ppxscal/embedding_network huggingface dataset:
Exploring the neighborhood with dora to expedite software maintenance
Authors: Emily Hill, Lori Pollock, K. Vijay-Shanker
Venue: Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering (2007)

Completing software maintenance and evolution tasks for todayâs large, complex software systems can be difficult, often requiring considerable time to understand the system well enough to make correct changes. Despite evidence that successful programmers use program structure as well as identifier names to explore software, most existing program exploration techniques use either structural or lexical identifier information. By using only one type of information, automated tools ignore valuable clues about a developer's intentions - clues critical to the human program comprehension process. In this paper, we present and evaluate a technique that exploits both program structure and lexical information to help programmers more effectively explore programs. Our approach uses structural information to focus automated program exploration and lexical information to prune irrelevant structure edges from consideration. For the important program exploration step of expanding from a seed, our experimental results demonstrate that an integrated lexical-and structural-based approach is significantly more effective than a state-of-the-art structural program exploration technique
Time series clustering and classification by the autoregressive metric
Authors: Marcella Corduas, Domenico Piccolo
Venue: Computational Statistics Data Analysis (2008)

The statistical properties of the autoregressive (AR) distance between ARIMA processes are investigated. In particular, the asymptotic distribution of the squared AR distance and an approximation which is computationally efficient are derived. Moreover, the problem of time series clustering and classification is discussed and the performance of the AR distance is illustrated by means of some empirical applications.
Mobile-Agent-Based Information-Driven Multiresolution Algorithm for target tracking in Wireless Sensor Networks
Authors: Hu Haifeng, Yang Zhen
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

in this paper, Mobile-Agent-based Information-Driven Multiresolution Algorithm (MAIDM) is presented for Target Tracking in Wireless Sensor Networks (WSN), in order to provide better accuracy and degree of fault tolerance while meeting the energy requirement. In a clustered-based wireless sensor networks, mobile agent is used to process data of nodes with multiresolution algorithm according to information contribution of different nodes , and the size of mobile agent is determined by the maximum value of the information contribution along the path of mobile agent. A balance has to be struck between the energy efficiency object and fault tolerance/accuracy object. Simulation results show that MAIDM performs better than IDSQ from perspectives of fault tolerance and accuracy, MAIDM "s energy-efficient performance is better than MA-CSIP.
Fuzzy load balancing in an industrial distributed system for job scheduling
Authors: Adnan Shaout, Patrick McAuliffe
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2000)

The paper presents a batch job scheduler for a distributed system which utilizes a fuzzy logic algorithm to balance the load on individual processors maximizing throughput of the overall system. The fuzzy load balancing algorithm has been implemented in a production processing environment rather than in simulation only. This paper demonstrates the power and simplicity of incorporating a fuzzy load balancing algorithm into a batch job scheduler which has produced excellent performance and reliability characteristics.
Testing for High Reliability: A Case Study
Authors: J. C. McDonald
Venue: Computer (1976)

Commercial grade plastic TTL is highly reliable if appropriate testing and screening is accomplished before delivery for operational service. This paper presents a case study, in a telephone company environment, which examines component selection from system design to field results. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Challenges and experience in prototyping a multi-modal stream analytic and monitoring application on System S
Authors: Kun-Lung Wu, Kirsten W. Hildrum, Wei Fan, Philip S. Yu, Charu C. Aggarwal, David A. George, Buǧra Gedik, Eric Bouillet, Xiaohui Gu, Gang Luo, Haixun Wang
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

In this paper, we describe the challenges of prototyping a reference application on System S, a distributed stream processing middleware under development at IBM Research. With a large number of stream PEs (Processing Elements) implementing various stream analytic algorithms, running on a large-scale, distributed cluster of nodes, and collaboratively digesting several multi-modal source streams with vastly differing rates, prototyping a reference application on System S faces many challenges. Specifically, we focus on our experience in prototyping DAC (Disaster Assistance Claim monitoring), a reference application dealing with multi-modal stream analytic and monitoring. We describe three critical challenges: (1) How do we generate correlated, multi-modal source streams for DAC? (2) How do we design and implement a comprehensive stream application, like DAC, from many divergent stream analytic PEs? (3) How do we deploy DAC in light of source streams with extremely different rates? We report our experience in addressing these challenges, including modeling a disaster claim processing center to generate correlated source streams, constructing the PE flow graph, utilizing programming supports from System S, adopting parallelism, and exploiting resource-adaptive computation.
Proactive displays: Supporting awareness in fluid social environments
Authors: David W. McDonald, Joseph F. McCarthy, Suzanne Soroczak, David H. Nguyen, Al M. Rashid
Venue: ACM Transactions on Computer-Human Interaction (TOCHI) (2008)

Academic conferences provide a social space for people to present their work and interact with one another. However, opportunities for interaction are unevenly distributed among the attendees. We seek to extend the opportunities for interaction among attendees by using technology to enable them to reveal information about their background and interests in different settings. We evaluate a suite of applications that augment three physical social spaces at an academic conference. The applications were designed to augment formal conference paper sessions and informal breaks. A mixture of qualitative observation and survey response data are used to frame the impacts from both individual and group perspectives. Respondents reported on their interactions and serendipitous findings of shared interests with other attendees. However, some respondents also identify distracting aspects of the augmentation. Our discussion relates these results to existing theory of group behavior in public places and how these social space augmentations relate to awareness as well as the problem of shared interaction models.
Partial permanence and extinction in an N-species nonautonomous Lotka-Volterra competitive system
Authors: Jinxian Li, Jurang Yan
Venue: Computers Mathematics with Applications (2008)

In this paper, we first consider a general N-species nonautonomous Lotka-Volterra system. We show that certain average conditions involving the respective averages of the growth rates and the interaction coefficients imply the total persistence of all species. Using this result, we then give computable conditions on the coefficients which imply the ultimate extinction of certain species in a N-dimensional Lotka-Volterra system.
An IA-Based Classification Rule Mining Algorithm
Authors: Ziqiang Wang, Qingzhou Zhang, Dexian Zhang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

This paper describes a novel immune algorithm(IA) for data mining, the goal of the novel algorithm is to extract classification rules from data in database. This algorithm is inspired by the theory of immunity in biology which mainly constructs an immune operator accomplished by two steps: 1) a vaccination and 2) an immune selection. Experimental results demonstrate the effectiveness of immune algorithm on three UCI benchmark data sets.
Rough Set Model Selection for Practical Decision Making
Authors: Joseph P. Herbert, JingTao Yao
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

One of the challenges a decision maker faces is choos- ing a suitable rough set model to use for data analysis. The traditional algebraic rough set model classifies objects into three regions, namely, the positive, negative, and bound- ary regions. Two different probabilistic models, variable- precision and decision-theoretic, modify these regions via l,u user-defined thresholds and , values from loss func- tions respectively. A decision maker whom uses these mod- els must know what type of decisions can be made within these regions. This will allow him or her to conclude which model is best for their decision needs. We present an out- line that can be used to select a model and better analyze the consequences and outcomes of those decisions.
Mining semantic distance between corpus terms
Authors: Ahmad El Sayed, Hakim Hacid, Djamel Zighed
Venue: Proceedings of the ACM first Ph.D. workshop in CIKM (2007)

In this paper, we face two problems in classical semantic similarity measures. Firstly, the context-dependency problem in knowledge-base measures since no one takes into account the context of the target domain. That is, a multisource context-dependent approach is presented. Secondly, the coverage problem with these measures since similarities can only be calculated between concepts included in a taxonomy. Moreover, "pure" corpus-based measures are still way from achieving performance reached by knowledge based measures. We present a more complex corpus-based approach using a taxonomy and data mining techniques in order to compute semantic distances between terms uncovered by the taxonomy. Experiments made show clearly the effectiveness of both proposed approaches.
A Multi-Drop Transmission-Line Interconnect in Si LSI
Authors: Junki Seita, Hiroyuki Ito, Kenichi Okada, Takashi Sato, Kazuya Masu
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

This paper proposes a branching method for on-chip transmission line (TL) interconnects, which can reduce delay and power of global interconnects. A 6-mm-long TL interconnect with a branch is fabricated by using a 0.18¿m standard Si CMOS process, and the measurement result performs 4 Gbps signal transmission.
Fault Diagnosis in Integrated Circuits with BIST
Authors: Raimund Ubar, Sergei Kostin, Jaan Raik, Teet Evartson, Harri Lensen
Venue: Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools (2007)

This paper presents an optimized fault diagnosing procedure applicable in Built-in Self-Test environments. Instead of the known approach based on a simple bisection of patterns in pseudorandom test sequences, we propose a novel bisection procedure where the diagnostic weight of test patterns is taken into account. Another novelty is the sequential nature of the procedure which allows pruning the search space. Opposite to the classical approach which targets all failing patterns, in the proposed method not all failing patterns are needed to be fixed for diagnosis. This allows to tradeoff the speed of diagnosis with diagnostic resolution. The proposed method is compared with three known fault diagnosis methods: classical Binary Search, Doubling and Jumping. Experimental results demonstrate the advantages of the proposed method compared to the previous ones.
Explaining clinical decisions by extracting regularity patterns
Authors: Concha Bielza, Juan A. Fernández del Pozo, Peter J. F. Lucas
Venue: Decision Support Systems (2008)

When solving clinical decision-making problems with modern graphical decision-theoretic models such as influence diagrams, we obtain decision tables with optimal decision alternatives describing the best course of action for a given patient or group of patients. For real-life clinical problems, these tables are often extremely large. This is an obstacle to understand their content. KBM2L lists are structures that minimize memory storage requirements for these tables, and, at the same time, improve their knowledge organization. The resulting improved knowledge organization can be interpreted as explanations of the decision-table content. In this paper, we explore the use of KBM2L lists in analyzing and explaining optimal treatment selection in patients with non-Hodgkin lymphoma of the stomach using an expert-designed influence diagram as an experimental vehicle. The selection of the appropriate treatment for non-Hodgkin lymphoma of the stomach is, as for many other types of cancer, difficult, mainly because of the uncertainties involved in the decision-making process. In this paper we look at an expert-designed clinical influence diagram as a representation of a body of clinical knowledge. This diagram can be analyzed and explained using KBM2L lists. It is shown that the resulting lists provide high-level explanations of optimal treatments for the disease. These explanations are useful for finding relationships between groups of variables and treatments. It is demonstrated that these lists can act as a basis for gaining a deeper understanding of the underlying clinical problem.
Improving computer security through environmental controls
Authors: Thomas C. Richards
Venue: ACM SIGSAC Review (1982)

The computer resides in an environment which has a critical impact on its continual operation and availability. This environment has several key control elements including, temperature and humidity controls, power supply controls, working space control, fire protection systems, and physical security systems. Most of these elements are impacted during machine installation which is usually a one-time process and consequently does not receive the attention given other control and security problems. Site design requires careful planning to insure an environment that will not adversely affect the computer center's reliability and security. The designer of a computer center should view the continuous operation of its services as paramount. The consequential loss through failure can very quickly run into large amounts of money and can be detrimental to the continued operation of a company in the worst scenario. Downtime can be costly resulting in lost production and lost business. The loss of essential services is often due to planning without regard to the above elements. "Downtime is a catastrophe. When that downtime is caused by a failure of the environment it is a needless catastrophe," writes James E. Hassett (6).
Coarse-grained optimization: techniques for rewriting SQL statement sequences
Authors: Tobias Kraft, Holger Schwarz, Ralf Rantzau, Bernhard Mitschang
Venue: Proceedings of the 29th international conference on Very large data bases - Volume 29 (2003)

Relational OLAP tools and other database applications generate sequences of SQL statements that are sent to the database server as result of a single information request provided by a user. Unfortunately, these sequences cannot be processed efficiently by current database systems because they typically optimize and process each statement in isolation. We propose a practical approach for this optimization problem, called "coarse-grained optimization," complementing the conventional query optimization phase. This new approach exploits the fact that statements of a sequence are correlated since they belong to the same information request. A lightweight heuristic optimizer modifies a given statement sequence using a small set of rewrite rules. Since the optimizer is part of a separate system layer, it is independent of but can be tuned to a specific underlying database system. We discuss implementation details and demonstrate that our approach leads to significant performance improvements.
Lifting the burden of history from adaptive query processing
Authors: Amol Deshpande, Joseph M. Hellerstein
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Adaptive query processing schemes attempt to re-optimize query plans during the course of query execution. A variety of techniques for adaptive query processing have been proposed, varying in the granularity at which they can make decisions [8]. The eddy [1] is the most aggressive of these techniques, with the flexibility to choose tuple-by-tuple how to order the application of operators. In this paper we identify and address a fundamental limitation of the original eddies proposal: the burden of history in routing. We observe that routing decisions have long-term effects on the state of operators in the query, and can severely constrain the ability of the eddy to adapt over time. We then propose a mechanism we call STAIRs that allows the query engine to manipulate the state stored inside the operators and undo the effects of past routing decisions. We demonstrate that eddies with STAIRs achieve both high adaptivity and good performance in the face of uncertainty, outperforming prior eddy proposals by orders of magnitude.
A Calculation Mechanism for Similarity Measure with Clustering an Unbalanced Hierarchical Terminology Structure
Authors: MinTzu Wang, PingYu Hsu, K. C. Lin, Jason Hung
Venue: Proceedings of the 2007 International Conference on Parallel Processing Workshops (2007)

The effective retrieval of reverent information often is quite useful to the user, for example, to query the respectful knowledge or information, especially for on-line e-leaner. The most common method is to make use of synonym and antonym from a dictionary with the most frequent terms. However, sometimes we are focusing on a pair of or a set of associated keywords offered by user, instead of same meaning. Generally, we would probably adopt the association rule to solve the problem. Nonetheless, the keywords or terms sets extracted from huge queries often contain sparse information composed of a wide range of keywords, with each term set only containing a few terms. These data render basket analysis with extremely low item support, lift the term to a higher level of concept hierarchy may get enough support, but missing the detailed information. Although a similarity measure represented by counting the depth of the least common ancestor normalized by the depth of the concept tree lifts the limitation of binary equality, it produces counter intuitive results when the concept hierarchy is unbalanced since two terms in deeper subtrees are very likely to have a higher similarity than two terms in shallower subtrees. The research proposes to calculate the distance between two terms by counting the edge traversal needed yet from user..s viewpoint to link them in order to solve the issues. The method is straight forward yet achieves better outcome with information query when concept hierarchy is unbalanced.
A Visual Text Mining approach for Systematic Reviews
Authors: Viviane Malheiros, Erika Hohn, Roberto Pinho, Manoel Mendonca, Jose Carlos Maldonado
Venue: Proceedings of the First International Symposium on Empirical Software Engineering and Measurement (2007)

The software engineering research community has been adopting systematic reviews as an unbiased and fair way to assess a research topic. Despite encouraging early results, a systematic review process can be time consuming and hard to conduct. Thus, tools that help on its planning or execution are needed. This article suggests the use of Visual Text Mining (VTM) to aid systematic reviews. A feasibility study was conducted comparing the proposed approach with a manual process. We observed that VTM can contribute to Systematic Review and we propose a new strategy called VTM-Based Systematic Review.
The ND2DB attack: database content extraction using timing attacks on the indexing algorithms
Authors: Ariel Futoransky Damián Saura Ariel Waissbein
Venue: Proceedings of the first USENIX workshop on Offensive Technologies (2007)

In this paper we present a new attack technique that allows extraction of selected database content relying merely on the attacker's ability to perform database transactions (INSERTs or UPDATEs) that are usually available to any anonymous database user. Our attack technique uses a side-channel timing attack in the realm of database indexing algorithms and data structures. We prove that by exploiting the inherent characteristics of the most commonly used indexing data structures and algorithms in today's commercial database management systems it is possible to extract privacy-sensitive data from a database. In particular we prove, both in theory and practice that it is feasible to do so if the B-tree data structure is used and the attacker is able to insert records with chosen data that is used as the search key of one of the table's indexes. We present experimental results of a successful attack implementation against MySQL and provide conclusions and ideas for further research.
Distributed monitoring of peer to peer systems
Authors: Serge Abiteboul, Bogdan Marinoiu
Venue: Proceedings of the 9th annual ACM international workshop on Web information and data management (2007)

In this paper, we are concerned with the distributed monitoring of P2P systems. We introduce the P2P Monitor system and a new declarative language, namely P2PML, for specifying monitoring tasks. A P2PML subscription is compiled into a distributed algebraic plan which is described using algebra over XML streams. The operators of this algebra are first alerters in charge of detecting specific events and acting as stream sources. Other operators process the streams or publish them. We introduce a filter for streams of XML documents that scales by processing first simple conditions and then, if still needed, evaluating complex queries. We also show how particular tasks can be supported by identifying subtasks that are already provided by existing streams.
On one-pass CPS transformations
Authors: Olivier Danvy, Kevin Millikin, Lasse R. Nielsen
Venue: Journal of Functional Programming (2007)

We bridge two distinct approaches to one-pass CPS transformations, i.e, CPS transformations that reduce administrative redexes at transformation time instead of in a post-processing phase. One approach is compositional and higher-order, and is independently due to Appel, Danvy and Filinski, and Wand, building on Plotkin's seminal work. The other is non-compositional and based on a reduction semantics for the lambda-calculus, and is due to Sabry and Felleisen. To relate the two approaches, we use three tools: Reynolds's defunctionalization and its left inverse, refunctionalization; a special case of fold–unfold fusion due to Ohori and Sasano, fixed-point promotion; and an implementation technique for reduction semantics due to Danvy and Nielsen, refocusing. This work is directly applicable to transforming programs into monadic normal form.
Requirements for Computerized Patient Monitoring Systems
Authors: E. Drazen, A. Wechsler, K. Wiig, A. D. Little
Venue: Computer (1975)

During the last decade, interest has increased in the use of computers in the delivery of health care services in the United States and Europe. One of the early applications of computers in clinical care was in intensive care units (ICU's) where computers were felt to be useful to nurses in monitoring the condition of these critically ill patients, and in alerting them to sudden changes in patient condition.