ppxscal/embedding_network huggingface dataset:
Software thread-level speculation: an optimistic library implementation
Authors: Cosmin E. Oancea, Alan Mycroft
Venue: Proceedings of the 1st international workshop on Multicore software engineering (2008)

Software thread level speculation (TLS) solutions tend to mirror the hardware ones, in the sense that they employ one, exact dependency-tracking mechanism. Our perspective is that software-flexibility is, perhaps, better exploited by a family of lighter, if less precise speculative models that can be combined together in an effective configuration, which takes advantage of the application's code-patterns. This paper reports on two main contributions. First, it introduces SpLSC: a software TLS model that trades the potential for false-positive violations for a small memory overhead and efficient implementation. Second, it presents PolyLibTLS: a library that encapsulates several lightweight models and enables their composition. In this context, we report on the template meta-programming techniques that we used to achieve performance and safety, while preserving library's modularity, extensibility and usability properties. Furthermore, we demonstrate that the user-framework interaction is straightforward and present parallelization timing results that validate our high-level perspective.
Airborne FTIR measurements over the Mt Etna volcano: preliminary results from the 2003 FASA Campaign
Authors: S. Amici, M. F. Buongiorno, S. Corradini, S. Pugnaghi, M. Sgavetti
Venue: International Journal of Remote Sensing (2007)

From 16 to 26 July 2003 an extensive field campaign was carried out around Mt Etna, Sicily, Italy. During the campaign a new airborne system, Fire Airborne Spectral Analyzer (FASA), was tested. The main instrument of the payload is a high resolution Michelson Interferometer with Rotating Retroreflector (MIROR), which operates in the nominal infrared 600-3000 cm-1 spectral range with a high resolution of 0.12 cm-1. This work investigates the feasibility of using MIROR data to retrieve the surface temperature, the hyper-spectral emissivity and the SO2 volcanic plume abundance. The results for the surface parameters show a good agreement with those obtained by satellite data and on ground measurements. In particular, the spectral emissivity shows a meaningful minimum, around 1040 cm-1, consistent with the basaltic properties of Mt Etna's surface. A sensitivity study has also been carried out to show the difficulties of SO2 columnar abundance retrieval due to the too low SO2 volcanic emission and the too high instrumental noise.
Solution Templates Tool for Enterprise Business Applications Integration
Authors: Shiwa S. Fu, Jeaha Yang, Jim Laredo, Ying Huang, Henry Chang, Santhosh Kumaran, Jen-Yao Chung, Yury Kosov
Venue: Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008) (2008)

Today's enterprises must meet the rapidly changing market demands while collaborating with much broader range of trading partners to maximize supply chain efficiency and improve services to customers and their profit margin. To accomplish these business goals, their business application systems, such as enterprise ERP, must integrate and adapt rapidly to meet these business demands and collaborate with other business system without major reimplementation effort. Our proposed approach addresses these problems by using model based approach of creating reusable solution template that consists of off-the-shelf artifacts to be quickly assembled as a solution. In this paper, we introduce a Solution Template Tool that simplifies the life cycle for creating an integration solution, through the flexible design and customization of solution templates, and an interactive environment driven by wizards. By providing levels of abstraction, the proposed tool allows users to compose templates of platform independent model without worrying about implementation details. The tool transforms the composed templates into platform specific IT execution model and a deployable solution, thus easing the task of solution integration lifecycle. A solution template of UCCnet illustrates our study.
An enhanced genetic approach to optimizing auto-reply accuracy of an e-learning system
Authors: Gwo-Jen Hwang, Peng-Yeng Yin, Tzu-Ting Wang, Judy C. R. Tseng, Gwo-Haur Hwang
Venue: Computers Education (2008)

With the rapid development in Information Technology (IT), the Internet has become one of the central media for conducting learning. However, most of the existing web-based learning systems only provide stand-alone subject materials for browsing and may face some drawbacks. For example, if students encounter problems during the learning process, their learning performances could be significantly devastated due to no instant aid. As an on-line learning system may interact with thousands of students, it is almost impossible for the teachers or the teaching assistants to answer all the students' questions manually, which is not only inefficient, but also human laborious. To cope with this problem, an e-learning system that is able to automatically answer the students' questions on the fly based on the training cases given by the teacher will be presented in this paper. Moreover, an enhanced genetic approach is proposed to optimize the weights of keywords for each candidate answer according to the feedbacks provided by the students, hence more accurate answers can be provided in the future. Experimental results have shown that the developed system can provide more accurate answerers than existing approaches by employing the self-adjusting method.
Application of CHL model for estimating biomass pyrolysis yield
Authors: Francesco Marra
Venue: Proceedings of the 1st WSEAS International Conference on Computational Chemistry (2007)

The pyrolysis of wood biomass represents a valid technique for recovering "green" fuel from residues of forestry and other activities, in agriculture as in industry, where wood and other plant residues are available. Wood biomass is essentially a composite material, the major constituents being cellulose, hemicellulose, lignin, organic extractives, and inorganic minerals. The weight percent of cellulose, hemicellulose, and lignin varies in different species of wood biomass. In this paper, a model based on cellulose, hemicelluloses and lignin content of investigated materials is proposed, as simple but effective tool for estimating the yield of pyrolysis of various biomasses available as by-product of typical agricultural activities in South of Italy. Results show that hazelnut shells and poplar prunings gives high yield in fuel (gas and tar vapours) between 700 K and 900 K, both for conventional slow pyrlysis and for fast pyrolysis, whereas olive tree prunings and chestnut wood residues give an appreciable yield (higher than 70%) only for temperatures above 900 K, for fast pyrolisis. Sunflowers residues, characterized by higher content of non-CHL compounds, give the lower yield in fuel for all the investigated conditions.
Sampling stable properties of massive track datasets
Authors: Christopher I. Connolly, J. Brian Burns, Hung H. Bui
Venue: Proceedings of the 2007 workshop on Massive datasets (2007)

Analysis of massive track datasets is a challenging problem, especially when examining n-way relations inherent in social networks. In this paper, we explore ways in which stable properties of sensor observations can be extracted and visualized using a statistical sampling of features from a very large track dataset, using very little ground truth or outside knowledge. Special attention is given to methods that are likely to scale well beyond the size of the Mitsubishi dataset.
Theoretical advances in artificial immune systems
Authors: J. Timmis, A. Hone, T. Stibor, E. Clark
Venue: Theoretical Computer Science (2008)

Artificial immune systems (AIS) constitute a relatively new area of bio-inspired computing. Biological models of the natural immune system, in particular the theories of clonal selection, immune networks and negative selection, have provided the inspiration for AIS algorithms. Moreover, such algorithms have been successfully employed in a wide variety of different application areas. However, despite these practical successes, until recently there has been a dearth of theory to justify their use. In this paper, the existing theoretical work on AIS is reviewed. After the presentation of a simple example of each of the three main types of AIS algorithm (that is, clonal selection, immune network and negative selection algorithms respectively), details of the theoretical analysis for each of these types are given. Some of the future challenges in this area are also highlighted.
The application of data mining techniques to characterize agricultural soil profiles
Authors: Leisa J. Armstrong, Dean Diepeveen, Rowan Maddern
Venue: Proceedings of the sixth Australasian conference on Data mining and analytics - Volume 70 (2007)

The advances in computing and information storage have provided vast amounts of data. The challenge has been to extract knowledge from this raw data; this has lead to new methods and techniques such as data mining that can bridge the knowledge gap. This research aimed to assess these new data mining techniques and apply them to a soil science database to establish if meaningful relationships can be found. A large data set extracted from the WA Department of Agriculture and Food (AGRIC) soils database has been used to conduct this research. The database contains measurements of soil profile data from various locations throughout the south west agricultural region of Western Australia. The research establishes whether meaningful relationships can be found in the soil profile data at different locations. In addition, comparison was made between current data mining techniques such as cluster analysis and statistical methods to establish the most effective technique. The outcome of the research may have many benefits, to agriculture, soil management and environmental
Commutative combinatorial Hopf algebras
Authors: Florent Hivert, Jean-Christophe Novelli, Jean-Yves Thibon
Venue: Journal of Algebraic Combinatorics: An International Journal (2008)

We propose several constructions of commutative or cocommutative Hopf algebras based on various combinatorial structures and investigate the relations between them. A commutative Hopf algebra of permutations is obtained by a general construction based on graphs, and its noncommutative dual is realized in three different ways, in particular, as the Grossman---Larson algebra of heap-ordered trees. Extensions to endofunctions, parking functions, set compositions, set partitions, planar binary trees, and rooted forests are discussed. Finally, we introduce one-parameter families interpolating between different structures constructed on the same combinatorial objects.
Cfengine for configuration management
Authors: Scott Lackey
Venue: Linux Journal (2008)

How to use cfengine to manage configuration files across large numbers of machines.
Image Differencing Approaches to Medical Image Classification
Authors: Dave Tahmoush
Venue: Proceedings of the 36th Applied Imagery Pattern Recognition Workshop (2007)

Image differencing is normally done by subtracting the low-level features like intensity in images that are already aligned. This paper extracts high-level features in order to learn an effective image differencing method for the diagnosis of breast cancer. However, this produces sets of features that are both spatial and unordered. Learning techniques are challenging when examples are sets of features that lack any sort of meaningful ordering and where spatial relationships are important. We demonstrate a technique that avoids arbitrary spatial constraints and is robust in the presence of noise, outliers, and imaging artifacts, while outperforming even commercial products in the diagnosis of breast cancer images. First, the landmarks are found and ranked, and then the top candidates are sorted into a point set. Second, the point sets of the two images are then differenced through a cluster comparison. A technique that radiologists use to diagnose breast cancer involves finding potentially cancerous sites in the mammograms and then comparing the left and right breasts to reduce the effect of false positives and to produce a diagnosis. The symmetry of the human body is utilized to increase the accuracy of the diagnosis. We emulate this technique in an attempt to understand and eventually capture the diagnosis of the radiologist. The image differencing with clustered comparison process determines the presence of cancer 80% of the time, outperforming all other systems, thus making it a strong classifier which should significantly improve systems for helping radiologists diagnose breast cancer images. The results compare favorably with the state of the art in both academic and commercial approaches, achieving a 9% overall improvement over the best academic approach and a 26% improvement on non-cancerous cases over the best commercial approach while maintaining the same accuracy on cancerous cases.
A topical PageRank based algorithm for recommender systems
Authors: Liyan Zhang, Kai Zhang, Chunping Li
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

In this paper, we propose a Topical PageRank based algorithm for recommender systems, which aim to rank products by analyzing previous user-item relationships, and recommend top-rank items to potentially interested users. We evaluate our algorithm on MovieLens dataset and empirical experiments demonstrate that it outperforms other state-of-the-art recommending algorithms.
Nanofabrication of spintronic devices with ultra small ferromagnetic contacts
Authors: Yifang Chen, Yun Zhou, Ling Wang, Zheng Cui, Ejaz Huq, Genhua Pan
Venue: Microelectronic Engineering (2008)

This paper reports a recently developed nanofabrication process for the fabrication of vertical nanocontacts in ferromagnetic film, combining electron beam lithography and reactive ion etch. Dry etch for nanopinholes in SiN"x layer has been studied. As small as 20nm contacts have been achieved. The developed nanoprocess is not only applicable for such kind of spintronic devices, but also suitable for general nanoelectronic devices.
Constructing cubic edge- but not vertex-transitive graphs
Authors: Dragan Marušič
Venue: Journal of Graph Theory (2000)

An infinite family of cubic edge-transitive but not vertex-transitive graphs with edge stabilizer isomorphic to ℤ2 is constructed. &copy; 2000 John Wiley Sons, Inc. J Graph Theory 35: 152160, 2000
To personalize or not to personalize: modeling queries with variation in user intent
Authors: Jaime Teevan, Susan T. Dumais, Daniel J. Liebling
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

In most previous work on personalized search algorithms, the results for all queries are personalized in the same manner. However, as we show in this paper, there is a lot of variation across queries in the benefits that can be achieved through personalization. For some queries, everyone who issues the query is looking for the same thing. For other queries, different people want very different results even though they express their need in the same way. We examine variability in user intent using both explicit relevance judgments and large-scale log analysis of user behavior patterns. While variation in user behavior is correlated with variation in explicit relevance judgments the same query, there are many other factors, such as result entropy, result quality, and task that can also affect the variation in behavior. We characterize queries using a variety of features of the query, the results returned for the query, and people's interaction history with the query. Using these features we build predictive models to identify queries that can benefit from personalization.
System architecture and implementation of MIMO sphere decoders on FPGA
Authors: Xinming Huang, Cao Liang, Jing Ma
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2008)

Multiple-input-multiple-output (MIMO) systems use multiple antennas in both transmitter and receiver ends for higher spectrum efficiency. The hardware implementation of MIMO detection becomes a challenging task as the computational complexity increases. This paper presents the architectures and implementations of two typical sphere decoding algorithms, including the Viterbo-Boutros (VB) algorithm and the Schnorr-Euchner (SE) algorithm. Hardware/software codesign technique is applied to partition the decoding algorithm on a single field-programmable gate array (FPGA) device. Three levels of parallelism are explored to improve the decoding rate: the concurrent execution of the channel matrix preprocessing on an embedded processor and the decoding functions on customized hardware modules, the parallel decoding of real/imaginary parts for complex constellation, and the concurrent execution of multiple steps during the closest lattice point search. The decoders for a 4 × 4 MIMO system with 16-QAM modulation are prototyped on a Xilinx XC2VP30 FPGA device with a MicroBlaze soft core processor. The hardware prototypes of the SE and VB algorithms show that they support up to 81.5 and 36.1 Mb/s data rates at 20 dB signal-to-noise ratio, which are about 22 and 97 times faster than their respective implementations in a digital signal processor.
A Latent Model Approach to Study Postural Instability for Parkinson's Disease
Authors: Peng Huang, Ming-Hui Chen, Debajyoti Sinha
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

Postural instability is an important measure of Parkinson's disease conditions. Because of the fluctuation of clinical symptoms and large inter-rater and intra-rater variation, traditional method of analyzing postural instability using its onset time measure can result in controversial conclusion of treatment benefit. We propose a Brownian motion based latent structure model to study treatment's effect on postural instability. The new method not only incorporates patient's multiple onset times, but also the special covariate structure of postural instability process. The proposed model does not require even-spaced visiting schedules, and the correlation of the binary process is naturally built through the underlying latent Brownian motion process. Theoretical and computational properties of the proposed model are examined. A dataset from a double-blinded multicenter Parkinson's disease clinical trial is used to demonstrate the methodology.
A rough set approach to the discovery of classification rules in spatial data
Authors: Yee Leung, Tung Fung, Ju-Sheng Mi, Wei-Zhi Wu
Venue: International Journal of Geographical Information Science (2007)

This paper proposes a novel rough set approach to discover classification rules in real-valued spatial data in general and remotely sensed data in particular. A knowledge induction process is formulated to select optimal decision rules with a minimal set of features necessary and sufficient for a remote sensing classification task. The approach first converts a real-valued or integer-valued decision system into an interval-valued information system. A knowledge induction procedure is then formulated to discover all classification rules hidden in the information system. Two real-life applications are made to verify and substantiate the conceptual arguments. It demonstrates that the proposed approach can effectively discover in remotely sensed data the optimal spectral bands and optimal rule set for a classification task. It is also capable of unraveling critical spectral band(s) discerning certain classes. The framework paves the road for data mining in mixed spatial databases consisting of qualitative and quantitative data.
Virtualization aware job schedulers for checkpoint-restart
Authors: R. Badrinath, R. Krishnakumar, R. K. Palanivel Rajan
Venue: Proceedings of the 13th International Conference on Parallel and Distributed Systems - Volume 02 (2007)

Application checkpoint and restart has been a widely studied problem over the last several decades. Despite immense volume of theory and several research project level implementations, there is very little by way of working solutions for the case of parallel distributed applications (such as MPI programs on a cluster). We describe our experiences in enhancing a job scheduler to leverage mechanisms of a virtual machine environment to support checkpoint-restart. We also describe the basic coordinated checkpoint-restart framework that we implemented on which this solution is based.
Space Complexity Vs. Query Complexity
Authors: Oded Lachish, Ilan Newman, Asaf Shapira
Venue: Computational Complexity (2008)

Combinatorial property testing deals with the following relaxation of decision problems: Given a fixed property and an input x, one wants to decide whether x satisfies the property or is "far" from satisfying it. The main focus of property testing is in identifying large families of properties that can be tested with a certain number of queries to the input. In this paper we study the relation between the space complexity of a language and its query complexity. Our main result is that for any space complexity s(n) ¿ log n there is a language with space complexity O(s(n)) and query complexity 2¿(s(n)).Our result has implications with respect to testing languages accepted by certain restricted machines. Alon et al. [FOCS 1999] have shown that any regular language is testable with a constant number of queries. It is well known that any language in space o(log log n) is regular, thus implying that such languages can be so tested. It was previously known that there are languages in space O(log n) that are not testable with a constant number of queries and Newman [FOCS 2000] raised the question of closing the exponential gap between these two results. A special case of our main result resolves this problem as it implies that there is a language in space O(log log n) that is not testable with a constant number of queries. It was also previously known that the class of testable properties cannot be extended to all context-free languages. We further show that one cannot even extend the family of testable languages to the class of languages accepted by single counter machines.
A test generation solution to automate software testing
Authors: Fabrice Bouquet, Christophe Grandpierre, Bruno Legeard, Fabien Peureux
Venue: Proceedings of the 3rd international workshop on Automation of software test (2008)

This paper describes the LEIRIOS Smart Testing™ approach to the functional validation of a subpart of the StarUML case study. This model-based testing process for test automation is shown from start to end: from functional requirements to the publication of generated tests in a test repository and automatic execution of scripts with a test execution robot. This is a short position paper illustrating how LEIRIOS Smart Testing" can help to answer to the question: how to automate the testing of UML/MDA platform StarUML.