ppxscal/embedding_network huggingface dataset:
Software Connector Classification and Selection for Data-Intensive Systems
Authors: Chris A. Mattmann, David Woollard, Nenad v, Reza Mahjourian
Venue: Proceedings of the Second International Workshop on Incorporating COTS Software into Software Systems: Tools and Techniques (2007)

Data-intensive systems and applications transfer large volumes of data and metadata to highly distributed users separated by geographic distance and organizational boundaries. An influential element in these large volume data transfers is the selection of the appropriate software connector that satisfies user constraints on the required data distribution scenarios. Currently, this task is typically accomplished by consulting "gurus", who rely on their intuitions, at best backed by anecdotal evidence. In this paper we present a systematic approach for selecting software connectors based on eight key dimensions of data distribution that we use to represent the data distribution scenarios. Our approach, dubbed DISCO, has been implemented as a Java-based framework. The early experience with DISCO indicates good accuracy and scalability.
Affine projection methods in fault tolerant adaptive filtering
Authors: R. A. Soni
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

Reliable performance is very important for high speed channel equalizers and echo cancellers used in high speed communications channels. A common type of hardware fault occurs when the coefficients get "stuck" at an uncontrollable value. Such faults lead to larger overall mean square errors, and generally poor performance. Redundancy can provide the ability to compensate for these types of faults if the proper design is introduced into the adaptive filter structure. Unfortunately this form of redundancy can lead to poor convergence performance for the adaptive filter after the fault occurrence. This paper examines the use of affine projection and row projection techniques to improve the convergence performance of the fault tolerant adaptive filtering structure. Algorithms are developed for two cases: fault knowledge and no fault knowledge incorporated in the adaptive filtering update. These algorithms are introduced in this paper and simulations are presented to illustrate the effectiveness of these approaches.
Distance-Dependent RED Policy (DDRED)
Authors: Sebastien Linck, Eugen Dedu, Francois Spies
Venue: Proceedings of the Sixth International Conference on Networking (2007)

The network quality of service (QoS) and the congestion control of the transport protocol are important parameters for the performance of a network data transfer. To this end, routers use various queue policies for packet dispatching, and all of them must deal with packet drop. We propose a new algorithm for packet drop in routers. Given that a packet drop wastes all the network resources it has already used, we propose a new policy which favors packets with higher distance from source. It can be simply integrated on top of tail drop or RED (with or without ECN) queue policies. Simulations with NS2 show that long flows are indeed favored compared to short flows, and lead to higher overall resource utilisation without sacrificing TCP fairness.
What types of events provide the strongest evidence that the stock market is affected by company specific news?
Authors: Calum Robertson, Shlomo Geva, Rodney Wolff
Venue: Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61 (2006)

The efficient market hypothesis states that an efficient market immediately incorporates all available information into the price of the traded entity. It is well established that the stock market is not an efficient market as it consists of numerous traders with differing strategies and interpretations of information. However there is substantial evidence to suggest that the stock market does incorporate new information into prices. Unfortunately little research has focussed on the high frequency effect of real time news, across a broad base of assets. This paper investigates how the US, UK, and Australian markets incorporate all real time news, not just Press Announcements, Annual Reports, etc. We find that there is strong evidence to suggest that the markets do incorporate news quickly.
Educational opportunities for US students abroad: how to internationalize and diversify your university
Authors: L. A. Gerhardt
Venue: Proceedings of the Frontiers in Education Conference, 2001. on 31st Annual - Volume 01 (2001)

Summary form only given. This paper discusses practical and effective models to help students study abroad and attract international students from around the world -with no lost revenue for educational institutions. The authors share insights into study abroad opportunities for US based engineering students, and describe some of the challenges posed by study abroad based on the experiences of the Global Engineering Education Exchange (Global E3) consortium. Topics covered include: how to promote study abroad to faculty and students; where students can study engineering overseas; financial aid and scholarships; and how to prepare students for the study abroad experience. The discussion also explores ways to welcome international students and how to advise them on academic and internship opportunities. The Global Engineering Education Exchange (Global E3) is an international exchange program that allows engineering students from 30+ US consortium-member institutions to study abroad and for students from international institutions in 14 countries to study at US member institutions. Through Global E3, students take courses overseas for credit at their home institutions, and receive practical training in another country, if desired. At the same time, the Global E3 program strives to minimize the increased costs associated with most study abroad programs.
Call Admission Control and Traffic Engineering of VoIP
Authors: James Yu, Imad Al-Ajarmeh
Venue: Proceedings of the Second International Conference on Digital Telecommunications (2007)

This paper presents an extension of the Erlnag-B model for traffic engineering of Voice over IP (VoIP). The Erlang-B model uses traffic intensity and Grade of Service (GoS) to determine the number of trunks in circuit-switched networks. VoIP traffic, however, is carried over packet-switched networks, and network capacity is measured in bits per second instead of the number of trunks. In this paper, we propose a new measurement scheme to translate network bandwidth into the maximum call load. With this new metric, the Erlang- B model is applicable to VoIP. We conducted experiments to measure the maximum call loads based on various voice codec schemes, including G.711, G.729A, and G.723.1. Our results show that call capacity is most likely constrained by network devices rather than physical connections. Based on this result, we recommend considering both packet throughput (pps) and bit throughput (bps) in determining the max call load. If network capacity is constrained by pps, codec schemes would have almost no effect on the maximum call load, while the sampling rate could easily double or half the call load.
A Hybrid Approach for Efficient Robust Design of Dynamic Systems
Authors: Martin Mo&uml;nnigmann, Wolfgang Marquardt, Christian H. Bischof, Thomas Beelitz, Bruno Lang, Paul Willems
Venue: SIAM Review (2007)

We propose a novel approach for the parametrically robust design of dynamic systems. The approach can be applied to system models with parameters that are uncertain in the sense that values for these parameters are not known precisely, but only within certain bounds. The novel approach is guaranteed to find an optimal steady state that is stable for each parameter combination within these bounds. Our approach combines the use of a standard solver for constrained optimization problems with the rigorous solution of nonlinear systems. The constraints for the optimization problems are based on the concept of parameter space normal vectors that measure the distance of a tentative optimum to the nearest known critical point, i.e., a point where stability may be lost. Such normal vectors are derived using methods from nonlinear dynamics. After the optimization, the rigorous solver is used to provide a guarantee that no critical points exist in the vicinity of the optimum, or to detect such points. In the latter case, the optimization is resumed, taking the newly found critical points into account. This optimize-and-verify procedure is repeated until the rigorous nonlinear solver can guarantee that the vicinity of the optimum is free from critical points and therefore the optimum is parametrically robust. In contrast to existing design methodologies, our approach can be automated and does not rely on the experience of the designing engineer. A simple model of a fermenter is used to illustrate the concepts and the order of activities arising in a typical design process.
Numerical modelling of biopotential field for detection of breast tumour
Authors: E. Y. K. Ng, W. K. Ng, L. S. J. Sim, U. Rajendra Acharya
Venue: Computers in Biology and Medicine (2007)

Breast cancer is a disease characterised by the uncontrolled growth of abnormal cells. These cancer cells can travel through the body by way of blood or lymph nodes. Previous studies have indicated that, changes in the electrical properties of abnormal breast are more significant compared to the breast normal tissues. In the present study, a simple 2D models of breast (close to realistic), with and without artificially inserted malignant cancer were simulated, based upon electrical activity within the breast. We developed an inhomogeneous female breast model, closer to the actual, by considering a breast as a hemisphere with various layers of unequal thickness in supine condition. In order to determine the potential distribution developed due to a dipole source, isotropic homogeneous conductivity was assigned to each of these compartments and the volume conductor problem was solved using finite element method. Significant changes in the potential distribution were recoded in the malignant and normal breast regions. The surface potential decreases about 0.5%, for the small malignant region of surface area 13mm^2 (spherical diameter=2mm). And it (surface potential) decreases about 16.4% for large malignant surface area of 615mm^2 (spherical diameter=14mm). Hence, the results show that, the sizes of tumours result in the reduction of surface potential and follows a fourth order polynomial equation. Thus, biofield analysis yields promising results in the detection of the breast cancer of various sizes.
Tracking performance of a stochastic gradient algorithm for transmit antenna weight adaptation with feedback
Authors: B. C. Banister
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05 (2001)

The tracking performance of a transmit antenna weight adaptation algorithm applied in a fading channel is considered. The system uses a stochastic gradient algorithm incorporating gradient sign feedback from a receiving unit to adjust the transmit weights. The feedback is simply a bit indicating which of two normalized perturbed transmission weights delivers greater power to the receiver. A reasonable performance measure is defined and an analytic estimate of the performance in an AR1 vector fading channel is derived and compared to simulations.
Protecting with Sensor Networks: Attention and Response
Authors: Jeffrey V. Nickerson, Stephan Olariu
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

Sensor networks are expected to play an important role in hybrid protection infrastructures when combined with robots and human decision makers. In order to be effective, detection of intruders needs to be attended to, and a timely response needs to be made. Intruders, on the other hand, if they can't avoid detection may make use of strategies to overload attention or dilute the response. Such strategies are related to Denial of Service attacks in electronic security. This paper develops the conceptual framework for modeling the game between intruders and defenders.
A Task Allocation Algorithm In a Multiprocessor Real-Time System
Authors: Jean-Pime BEAUVAIS, Anne-Marie DEPLANCHE
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 02 (1993)

This paper describes a heuristic algorithm in 0(n^2) which assigns a set of real-time task to a set of processing sites, The main objective that we try to achieve is to balance the load over the different processors of tke system to improve the safety of the system us well as checking the scheduling conditions that must be satisfied in a real-time context and taking into account given allocation consraints.
Mastering the Integration Chaos Following Frequent M&As: IS Integration with SOA Technology
Authors: Stefan Henningsson, Claes Svensson, Linus Vallen
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

The use of Service Oriented Architectures (SOA) is rapidly penetrating contemporary business life based on the promise of scalable and flexible information infrastructures. However the technique is still in it infancy and many questions regarding the consequences of a shift towards this kind of IT architecture still remains unanswered. We approach the relation between SOA and another actual topic, namely corporate mergers and acquisitions (M&A). Based on a literature review and an empirical study of five industrial companies we conclude seven relationships between properties of SOA and M&A, which should be valuable both for business professionals considering the SOA alternative and to advance the academic domain that is concerned with integration and M&A.
Comparing Interpersonal Interactions with a Virtual Human to Those with a Real Human
Authors: Andrew B. Raij Kyle Johnsen Robert F. Dickerson, Benjamin C. Lok
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

This paper provides key insights into the construction and evaluation of interpersonal simulators—systems that enable interpersonal interaction with virtual humans. Using an interpersonal simulator, two studies were conducted that compare interactions with a virtual human to interactions with a similar real human. The specific interpersonal scenario employed was that of a medical interview. Medical students interacted with either a virtual human simulating appendicitis or a real human pretending to have the same symptoms. In Study I (n = 24), medical students elicited the same information from the virtual and real human, indicating that the content of the virtual and real interactions were similar. However, participants appeared less engaged and insincere with the virtual human. These behavioral differences likely stemmed from the virtual human's limited expressive behavior. Study II (n = 58) explored participant behavior using new measures. Nonverbal behavior appeared to communicate lower interest and a poorer attitude toward the virtual human. Some subjective measures of participant behavior yielded contradictory results, highlighting the need for objective, physically-based measures in future studies.
SMART: an integrated multi-action advisor for storage systems
Authors: Li Yin, Sandeep Uttamchandani, Madhukar Korupolu, Kaladhar Voruganti, Randy Katz
Venue: Proceedings of the annual conference on USENIX '06 Annual Technical Conference (2006)

The designers of clustered file systems, storage resource management software and storage virtualization devices are trying to provide the necessary planning functionality in their products to facilitate the invocation of the appropriate corrective actions in order to satisfy user specified service level objectives (SLOs). However, most existing approaches only perform planning for a single type of action such as workload throttling, or data migration, or addition of new resources. As will be shown in this paper, single action based plans are not always cost effective. In this paper we present a framework SMART that considers multiple types of corrective actions in an integrated manner and generates a combined corrective action schedule. Furthermore, often times, the best cost-effective schedule for a one-week lookahead could be different from the best cost-effective schedule for a one-year lookahead. An advantage of the SMART framework is that it considers this lookahead time window in coming up with its corrective action schedules. Finally, another key advantage of this framework is that it has a built-in mechanism to handle unexpected surges in workloads. We have implemented our framework and algorithm as part of a clustered file system and performed various experiments to show the benefits of our approach.
Mobile data services: voices in the wilderness
Authors: D. Wisely, R. M. Dennis
Venue: BT Technology Journal (2007)

Killer applications or services tend to be a combination of inspiration, form, function and a solution to unmet need. The mobile phone and the iPod are obvious examples, but what will be the next killer application and why. Increasingly, convergence will add a new dimension to the quest for such an application. This paper considers that it may just be time for more than voices in the wilderness.
Surface reconstruction from images
Authors: Long Quan
Venue:  (2006)

Surface reconstruction from images is an old, fundamental yet difficult problem in computer vision, which has been extensively investigated over the past three decades. Recent developments in camera calibration and multimedia computing have broadened the interests in the reconstruction problem, and the big proliferation of digital cameras and computers allow to take and process multiple images respectively. The emphasis of the nowaday applications has been shifted to generating more "appearance" views of the scene, and it requires highly detailed surfaces to be constructed within a tolerable computational resources. Such a task, however, is difficult to accomplish due to the intrinsic ill-posedness of the reconstruction, interference from image noise, and insufficiency of scalability and flexibility. Mathematically, scene objects can be represented as smooth surfaces with arbitrary topology, and surface reconstruction from images could be cast into various problems and formulations. In this dissertation, we focus on the mathematical descriptions and representations, and discuss the reconstruction approaches that use volumetric, graph-cut, and level-set optimization tools, and the objective functionals that use different image cues, such as silhouette, photometry, texture and shading. The dissertation is also a general introduction to the surface reconstruction background knowledge, and a general discussion and comparison among different kinds of reconstruction methods. In despite of the successful mathematical solutions to the ill-posedness of the reconstruction and the interference from image noise, the scalability and flexibility issues remain largely unaddressed. In order to overcome the limitations stemmed from these issues, we further propose the patchwork representation and reconstruction, which is a collection of small surface patches progressively and stitched together. This patchwork framework is capable of retrieving both complete shapes and open surfaces. The final part of this dissertation contains a discussion beyond multi-view surface reconstruction. This is because, in some situations, when only a single image is provided or when the structural information is predominant, multi-view surface reconstruction is not capable of modeling the scene. The main focuses are given to single-view surface reconstruction and multi-view space curve reconstruction. Meanwhile, shape-from-shading is formulated with the classical graph theory of finding the shortest path on a network, and solved with the Fast Marching methods. Space curve is represented by an implicit distance function, and optimized using the variational framework.
Adaptive Feature Learning for Information Pattern Recognition
Authors: Hong Liang
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2007)

Adaptive feature learning is an effective method to explore the mechanism of information pattern recognition in information flow. This paper integrates the progresses of expert learning and artificial intelligence to propose a few new learning algorithms for pattern recognition in information flow. For solving high order matrix computing problem, this paper proposes an Orthogonal Transformation algorithm. For solving Frequency Modulation (FM) pattern recognition problem, this paper proposes a differential algorithm. For solving unknown pattern recognition in large scale information flow problem, this paper proposes inverse convolution algorithm and probability spectrum algorithm. These feature learning algorithms can extract and recognize pattern fast, efficiently and explicitly, even patterns are complex, confused and incomplete.
The Interactive Digital Entertainment (IDE) Unification Framework: Creating a Taxonomy of IDE and Lifestyle Computing
Authors: Greg Moody, Taylor Wells, Paul Benjamin Lowry
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

In this paper, we create a taxonomy of interactive digital entertainment (IDE), which can be used to guide future research in IDE and direct the design of interactive entertainment. We start by defining and explaining the differences between IDE and lifestyle computing. We then review the major taxonomies on gaming that can illuminate research and practice with IDE. Given this review, we propose an overarching taxonomy called the IDE Unification Framework. Based on this framework, we then propose promising areas for future research.
Disintermediated Active Communication
Authors: Anne Bracy, Kshitij Doshi, Quinn Jacobson
Venue: IEEE Computer Architecture Letters (2006)

Disintermediated Active Communication (DAC) is a new paradigm of communication in which a sending thread actively engages a receiving thread when sending it a message via shared memory. DAC is different than existing approaches that use passive communication through shared-memory based on intermittently checking for messages or that use preemptive communication but must rely on intermediaries such as the operating system or dedicated interrupt channels. An implementation of DAC builds on existing cache coherency support and exploits light-weight user-level interrupts. Inter-thread communication occurs via monitored memory locations where the receiver thread responds to invalidations of monitored addresses with a light-weight user-level software-defined handler. Address monitoring is supported by Cache Line User-bits, or CLUbits. CLUbits reside in the cache next to the coherence state, are private per thread, and maintain userdefined per-cache-line state. A light weight software library can demultiplex asynchronous notifications and handle exceptional cases. In DAC-based programs threads coordinate with one another by explicit signaling and implicit resource monitoring. With the simple and direct communication primitives of DAC, multi-threaded workloads synchronize at a finer granularity and more efficiently utilize the hardware of upcoming multi-core designs. This paper introduces DAC, presents several signaling models for DAC-based programs, and describes a simple memory-based framework that supports DAC by leveraging existing cache-coherency models. Our framework is general enough to support uses beyond DAC.