ppxscal/embedding_network huggingface dataset:
New broadcast encryption scheme using tree-based circle
Authors: Nam-Su Jho, Eun Sun Yoo, Jung Hee Cheon, Myung-Hwan Kim
Venue: Proceedings of the 5th ACM workshop on Digital rights management (2005)

Since broadcast encryption was first introduced in 1993 by Fiat and Naor, many broadcast encryption schemes have been developed. Among these, schemes based on tree structure and linear structure are notable. The subset difference (SD) scheme and layered subset difference (LSD) scheme based on tree structure have small user-key size and small transmission overhead when the number r of revoked users is very small. The punctured interval (PI) scheme based on linear (or circular) structure has better transmission overhead when r is not too small.In this paper, we propose a new broadcast encryption scheme, called the tree-based circle (TC) scheme, combining tree structure and circular structure. In this scheme, the transmission overhead is proportional to r like in the SD scheme for small r and becomes asymptotically same as that of the PI scheme when r grows, keeping the computation cost and the storage size small. The TC scheme also inherits the flexibility of the PI scheme. We further improve the transmission overhead of the TC scheme, when r is very small, by adopting the notion of cascade arc.
A Two-Level Gradient Based Approach for Intelligent Coordination of Large-Scale Systems — Part I
Authors: Nasser Sadati
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

In this paper, the concept of coordination is introduced within the framework of two-level large-scale systems and a new approach based on Interaction Prediction Principle is presented. The proposed approach is formulated in an intelligent manner in such a way that it provides a new strategy that can be used to synthesize an on-line supervisory controller for the overall two-level large-scale systems, extendable to multi-level control systems. By using the new methodology which is based on using neural network for modeling each sub-system, typical gradient method for optimization of first-level sub-problems, and the gradient of the interaction prediction errors related to the predicted interactions, at the second level, the coordination of the overall large-scale system is done. Simulation results demonstrate the effectiveness of the proposed strategy in compare to the classical methods.
Local Detection of Selfish Routing Behavior in Ad Hoc Networks
Authors: Bo Wang, Sohraab Soltani, Jonathan K. Shapiro, Pang-Ning Tan
Venue: Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks (2005)

Reputation mechanisms for detecting and punishing free-riders in ad hoc networks depend on the local detection of selfish behavior. Although naive selfish strategies based on dropping data packets are readily detected, more sophisticated strategies that manipulate ad hoc routing protocols present a greater challenge. In this work we develop a method to distinguish selfish peers from cooperative ones based solely on local observations of AODV routing protocol behavior. Our approach uses the finite state machine model of locally observed AODV actions to build up a statistical description of the behavior of each neighbor. We apply a series of wellknown statistical tests to features derived from this description to partition the set neighboring nodes into a cooperative and selfish class. Simulation results for a non-mobile ad hoc network show that our approach can detect two different types of routing manipulation while maintaining a low rate of false positives.
Convergence of Estimation of Distribution Algorithms in Optimization of Additively Noisy Fitness Functions
Authors: Yi Hong, Qingsheng Ren, Jin Zeng, Yuchou Chang
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

Noise is a common phenomenon in many real-world optimizations. It has long been argued that evolutionary algorithm (EA) should be relatively robust against it. As a novel computing model in evolutionary computations, Estimation of Distribution Algorithm (EDA) is also encountered with it. This paper initially presents three dynamic models of EDA under the additively noisy environment with three different selection methods (proportional selection method, truncation selection method and tournament selection method). We verify that when the population size is infinite, EDA can converge to the global optimal point. This concept establishes the theoretic foundation for optimization of noisy fitness functions with EDA.
Transshipment and Time Windows in Vehicle Routing
Authors: Christopher Mues, Stefan Pickl
Venue: Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks (2005)

Transshipment Problems and Vehicle Routing Problems with Time Windows (VRPTW) are common network flow problems and well studied. Combinations of both are known as intermodal transportation problems. This concept describes some real world transportation problems more precisely and can lead to better solutions. But they are examined rarely as mathematical optimization problems. In this paper two approaches will be developed for this kind of merged problems. The source for our considerations is the Pickup and Delivery Problem with time windows as a generalization of the VRPTW. This will be extended by transshipment. Thereby loads can be transported by different vehicles on their path from origin to destination. A column generation technique is proposed for solving this problem.
Agile project management: steering from the edges
Authors: Sanjiv Augustine, Bob Payne, Fred Sencindiver Susan Woodcock
Venue: Communications of the ACM (2005)

Agile project management lets software project managers and employees alike adapt to changing circumstances, rather than try to impose rigid formal controls, as in traditional linear development methods.
Efficient Design and Analysis of Robust Power Distribution Meshes
Authors: Puneet Gupta, Andrew B. Kahng
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

With increasing design complexity, as well as continued scaling of supplies, the design and analysis of power/ground distribution networks poses a difficult problem in modern IC design. We propose several closed-form solutions for power distribution network optimization and analysis which explicitly take into consideration the mesh topology of modern power-ground networks. Our analysis and optimization methods have essentially zero runtime for global power grids, and are therefore usable for layout optimization. Experimental validation shows that our IR drop estimation method has almost perfect correlation with true IR drop. Our closed-form sizing solutions save up to 32% area while preserving the peak IR drop; alternatively, we can reduce peak IR drop by up to 33% while preserving the total area of the power distribution network. Our iterated incremental power distribution network improvement technique achieves up to 33% reduction (in one iteration) in peak IR drop over uniformly sized meshes. We also introduce a measure for robustness of power distribution networks to current and process variations.
TeamSearch: Comparing Techniques for Co-Present Collaborative Search of Digital Media
Authors: Meredith Ringel Morris, Andreas Paepcke, Terry Winograd
Venue: Proceedings of the First IEEE International Workshop on Horizontal Interactive Human-Computer Systems (2006)

Interactive tables can enhance small-group colocated collaborative work in many domains. One application enabled by this new technology is copresent, collaborative search for digital content. For example, a group of students could sit around an interactive table and search for digital images to use in a report. We have developed TeamSearch, an application that enables this type of activity by supporting group specification of Boolean-style queries. We explore whether TeamSearch should consider all group members' activities as contributing to a single query or should interpret them as separate, parallel search requests. The results reveal that both strategies are similarly efficient, but that collective query formation has advantages in terms of enhancing group collaboration and awareness, allowing users to bootstrap query-specification skills, and personal preference. This suggests that team-centric UIs may offer benefits beyond the "staples" of efficiency and result quality that are usually considered when designing search interfaces.
Horizontal decomposition of Prevayler
Authors: Irum Godil, Hans-Arno Jacobsen
Venue: Proceedings of the 2005 conference of the Centre for Advanced Studies on Collaborative research (2005)

Aspect-Oriented Programming (AOP) is an emerging paradigm to modularize crosscutting concerns. A series of guidelines to refactor a software system into a common core and a set of variable functionalities have become known as Horizontal Decomposition (HD). In this paper we apply the HD principles to the Prevayler main memory database management system. The objective is to evaluate and refine these principles and to extract patterns of their use through a case study on a popular open-source software system. Our evaluation shows that HD reveals six crosscutting functionalities. The refactoring of these concerns yield 36 different configurations of the Prevayler system which were previously not possible. The refactoring also reduces the core Prevayler code size by 53%, demonstrates a decrease of coupling between core functionality components by 43%, and reduces the lack of cohesion of the core system by 71%. Given the heterogeneous nature of crosscutting displayed in Prevayler, the size and separation of concern metrics have not reduced for the overall refactored system, i.e., for the core composed with the aspects. A posterior analysis of the re-engineering process reveals 22 refactoring patterns that could be readily used by an automatic aspect refactoring tool.
An Evaluation of Java Application Containers according to Security Requirements
Authors: Almut Herzog, Nahid Shahmehri
Venue: Proceedings of the 14th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprise (2005)

Web browsers, web servers, Java application servers and OSGi frameworks are all instances of Java execution environments that run more or less untrusted Java applications. In all these environments, Java applications can come from different sources. Consequently, application developers rarely know which other applications exist in the target Java execution environment. This paper investigates the requirements that need to be imposed on such a container from a security point of view and how the requirements have been implemented by different Java application containers. More specifically, we show a general risk analysis considering assets, threats and vulnerabilities of a Java container. This risk analysis exposes generic Java security problems and leads to a set of security requirements. These security requirements are then used to evaluate the security architecture of existing Java containers for Java applications, applets, servlets, OSGi bundles, and Enterprise Java Beans. For comparison, the requirements are also examined for a C++ application.
Towards a software architecture for DRM
Authors: Sam Michiels, Kristof Verslype, Wouter Joosen, Bart De Decker
Venue: Proceedings of the 5th ACM workshop on Digital rights management (2005)

The domain of digital rights management (DRM) is currently lacking a generic architecture that supports interoperability and reuse of specific DRM technologies. This lack of architectural support is a serious drawback in light of the rapid evolution of a complex domain like DRM. It is highly unlikely that a single DRM technology or standard will be able to support the diversity of devices, users, platforms, and media, or the wide variety of system requirements concerning security, flexibility, and efficiency. This paper analyses state-of-the-art DRM technologies and extracts from them high level usage scenarios according to content consumers, producers, and publishers. In addition, the key services are identified both from a functional and security perspective. Identifying key DRM services and locating them in an overall structure brings us one step closer to a software architecture for DRM. Having available a software architecture should help the DRM community in reasoning about DRM systems, and in achieving reuse and interoperability of multiple domain-specific DRM technologies and standards.
A study on security of multi-user systems and stream ciphers
Authors: Shaoquan Jiang
Venue:  (2005)

Multi-user security systems widely exist in the real world. The password based key exchange (KE) protocol is such an example, where parties hold a human memorable password, using which they establish a common session key and then secure the subsequent communication with this key. In the security point, besides the well understood man-in-the-middle attack, the adversary might launch a brute force search like attack (called a dictionary attack). Our first work is a construction of a 3-round password based two party key exchange protocol that supports mutual authentication. Our protocol is provably secure without random oracles. This is the first work in the literature to achieve all these simultaneously. Our second work considers the problem of a group password authenticated key exchange, where each user individually shares an independent password with a common server. Our main result is to prove the security of a protocol reported by Wan et al. This is the first provably secure result for password based group key exchange protocols where the group size is general. We then consider another multi-user system: a multi-service oriented broadcast encryption system, where a center wants to securely distribute data to a dynamic set of authorized users. In our work, we propose a simple framework for this problem. Our work is an extension of the single service framework due to Naor et al. and mainly has the following features: (1) each user's secret storage is independent of the number of services; (2) the service unsubscriptions are dealt scalably. We show that our framework is secure with respect to a model of dynamic security. Then, we move to the security of stream ciphers. We first propose a simple stream cipher called an editing generator, which is a combined model from the Stop-and-Go generator and the Shrinking generator. We provide a security analysis for our generator. Next, we investigate a success probability conjecture on an edit distance attack to the well-known alternating step generator. We show that this attack is successful.
Tracking users' capture intention: a novel complementary view for home video content analysis
Authors: Tao Mei, Xian-Sheng Hua, He-Qin Zhou
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

In this paper, we present a novel view to home video content analysis, which aims at tracking the capture intention of camcorder users. Based on the study of intention mechanism in psychology, a set of domain-specific capture intention concepts are defined. A comprehensive and extensible scheme consisting of video structuring, intention oriented feature analysis, as well as intention unit segmentation and classification is proposed to mine the users' capture intention. Experiments were carried on home video sequences of 90 hours in total, taken by 16 persons in recent 20 years. Both the user study and objective evaluations indicate that our proposed intention-based approach is an effective complement to existing home video content analysis schemes.
Achieving Weighted Fairness between Uplink and Downlink in IEEE 802.11 DCF-Based WLANs
Authors: Jiwoong Jeong, Sunghyun Choi, Chong-kwon Kim
Venue: Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

In this paper, we first propose an analytical model of WLANs (Wireless LANs) with an arbitrary backoff distribution and AIFS (Arbitration Inter-Frame Space). From the analysis, we show that the achievable bandwidth is determined by the mean of backoff distribution regardless of the shape of the backoff distribution. We compare the effectiveness of four parameters on channel access differentiation, namely, the mean of backoff distribution, CWmin (Initial Contention Window), the number of backoff stages, and AIFS. Numerical results show that the mean of backoff distribution provides weighted fair channel access most accurately. Second, based on the proposed analytic frame work, we develop three schemes for the uplink/downlink bandwidth differentiation in order to achieve weighted fairness between uplink and downlink transmissions. Note that IEEE 802.11 is known to have unfairness between uplink and downlink accesses. Each scheme is characterized according to the corresponding channel access rule. The simulation results show that the proposed schemes achieve high system throughput while accurately differentiating bandwidth allocation.
Developing semantic digital libraries using data mining techniques
Authors: Hyunki Kim
Venue:  (2005)

We define the semantic digital libraries as the digital libraries that can discover hidden, useful information from large amounts of stored data using data mining techniques such as clustering, classification, association rule mining, and visualization techniques. To build a semantic digital library, we first propose an integrated digital library system that provides multiple viewpoints of harvested metadata collections by combining search and data mining technologies. This system provides three value-added services: (1) the cross-archive search service provides a term view of harvested metadata, (2) the concept browsing service provides a subject view of harvested metadata, and (3) the collection summary service provides a collection view of each metadata collection. We also propose a text data mining method using a hierarchical self-organizing map algorithm to build concept hierarchies from Dublin Core metadata. We then present a new classification method, called Associative Na&iuml;ve Bayes (ANB), to associate MEDLINE citations with Gene Ontology (GO) terms. We define the concept of class-support to find frequent itemsets and the concept of class-all-confidence to find interesting itemsets. In the training phase, ANB finds frequent and interesting itemsets and estimates the class prior probabilities and the probabilities of itemsets for all classes. Once the frequent and interesting itemsets are discovered in the training phase, new unlabeled examples are classified by the classification algorithm by incrementally choosing the most interesting itemset. Empirical test results on three MEDLINE datasets show that ANB is superior to both naive Bayesian classifier and Large Bayes. The results also show that ANB is more scalable than Support Vector Machines. Finally, we present a text mining method that uses both text categorization and text clustering for building concept hierarchies for MEDLINE citations. The approach we propose is a three-step data mining process for organizing MEDLINE database: (1) categorizations according to Medical Subject Headings (MeSH) terms, MeSH major topics, and the co-occurrence of MeSH descriptors; (2) clustering using the results of MeSH term categorization; and (3) visualization of categories and hierarchical clusters. The hierarchies automatically generated may be used to support users in browsing behavior and help them identify good starting points for searching.
Guest Editor's Introduction: ITC Examines How Test Helps the Fittest Survive
Authors: Scott Davidson
Venue: IEEE Design Test (2005)

The theme of the 2005 International Test Conference is "Test: Survival of the Fittest." In conjunction with this year's ITC, this special section examines how test helps the fittest of the industry's chips, boards, and systems survive manufacturing to reach its customers. These articles discuss topics such as X-tolerant test response compaction, reducing yield loss using a constrained ATPG, and using IDDQ testing with today's high background currents.
Edge detection, image segmentation and their applications in microarray image analysis
Authors: Peihua Qiu
Venue:  (2005)

We consider the problem of detecting jump location curves of regression surfaces. In the literature, most existing methods detect jumps in regression surfaces based on estimation of either the first-order or the second-order derivatives of the regression surface. Methods based on the first-order derivatives are usually better in removing the noise effect, whereas methods based on the second-order derivatives are often superior in localization of the detected jumps. In this thesis research, we suggest a new procedure for jump detection in regression surfaces, which combines the major strengths of the above two types of methods. Our method is based on estimation of both the first-order and second-order derivatives of the true regression surface. Theoretical justifications and numerical studies show that it works well in applications. Jump detection in regression surfaces has many applications. One important application is image segmentation for analyzing gene microarray images. Gene microarray data are widely used in applications, including pharmaceutical and clinical research. By comparing gene expressions in normal and abnormal cells, microarrays can be used for identifying genes involved in particular diseases, and then these genes can be targeted by therapeutic drugs. Many gene expression data are produced from spotted microarray images. A microarray image consists of thousands of spots, with individual DNA sequences first printed at each spot and then equal amount of probe samples from treatment and control cells mixed and hybridized with the printed DNA sequences. To obtain gene expression data, the image needs to be segmented first to separate foregrounds from backgrounds for individual spots, and then averages of foreground pixels are used for computing the gene expression data. So image segmentation of microarray images is related directly to the reliability of gene expression data. Several image segmentation procedures have been suggested and included in some software packages handling gene microarray data. In this thesis research, a new image segmentation methodology is proposed based on local polynomial kernel smoothing. Theoretical arguments and numerical studies show that it has some good statistical properties and would perform well in applications.