ppxscal/embedding_network huggingface dataset:
Spatial temperature profiling by semi-passive RFID loggers for perishable food transportation
Authors: Reiner Jedermann, Luis Ruiz-Garcia, Walter Lang
Venue: Computers and Electronics in Agriculture (2009)

Perishable food products are at risk of suffering various damages along the cold chain. The parties involved should control and monitor the conditions of goods in order to ensure their quality for consumers and to comply with all legal requirements. Among environmental parameters during transport, temperature is the most important in prolonging the shelf life of the products. Radio Frequency IDentification (RFID) is an emergent technology that has proven its suitability for tracking and tracing in logistics. This paper shows how miniaturized RFID temperature loggers can be adapted to analyze the amount of local deviations, detect temperature gradients, and estimate the minimum number of sensors that are necessary for reliable monitoring inside a truck or container. These devices are useful tools for improving the control during the transport chain and detecting weaknesses by identifying specific problem areas where corrective actions are necessitated. In a first step, the RFID tags were tested by studying the temperature distribution in a pallet. Then, 15 shipments from a wholesale company in Germany in compartmented trucks were monitored, covering different temperature range conditions. During transport, several temperature differences were found in the same compartment. Using a factorial Analysis of Variance (ANOVA) the influence of different factors has been studied, such as: the location of the logger, type of truck, and external temperature. The shelf life, or keeping quality model, was applied to the recorded temperature profiles. Suggestions for future research areas are also discussed.
A novel hurricane model for software engineering
Authors: Xuejun Liu
Venue: Proceedings of the 3rd WSEAS international conference on Circuits, systems, signal and telecommunications (2009)

A lot of process models for software development are almost based on description of the relationship between the scale, complex of software project and technology tasks in every phases and methods as the main content. They can open out the characteristic of the technique works, but ignore the connotation of the management in software process. Based on such models, it will brings us lots of inconvenience and trouble for studying and opening out the characteristic of management in software development. In this paper, we propose a novel process model to Team Software Process. The model includes 6 basic tasks and 4 administrative levels, we call it hurricane model. The hurricane model describes relationship between basic tasks and administrative levels in a team, and can supervise all key aspects of the project operations for team software. It also provides a new solution for describing, theoretical research on the software engineering subject and the development of assistant tools.
An analysis of building habitat with networked tools
Authors: Ann Light, Clodagh Miskelly, Steve Thompson
Venue: Proceedings of the 20th Australasian Conference on Computer-Human Interaction: Designing for Habitus and Habitat (2008)

Interactive network technologies are taking our attention away from our habitat and distributing it worldwide. Can outward-pointing tools be turned back to focus on local needs? We examine social networking tools and location sensitive media for their potential to connect people to their environment in different ways, putting the tools' use in context through an analysis of socially-motivated design practice. We explore two case studies of designing and conclude with a description of how we can support the embedding of social practices, and thus people, in their habitat through design interventions.
Space Invading Systems Code
Authors: Cristiano Calcagno, Dino Distefano, Peter O'Hearn, Hongseok Yang
Venue: Logic-Based Program Synthesis and Transformation: 18th International Symposium, LOPSTR 2008, Valencia, Spain, July 17-18, 2008, Revised Selected Papers (2009)

Space Invader is a static analysis tool that aims to perform accurate, automatic verification of the way that programs use pointers. It uses separation logic assertions [10,11] to describe states, and works by performing a proof search, using abstract interpretation to enable convergence. As well as having roots in separation logic, Invader draws on the fundamental work of Sagiv et. al. on shape analysis [12]. It is complementary to other tools - e.g., SLAM [1], Blast [8], ASTRÉE [6] - that use abstract interpretation for verification, but that use coarse or limited models of the heap.
Direct and iterative solution of the generalized Dirichlet-Neumann map for elliptic PDEs on square domains
Authors: A. G. Sifalakis, S. R. Fulton, E. P. Papadopoulou, Y. G. Saridakis
Venue: Journal of Computational and Applied Mathematics (2009)

In this work we derive the structural properties of the Collocation coefficient matrix associated with the Dirichlet-Neumann map for Laplace's equation on a square domain. The analysis is independent of the choice of basis functions and includes the case involving the same type of boundary conditions on all sides, as well as the case where different boundary conditions are used on each side of the square domain. Taking advantage of said properties, we present efficient implementations of direct factorization and iterative methods, including classical SOR-type and Krylov subspace (Bi-CGSTAB and GMRES) methods appropriately preconditioned, for both Sine and Chebyshev basis functions. Numerical experimentation, to verify our results, is also included.
Automatic multi-interface management through profile handling
Authors: Jean-Marie Bonnin, Imed Lassoued, Zied Ben Hamouda
Venue: Mobile Networks and Applications (2009)

In the recent years, wireless communication systems have received increased interest in commercial applications. Different kind of wireless public access have become increasingly available in various areas like airports, stations and shopping centers as well as at office or at home. Mobile terminals, such as phones or laptops, are often equipped with several network interfaces and may use simultaneously several access networks. For instance it is nowadays common to have UMTS, WiFi, BlueTooth, and even WiMAX interfaces on a single mobile device. Each of them can be attached to different Internet providers offering seamless connectivity, high-speed multimedia services with different billing models and security levels. In this paper, we focus on an advanced middleware that allows, through a comprehensive profile management, the support of automatic interface configuration and per-flow interface selection. The system takes into account preferences given by the terminals owner, the users and the applications. This middleware makes the terminal to be always "best" connected and provides service continuity in case of vertical handover. As illustration, we show how the proposed middleware allows cost-effective management of a fleet of terminals.
WiMAX cybercity & NGN
Authors: H. F. Rashvand
Venue: Proceedings of the International Conference on Mobile Technology, Applications, and Systems (2008)

Following the last decade's continuous progress of wireless and associated technological development a clear market gap for addressing the need for wireless broadband access (WBA) came into reality at the turn of century, promoted by the standard IEEE 802.16 known as WiMAX. Appearance of this timely technology push innovation brought a new hurdle and change to the telecom industry with the promise of a futuristic wireless Cybecity based telecom industry where we can reach virtually all our telecom needs and services through wireless data connectivity that may bring many new features such as low infrastructural investment, ultimate portability and mobility under a new umbrella. As always, a radical innovation at this scale cannot be implemented without practical complications including market resistance and tough competition from the existing systems from both fixed and mobile
Unifying Sets and Programs via Dependent Types
Authors: Wojciech Moczydłowski
Venue: Proceedings of the 2009 International Symposium on Logical Foundations of Computer Science (2009)

We present a foundational framework, which we call D, unifying a lazy programming language with an impredicative constructive set theory IZF R by means of dependent types. We show that unification brings many benefits to both worlds. First, D supports two paramount paradigms of creating reliable software: correctness by construction and post-construction verification, while retaining the expressiveness of set theory. Second, D provides new expressive power, which makes it possible to internalize and prove inside D the standard meta-theoretic properties of constructive systems, such as Numerical Existence Property and Program Extraction. Finally, computation arising from the programming language significantly enriches set theory, as we show that D is stronger than IZF R and that its real numbers behave in a better way.
Modeling the Quantizer Behavior of Subbands for Data Rate Limitations in JPEG2000
Authors: Christian Günter, Albrecht Rothermel
Venue: Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling (2009)

In the JPEG2000 standard the very cost intensive EBCOT encoder based on an arithmetic encoder with an embedded quantization is said to be the optimum. Embedded systems with limited processing power have difficulties to encode images into this JPEG2000 image format due to its high processing load. A rekursive optimization of the quantization is not possible. This paper proposes a new method based on a model for subband quantization behavior of two-dimensional wavelet transformations to estimate a good quantizer stepsize for data rate limitations. With an additional, simple optimization algorithm an average variation in the resulting data length of < 1.6% is achieved.
Performance Comparison of Polling Mechanisms in IEEE 802.16 Networks
Authors: Fei Yin, Guy Pujolle
Venue: Proceedings of the 2008 The Second International Conference on Next Generation Mobile Applications, Services, and Technologies (2008)

IEEE 802.16 standard suite defines two main polling mode: unicast polling and contention-base polling including multicast and broadcast polling. Unicast polling completely overcomes the request collision and is suitable for real-time application. Contention-based polling suffers from collisions and is suitable for non-real-time applications. Though the standard defined different service classes for implementing the polling mechanisms, it does not define exactly an adaptation polling mechanism to efficiently allocate bandwidth. In this paper we evaluate the performance of different polling mechanisms defined in IEEE 802.16 by simulation. We also propose a new optimal unicast and contention-based mixed polling mechanism and show that this optimal mixed polling mechanism could always achieve better performance than any polling mechanisms defined in IEEE 802.16.
Multiprocessor performance analysis
Authors: John Mitchell, Charles Knadler, Gary Lunsford, Steve Yang
Venue: Proceedings of the May 6-10, 1974, national computer conference and exposition (1974)

This paper reports the results of a study to determine the expected performance of a "classical" multiprocessor. The "classical" multiprocessor as used here is a multiprocessor consisting of K (K>1) central processor units which have access to N storage units. The tool used for studying the performance is a discrete Fortran model of the hardware and software. Hardware measurements of the real system performance were available for validation of the model. The primary indicator of performance is the system thruput in millions of instructions executed per second (MIPS). Since the application of the hardware is in a real-time system, consideration is also given to response times of critical software tasks.
The Secretary Problem with a Hazard Rate Condition
Authors: Mohammad Mahdian, Randolph Preston Mcafee, David Pennock
Venue: Proceedings of the 4th International Workshop on Internet and Network Economics (2008)

In the classical secretary problem, the objective is to select the candidate of maximum value among a set of n candidates arriving one by one. The value of the candidates come from an unknown distribution and is revealed at the time the candidate arrives, at which point an irrevocable decision on whether to select the candidate must be made. The well-known solution to this problem, due to Dynkin, waits for n/e steps to set an "aspiration level" equal to the maximum value of the candidates seen, and then accepts the first candidate whose value exceeds this level. This guarantees a probability of at least 1/e of selecting the maximum value candidate, and there are distributions for which this is essentially the best possible. One feature of this algorithm that seems at odds with reality is that it prescribes a long waiting period before selecting a candidate. In this paper, we show that if a standard hazard rate condition is imposed on the distribution of values, the waiting period falls from n/e to n/log(n), meaning that it is enough to observe a diminishingly small sample to set the optimal aspiration level. This result is tight, as both the hazard condition and the optimal sampling period bind exactly for the exponential distribution.
Lower bounds for three algorithms for transversal hypergraph generation
Authors: Matthias Hagen
Venue: Discrete Applied Mathematics (2009)

The computation of all minimal transversals of a given hypergraph in output-polynomial time is a long standing open question known as Transversal Hypergraph Generation. One of the first attempts at this problem-the sequential method [Claude Berge, Hypergraphs, in: North-Holland Mathematical Library, vol. 45, North-Holland, 1989]-is not output-polynomial as was shown by Takata [Ken Takata, A worst-case analysis of the sequential method to list the minimal hitting sets of a hypergraph, SIAM Journal on Discrete Mathematics 21 (4) (2007) 936-946]. Recently, three new algorithms improving the sequential method were published and experimentally shown to perform very well in practice [James Bailey, Thomas Manoukian, Kotagiri Ramamohanarao, A fast algorithm for computing hypergraph transversals and its application in mining emerging patterns, in: Proceedings of the 3rd IEEE International Conference on Data Mining, ICDM 2003, 19-22 December 2003, Melbourne, FL, USA, IEEE Computer Society, 2003, pp. 485-488; Guozhu Dong, Jinyan Li, Mining border descriptions of emerging patterns from dataset pairs, Knowledge and Information Systems 8 (2) (2005) 178-202; Dimitris J. Kavvadias, Elias C. Stavropoulos, An efficient algorithm for the transversal hypergraph generation, Journal of Graph Algorithms and Applications 9 (2) (2005) 239-264]. Nevertheless, a theoretical worst-case analysis has been pending. We close this gap by proving lower bounds for all three algorithms. Thereby, we show that none of them are output-polynomial.
Fault-Aware Runtime Strategies for High-Performance Computing
Authors: Yawei Li, Zhiling Lan, Prashasta Gujrati, Xian-He Sun
Venue: IEEE Transactions on Parallel and Distributed Systems (2009)

As the scale of parallel systems continues to grow, fault management of these systems is becoming a critical challenge. While existing research mainly focuses on developing or improving fault tolerance techniques, a number of key issues remain open. In this paper, we propose runtime strategies for spare node allocation and job rescheduling in response to failure prediction. These strategies, together with failure predictor and fault tolerance techniques, construct a runtime system called FARS (Fault-Aware Runtime System). In particular, we propose a 0-1 knapsack model and demonstrate its flexibility and effectiveness for reallocating running jobs to avoid failures. Experiments, by means of synthetic data and real traces from production systems, show that FARS has the potential to significantly improve system productivity (i.e., performance and reliability).
A neural-network-based nonlinear metamodeling approach to financial time series forecasting
Authors: Lean Yu, Shouyang Wang, Kin Keung Lai
Venue: Applied Soft Computing (2009)

In financial time series forecasting, the problem that we often encounter is how to increase the prediction accuracy as possible using the financial data with noise. In this study, we discuss the use of supervised neural networks as a meta-learning technique to design a financial time series forecasting system to solve this problem. In this system, some data sampling techniques are first used to generate different training subsets from the original datasets. In terms of these different training subsets, different neural networks with different initial conditions or training algorithms are then trained to formulate different prediction models, i.e., base models. Subsequently, to improve the efficiency of predictions of metamodeling, the principal component analysis (PCA) technique is used as a pruning tool to generate an optimal set of base models. Finally, a neural-network-based nonlinear metamodel can be produced by learning from the selected base models, so as to improve the prediction accuracy. For illustration and verification purposes, the proposed metamodel is conducted on four typical financial time series. Empirical results obtained reveal that the proposed neural-network-based nonlinear metamodeling technique is a very promising approach to financial time series forecasting.
Accurate appearance-based Bayesian tracking for maneuvering targets
Authors: Emilio Maggio, Andrea Cavallaro
Venue: Computer Vision and Image Understanding (2009)

We propose a tracking algorithm that combines the Mean Shift search in a Particle Filtering framework and a target representation that uses multiple semi-overlapping color histograms. The target representation introduces spatial information that accounts for rotation and anisotropic scaling without compromising the flexibility typical of color histograms. Moreover, the proposed tracker can generate a smaller number of samples than Particle Filter as it increases the particle efficiency by moving the samples toward close local maxima of the likelihood using Mean Shift. Experimental results show that the proposed representation improves the robustness to clutter and that, especially on highly maneuvering targets, the combined tracker outperforms Particle Filter and Mean Shift in terms of accuracy in estimating the target size and position while generating only 25% of the samples used by Particle Filter.
A Novel Language-Model-Based Approach for Image Object Mining and Re-ranking
Authors: Jen-Hao Hsiao, Chu-Song Chen, Ming-Syan Chen
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

One leading framework for image object mining is the bag-of-words (BOW) approach. The idea is to encode an image as a collection of visual words of the quantized local patches. Objects in the image can then be retrieved through inferring the semantic topics associated with the set of visual words. However, the visual BOW mining framework is apt to suffer from the so-called term-mismatch problem (a.k.a. vocabulary problem). This is caused by the poverty of query information, and consequently becomes an obstacle to deal with synonymy (i.e., different visual words for describing the same object). In this paper, we propose a novel language-model-based approach with pseudo-relevance feedback for addressing the vocabulary problem in visual BOW mining. We employ the pseudo positive images produced in response to the original query as a set of “cues” to gradually refine the query language model. Unlike traditional approaches that only ruggedly append feedback information into the original query, the proposed approach reconstructs the query language model with finer granularities so that the query concepts can be captured more accurately. The proposed approach is experimentally evaluated using two different types of image object databases. Our algorithms are shown to bring significant improvement in the retrieval accuracy over a non-feedback baseline, and achieve better performance than conventional feedback approaches.
Using Visual Logic© to teach programming logic in an introductory CS course
Authors: Lisa M. Olivieri
Venue: Journal of Computing Sciences in Colleges (2009)

Encouraging qualified students to enroll in an introductory computer science class continues to be a challenge in many colleges and universities. Students often avoid registering for computer science courses, especially those that involve a significant amount of programming. Computer Science faculty who are involved in teaching these introductory courses are constantly exploring ways to make programming more inviting to students.
Incremental Reasoning for Multiple Inheritance
Authors: Johan Dovland, Einar Broch Johnsen, Olaf Owe, Martin Steffen
Venue: Proceedings of the 7th International Conference on Integrated Formal Methods (2009)

Object-orientation supports code reuse and incremental programming. Multiple inheritance increases the power of code reuse, but complicates the binding of method calls and thereby program analysis. Behavioral subtyping allows program analysis under an open world assumption; i.e., under the assumption that class hierarchies are extensible. However, method redefinition is severely restricted by behavioral subtyping, and multiple inheritance often leads to conflicting restrictions from independently designed superclasses. This paper presents an approach to incremental reasoning for multiple inheritance under an open world assumption. The approach, based on a notion of lazy behavioral subtyping, is less restrictive than behavioral subtyping and fits well with multiple inheritance, as it incrementally imposes context-dependent behavioral constraints on new subclasses. We formalize the approach as a calculus, for which we show soundness.
Hebbian Learning from Spiking Neural P Systems View
Authors: Miguel A. Gutiérrez-Naranjo, Mario J. Pérez-Jiménez
Venue: Membrane Computing: 9th International Workshop, WMC 2008, Edinburgh, UK, July 28-31, 2008, Revised Selected and Invited Papers (2009)

Spiking neural P systems and artificial neural networks are computational devices which share a biological inspiration based on the flow of information among neurons. In this paper we present a first model for Hebbian learning in the framework of spiking neural P systems by using concepts borrowed from neuroscience and artificial neural network theory.
Geostatistical modeling of sedimentological parameters using multi-scale terrain variables: application along the Belgian Part of the North Sea
Authors: E. Verfaillie, I. Du Four, M. Van Meirvenne, V. Van Lancker
Venue: International Journal of Geographical Information Science (2009)

In the nowadays highly pressurized marine environment, a science-based approach to management becomes increasingly important. In many cases, the sediment nature and processes are the key to the understanding of the marine ecosystem, and can explain particularly the presence of soft-substrata habitats. For predictions of the occurrence of species and habitats, detailed sedimentological information is required. This paper presents a methodology to create high quality sedimentological data grids of grain-size fractions and the percentage of silt-clay. Based on a multibeam bathymetry terrain model, multiple sources of secondary information (multi-scale terrain variables) were derived. Through the use of the geostatistical technique, Kriging with an external drift (KED), this secondary information was used to assist in the interpolation of the sedimentological data. For comparison purposes, the more commonly used Ordinary Kriging technique was also applied. Validation indices indicated that KED gave better results for all of the maps.