ppxscal/embedding_network huggingface dataset:
Multi-aspect profiling of kernel rootkit behavior
Authors: Ryan Riley, Xuxian Jiang, Dongyan Xu
Venue: Proceedings of the 4th ACM European conference on Computer systems (2009)

Kernel rootkits, malicious software designed to compromise a running operating system kernel, are difficult to analyze and profile due to their elusive nature, the variety and complexity of their behavior, and the privilege level at which they run. However, a comprehensive kernel rootkit profile that reveals key aspects of the rootkit's behavior is helpful in aiding a detailed manual analysis by a human expert. In this paper we present PoKeR, a kernel rootkit profiler capable of producing multi-aspect rootkit profiles which include the revelation of rootkit hooking behavior, the exposure of targeted kernel objects (both static and dynamic), assessment of user-level impacts, as well as the extraction of kernel rootkit code. The system is designed to be deployed in scenarios which can tolerate high overheads, such as honeypots. Our evaluation results with a number of real-world kernel rootkits show that PoKeR is able to accurately profile a variety of rootkits ranging from traditional ones with system call hooking to more advanced ones with direct kernel object manipulation. The obtained profiles lead to unique insights into the rootkits' characteristics and demonstrate PoKeR's usefulness as a tool for rootkit investigators.
Local Image Descriptors Using Supervised Kernel ICA
Authors: Masaki Yamazaki, Sidney Fels
Venue: Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology (2009)

PCA-SIFT is an extension to SIFT which aims to reduce SIFT's high dimensionality (128 dimensions) by applying PCA to the gradient image patches. However PCA is not a discriminative representation for recognition due to its global feature nature and unsupervised algorithm. In addition, linear methods such as PCA and ICA can fail in the case of non-linearity. In this paper, we propose a new discriminative method called Supervised Kernel ICA (SKICA) that uses a non-linear kernel approach combined with Supervised ICA-based local image descriptors. Our approach blends the advantages of a low dimensionality representation, like PCA-SIFT, with supervised learning based on non-linear properties of kernels to overcome separability limitations of nonlinear representations for recognition. Using five different test data sets we show that the SKICA descriptors produce better object recognition performance than other related approaches with the same dimensionality. The SKICA-based representation has local sensitivity, non-linear independence and high class separability providing an effective method for local image descriptors.
Successively Structured Gaussian Two-terminal Source Coding
Authors: Hamid Behroozi, M. Reza Soleymani
Venue: Wireless Personal Communications: An International Journal (2009)

Multiterminal source coding refers to separate encoding and joint decoding of multiple correlated sources. Joint decoding requires all the messages to be decoded simultaneously which is exponentially more complex than a sequence of single-message decodings. Inspired by previous work on successive coding, we apply the successive Wyner-Ziv coding, which is inherently a low complexity approach of obtaining a prescribed distortion, to the two-terminal source coding scheme. First, we consider 1-helper problem where one source provides partial side information to the decoder to help the reconstruction of the main source. Our results show that the successive coding strategy is an optimal strategy in the sense of achieving the rate-distortion function. By developing connections between source encoding and data fusion steps, it is shown that the whole rate-distortion region for the 2-terminal source coding problem is achievable using the successive coding strategy. Comparing the performance of the sequential coding with the performance of the successive coding, we show that there is no sum-rate loss when the side information is not available at the encoder. This result is of special interest in some applications such as video coding where there are processing and storage constraints at the encoder. Finally, we provide an achievable rate-distortion region for the m-terminal source coding.
Simulation of process execution monitoring and adjustment schemes
Authors: Russell R. Barton, Jun Shu
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Optimization and design of production and service operations has been a cornerstone of simulation applications for many years. Recently there has been increasing interest in excellence in process execution, for service processes, supply chains, and manufacturing operations. Simulation again has an important role to play, in evaluating the effectiveness of different execution monitoring schemes. The focus of analysis changes in this setting, however, from monitoring characteristics of resources, such as queue length, waiting time and utilization, to monitoring the timeliness and correctness of the progress of entities through the system, and reacting with real-time adjustments to resources and routings. This paper describes the types of simulation analysis needed, and identifies difficulties in conducting such simulation studies using current commercial software.
Online Generation and Dissemination of Disaster Information Based on Satellite Remote Sensing Data
Authors: Chao-Yang Fang, Hui Lin, Qing Xu, Dan-Ling Tang, Wong-Chiu Anthony Wang, Jun-Xian Zhang, Yick-Cheung Matthew Pang
Venue: Proceedings of the 8th International Symposium on Web and Wireless Geographical Information Systems (2008)

This paper aims to introduce a system framework for online generation and dissemination of disaster information based on satellite remote sensing data, that is, the design and application of the WEB-based Disaster Monitoring and Warning Information System --- WEB-DMWIS. By integrating the satellite remote sensing data, scientific workflow technique, and the Application Service Provider (ASP) service model, WEB-DMWIS makes it possible for different levels of users to access customized disaster information via WEB. In this way, it provides an information platform which supports widely-used near real-time monitoring and early warning of natural disasters. The system is composed of two parts: (a) a user-side browser; (b) a server-side disaster information center. After introducing the system framework and functions of main engines, this paper described in detail the principle and realization of the online generation and distribution of disaster information. In addition, the disaster monitoring and early warning information system for fishery industry in Pearl River Delta region is developed on the basis of the WEB-DMWIS to verify and demonstrate the effectiveness of the framework.
Emotion Recognition and Its Application to Computer Agents with Spontaneous Interactive Capabilities
Authors: Ryohei Nakatsu, Alexandre Solomides, Naoko Tosa
Venue: Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02 (1999)

Nonverbal information such as emotion plays an essential role in human communication. We first study the recognition of emotions involved in human speech. We propose an emotion recognition algorithm based on a neural network. An emotion recognition rate of approximately 50% was obtained in a speaker-independent mode for eight emotion states.We tried to apply this emotion recognition algorithm to a computer agent that plays a character role in the interactive movie system we are developing. We propose to use emotion recognition as key technology for an architecture of the computer characters with both narrative-based and spontaneous interaction capabilities.
Ultrafast All-Optical Signal Processing Devices
Authors: Hiroshi Ishikawa
Venue:  (2008)

Semiconductor-based Ultra-Fast All-Optical Signal Processing Devices a key technology for the next generation of ultrahigh bandwidth optical communication systems!The introduction of ultra-fast communication systems based on all-optical signal processing is considered to be one of the most promising ways to handle the rapidly increasing global communication traffic. Such systems will enable real time super-high definition moving pictures such as high reality TV-conference, remote diagnosis and surgery, cinema entertainment and many other applications with small power consumption. The key issue to realize such systems is to develop ultra-fast optical devices such as light sources, all-optical gates and wavelength converters.Ultra-Fast All-Optical Signal Processing Devices discusses the state of the art development of semiconductor-based ultrafast all-optical devices, and their various signal processing applications for bit-rates 100Gb/s to 1Tb/s.Ultra-Fast All-Optical Signal Processing Devices: Provides a thorough and in-depth treatment of the most recent achievements in ultrafast all-optical devices Discusses future networks with applications such as HD-TV and super-high definition moving screens as a motivating background for devices research Covers mode-locked semiconductor lasers, electro-absorption modulator based 160Gb/s signal sources, SOA based symmetric Mach-Zehnder type all-optical gates, intersubband transition gate device, and more Explains the technical issues behind turning the ultra-fast optical devices into practical working tools Examples of above 160Gb/s transmission experiments Discusses future prospects of the ultra-fast signal processing devices This invaluable reference will provide device researchers and engineers in industry, researchers at universities (including graduate students, and post doctorial researchers and professors) and research institutes with a thorough understanding of ultrahigh bandwidth optical communication systems. Device and communication market watchers will also find this book useful.
New approach on power efficiency of a RISC processor
Authors: Orest Oltu, Valentin Voiculescu, Gary Gibson, Lucian Milea, Adrian Barbilian
Venue: Proceedings of the 8th conference on Applied informatics and communications (2008)

Most often, for a digital electronic device, the consumed power is indicated as an average value without explicitly expressing the functional conditions under which this power was measured. This is also true for microprocessors. For a large part of the ARM (Advanced RISC Microprocessors) used in battery-supplied devices the consumed power represents a critical parameter. Any drop in power absorption from the battery is important. For designers working on improving this parameter, it is very useful to be able to have a different way to characterize the processor from an energetic point of view instead of the classical model of power consumption figures measured in microwatts per Megahertz. In this paper we propose a new method to compare two hardware variants of ARM processors, designed to work for a specific set of applications. Because the absorbed power varies dynamically during the time the application is running, we consider that the total energy required during this time for the run is a more exact and correct way to characterize the energetic efficiency of the microprocessor.
Dynamic Web Service Composition
Authors: Faisal Mustafa, T. L. McCluskey
Venue: Proceedings of the 2009 International Conference on Computer Engineering and Technology - Volume 02 (2009)

A major area of recent web-related research concerns automated web service composition. A major advantage of web services technology lies in the potential of creating value-added services by combining existing ones to achieve customized tasks. How to combine these services efficiently into an arrangement that is both functionally sound and architecturally realizable is a very challenging topic that has founded a significant research area within computer science. Our research contribution lies in the area of dynamic composition services selection. We have started by collating and analyzing current outstanding problems within the dynamic composition area. To help explain the background to these challenges we compare, firstly, the key components of distributed computing technologies with web service composition. Then we define the ‘execute ability’ problem - the key idea that preconditions of web services must be satisfied before or as a result of composition. We discuss data distribution strategies among services, how they can be used to overcome problems in dynamic composition problems and how they relate to the quality of service. Finally, we present our proposed framework model to handle the process of web service composition and execution. We propose that this framework eliminates the main problems as discussed in the paper.
UCSD Pascal&trade;: a portable software environment for small computers
Authors: Mark Overgaard
Venue: Proceedings of the May 19-22, 1980, national computer conference (1980)

The UCSD Pascal System is a complete program development and execution environment for small computers. Its facilities include text editors and file management utilities, as well as compilers (for Pascal, in particular), assemblers, and a linkage editor. The system is highly portable; versions have been implemented on almost twenty minicomputers and microprocessors. (A concise description of system facilities is provided in an appendix.)
A temporal case retrieval model to predict railway passenger arrivals
Authors: Tsung-Hsien Tsai
Venue: Expert Systems with Applications: An International Journal (2009)

This paper proposes a three-stage model to predict final sales when advanced booking, which is prevalent in the service industry, is available. The concept behind the proposal is that similar booking patterns during the reservation period indicate the trend of sales. Booking curves which record accumulated reservations were collected from a railway company. The first stage is to evaluate the similarity of booking patterns between the collected samples and the days to be predicted. Then samples with high similarity to the forecasting target are chosen from the collected observations. Integrating the final sales of these selected samples to project future volumes is the main job in the last stage. Regression and Pick Up models, common in practice, are also constructed for comparing purposes. The results show that the proposed model can significantly improve predictive accuracy in the testing cases.
Superconducting memories employing Josephson devices
Authors: W. Anacker
Venue: Proceedings of the May 19-22, 1975, national computer conference and exposition (1975)

Experimental superconducting Josephson devices being investigated for use in digital logic and memory circuits have been demonstrated to switch in the 10 to 100 picosecond (1 picosecond = 10-12 sec) range. Projections based on the operation of individual logic circuits indicate that they may surpass semiconductor circuits in very high performance CPU's. This potential is based on the fact that these circuits dissipate extremely little energy, on the order of 10 to 1000 attojoules (attojoule = 10-18 joule), while operating with subnanosecond delays. It should, therefore, be possible to package Josephson devices very densely and interconnect them by properly terminated superconducting transmission lines so that the fast switching speed of individual circuits is retained throughout large logic networks.
Blocking links to minimize contamination spread in a social network
Authors: Masahiro Kimura, Kazumi Saito, Hiroshi Motoda
Venue: ACM Transactions on Knowledge Discovery from Data (TKDD) (2009)

We address the problem of minimizing the propagation of undesirable things, such as computer viruses or malicious rumors, by blocking a limited number of links in a network, which is converse to the influence maximization problem in which the most influential nodes for information diffusion is searched in a social network. This minimization problem is more fundamental than the problem of preventing the spread of contamination by removing nodes in a network. We introduce two definitions for the contamination degree of a network, accordingly define two contamination minimization problems, and propose methods for efficiently finding good approximate solutions to these problems on the basis of a naturally greedy strategy. Using large social networks, we experimentally demonstrate that the proposed methods outperform conventional link-removal methods. We also show that unlike the case of blocking a limited number of nodes, the strategy of removing nodes with high out-degrees is not necessarily effective for these problems.
Generalized interpolating refinable function vectors
Authors: Bin Han, Soon-Geol Kwon, Xiaosheng Zhuang
Venue: Journal of Computational and Applied Mathematics (2009)

Interpolating scalar refinable functions with compact support are of interest in several applications such as sampling theory, signal processing, computer graphics, and numerical algorithms. In this paper, we shall generalize the notion of interpolating scalar refinable functions to compactly supported interpolating d-refinable function vectors with any multiplicity r and dilation factor d. More precisely, we are interested in a d-refinable function vector @f=[@f"1,...,@f"r]^T such that @f is an rx1 column vector of compactly supported continuous functions with the following interpolation property @f"@?(mr+k)=@d"k@d"@?"-"1"-"m,@?k@?Z,m=0,...,r-1,@?=1,...,r, where @d"0=1 and @d"k=0 for k=2 or d>2, such interpolating refinable function vectors can have the additional orthogonality property: =r^-^1@d"@?"-"@?"^"'@d"k"-"k"^"' for all k,k^'@?Z and 1=
Toward Multi-modal Music Emotion Classification
Authors: Yi-Hsuan Yang, Yu-Ching Lin, Heng-Tze Cheng, I-Bin Liao, Yeh-Chin Ho, Homer H. Chen
Venue: Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing (2008)

The performance of categorical music emotion classification that divides emotion into classes and uses audio features alone for emotion classification has reached a limit due to the presence of a semantic gap between the object feature level and the human cognitive level of emotion perception. Motivated by the fact that lyrics carry rich semantic information of a song, we propose a multi-modal approach to help improve categorical music emotion classification. By exploiting both the audio features and the lyrics of a song, the proposed approach improves the 4-class emotion classification accuracy from 46.6% to 57.1%. The results also show that the incorporation of lyrics significantly enhances the classification accuracy of valence.
Skin Color Profile Capture for Scale and Rotation Invariant Hand Gesture Recognition
Authors: Rafael Bastos, Miguel Sales Dias
Venue: Gesture-Based Human-Computer Interaction and Simulation: 7th International Gesture Workshop, GW 2007, Lisbon, Portugal, May 23-25, 2007, Revised Selected Papers (2009)

This paper presents a new approach to real-time scale and rotation invariant hand pose detection, which is based on a technique for computing the best hand skin color segmentation map. This segmentation map, a vector entity referred to as a "skin profile", is used during an online hand gesture calibration stage to enable correct classification of skin regions. Subsequently, we construct efficient and reliable scale and rotation invariant hand pose gesture descriptors, by introducing an innovative technique, referred to as "oriented gesture descriptors". Finally, hand pose gesture recognition is computed using a template matching technique which is luminance invariant.
Supporting the creation of hybrid museum experiences
Authors: Boriana Koleva, Stefan Rennick Egglestone, Holger Schnädelbach, Kevin Glover, Chris Greenhalgh, Tom Rodden, Martyn Dade-Robertson
Venue: Proceedings of the 27th international conference on Human factors in computing systems (2009)

This paper presents the evolution of a tool to support the rapid prototyping of hybrid museum experiences by domain professionals. The developed tool uses visual markers to associate digital resources with physical artefacts. We present the iterative development of the tool through a user centred design process and demonstrate its use by domain experts to realise two distinct hybrid exhibits. The process of design and refinement of the tool highlights the need to adopt an experience oriented approach allowing authors to think in terms of the physical and digital "things" that comprise a hybrid experience rather than in terms of the underlying technical components.
Using lifelogging to support recollection for people with episodic memory impairment and their caregivers
Authors: Matthew L. Lee, Anind K. Dey
Venue: Proceedings of the 2nd International Workshop on Systems and Networking Support for Health Care and Assisted Living Environments (2008)

We designed a lifelogging system to assist people with episodic memory impairment (EMI) to reminisce about recent experiences and reduce the burden on their caregivers. Our system uses a mobile passive capture approach so that the person with EMI does not have to remember to initiate capture. Our system leverages both automated content and context analysis and the expertise of the caregiver to extract the most salient cues from the lifelog. Finally, our system structures the cue review interaction so that it allows the person with EMI to think more deeply about each cue and remember the details of their experiences without repeatedly burdening the caregiver.
An improved approximation to the precision of fixed effects from restricted maximum likelihood
Authors: Michael G. Kenward, James H. Roger
Venue: Computational Statistics Data Analysis (2009)

An approximate small sample variance estimator for fixed effects from the multivariate normal linear model, together with appropriate inference tools based on a scaled F pivot, is now well established in practice and there is a growing literature on its properties in a variety of settings. Although effective under linear covariance structures, there are examples of nonlinear structures for which it does not perform as well. The cause of this problem is shown to be a missing term in the underlying Taylor series expansion which accommodates the bias in the estimators of the parameters of the covariance structure. The form of this missing term is derived, and then used to adjust the small sample variance estimator. The behaviour of the resulting estimator is explored in terms of invariance under transformation of the covariance parameters and also using a simulation study. It is seen to perform successfully in the way predicted from its derivation.