ppxscal/embedding_network huggingface dataset:
Proactive Reed-Solomon Bypasss (PRSB): A Technique for Real-Time Multimedia Processing in 3G Cellular Broadcast Networks
Authors: Yongwoo Cho, Kyungtae Kang, Joonho Lee, Heonshik Shin
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

We analyze the execution time of MAC-layer Reed-Solomonerror recovery in cdma2000 1xEV-DO broadcast and multicast services (BCMCS), with respect to cache size and air channel condition. We observe that a deteriorating channel condition often causes an intolerable delay for real-time tasks because of the error recovery process, even when sufficient cache memory is available to increase CPU throughput. To overcome this problem, we propose proactive Reed-Solomon bypass (PRSB), which determines whether the Reed-Solomon scheme should be used to correct errors in the real-time communication environment. The proposed scheme utilizes the cache effectively, thus preventing reset of the entire decoding process and allowing real-time multimedia applications to meet their deadline constraints. Simulation results show that the PRSB greatly improves the overall playback quality of a video.
Supporting multimedia streaming between mobile peers with link availability prediction
Authors: Min Qin, Roger Zimmermann, Leslie S. Liu
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

Numerous types of mobile devices are now popular with end users, who increasingly use them to carry multimedia content on the go. As wireless connectivity is integrated with more handhelds, streaming multimedia content among mobile peers is becoming a popular application. One of the main challenges in mobile streaming is the requirement that the link must be continuously available for a period of time to enable uninterrupted data transmission and a smooth media performance. Hence, an accurate prediction of future link availability is very desirable and allows, for example, the selection of the most stable link when a multimedia object is available from multiple peers. In this paper, we present a novel iterative algorithm for predicting continuous link availability between two mobile ad-hoc peers. Our method can function without the support of GPS equipment. By a rough estimation of the distance between two peers, our approach is able to accurately predict link availability over a short period of time. Experimental results show that our algorithm can accurately estimate the future link status with an error margin lower than 7%. To demonstrate the feasibility of our approach we have integrated our link prediction algorithm into MStream: a pioneering mobile audio streaming application. Simulation results show that our link availability model can reduce the number of link breaks and achieve smooth streaming experiences among mobile peers.
On random &plusmn;1 matrices: Singularity and determinant
Authors: Terence Tao, Van Vu
Venue: Random Structures Algorithms (2006)

This papers contains two results concerning random n &times; n Bernoulli matrices. First, we show that with probability tending to 1 the determinant has absolute value $\sqrt{n!}\exp(O(\sqrt{n \ln n}))$. Next, we prove a new upper bound 0.958n on the probability that the matrix is singular.&copy; 2005 Wiley Periodicals, Inc. Random Struct. Alg., 2006
A Reinforcement Learning Algorithm in Cooperative Multi-Robot Domains
Authors: Fernando Fernández, Daniel Borrajo, Lynne E. Parker
Venue: Journal of Intelligent and Robotic Systems (2005)

Reinforcement learning has been widely applied to solve a diverse set of learning tasks, from board games to robot behaviours. In some of them, results have been very successful, but some tasks present several characteristics that make the application of reinforcement learning harder to define. One of these areas is multi-robot learning, which has two important problems. The first is credit assignment, or how to define the reinforcement signal to each robot belonging to a cooperative team depending on the results achieved by the whole team. The second one is working with large domains, where the amount of data can be large and different in each moment of a learning step. This paper studies both issues in a multi-robot environment, showing that introducing domain knowledge and machine learning algorithms can be combined to achieve successful cooperative behaviours.
Adding the modal mu-calculus to the instruction-set process calculus
Authors: Shiu-Kai Chin, Susan Older
Venue:  (2005)

IspCal is a formal language well suited for describing synchronous digital systems, and it supports hardware composition. It is also a calculus with which we can equate one description with another. However, its original description lacked the ability to express crucial temporal properties of systems, such as safety and liveness. To provide the ability of expressing temporal properties, we have added a temporal logic (the modal mu-calculus) to IspCal. By adding the modal mu-calculus to IspCal, we enriched the expressiveness of IspCal so that we can express safety-critical temporal properties of systems and verify that systems satisfy the properties. In addition we proved an important proposition of the modal mu-calculus, the satisfaction-equivalence proposition. This proposition states that bisimilar processes share the same properties. The result is a potential great savings in time and effort for property checking. In this thesis we focus on the procedures for adding the modal mu-calculus to Isp-Cal. We implement the syntax and semantics of the modal mu-calculus as conservative extensions to the Higher Order Logic (HOL4) theorem prover. We also prove several propositions of modal mu-calculus in HOL, such as the satisfaction-equivalence proposition.
Wave pipelining with self reset logic
Authors: Samiha Mourad
Venue:  (2005)

Implementation of Wave Pipelining using a new family of Self Reset Logic (SRL) cells is presented in this work. Wave pipelining maximizes data throughput and as intermediate storage elements are removed it leads to circuit implementations that are fast and lean because of the savings in area and power. Dynamic circuits have been shown to achieve higher speeds compared to their static counterparts, while adding clocking overhead. In SRL power consumption is data dependent because power is consumed only if new data is purmped through the logic. There is no clock distribution network, each stage is in stand-by mode and reacts upon receiving new data. The clocking overhead is thus reduced, while still achieving as good or better speed than other dynamic implementations. Combining Wave Pipelining and Self Reset Logic provides and elegant solution at high speed and data throughput with significant savings in power and area. To resolve some limitations in previous SRL art we employ a new SRL family, namely: Self Reset Logic with Input Disable (SRL-ID). To overcome the monotonicity of the basic SRL-ID cell, a Dual Rail (DRSRL-ID) implementation is proposed. DRSRL-ID gates depict small delay variations for all input combinations, and produce output pulses of fairly constant width for varying fanout and logic depth, leaving enough headroom in the design to accommodate process, supply voltage and temperature variations (PVT). These properties simple the implementation of wave pipelined circuits. Case study examples are included to show the design methodology and feasibility of wave pipelined circuits implemented with these gates.
AICTO: An Improved Algorithm for Planning Inter-class Test Order
Authors: Chengying Mao, Yansheng Lu
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

Determining inter-class test order is one of the most difficult tasks in cluster level testing. This paper proposes the concept of weighted object relation diagram (WORD) by extending the traditional object relation diagram (ORD). When generating the interclass test order based on WORD, minimizing the number of realistic stubs (not the number of classes to be stubbed) is regarded as optimization objective. Some heuristic rules, such as association intensity, cycling weight and direction factors of edges, are used as important criteria to cut association edges to break cycles. An improved algorithm AICTO is presented via analyzing some principles of the existing methods and overcoming some of their drawbacks. This algorithm has some merits such as the fewer number of classes to be stubbed, holding the association edges with higher RD and excellent stability. In practice, the algorithm AICTO has been applied to our C/C++ program testing prototype CppTest and produces favorable effects.
A Performance and Power Co-optimization Approach for Modern Processors
Authors: Yongxin ZHU, Weng-Fai WONG, Cheng-kok KOH
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

In embedded systems, performance and power are important inter-related issues that cannot be decoupled. Expensive and extensive simulations in a processor design space are usually required to verify whether a design meets both performance and power requirements. In this paper, an analytical co-optimization approach based on an integrated workload, performance and power model for modern processors is described and studied. A design space consisting of more than 15 architectural and workload parameters can be quickly explored for co-optimization. Validation with measured results obtained from simulators as well as physical processors showed that the model has a good degree of accuracy. We shall describe the details of approach and the model, and show how to apply the approach to the problem of co-optimizing the power and performance of processor design. With the completeness, flexibility and efficiency, our approach provides clear insights into the tradeoffs of designs for performance and power.
What is needed for robust simulation?
Authors: M. S. Elzas
Venue: ACM SIGSIM Simulation Digest (1977)

In the first place a definition will be be constructed of what the author thinks should be understood under "robust simulation". This definition will encompass not only a type of "foolproofness" of the underlying computational algorithms but also such things as universality of concepts, model description validity, program integrity, documentation and implications of new hardware.
The Role of the Risk Management Database in the Risk Management Process
Authors: Louis Fussell, Scott Field
Venue: Proceedings of the 18th International Conference on Systems Engineering (2005)

The role of the risk management database is to help document and communicate risk information. In this regard, standardized risk management databases lead to a common understanding of risk management information. While risk information is similar from program to program, program characteristics, such as the organizational components, program goals and objectives, and major program threats, require significant variations in the risk management process. To support aspects of the risk management process other than documentation and communication (e.g., identification, analysis, handling, tracking), the risk management database should be tailored to meet the needs of the program. This paper examines each step in the risk management process and discusses how the risk management database should be tailored to facilitate process execution.
A Strong User Authentication Protocol for GSM
Authors: Ozer Aydemir, Ali Aydyn Selcuk
Venue: Proceedings of the 14th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprise (2005)

Traditionally, the authentication protocols for cellular phone networks have been designed for device authentication rather than user authentication, which brings certain limitations and restrictions on the functionality of the system. In this paper we propose a user authentication protocol for the Global Standards for Mobile (GSM) which permits the use of weak secrets (e.g. passwords or PINs) for authentication, providing new flexibilities for the GSM users.
Hierarchic Bayesian models for kernel learning
Authors: Mark Girolami, Simon Rogers
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance when compared to that obtained from any single data source. We present a Bayesian hierarchical model which enables kernel learning and present effective variational Bayes estimators for regression and classification. Illustrative experiments demonstrate the utility of the proposed method. Matlab code replicating results reported is available at http://www.dcs.gla.ac.uk/~srogers/kernel_comb.html.
Frameworks on New XML/EDI System for B2B Shipping Companies in Korea
Authors: Soung Won Kim, Ran Jung, Myoung Soo Kim
Venue: Proceedings of the Third ACIS Int'l Conference on Software Engineering Research, Management and Applications (2005)

In this paper, we survey and analyze the actual conditions of EDI system for B2B business of transport companies in Korea. As the result of our analyses, it comes an old fashioned EDI system at harbor and logistics industry, and the VAN based systems are still widely used in Korea. In conclusion, the next generation EDI, XML/EDI, is very effective to solve these kinds of problems. So, we suggest and implement a scheme of XML/EDI as a substitute for the traditional one. We design and implement the XML/EDI system on B2B of Shipping Request to show the effectiveness and strength of XML/EDI over the traditional EDI. At first, we analyze the standard items of shipping request EDI, and define the document by the DTD of shipping request. And we implement the document creation module in order to generate the document without user's knowledge of XML, and also implement XML storage module to store the generated XML document.
Conference record of the 33rd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Venue: Annual Symposium on Principles of Programming Languages (2006)

It is my great pleasure to welcome you to POPL'06, the 33rd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, one of the flagship conferences in the programming languages calendar.The Call for Papers attracted a total of 167 submissions. Each paper was assigned to three members of the program committee. Committee members were expected to read each paper assigned to them, and write a review, but were also encouraged to seek additional reviews from others. In practice, most papers indeed benefited from these additional reviews. We are hugely grateful to these referees, whose names are listed later in this proceedings.All the reviews were made available to authors a week before the program committee meeting, so that they had the opportunity to make a 500-word response. These responses were read by the committee members responsible, and were taken into account during the committee's discussions. I did not ask committee members to make a written reply to each author response.The committee held a physical meeting in Cambridge, England, on 21st and 22nd September, which every member of the committee attended. We were conscious that POPL's rejection ratio is comparatively high, because it receives so many submissions, and that, as a result, high-quality papers might be rejected. For 2006 we decided to increase the number of accepted papers by shortening the length of each talk from 30 to 25 minutes, and by extending the conference to a full three days (as in 2005). Nevertheless, our over-riding concern was to maintain the standard of accepted papers. Balancing these concerns, we eventually accepted 33 papers, a rather modest increase over the 31 accepted in 2005, but the shorter talks have made it possible to have shorter sessions and longer breaks during the conference. I would welcome your feedback about whether or not you regard these changes as improvements.The POPL'06 program also features three invited talks, given by James McKinna, Martin Odersky, and Tim Sweeney.
A Strategy for the Formal Composition of Frameworks
Authors: Walter Mesquita, Augusto Sampaio, Ana C. V. De Melo
Venue: Proceedings of the Third IEEE International Conference on Software Engineering and Formal Methods (2005)

Framework composition, when used for designing and implementing applications, offers great potential for reuse and extensibility in large scale. However, the literature shows that composing frameworks may result in unexpected side-effects like, for instance, the introduction of deadlock. In this work, we use the process algebra CSP to formally characterize the framework composition problem, abstracting from implementation details or technology. We propose a framework composition strategy which guarantees that the properties of the compound frameworks are preserved after composition. The strategy is presented through a case study: a client/server application.
Just In Time Dynamic Voltage Scaling: Exploiting Inter-Node Slack to Save Energy in MPI Programs
Authors: Nandini Kappiah, Vincent W. Freeh, David K. Lowenthal
Venue: Proceedings of the 2005 ACM/IEEE conference on Supercomputing (2005)

Recently, improving the energy efficiency of HPC machines has become important. As a result, interest in using powerscalable clusters, where frequency and voltage can be dynamically modified, has increased. On power-scalable clusters, one opportunity for saving energy with little or no loss of performance exists when the computational load is not perfectly balanced. This situation occurs frequently, as balancing load between nodes is one of the long standing problems in parallel and distributed computing. In this paper we present a system called Jitter, which reduces the frequency on nodes that are assigned less computation and therefore have slack time. This saves energy on these nodes, and the goal of Jitter is to attempt to ensure that they arrive "just in time" so that they avoid increasing overall execution time. For example, in Aztec, from the ASCI Purple suite, our algorithm uses 8% less energy while increasing execution time by only 2.6%.
Automatic motif discovery in an enzyme database using a genetic algorithm-based approach
Authors: D. F. Tsunoda, H. S. Lopes
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2006)

Proteins can be grouped into families according to some features such as hydrophobicity, composition or structure, aiming to establish the common biological functions. This paper presents a system that was conceived to discover features (particular sequences of amino acids, or motifs) that occur very often in proteins of a given family but rarely occur in proteins of other families. These features can be used for the classification of unknown proteins, that is, to predict their function by analyzing the primary structure. Runnings were done with the enzymes subset extracted from the Protein Data Bank. The heuristic method used was based on a genetic algorithm using specially tailored operators for the problem. Motifs found were used to build a decision tree using the C4.5 algorithm. The results were compared with motifs found by MEME, a freely available web tool. Another comparison was made with classification results of other two systems: a neural network-based tool and a hidden Markov model-based tool. The final performance was measured using sensitivity (Se) and specificity (Sp): similar results were obtained for the proposed tool (78.79 and 95.82) and the neural network-based tool (74.65 and 94.80, respectively), while MEME and HMMER resulted in an inferior performance. The proposed system has the advantage of giving comprehensible rules when compared with the other approaches. These results obtained for the enzyme dataset suggest that the evolutionary computation method proposed is very efficient to find patterns for protein classification.
UMD Experiments with FRGC Data
Authors: Gaurav Aggarwal, Soma Biswas, Rama Chellappa
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

Although significant work has been done in the field of face recognition, the performance of state-of-the art face recognition algorithms is not good enough to be effective in operational systems. Though most algorithms work well for controlled images, they are quite susceptible to changes in illumination and pose. Face Recognition Grand Challenge (FRGC) is an effort to examine such issues to suitably guide future research in the area. This paper describes the efforts made at UMD in this direction. We present our results on several experiments suggested in FRGC. We believe that though pattern classification techniques play an extremely significant role in automatic face recognition under controlled conditions, physical modeling is required to generalize across varying situations. Accordingly, we describe a generative approach to recognize faces across varying illumination. Unlike most current methods, our method does not ignore shadows. Instead we use them to our benefit by modeling attached shadows in our formulation.
Time series forecasting: obtaining long term trends with self-organizing maps
Authors: G. Simon, A. Lendasse, M. Cottrell, J.-C. Fort, M. Verleysen
Venue: Pattern Recognition Letters (2005)

Kohonen self-organisation maps are a well know classification tool, commonly used in a wide variety of problems, but with limited applications in time series forecasting context. In this paper, we propose a forecasting method specifically designed for multi-dimensional long-term trends prediction, with a double application of the Kohonen algorithm. Practical applications of the method are also presented.
Bridging the Gap between Data Warehouses and Business Processes: A Business Intelligence Perspective for Event-Driven Process Chains
Authors: Veronika Stefanov, Beate List
Venue: Proceedings of the Ninth IEEE International EDOC Enterprise Computing Conference (2005)

Data Warehouse (DWH) information is accessed by business processes, and sometimes may also initiate changes of the control flow of business process instances. Today, there are no conceptual models available that make the relationship between the DWH and the business processes transparent. In this paper, we extend the Event-Driven Process Chain, a business process modeling language, with an additional perspective to make this relationship explicit in a conceptual model. The model is tested with example business processes.
Incremental Commit Groups for Non-Atomic Trace Processing
Authors: Matt T. Yourst, Kanad Ghose
Venue: Proceedings of the 38th annual IEEE/ACM International Symposium on Microarchitecture (2005)

We introduce techniques to support efficient non-atomic execution of very long traces on a new binary translation based, x86-64 compatible VLIW microprocessor. Incrementally committed long traces significantly reduce wasted computations on exception induced rollbacks by retaining the correctly committed parts of traces. We divide each scheduled trace into multiple commit groups; groups are committed to the architectural state after all instructions within and prior to each group complete without exceptions. Architectural state updates are only visible after future commit points are deferred using a simple hardware commit buffer. We employ a commit depth predictor to predict how many groups a trace will complete, thereby eliminating pipeline flushes on repeated rollbacks. Unlike atomic traces, we allow instructions to be freely scheduled across commit points throughout the trace to maximize ILP. Commit groups are formed after scheduling, allowing the commit points terminating each group to be inserted more optimally. Commit groups promote significantly faster convergence on optimized traces, since we salvage partially executed traces and splice the working parts together into new optimized traces. We use detailed models to demonstrate how commit groups substantially improve performance (on average, over 1.5× on SPEC 2000) relative to atomic traces.