ppxscal/embedding_network huggingface dataset:
Finding Transport Proteins in a General Protein Database
Authors: Sanmay Das, Milton H. Saier,  Jr., Charles Elkan
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

The number of specialized databases in molecular biology is growing fast, as is the availability of molecular data. These trends necessitate the development of automatic methods for finding relevant information to include in specialized databases. We show how to use a comprehensive database (SwissProt) as a source of new entries for a specialized database (TCDB, the Transport Classification Database). Even carefully constructed keyword-based queries perform poorly in determining which SwissProt records are relevant to TCDB; we show that a machine learning approach performs well. We describe a maximum-entropy classifier, trained on SwissProt records, that achieves high precision and recall in cross-validation experiments. This classifier has been deployed as part of a pipeline for updating TCDB that allows a human expert to examine only about 2% of SwissProt records for potential inclusion in TCDB. The methods we describe are flexible and general, so they can be applied easily to other specialized databases.
Algorithms for Temperature-Aware Task Scheduling in Microprocessor Systems
Authors: Marek Chrobak, Christoph Dürr, Mathilde Hurand, Julien Robert
Venue: Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management (2008)

We study scheduling problems motivated by recently developed techniques for microprocessor thermal management at the operating systems level. The general scenario can be described as follows. The microprocessor temperature is controlled by the hardware thermal management system that continuously senses the chip temperature and automatically reduces the processor's speed as soon as the thermal threshold is exceeded. Some tasks are more CPU-intensive than other and thus generate more heat during execution. The cooling system operates non-stop, reducing (at an exponential rate) the deviation of the processor's temperature from the ambient temperature. As a result, the processor's temperature, and thus the performance as well, depends on the order of the task execution. Given a variety of possible underlying architectures, models for cooling and for hardware thermal management, as well as types of tasks, this gives rise to a plethora of interesting and never studied scheduling problems.We focus on scheduling real-time jobs in a simplified model for cooling and thermal management. A collection of unit-length jobs is given, each job specified by its release time, deadline and heat contribution. If, at some time step, the temperature of the system is t and the processor executes a job with heat contribution h, then the temperature at the next step is (t + h)/2. The temperature cannot exceed the given thermal threshold ¿. The objective is to maximize the throughput, that is, the number of tasks that meet their deadlines. We prove that in the offline case computing the optimum schedule is NP-hard, even if all jobs are released at the same time. In the online case, we show a 2-competitive deterministic algorithm and a matching lower bound.
The ICFP developer conference 2008
Authors: James Hook, Michael Sperber
Venue: ACM SIGPLAN Notices (2008)

Functional Programming has seen greatly increased interest in recent years: From being an academic pursuit, functional programming is rapidly becoming a sought-after technology with increasingly broad applications. To accommodate the growing interest in FP, this year's International Conference on Functional Programming (in Victoria, British Columbia, Canada) will be followed by the ICFP Developer Conference, designed to help both decision-makers and developers to learn about the potential of functional programming for their projects, as well as gaining hands-on instruction on how to realize that potential.
Interpolation and Extrapolation of Motion Patterns in the Proto-symbol Space
Authors: Tetsunari Inamura, Tomohiro Shibata
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

We propose a new method for interpolation and extrapolation of motion patterns in proto-symbol spaces. The proto-symbol space is a topological space which abstracts motion patterns by utilizing continuous hidden Markov models, and the mimesis model that recognizes/generates known/unknown motion patterns by using this topological space. An interpolation algorithm for the proto-symbol space has already been proposed, but it had a mathematical problem. Furthermore, extrapolation of motion patterns was not defined, and could not be calculated. In the new method, the synthesis of proto-symbols is done separately for state transition probabilities and output probabilities, and the synthesis of the state transition probabilities is done in the time domain. Experiments in a simulation environment demonstrate the feasibility of this method.
Microsystems Microprogram Assemblers for Bit Slice Microprocessors
Authors: V. M. Powers
Venue: Computer (1978)

Designers of high-speed microprocessors need good software to help them construct the microprogram, but the seven bit-slice assemblers surveyed here remain essentially low level and even primitive.
Two-factor mutual authentication based on smart cards and passwords
Authors: Guomin Yang, Duncan S. Wong, Huaxiong Wang, Xiaotie Deng
Venue: Journal of Computer and System Sciences (2008)

One of the most commonly used two-factor user authentication mechanisms nowadays is based on smart-card and password. A scheme of this type is called a smart-card-based password authentication scheme. The core feature of such a scheme is to enforce two-factor authentication in the sense that the client must have the smart-card and know the password in order to gain access to the server. In this paper, we scrutinize the security requirements of this kind of schemes, and propose a new scheme and a generic construction framework for smart-card-based password authentication. We show that a secure password based key exchange protocol can be efficiently transformed to a smart-card-based password authentication scheme provided that there exist pseudorandom functions and target collision resistant hash functions. Our construction appears to be the first one with provable security. In addition, we show that two recently proposed schemes of this kind are insecure.
Possibilistic programming approach for fuzzy multidimensional analysis of preference in group decision making
Authors: Soheil Sadi-Nezhad, Pari Akhtari
Venue: Applied Soft Computing (2008)

Multiple attribute decision making (MADM) problems are the most encountered problems in decision making. Fuzziness is inherent in decision making process and linguistic variables are well suited to assessing an alternative on qualitative attributes using fuzzy rating. A few techniques in MADM assess the weights of attributes based on preference information on alternatives. But they are not practical any more when the set of all paired comparison judgments from decision makers (DMs) on attributes are not crisp and also we have to deal with fuzzy decision matrix. This paper investigates the generation of a possibilistic model for multidimensional analysis of preference (LINMAP). The model assesses the fuzzy weights as well as locating the ideal solution with fuzzy decision making preference on attributes and fuzzy decision matrix. All of the information is assumed as triangular fuzzy numbers (TFNs). This method is developed in group decision making environments and formulates the problem as a possibilistic programming with multiple objectives.
Fuzzy Neural Network-Based Sliding Mode Control for Non-spinning Warhead with Moving Mass Actuators
Authors: Hongchao Zhao, Ruchuan Zhang, Ting Wang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Dynamic model of a non-spinning reentry warhead with moving mass actuators is analyzed. The coupling terms between pitch channel and yaw channel are regarded as the uncertainties of each channel, thus the dynamic model is simplified. In order to approximate the bound of lumped uncertainty, two fuzzy neural network-based sliding mode controllers are designed for the moving mass control systems of pitch channel and yaw channel. They control the motion of two moving masses and realize the exact control of warhead's attitude angles. The effect of coupling terms is overcome, and thus the robustness and control precision of the moving mass control systems are improved. Simulation results show the designed fuzzy neural network-based sliding mode controllers have good control effect.
UMQL: A Unified Multimedia Query Language
Authors: Zhongsheng Cao, Zongda Wu, Yuanzhen Wang
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

We propose a unified multimedia query language called UMQL, based on a semi-structured data model. In contrast to previous multimedia query languages that are either designed only for one particular medium or not powerful enough on multimedia query ability, UMQL is a general and powerful multimedia language which can support effectively queries based on content, structure, spatial relationships and temporal relationships of multimedia data, and finally has been shown to be very expressive and quite suitable for multimedia information retrieval.
Segmentation on Multispectral Remote Sensing Image Using Watershed Transformation
Authors: Yun Zhang, Xuezhi Feng, Xinghua Le
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

In this paper, a new method for segmenting multispectral remote sensing image is proposed, which combines spectral properties of the pixels and their spatial properties. Spectral properties are studied by analyzing spectral angle of pixels while spatial properties are studied by morphological method. The spectral angle of each pixel is first computed by taken them as a vector with n-dimension. After an automatic selection of significant minima, an initial segmentation is achieved by applying watershed transformation to spectral angle map. To overcome the over-segmentation problem of watershed transformation, a region merging process using region adjacency graph (RAG) is employed to get the final segmentation result.
Comparing Local Feature Descriptors in pLSA-Based Image Models
Authors: Eva Hörster, Thomas Greif, Rainer Lienhart, Malcolm Slaney
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

Probabilistic models with hidden variables such as probabilistic Latent Semantic Analysis (pLSA) and Latent Dirichlet Allocation (LDA) have recently become popular for solving several image content analysis tasks. In this work we will use a pLSA model to represent images for performing scene classification. We evaluate the influence of the type of local feature descriptor in this context and compare three different descriptors. Moreover we also examine three different local interest region detectors with respect to their suitability for this task. Our results show that two examined local descriptors, the geometric blur and the self-similarity feature, outperform the commonly used SIFT descriptor by a large margin.
The senior companion multiagent dialogue system
Authors: Hugo Pinto, Yorick Wilks, Roberta Catizone, Alexiei Dingli
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3 (2008)

This article presents a multi-agent dialogue system. We show how a collection of relatively simple agents is able to treat complex dialogue phenomena and deal successfully with different deployment configurations. We analyze our system regarding robustness and scalability. We show that it degrades gracefully under different failures and that the architecture allows one to easily add new modalities was well as porting the system to different applications and platforms.
iCAN: Pursuing Technology for Near-Future ITS
Authors: Massaki Wada, Mami Mizutani, Masaki Saito, Xuchu Mao, Hideki Hashimoto
Venue: IEEE Intelligent Systems (2004)

The iCAN (Intelligent Car Navigation Systems) project is a collaboration between academia (the University of Tokyo) and industry (the Toshiba and Yazaki corporations) to pursue intelligent systems and their enabling technologies for near-future intelligent transportation systems.
Camera Phone Bans Expected
Authors: Terry Costlow
Venue: IEEE Distributed Systems Online (2004)

With the growing popularity of camera phones, privacy is becoming an issue. Some worry they could be used to take embarrasing photos in locker rooms, or even to perpetuate identity theft.
Extended enterprise resource planning: conceptual approach using multiagent systems
Authors: Darius Plikynas
Venue: Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation (2008)

Globalization and mass-customization is shaping a new kind of e-business for manufacturing and service organizations alike. Enterprises are strongly conditioned by unpredictable changes in the markets. The raising question is how to provide efficient, cost-effective and customer-oriented solutions on time. In fact, current systems such as enterprise resource planning (ERP) and supply chain management (SCM) do not provide adequate facilities for addressing this problem. This paper conceptualizes how multiplatform integration may contribute to the evolving new phenomenon, i.e. global enterprise resource planning (GERP) systems. We are talking about perspectives of merging multi-agent approach with the ERP and SCM platforms, where communication framework is facilitated by the field-based model adopted from the recent advances in the robotics research. Intuitive reasoning behind it is based upon behavior of complex social networks, where are prevailing not pair-to-pair interactions among agents, but rather field-like medium for the effective information exchange. The paper examines each approach consequently and gives some clues how merging of different approaches may contribute to the achievement of better communication results for GERP.
Modelling Anisotropic Viscoelasticity for Real-Time Soft Tissue Simulation
Authors: Zeike A. Taylor, Olivier Comas, Mario Cheng, Josh Passenger, David J. Hawkes, David Atkinson, Sébastien Ourselin
Venue: Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I (2008)

Previously almost all biomechanically-based time-critical surgical simulation has ignored the well established features of tissue mechanical response of anisotropy and time-dependence. We address this issue by presenting an efficient solution procedure for anisotropic visco-hyperelastic constitutive models which allows use of these in nonlinear explicit dynamic finite element algorithms. We show that the procedure allows incorporation of both anisotropy and viscoelasticity for as little as 5.1% additional cost compared with the usual isotropic elastic models. When combined with high performance GPU execution the complete framework is suitable for time-critical simulation applications such as interactive surgical simulation and intraoperative image registration.
Upper Bounds on the Noise Threshold for Fault-Tolerant Quantum Computing
Authors: Julia Kempe, Oded Regev, Falk Unger, Ronald Wolf
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

We prove new upper bounds on the tolerable level of noise in a quantum circuit. Our circuits consist of unitary k-qubit gates each of whose input wires is subject to depolarizing noise of strength p, and arbitrary one-qubit gates that are essentially noise-free. We assume the output of the circuit is the result of measuring some designated qubit in the final state. Our main result is that for $p>1-{\it \Theta}(1/\sqrt{k})$, the output of any such circuit of large enough depth is essentially independent of its input, thereby making the circuit useless. For the important special case of k = 2, our bound is p > 35.7%. Moreover, if the only gate on more than one qubit is the CNOT, then our bound becomes 29.3%. These bounds on p are notably better than previous bounds, yet incomparable because of the somewhat different circuit model that we are using. Our main technique is a Pauli basis decomposition, which we believe should lead to further progress in deriving such bounds.
A simulation model for stem cells differentiation into specialized cells of non-connective tissues
Authors: Massimo Pisu, Alessandro Concas, Sarah Fadda, Alberto Cincotti, Giacomo Cao
Venue: Computational Biology and Chemistry (2008)

A novel mathematical model to simulate stem cells differentiation into specialized cells of non-connective tissues is proposed. The model is based upon material balances for growth factors coupled with a mass-structured population balance describing cell growth, proliferation and differentiation. The proposed model is written in a general form and it may be used to simulate a generic cell differentiation pathway during in vitro cultivation when specific growth factors are used. Literature experimental data concerning the differentiation of central nervous stem cells into astrocytes are successfully compared with model results, thus demonstrating the validity of the proposed model as well as its predictive capability. Finally, sensitivity analysis of model parameters is also performed in order to clarify what mechanisms most strongly influence differentiation and cell types distribution.
Modeling Components and Component-Based Systems in KobrA
Authors: Colin Atkinson, Philipp Bostan, Daniel Brenner, Giovanni Falcone, Matthias Gutheil, Oliver Hummel, Monika Juhasz, Dietmar Stoll
Venue: The Common Component Modeling Example: Comparing Software Component Models (2007)

In this chapter we present a version of the Trading System case study modeled according to the KobrA approach. KobrA is a UML-based method for describing components and component-based systems developed at the Fraunhofer Institute for Experimental Software Engineering at the beginning of the decade. The acronym stands for the term "Komponenten basierte Anwendungsentwicklung" --- German for "Component-based Application Development". KobrA has been successfully used by a number of companies in industrial settings and has given rise to numerous specializations and offshoots (e.g. MARMOT [1] and MORABIT [2]). The original version of the method [3] was developed for the UML 1.x flavor of the UML, but in this chapter we introduce an updated version optimized for use with the 2.x versions of the UML [4] and its related standards such as OCL [5]. KobrA also provides support for other advanced software engineering approaches such as product-lines, but these are beyond the scope of this chapter. Here we focus on the component-modeling aspects of the method.
An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models
Authors: Carolina López-Nicolás, Francisco J. Molina-Castillo, Harry Bouwman
Venue: Information and Management (2008)

Today, in addition to traditional mobile services, there are new ones already being used, thanks to the advances in 3G-related technologies. Our work contributed to the emerging body of research by integrating TAM and Diffusion Theory. Based on a sample of 542 Dutch consumers, we found that traditional antecedents of behavioral intention, ease of use and perceived usefulness, can be linked to diffusion-related variables, such as social influence and perceived benefits (flexibility and status).
Practical, Fast and Simple Concurrent FIFO Queues Using Single Word Synchronization Primitives
Authors: Claude Evéquoz
Venue: Proceedings of the 13th Ada-Europe international conference on Reliable Software Technologies (2008)

We present an efficient and practical non-blocking implementation of a concurrent array-based FIFO queue that is suitable for preemptive multi threaded systems. It is well known that concurrent FIFO queues relying on mutual exclusion cause blocking, which have several drawbacks and degrade overall system performance. Link-based non-blocking queue algorithms have a memory management problem whereby a removed node from the queue can neither be freed nor reused because other threads may still be accessing the node. Existing solutions to this problem introduce a fair amount of overhead and are shown to be less efficient compared to array-based algorithms, which inherently do not suffer from this problem. In addition to being independent in advance knowledge of the number of threads that can access the queue, our new algorithm improves on previously proposed algorithms in that it does not re quire any special instruction other than a load-linked/store-conditional atomic instruction operating on pointer-wide number of bits.
Inbound Traffic Load Balancing in BGP Multi-homed Stub Networks
Authors: Xiaomei Liu, Li Xiao
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems (2008)

Multihoming load balancing improves network performance by leveraging the traffic among the access links in a multi-homed network. Currently, no effective load balancing system is available to handle the inbound traffic in a BGP multi-homed stub network, where the traffic volume is unknown to the network and the route of the traffic is hard to control. In this paper, we propose ILBO, an inbound traffic load balancing mechanism to effectively balance the inbound traffic in a BGP multi-homed stub network. ILBO predicts and schedules the inbound traffic based on outbound traffic. It also provides an inbound traffic control scheme that can guarantee the successful execution of the traffic scheduling.
The Heidelberg Polyp System
Authors: Reinhard Maenner, Richard Shoemaker, Peter Bartels
Venue: IEEE Micro (1987)

Comprising pools of processing elements interconnected by multiple global data buses, this multi-microprocessor allows its users to change the number of processing elements and the interconnection buses' bandwidth without having to change the system software.
Detecting Biomarkers for Major Adverse Cardiac Events Using SVM with PLS Feature Selection and Extraction
Authors: Zheng Yin, Xiaobo Zhou, Honghui Wang, Youxian Sun, Stephen T. Wong
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Detection of biomarkers capable of predicting a patient's risk of major adverse cardiac events (MACE) is of clinical significance. Due to the high dynamic range of the protein concentration in human blood, applying proteomics techniques for protein profiling can generate large arrays of data for development of optimized clinical biomarker panels. The objective of this study is to discover an optimized subset of biomarkers for predicting risk of MACE containing less than ten biomarkers. In this paper, we connect linear SVM with PLS feature selection and extraction. A simplified PLS algorithm selects a subset of biomarkers and extracts latent variables and prediction performance of linear SVM is dramatically improved. The proposed method is compared with a widely used PLS-Logistic Discriminant solution and several other reported methods based on the MACE prediction experiments.