ppxscal/embedding_network huggingface dataset:
A Novel Method of Tongue Image Recognition
Authors: Wenshu Li, Jianglong Xu, Changle Zhou, Zhifeng Zhang
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

A novel LDA method for Tongue Images Recognition (TIR) based on a combination of global features extracted by nonlinear kernel principal component analysis and local features derived by applying Gabor wavelets is discussed. It is well known that the distribution of tongue images is highly nonlinear under a large variation in viewpoints. Therefore, linear methods such as Principle Component Analysis or Linear Discriminant Analysis cannot provide reliable and robust solutions for TIR problems. In our framework, the improved LDA in the unitary space makes use of the null space of the withinclass scatter matrix effectively, and Global feature vectors and local feature vectors are integrated by complex vectors as input feature of the improved LDA. The experiment results demonstrate that the proposed methodology is more effective and robust for tongue images recognition.
Specialization and extrapolation of software cost models
Authors: Tim Menzies, Dan Port, Zhihao Chen, Jairus Hihn
Venue: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering (2005)

Despite the widespread availability of software effort estimation models (e.g. COCOMO [2], Price-S [12], SEER-SEM [13], SLIM [14]), most managers still estimate new projects by extrapolating from old projects [3, 5, 7]. In this delta method, the cost of the next project is the cost of the last project multiplied by some factors modeling the difference between old and new projects [2].Delta estimation is simple, fast, and best of all, can take full advantage of local costing information. However delta estimation fails when the experience base (the old projects) can not be extrapolated to the new projects. Previously [10], we have shown that for a set of NASA projects, delta estimation would usually fail since most of the features and coefficients of the learned model vary wildly across sub-samples of the training data. In that prior work, no solution was offered for this problem.Here, we offer a solution and report the results of experiment with feature subset selection (FSS) and extrapolation. FSS methods are usually assessed via the mean change in model performance. However, as shown below, FSS can significantly reduce the variance as well. Hence, FSS should be routinely used in cost estimation.Our results should stop the trend in the effort modeling community of continually adding to the number of features in a model in order to improve estimation performance. Here we show that there are benefits in intelligently subtracting model features.
A unified framework for resolving ambiguity in copy detection
Authors: Sujoy Roy, Ee-Chien Chang, K. Natarajan
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

Copy detection is an important component of digital rights management and can be implemented using a retrieval-based approach. Under this approach, a query image, suspected to be a copy, is compared against all the images in the owner database. The comparison is done based on a distance metric in feature space. The performance of such a system depends on the mutual separation of the feature representation of the images in the database. In this paper we propose a framework that increases this mutual separation by literally shifting them away from each other. The idea of modifying the features derives its inspiration from the field of watermarking. It is also important to make sure that the semantics of the images do not change after modification. Thus the focus of this paper is on how to modify the images in the database, so that the mutual separation between the images in feature space is above a certain threshold and the distortion induced is minimized. This problem can be formulated as a non-convex optimization problem which is difficult to solve. We propose a restriction of the problem and solve it using second-order cone programming. We present a practical implementation of our framework, named RAM, which uses AFMT as the feature representation. We conduct experiments to test the performance of RAM.
A new construction for skew multivariate distributions
Authors: Dipak K. Dey, Junfeng Liu
Venue: Journal of Multivariate Analysis (2005)

This paper considers a new approach to develop a very general class of skew multivariate distributions. The approach is based on a linear combination of an elliptically distributed random variable with a linear constraint. Using this approach two different classes of multivariate distributions are constructed based on original distribution. These new classes include different types of skew normal (type A and type B) and other skew elliptical distributions, exist in the literature. We also derive the moment generating function, marginal and conditional density of our proposed classes of distributions. Straightforward explanations are applied to demonstrate the relationships among previous approaches by others with our proposed class of skew distributions.
The limits of global scanning worm detectors in the presence of background noise
Authors: David W. Richardson, Steven D. Gribble, Edward D. Lazowska
Venue: Proceedings of the 2005 ACM workshop on Rapid malcode (2005)

Internet worms cause billions of dollars in damage each year. To combat them, researchers have been exploring global worm detection systems to spot a new random scanning worm outbreak quickly. These systems passively listen for worm probes on unused IP addresses, looking for anomalous increases in probe traffic to distinguish the emergence of a new worm from background Internet noise.In this paper, we use analytic modeling, simulation, and measurement to understand how background noise impacts the detection ability of global scanning worm detectors. We investigate the relationship between the average background noise level, the number of IP addresses monitored, and the detection latency for two classes of global scanning worm detectors: scan packet-based and victims-based schemes. Our results show how worm detection latency degrades as a function of the background noise level. To compensate, global scanning worm detectors can increase the number of IP addresses that they monitor. However, given the growth trend of background noise levels, the number of IP addresses which must be monitored may quickly become unreasonable. Because of this, we conclude that global scanning worm detection schemes are unlikely to be competitive with local scanning and signature-based worm detection schemes.
Separating Abstractions from Resources in a Tactical Storage System
Authors: Douglas Thain, Sander Klous, Justin Wozniak, Paul Brenner, Aaron Striegel, Jesus Izaguirre
Venue: Proceedings of the 2005 ACM/IEEE conference on Supercomputing (2005)

Sharing data and storage space in a distributed system remains a difficult task for ordinary users, who are constrained to the fixed abstractions and resources provided by administrators. To remedy this situation, we introduce the concept of a tactical storage system (TSS) that separates storage abstractions from storage resources, leaving users free to create, reconfigure, and destroy abstractions as their needs change. In this paper, we describe how a TSS can provide a variety of filesystem and database abstractions for unmodified applications without requiring special privileges or kernel changes. A TSS provides performance competitive with NFS for single clients and also scales well for multiple servers and multiple clients. A prototype TSS of 120 disks and 6 TB of storage has been deployed at the University of Notre Dame and used for applications in high energy physics and bioinformatics.
Digital violin tutor: an integrated system for beginning violin learners
Authors: Jun Yin, Ye Wang, David Hsu
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

Prompt feedback is essential for beginning violin learners; however, most amateur learners can only meet with teachers and receive feedback once or twice a week. To help such learners, we have attempted an initial design of Digital Violin Tutor (DVT), an integrated system that provides the much-needed feedback when human teachers are not available. DVT combines violin audio transcription with visualization. Our transcription method is fast, accurate, and robust again noise for violin audio recorded in home environments. The visualization is designed to be intuitive and easily understandable by people with little music knowledge. The different visualization modalities--video, 2D fingerboard animation, 3D avatar animation--help learners to practice and learn more effectively. The entire system has been implemented with off-the-shelf hardware and shown to be practical in home environments. In our user study, the system has received very positive evaluation.
Lifeblog: A New Concept in Mobile Learning?
Authors: Elizabeth Hartnell Young, Frank Vetere
Venue: Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education (2005)

In this paper we report early findings from a sample of Australian participants using Nokia's Lifeblog software on mobile phones to record aspects of living and learning in both formal and informal settings. We take the view that learning is the process people engage in when they are making meaning and constructing knowledge. The Lifeblog software affords new opportunities to capture, manipulate and communicate daily events and thoughts that assist in making meaning in individual and collective contexts. We aim to link this with the emerging phenomena of digital storytelling and ePortfolios, which are both examples of learners actively creating digital material for an audience, rather than passively receiving information. Findings to date indicate that the creative capacity of the mobile phones is not frequently encouraged in formal educational settings.
A Hierarchical Parallel Placement Technique based on Genetic Algorithm
Authors: Masaya Yoshikawa, Hidekazu Terai
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

Deep-Sub-Micron technology (DSM) of 0.18 micron and below enable the integration of logical circuits having more than 10 million gates. In such a DSM technology, layout design has become the dominant design phase. This paper discusses a novel performancedriven placement technique. The proposed algorithm based on Genetic Algorithms (GA) has a two-level hierarchical structure. For selection control, new objective functions are introduced for improving chip area, interconnect delay and power consumption. In order to reduce run time, the two kind of parallel processing suitable for hierarchical processing is introduced. Experimental results show improvement comparison with commercial EDA tool.
Exploring the cache design space for large scale CMPs
Authors: Lisa Hsu, Ravi Iyer, Srihari Makineni, Steve Reinhardt, Donald Newell
Venue: ACM SIGARCH Computer Architecture News (2005)

With the advent of dual-core chips in the marketplace, small-scale CMP (chip multiprocessor) architectures are becoming commonplace. We expect a continuing trend of increasing the number of cores on a die to maximize the performance/power efficiency of a single chip. We believe an era of large-scale CMPs (LCMPs) with several tens to hundreds of cores is on the way, but as of now architects have little understanding of how best to build a cache hierarchy given such a large number of cores/threads to support. With this in mind, our initial goals are to prune the cache design space for LCMPs by characterizing basic server workload behavior in such an environment.In this paper, we describe the range of methodologies that we are developing to overcome the challenges of exploring the cache design space for LCMP platforms. We then focus on employing a trace-driven approach to characterizing one key server workload (OLTP) in both a homogeneous and a heterogeneous workload environment. We study the effect of increasing threads (from 1 to 128) on a three-level cache hierarchy with emphasis on second and third level caches. We study the effect of varying sizes at these cache levels and show the effects of threads contending for cache space, the effects of prefetching instruction addresses, and the effects of inclusion. We make initial observations and conclusions about the factors on which LCMP cache hierarchy design decisions should be based and discuss future work.
Modeling Security Requirements Through Ownership, Permission and Delegation
Authors: Paolo Giorgini, Fabio Massacci, John Mylopoulos, Nicola Zannone
Venue: Proceedings of the 13th IEEE International Conference on Requirements Engineering (2005)

Security Requirements Engineering is emerging as a branch of Software Engineering, spurred by the realization that security must be dealt with early on during the requirements phase. Methodologies in this ?eld are challenging, as they must take into account subtle notions such as trust (or lack thereof), delegation, and permission; they must also model entire organizations and not only systems-to-be. In our previous work we introduced Secure Tropos, a formal framework for modeling and analyzing security requirements. Secure Tropos is founded on three main notions: ownership, trust, and delegation. In this paper we re?ne Secure Tropos introducing the notions of at-least delegation and trust of execution; also, at-most delegation and trust of permission. We also propose monitoring as a security design pattern intended to overcome the problem of lack of trust between actors. The paper presents a semantics for these notions, and describes an implemented formal reasoning tool based on Datalog.
Differencing Worm Flows and Normal Flows for Automatic Generation of Worm Signatures
Authors: Kumar Simkhada, Hiroshi Tsunoda, Yuji Waizumi, Yoshiaki Nemoto
Venue: Proceedings of the Seventh IEEE International Symposium on Multimedia (2005)

Internet worms pose a serious threat to networks. Most current Intrusion Detection Systems (IDSs) take signature matching approach to detect worms. Given the fact that most signatures are developed manually, generating new signatures for each variant of a worm incurs significant overhead. In this paper, we propose a difference-based scheme which differences worm flows and normal flows to generate robust worm signatures. The proposed scheme is based on two observational facts - worm flows contain several invariant portions in their payloads, and core worm codes do not exist in normal flows. It uses samples of worm flows detected by available means to extract common tokens. It then differences the set of these tokens with those of normal flows and generates signature candidates. By using such signatures within enterprises, out of reach of worm writers, the possibility of being tricked by worm writers can be reduced. We evaluate the proposed scheme using real network traffic traces that contains worms. Experiment results show that the proposed scheme exhibits high detection rate with low false positives.
An analysis of rule coverage as a criterion in generating minimal test suites for grammar-based software
Authors: Mark Hennessy, James F. Power
Venue: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering (2005)

The term grammar-based software describes software whose input can be specified by a context-free grammar. This grammar may occur explicitly in the software, in the form of an input specification to a parser generator, or implicitly, in the form of a hand-written parser, or other input-verification routines. Grammar-based software includes not only programming language compilers, but also tools for program analysis, reverse engineering, software metrics and documentation generation. Such tools often play a crucial role in automated software development, and ensuring their completeness and correctness is a vital prerequisite for their us.In this paper we propose a strategy for the construction of test suites for grammar based software, and illustrate this strategy using the ISO CPP grammar. We use the concept of rule coverage as a pivot for the reduction of implementation-based and specification-based test suites, and demonstrate a significant decrease in the size of these suites. To demonstrate the validity of the approach, we use the reduced test suite to analyze three grammar-based tools for CPP++. We compare the effectiveness of the reduced test suite with the original suite in terms of code coverage and fault detection.
Visual Exploration of Malicious Network Objects Using Semantic Zoom, Interactive Encoding and Dynamic Queries
Authors: Gregory Conti, Julian Grizzard, Mustaque Ahamad, Henry Owen
Venue: Proceedings of the IEEE Workshops on Visualization for Computer Security (2005)

This paper explores the application of visualization techniques to aid in the analysis of malicious and non-malicious binary objects. These objects may include any logically distinct chunks of binary data such as image files, word processing documents and network packets. To facilitate this analysis, we present a novel visualization technique for comparing and navigating among 600-1000+ such objects at one time. While the visualization technique alone has powerful application for both directed and undirected exploration of many classes of binary objects, we chose to study network packets. To increase effectiveness, we strengthened the visualization technique with novel, domain-specific semantic zooming, interactive encoding and dynamic querying capabilities. We present results and lessons learned from implementing these techniques and from studying both malicious and non-malicious network packets. Our results indicate that the information visualization system we present is an efficient and effective way to compare large numbers of network packets, visually examine their payloads and navigate to areas of interest within large network datasets.
Functional test generation based on word-level SAT
Authors: Zhihong Zeng, Kesava R. Talupuru, Maciej Ciesielski
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2005)

Functional test generation coupled with symbolic simulation offers a good compromise between formal verification and numerical simulation for design validation. The generation of functional test vectors guided by miscellaneous coverage metrics can be posed as a satisfiability problem (SAT). While a number of efficient Boolean SAT engines have been developed for gate level designs, they are not directly applicable to behavioral and RTL designs containing significant arithmetic components. This paper presents two approaches that enhance the capability of functional test generation by preserving arithmetic operators in the design. They are based on word-level SAT techniques: (1) LPSAT, based on integer linear programming, and (2) CLP-SAT, based on constraint logic programming. The proposed SAT solvers allow to efficiently handle the designs with mixed word-level arithmetic operators and bit-level logic gates. The experimental results are quite encouraging compared to traditional CNF-based and BDD-based SAT solvers. The paper also suggests a method to build an integrated SAT solving framework where different SAT solvers work together to provide a more complete solution to functional test generation and other verification applications.
Compositing color with texture for multi-variate visualization
Authors: Haleh. H. Shenas, Victoria Interrante
Venue: Proceedings of the 3rd international conference on Computer graphics and interactive techniques in Australasia and South East Asia (2005)

Multivariate data visualization requires the development of effective techniques for simultaneously conveying multiple different data distributions over a common domain. Although it is easy to successfully use color to represent the value of a single variable at a given location, effectively using color to represent the values of multiple variables at the same point at the same time is a trickier business. In this paper, we provide a comprehensive overview of strategies for effectively combining color with texture to represent multiple values at a single spatial location, and present a new technique for automatically interweaving multiple colors through the structure of an acquired texture pattern.
Worm evolution tracking via timing analysis
Authors: Moheeb Abu Rajab, Fabian Monrose, Andreas Terzis
Venue: Proceedings of the 2005 ACM workshop on Rapid malcode (2005)

We present a technique to infer a worm's infection sequence from traffic traces collected at a network telescope. We analyze the fidelity of the infection evolution as inferred by our technique, and explore its effectiveness under varying constraints including the scanning rate of the worm, the size of the vulnerable population, and the size of the telescope itself. Moreover, we provide guidance regarding the point at which our method's accuracy diminishes beyond practical value. As we show empirically, this point is reached well after a few hundred initial infected hosts (possibly including "patient zero'') has been reliably identified with more than 80% accuracy. We generalize our mechanism by exploiting the change in the pattern of inter-arrival times exhibited during the early stages of such an outbreak to detect the presence and approximate size of the hit-list. Our mechanism is resilient to varying parameters like the worm scanning rate and the size of the vulnerable population, and can provide significant insights into the characteristics of the hit-list even under spreading dynamics that exceed that of currently known worms. Lastly, to illustrate the practicality of our solution, we apply our approach to real-world traces of the Witty worm and provide a refined estimate on the previously suspected hit-list size.
CHIL computing to overcome techno-clutter
Authors: Alex Waibel
Venue: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies (2005)

After building computers that paid no intention to communicating with humans, we have in recent years developed ever more sophisticated interfaces that put the "human in the loop" of computers. These interfaces have improved usability by providing more appealing output (graphics, animations), more easy to use input methods (mouse, pointing, clicking, dragging) and more natural interaction modes (speech, vision, gesture, etc.). Yet the productivity gains that have been promised have largely not been seen and human-machine interaction still remains a partially frustrating and tedious experience, full of techno-clutter and excessive attention required by the technical artifact.In this talk, I will argue, that we must transition to a third paradigm of computer use, in which we let people interact with people, and move the machine into the background to observe the humans' activities and to provide services implicitly, that is, -to the extent possible- without explicit request. Putting the "Computer in the Human Interaction Loop" (CHIL), instead of the other way round, however, brings formidable technical challenges. The machine must now always observe and understand humans, model their activities, their interaction with other humans, the human state as well as the state of the space they are in, and finally, infer intentions and needs. From a perceptual user interface point of view, we must process signals from sensors that are always on, frequently inappropriately positioned, and subject to much greater variablity. We must also not only recognize WHAT was seen or said in a given space, but also a broad range of additional information, such as the WHO, WHERE, HOW, TO WHOM, WHY, WHEN of human interaction and engagement.In this talk, I will describe a variety of multimodal interface technologies that we have developed to answer these questions and some preliminary CHIL type services that take advantage of such perceptual interfaces.