ppxscal/embedding_network huggingface dataset:
An integrated JIT-PQD model for enhancing buyer-supplier linkage
Authors: C.-T. Chang
Venue: International Journal of Systems Science (2007)

Price-quantity discount (PQD) is when suppliers often reduce the unit-purchasing price for large orders to increase their benefits. However, with the adoption of just-in-time (JIT) philosophy, buyers are encouraged to purchase material in small lots to synchronize production with deliveries. Thus, buyers find it difficult to obtain the benefits from both JIT and PQD simultaneously. This paper proposes an integrated JIT-PQD model for enhancing buyer-supplier linkage in which buyers need not abandon either JIT and PQD but suppliers can increase their benefits. Furthermore, the integrated JIT-PQD model allows resource constraints to be added by the decision-maker as deemed appropriate in real-world situations. To demonstrate the usefulness of the proposed method an illustrative example is included.
Framework for Intrusion Tolerant Certification Authority System Evaluation
Authors: Jingqiang Lin, Jiwu Jing, Peng Liu
Venue: Proceedings of the 26th IEEE International Symposium on Reliable Distributed Systems (2007)

Various intrusion tolerant certification authority (CA) systems have been recently proposed to provide attack resistant certificate update/query services. However, it is difficult to compare them against each other directly due to diversity in system organizations, threshold cryptography schemes, protocols and usage scenarios. We present a framework for intrusion tolerant CA system evaluation, which consists of three components, namely, an intrusion tolerant CA model, a threat model and a metric for comparative evaluation. The framework covers system organizations, protocols, usage scenarios, period of certificate validity, revocation rate and mean time to recovery (MTTR). Based on the framework, four representative CA systems are evaluated and compared in three typical usage scenarios, producing reasonable and insightful results. The inter-dependency between usage scenarios and system characteristics is investigated, providing a guideline to design better systems for different usage scenarios. The proposed framework provides an effective method to evaluate intrusion tolerant CA systems quantitatively. Moreover, the comparison results offer valuable insights to further improve the attack resilience of intrusion tolerant CA systems.
An optimal algorithm to fetch DHT routable
Authors: Yong-xiang Zhao, Chang-jia Chen
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

During recent years, Distributed Hash Tables (DHTs) have been a hot topic in P2P community. Route table of each peer is the key component to ensure high performance and scalability for DHT network. Hence to measure peer's route table in real network is an important research topics for evaluation the performance and for understanding the structure of real network. A splitting tree like algorithm named as APQ (Adaptive Prefix Query) has been developed to get node routable. We will show APQ is an optimal algorithm in sense of worst-case query numbers.
Layout-Aware Multi-Layer Multi-Level Scan Tree Synthesis
Authors: Sying-Jyan Wang, Xin-Long Li, Katherine Shu-Min Li
Venue: Proceedings of the 16th Asian Test Symposium (2007)

In this paper, we propose a layout-aware scan tree synthesis methodology. Scan tree can greatly reduce test data volume, which is very desirable in SOC testing. However, previous researches on scan tree synthesis have not considered routing issues in physical design, which may create a tree with excessively long routing path. In this paper we present a multi-layer multi-level scan tree synthesis method, in which both data compression and routing length are taken into account. Experimental results show that the proposed test method achieves high compression rate with limited routing overhead.
GA-Based Learning Algorithms to Identify Fuzzy Rules for Fuzzy Neural Networks
Authors: K. Almejalli, K. Dahal, A. Hossain
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

Identification of fuzzy rules is an important issue in designing of a fuzzy neural network (FNN). However, there is no systematic design procedure at present. In this paper we present a genetic algorithm (GA) based learning algorithm to make use of the known member- ship function to identify the fuzzy rules form a large set of all possible rules. The proposed learning algorithm initially considers all possible rules then uses the training data and the fitness function to perform rule- selection. The proposed GA based learning algorithm has been tested with two different sets of training data. The results obtained from the experiments are promis- ing and demonstrate that the proposed GA based learning algorithm can provide a reliable mechanism for fuzzy rule selection.
On the use of mobile tools in everyday life
Authors: Jason Pascoe, Kirsten Thomson
Venue: Proceedings of the 19th Australasian conference on Computer-Human Interaction: Entertaining User Interfaces (2007)

This paper explores how mobile tools are used in everyday life and investigates the issues surrounding their usage, or indeed, their lack of usage. Personal computers support us in a wide range of our desk-bound activities, but there is still relatively little use of computer-based tools in other parts of our day-to-day lives. We hypothesise that this is because certain barriers-to-use exist that discourage their use in everyday environments, namely that the tools are not readily to hand at the time of need and/or that they distract the user's attention too much from the surrounding environment or main task at hand. We briefly present our concept of a Smartwatch -- a wrist-worn form of a general-purpose wearable computer -- that aims to overcome these barriers. However, we strongly believe that a prerequisite to the successful development of this, and other types of mobile devices, is a better understanding of the use, or disuse, of mobile tools in everyday life (including traditional and paper-based solutions). To gain this understanding we conducted a diary study in which a group of twelve volunteers recorded their usage of mobile tools over a period of 2 days. With the large volume of data that was collected we performed a qualitative analysis based on grounded theory techniques, resulting in a comprehensive and detailed picture of the use of mobile tools in everyday life. From this understanding we have drawn out nine key themes which we present in some detail in this paper, including: situational versus portability strategies, the mobility of information, new behaviours derived from mobile phone usage, the importance of creative expression, concern over privacy and security issues, and the demonstrated existence of the barriers-to-use.
A Combined Genetic Algorithm and Orthogonal Transformation for Designing Feedforward Neural Networks
Authors: Jinhua Xu, Yue Lu, Daniel W. C. Ho
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

In this paper, a hybrid algorithm is proposed for designing feedforward neural networks. A genetic algorithm is used to tune the connections and parameters between the input layer and the hidden layer, and orthogonal transformation is applied to tune the connections and parameters between the hidden layer and the output layer. In this way, both the structure and parameters of a neural network can be optimized efficiently. Simulations are presented to demonstrate the effectiveness of the proposed approach.
Toward content-aware multimodal tagging of personal photo collections
Authors: Paulo Barthelmess, Edward Kaiser, David R. McGee
Venue: Proceedings of the 9th international conference on Multimodal interfaces (2007)

A growing number of tools is becoming available, that make use ofexisting tags to help organize and retrieve photos, facilitating the management and use of photo sets. The tagging on which these techniques rely remains a time consuming, labor intensive task that discourages many users. To address this problem, we aim to leverage the multimodal content of naturally occurring photo discussions among friends and families to automatically extract tags from a combination of conversational speech, handwriting, and photo content analysis. While naturally occurring discussions are rich sources of informationabout photos, methods need to be developed to reliably extract a set of discriminative tags from this noisy, unconstrained group discourse. To this end, this paper contributes ananalysis of pilot data identifying robust multimodal features examining the interplay between photo content and other modalities such as speech and handwriting. Our analysis is motivated by a search for design implications leading to the effective incorporation of automated location and person identification(e.g. based on GPS and facial recognition technologies) into a system able to extract tags from natural multimodal conversations.
Automatic Quality Assessment of SRS Text by Means of a Decision-Tree-Based Text Classifier
Authors: Ishrar Hussain, Olga Ormandjieva, Leila Kosseim
Venue: Proceedings of the Seventh International Conference on Quality Software (2007)

The success of a software project is largely dependent upon the quality of the Software Requirements Specification (SRS) document, which serves as a medium to communicate user requirements to the technical personnel responsible for developing the software. This paper addresses the problem of providing automated assistance for assessing the quality of textual requirements from an innovative point of view, namely through the use of a decision- tree-based text classifier, equipped with Natural Language Processing (NLP) tools. The objective is to apply the text classification technique to build a system for the automatic detection of ambiguity in SRS text based on the quality indicators defined in the quality model proposed in this paper. We believe that, with proper training, such a text classification system will prove to be of immense benefit in assessing SRS quality. To the authors' best knowledge, ours is the first documented attempt to apply the text classification technique for assessing the quality of software documents.
Auditing compliance with a Hippocratic database
Authors: Rakesh Agrawal, Roberto Bayardo, Christos Faloutsos, Jerry Kiernan, Ralf Rantzau, Ramakrishnan Srikant
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

We introduce an auditing framework for determining whether a database system is adhering to its data disclosure policies. Users formulate audit expressions to specify the (sensitive) data subject to disclosure review. An audit component accepts audit expressions and returns all queries (deemed "suspicious") that accessed the specified data during their execution. The overhead of our approach on query processing is small, involving primarily the logging of each query string along with other minor annotations. Database triggers are used to capture updates in a backlog database. At the time of audit, a static analysis phase selects a subset of logged queries for further analysis. These queries are combined and transformed into an SQL audit query, which when run against the backlog database, identifies the suspicious queries efficiently and precisely. We describe the algorithms and data structures used in a DB2-based implementation of this framework. Experimental results reinforce our design choices and show the practicality of the approach.
On Computing Strength of Evidence for Writer Verification
Authors: H. Srinivasan, S. Kabra, C. Huang, S. Srihari
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02 (2007)

The problem of Writer Verification is to make a decision of whether or not two handwritten documents are written by the same person. Providing a strength of evidence for any such decision is an integral part of the writer verifi- cation problem. The strength of evidence should incorpo- rate (i) The amount of information compared in each of the two documents (line/half page/full page etc.), (ii) The na- ture of content present in the document (same/different con- tent), (iii) Features used for comparison and (iv) The error rate of the model used for making the decision. This pa- per describes the statistical model used for writer verifica- tion and also introduces a mathematical formulation to in- clude the above four mentioned parameters, for calculating strength of evidence of same/different writer. The statisti- cal model uses Gamma and Gaussian densities to paramet- rically model the distance space distribution arising from comparing ensemble of pairs of documents. The strength of evidence is mapped to a 9-point qualitative scale for the decision; one that is often used by questioned document ex- aminers. Experiments and results show that with increase in information content from just a single word to a full page of document, the verification accuracy of the model increases.
Software maintenance project delays prediction using Bayesian Networks
Authors: Ana C. V. de Melo, Adilson J. Sanchez
Venue: Expert Systems with Applications: An International Journal (2008)

Managing software maintenance is rarely a precise task due to uncertainties concerned with resources and services descriptions. Even when a well-established maintenance process is followed, the risk of delaying tasks remains if the new services are not precisely described or when resources change during process execution. Also, the delay of a task at an early process stage may represent a different delay at the end of the process, depending on complexity or services reliability requirements. This paper presents a knowledge-based representation (Bayesian Networks) for maintenance project delays based on specialists experience and a corresponding tool to help in managing software maintenance projects.
Dissent in a Majority Voting System
Authors: S. L. Hight
Venue: IEEE Transactions on Computers (1973)

The reliability of digital computing systems is a significant problem. A scheme using multiply redundant computing devices with a majority voting device to determine the output has been shown to improve the reliability of that output. In this paper, a devices called a dissent detector is suggested as an addition to the system. The function of this device is that of an alarm to indicate the quality of the information (likelihood that the information is correct). Dissent is defined as a family of logic functions that compare the outputs of the voters to the output of the majority gate and report the disagreement or degree of disagreement that takes place. The operation of a dissent-detector that reports any disagreement in a triplicated majority voting system is demonstrated by example. The example illustrates the importance of the dissent information to the conditional reliability of the output of the majority gate. The results show that, with very little additional equipment, the conditional reliability of a majority voting system can be greatly enhanced. In fact, the conditional reliability of the example system exceeds the reliability of any of the system components, including the majority gate and the dissent detector.
Text Clustering Algorithm Based on Lexical Graph
Authors: Yun Sha, Guoying Zhang, Huina Jiang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

Text clustering methods can group text into thematic clusters, which is an important topic in many fields, such as search engine. The well-known methods of text clustering, however, do not really address the special problems of text clustering because of the very high dimensionality data and understandability of the cluster description. An algorithm for text clustering based on lexical graph is proposed in this paper, which is a kind of term-based cluster method. The lexical graph is build with nodes representing words and edges representing their concurrent in text. The attribute of each node is text which the word occurs in. A cluster center is defined as node (word) with large degree in this graph, the center attributes (text occurs in) and its neighbors' are partitioned to one cluster whose description is the center node. This approach reduces drastically the dimensionality of the data and improves the synonymy extension ability. An experimental evaluation on web documents as well as classical text documents on demonstrates that the proposed algorithms obtain clustering of comparable quality significantly more efficiently than K-Means and STC algorithms on the search results data set. Furthermore, this method provides an understandable description of the discovered clusters by their center.
Handheld Device Oriented Adaptation Disposal for Web Access
Authors: Liu Baolin, Xin Shuai, Aimin Liang, Tieshuai Li
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

In mobile environment, because of the handheld devices' capability limitation and diversity, content adaptation becomes an essential technology for web services. In this paper, adaptation for handheld device's web access is studied. For solving the JSP resource-wrapping problem, a document type definition (DTD) is given for device independent page markup language (DIML)[1]. The problem for collecting the properties and the environment context of devices is solved by defining DTM (Device logical traits modeling). Finally we describe the adaptationprocessing algorithm by using DIML and DTM, and solve the problem for adaptation of massive HTML pages of Java-based web servers.
Query rewrite for XML in Oracle XML DB
Authors: Muralidhar Krishnaprasad, Zhen Hua Liu, Anand Manikutty, James W. Warner, Vikas Arora, Susan Kotsovolos
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Oracle XML DB integrates XML storage and querying using the Oracle relational and object relational framework. It has the capability to physically store XML documents by shredding them as relational or object relational data, and creating logical XML documents using SQL/XML publishing functions. However, querying XML in a relational or object relational database poses several challenges. The biggest challenge is to efficiently process queries against XML in a database whose fundamental storage is table-based and whose fundamental query engine is tuple-oriented. In this paper, we present the 'XML Query Rewrite' technique used in Oracle XML DB. This technique integrates querying XML using XPath embedded inside SQL operators and SQL/XML publishing functions with the object relational and relational algebra. A common set of algebraic rules is used to reduce both XML and object queries into their relational equivalent. This enables a large class of XML queries over XML type tables and views to be transformed into their semantically equivalent relational or object relational queries. These queries are then amenable to classical relational optimisations yielding XML query performance comparable to relational. Furthermore, this rewrite technique lays out a foundation to enable rewrite of XQuery [1] over XML.
Disaster recovery codes: increasing reliability with large-stripe erasure correcting codes
Authors: Kevin M. Greenan, Ethan L. Miller, Thomas J. E. Schwarz, Darrell D.E. Long
Venue: Proceedings of the 2007 ACM workshop on Storage security and survivability (2007)

Large-scale storage systems need to provide the right amount of redundancy in their storage scheme to protect client data. In particular, many high-performance systems require data protection that imposes minimal impact on performance; thus, such systems use mirroring to guard against data loss. Unfortunately, as the number of copies increases, mirroring becomes costly and contributes relatively little to the overall system reliability. Compared to mirroring, parity-based schemes are space-efficient, but incur greater update and degraded-mode read costs. An ideal data protection scheme should perform similarly to mirroring, while providing the space efficiency of a parity-based erasure code. Our goal is to increase the reliability of systems that currently mirror data for protection without impacting performance or space overhead. To this end, we propose the use of large parity codes across two-way mirrored reliability groups. The secondary reliability groups are defined across an arbitrarily large set of mirrored groups, necessitating a small amount of non-volatile RAM for parity. Since each parity element is stored in non-volatile RAM, our scheme drastically increases the mean time to data loss without impacting overall system performance.
A Program of Continuing Education in Applied Computer Science
Authors: R. Hinderliter
Venue: Computer (1981)

This existing curriculum presents state-of-the-art material to MS-level technical staff with no formal computer science background. Cooperation between industry and academia made it work.
Intelligent Control of a Flexible Manipulator Using a Robust Controller
Authors: Lingli Cui, Jianyu Zhang, Lixin Gao
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

This paper addresses the issues related to the design of robust controller using intelligent optimization algorithms for lightweight, one-link flexible manipulators working under dynamic environments and other uncertain influences. By selecting the controller coefficients properly using the intelligent genetic method, an improved robust controller design is developed to ensure robustness of manipulator control systems for varying payloads and other modeling uncertainties. Numeric simulation has been conducted and the results have demonstrated the effectiveness of the proposed method.
An Efficient H.264 Rate Control Scheme with Accurate \theta Estimation
Authors: Qingde Chen, Dong Hu
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

An efficient rate control scheme for H.264 encoding has been proposed, where \rho domain source modeling, which was first used in block-based DCT coding system such as H.263, MPEG-2 and MPEG-4, is introduced. For accurate rate control, parameter \theta, the slope of the linear function of bit rate R vs. \rho, should be estimated in advance for each frame. Least-Mean- Square (LMS) algorithm is adopted for the estimation of \theta, which is further refined by a new factor \theta-ratio for each frame. Simulation results for standard test sequences show that, compared with JVT-H017, the new algorithm achieves better coding performance, while the output bit rates are more accurate.
Analysis of 3D Face Reconstruction
Authors: S. Hassan Amin, Duncan Gillies
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

3D shape reconstruction from 2D images is an inverse problem, and is therefore mathematically illposed. One solution to 3D shape reconstruction problem is to use a model based approach. This paper presents an analysis by synthesis method for solving 3D face reconstruction problems using anatomical landmarks and intensity from 2D frontal face images. To improve the quality of 3D shape reconstruction we incorporate a number of steps in analysis by synthesis framework. Firstly, we approach the 3D model construction problem by using rigid and non rigid surface registration. Secondly, we simplify the shape estimation by using multidimensional amoeba optimization to optimize shape parameters while mapping texture directly using 3D-2D alignment. Thirdly, we evaluate the quality of the 3D shape reconstruction in the context of 3D shape error as well as by visual analysis.