ppxscal/embedding_network huggingface dataset:
Pointer Analysis for Source-to-Source Transformations
Authors: Marcio Buss, Stephen A. Edwards, Bin Yao, Daniel Waddington
Venue: Proceedings of the Fifth IEEE International Workshop on Source Code Analysis and Manipulation (2005)

We present a pointer analysis algorithm designed for source-to-source transformations. Existing techniques for pointer analysis apply a collection of inference rules to a dismantled intermediate form of the source program, making them difficult to apply to source-to-source tools that generally work on abstract syntax trees to preserve details of the source program. Our pointer analysis algorithm operates directly on the abstract syntax tree of a C program and uses a form of standard dataflow analysis to compute the desired points-to information. We have implemented our algorithm in a sourceto- source translation framework and experimental results show that it is practical on real-world examples.
Cooking navi: assistant for daily cooking in kitchen
Authors: Reiko Hamada, Jun Okabe, Ichiro Ide, Shin'ichi Satoh, Shuichi Sakai, Hidehiko Tanaka
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

We are developing a cooking navigation system, which helps even a novice user to cook several recipes in parallel without failure, while improving an advanced user's skill further. To realize this, the system optimizes the cooking procedure considering the following restrictions: (1) Duration of cooking, (2) Accuracy of cooking, and (3) Learning effect, by providing appropriate instructions to user's at the right timing, making full use of multimedia information. The users should be able to cook perfectly and comfortably just by following the text, video and audio provided by the system. According to the result of a preliminary experiment, all users from novice to experienced cooks could finish two dishes in parallel while enjoyeing the cooking very much. The result of a questionnaire shows the effectiveness of the multimedia navigation that we propose.
Metastability in Asynchronous Wait-Free Protocols
Authors: Stephen E. Paynter, Neil Henderson, James M. Armstrong
Venue: IEEE Transactions on Computers (2006)

We demonstrate that the safe register abstraction is an inappropriate model of a shared bit variable in an ACM. This is due to the phenomenon of metastability and the way that circuits are engineered to reduce the probability of it propagating. We give a bit model that takes the engineered restrictions into account and which is therefore stronger than the safe bit model. With our bit model we show that some impossibility results concerning ACMs which are based on safe bit models are pessimistic. We establish this using the CSP process algebra and the FDR2 model-checker, by investigating the impact of various models of shared bits on different wait-free protocols, including Lamport's regular register, Simpson's 4-slot ACM, Kirousis et al.'s ACM, Tromp's Atomic Bit and 4-Track ACMs, and Haldar and Subramanian's ACM. We show how these protocols can fail in the presence of rereadable metastability.
Self-monitoring of thread interactions for improved resource management in multithreaded systems
Authors: Tong Li
Venue:  (2005)

Hardware-level multithreaded systems provide infrastructure capable of executing multiple software threads in parallel. Such systems range from conventional multiprocessors to the recent simultaneous multithreading (SMT) and chip-multiprocessor (CMP) systems. To ensure that application programs receive high &ldquo;quality-of-service&rdquo; (e.g., high throughput, low response time), it is important for multithreaded systems to manage their hardware resources efficiently. Existing resource management solutions in operating systems and hardware are far from optimal. The major obstacle they face is the lack of accurate knowledge in the OS and hardware about application runtime behavior. For example, existing processors try their best to maximize metric values (e.g., instructions-per-cycle) meaningful to them, which, however, often do not correlate with metrics in which the applications are interested (e.g., transactions-per-second for a database application). Such lack of knowledge about application behavior often leads to inefficient resource usage in multithreaded systems. In this thesis, we develop mechanisms that enable multithreaded systems to self-monitor application runtime behavior. To support efficient management of processor resources (e.g., functional units), we study monitoring of thread microexecutions and their correlations with application-level performance metrics. To support efficient management of system resources (e.g., entire processors), we study monitoring of thread interactions. We focus on monitoring thread synchronization behaviors, which reflect application performance, and thread deadlocks, which reveal errors in applications. We make three contributions in this thesis. First, we develop a directed acyclic graph (DAG) model for quantifying the criticality of instructions on shared memory multithreaded systems. Second, we design a hardware mechanism that dynamically detects spinning synchronizations in multithreaded programs. Based on this design, we develop (1) hardware performance counters that more accurately reflect application performance than existing counters, (2) thread scheduling and power control policies that more efficiently manage resources than existing policies, and (3) OS and hardware support for detecting application livelocks. The third contribution of this thesis is an operating system mechanism, called Pulse, which can dynamically detect deadlocks in user applications. By using OS-level speculative execution, Pulse can detect deadlocks involving consumable resources, such as synchronization semaphores and pipes, which, to the best of our knowledge, no existing tools can detect.
Discriminative methods for label sequence learning
Authors: Thomas Hofmann
Venue:  (2005)

Discriminative learning framework is one of the very successful fields of machine learning. The methods of this paradigm, such as Boosting and Support Vector Machines, have significantly advanced the state-of-the-art for classification by improving the accuracy and by increasing the applicability of machine learning methods. One of the key benefits of these methods is their ability to learn efficiently in high dimensional feature spaces, either by the use of implicit data representations via kernels or by explicit feature induction. However, traditionally these methods do not exploit dependencies between class labels where more than one label is predicted. Many real-world classification problems involve sequential, temporal or structural dependencies between multiple labels. The goal of this research is to generalize discriminative learning methods for such scenarios. In particular, we focus on label sequence learning. Label sequence learning is the problem of inferring a state sequence from an observation sequence, where the state sequence may encode a labeling, an annotation or a segmentation of the sequence. Prominent examples include part-of-speech tagging, named entity classification, information extraction, continuous speech recognition, and secondary protein structure prediction. In this thesis, we present three novel discriminative methods that are generalizations of AdaBoost and multiclass Support Vector Machines (SVM) and a Gaussian Process formulation for label sequence learning. These techniques combine the efficiency of dynamic programming methods with the advantages of the state-of-the-art learning methods. We present theoretical analysis and experimental evaluations on pitch accent prediction, named entity recognition and part-of-speech tagging which demonstrate the advantages over classical approaches like Hidden Markov Models as well as the state-of-the-art methods like Conditional Random Fields.
A Scalable Collaborative Filtering Framework Based on Co-Clustering
Authors: Thomas George, Srujana Merugu
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

Collaborative filtering-based recommender systems have become extremely popular in recent years due to the increase in web-based activities such as e-commerce and online content distribution. Current collaborative filtering (CF) techniques such as correlation and SVD based methods provide good accuracy, but are computationally expensive and can be deployed only in static off-line settings. However, a number of practical scenarios require dynamic real-time collaborative filtering that can allow new users, items and ratings to enter the system at a rapid rate. In this paper, we consider a novel CF approach based on a recently proposed weighted co-clustering algorithm [1] that involves simultaneous clustering of users and items. We design incremental and parallel versions of the co-clustering algorithm and use it to build an efficient real-time CF framework. Empirical evaluation demonstrates that our approach provides an accuracy comparable to that of the correlation and matrix factorization based approaches at a much lower computational cost.
Mobility Patterns in Microcellular Wireless Networks
Authors: Suttipong Thajchayapong, Jon M. Peha
Venue: IEEE Transactions on Mobile Computing (2006)

This study investigates mobility patterns in microcellular wireless networks, based on measurements from the 802.11-based system that blankets the Carnegie Mellon University campus. We characterize the distribution of dwell time, which is the length of time that a mobile device remains in a cell until the next handoff, and sign-on interarrival time, which is the length of time between successive sign-ons from the same mobile device. Many researchers have assumed that these distributions are exponential, but our results based on empirical analysis show that dwell time and sign-on interarrival time can be accurately described using heavy-tailed arithmetic distributions that have infinite mean and variance. We also show that the number of handoffs per sign-on can be modeled accurately with a heavy-tailed distribution.
Concepts for advanced computer assisted models
Authors: Tuncer I. Oren
Venue: ACM SIGSIM Simulation Digest (1977)

Computers can provide valuable assistance in the process of modelling itself, as well as in the usability, acceptability, and referability of models.
The SQUASH 1000 Tangible User Interface System
Authors: Mark Fiala
Venue: Proceedings of the 4th IEEE/ACM International Symposium on Mixed and Augmented Reality (2005)

A hand-held object whose pose can be determined automatically is useful for Augmented Reality (AR) and other applications needing human-computer interaction. Some existing such input devices use active (ex. LED lighting) or passive markers to be recognized in a video image by computer vision. Markers are typically mounted onto flat objects which are not ergonomic, or can only have limited number of sides due to the small library and inter-marker confusion rate of the marker system used. A system is presented based on the ARTag fiducial marker system where objects of arbitrary shape can be covered with many small markers, the pose of the object is recovered automatically and can be used as an input device. Other tangible user interface systems require specialized hardware, whereas this approach needs only a printer, a video camera or webcam, and a large garden vegetable. The utility of this system both for measuring pose and for 3D modeling is shown.
Efficient Use of Invisible Registers in Thumb Code
Authors: Arvind Krishnaswamy, Rajiv Gupta
Venue: Proceedings of the 38th annual IEEE/ACM International Symposium on Microarchitecture (2005)

The ARM processor is a dual width ISA processor that provides a 16-bit Thumb instruction set in addition to the 32-bit ARM instruction set. The compromises made in designing the Thumb instruction set leads to significantly increased instruction counts. This increase is in part due to the fact that only half of the register file is visible to most instructions in Thumb code. In this paper we address this inefficiency by providing a new instruction, the SetMask instruction, using which the compiler can change the visible subset of registers at any program point. Thus, through the use of this instruction the compiler can make use of all registers in all instructions. We present compiler techniques for allocating invisible registers and introducing SetMask instructions in a manner that the number of introduced instructions is minimized so that the increase in code size is insignificant. We implement this new instruction using the Dynamic Instruction Coalescing Framework which enables the SetMask instruction to have zero execution time cost. Our techniques eliminated 11.7% of MOV instructions from Thumb code while causing negligible code size increase.
Anonymous DoS-Resistant Access Control Protocol Using Passwords for Wireless Networks
Authors: Zhiguo Wan, Akkihebbal L. Ananda, Robert H. Deng, Feng Bao
Venue: Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary (2005)

Wireless networks have gained overwhelming popularity over their wired counterpart due to their great flexibility and convenience, but access control of wireless networks has been a serious problem because of the open medium. Passwords remain the most popular way for access control as well as authentication and key exchange. But existing password-based access control protocols are not satisfactory in that they do not provide DoS-resistance or anonymity. In this paper we analyze the weaknesses of an access control protocol using passwords for wireless networks in IEEE LCN 2001, and propose a different access control protocol using passwords for wireless networks. Our new protocol avoids the weaknesses of the previous protocol, and the client can anonymously authenticate himself to the server with a human-memorable password, while the server is free of DoS attacks. We also present detailed security and performance analysis for our protocols, and show that our protocol is both secure and efficient for access control in wireless networks.
The Stoker Problem for Multidimensional Discrete Phase Control Systems
Authors: N. V. Utina, A. I. Shepelyavyi
Venue: Automation and Remote Control (2005)

Upper and lower estimates for the number of cycle slippings in the transition processes in multidimensional discrete phase control systems under external action are derived by the Lyapunov function method with the frequency theorem and a modified method of nonlocal reduction of discrete systems. The effectiveness of analytical results is illustrated with an example on the transition processes in a pulse phase-locked system with proportionally integrating filter and standard phase detector characteristics.
A requirements monitoring framework for enterprise systems
Authors: N. Robinson
Venue: Requirements Engineering (2005)

Requirements compliant software is becoming a necessity. Fewer and fewer organizations will run their critical transactions on software that has no visible relationship to its requirements. Businesses wish to see their software being consistent with their policies. Moreover, partnership agreements are pressuring less mature organizations to improve their systems. Businesses that rely on web services, for example, are vulnerable to the problems of their web service providers. While electronic commerce has increased the speed of on-line transactions, the technology for monitoring requirements compliance&#x2014;especially for transactions&#x2014;has lagged behind. To address the requirements monitoring problem for enterprise information systems, we integrate techniques for requirements analysis and software execution monitoring. Our framework assists analysts in the development of requirements monitors for enterprise services. The deployed system raises alerts when services succeed or fail to satisfy their specified requirements, thereby making software requirements visible. The framework usage is demonstrated with an analysis of ebXML marketplace specifications. An analyst applies goal analysis to discover potential service obstacles, and then derives requirements monitors and a distributed monitoring system. Once deployed, the monitoring system provides alerts when obstacles occur. A summary of the framework implementation is presented, along with analysis of two monitor component implementations. We conclude that the approach implemented in the framework, called ReqMon, provides real-time feedback on requirements satisfaction, and thereby provides visibility into requirements compliance of enterprise information systems.
A Remote User Authentication Scheme Using Strong Graphical Passwords
Authors: Wei-Chi Ku, Maw-Jinn Tsaur
Venue: Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary (2005)

Conventional remote user strong-password authentication schemes have the common drawback that the user has to memorize a hard-to-remember textual password, and therefore their applications are restricted. To solve this problem, we propose a remote user authentication scheme using strong graphical passwords in this paper. As graphical passwords are easy to remember for the user and conventionally dictionary attacks on graphical passwords are infeasible, the practicability of the proposed scheme is improved. Next, we show that the proposed scheme can withstand the replay attack, the password- file compromise attack, the denial-of-service attack, the predictable n attack, and the insider attack. In particular, the proposed scheme is easily reparable.
A Novel Architecture Using the Decorrelating Transform for Low Power Adaptive Filters
Authors: Mark P. Tennant, Ahmet T. Erdogan, Tughrul Arslan, John Thompson
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

This paper presents a novel architecture using the decorrelating (DECOR) transformation technique when applied to an LMS adaptive filter. The DECOR transform has been evaluated previously, however no practical evaluation has previously ever been made of how area and power performance is affected by the addition of the DECOR transform to an LMS adaptive filter. Neither has analysis been carried out to determine any tradeoff in increased area this might incur against power saved. This paper presents the first complete architectural VLSI implementation of the decorrelating transform when applied to an adaptive filter and includes a performance study in terms of area and power.
The Nature of the Cyber Firm: Contextual Model of Business for Cyber World
Authors: Ravindra Dastikop
Venue: Proceedings of the 2005 International Conference on Cyberworlds (2005)

In this paper we present a new business model, called contextual model of business and use it to provide a foundation to create a new category of enterprise. This model creates business value by converting the disparate data stream into meaningful context and serves its contextual customers. Our contribution is the idea of a contexting enterprise supplying the entire knowledge market in a planned and organized fashion where as currently information providers are considering themselves as producers of individual information products and each is trying to appeal to all the potential customers.
Word-oriented approximate string matching using occurrence heuristic tables: A heuristic for searching Arabic text: Research Articles
Authors: Suleiman H. Mustafa
Venue: Journal of the American Society for Information Science and Technology (2005)

In this article, a word-oriented approximate string matching approach for searching Arabic text is presented. The distance between a pair of words is determined on the basis of aligning the two words by using occurrence heuristic tables. Two words are considered related if they have the same morphological or lexical basis. The heuristic reports an approximate match if common letters agree in order and noncommon letters represent valid affixes. The heuristic was tested by using four different alignment strategies: forward, backward, combined forward&ndash;backward, and combined backward&ndash; forward. Using the error rate and missing rate as performance indicators, the approach was successful in providing more than 80&percnt; correct matches. Within the conditions of the experiments performed, the results indicated that the combined forward&ndash;backward strategy seemed to exhibit the best performance. Most of the errors were caused by multiple-letter occurrences and by the presence of weak letters in cases in which the shared core consisted of one or two letters. &copy; 2005 Wiley Periodicals, Inc.
The collective: a common information service for self-managed middleware
Authors: Edward Curry, Enda Ridge
Venue: Proceedings of the 4th workshop on Reflective and adaptive middleware systems (2005)

As the deployment of self-managed reflective middleware platforms increases, the process of collecting and examining information used within the reflective process becomes ever more complex. The quality of such information is vital to ensure the successful outcome of the self-management process. However, the cost associated with the collection of this information plays a major role in influencing the success of a self-managed system.Within typical deployment environments it is not uncommon for multiple self-managed systems to be deployed, each collecting information for use within their respective reflective computations. In many cases, these systems will collect the same information, replicating the effort required to retrieve the information. Such replication could be avoided by sharing information between systems to reduce the overall cost of collection within the deployment environments.Current self-managed systems lack adequate support for information collection and sharing. This work proposes the use of an independent information service to assist in the collection and management of information within self-managed middleware systems.
Mining Quantitative Frequent Itemsets Using Adaptive Density-Based Subspace Clustering
Authors: Takashi Washio, Yuki Mitsunaga, Hiroshi Motoda
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

A novel approach to subspace clustering is proposed to exhaustively and efficiently mine quantitative frequent itemsets (QFIs) from massive transaction data¹. For the computational tractability, our approach introduces adaptive density-based and Apriori-like algorithm. Its outstanding performance is shown through numerical experiments.