ppxscal/embedding_network huggingface dataset:
Packet loss resilience using unequal forward error correction assignment for video transmission over communication networks
Authors: Hojin Ha, Changhoon Yim, Young Yong Kim
Venue: Computer Communications (2007)

Forward error correction (FEC) methods have been developed for packet loss resilience in application layer for real-time video transmission over communication networks. In this paper, an efficient packet loss resilience method is proposed using closed form solution for unequal FEC assignment based on a new packet distortion model. We first derive the packet distortion model by investigating the error concealment property and error propagation effect in H.264. To select the source and channel rate minimizing the overall distortion, we present a model-based rate allocation algorithm using the packet distortion model and rate-distortion function. Then we propose the closed form solution for unequal FEC assignment, which uses the packet distortion model and considers channel status information. Simulation results show that the proposed method gives substantial improvement for the received video quality in packet-lossy Internet and wireless network environments, while it requires much less computational complexity compared to the previous scheme.
Using Artificial Neural Network in Multi-Agent Supply Chain Systems
Authors: Hsiao Ching Chen, Hui Ming Wee, Kung-Jeng Wang, Yao-Hung Hsieh
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

In modern global market, one of the most important issues of the supply chain (SC) management is to satisfy changing customer demands, and enterprises should enhance the long-term advantage through the optimal inventory control. In this study, we model a supply chain framework by multi-agent with mixed inventory policies of facilities to consider the impact factors of the total supply chain cost. This paper develops a multi-agent system to simulate supply chain system. Artificial Neural Network (ANN) is used to derive the optimal inventory policies in the SC numbers. We examine the performance of the optimal inventory policies by cutting costs and increasing supply chain management efficiency. The proposed inventory policy using multi-agent and ANN provides managerial insights on the impact of the decision making in all the SC numbers.
Scaling Analytical Models for Soft Error Rate Estimation Under a Multiple-Fault Environment
Authors: Christian J. Hescott, Drew C. Ness, David J. Lilja
Venue: Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools (2007)

With continuing increase in soft error rates, its foreseeable that multiple faults will eventually need to be considered when modeling circuit sensitivity and evaluating faulttolerance techniques. Previous work that considers multiple faults assumes the faults are permanent. These assumptions aren't directly valid for soft errors. In this work, we evaluate two currently available models for analyzing circuit sensitivities but subject them to multiple transient fault environments. The first model targets the application of triple modular redundancy (TMR) to a non-branching (no fan-out) circuit with permanent faults. We demonstrate this model's inability to adequately predict sensitivity when circuits with branching are considered and subjected to transient faults. We motivate the need for a model that captures logical masking. This is provided by modifying a soft error rate (SER) estimation algorithm to handle multiple faults and gate input interdependence. We conclude that the simple non-branching model can predict a trade-off threshold for when TMR can benefit a circuit. However accurately predicting the magnitude of reliability changes requires the inclusion of more complicated branching effects and logical masking.
Using coverage as a model building constraint in learning classifier systems
Authors: David Perry Greene, Stephen F. Smith
Venue: Evolutionary Computation (1994)

Promoting and maintaining diversity is a critical requirement of search in learning classifier systems (LCSs). What is required of the genetic algorithm (GA) in an LCS context is not convergence to a single global maximum, as in the standard optimization framework, but instead the generation of individuals (i.e., rules) that collectively cover the overall problem space. COGIN (COverage-based Genetic INduction) is a system designed to exploit genetic recombination for the purpose of constructing rule-based classification models from examples. The distinguishing characteristic of COGIN is its use of coverage of training set examples as an explicit constraint on the search, which acts to promote appropriate diversity in the population of rules over time. By treating training examples as limited resources, COGIN creates an ecological model that simultaneously accommodates a dynamic range of niches while encouraging superior individuals within a niche, leading to concise and accurate decision models. Previous experimental studies with COGIN have demonstrated its performance advantages over several well-known symbolic induction approaches. In this paper, we examine the effects of two modifications to the original system configuration, each designed to inject additional diversity into the search: increasing the carrying capacity of training set examples (i.e., increasing coverage redundancy) and increasing the level of disruption in the recombination operator used to generate new rules. Experimental results are given that show both types of modifications to yield substantial improvements to previously published results.
Improving the scalability of an IMS-compliant conferencing framework through presence and event notification
Authors: A. Amirante, T. Castaldi, L. Miniero, S. P. Romano
Venue: Proceedings of the 1st international conference on Principles, systems and applications of IP telecommunications (2007)

In this article we present a thorough performance analysis of an actual implementation of a distributed conferencing framework compliant with the IP multimedia core network subsystem specification. The subject of our experimental campaign has been an architecture implemented by exploiting existing achievements in the field of conferencing. The work presented is based on the standard centralized conferencing framework defined by the IETF XCON working group, for which we recently provided an open source implementation. Starting from here, we devised a distributed conferencing solution that has been implemented as an overlay network of centralized conferencing clouds able to: (i) discover each other by means of presence mechanisms; (ii) exchange conference related information through an event notification paradigm; (iii) manage distributed conferences through out-of-band dedicated channels. The study is conducted by first measuring the main performance figures of the centralized solution and then assessing the capability of the distributed framework to improve such performance by scaling both in the number of supported users/conferences and in the overall resource consumption.
Estimating Software Vulnerabilities
Authors: Jeffrey R. Jones
Venue: IEEE Security and Privacy (2007)

Any given piece of software has some number of publicly disclosed vulnerabilities at any moment, leaving the system exposed to potential attack. The author presents a method for identifying and analyzing these vulnerabilities using public data from easily accessible sources.
Performance Comparison of TCP and CBR in MAODV Ad hoc Network
Authors: Warodom Werapun, Krit Thavornvisit
Venue: Proceedings of the Second International Conference on Systems and Networks Communications (2007)

Multicast Ad hoc On-Demand Distance Vector (MAODV) [1] is the multicast protocol associated with the Ad hoc On-Demand Distance Vector (AODV) [2,7] routing protocol, and as such it shares many similarities and packet formats with AODV. The Route Request and Route Reply packet types are based on those used by AODV, as is the unicast Route Table. The purpose of this paper is to compare the performance of TCP and CBR in MAODV Ad hoc network, where the efficiencies of TCP and CBR are evaluated in various parameters environment.
R68-12 An Experimental Model of System/ 360
Authors: N. R. Nielsen
Venue: IEEE Transactions on Computers (1968)

The deliveries of the new third generation computers have presented users with a multitude of problems. Not the least of these is the question of machine configuration. One of the characteristics of the new systems is the flexibility of configuration relative to the older equipment being replaced. No longer can one install "system x." Rather one selects central processor unit (CPU) x and then adds a wide variety of I/O channels, control units, and devices. Equipment selection is not the end of the problem either, for there are many ways to arrange any particular set of devices. Further, not only can configuration changes significantly affect performance, but the effectiveness of any particular configuration is dependent upon an installation's workload. Thus, a configuration which is quite satisfactory for Company Y may be very ineffective for Company Z.
Adaptive IIR notch filters based on new error criteria
Authors: R. Punchalard, A. Lorsawatsiri, J. Koseeyaporn, P. Wardkein, A. Roeksabutr
Venue: Signal Processing (2008)

Modified indirect and direct plain gradient (MIPG and MDPG) algorithms using new error criteria for second-order adaptive IIR (infinite-impulse response) notch filters (ANFs) with constrained poles and zeros are proposed in this paper. The proposed techniques are based on modifying error functions of the standard indirect and direct ANFs. In this work, the proposed error criteria are modified as the mean value of the product of the two signals which are, respectively, produced by the FIR (finite-impulse response) and IIR sections of the ANFs. Due to a non-zero slope straight line-like characteristic of the new cost functions, the gradient based adaptive algorithm rapidly converges to an optimum solution resulting in faster convergence speed than that of the conventional method. The closed form expressions for steady-state estimation bias and mean square error (MSE) of the proposed algorithms are also carried out. In addition, extensive simulations of the proposed algorithms compared to other methods are provided to support the theoretical analyses. Although, there are some limitations in the proposed algorithms, however, the demonstrated results obtained from tested algorithms at the same condition confirm that the proposed MIPG and MDPG algorithms are superior to others in convergent speed.
Solving pattern nesting problems with genetic algorithms employing task decomposition and contact detection
Authors: Rahul Dighe, Mark J. Jakiela
Venue: Evolutionary Computation (1995)

A hierarchical approach for nesting two-dimensional shapes based on genetic algorithms is described. For the higher-level search, a representation that facilitates genetic search based on recombination is developed. An alternatiye to overlap computation based on assembly of polygons is used at the lower level of search. Two implementations to find minimum-area enclosures for polygons, with and without a cohstraint on the width of stock, are discussed. Sample output illustrating the effectiveness of the approach is provided.
Collaborative Memory Pool in Cluster System
Authors: Nan Wang, Xuhui Liu, Jin He, Jizhong Han, Lisheng Zhang, Zhiyong Xu
Venue: Proceedings of the 2007 International Conference on Parallel Processing (2007)

With the developments of network technologies, many mechanisms have been introduced to improve system performance in cluster systems by exploiting remote idle memory. However, none of them can satisfy the requirements from different applications. Most methods can only improve the performance of a particular type of applications but not for others. One important reason is they failed to provide unified interfaces. In this paper, we propose Collaborative Memory Pool (CMP) to solve this problems. CMP brings scalability and high performance. It has five features: 1) Providing malloc-like interfaces, block device interfaces and kernel API for different applications, which benefit both user-level and kernel-level applications; 2) Retaining traditional VM mechanism, programmers and uses have the freedom to select CMP or not; 3) Improving kernel applications performance by eliminating remote swapping; 4) Avoiding loan while in debt problem with dynamic workload; 5) Providing optional memory servers to further improve performance. In our testbed with CMP-based swap devices, Qsort gets 83.28% improvement comparing with the case using disk-based swap devices.
An Improved Particle Swarm Optimization for SVM Training
Authors: Ying Li, Yan Tong, Bendu Bai, Yanning Zhang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

Since training a SVM requires solving a constrained quadratic programming problem which becomes difficult for very large datasets, an improved particle swarm optimization algorithm is proposed as an alternative to current numeric SVM training methods. In the improved algorithm, the particles studies not only from itself and the best one but also from the mean value of some other particles. In addition, adaptive mutation was introduced to reduce the rate of premature convergence. The experimental results show that the improved algorithm is feasible and effective for SVM training.
Facial Composites, Ophthalmic Geometry Pattern, and Based on Stated Phenomena: the Test of Person/Personality Liveness
Authors: Leonid Kompanets
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

The scientific aspects of automatic procedures of precise facial composites synthesis, ophthalmic geometry pattern extraction/ interpretation as well as based on these ones the Test of Person/Personality Liveness are proposed. Main research idea is that two relatively novel phenomena (functional asymmetry of left/right brain hemispheres and ophthalmic geometry pattern), are contained sufficient information of different scales for biometrics person recognition, psychological personality type definition, some biologic, artistic/ sculptural, artificial intelligent applications; it means that appropriate entities can be quantitatively tested. Moreover, it is possibly to testing whether person/ personality are biological or virtual ones. The mentioned information is poorly distinguished by human being but may automatic be extracted with computer from frontal facial image and/or interpreted in biometrics or modern psychology terms.
Bandwidth of Crossbar and Multiple-Bus Connections for Multiprocessors
Authors: T. Lang
Venue: IEEE Transactions on Computers (1982)

In this paper we compare the effective bandwidth in a multiprocessor with shared memory using as interconnection networks the crossbar or the multiple-bus. We consider a system with N processors and N memory modules, in which the processor requests to the memory modules are independent and uniformly distributed random variables. We consider two cases: in the first the processor makes another request immediately after a memory service, and in the second there is some internal processing time.
Even Data Bases That Lie Can Be Compromised
Authors: R. A. Demillo
Venue: IEEE Transactions on Software Engineering (1978)

Users can compromise data bases by asking a series of questions, even when the data bases are allowed to lie.
A Bucket Grid Structure to Speed Up Table Lookup in Gauge-Based Photometric Stereo
Authors: Helena Cristina G. Leitao, Rafael Felipe V. Saracchini, Jorge Stolfi
Venue: Proceedings of the XX Brazilian Symposium on Computer Graphics and Image Processing (2007)

In this paper, we show how to speed up the table lookup step in gauge-based multi-image photometric stereo. In that step, one must find a pixel of a gauge object, of known shape and color, whose appearance under m different illumination fields is similar to that of a given scene pixel. This search reduces to finding the closest match to a given mvector in a table with a thousand or more m-vectors. Our speed-up method exploits the fact that the table is in fact a fairly flat two-dimensional manifold in m-dimensional space, so that the search can be efficiently solved with a two-dimensional bucket grid structure.
An Efficient Fine-grained Parallel Genetic Algorithm Based on GPU-Accelerated
Authors: JIAN-MING LI, XIAO-JING WANG, RONG-SHENG HE, ZHONG-XIAN CHI
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

Fine-grained parallel genetic algorithm (FGPGA), though a popular and robust strategy for solving complicated optimization problems, is sometimes inconvenient to use as its population size is restricted by heavy data communication and the parallel computers are relatively difficult to use, manage, maintain and may not be accessible to most researchers. In this paper, we propose a FGPGA method based on GPU-acceleration, which maps parallel GA algorithm to texture-rendering on consumer-level graphics cards. The analytical results demonstrate that the proposed method increases the population size, speeds up its execution and provides ordinary users with a feasible FGPGA solution.
Transfer Learning via Inter-Task Mappings for Temporal Difference Learning
Authors: Matthew E. Taylor, Peter Stone, Yaxin Liu
Venue: The Journal of Machine Learning Research (2007)

Temporal difference (TD) learning (Sutton and Barto, 1998) has become a popular reinforcement learning technique in recent years. TD methods, relying on function approximators to generalize learning to novel situations, have had some experimental successes and have been shown to exhibit some desirable properties in theory, but the most basic algorithms have often been found slow in practice. This empirical result has motivated the development of many methods that speed up reinforcement learning by modifying a task for the learner or helping the learner better generalize to novel situations. This article focuses on generalizing across tasks, thereby speeding up learning, via a novel form of transfer using handcoded task relationships. We compare learning on a complex task with three function approximators, a cerebellar model arithmetic computer (CMAC), an artificial neural network (ANN), and a radial basis function (RBF), and empirically demonstrate that directly transferring the action-value function can lead to a dramatic speedup in learning with all three. Using transfer via inter-task mapping (TVITM), agents are able to learn one task and then markedly reduce the time it takes to learn a more complex task. Our algorithms are fully implemented and tested in the RoboCup soccer Keepaway domain. This article contains and extends material published in two conference papers (Taylor and Stone, 2005; Taylor et al., 2005).
Phase Unwrapping Algorithm for 3D Reconstruction
Authors: H. Zhang, H. Su, X. Y. Su
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

Phase unwrapping algorithms play an important role in noncontact optical profilometries such as phase-measuring profilometry. The depth information of the measured object is implicitly defined by certain trigonometric equations derived from image data. The direct solutions to the equations, called the wrapped phases, have a limited range from -\pi to \pi. The main computational problem is to unwrap the wrapped phases over the entire image. This phase unwrapping process is often hindered by the presence of noises, spots of low intensity modulation, and instability of the solutions. We present a novel approach to the problem by formulating the phase solving and unwrapping as an ill-posed problem. By using the regularization method, we will be able to provide a unified view to address various challenges in the problem. A new fully automated algorithm for phase unwrapping based on this approach is also presented.
Parameter Identifications In Differential Equations By Gene Expression Programming
Authors: Dazhi Jiang, Zhijian Wu, Lishan Kang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

As for inverse problem, there exist lots of traditional mathematic and physical methods. In recent years, the burgeoning evolutionary algorithms have been widely utilized in many areas. Their global optimization, parallelism, and effectiveness are widely applied to functional optimization problems. A method based on Gene Expression Programming is presented in this paper for identifying the parameter in inverse problems. The results show that the new method is very effective for solving the inverse problem even for the case with large noise in the observation data.
Fortran Can it be Structured-Should it be?
Authors: E. Horowitz
Venue: Computer (1975)

There is no doubt about it, structured programming (SP) is making waves. Wherever one goes within the computing community people are asking what it is and how they can use it. And the answers they are receiving are sometimes very different. This inability to pin down a precise definition has caused the original concept of SP to become widely distorted. For example, a recent advertisement described SP as "a means of improving the quality of the code, improving project control, reducing the debugging phase of the project, forcing good software documentation as an integral part of the system design, and making programs less sensitive to turnover of project personnel."1 Thus portrayed as a panacea for the entire programming process, it is not surprising that in a recent week-long seminar given by Dr. Dijkstra, he refused to use the term at all.
Double-Step Circle Drawing Algorithm with and without Grey Scale
Authors: Yong Kui Liu, Xiao Niu Li
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

In this paper, a double-step circle drawing algorithm is presented first. It chooses the best approximate pixels to the circle with only integer arithmetic. The results of comparison show that its speed is higher than the existing circle drawing algorithms. Furthermore, this algorithm can be used to draw anti-aliased circles, e.g. to draw filled circle edges with different intensity, without increase in calculations. It generates two more intermediate shades of grey scale than the double-step algorithm by Wu and Rokne and the greatest error of intensity is only half of that of the latter.
Improved Ant Colony Optimization for One-Dimensional Bin Packing Problem with Precedence Constraints
Authors: Zeqiang Zhang, Wenming Cheng, Liansheng Tang, Yue Cheng
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

Bin packing is a well studied problem which has many applications. In this paper, a new design of ant colony optimization (ACO) is proposed for solving the one-dimensional bin packing problem with precedence constraints (PCBPP). The proposed algorithm made use of the trail information which is deposited between the item and the item selected position, and pheromone summation rules was adopted. Furthermore, heuristic methods, which synthesis consider size of the item and the number of successors and are effective for the bin packing problem, are introduced into our ACO for quick obtaining a solution. The effectiveness of our ACO is investigated through computational results for test instances.