ppxscal/embedding_network huggingface dataset:
Addressing library creation challenges from recent Liberty extensions
Authors: Richard Trihy
Venue: Proceedings of the 45th annual Design Automation Conference (2008)

The Liberty Format is an open source industry standard for library modeling that has seen significant enhancement in recent years to address the challenges introduced by the new smaller technologies at 65nm and below. Issues associated with modeling Timing, Power and Noise have seen an explosion in complexity. The paper discusses the challenges introduced by the new high accuracy models and techniques to ameliorate them for Library providers.
Runtime software adaptation: framework, approaches, and styles
Authors: Peyman Oreizy, Nenad Medvidovic, Richard N. Taylor
Venue: Companion of the 30th international conference on Software engineering (2008)

Our ICSE 1998 paper showed how an application can be adapted at runtime by manipulating its architectural model. In particular, our paper demonstrated the beneficial role of (1) software connectors in aiding runtime change, (2) an explicit architectural model fielded with the system and used as the basis for runtime change, and (3) architectural style in providing both structural and behavioral constraints over runtime change. This paper examines runtime evolution in the decade hence. A broad framework for studying and describing evolution is introduced that serves to unify the wide range of work now found in the field of dynamic software adaptation. This paper also looks to the future, identifying what we believe to be highly promising directions.
Comparison between back propagation neural network and regression models for the estimation of pigment content in rice leaves and panicles using hyperspectral data
Authors: L. Chen, J. F. Huang, F. M. Wang, Y. L. Tang
Venue: International Journal of Remote Sensing (2007)

Two nitrogen experiments on rice were conducted in 2002, and the reflectances (350 to 2500 nm) and pigment contents (chlorophylls a and b, total chlorophylls and carotenoids) for leaf and panicle samples at different growth stages were measured in the laboratory. After performing an outlier analysis, the number of samples were 843 for leaves and 188 for panicles. Absorption features at 430, 460, 470, 640 and 660 nm for different pigments, and the relative reflectance of the green peak around 550 nm calculated by the continuum-removed method, as well as the red edge position (REP) of rice leaves and panicles were selected as the independent variables, and measured pigment contents were selected as the dependent variables. Then, back propagation neural network (BPN) models, a kind of artificial neuron network (ANN), and multivariate linear regression models (MLR) were trained and tested. The main objective of this study was to compare the predictive ability of the ANN models to that of the MLR models in estimating the content of pigments in rice leaves and panicles. Results showed that all BPN models gave higher coefficients of determination (R2) and lower absolute errors (ABSEs) and root mean squared errors (RMSEs) than the corresponding MLR models, in both calibration and validation tests. Further significance tests by paired t tests and bootstrapping algorithms indicated that most of the BPN models outperformed the MLR models. When trained by combination data that did not meet the assumption of normal distribution, the BPN models appeared to not only have a better learning ability, but also had a more accurate predictive power than the MLR models. The estimation of leaf pigments was more accurate than that of panicle pigments, independent of which model was used.
Dependence on initial conditions of oscillator displacement modulated by parametric noise
Authors: Nobutoshi Ikeda
Venue: Proceedings of the 12th WSEAS International Conference on Applied Mathematics (2007)

Stochastic dynamics involving parametric noise sometimes exhibits transition from an energetic stable state to an unstable state, while dynamics with additive noise only exhibits fluctuation around its average behavior. We investigated the dependence of transient behavior of oscillator on its initial conditions by introducing noise taking discrete values. We found that relaxation time of probability distribution becomes infinity as the intensity of parametric noise approaches a critical value, and above the critical value the difference between the second moments of the oscillator with different initial conditions increases exponentially.
Stable Running with Segmented Legs
Authors: Juergen Rummel, Andre Seyfarth
Venue: International Journal of Robotics Research (2008)

Spring-like leg behavior is found in both humans and animals when running. In a spring-mass model, running proves to be self-stable in terms of external perturbations or variations in leg properties (for example, landing angle). However, biological limbs are not made of springs, rather, they consist of segments where spring-like behavior can be localized at the joint level. Here, we use a two-segment leg model to investigate the effects of leg compliance originating from the joint level on running stability. Owing to leg geometry a non-linear relationship between leg force and leg compression is found. In contrast to the linear leg spring, the segmented leg is capable of reducing the minimum speed for self-stable running from 3.5 m s-1 in the spring-mass model to 1.5 m s-1 for almost straight joint configurations, which is below the preferred transition speed from human walking to running (&#x2248;2 m s-1). At moderate speeds the tolerated range of landing angle is largely increased (17&#x00B0; at 5 m s-1) compare with the linear leg spring model (2&#x00B0;). However, for fast running an increase in joint stiffness is required to compensate for the mechanical disadvantage of larger leg compression. This could be achieved through the use of non-linear springs to enhance joint stiffness in fast running.
The Confirmatory Research on Representative Method of Knowledge Work Process
Authors: Li Jinkun, Wang Bo, Li Yongjian, Fu Hao
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

The key point of improving the efficiency of knowledge work lies in the presentation of knowledge work process. Knowledge work is a process in human’s brain on subject symbols. Representation of knowledge work based on mental operation (MO) provides an analytical methods for improving the efficiency of knowledge work. We adopted the methodology of survey and the analytical tool of structure equation model (SEM) to justify the validity of using MO concept set to represent knowledge work process. We tried to provide a conceptual framework and theoretical thinking for knowledge work management and optimization.
Real-Time Market Model for Pricing Differentiated Services
Authors: Ruzana Davoyan, Jörn Altmann
Venue: Proceedings of the Fourth International Conference on Networking and Services (2008)

Pricing network resources is a crucial component for proper resource management and the provision of quality of service guarantees. In this paper we propose a decentralized real-time market (RTM) model for pricing differentiated services (DiffServ), which attempts to achieve efficient resource allocation, while reducing computational overheads. We review issues relating to congestion sensitive pricing of the network resources and propose an approach to alleviate price fluctuation that considers the actual state of the network. In comparison with the existing studies that consider the existence of a single point of market equilibrium, we consider the existence of a set of equilibrium states. The proposed strategy relies on the division of link capacity into intervals called steps, where current supply is determined according to the expected resource prices, and is the sum of the allocated steps. Consequently, the real state of the market is described by immediately accessible information, such as price.
Classification trees for ordinal variables
Authors: Raffaella Piccarreta
Venue: Computational Statistics (2008)

We introduce new criteria to obtain classification trees for ordinal response variables. At this aim, Breiman et al. (Classification and regression trees. Wadsworth, Belmont, 1984), extended their twoing criterion to the ordinal case. Following CART procedure, we extend the well known Gini---Simpson criterion to the ordinal case. Referring to the exclusivity preference property (introduced by Taylor and Silverman in Stat Comput 3:147---161, 1993, for the nominal case), suitably modified for the ordinal case, a second criterion is introduced. The hereby proposed methods are compared with the ordered twoing criterion via simulations.
Global and local spatial indices of urban segregation
Authors: F. F. Feitosa, G. Câmara, A. M. V. Monteiro, T. Koschitzki, M. P. S. Silva
Venue: International Journal of Geographical Information Science (2007)

Urban segregation has received increasing attention in the literature due to the negative impacts that it has on urban populations. Indices of urban segregation are useful instruments for understanding the problem as well as for setting up public policies. The usefulness of spatial segregation indices depends on their ability to account for the spatial arrangement of population and to show how segregation varies across the city. This paper proposes global spatial indices of segregation that capture interaction among population groups at different scales. We also decompose the global indices to obtain local spatial indices of segregation, which enable visualization and exploration of segregation patterns. We propose the use of statistical tests to determine the significance of the indices. The proposed indices are illustrated using an artificial dataset and a case study of socio-economic segregation in São José dos Campos (SP, Brazil).
Stability for two-dimensional singular discrete systems described by general model
Authors: Yun Zou, Huiling Xu, Weiqun Wang
Venue: Multidimensional Systems and Signal Processing (2008)

This paper discusses the problem of stability for linear discrete 2-D singular general models (2-D SGM). A sufficient condition for the internally stability of the 2-D SGM is derived in terms of linear matrix inequalities (LMIs).
Google Guice: Agile Lightweight Dependency Injection Framework (Firstpress)
Authors: Robbie Vanbrabant
Venue:  (2008)

Guice (pronounced Juice) is the Jolt Award winning, 100% Java icing on the cake of Java dependency injection. Unlike other popular DI frameworks such as Spring, Guice fully embraces modern Java language features and combines simplicity with stunning performance and developerfriendliness. Google Guice: Agile Lightweight Dependency Injection Framework will not only tell you how, it will also tell you why and why not, so that all the knowledge you gain will be as widely applicable as possible. Filled with examples and background information, this book is an invaluable addition to your knowledge of modern agile Java. Learn simple annotationdriven dependency injection, scoping and AOP, and why it all works the way it works. Be the first to familiarize yourself with concepts that are likely to be included in a future Java EE or SE release (through JSR 299). Get things done without having to write any XML. What youll learn Find out why dependency injection frameworks solve your problems, and how Guice fills that gap. What Guice can do, cant do and how to apply that knowledge. How Guice compares to popular alternatives like the Spring Framework. What the future has in store, including Guice IDE, the next Guice version and the standardization of Guices concepts through JSR 299. How you can build realworld, Guicepowered web applications using popular frameworks like Wicket or Struts 2. How to develop a full stack Guice/Struts 2/Hibernate application. What you can really do with modern Java. Who is this book for? This book is for professional Java developers who are interested in dependency injection and modern Java coding practices, and who want to tackle complexity with a simple, powerful, and highquality solution that powers one of Googles highest profile applications: AdWords. This may be an alternative to Spring for many.
A reranking model for genomics aspect search
Authors: Qinmin Hu, Xiangji Huang
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

In this paper, we propose a reranking model to improve the aspect-level performance in the biomedical domain. This model iteratively computes the maximum hidden aspect for every retrieved passage and then reranks these passages from aspect subsets. The experimental results show the improvements of the aspect-level performance up to 27.14% for 2006 Genomics topics and 27.09% for 2007 Genomics topics.
Industrialization, structure change and electricity consumption: the case of China
Authors: Zhao Chang-Hong, Xiong Min-Peng, Yuan Jia-Hai
Venue: Proceedings of the 10th WSEAS International Conference on APPLIED MATHEMATICS (2006)

In the paper factor decomposition method is used for the study of China's industrial electricity consumption from 1990 to 2003. The output effect, structural effect and intensity effect of industrial electricity growth is reported, demonstrating the reason of rapid industrial electricity growth is in the rapid growth of industrial output. Then according to the three-stage classification of industrialization process three kinds of industries are classified and the industrial structure transition from 1990 to 2003 is analyzed. Finally the effect of industrialization to electricity demand is analyzed. The paper concludes that the deepening of industrialization will lessen electricity intensity overall, while the structural effect of three kind of industries is related with the order of industrialization process, with the first two being negative and the third being positive.
Poking facebook: characterization of osn applications
Authors: Minas Gjoka, Michael Sirivianos, Athina Markopoulou, Xiaowei Yang
Venue: Proceedings of the first workshop on Online social networks (2008)

Facebook is one of the most popular Internet sites today. A key feature that arguably contributed to Facebook's unprecedented success is its application platform, which enables the development of third-party social-networking applications. Understanding how these applications are installed and used is important for the function and utility of web-based online social networks, e.g. to better engineer them and/or to design advertising campaigns. In this paper, we characterize the popularity and user reach of Facebook applications. We analyze application usage data gathered over a period of six months from Facebook and Adonomics - a Facebook analytics service. We also crawl publicly accessible Facebook user profiles and obtain per-user application installation statistics, for approximately 300K users and 13.6K applications. Our findings include that (i) the popularity of Facebook applications has a highly skewed distribution; (ii) although the total number of application installations increases with time, the average user activity decreases; and (iii) users with more applications installed are more likely to install new applications.
Biomarker Identification for Early Tumor Detection Aided by Bioinformatics Gene Expression Analysis
Authors: Wanling Yang, Peng Huang, Minghui Zhao, Yu Lung Lau
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

Early detection of cancer is key to prompt treatment and patient’s long term survival. Designing non-invasive and simple methodologies that can be used in large scale screening for early tumor detection is an important research area that could have profound impact on cancer prevention and treatment. Taking advantage of available gene expression databases, we have performed extensive analysis on differentially expressed (DE) genes and alternatively spliced (AS) forms of genes in cancer tissues. In this study we detected genes that are potentially up-regulated in tumor tissues comparing to normal tissues. We also aligned the 8 million human EST sequences in dbEST with human genomic sequences, and found several hundreds AS variants that have a potential to be specific to or overexpressed in tumor tissues comparing to normal tissues. Our results showed the possibility of using gene expression databases to detect potential “cancer genes”, and to use those DS genes and AS variants of genes as markers for early cancer detection.
Investigation of Q-learning in the context of a virtual learning environment
Authors: Dalia Baziukaite
Venue: Informatics in education (2007)

We investigate the possibility to apply a known machine learning algorithm of Q-learning in the domain of a Virtual Learning Environment (VLE). It is important in this problem domain to have algorithms that learn their optimal values in a rather short time expressed in terms of the iteration number. The problem domain is a VLE in which an agent plays a role of the teacher. With time it moves to different states and makes decisions which regarding action to choose for moving from current state to the next state. Some actions taken are more efficient than others. The transition process through the set of states ends in a final (goal) state, one which provides the agent with the largest benefit possible. The best course of action is to reach the goal state with the maximum return available. This paper introduces a way of definition of a rewards matrix, which allows the maximum tolerance for the changes of a discounted reward value to be achieved. It also proposes way of an application of the Q-learning that allows a teaching policy to exist, which maps the situation in the learning environment.
Phase-only transform based shaping for error concealment coding
Authors: Lihong Ma, Guifeng Cheng, Zhijian Wu, Xiaoxi Luo, Hanqing Lu
Venue: Proceedings of the 2nd international conference on Mobile multimedia communications (2006)

In this paper, we propose a novel approach of error resilient coding by introducing a phase-only transform to the low bit MDVQ (Multiple description vector quantization) method. Phase-only transform has the characteristic of shape preserving. Thus the original image could be synthesized using the true phases and the coarser descriptions. When both descriptions are received, a high quality reconstruction can be obtained. On the contrary, if only one description is available, a lower quality image would still be decoded from a received description. Even if an image suffers damages from an eraser channel, a signal with acceptable quality could be rebuilt with our scheme at least. Simulation results show that the proposed method outperforms several other approaches such as pixel interleaving, MDVQ and phase scrambling in PSNR.
Widening the pipeline of K-12 students with flash
Authors: Mike Sands, Nick Moukhine, Glenn Blank
Venue: Journal of Computing Sciences in Colleges (2008)

There are many negative stereotypes about computer science. These preconceived ideas may discourage students, especially women and minorities, from pursuing a computer science education. Our goal is to create a program that dispels these misconceptions, both in inner city middle and high schools and in an outreach program that attracts at-risk students to Lehigh University to learn about information technology. A curriculum that uses Flash programming helps to dispel these misconceptions and bring more minority and female high school students back into the pipeline of potential computer scientists.
Software engineering field and curriculum adaptationin turkey
Authors: Ali H. Dogru, Meltem Turhan-Yondem
Venue: Proceedings of the 2008 international workshop on Software Engineering in east and south europe (2008)

Introduction of a non-thesis Master of Science in Software Engineering program in Turkey is discussed along with its relations to industry. New programs in Software Engineering are flourishing in Turkey and their influence is interesting to discuss along the peculiarities of the country, as presented in this article. Turkey delivers rather quality software products in non-trivial domains but could not catch the success levels of India and some other small countries, especially in mass development. With well trained engineers and its proximity to Europe, the capability to invite once missed IT boom opportunity depends partially on the maturity of the software industry. This article presents the first graduate degree program in Software Engineering as a tool for the transitioning of the industry.
Multi-stage extreme learning machine for fault diagnosis on hydraulic tube tester
Authors: Xue-fa Hu, Zhen Zhao, Shu Wang, Fu-li Wang, Da-kuo He, Shui-kang Wu
Venue: Neural Computing and Applications (2008)

The running status of hydraulic tube tester is reflected by the boosting pressure curve in Hydrostatic testing process. The authors present the extreme learning machine (ELM), a novel good learning scheme much faster than traditional gradient-based learning algorithms, as a mechanism for clustering the pressure curves. However, it caused low accuracy for clustering pressure curves for hydraulic tube tester. In this paper, a multi-stage ELM is proposed to improve the accuracy of clustering. During the process of this new ELM, the input data were divided into several stages, then, every stage was analyzed independently. At last, this method has been used in hydraulic tube tester data. Compared with individual ELM, it has better function for considering the characteristics of input data.
Bayesian feature evaluation for visual saliency estimation
Authors: Xiao-Peng Hu, Laura Dempere-Marco, E. Roy Davies
Venue: Pattern Recognition (2008)

This paper presents a computational method of feature evaluation for modeling saliency in visual scenes. This is highly relevant in visual search studies since visual saliency is at the basis of visual attention deployment. Visual saliency can also become important in computer vision applications as it can be used to reduce the computational requirements by permitting processing only in those regions of the scenes containing relevant information. The method is based on Bayesian theory to describe the interaction between top-down and bottom-up information. Unlike other approaches, it evaluates and selects visual features before saliency estimation. This can reduce the complexity and, potentially, improve the accuracy of the saliency computation. To this end, we present an algorithm for feature evaluation and selection. A two-color conjunction search experiment has been applied to illustrate the theoretical framework of the proposed model. The practical value of the method is demonstrated with video segmentation of instruments in a laparoscopic cholecystectomy operation.