ppxscal/embedding_network huggingface dataset:
Sun, wind and water flow as energy supply for small stationary data acquisition platforms
Authors: Raul Morais, Samuel G. Matos, Miguel A. Fernandes, António L. G. Valente, Salviano F. S. P. Soares, P. J. S. G. Ferreira, M. J. C. S. Reis
Venue: Computers and Electronics in Agriculture (2008)

The deployment of large mesh-type wireless networks is a challenge due to the multitude of arising issues. Perpetual operation of a network node is undoubtedly one of the major goals of any energy-aware protocol or power-efficient hardware platform. Energy harvesting has emerged as the natural way to keep small stationary hardware platforms running, even when operating continuously as network routing devices. This paper analyses solar radiation, wind and water flow as feasible energy sources that can be explored to meet the energy needs of a wireless sensor network router within the context of precision agriculture, and presents a multi-powered platform solution for wireless devices. Experimental results prove that our prototype, the MPWiNodeX, can manage simultaneously the three energy sources for charging a NiMH battery pack, resulting in an almost perpetual operation of the evaluated ZigBee network router. In addition to this, the energy scavenging techniques double up as sensors, yielding data on the amount of solar radiation, water flow and wind speed, a capability that avoids the use of specific sensors.
Energy-efficient neighbor discovery protocol for mobile wireless sensor networks
Authors: Mikko Kohvakka, Jukka Suhonen, Mauri Kuorilehto, Ville Kaseva, Marko Hännikäinen, Timo D. Hämäläinen
Venue: Ad Hoc Networks (2009)

Low energy consumption is a critical design requirement for most wireless sensor network (WSN) applications. Due to minimal transmission power levels, time-varying environmental factors and mobility of nodes, network neighborhood changes frequently. In these conditions, the most critical issue for energy is to minimize the transactions and time consumed for neighbor discovery operations. In this paper, we present an energy-efficient neighbor discovery protocol targeted at synchronized low duty-cycle medium access control (MAC) schemes such as IEEE 802.15.4 and S-MAC. The protocol effectively reduces the need for costly network scans by proactively distributing node schedule information in MAC protocol beacons and by using this information for establishing new communication links. Energy consumption is further reduced by optimizing the beacon transmission rate. The protocol is validated by performance analysis and experimental measurements with physical WSN prototypes. Experimental results show that the protocol can reduce node energy consumption up to 80% at 1-3m/s node mobility.
The SIGIR 2008 workshop program
Authors: Peter Anick, Hwee Tou Ng
Venue: ACM SIGIR Forum (2008)

With the ever-expanding scope of the field of Information Retrieval, the SIGIR workshops program has grown into a vital component of the annual SIGIR conference. It provides an informal but structured setting for extended dialog and brainstorming. It allows scholars in budding areas to share ideas and set research agendas. It supports cross fertilization between existing communities and the development of new ones, often bringing together practitioners from industry and academia.
An iterative point correspondence algorithm for automatic image registration: An application to dental subtraction radiography
Authors: Vasiliki E. Markaki, Pantelis A. Asvestas, George K. Matsopoulos
Venue: Computer Methods and Programs in Biomedicine (2009)

In this paper, an Automatic Iterative Point Correspondence (AIPC) algorithm towards image registration is presented. Given an image pair, distinctive points are extracted only in one of the images (reference image), and the corresponding points in the other image are obtained automatically by maximizing a similarity measure between regions of the two images with respect to the parameters of a local transformation. The maximization is accomplished by means of an iterative procedure, in which candidate solutions for the transformation parameters are tested at each iteration; these solutions are evaluated by the similarity measure between image regions. The detected point pairs by the application of the AIPC algorithm are then used to estimate the parameters of a global projective transformation for the registration of the image pair. The proposed AIPC algorithm was applied on 113 in vitro and in vivo dental image pairs providing improved registration accuracy against three widely used registration methods.
An incremental algorithm to construct a lattice of set intersections
Authors: Derrick G. Kourie, Sergei Obiedkov, Bruce W. Watson, Dean van der Merwe
Venue: Science of Computer Programming (2009)

An incremental algorithm to construct a lattice from a collection of sets is derived, refined, analyzed, and related to a similar previously published algorithm for constructing concept lattices. The lattice constructed by the algorithm is the one obtained by closing the collection of sets with respect to set intersection. The analysis explains the empirical efficiency of the related concept lattice construction algorithm that had been observed in previous studies. The derivation highlights the effectiveness of a correctness-by-construction approach to algorithm development.
Understanding implications of DNS zone provisioning
Authors: Andrew J. Kalafut, Craig A. Shue, Minaxi Gupta
Venue: Proceedings of the 8th ACM SIGCOMM conference on Internet measurement (2008)

DNS is a critical component of the Internet. This paper takes a comprehensive look at the provisioning of Internet domains and its impact on the availability of various services. To gather data, we sweep 60% of the Internet's domains for zone transfers. 6.6% of them allow us to transfer their complete information. We find that carelessness in handling DNS records can lead to reduced availability of name servers, email, and Web servers. It also undermines anti-spam efforts and the efforts to shut down phishing sites or to contain malware infections.
A framework for application of neuro-case-rule base hybridization in medical diagnosis
Authors: O. U. Obot, Faith-Michael E. Uzoka
Venue: Applied Soft Computing (2009)

Every approach to handling automation has its unique limitations. In the symbolic (rule base) approach, the brittleness of rules leads to the ineffectiveness of handling noisy data, but it derives its strengths in heuristic search. In the same vein, a case base reasoning paradigm is bedeviled with retrieval and adaptation problems. Neural Networks (NN) methodology suffers from intolerance of incremental insertion of new knowledge and limited explanation capability, but triumphs over other methods when it comes to adaptation using its generalization characteristics. Based on all these, a tight coupling of case base, rule base and neural networks methodologies is proposed for medical diagnosis. The case base provides the 'desired' outputs, which constitute an input to the neural networks. The results obtained from the trained neural networks assisted in formulating diagnostic rules, which form the rule base. Through the rule base, an inference engine that represents the hybrid is built. Data collected from three hospitals in Nigeria on hepatitis patients were used to test the functionality of the proposed system. The results obtained from the hybrid were compared with that obtained from the Multilayer Peceptron Neural Networks (MLPNN) training using NeuroSolutions 5.0 and found to covary strongly. The hybrid exhibits an explanation characteristic, a feature not found in neural networks.
Genetic nearest feature plane
Authors: Loris Nanni, Alessandra Lumini
Venue: Expert Systems with Applications: An International Journal (2009)

The problem addressed in this paper concerns the complexity reduction of the nearest feature plane classifier, so that it may be applied also in dataset where the training set contains many patterns. This classifier considers, to classify a test pattern, the subspaces created by each combination of three training patterns. The main problem is that in dataset of high cardinality this method is unfeasible. A genetic algorithm is here used for dividing the training patterns in several clusters which centroids are used to build the feature planes used to classify the test set. The performance improvement with respect to other nearest neighbor based classifiers is validated through experiments with several benchmark datasets.
A mathematical model and a genetic algorithm for two-sided assembly line balancing
Authors: Yeo Keun Kim, Won Seop Song, Jun Hyuk Kim
Venue: Computers and Operations Research (2009)

A two-sided assembly line is a type of production line where tasks are performed in parallel at both sides of the line. The line is often found in producing large products such as trucks and buses. This paper presents a mathematical model and a genetic algorithm (GA) for two-sided assembly line balancing (two-ALB). The mathematical model can be used as a foundation for further practical development in the design of two-sided assembly lines. In the GA, we adopt the strategy of localized evolution and steady-state reproduction to promote population diversity and search efficiency. When designing the GA components, including encoding and decoding schemes, procedures of forming the initial population, and genetic operators, we take account of the features specific to two-ALB. Through computational experiments, the performance of the proposed GA is compared with that of a heuristic and an existing GA with various problem instances. The experimental results show that the proposed GA outperforms the heuristic and the compared GA.
Modular verification of web services using efficient symbolic encoding and summarization
Authors: Fang Yu, Chao Wang, Aarti Gupta, Tevfik Bultan
Venue: Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering (2008)

We propose a novel method for modular verification of web service compositions. We first use symbolic fixpoint computations to derive conditions on the incoming messages and relations among the incoming and outgoing messages of individual BPEL web services. These pre- and post-conditions are accumulated and serve as a repository of summarizations of individual web services. We then compose the summaries of the invoked BPEL services to model external invocations, resulting in a scalable verification approach for web service compositions. Our technical contributions include (1) an efficient symbolic encoding for modeling the concurrency semantics of systems having both multi-threading and message passing, and (2) a scalable method for summarizing concurrent processes that interact with each other using synchronous message passing, along with a modular framework that utilizes these summaries for scalable verification.
How Image Based Factors and Human Factors Contribute to Threat Detection Performance in X-Ray Aviation Security Screening
Authors: Anton Bolfing, Tobias Halbherr, Adrian Schwaninger
Venue: Proceedings of the 4th Symposium of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society on HCI and Usability for Education and Work (2008)

The present study examines the relative importance of a series of known and expected factors that highly affect threat detection performance in aviation security X-ray screening. Examined image based factors were threat item view difficulty, threat item superposition, bag complexity and bag size. Further, also the two human/demographic factors X-ray image interpretation training and age were examined. Image measurements and performance statistics for factors estimation are introduced. Three statistical approaches were applied in order to examine the impact of the introduced factors on threat detection performance and revealed consistent results. Bivariate correlations between detection performance and predictors/factors were analysed to estimate the isolated impact of each single factor independently of any other. Multiple linear regression analyses were applied for estimating the overall impact of all image based factors and human/demographic factors respectively. And analyses of covariance were applied in order to check for possible interaction effects between all factors of the models. All analyses were applied separately for the four threat item categories guns, knives, improvised explosive devices and other.
Knowledge acquisition for decision support systems on an electronic assembly line
Authors: Sébastien Gebus, Kauko Leiviskä
Venue: Expert Systems with Applications: An International Journal (2009)

Increasing global competition has made many manufacturing companies recognize that competitive manufacturing in terms of low cost and high quality is crucial for success. Real-time process control and production optimization are, however, extremely challenging areas because manufacturing processes are getting ever more complex and involve many different parameters. This is a major problem when building decision support systems especially in electronics manufacturing. Although problem-solving is a knowledge intensive activity undertaken by people on the production floor, it is quite common to have large databases and run blindly feature extraction and data mining methods. Performance of these methods could, however, be drastically increased when combined with knowledge or expertise of the process. This paper describes how defect-related knowledge on an electronic assembly line can be integrated in the decision making process at an operational and organizational level. It focuses in particular on the efficient acquisition of shallow knowledge concerning everyday human interventions on the production lines, as well as on the factory-wide sharing of the resulting information for an improved defect management. Software with dedicated interfaces has been developed using a knowledge representation that supports portability and flexibility of the system. Semi-automatic knowledge acquisition from the production floor and generation of comprehensive reports for the quality department resulted in an improvement of the usability, usage, and usefulness of the decision support system.
Nonlinear systems control using self-constructing wavelet networks
Authors: Cheng-Jian Lin
Venue: Applied Soft Computing (2009)

This paper describes a self-constructing wavelet network (SCWN) controller for nonlinear systems control. The proposed SCWN controller has a four-layer structure. We adopt the orthogonal wavelet functions as its node functions. An online learning algorithm, structure learning and parameter learning, allows the dynamic determining of the number of wavelet bases, and adjusting the shape of the wavelet bases and the connection weights. The SCWN controller is a highly autonomous system. Initially, there are no hidden nodes. They are created and begin to grow as learning proceeds. Computer simulations have been conducted to illustrate the performance and applicability of the proposed learning scheme.
An Optimal Approach for Workflow Staff Assignment Based on Hidden Markov Models
Authors: Hedong Yang, Chaokun Wang, Yingbo Liu, Jianmin Wang
Venue: Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS (2008)

Staff assignment of workflow is often performed manually and empirically. In this paper we propose an optimal approach named SAHMM ( Staff Assignment based on Hidden Markov Models ) to allocate the most proficient set of employees for a whole business process based on workflow event logs. The Hidden Markov Model( HMM ) is used to describe the complicated relationships among employees which are ignored by previous approaches. The validity of the approach is confirmed by experiments on real data.
Evaluation of interrupt handling timeliness in real-time Linux operating systems
Authors: Paul Regnier, George Lima, Luciano Barreto
Venue: ACM SIGOPS Operating Systems Review (2008)

Several real-time Linux extensions are available nowadays. Two of those extensions that have received special attention recently are Preempt-RT and Xenomai. This paper evaluates to what extent they provide deterministic guarantees when reacting to external events, an essential characteristic when it comes to real-time systems. For this, we define two simple experimental approaches. Our results indicate that Preempt-RT is more prone to temporal variations than Xenomai when the system is subject to overload scenarios.
How text and audio chat change the online video experience
Authors: Justin D. Weisz, Sara Kiesler
Venue: Proceeding of the 1st international conference on Designing interactive user experiences for TV and video (2008)

Many online video sites provide a text chat feature so viewers can chat with others while watching videos. How does chatting affect their experience? Would audio chat be more fun or would it be too distracting? The richer medium of audio may more closely approximate the living room or club experience, but human factors research suggests that audio chat could increase distraction and detract from the viewing experience. This paper presents the results of an experiment comparing text with audio chat when the video does or does not have dialogue, and when viewers are watching the videos in the same or a different order. A control group watched videos without chat. Overall, audio chat and text chat were equally distracting, and chat was more distracting when the video contained dialogue. Despite the presence of distraction, viewers found both text and audio chat enjoyable. Those who used audio chat preferred it to text chat for talking with others while watching videos with their friends.
Mixed integer programming approaches to exact minimization of total treatment time in cancer radiotherapy using multileaf collimators
Authors: Giulia M. G. H. Wake, Natashia Boland, Les S. Jennings
Venue: Computers and Operations Research (2009)

The effectiveness of radiation therapy for cancer depends on the patient remaining still during treatment. It is thus important to minimize the total treatment time (TTT). When such treatment is delivered using multileaf collimators in ''step-and-shoot'' mode, it consists of a sequence of collimator configurations, or patterns; for each, the patient is exposed to radiation for a specified time, or beam-on time. The TTT can thus be divided into the total beam-on time and the time spent reconfiguring the collimators. The latter can reasonably be approximated by the number of patterns, multiplied by a constant overhead time per pattern. Previous approaches to this problem have all been heuristic; in particular none of them actually use the pattern overhead time to ascertain the best trade-off between beam-on time and number of patterns. In this paper, we develop exact solution approaches, based on mixed integer programming (MIP) formulations, which minimize the TTT. We consider direct solution of MIP formulations, and then exploit the bicriteria structure of the objective to derive an algorithm that ''steps up'' through the number of patterns used, leading to substantial computational savings.
Keyword Auction Protocol for Dynamically Adjusting the Number of Advertisements
Authors: Yuko Sakurai, Atsushi Iwasaki, Makoto Yokoo
Venue: Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02 (2008)

Search engines including Yahoo! and Google utilize a keyword auction for ranking the advertisements displayed around the search results. In existing keyword auctions called the GSP, the number of displayed advertisements (slots) is determined in advance. Therefore, we consider adjusting the number of advertisements dynamically based on bids in order to improve both social surplus and seller's revenue. For example, we allow a bidder to display her advertisement exclusively when she is willing to pay a premium. We propose a new keyword auction protocol called the GSP-ExR in which the number of slots can be either 1 or K. The GSP-ExR pricing scheme is relatively simple and the seller's revenue is at least as good as with the GSP. If the highest ranked bidder's bid is large enough, she can exclusively display her advertisement by paying a premium.Otherwise, the GSP-ExR is identical to the GSP.
Multimodal slideshow: demonstration of the openinterface interaction development environment
Authors: David Juras, Laurence Nigay, Michael Ortega, Marcos Serrano
Venue: Proceedings of the 10th international conference on Multimodal interfaces (2008)

In this paper, we illustrate the OpenInterface Interaction Development Environment (OIDE) that addresses the design and development of multimodal interfaces. Multimodal interaction software development presents a particular challenge because of the ever increasing number of novel interaction devices and modalities that can used for a given interactive application. To demonstrate our graphical OIDE and its underlying approach, we present a multimodal slideshow implemented with our tool.
Collaborative interactions for medical e-diagnosis
Authors: D. Fuin, E. Garcia, H. Guyennet, J-C. Lapayre
Venue: International Journal of High Performance Computing and Networking (2008)

The Network and Distributed Systems Group within the University of Franche-Comte's computer research lab (LIFC) gained solid expertise on medical e-diagnosis in the area of remote collaboration through continued research and findings. TeNeCi (Cooperative Teleneurology) is a European remote diagnosis project applied to neurology developed under the aegis of INTERREGIII. INTERREGIII is a European Community Initiative program aiming at supporting cross-border, transnational and interregional co-operation in both social and economic perspectives. This paper has a dual objective: it first presents the improvements and contributions made to advance the TeNeCi project which is a research and development tool, and then it synthesises our research work in collaborative medical e-diagnosis. The TeNeCi tool originality is to allow practitioners to act as if they were at the same diagnosis table, using a great panel of medical tools (images, software,...). Collaboration and awareness features are used to make TeNeCi more efficient than classical telemedicine software in terms of collaboration level.
Visual Navigation for Mobile Robots: A Survey
Authors: Francisco Bonin-Font, Alberto Ortiz, Gabriel Oliver
Venue: Journal of Intelligent and Robotic Systems (2008)

Mobile robot vision-based navigation has been the source of countless research contributions, from the domains of both vision and control. Vision is becoming more and more common in applications such as localization, automatic map construction, autonomous navigation, path following, inspection, monitoring or risky situation detection. This survey presents those pieces of work, from the nineties until nowadays, which constitute a wide progress in visual navigation techniques for land, aerial and autonomous underwater vehicles. The paper deals with two major approaches: map-based navigation and mapless navigation. Map-based navigation has been in turn subdivided in metric map-based navigation and topological map-based navigation. Our outline to mapless navigation includes reactive techniques based on qualitative characteristics extraction, appearance-based localization, optical flow, features tracking, plane ground detection/tracking, etc... The recent concept of visual sonar has also been revised.