundamentals of microsystem technology, this book also serves as a compendium for engineers and technicians working with microsystem technology.
Note: A new proof of Vázsonyi's conjecture
Authors: Konrad J. Swanepoel
Venue: Journal of Combinatorial Theory Series A (2008)

The diameter graph G of n points in Euclidean 3-space has a bipartite, centrally symmetric double covering on the sphere. Three easy corollaries follow: (1) A self-contained proof of Vazsonyi's conjecture that G has at most 2n-2 edges, which avoids the ball polytopes used in the original proofs given by Grunbaum, Heppes and Straszewicz. (2) G can be embedded in the projective plane. (3) Any two odd cycles in G intersect [V.L. Dol'nikov, Some properties of graphs of diameters, Discrete Comput. Geom. 24 (2000) 293-299].
Batch-to-batch control of fed-batch processes using control-affine feedforward neural network
Authors: Zhihua Xiong, Yixin Xu, Jie Zhang, Jin Dong
Venue: Neural Computing and Applications (2008)

A control strategy for fed-batch processes is proposed based on control affine feed-forward neural network (CAFNN). Many fed-batch processes can be considered as a class of control affine nonlinear systems. CAFNN is constructed by a special structure to fit the control affine system. It is similar to a multi-layer feed-forward neural network, but it has its own particular feature to model the fed-batch process. CAFNN can be trained by a modified Levenberg&#x2013;Marquardt (LM) algorithm. However, due to model-plant mismatches and unknown disturbances, the optimal control policy calculated based on the CAFNN model may not be optimal when applied to the fed-batch process. In terms of the repetitive nature of fed-batch processes, iterative learning control (ILC) can be used to improve the process performance from batch to batch. Due to the special structure of CAFNN, the gradient information of CAFNN can be computed analytically and applied to the batch-to-batch ILC. Under the ILC strategy from batch to batch, endpoint product qualities of fed-batch processes can be improved gradually. The proposed control scheme is illustrated on a simulated fed-batch ethanol fermentation process.
Unsupervised semantic markup of literature for biodiversity digital libraries
Authors: Hong Cui
Venue: Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries (2008)

This paper reports the further development of machine learning techniques for semantic markup of biodiversity literature, especially morphological descriptions of living organisms such as those hosted at efloras.org and algaebase.org. Syntactic parsing and supervised machine learning techniques have been explored by earlier research. Limitations of these techniques promoted our investigation of an unsupervised learning approach that combines the strength of earlier techniques and avoids the limitations. Semantic markup at the organ and character levels is discussed. Research on semantic markup of natural heritage literature has direct impact on the development of semantic-based access in biodiversity digital libraries.
Developing a concurrent service orchestration engine in ccr
Authors: Wei Lu, Thilina Gunarathne, Dennis Gannon
Venue: Proceedings of the 1st international workshop on Multicore software engineering (2008)

As the Grid application models move towardsWeb services and the service oriented architecture (SOA), the service orchestration is becoming the key to build the large-scale system. With the significant attention, WS-BPEL is widely adopted as the standard web service orchestration language. As a concurrent workflow language WSBPEL introduces a set of complex and sophisticated concurrent and coordination semantics. Meanwhile the centralized architecture makes the orchestration engine be the inherent candidate for the performance bottleneck. Therefore implementing a correct and highly concurrent WS-BPEL engine presents significant challenge. The conventional thread based concurrent programming model is inadequate here. Instead, we believe an alternative model, namely the event-driven programming model aided with the high level coordination constructs such as join patterns, is more suitable for this case, from the perspective of system performance as well as the programmability. In this paper we present the implementation of a high performance WS-BPEL engine prototype, which is built upon the event-driven architecture and join patterns provided by the Microsoft Concurrent Coordination Runtime(CCR). We focus on how to interpret the concurrency semantics in WS-BPEL by using the event and join patterns, and how to drive the execution of a workflow in a reactive manner. Also our experience shows that the event driven architecture enables the orchestration engine to efficiently handle the massive concurrency on the multicore machine.
Radio planning and coverage optimization of 3G cellular networks
Authors: Edoardo Amaldi, Antonio Capone, Federico Malucelli
Venue: Wireless Networks (2008)

Radio planning and coverage optimization are critical issues for service providers and vendors that are deploying third generation mobile networks and need to control coverage as well as the huge costs involved. Due to the peculiarities of the Code Division Multiple Access (CDMA) scheme used in 3G cellular systems like UMTS and CDMA2000, network planning cannot be based only on signal predictions, and the approach relying on classical set covering formulations adopted for second generation systems is not appropriate. In this paper we investigate mathematical programming models for supporting the decisions on where to install new base stations and how to select their configuration (antenna height and tilt, sector orientations, maximum emission power, pilot signal, etc.) so as to find a trade-off between maximizing coverage and minimizing costs. The overall model takes into account signal-quality constraints in both uplink and downlink directions, as well as the power control mechanism and the pilot signal. Since even small and simplified instances of this NP-hard problem are beyond the reach of state-of-the-art techniques for mixed integer programming, we propose a Tabu Search algorithm which provides good solutions within a reasonable computing time. Computational results obtained for realistic instances, generated according to classical propagation models, with different traffic scenarios (voice and data) are reported and discussed.
Interval iterative algorithm for computing the piecewise algebraic variety
Authors: Renhong Wang, Xiaolei Zhang
Venue: Computers Mathematics with Applications (2008)

As the set of the common zeros of the multivariate splines, the piecewise algebraic variety is a kind of generalization of the classical algebraic variety. In this paper, we discuss the computation problem of the piecewise algebraic variety. The approach presented here is the interval iterative algorithm by introducing the concept of @e-deviation solutions. Meanwhile, we present a simple method to evaluate the bound on the value of the derivative of the function on a given region.
Radio planning of wireless local area networks
Authors: Sandro Bosio, Antonio Capone, Matteo Cesana
Venue: IEEE/ACM Transactions on Networking (TON) (2007)

In this paper we propose mathematical models to tackle the WLAN planning problem. Our approach aims at maximizing network efficiency by taking into account the inter-AP domain interference and the access mechanism. Both the single-channel and the multiple-channel WLAN planning problems are considered. We give different formulations which capture at different levels of detail the effect of interference on the network efficiency. In order to evaluate the quality of the proposed models, we obtain the optimal solutions for synthetic network instances, and propose heuristics to get suboptimal solutions in a reasonable computing time. We show that the networks planned according to our approach feature higher efficiency than the ones planned using classical models, like the minimum-cardinality set covering problem (SCP), by privileging network solutions with low-power APs installed. The achieved gain reaches 167% in particular network scenarios. Moreover, we test the obtained solutions through simulation and real-life testbed implementation; both analyses show that the networks planned with the proposed approaches are the ones with the highest saturation throughput with respect to those configurations obtained with SCP.
Exploiting In-Memory and On-Disk Redundancy to Conserve Energy in Storage Systems
Authors: Jun Wang, Xiaoyu Yao, Huijun Zhu
Venue: IEEE Transactions on Computers (2008)

Today's storage system places an imperative demand on energy efficiency. Storage system often places disks into standby mode by stopping them from spinning to conserve energy when load is not high. The major obstacle of this method is by introducing a high spin-up cost introduced by passively waking up the standby disk to service the request. In this paper, we propose a redundancy-based, hierarchical I/O cache architecture called RIMAC to solve the problem. The idea of RIMAC is to enable data on the standby disk(s) to be recovered by accessing two-level I/O cache and/or active disks if needed. In parity-based redundant disk arrays, RIMAC exploits parity redundancy to dynamically XOR-reconstruct data being accessed toward standby disk(s) at both cache and disk levels. By avoiding passive spin-ups, RIMAC can significantly improve both energy efficiency and performance. We evaluated RIMAC by augmenting a validated storage system simulator disksim and tested four real-life server traces including HP's cello99, TPC-D, OLTP and SPC's search engine. Comprehensive results indicate RIMAC is able to reduce energy consumption by up to 18% and simultaneously improve the average response time by up to 34% in a small-scale RAID-5 system compared with threshold-based power management schemes.
Bézier surfaces with linear isoparametric lines
Authors: Imre Juhász, Ágoston Róth
Venue: Computer Aided Geometric Design (2008)

We provide control point based necessary and sufficient conditions for (n,m) Bezier surfaces to have linear isoparametric lines.
Integrating rich user feedback into intelligent user interfaces
Authors: Simone Stumpf, Erin Sullivan, Erin Fitzhenry, Ian Oberst, Weng-Keen Wong, Margaret Burnett
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2008)

The potential for machine learning systems to improve via a mutually beneficial exchange of information with users has yet to be explored in much detail. Previously, we found that users were willing to provide a generous amount of rich feedback to machine learning systems, and that the types of some of this rich feedback seem promising for assimilation by machine learning algorithms. Following up on those findings, we ran an experiment to assess the viability of incorporating real-time keyword-based feedback in initial training phases when data is limited. We found that rich feedback improved accuracy but an initial unstable period often caused large fluctuations in classifier behavior. Participants were able to give feedback by relying heavily on system communication in order to respond to changes. The results show that in order to benefit from the user's knowledge, machine learning systems must be able to absorb keyword-based rich feedback in a graceful manner and provide clear explanations of their predictions.
Forbidden ordered subgraph vs. forbidden subgraph characterizations of graph classes
Authors: Mark Ginn
Venue: Journal of Graph Theory (1999)

We show that the minimum set of unordered graphs that must be forbidden to get the same graph class characterized by forbidding a single ordered graph is infinite. &copy; 1999 John Wiley & Sons, Inc. J Graph Theory 30: 71&ndash;76, 1999 This work was done while the author was at Dept. of Mathematics and Computer Science, Austin Peay State University, Clarksville, TN 37044.
I'm Pc01002/SpringPeeper/ED288l.6; Who are You?
Authors: Susan Landau, Deirdre K. Mulligan
Venue: IEEE Security and Privacy (2008)

In considering identity management, the first issue is—What is identity? This is, of course, an issue that has plagued poets, philosophers, and playwrights for centuries. We're concerned with a more prosaic version of the question: How does an entity recognize another entity? This important question occurs when access to resources, such as health or financial records, services, or benefits, is limited to specific entities. The entity in question could be a person, a computer, or even a device with quite limited memory and computational power. In this issue of IEEE Security & Privacy—the first of what we suspect will be several special issues on identity management—we have chosen to focus on identity management in which the entity being identified is a person.
Development of a Knowledge Management System Integrated with Local Communication Channels and Knowledge Management Initiatives for Kenyan Rural Farming Communities
Authors: N. M. A. E. Dewi Wirastuti, Rose Luckin, Ray E. Sheriff, Kevin Walker, Josh Underwood, Lynne Dunckley
Venue: Proceedings of the Fifth IEEE International Conference on Wireless, Mobile, and Ubiquitous Technology in Education (2008)

This paper presents an innovative application of wireless, mobile and ubiquitous technologies to support informal and collaborative learning in Kenyan rural farming communities. Such an approach is achieved by the development of a Knowledge Management System (KMS) integrated with existing local community communication channels, together with experimental Knowledge Management (KM) initiatives employing the VeSeL (Village e-Science for Life) distributed resource kits (DRKs). The initiatives support illiterate and semi-literate farming community groups, in learning new agriculture practices, and also enable the use of advanced digital technology to improve their agricultural practices and literacy levels. Results of a recent field trip to Kenya are presented and an application sketch is developed. The process of applying wireless and Internet technologies for the education of local farming communities, using irrigation and water management as the application, concludes the paper.
A Case Study: A Model-Based Approach to Retrofit a Network Fault Management System with Self-Healing Functionality
Authors: Yan Liu, Jing Zhang, Michael Jiang, David Raymer, John Strassner
Venue: Proceedings of the 15th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems (2008)

Adding self-healing capabilities to network management systems holds great promise for delivering important goals, such as QoS, while simultaneously lowering capital expenditure, operation cost, and maintenance cost. In this paper, we present a model-based approach to add self-healing capabilities to a fault management system for cellular networks. We propose a generic modeling framework to categorize software failures and specify their dispositions at the model level for the target system. This facilitates the deployment of a control loop for adding autonomic capabilities into the system architecture, which include self-monitoring, self-healing, and self-adjusting functionality. While self-monitoring oversees the environmental conditions and system behavior, self-healing is accomplished by instrumenting the system with self-adjusting operations. We include a case study on a prototype Intelligent Network Fault Management system to illustrate this approach by showing how these autonomic capabilities can be added and deployed. Specifically, these autonomic capabilities are derived from self-* model specifications, and are used to mitigate the risk of specified failures and maintain the health of the system in response to different types of faults encountered.
Web query translation via web log mining
Authors: Rong Hu, Weizhu Chen, Peng Bai, Yansheng Lu, Zheng Chen, Qiang Yang
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

This paper describes a method to automatically acquire query translation pairs by mining web click-through data. The extraction requires no crawling or Chinese words segmentation, and can capture popular translations. Experimental results on a real click-through data show that only 17.4% of the extracted queries are in the dictionary, and our method can achieve 62.2% (in top-1) to 80.0% (in top-5) precision in translating web queries. Moreover, the extracted translations are semantically relevant to the source query, which is particularly useful for Cross-Lingual Information Retrieval (CLIR).
A Predictable Mobility-Based Data Dissemination Protocol for Wireless Sensor Networks
Authors: Euisin Lee, Soochang Park, Fucai Yu, Younghwan Choi, Min-Sook Jin, Sang-Ha Kim
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (2008)

Many dissemination protocols on the mobility support in wireless sensor networks have been designed based on the assumption that the movement trace of sinks is random. However, the mobility of the sinks in many applications, for example, the movement traces of a soldier on operation in a battle field or a firefight on rescue operation in the disaster area, can be determined in advance since they move in accordance with the decided operation or the drill regulation to perform their task. In this paper, we propose a Predictable Mobility-based Data Dissemination protocol (PMDD) that enables data to directly route from source nodes to moving sinks by taking into consideration predictable movement behavior of the sinks. We also compare the performance of the PMDD with those of other dissemination protocols with random movement behavior of the sinks, and show the superiority of the PMDD based on network lifetime, data delivery ratio, and delay latency.
Supporting the development of collaborative problem-based learning environments with an intelligent diagnosis tool
Authors: Chenn-Jung Huang, Yi-Ta Chuang
Venue: Expert Systems with Applications: An International Journal (2008)

Problem-based learning (PBL) has been implemented for years in lots of countries and the achieved performance is plausible. However, the implementation of PBL course often needs a lot of human resources; the instructors often need offering instructions to the learners intensively. As the modern computer science and the Internet gains wide popularity around the world, e-learning is taken by the learners as an important study aid and thereby lightens the burden of the instructors. In this research, we incorporate the PBL activity into an open software e-learning platform, Moodle, and a learning diagnosis tool is added in the platform to alleviate the loading of the instructors. The learners' transcripts posted on discussion board and chatting room are first preprocessed by the learning parameter extraction module to truly reflect the learners' planning on the solutions to the designated problem. The extracted parameters are further fed into a classification algorithm to examine the quality of the learners' suggestions and some appropriate feedback will be issued to the learners/instructor if needed. The experimental results show that the text mining and machine learning techniques used in this work are effective in automatically providing useful feedback for the learners to progress through the ill-structured problem solving.
Non-linear variable selection for artificial neural networks using partial mutual information
Authors: Robert J. May, Holger R. Maier, Graeme C. Dandy, T.M.K. Gayani Fernando
Venue: Environmental Modelling Software (2008)

Artificial neural networks (ANNs) have been widely used to model environmental processes. The ability of ANN models to accurately represent the complex, non-linear behaviour of relatively poorly understood processes makes them highly suited to this task. However, the selection of an appropriate set of input variables during ANN development is important for obtaining high-quality models. This can be a difficult task when considering that many input variable selection (IVS) techniques fail to perform adequately due to an underlying assumption of linearity, or due to redundancy within the available data. This paper focuses on a recently proposed IVS algorithm, based on estimation of partial mutual information (PMI), which can overcome both of these issues and is considered highly suited to the development of ANN models. In particular, this paper addresses the computational efficiency and accuracy of the algorithm via the formulation and evaluation of alternative techniques for determining the significance of PMI values estimated during selection. Furthermore, this paper presents a rigorous assessment of the PMI-based algorithm and clearly demonstrates the superior performance of this non-linear IVS technique in comparison to linear correlation-based techniques.