ppxscal/embedding_network huggingface dataset:
Maximizing throughput in multi-queue switches
Authors: Yossi Azar, Arik Litichevskey
Venue: Algorithmica (2006)

We study a basic problem in Multi-Queue switches. A switch connectsm input ports to a single output port. Each input port is equipped with an incoming FIFO queue with bounded capacityB. A switch serves its input queues by transmitting packets arriving at these queues, one packet per time unit. Since the arrival rate can be higher than the transmission rate and each queue has limited capacity, packet loss may occur as a result of insufficient queue space. The goal is to maximize the number of transmitted packets. This general scenario models most current networks (e.g. IP networks) which only support a &#x201c;best effort&#x201d; service in which all packet streams are treated equally. A 2-competitive algorithm for this problem was designed in [5] for arbitraryB. Recently, a (17/9 &#x2248; 1.89)-competitive algorithm was presented forB>1 in [3]. Our main result in this paper shows that forB which is not too small our algorithm can do better than 1.89, and approach a competitive ratio ofe/(e &#x2212; 1) &#x2248; 1.58.
An Improved Method of Variable Structure Control for Uncertain Discrete-Time Systems
Authors: Yan-e Mao, Xia Chen, Zhen Luo, Yuanwei Jing, Siying Zhang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 01 (2007)

On the basis analysis of the design of sliding surface, some defects of the conventional methods are stated. To overcome the defects, an improved method of variable structure control for uncertain discrete-time systems is pre- sented. The equivalent control strategy is formed. Accord- ing to the improved method, the variable structure control systems lie on the sliding surface from the beginning of any initial state, and are robust to the parameter variations and disturbance. The simulation results illustrate that the im- proved method is feasible.
Architectural support for run-time validation of program data properties
Authors: Divya Arora, Srivaths Ravi, Anand Raghunathan, Niraj K. Jha
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2007)

As computer systems penetrate deeper into our lives and handle private data, safety-critical applications, and transactions of high monetary value, efforts to breach their security also assume significant dimensions way beyond an amateur hacker's play. Until now, security was always an afterthought. This is evident in regular updates to antivirus software, patches issued by vendors after software bugs are discovered, etc. However, increasingly, we are realizing the need to incorporate security during the design of a system, be it software or hardware. We invoke this philosophy in the design of a hardware-based system to enable protection of a program's data during execution, in this paper, we develop a general framework that provides security assurance against a wide class of security attacks. Our work is based on the observation that a program's normal or permissible behavior with respect to data accesses can be characterized by various properties. We present a hardware/software approach wherein such properties can be encoded as data attributes and enforced as security policies during program execution. These policies may be application-specific (e.g., access control for certain data structures), compiler-generated (e.g., enforcing that variables are accessed only within their scope), or universally applicable to all programs (e.g., disallowing WRITES to unallocated memory). We show how an embedded system architecture can support such policies by: 1) enhancing the memory hierarchy to represent the attributes of each datum as security tags that are linked to it throughout its lifetime and 2) adding a configurable hardware checker that interprets the semantics of the tags and enforces the desired security policies. We evaluated the effectiveness of the proposed architecture in enforcing various security policies for several embedded benchmark applications. Our experiments in the context of the Simplescalar framework demonstrate that the proposed solution ensures run-time validation of application-defined data properties with minimal execution time overheads.
Postsecondary Education & Autism: Developing an Online Community
Authors: Scott M. Robertson
Venue: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (2007)

This paper will discuss a research project to develop an online community that supports the transition from secondary to postsecondary education for autistic students. It first will highlight the impact of inadequate existing support resources for postsecondary education and autism. The paper will then share how semi-structured interviews with five key stakeholder groups will inform the development of the online community. Finally, the paper will discuss potential technological and social-cultural infrastructure for the community, as well as this project's long-term implications for academia and practice.
A Generalized Model for Mediator Based Information Integration
Authors: Ali Kiani, Nematollaah Shiri
Venue: Proceedings of the 11th International Database Engineering and Applications Symposium (2007)

Heterogeneity of schema and data in information integration complicates metadata management and query processing. We consider a mediator-based approach (MI) to information integration and propose a model theoretic approach to describe integration. In this model, we view the schema of the integration as a 3D space, and assume it is a complete lattice. The first dimension in the model specifies the concepts (e.g., entity sets, relations, classes, etc), the second dimension indicates the data model in which a concept is represented (e.g., relational, semi-structured, object-oriented, etc), and the third dimension gives the application domain. We also introduce three basic transformations, called X-transform, Y-transform, and Z-transform, to all of which we refer as primitive queries and show how user queries can be expressed using primitive queries. We show a typical architecture and illustrate usefulness of this model as it generalizes the mediator based information integration in which the global schema is basically the least upper bound of all the points in the 3D space.
Variable Weighted Combination Forecasting Model Based on Genetic Algorithm and Artificial Neural Network
Authors: Junfeng Li, Wenzhan Dai, Haipeng Pan
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

In this paper, the variable weight combination forecasting approach which both uses genetic algorithm with global searching ability and uses neural network with nonlinear mapping ability is put forward. First, the weight coefficients are gained by means of adaptive genetic algorithm. Second, the neural network is trained by weight -obtained and the intending weighted values are predicted further. The method has character that whole weighted values is positive and the summation of weight values at same time equals to 1. At last, the variable weight combination forecasting model is built and applied into forecasting total consumption expenditure in Shanghai GDP . Simulation shows the effectiveness of the proposed approach.
A method for linking computed image features to histological semantics in neuropathology
Authors: B. Lessmann, T. W. Nattkemper, V. H. Hans, A. Degenhard
Venue: Journal of Biomedical Informatics (2007)

In medical image analysis the image content is often represented by features computed from the pixel matrix in order to support the development of improved clinical diagnosis systems. These features need to be interpreted and understood at a clinical level of understanding Many features are of abstract nature, as for instance features derived from a wavelet transform. The interpretation and analysis of such features are difficult. This lack of coincidence between computed features and their meaning for a user in a given situation is commonly referred to as the semantic gap. In this work, we propose a method for feature analysis and interpretation based on the simultaneous visualization of feature and image domain. Histopathological images of meningiomas WHO (World Health Organization) grade I are represented by features derived from color transforms and the Discrete Wavelet Transform. The wavelet-based feature space is then visualized and explored using unsupervised machine learning methods. We show how to analyze and select features according to their relevance for the description of clinically relevant characteristics.
Study of Detection Technique Simulation of High Resolution Radar Based on BP Neural Network
Authors: Xuan Hou, Mingyi He
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Technology applying Neural Network to detection of high resolution radar is advised. Firstly, it analyses the principle of detection technique of high resolution radar and the conception of "Distance Corridor". Secondly, it introduces the basal principle of BP algorithm. The principle and structure of three layers BP Neural Network is analysed. Thirdly, the detection technology and algorithm of high resolution radar based on BP Neural Network is researched. The result of research of target detection technology based on BP Neural Network possesses superperformance, which is in view of Four Distance Corridor and Ten Distance Corridor, which are the Neural Network that possesses four input neurons and ten input neurons. At last, the research is carried out by Matlab, the result are visible and understandable.
How-To Web Pages
Authors: Cristen Torrey, David W. McDonald
Venue: Computer (2007)

How-to pages help anyone break it, fix it, or make it.
VoicePen: augmenting pen input with simultaneous non-linguisitic vocalization
Authors: Susumu Harada, T. Scott Saponas, James A. Landay
Venue: Proceedings of the 9th international conference on Multimodal interfaces (2007)

This paper explores using non-linguistic vocalization as an additional modality to augment digital pen input on a tablet computer. We investigated this through a set of novel interaction techniques and a feasibility study. Typically, digital pen users control one or two parameters using stylus position and sometimes pen pressure. However, in many scenarios the user can benefit from the ability to continuously vary additional parameters. Non-linguistic vocalizations, such as vowel sounds, variation of pitch, or control of loudness have the potential to provide fluid continuous input concurrently with pen interaction. We present a set of interaction techniques that leverage the combination of voice and pen input when performing both creative drawing and object manipulation tasks. Our feasibility evaluation suggests that with little training people can use non-linguistic vocalization to productively augment digital pen interaction.
Efficacious data cube exploration by semantic summarization and compression
Authors: Laks V. S. Lakshmanan, Jian Pei, Yan Zhao
Venue: Proceedings of the 29th international conference on Very large data bases - Volume 29 (2003)

Data cube is the core operator in data warehousing and OLAP. Its efficient computation, maintenance, and utilization for query answering and advanced analysis have been the subjects of numerous studies. However, for many applications, the huge size of the data cube limits its applicability as a means for semantic exploration by the user. Recently, we have developed a systematic approach to achieve efficacious data cube construction and exploration by semantic summarization and compression. Our approach is pivoted on a notion of quotient cube that groups together structurally related data cube cells with common (aggregate) measure values into equivalence classes. The equivalence relation used to partition the cube lattice preserves the roll-up/drill-down semantics of the data cube, in that the same kind of explorations can be conducted in the quotient cube as in the original cube, between classes instead of between cells. We have also developed compact data structures for representing a quotient cube and efficient algorithms for answering queries using a quotient cube for its incremental maintenance against updates. We have implemented SOCQET, a prototype data warehousing system making use of our results on quotient cube. In this demo, we will demonstrate (1) the critical techniques of building a quotient cube; (2) use of a quotient cube to answer various queries and to support advanced OLAP; (3) an empirical study on the effectiveness and efficiency of quotient cube-based data warehouses and OLAP; (4) a user interface for visual and interactive OLAP; and (5) SOCQET, a research prototype data warehousing system integrating all the techniques. The demo reflects our latest research results and may stimulate some interesting future studies.
Transformation of an Arbitrary Switching Function to a Totally Symmetric Function
Authors: S. S. Yau, Y. S. Tang
Venue: IEEE Transactions on Computers (1971)

It is known that any switching function can be written as a totally symmetric function with some of its variables being repetitive. In this note, the least upper bound for the number of variables of the transformed totally symmetric functions based on the partition on the set of variables induced by the partial symmetry of the given switching function is found, and a technique for obtaining a transformed totally symmetric function with the number of variables equal to the least upper bound is given.
Warehousing the world: a few remaining challenges
Authors: Torben Bach Pedersen
Venue: Proceedings of the ACM tenth international workshop on Data warehousing and OLAP (2007)

Data warehouses (DWs) have become very successful in many enterprises, but only for relatively simple and traditional types of data. It is now time to extend the benefits of DWs to a much wider range of data, making it feasible to literally "warehouse the world". To do this, five unique challenges must be addressed: warehousing data about the physical world, integrating structured, semi-structured, and unstructured data in DWs, integrating the past, the present, and the future, warehousing imperfect data, and ensuring privacy in DW.
Distribution Center Location Decision-making Based on PCA and Support Vector Machine Approach
Authors: Dongxiao Niu, Jinchao Li, Mian Xing
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Distribution centers location involves many factors, as a complicated systems engineering. A right location can get better economic benefit and society contribution. There are so many factors which influence the decision-making of the distribution center. Meanwhile there are relations between the factors because it's difficulty for us to set up an index system which only has independent indexes. In other words, eliminating an index at discretion may reduce the decision-making accuracy of the distribution centers location. But too many indexes will induce the complex of the computation. Thinking about the upper problems, the principal component analysis is introduced to deal with the indexes. It can form a new series of index which are independent among each other and reduce the index number. Then, the support vector machine was used to calculate the fit degree of the distribution center location. At last, it is validated that the results by SVM is feasible for decision-making.
Laplacian Regularized Least Squares Regression and its Dynamic Parameter Optimization for Near Infrared Spectroscopy Modeling
Authors: Hui-hua Yang, Feng Qin, Yong Wang, Qiong-lin Liang, Yi-ming Wang, Guo-an Luo
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Partial Least Square (PLS) is the most commonly used algorithm for Near Infrared (NIR) modeling. NIR modeling features that it's cheap, easy and fast to measure the NIR spectroscopy, while expensive, difficult and time- consuming to measure the reference value for this spectroscopy. PLS often faces the challenge of that limited samples are available in training set to build a predicative model. To tackle this problem, a novel NIR modeling method - Laplacian Regularized Least Squares Regression (LapRLSR) and its dynamically adaptive parameters optimization method was presented. Based on the semi-supervised learning framework, LapRLSR can take the advantage of many unlabeled spectra to promote the prediction performance of the model though there are only few labeled samples. The proposed LapRLSR modeling algorithm was applied to the online monitoring of the concentration of salvia acid B in the column separation procedure of TCM manufacturing, and the results demonstrated that its prediction capability outperformed PLS and Regularized Least Square Regression method.
An Alternative Product Extraction Method for E-Commerce Applications
Authors: Murat Koyuncu
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

Customers generally like to see alternative products and compare their characteristics and prices before deciding on one of them. Therefore, proposing alternative products is one of the crucial issues for e-commerce applications to increase customer satisfaction. This paper proposes a fuzzy similarity-based approach to determine similar products recorded in a database and submit them intelligently to the customer in a ranked way as alternative products.
Optimizing Network Configurations Based on Potential Profit Loss
Authors: Feng Zhao, Peidong Zhu, Meng Wang, Baosheng Wang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

IP routing protocols, such as OSPF (Open Shortest Path First) or BGP (Border Gateway Protocol), have many configurable parameters (e.g., timers) and interact with each other in complex ways. Network operators may need to explore numerous candidate configuration changes before identifying a choice. In this paper, from the point of view of the economics of the Internet backbone, we propose a potential profit loss metric to evaluate configurations. Then we focus on analyzing the potential profit loss caused by link state changes under different configurations. We give quantitative relations between the potential profit loss and the major influential factors: OSPF timers, BGP timers and failure duration. From the quantitative relations we can see that appropriate configurations can reduce the profit loss much.
Multi-neural Networks Control of Marine Diesel Engine Generator Set
Authors: Weifeng Shi
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

For multi-variable control system of voltage and frequency of marine diesel engine generator set, multiple CMAC neural networks (NN) controllers are designed and applied in system control according to principle of mapping connection and learning rule of CMAC NN. The CMAC NN control algorithm is provided with ability of fast learning rate on line. In control realizing process, the inverse dynamic model of object control system was obtained by multiple CMAC NN through learning. This model is a general approach model. The simulation results of the responses of generator load testing indicated that the quality is well in coordinate between two CMAC NN control loops.
Error Correction in High-Speed Arithmetic
Authors: R. T. Chien
Venue: IEEE Transactions on Computers (1972)

In high-speed multipliers, multiplication is activated by processing a group of bits in parallel. As a result, any defects in circuitry produce possible errors in positions that are separated by fixed periods. A class of codes for the correction of such iterative error patterns resulting from a single fault is presented in this paper. A decoding algorithm together with a simple implementation scheme is also discussed.
A note on problem difficulty measures in black-box optimization: Classification, realizations and predictability
Authors: Jun He, Colin Reeves, Carsten Witt, Xin Yao
Venue: Evolutionary Computation (2007)

Various methods have been defined to measure the hardness of a fitness function for evolutionary algorithms and other black-box heuristics. Examples include fitness landscape analysis, epistasis, fitness-distance correlations etc., all of which are relatively easy to describe. However, they do not always correctly specify the hardness of the function. Some measures are easy to implement, others are more intuitive and hard to formalize. This paper rigorously defines difficulty measures in black-box optimization and proposes a classification. Different types of realizations of such measures are studied, namely exact and approximate ones. For both types of realizations, it is proven that predictive versions that run in polynomial time in general do not exist unless certain complexity-theoretical assumptions are wrong.
New materials of spin-on organic hardmask for sub-70nm devices
Authors: Sang-Jun Choi, Chang-Il Oh, Dong-Seon Uh
Venue: Microelectronic Engineering (2007)

In ArF lithography for sub-80nm L/S, amorphous carbon layer (ACL) deposition becomes an inevitable process, because thin ArF resist itself cannot provide suitable etch selectivity to sub-layers. One of the problems of the ACL hardmask is the presence of surface particles, which are more problematic in mass production. Limited capacity, high cost-of-ownership, and low process efficiency also make ACL hardmasks a dilemma, which cannot be ignored by device makers. One of the answers to these problems is using a spin-on organic hardmask (SOH) material instead of ACL hardmask. Therefore, several processes including bi-layer resist process, tri-layer resist process (TLR), and multi-layer resist process have been investigated. In this paper, we have described new SOH materials applicable to 70nm memory devices. Applications to the TLR were investigated in terms of photo property, etch property and process compatibility. Based on the test results described in this paper, our spin-on organic hardmask materials are expected to be used in mass production.
Intelligent Cultural Advisor System: an interactive On-line Culture Guidebook
Authors: Harry Zhou
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

International visitors in a foreign country often run into an unfamiliar situation and needs to know how to handle it appropriately in the context of a particular culture. This paper describes the development of an intelligent Cultural Advisor online System tested in the domain of Iraqi culture. With a knowledge base, a database, and a case base, this system assumes the role of a hypothetical cultural advisor simulating a local resident in a particular society. It can give advice, upon request, on the topics including but not limited to history, religion, social customs, ethnicity, geography and beliefs.
Some Frills for Modal Tic-Tac-Toe: Semantics of Predicate Complement Constructions
Authors: A. K. Joshi
Venue: IEEE Transactions on Computers (1976)

Predicate complement constructions are a rich source of semantic problems. A system for testing the semantic properties (presuppositions and entailments) of predicate complement constructions has been constructed, and, in particular, the implementations of these constructions have been explored in some detail in the context of the tic-tac-toe game-playing setting of Isard and Longuet-Higgins [2] and Davies and Isard [1]. Even in such a limited setting, the implementations of many of these constructions (especially composite predicate complement constructions) are nontrivial, suggesting that such restricted settings provide a good testing ground for many key linguistic problems.