ppxscal/embedding_network huggingface dataset:
Games interlocutors play: new adventures in compositionality and conversational implicature
Authors: Robin Clark
Venue:  (2006)

How much of linguistic meaning is simply a corollary of rational behavior? And what is the best way to represent and compute conversational implicatures? I aim to show that the Games of Partial Information (GPIs) of Parikh (2001) are descriptively and explanatorily superior to the leading pragmatic theories of conversational implicature. Explicitly based on utility maximization, Parikh's game-theoretic account of communication captures the distinct advantages of the current disparate theories of conversational implicature. It has the clarity, focus, and explicit predictions of the neo-Griceans' accounts of utterance meaning (Levinson, 2000), while also demonstrating the flexibility of relevance theorists' accounts focused on utterance interpretation (Sperber and Wilson, 1995). Bidirectional Optimality Theory (Dekker and van Rooy, 2000), another game-theoretic/utility-based framework, is a marked improvement over neo-Gricean and relevance theory, but it lacks the scope and power needed to fully account for the context sensitivity of conversational implicature. The prior probabilities of GPIs (and their weighted sums) allow contextual factors to be taken into account, and can explain hitherto unexamined aspects of scalar implicature. It is shown that in some cases both Sauerland's and Chierchia's theories fail and in other cases one fails and the other does not. GPIs provide a framework that obviates the need for exclusively localist or globalist accounts of implicature. The insight missing from Chierchia's and Sauerland's theories is that their sets of predictions are not mutually exclusive: whether utterances have Chierchia-style localist meanings or a Sauerland-style globalist meanings is not a question that can be settled across the board, once and for all. Rather, whether a particular utterance has a localist or globalist meaning depends on a set of context-sensitive parameters: prior probabilities of possible intended meanings, the utterance costs of unambiguous expressions of those meanings, and the (dis)utility that the interlocutors derive from (mis)communicating those meanings. In cases for which the localist and the globalist make the same predictions, there is simply no fact of the matter of whether that meaning was local or global---the problem is ultimately solved on a higher level of abstraction, rendering localism and globalism both epiphenomenal.
An efficient crest factor reduction technique for wideband applications
Authors: Wan-Jong Kim, Kyoung-Joon Cho, Shawn P. Stapleton, Jong-Heon Kim
Venue: Analog Integrated Circuits and Signal Processing (2007)

This paper describes a new efficient crest factor reduction technique for wideband applications. The technique is based on using peak cancellation to reduce the peak-to-average power ratio (PAPR) of the input signal. Conventional iterative peak cancellation requires several iterations so as to converge into the targeted PAPR, since filtering causes peak re-growth. The proposed algorithm is able to eliminate several iterations, which subsequently saves hardware resources. In numerical simulations using four WCDMA carriers, it achieves a PAPR of 5.7 dB with a fixed EVM of 10%. A 240 W PEP Class AB power amplifier was utilized to verify the performance of the proposed technique and demonstrate the efficiency gains. The measured results demonstrate that this algorithm can enhance the efficiency of our PA by up to 6.6%, when compared to the efficiency without the PAPR technique.
Dynamic reconfiguration in sensor networks with regenerative energy sources
Authors: Ani Nahapetian, Paolo Lombardo, Andrea Acquaviva, Luca Benini, Majid Sarrafzadeh
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

In highly power constrained sensor networks, harvesting energy from the environment makes prolonged or even perpetual execution feasible. In such energy harvesting systems, energy sources are characterized as being regenerative. Regenerative energy sources fundamentally change the problem of power scheduling for embedded devices. Instead of the problem being one of maximizing the lifetime of the system given a total amount of energy, as in traditional battery powered devices, the problem becomes one of preventing energy depletion at any given time. Coupling relatively computationally intensive applications, such as video processing applications, with the constrained FPGAs that are feasible on power constrained embedded systems, makes dynamic reconfiguration essential. It provides the speed comparable to a hardware implementation, but it also allows the dynamic reconfiguration to meet the multiple application needs of the system. Different applications can be loaded on the FPGA, as the system's needs change over time. The problem becomes how to schedule the dynamic reconfiguration to appropriately make use of the regenerative energy source, to ensure the proper availability of energy for the system over time. In this paper, we present a methodology for carrying out dynamic reconfiguration for regenerative energy sources, based on statistical analysis of tasks and supply energy. The approach is evaluated through extensive simulations. Additionally, we have evaluated our implementation on our regenerative energy, dynamically reconfigurable prototype, known as the MicrelEye. Our approach is shown to miss 57.7% less deadlines on average than the current approach for reconfiguration with regenerative energy sources.
ARMADA - An algorithm for discovering richer relative temporal association rules from interval-based data
Authors: Edi Winarko, John F. Roddick
Venue: Data Knowledge Engineering (2007)

Temporal association rule mining promises the ability to discover time-dependent correlations or patterns between events in large volumes of data. To date, most temporal data mining research has focused on events existing at a point in time rather than over a temporal interval. In comparison to static rules, mining with respect to time points provides semantically richer rules. However, accommodating temporal intervals offers rules that are richer still. In this paper we outline a new algorithm, ARMADA, to discover frequent temporal patterns and to generate richer interval-based temporal association rules. In addition, we introduce a maximum gap time constraint that can be used to get rid of insignificant patterns and rules so that the number of generated patterns and rules can be reduced. Synthetic datasets are utilized to assess the performance of the algorithm.
Optimizing Linux device drivers for SMP
Authors: Jes Sorensen
Venue: Proceedings of the 3rd annual conference on Atlanta Linux Showcase - Volume 3 (1999)

Linux is now perceived as being suitable for use as a large server and as a high-end computing platform. To meet the needs of these environments, a lot of work is being put into making Linux scale better on SMP systems. Allowing device drivers to run multithreaded is an important part of this work. This talk will look at the aspects of making device drivers SMP aware and how to optimize them for speed. It will show how the use of atomic types can reduce or even eliminate the need for spinlocks, resulting in a faster, lock-free driver. Other aspects covered will include the use of memory mapped I/O rather than I/O mapped and the reduction of cache effects by keeping code and data structures local to the CPU. The specific example used in the talk will be the driver for the Alteon AceNIC Gigabit Ethernet card, however the techniques are applicable to most of the drivers in the kernel.
Sharing networked resources with brokered leases
Authors: David Irwin, Jeffrey Chase, Laura Grit, Aydan Yumerefendi, David Becker, Kenneth G. Yocum
Venue: Proceedings of the annual conference on USENIX '06 Annual Technical Conference (2006)

This paper presents the design and implementation of Shirako, a system for on-demand leasing of shared networked resources. Shirako is a prototype of a service-oriented architecture for resource providers and consumers to negotiate access to resources over time, arbitrated by brokers. It is based on a general lease abstraction: a lease represents a contract for some quantity of a typed resource over an interval of time. Resource types have attributes that define their performance behavior and degree of isolation. Shirako decouples fundamental leasing mechanisms from resource allocation policies and the details of managing a specific resource or service. It offers an extensible interface for custom resource management policies and new resource types. We show how Shirako enables applications to lease groups of resources across multiple autonomous sites, adapt to the dynamics of resource competition and changing load, and guide configuration and deployment. Experiments with the prototype quantify the costs and scalability of the leasing mechanisms, and the impact of lease terms on fidelity and adaptation.
Calligraphic packing
Authors: Jie Xu, Craig S. Kaplan
Venue: Proceedings of Graphics Interface 2007 (2007)

There are many algorithms in non-photorealistic rendering for representing an image as a composition of small objects. In this paper, we focus on the specific case where the objects to be assembled into a composition are letters rather than images or abstract geometric forms. We develop a solution to the "calligraphic packing" problem based on dividing up a target region into pieces and warping a letter into each piece. We define an energy function that chooses a warp that best represents the original letter. We discuss variations in rendering style and show results produced by our system.
A new radix-6 FFT algorithm suitable for multiply-add instruction
Authors: D. Takahashi
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06 (2000)

A new radix-6 FFT algorithm suitable for multiply-add instruction is proposed. The new radix-6 FFT algorithm requires fewer floating-point instructions than the conventional radix-6 FFT algorithms on processors that have a multiply-add instruction. We use Goedecker's (1997) techniques to obtain an algorithm for computing radix-6 FFT with fewer floating-point instructions than conventional radix-6 FFT algorithms. The number of floating-point instructions for the new radix-6 FFT algorithm is compared with those of conventional radix-6 FFT algorithms on processors with multiply-add instruction.
Targeting program visualizations
Authors: Essi Lahtinen, Hannu-Matti Järvinen, Suvi Melakoski-Vistbacka
Venue: Proceedings of the 12th annual SIGCSE conference on Innovation and technology in computer science education (2007)

To instruct students on the use of visualizations most beneficially the teacher needs to know who the students are that use the visualizations, for what they use them, and what kind of problems they have. Empirical research has been carried out on the educational impact of visualizations in test situations, but this survey presents the students' normal way of studying when the use of visualizations is voluntary. We present the results of an international survey of 335 students who are studying programming and whose teachers have offered visualizations as extra material for the students. Their teachers also answered the survey. The article analyses different kinds of student groups, their usage of visualizations, and problems with them. We explore the background and motivation of the students and compare this information to their experiences of the use of the visualizations. We identified two groups of students who use visualizations differently: moderately successful students able to work independently and weaker students who need teachers guidance with the visualizations. We suggest tips for teachers on how to use visualizations in teaching and provide information for the development of program visualization tools.
On rank correlation in information retrieval evaluation
Authors: Massimo Melucci
Venue: ACM SIGIR Forum (2007)

Some methods for rank correlation in evaluation are examined and their relative advantages and disadvantages are discussed. In particular, it is suggested that different test statistics should be used for providing additional information about the experiments other that the one provided by statistical significance testing. Kendall's &tau; is often used for testing-rank correlation, yet it is little appropriate if the objective of the test is different from what &tau; was designed for. In particular, attention should be paid to the null hypothesis. Other measures for rank correlation are described. If one test statistic suggests to reject a hypothesis, other test statistics should be used to support or to revise the decision. The paper then focuses on rank correlation between webpage lists ordered by PageRank for applying the general reflections on these test statistics. An interpretation of PageRank behaviour is provided on the basis of the discussion of the test statistics for rank correlation.
A Neural Net Branch Predictor to Reduce Power
Authors: Rajamani Sethuram, Omar I. Khan, Hari Vijay Venkatanarayanan, Michael L. Bushnell
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

We present a power-aware neural network (PAN) branch prediction (BP) scheme for dynamic branch prediction, and schemes to incorporate anti-aliasing techniques into the neural branch predictor. We avoid incorrectly falling into segments of code that consume much power. By adding lookup table-based hardware, we estimate the power dissipated in the entire processor between successive branches. We consider a processor with a neural net branch predictor and use Aggressive Training on the neural network (NN) to severely penalize incorrect branch predictions that cause the processor to waste power. Our scheme dynamically learns to dissipate less power during successive calls to a particular branch instruction. Hence, our approach is different from all prior approaches that reduce miss-prediction or use hardware techniques (clock gating, banking) to reduce power dissipation.
Perception-based residual analysis-synthesis system
Authors: Y. H. Lam
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

The paper describes a residual analysis-synthesis system which exploits the human perception mechanism on temporal varying signals using Zwicker's (1990) three dimensional excitation-critical-bandrate time pattern as the framework. Temporal information is retrieved using a linear predictive analysis on the discrete cosine transformed signal and critical band intensity information is obtained by using non-uniform filter banks. The system is characterized by high frequency resolution and good time resolution. Novel phase prediction and phase correction techniques are employed to eliminate any boundary discontinuities between two time frames. Experimental results illustrate that high quality residual signals can be reproduced using a few parameters regardless of the temporal characteristics of the signal.
Design challenges at 65nm and beyond
Authors: Andrew B. Kahng
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

Semiconductor manufacturing technology faces ever-greater challenges of pitch, mobility, variability, leakage, and reliability. To enable cost-effective continuation of the semiconductor roadmap, there is greater need for design technology to provide "equivalent scaling", and for product-specific design innovation (multi-core architecture, software support, beyond-die integration, etc.) to provide "more than Moore" scaling. Design challenges along the road to 45nm include variability and power management, and leverage of design-manufacturing synergies. Potential solutions include "design for manufacturability" bridges between chip implementation and manufacturing know-how.
A Robust UART Architecture Based on Recursive Running Sum Filter for Better Noise Performance
Authors: Himanshu Patel, Sanjay Trivedi, R. Neelkanthan, V. R. Gujraty
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

This paper describes a novel architecture of Universal Asynchronous Receiver Transmitter (UART) based on Recursive Running Sum (RRS) filter. UARTs are used for asynchronous serial data communication between remote embedded systems. If physical channel is noisy then, serial data bits get corrupted during transmission. The robust UART core described here, utilizes recursive running sum filter to remove noisy samples. Input data signal is directly sampled with system clock and samples are accumulated over a window size. The window size is user programmable and it should be set to one third of required bit period. The intermediate data bit is decoded using magnitude comparator. A majority voter is used to decode actual data bit from three intermediate data bits. Comparison of MATLAB simulation results at different noise level shows that the robust UART described here has far better performance than standard UART at higher noise levels. Other advantage of this architecture is that baud rate is decided by the window size so there is no need of any external "timer module" which is normally required for standard UARTs. The robust UART core described here is designed using VHDL and implemented on Xilinx Virtex FPGA.
Perspectives on learning in a capstone design course
Authors: D. T. Rover
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 02 (2000)

A new course learning model was developed for our capstone design course in computer engineering, ECE 482-Capstone: Computer System Design. It has been delivered during six semesters, each providing a set of new experiences and an array of lessons learned. Students, employers and educational researchers have recognized the benefits of the course. Despite the positive outcomes, key questions and obstacles remain that impact sustainable reform in the capstone design experience. We chronicle the experiences and lessons from the perspectives of the faculty and students involved with the course. We focus on the learning model, including its implementation, adaptation, impact and perception.
High resolution direction of arrival estimation of multiple wide-band sources in multichannel adaptive nulling systems
Authors: M. G. Amin
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05 (1996)

The main purpose of this paper is to demonstrate that the adaptive weights obtained from different frequency channels can be used for high-resolution direction of arrival (DOA) estimation. It is shown that these weights have sufficient information which can be processed by eigenstructure methods to yield the signal and the noise subspaces. As such, with the availability of the adaptive weights in a multichannel nulling system, source localization using the data matrix or time-averaged estimation of the covariance matrix may, in most casts, prove unnecessary and can only add meager improvement over the proposed method. We present two approaches to extract the eigenstructures from the multichannel adaptive weights. Both approaches are based on coherent subspace averaging, namely the focusing techniques.
Sarir: A Rebeca to mCRL2 Translator
Authors: H. Hojjat, M. Sirjani, M. R. Mousavi, J. F. Groote
Venue: Proceedings of the Seventh International Conference on Application of Concurrency to System Design (2007)

We describe a translation from Rebeca, an actor-based language, to mCRL2, a process algebra enhanced with data types. The main motivation is to exploit the verification tools and theories developed for mCRL2 in Rebeca. The mapping is applied to several case-studies including the tree identify phase of the IEEE 1394 standard. The results of the experiment show that the minimization tools of mCRL2 can be very effective and the outcome of the present translation outperforms that of the translation to the input language of the Spin model-checker.
Blind multiuser vector channel estimation for space-time diffused signals
Authors: J. S. Lee
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

A near-far resistant channel estimation technique is proposed for DS-CDMA signals transmitted over a multiuser frequency-selective fading channel. The spatially and temporally diffuse rays for a particular user are considered to arrive in clusters, separated in time and/or space. The proposed technique estimates the DOA mean and variance, and the time delay offset and decay factor for each cluster. The technique is shown to effectively resolve sources even where they are closely located in time and space. Furthermore, unlike many DS-CDMA channel estimators, the technique also performs well in the presence of co-code interferers.
Oversampled FIR filter banks and frames in l/sup 2/(Z)
Authors: M. Vetterli
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03 (1996)

Perfect reconstruction FIR filter banks are equivalent to a particular class of frames in l/sup 2/(Z). These frames are the subject of this paper. Necessary and sufficient conditions on a filter bank to implement a frame or a tight frame decomposition are given, as well as the necessary and sufficient condition for perfect reconstruction using FIR filters. Complete parameterizations of FIR filter banks satisfying these conditions are also given. Further, we study the condition under which the frame dual to the frame associated to an FIR filter bank is also FIR, and give a parameterization of a class of filter banks having this property.
Algorithmic embeddings
Authors: Piotr Indyk
Venue:  (2006)

We present several computationally efficient algorithms, and complexity results on low distortion mappings between metric spaces. An embedding between two metric spaces is a mapping between the two metric spaces and the distortion of the embedding is the factor by which the distances change. We have pioneered theoretical work on relative (or approximation) version of this problem. In this setting, the question is the following: for the class of metrics C, and a host metric M', what is the smallest approximation factor a &ge; 1 of an efficient algorithm minimizing the distortion of an embedding of a given input metric M &isin; C into M'? This formulation enables the algorithm to adapt to a given input metric. In particular, if the host metric is "expressive enough" to accurately model the input distances, the minimum achievable distortion is low, and the algorithm will produce an embedding with low distortion as well. This problem has been a subject of extensive applied research during the last few decades. However, almost all known algorithms for this problem are heuristic. As such, they can get stuck in local minima, and do not provide any global guarantees on solution quality. We investigate several variants of the above problem, varying different host and target metrics, and definitions of distortion. We present results for different types of distortion: multiplicative versus additive, worst-case versus average-case and several types of target metrics, such as the line, the plane, d-dimensional Euclidean space, ultrametrics, and trees. We also present algorithms for ordinal embeddings and embedding with extra information. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)