ppxscal/embedding_network huggingface dataset:
Throughput-efficient sequential channel sensing and probing in cognitive radio networks under sensing errors
Authors: Tao Shu, Marwan Krunz
Venue: Proceedings of the 15th annual international conference on Mobile computing and networking (2009)

In this paper, we exploit channel diversity for opportunistic spectrum access (OSA). Our approach uses channel quality as a second criterion (along with the idle/busy status of the channel) in selecting channels to use for opportunistic transmission. The difficulty of the problem comes from the fact that it is practically infeasible for a CR to first scan all channels and then pick the best among them, due to the potentially large number of channels open to OSA and the limited power/hardware capability of a CR. As a result, the CR can only sense and probe channels sequentially. To avoid collisions with other CRs, after sensing and probing a channel, the CR needs to make a decision on whether to terminate the scan and use the underlying channel or to skip it and scan the next one. The optimal use-or-skip decision strategy that maximizes the CR's average throughput is one of our primary concerns in this study. This problem is further complicated by practical considerations, such as sensing/probing overhead and sensing errors. An optimal decision strategy that addresses all the above considerations is derived by formulating the sequential sensing/probing process as a rate-of-return problem, which we solve using optimal stopping theory. We further explore the special structure of this strategy to conduct a "second-round" optimization over the operational parameters, such as the sensing and probing times. We show through simulations that significant throughput gains (e.g., about 100%) are achieved using our joint sensing/probing scheme over the conventional one that uses sensing alone.
Globally Optimal Least Squares Solutions for Quasiconvex 1D Vision Problems
Authors: Carl Olsson, Martin Byröd, Fredrik Kahl
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

Solutions to non-linear least squares problems play an essential role in structure and motion problems in computer vision. The predominant approach for solving these problems is a Newton like scheme which uses the hessian of the function to iteratively find a local solution. Although fast, this strategy inevitably leeds to issues with poor local minima and missed global minima.In this paper rather than trying to develop an algorithm that is guaranteed to always work, we show that it is often possible to verify that a local solution is in fact also global. We present a simple test that verifies optimality of a solution using only a few linear programs. We show on both synthetic and real data that for the vast majority of cases we are able to verify optimality. Further more we show even if the above test fails it is still often possible to verify that the local solution is global with high probability.
Length Encoded Secondary Structure Profile for Remote Homologous Protein Detection
Authors: Yen-Chu Hsu, Chien-Ming Chen, Tun-Wen Pai, Jyh-Fu Jeng, Chin-Hua Hu, Wen-Shyong Tzou
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

Protein data has an explosive increasing rate both in volume and diversity, yet many of its structures remain unresolved, as well their functions remain to be identified. The conventional sequence alignment tools are insufficient in remote homology detection, while the current structural alignment tools would encounter the difficulties for proteins of unresolved structure. Here, we aimed to overcome the combination of two major obstacles for detecting remote homologous proteins: proteins with unresolved structure, and proteins of low sequence identity but high structural similarity. We proposed a novel method for improving the performance of protein matching problem, especially for mining remote homologous proteins. In this study, existing secondary structure prediction techniques were applied to provide the locations of secondary structure elements of proteins. The proposed LESS (Length Encoded Secondary Structure) profile was then constructed for segment-based similarity comparison in parallel computing. As compared to a conventional residue-based sequence alignment tool, detection of remote protein homologies through LESS profile is favourable in terms of speed and high sequence diversity, and its accuracy and performance can improve the deficiencies of the traditional primary sequence alignment methodology. This method may further support biologists in protein folding, evolution, and function prediction.
Multi-Agent System Using G-XMDR for Data Synchronization in Pervasive Computing Environments
Authors: Youn-Gyou Kook, R. Young-Chul Kim, Young-Keun Choi
Venue: Multi-Agent Systems for Society: 8th Pacific Rim International Workshop on Multi-Agents, PRIMA 2005, Kuala Lumpur, Malaysia, September 26-28, 2005, Revised Selected Papers (2009)

This paper extends XMDR[19] into G-XMDR (Global-Extended Metadata Registry) to ensure the interoperability of data, and to describe multi agent system using G-XMDR. The proposal G-XMDR will be solved the problem of data heterogeneity and inconsistency in sharing and exchanging each local data in virtual pervasive computing environments. Data heterogeneity is generated by different definition or mismatched expression of the same meaning data. Therefore, we define and design G-XMDR based on XMDR(ISO/IEC 11179) specification to interoperate various each local data in pervasive computing. We also describe our synchronizing multi agent system, which uses G-XMDR to solve data heterogeneity for data interoperability through synchronizing data. It provides more efficient agent through reducing errors that happened on synchronizing requests and adding new pervasive computing environments with their own each local data.
A Uniform (Bi-)Simulation-Based Framework for Reducing Tree Automata
Authors: Parosh A. Abdulla, Lukáš Holík, Lisa Kaati, Tomáš Vojnar
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

In this paper, we address the problem of reducing the size of nondeterministic (bottom-up) tree automata. We propose a uniform framework that allows for combining various upward and downward bisimulation and simulation relations in order to obtain a language-preserving combined relation suitable for reducing tree automata without a need to determinise them. The framework generalises and extends several previous works and provides a broad spectrum of different relations yielding a possibility of a fine choice between the amount of reduction and the computational demands. We, moreover, provide a significantly improved way of computing the various combined (bi-)simulation relations. We analyse properties of the considered relations both theoretically as well as through a series of experiments.
Crops selection for optimal soil planning using multiobjective evolutionary algorithms
Authors: Christian Von Lücken, Ricardo Brunelli
Venue: Proceedings of the 20th national conference on Innovative applications of artificial intelligence - Volume 3 (2008)

Farm managers have to deal with many conflicting objectives when planning which crop to cultivate. Soil characteristics are extremely important when determining yield potential. Fertilization and liming are commonly used to adapt soils to the nutritional requirements of the crops to be cultivated. Planting the crop that will best fit the soil characteristics is an interesting alternative to minimize the need for soil treatment, reducing costs and potential environmental damages. In addition farmers usually look for investments that offer the greatest potential earnings with the least possible risks. According to the objectives to be considered the crop selection problem can be difficult to solve using traditional tools. Therefore, this work proposes an approach based on Multiobjective Evolutionary Algorithms to help in the selection of an appropriate cultivation plan considering five crop alternatives and five objectives simultaneously.
Avoiding Spurious Feedback Loops in the Reconstruction of Gene Regulatory Networks with Dynamic Bayesian Networks
Authors: Marco Grzegorczyk, Dirk Husmeier
Venue: Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics (2009)

Feedback loops and recurrent structures are essential to the regulation and stable control of complex biological systems. The application of dynamic as opposed to static Bayesian networks is promising in that, in principle, these feedback loops can be learned. However, we show that the widely applied BGe score is susceptible to learning spurious feedback loops, which are a consequence of non-linear regulation and autocorrelation in the data. We propose a non-linear generalisation of the BGe model, based on a mixture model, and demonstrate that this approach successfully represses spurious feedback loops.
Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Venue: European Chapter Meeting of the ACL (2009)

We are delighted to present you with this volume containing the papers accepted for presentation at the 12th Conference of the European Chapter of the Association for Computational Linguistics, held in Athens, Greece, from March 30th till April 3rd 2009. EACL 2009 received yet another record-breaking number of submissions, with 360 valid submissions against 264 for EACL 2006 and 181 for EACL 2003. Thanks to the new policy adopted by EACL regarding modes of presentation, we were nonetheless able to accept 100 papers (of which 2 were later withdrawn), achieving a healthy acceptance rate of 28% against only 20% in 2006 and 27% in 2003. Indeed, in 2009, the EACL conference will renew its format by having the main conference papers presented either as regular talks or as posters, with posters getting both a ten-minute quick-fire presentation in a thematic session and a one-hour discussion period in a traditional poster session. EACL 2009 will thus feature 41 posters and 57 talks, all with equal status in terms of quality and appearance in the proceedings. Not only does this move towards a balanced mix of traditional talks, quick-fire presentations and poster sessions allow us to maintain a reasonable acceptance rate, we also believe that it will increase interaction between researchers and contribute to a more lively scientific exchange. The increased number of submissions naturally comes with an increased reviewing load and we are greatly indebted to the 11 area chairs who recruited 449 reviewers and managed the reviewing process in their areas. Each paper submission was reviewed by three reviewers, who were furthermore encouraged to discuss any divergences they might have, and the papers in each area were ranked by the area chair. The final selection was made by the program co-chairs after an independent check of all reviews and discussions with the area chairs.
An Agent-Based English Auction Protocol Using Elliptic Curve Cryptosystem for Mobile Commerce
Authors: Yu-Fang Chung, Tzer-Shyong Chen, Yu-Ting Chen, Chiu-Chan Lee, Szu-Wen Wang
Venue: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing (2009)

With the rapid development of Internet and the extensive use of mobile phones, the demand for the use of mobile devices in Internet auctions has increased. Because of this trend, there is an incentive to develop an auction model that is to be used on a mobile-based environment. Recently, Kuo-Hsuan Huang proposed a mobile auction agent model (MoAAM), which allows the bidders to participate in online auctions through a mobile agent. Huang used modular exponentiation operations in his method; however, it would increase the processing time for key generation, bidding, and verification. Thus, we propose to add the concept of Elliptic Curve Cryptosystem (ECC) onto MoAAM, because ECC is able to provide low computation amount and small key size. It would aid to increase the speed in generating keys, bidding, and verification. In terms of reduction of computation load on mobile devices and auction-manager server load, the proposed method will make online auction system become more convenient for users. This paper mainly uses the English auction protocol as the key auction protocol. The protocol consists of four entities: Registration Manager, Agent House, Auction House and Bidder. Especially, our proposed method conforms to the requirements of an online auction protocol, like anonymity, public verifiability, one-time registration, etc.
Supraliminal Audio Steganography: Audio Files Tricking Audiophiles
Authors: Heather Crawford, John Aycock
Venue: Information Hiding: 11th International Workshop, IH 2009, Darmstadt, Germany, June 8-10, 2009, Revised Selected Papers (2009)

A supraliminal channel is one in which the secret message is encoded in the semantic content of a cover object, and that is robust against an active warden. Such channels frequently have a very low embedding rate and therefore are unsuitable for more than simply exchanging steganographic public keys. This paper introduces a proof-of-concept supraliminal channel that uses WAV files to provide a high-bitrate method of embedding information in common media.
Reasoning with cardinal directions: an efficient algorithm
Authors: Xiaotong Zhang, Weiming Liu, Sanjiang Li, Mingsheng Ying
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

Direction relations between extended spatial objects are important commonsense knowledge. Recently, Goyal and Egenhofer proposed a formal model, called Cardinal Direction Calculus (CDC), for representing direction relations between connected plane regions. CDC is perhaps the most expressive qualitative calculus for directional information, and has attracted increasing interest from areas such as artificial intelligence, geographical information science, and image retrieval. Given a network of CDC constraints, the consistency problem is deciding if the network is realizable by connected regions in the real plane. This paper provides a cubic algorithm for checking consistency of basic CDC constraint networks. As one by product, we also show that any consistent network of CDC constraints has a canonical realization in digital plane. The cubic algorithm can also been adapted to cope with disconnected regions, in which case the current best algorithm is of time complexity O(n5).
Peer-to-peer estimation over wireless sensor networks via Lipschitz optimization
Authors: Carlo Fischione, Alberto Speranzon, Karl Henrik Johansson, Alberto Sangiovanni-Vincentelli
Venue: Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (2009)

Motivated by a peer-to-peer estimation algorithm in which adaptive weights are optimized to minimize the estimation error variance, we formulate and solve a novel nonconvex Lipschitz optimization problem that guarantees global stability of a large class of peer-to-peer consensus-based algorithms for wireless sensor network. Because of packet losses, the solution of this optimization problem cannot be achieved efficiently with either traditional centralized methods or distributed Lagrangian message passing. We prove that the optimal solution can be obtained by solving a set of nonlinear equations. A fast distributed algorithm, which requires only local computations, is presented for solving these equations. Analysis and computer simulations illustrate the algorithm and its application to various network topologies.
Development of Symbiotic Brain-Machine Interfaces Using a Neurophysiology Cyberworkstation
Authors: Justin C. Sanchez, Renato Figueiredo, Jose Fortes, Jose C. Principe
Venue: Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques (2009)

We seek to develop a new generation of brain-machine interfaces (BMI) that enable both the user and the computer to engage in a symbiotic relationship where they must co-adapt to each other to solve goal-directed tasks. Such a framework would allow the possibility real-time understanding and modeling of brain behavior and adaptation to a changing environment, a major departure from either offline learning and static models or one-way adaptive models in conventional BMIs. To achieve a symbiotic architecture requires a computing infrastructure that can accommodate multiple neural systems, respond within the processing deadlines of sensorimotor information, and can provide powerful computational resources to design new modeling approaches. To address these issues we present or ongoing work in the development of a neurophysiology Cyberworkstation for BMI design.
Characterizing, Measuring, and Validating the Temporal Consistency of Live-Virtual-Constructive Environments
Authors: Douglas D. Hodson, Rusty O. Baldwin
Venue: Simulation (2009)

A distinguishing characteristic of interactive live-virtual-constructive (LVC) environments is the relaxation of data consistency to improve the performance and scalability of the underlying distributed simulation. Relaxing data consistency improves the interactive performance of the environment because autonomous distributed simulation applications can continue executing and responding to local inputs without waiting for the most current shared data values. Scalability also improves since live and simulated entities from distant geographic locations can be interconnected through relatively high-latency networks. We introduce a temporal consistency model to formally define consistency for the dynamic shared state of a LVC environment for both continuous and discrete data objects. The level of inconsistency tolerated by a LVC is found to be a function of the accuracy and timeliness requirements for the distributed data objects. These requirements are mapped to specific time intervals for which data objects are considered valid. We also develop a real-time algorithm to compute the temporal consistency of individual data objects within the LVC.
Horizontal collaboration in semiconductor manufacturing industry supply chain: An evaluation of collaboration intensity index
Authors: Bikram K. Bahinipati, Arun Kanda, S. G. Deshmukh
Venue: Computers and Industrial Engineering (2009)

This paper aims to provide a generic quantitative model to comprehensively assess the degree of collaboration with individual horizontal collaboration initiatives with a view to check feasibility for satisfying the customer requirements. The analytic hierarchy process-fuzzy logic model (AHP-FLM) approach is chosen for developing the model, a method that is often used to tackle complex strategic decision making that calls for subjective judgment based on well-established logical reasoning, rather than on simple feeling and intuition. In the process, the complex and unstructured problem for 'compatibility test' is broken down into elements, and then a customized hierarchy structure is set up to demonstrate the relationship between different hierarchy levels and among these elements. Each element may have a different level of importance for the horizontal collaboration. A fuzzy rule based collaboration intensity index (CII) is developed to build up the relationships among these evaluation attributes. Synthesizing the generic relative importance and the forecasted degree of collaboration, the proposed approach can determine the success of the collaboration initiative. An illustrative example of a semiconductor industry supply chain (SSC) member that intends to partner with a potential and competing candidate enterprise is developed to demonstrate the applicability of the proposed fuzzy strategic alliance selection framework and to measure the effectiveness of a horizontal collaboration initiative.
The Application of Zigbee Based Wireless Sensor Network and GIS in the Air Pollution Monitoring
Authors: Han Zhi-gang, Cui Cai-hui
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 02 (2009)

With the fast development of the industrialization and urbanization process in the world, the various issues of air pollution are appearing, and most of all are health-related issues. So the air pollution monitoring should be focused on by the human. The paper reviews the development of the technology of air pollution monitoring, point out the shortages of the current monitoring technology, and bring forward the advantage of the technology of the ZigBee based wireless sensor network in air pollution monitoring, discusses the GIS technology, focusing on the requirements of air pollution monitoring system. Finally, based on the above mentioned, the application schema of the ZigBee based WSN and GIS is designed and discussed in detail.
MapReduce Programming Model for .NET-Based Cloud Computing
Authors: Chao Jin, Rajkumar Buyya
Venue: Proceedings of the 15th International Euro-Par Conference on Parallel Processing (2009)

Recently many large scale computer systems are built in order to meet the high storage and processing demands of compute and data-intensive applications. MapReduce is one of the most popular programming models designed to support the development of such applications. It was initially created by Google for simplifying the development of large scale web search applications in data centers and has been proposed to form the basis of a `Data center computer' This paper presents a realization of MapReduce for .NET-based data centers, including the programming model and the runtime system. The design and implementation of MapReduce.NET are described and its performance evaluation is presented.
A tool to achieve correct and precise measurements for oral implant planning and simulation
Authors: Tommaso Chiarelli, Evelina Lamma, Tommaso Sansoni
Venue: Proceedings of the 2009 IEEE International Workshop on Medical Measurements and Applications (2009)

Most software systems for oral implantology are based on a multi-view approach, often accompanied with a 3D rendered model. A more integrated and realistic 3D approach for implant surgery is desirable, in order to gain a deep and sure knowledge of patient's anatomy before inserting the implants, thus reducing the risk of damaging surrounding structures. We present a 3D software system where computer graphic techniques have been used to create a smooth and user-friendly 3D environment to work upon for oral implant planning and simulation. Interpolation of the axial slices is used to produce a continuous radiographic volume and to get a isotropic voxel, in order to achieve a correct work context. Freedom of choosing, arbitrarily, during the planning phase, the best cross-sectional plane for achieving correct measurements is obtained through interpolation and texture generation. Correct orientation of the planned implants is also easily computed, by exploiting a radiological mask with radio-opaque markers, worn by the patient during the Computed Tomography (CT) scan. Precision in measures was validated by considering different scans of a dried human partially edentulous mandible, which was scanned several times, with different angular orientations. Precision achieved outperforms usual DentaScan multi-view approaches, and it is comparable with or better than that obtained by the DentalVox tool (from 0.16% to 0.71% error in measures).