ppxscal/embedding_network huggingface dataset:
Affixal Approach for Arabic Decomposable Vocabulary Recognition: A Validation on Printed Word in Only One Font
Authors: Slim KANOUN, Adel Mohamed ALIMI, Yves LECOURTIER
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

We propose a new approach for Arabic word recognition called affixal approach. This approach is founded on morphological structure of Arabic vocabulary. A mechanism of decompositionrecognition is used in our approach and makes it possible to lead to a set of reliable solutions for each word. This mechanism tries to recognize word basic morphemes: prefix, infix, suffix and root contrary to existing approaches which are usually based on recognition of word entity by holistic approach, pseudo-word entity by pseudo-analytical approach or letter entity by analytical approach. In this paper, we will present limits of existing approaches for Arabic word recognition. We will expose then Arabic vocabulary structure. We will detail after affixal approach for Arabic decomposable vocabulary recognition with a word example. Lastly, we will expose experimental results obtained on a basis of 1000 words data set.
Augmenting collaboration through situated representations of scientific knowledge
Authors: Mark N. Gahegan
Venue:  (2005)

Information systems that support scientific collaboration often facilitate the sharing of tangible resources, such as data files, as a proxy for sharing the knowledge embedded in or emerging from those resources. Current computational aids to science work thus do little to support knowledge-based inquiry; the human knowledge that creates meaning out of analyses is often only recorded when work reaches publication&mdash;or worse, left unrecorded altogether&mdash;for lack of an abstract model for scientific concepts that can capture knowledge as it is created and used. In this research, concepts rather than datasets are treated as the primitive elements of scientific inquiry. A model for scientific concepts is developed that incorporates representation of (1) the situated processes of science work, (2) the social construction of knowledge, and (3) the emergence and evolution of understanding over time. In this model, knowledge is the result of collaboration, negotiation, and manipulation by teams of researchers. Capturing the situations in which knowledge is created and used helps these collaborators discover areas of agreement and discord, while allowing individual inquirers to maintain different perspectives on the same information. The capture of provenance information allows historical trails of reasoning to be reconstructed, revealing the process by which knowledge is adopted, revised, and reused in a community. This work leverages advancement in the areas of cyberinfrastructure and the Semantic Web to produce a proof-of-concept system, called Codex, based on this situated knowledge model. Codex supports visualization of knowledge structures and inference across those structures. The proof-of-concept is deployed in two collaborative application contexts, human-environment interaction and geoscience. These use cases demonstrate the viability of Codex to support distributed teams of learners and researchers by encouraging greater appreciation for shared understanding.
Link Scheduling with Power Control for Throughput Enhancement in Multihop Wireless Networks
Authors: Jian Tang, Guoliang Xue, Christopher Chandler, Weiyi Zhang
Venue: Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

Throughput is an important performance consideration for multihop wireless networks. In this paper, we study the joint link scheduling and power control problem, focusing on maximizing the network throughput.We formulate the MAximum THroughput link Scheduling with Power Control (MATH-SPC) problem, and present a Mixed Integer Linear Programming (MILP) formulation to provide optimal solutions. However, simply maximizing the throughput leads to a severe bias on bandwidth allocation among all links. In order to enhance both throughput and fairness, we define a new parameter, the Demand Satisfaction Factor (DSF), to characterize the fairness of bandwidth allocation. We formulate the MAximum Throughput fAir link Scheduling with Power Control (MATA-SPC) problem and present an MILP formulation for this problem. We also present an effective polynomial time heuristic algorithm, namely, the Serial LP Rounding (SLPR) heuristic. Our numerical results show that bandwidth can be fairly allocated among all links/flows by solving our MATA-SPC formulation or using our heuristic algorithm at the cost of a minor reduction of network throughput.
Distributed delay constrained multicast routing algorithm with efficient fault recovery
Authors: Hasan Ural, Keqin Zhu
Venue: Networks (2006)

Existing distributed delay constrained multicast routing algorithms construct a multicast tree in a sequential fashion and need to be restarted when failures occur during the multicast tree construction phase or during an on-going multicast session. This article proposes an efficient distributed delay constrained multicast routing algorithm that constructs a multicast tree in a concurrent fashion by taking advantage of the concurrency in the underlying distributed computation. The proposed algorithm has a message complexity of O(mn) and time complexity of O(n) in the worst case, where m is the number of destinations and n is the number of nodes in the network. It constructs multicast trees with the same tree costs as the ones constructed by well-known algorithms such as DKPP and DSHP while utilizing 409 to 1734 times fewer messages and 56 to 364 times less time than these algorithms under comparable success rate ratios. The proposed algorithm has been augmented with a fault recovery mechanism that efficiently constructs a multicast tree when failures occur during the tree construction phase and recovers from any failure in the multicast tree during an on-going multicast session without interrupting the running traffic on the unaffected portion of the tree. &copy; 2005 Wiley Periodicals, Inc. NETWORKS, Vol. 47(1), 37&ndash;51 2006
To do or not to do: If the requirements engineering payoff is so good, why aren"t more companies doing it?
Authors: Daniel M. Berry, Daniela Damian, Anthony Finkelstein, Don Gause, Robert Hall, Alan Wassyng
Venue: Proceedings of the 13th IEEE International Conference on Requirements Engineering (2005)

The by an author¿s name means that the author plans to be present at the panel session. RE researchers have noted time and again the difficulty of technology transfer, that of getting technology that RE research has developed and found useful to be used in industrial practice. The numerous panels we have had over the years on this subject are proof of the pervasiveness and permanence of this problem. One thing that keeps many software-development organizations from doing serious requirements engineering before beginning development is the perception that doing requirements engineering wastes time and delays getting on to the real work, designing and programming. Many a manager says, "I know that we should work out the requirements in detail, but we don¿t have time. We have to get started on the programming because we have a short deadline to deliver the code!". He or she says this despite all the evidence out there that each day spent in thrashing out requirement details leads to a reduction of up to 10 days in development time because of the reduction in the errors programmed into the code and the resultant reduction in both programming time and testing time. A relevant quotation in this respect is that of Trevor Devon of fizer, "Weeks of coding can save hours of planning". When confronted with this evidence, the average manager relies on his or her gut feelings that says that if the beginning of coding is delayed by n days, then the completion of coding is delayed by more than n days. Therefore, it¿s best to get started coding as soon as possible. Therefore, the first third of this panel is a series of 5- minute talks presenting anecdotal and case study evidence that upfront RE pays off big. When an author is not present, someone else presents his slides. 1. Daniel Berry: Overview of Theme
Implementing computer assisted instruction in a multilevel-multigraded classroom evaluation/action plan
Authors: Harold E. Vietti
Venue:  (2005)

Under the requirements of Standards-Based-Instruction (SBI), it is difficult to insure that multigrade, multilevel classroom teachers have enough time in the instructional day and year to teach all of the required state standards to each student at each grade level. Two areas in which demands are greater include (1) increased workload and (2) more complex class organization time. For multi-graded classroom teachers to be successful under the demands of standards based instruction, it is imperative that teachers have the proper tools and environment to provide student centered individualized instruction. This study provides evidence that Computer Assisted Instruction (CAI) is an effective tool that can create an instructional environment that provides time for teachers to deliver grade level standards and individualized instruction in mathematics. Pre and post-test data indicated that students improved their math scores by a substantial amount. Though the improvement in scores showed no statistical difference, meaning the study could not be generalized to larger populations, due to the small sample size of 28, the calculated improvement in scores did show practical significance (effect size > .5) indicating that the improvement in scores had a positive effect on student learning for the group studied. Also more importantly, is that the teachers felt and believed that their students were improving their skills based on the observed results. Surveys of students, teachers and parents, indicated that CAI provided increased student motivation through the use of a variety of techniques and activities provided in the software programs. By allowing students to work at their own pace, the students experienced less frustration by being &ldquo;held back&rdquo; or frantically trying to keep up as in the case of a slower learner. Teacher interviews indicated that CAI released them from the burden of instructional delivery. They also indicated that they could customize the curriculum to match learners' developmental needs as well as personal interests. The most pervasive perception among the teachers surveyed is that computers have improved the climate for learning by increasing student motivation in mathematics for which they used computers.
An Efficient Solution to Factor Drifting Problem in the pLSA Model
Authors: Liang Zhang, Chaoran Li, Yanfei Xu, Baile Shi
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

Probabilistic Latent Semantic Analysis (pLSA) is a powerful statistical technique to analyze relation between factors in dyadic data Although various pLSA-based applications, ranging from information retrieval, information filtering, to text-mining and visualization, have been successfully conducted, they can not afford dynamic revising of model when one of the factors changes constantly. In this paper, we take the advantage of decoupling ability of pLSA thoroughly, and propose a more elegant approach based on maximum likelihood estimation to gain an incremental learning with the drift of a factor. We demonstrate our method in the context of collaborative filtering where single user interests change fast, but the community interests remain almost constant. Experiments against the MovieLens and EachMovie data sets reveal that the proposed method improves the recommending accuracy 10% further beyond the original pLSA at a less computation cost.
Predictive low-rank decomposition for kernel methods
Authors: Francis R. Bach, Michael I. Jordan
Venue: Proceedings of the 22nd international conference on Machine learning (2005)

Low-rank matrix decompositions are essential tools in the application of kernel methods to large-scale learning problems. These decompositions have generally been treated as black boxes---the decomposition of the kernel matrix that they deliver is independent of the specific learning task at hand---and this is a potentially significant source of inefficiency. In this paper, we present an algorithm that can exploit side information (e.g., classification labels, regression responses) in the computation of low-rank decompositions for kernel matrices. Our algorithm has the same favorable scaling as state-of-the-art methods such as incomplete Cholesky decomposition---it is linear in the number of data points and quadratic in the rank of the approximation. We present simulation results that show that our algorithm yields decompositions of significantly smaller rank than those found by incomplete Cholesky decomposition.
A simulation-based study of wireless sensor network middleware
Authors: Matthew Wolenetz
Venue: International Journal of Network Management (2005)

Future wireless sensor networks (WSNs) will transport high-bandwidth, low-latency streaming data, and will host sophisticated processing, such as image fusion and object tracking, in-network on sensor network nodes. Recent middleware proposals provide capabilities for in-network processing, reducing energy drain based on communication costs alone. However, hosting complex processing on WSN nodes incurs additional processing energy and latency costs that impact network lifetime and application performance. There is a need for a WSN planning framework to explore energy saving and application performance trade-offs for models of future sensor networks that account for processing costs in addition to communication costs. In this work, we present a simulation framework to analyze the interplay between resource requirements for compute-and communication-intensive in-network processing for streaming applications. We simulate a surveillance application workload with middleware capabilities for data fusion, adaptive policy-driven migration of data fusion computation across network nodes, and prefetching of streaming data inputs for fusion processing. Our study sheds light on application figures of merit such as latency, throughput, and lifetime with respect to migration policy and node CPU and radio characteristics.
Adaptive Chip-Level Channel Estimation for IMT-DS System: DL and UL
Authors: S. Faisal Shah, Asrar U. Sheikh
Venue: Wireless Personal Communications: An International Journal (2005)

In this paper, chip-level adaptive channel estimation has been explored by using LMS algorithm for wideband CDMA channel estimation. The expression for the optimum step-size is modified for fading channel estimation problem. In addition, a new method is proposed to obtain channel estimates with known pilot symbols which is found to give better results than other methods. For slow fading channels, like pedestrian channel, LMS estimator with no update mode is found to give satisfactory results. For fast fading channels, like vehicular channel, a common decision directed technique of channel estimation is modified to be used at chip-level in the downlink (DL). A novel despreader-respreader based channel estimator has been proposed to obtain uplink channel estimates at chip level which resolves the deficiencies of conventional methods. The performance of Rake receiver with proposed channel estimation schemes for IMT-DS system --- a 3G mobile communication standard --- is evaluated in terms of BER.
Heterogenous Committees with Competence Analysis
Authors: Norbert Jankowski, Krzysztof Grabczewski
Venue: Proceedings of the Fifth International Conference on Hybrid Intelligent Systems (2005)

We explore some new types of committees in search of hybrid models successful in many different classification benchmarks. To provide a reliable comparison of the ensembles we restrict the task to some constant configuration of committee members for each benchmark. We were looking for new types of committees which, in such configuration, would be as much accurate and stable as possible. The paper focuses on some ideas of heterogenous committees with different ways of their members competence estimation. Heterogenous committee members adapt in different ways and are able to solve different problems. Measuring the competence of committee members helps in making competent and accurate decisions.
Pedestrian Tracking Based on Colour and Spatial Information
Authors: Florian H. Seitner, Brian C. Lovell
Venue: Proceedings of the Digital Image Computing on Techniques and Applications (2005)

This paper describes a tracking with appearance modelling system for pedestrians. A cascade of boosted classifiers and Haar-like rectangular features [6, 12] are used for the pedestrian detection. Statistical modelling in the HSV colour space is used for adaptive background modelling and subtraction, where the use of circular statistics for hue is proposed. By using the background model in combination with the detector, the system extracts a feature vector based on colour statistics and the spatial information. Circular [9] and linear statistics are applied on the extracted features to robustly track the pedestrians and other moving objects through the scene. An adaptive appearance model copes with partial or full occlusions and addresses the problem of missing or wrong detections in single frames.
Handling Generalized Cost Functions in the Partitioning Optimization Problem through Sequential Binary Programming
Authors: Alan S. Abrahams, Adrian Becker, Daniel Fleder, Ian C. MacMillan
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

This paper proposes a framework for cost-sensitive classification under a generalized cost function. By combining decision trees with sequential binary programming, we can handle unequal misclassification costs, constrained classification, and complex objective functions that other methods cannot. Our approach has two main contributions. First, it provides a new method for cost-sensitive classification that outperforms a traditional, accuracy-based method and some current cost-sensitive approaches. Second, and more important, our approach can handle a generalized cost function, instead of the simpler misclassification cost matrix to which other approaches are limited.
Secured storage using secureParser™
Authors: Sabre A. Schnitzer, Robert A. Johnson Henry Hoyt
Venue: Proceedings of the 2005 ACM workshop on Storage security and survivability (2005)

Securing storage data is a manifold problem with requirements in three dimensions: data security, data integrity, and the safety of data. Meeting the requirements for one dimension often means compromising another. SecureParser™ is a software technology which addresses all three dimensions of secure storage without compromising any. In this paper, we describe the SecureParser™ technology and discuss how it addresses the three dimensions of secured storage: security, integrity, and safety.
Insider computer fraud detection in applications: a defense in depth framework involving software engineering and novelty neural networks
Authors: Kenneth Charles Brancik
Venue:  (2005)

The software development methodologies and products being manufactured exclude any substantive INFOSEC requirements or guidelines as part of a risk assessment design process. Increasing software functionality over security controls has elevated the level of risk in the software development process at the expense of designing and developing secure software applications. Furthermore, current software development methodologies do not adequately identify and report on anomalistic user behavior, which may originate from the insider threat. The research conducted from this dissertation topic will establish a risk-based framework to identify insider misuse through computer fraud. This dissertation will design a security solution to mitigate the risks associated with the insider threat, involving computer fraud, based on the completion of a taxonomy of computer fraud, development of fraud and information security Patterns and training of a neural network to detect unusual user activity. Based on the aforementioned analysis, computer forensic journaling will be identified for incorporation within the systems or applications software development lifecycle as an early warning system of aberrant insider behavior.
3D and Moving Target Extraction from Dynamic Pushbroom Stereo Mosaics
Authors: Zhigang Zhu, Hao Tang, Bing Shen, George Wolberg
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

In this paper, we propose a dynamic pushbroom stereo mosaic approach for representing and extracting 3D structures and independent moving targets from urban 3D scenes. Our goal is to acquire panoramic mosaic maps with motion tracking information for 3D (moving) targets using a light aerial vehicle equipped with a video camera flying over an unknown area for urban surveillance. In dynamic pushbroom stereo mosaics, independent moving targets can be easily identified in the matching process of stereo mosaics by detecting the "out-ofplace" regions that violate epipolar constraints and/or give 3D anomalies. We propose a segmentation-based stereo matching approach with natural matching primitives to estimate the 3D structure of the scene, particularly the ground structures (e.g., roads) on which humans or vehicles move, and then to identify moving targets and to measure their 3D structures and movements.
Priority-Driven Coding of Progressive JPEG Images for Transmission in Real-Time Applications
Authors: Albert Mo Kim Cheng, Feng Shang
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

Since high-quality image/video systems based on the JPEG/MPEG compression standards often require power-expensive implementations at relatively high bit-rates, they have not been widely used in low-power wireless applications. To alleviate this problem, we designed, implemented, and evaluated a strategy that can adapt to different compression and transmission rates. (1) It gives important parts of an image higher priority over unimportant parts. Therefore, the high-priority parts can achieve high image quality, while the low-priority parts, with a slight sacrifice of quality, can achieve huge compression rate and thus save the power/energy of a low-power wireless system. (2) We also introduce a priority-driven scheduling approach into our coding algorithm, which makes the transmission of important parts earlier with more data than other parts. Through a balanced trade-off between the available time/bandwidth/power and the image quality, this adaptive strategy can satisfy users with desired images quality and lead to a significant reduction of the important parts¿ deadline misses.
The spectrum of mathematical modeling and systems simulation
Authors: Walter J. Karplus
Venue: ACM SIGSIM Simulation Digest (1977)

The methodology involved in the modeling and simulation of physical, life and social science systems is viewed in perspective. A critical factor determining the validity of a model is the extent to which it can be derived from basic laws and insights into the internal structure of the system using deductive methods, rather than relying upon observations and measurements of the system input and outputs. Accordingly, the mathematical models as they arise in various application disciplines are arranged along a spectrum according to the relative amount of deduction and induction involved in their construction. This provides an insight into the ultimate validity of simulations and to what use they can properly be put.