ppxscal/embedding_network huggingface dataset:
Context learning in the rodent hippocampus
Authors: Mark C. Fuhs, David S. Touretzky
Venue: Neural Computation (2007)

We present a Bayesian statistical theory of context learning in the rodent hippocampus. While context is often defined in an experimental setting in relation to specific background cues or task demands, we advance a single, more general notion of context that suffices for a variety of learning phenomena. Specifically, a context is defined as a statistically stationary distribution of experiences, and context learning is defined as the problem of how to form contexts out of groups of experiences that cluster together in time. The challenge of context learning is solving the model selection problem: How many contexts make up the rodent's world? Solving this problem requires balancing two opposing goals: minimize the variability of the distribution of experiences within a context and minimize the likelihood of transitioning between contexts. The theory provides an understanding of why hippocampal place cell remapping sometimes develops gradually over many days of experience and why even consistent landmark differences may need to be relearned after other environmental changes. The theory provides an explanation for progressive performance improvements in serial reversal learning, based on a clear dissociation between the incremental process of context learning and the relatively abrupt context selection process. The impact of partial reinforcement on reversal learning is also addressed. Finally, the theory explains why alternating sequence learning does not consistently result in unique context-dependent sequence representations in hippocampus.
A Provably Secure ID-Based Mediated Signcryption Scheme
Authors: Yong Yu, Bo Yang, Ying Sun
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

It has been a critical issue to find efficient methods for fast revocation of a user's identity in identity (ID)-based cryptosystems. Unfortunately, none of the previous ID-based cryptography can find a practical way. Motivated by Boneh et al.'s idea of mediated RSA, in this paper, we propose the concept of ID-based mediated signcryption and give a concrete scheme, which yields a complete solution to the fast revocation of a user's identity in ID-based signcryption schemes. To address the security issues, we formulate security model and define strong security notions for ID-based mediated signcryption schemes. We also prove that our scheme satisfies these security requirements in the random oracle model.
Computer Education
Authors: D. C. Rine
Venue: Computer (1980)

High-quality education is critical to the success of computer applications in the 1980's. Herewith an examination, of computer science education; next month-using computers in education.
An Algorithm for Determining the Topological Dimensionality of Point Clusters
Authors: D. H. Schwartzmann
Venue: IEEE Transactions on Computers (1975)

The main thrust of this paper is to present a new algorithm for the analysis of structure in multivariate data point clusters from the standpoint of intrinsic (topological) dimensionality.
Allocating Resources to Parallel Query Plans in Data Grids
Authors: Sumit Kumar Bose, Srikumar Krishnamoorthy, Nilesh Ranade
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

In this paper we present a heuristic algorithm for solving the parallel query plan scheduling problem in data grids. The algorithm exploits the binary tree structure of the query plan to determine profitable allocations. It takes care of multiple forms of parallelism while allocating resources to the subplans. Previous approaches towards solving the problem either ignores partitioned parallelism by focusing solely on pipelined parallelism wherein the communication cost is minimized or lays more emphasis on partitioned parallelism at the cost of pipelined parallelism. The work in this paper attempts to take care of both pipelining and partitioning mechanisms while optimizing the allocation of resources to the query sub-plans. The algorithm is particularly well suited for allocation of resources to sub-plans in a bushy query plan - which is the most profitable form of query plan in distributed database query optimization.
Staircase-down SET programming approach for phase-change memories
Authors: Ferdinando Bedeschi, Chiara Boffino, Edoardo Bonizzoni, Claudio Resta, Guido Torelli
Venue: Microelectronics Journal (2007)

This paper presents a staircase-down SET programming technique for phase-change memories (PCMs). The proposed programming approach allows compensating for spreads in cell physical parameters and obtaining adequately narrow cell distributions, which results in improved read margin. The cell programming curve is experimentally evaluated and discussed. The effectiveness of the proposed technique is demonstrated by comparing cell distributions obtained on an 8-Mb bipolar junction transistor (BJT)-selected PCM demonstrator by means of a conventional SET box pulse and a staircase-down SET pulse, respectively.
Content and Illumination Invariant Blur Measures for Realtime Video Processing
Authors: Sebastien Harasse, Laurent Bonnaud, Michel Desvignes
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

This paper presents an approach to optical blur esti- mation in images based on the measuring of the spread of edges. Two measures based on this approach are proposed. The first measure defines a model of amplified gaussian with background for the profile of edges. The second measure is an approximation that does not require the extraction of profiles at edges. Both measures do not depend on the con- tent or illumination of the image, making them suitable for dynamic videos. The behaviour of the proposed measures is finally presented in the context of dynamic videos from a surveillance camera embedded in a transportation vehicle.
A Guided Tour of Program Design Methodologies
Authors: G. D. Bergland
Venue: Computer (1981)

After describing, applying, comparing, and evaluating four major methodologies, this guided tour concludes with an interim procedure for use until the "right" method appears.
LEAF: A System Level Leakage-Aware Floorplanner for SoCs
Authors: A. Gupta, N. D. Dutt, F. J. Kurdahi
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

Process scaling and higher leakage power have resulted in increased power densities and elevated die temperatures. Due to the interdependence of temperature and leakage power, we observe that the floorplan has an impact on both the temperatures and the leakage of the IP-blocks in a system on chip (SoC). Hence, in this paper we propose a novel system level leakage aware floorplanner (LEAF) which optimizes floorplans for temperature-aware leakage power along with the traditional metrics of area and wire length. Our floorplanner takes a SoC netlist and the dynamic power profile of functional blocks to determine a placement while optimizing for temperature dependent leakage power, area, and wire length. To demonstrate the effectiveness of LEAF, we implemented our methodology on ten industrial SoC designs from Freescale Semiconductor Inc. and evaluated the trade-off between leakage power and area. We observed up to 190% difference in the leakage power between leakage-unaware and leakage aware floorplanning.
Applying Multiple Classifier Systems to SoftMan's Perception System
Authors: Aizhong Mi, Xuefeng Zheng, Xuyan Tu
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

SoftMan, the virtual robot in network environment, is a kind of software Artificial Life living in computer networks. It has a humanoid structure, and simulating human, its perception system should be able to recognize perceptive objects. Enlightened by human's perception system and the "disassemble-integration" method in analyzing large systems, a cooperative classification model in SoftMan's perception system is proposed. In the model, different humanoid senses are simulated by multiple classifier systems (MCS). Consequently, SoftMan can perform multi-sense cooperative classification on its perceptive objects. A simulated experiment validates the basic feasibility of the model.
A Simulation Study of Multi-Color Marking of TCP Aggregates
Authors: Miriam Allalouf, Yuval Shavitt
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

Service Level Agreements (SLAs) are contracts signed between a provider and a customer to govern the amount of traffic that will be serviced. This work pinpoints an important problem faced by the Internet service provider (ISP) which is to be able to differentiate between the services given to aggregates of multiple TCP connections. The Metro-Ethernet access network, the Differentiated Services (DiffServ) architecture and the ATM reference model are three architectural models where edge routers perform traffic metering and coloring of aggregated flows according to the SLA. Finer color marking was suggested to improve differentiation quality. We observe that increasing the number of colors indeed provides a good differentiation between the aggregates according to the committed and the excess rates. We also show that the token bucket coloring policies, which are widely used for this purpose, prefer short packets and mark them with higher priority colors. The differentiation process is more difficult for the short TCP connections that remain in the slow start phase, than for the long connections that are usually in the congestion avoidance phase.
Two-Level Approach to Efficient Visualization of Protein Dynamics
Authors: Ove Daae Lampe Ivan Viola, Nathalie Reuter Helwig Hauser
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

Proteins are highly flexible and large amplitude deformations of their structure, also called slow dynamics, are often decisive to their function. We present a two-level rendering approach that enables visualization of slow dynamics of large protein assemblies. Our approach is aligned with a hierarchical model of large scale molecules. Instead of constantly updating positions of large amounts of atoms, we update the position and rotation of residues, i.e., higher level building blocks of a protein. Residues are represented by one vertex only indicating its position and additional information defining the rotation. The atoms in the residues are generated on-the-fly on the GPU, exploiting the new graphics hardware geometry shader capabilities. Moreover, we represent the atoms by billboards instead of tessellated spheres. Our representation is then significantly faster and pixel precise. We demonstrate the usefulness of our new approach in the context of our collaborative bioinformatics project.
Towards Quantitative Evaluation of UML based Software Architecture
Authors: Jinhua Li, Zhenbo Guo, Yun Zhao, Zhenhua Zhang, Ruijuan Pang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

The architecture of a software system is a critical artifact in the software lifecycle and should be evaluated as early as possible. Recent efforts to software architecture evaluation are concentrated on scenario-based methods which are qualitative, subjective and need not any special architecture description languages. This paper investigates an approach to metrics based quantitative evaluation of UML software architecture. UML is a visual modeling language with well-formed hierarchical syntax and semantics, and is uniformly applied in various development stages. With supplementation UML has been adapted to describing software architecture. By utilization of these features three types of metrics for UML diagrams are proposed. They measure the amount of information, visual effect and connectivity degree in different UML diagrams. The application of these metrics in quantitative evaluating qualities at the architecture-level such as system scale, complexity and structural characteristics is discussed.
Fault-Prone Filtering: Detection of Fault-Prone Modules Using Spam Filtering Technique
Authors: Osamu Mizuno, Shiro Ikami, Shuya Nakaichi, Tohru Kikuno
Venue: Proceedings of the First International Symposium on Empirical Software Engineering and Measurement (2007)

The fault-prone module detection in source code is of importance for assurance of software quality. Most of previous conventional fault-prone detection approaches have been based on using software metrics. Such approaches, however, have difficulties in collecting the metrics and constructing mathematical models based on the metrics. In order to mitigate such difficulties, we propose a novel approach for detecting fault-prone modules using a spam filtering technique. Because of the increase of needs for spam e-mail detection, the spam filtering technique has been progressed as a convenient and effective technique for text mining. In our approach, fault-prone modules are detected in a way that the source code modules are considered as text files and are applied to the spam filter directly. In order to show the usefulness of our approach, we conducted an experiment using source code repository of a Java based open source development. The result of experiment shows that our approach can classify more than 70% of software modules correctly.
An Improved Chaos-Based Stream Cipher Algorithm
Authors: Chong Fu, Zhi-liang Zhu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

This paper proposes an improved chaos-based stream cipher algorithm to enhance the security of an encryption system under precision limited condition. The key stream generator is constructed by three one dimension chaotic maps and their nonlinear transform. The balance and correlation properties of the key stream are analyzed. The sequence is proved to be a binary Bernoulli sequence and the distribution of the differences between the amounts of 0 and 1 is analyzed. The side lobes of auto and cross correlation are proved to obey normal distribution N(0, 1/N). Compared with the conventional single chaos map based encryption system, the algorithm proposed in this paper enlarges the key space, extends the period and improve the linear complexity of the key stream under precision restricted condition. The theoretical analysis and experimental results indicate that the system is strong against various common attack methods.
Analyzing sequential patterns in retail databases
Authors: Unil Yun
Venue: Journal of Computer Science and Technology (2007)

Finding correlated sequential patterns in large sequence databases is one of the essential tasks in data mining since a huge number of sequential patterns are usually mined, but it is hard to find sequential patterns with the correlation. According to the requirement of real applications, the needed data analysis should be different. In previous mining approaches, after mining the sequential patterns, sequential patterns with the weak affinity are found even with a high minimum support. In this paper, a new framework is suggested for mining weighted support affinity patterns in which an objective measure, sequential ws-confidence is developed to detect correlated sequential patterns with weighted support affinity patterns. To efficiently prune the weak affinity patterns, it is proved that ws-confidence measure satisfies the anti-monotone and cross weighted support properties which can be applied to eliminate sequential patterns with dissimilar weighted support levels. Based on the framework, a weighted support affinity pattern mining algorithm (WSMiner) is suggested. The performance study shows that WSMiner is efficient and scalable for mining weighted support affinity patterns.
Hop-count based probabilistic packet dropping: Congestion mitigation with loss rate differentiation
Authors: Xiaobo Zhou, Dennis Ippoliti, Terrance Boult
Venue: Computer Communications (2007)

Network applications and users have very diverse service expectations and requirements, demanding for provisioning different levels of quality of service on the Internet. As the speed of network links has been rising at a pace that exceeds that of the growth in the buffer size, packet loss rate differentiation has been an active research topic. However, none of the existing packet dropping schemes for loss rate differentiation considered an important issue, that is, the retransmission overhead of dropped packets. In this paper, we design a hop-count based probabilistic packet dropper (HPPD) for congestion mitigation and loss rate differentiation. HPPD aims to meet a unique two-fold objective by two-dimensional loss rate differentiation: the primary one is the congestion mitigation that aims to reduce congestion in the first place by dropping intra-class packets differently based on their maturity levels to reduce retransmission cost; the other is inter-class proportional loss rate differentiation. The maturity level of a packet, the number of hops it has travelled, is inferred from its time-to-live value in the IP header. We propose a novel intra-class nth-root proportional dropping scheme. The scheme reduces retransmission cost by giving higher dropping probabilities to less mature packets while all packets have their forwarding chances. The n is a controllable parameter trading off dropping fairness for congestion mitigation. It provides great controllability to network operators. Simulation results show that HPPD can significantly mitigate the congestion by reducing the retransmission overhead of dropped packets and achieve the proportional loss rate differentiation at the same time.
Optimal security hardening using multi-objective optimization on attack tree models of networks
Authors: Rinku Dewri, Nayot Poolsappasit, Indrajit Ray, Darrell Whitley
Venue: Proceedings of the 14th ACM conference on Computer and communications security (2007)

Researchers have previously looked into the problem of determining if a given set of security hardening measures can effectively make a networked system secure. Many of them also addressed the problem of minimizing the total cost of implementing these hardening measures, given costs for individual measures. However, system administrators are often faced with a more challenging problem since they have to work within a fixed budget which may be less than the minimum cost of system hardening. Their problem is how to select a subset of security hardening measures so as to be within the budget and yet minimize the residual damage to the system caused by not plugging all required security holes. In this work, we develop a systematic approach to solve this problem by formulating it as a multi-objective optimization problem on an attack tree model of the system and then use an evolutionary algorithm to solve it.
Hardware architecture of reinforcement learning scheme for dynamic power management in embedded systems
Authors: Viswanathan Lakshmi Prabha, Elwin Chandra Monie
Venue: EURASIP Journal on Embedded Systems (2007)

Dynamic power management (DPM) is a technique to reduce power consumption of electronic systems by selectively shutting down idle components. In this paper, a novel and nontrivial enhancement of conventional reinforcement learning (RL) is adopted to choose the optimal policy out of the existing DPM policies. A hardware architecture evolved from the VHDL model of Temporal Difference RL algorithm is proposed in this paper, which can suggest the winner policy to be adopted for any given workload to achieve power savings. The effectiveness of this approach is also demonstrated by an event-driven simulator, which is designed using JAVA for power-manageable embedded devices. The results show that RL applied to DPM can lead up to 28% power savings.
The New Front Line: Estonia under Cyberassault
Authors: Michael Lesk
Venue: IEEE Security and Privacy (2007)

Distributed denial-of-service (DDoS) attacks against Estonian computers were completed inexpensively enough to seriously call into question any assumptions that they were coordinated or run by agents of the Russian government. Indeed, motivated businesses and organization now have many resources within easy reach to launch botnet attacks.
A Flexible Applicable RBAC Model and Its Administration
Authors: Zhenxing Luo, Nuermaimaiti Heilili, Zuoquan Lin
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

With the increasing number of users and applications, enterprises or organizations need to effectively protect their important information and easily administrate the security policy. In this paper we analyze the existing access control models and propose an improved role-based access control model and its administration with practical experience to handle with the user privilege assignment relation flexibly.
Destination Clustering Geographic Multicast forWireless Sensor Networks
Authors: Gang Zhao, Xiangqian Liu, Anup Kumar
Venue: Proceedings of the 2007 International Conference on Parallel Processing Workshops (2007)

Geographic routing has been proven to provide efficient and scalable unicast routing in resource-constrained sensor networks. However, its applications in multicast routing remain largely unexplored. In this paper, we propose the DCGM (Destination Clustering Geographic Multicast) routing protocol for wireless sensor networks. By clustering destinations that can share the same next hop, we iteratively select the next hop as the neighbor with the maximum number of destinations. We prove that the complexity of DCGM is O(nk), where n is the number of neighbors of the current node and k is the number of destinations associated with the current node. Simulations show that DCGM achieves better performance than existing geographic multicast algorithms in terms of path length, but with much lower computation complexity.
Test Considerations for Gate Oxide Shorts in CMOS ICs
Authors: Jerry Soden, Charles Hawkins
Venue: IEEE Design Test (1986)

Gate oxide shorts are defects that must be detected to produce high-reliability ICs. These problems will continue as devicesare scaled down and oxide thicknesses are reduced to the 100-? range. Complete detection of gate oxide shorts and other CMOSfailure mechanisms requires measuring the IDD current during the quiescent state after each test vector is applied to theIC. A 100-percent stuck-at fault test set is effective only if each test vector is accompanied by an IDD measurement. Thisarticle examines the need for a fast, sensitive method of measuring IDD during each test vector and discusses problems confrontingCMOS IC designers, test engineers and test instrumentation designers as they work to meet these demands.
Hand-based Interface for Augmented Reality
Authors: F. Javier Toledo-Moreo, J. Javier Martinez-Alvarez, J. Manuel Ferrandez-Vicente
Venue: Proceedings of the 15th Annual IEEE Symposium on Field-Programmable Custom Computing Machines (2007)

Augmented reality (AR) is a highly interdisciplinary field which has received increasing attention since late 90s. Basically, it consists of a combination of the real scene viewed by a user and a computer generated image, running in real time. So, AR allows the user to see the real world supplemented, in general, with some information considered as useful, enhancing the users perception and knowledge of the environment. Benefits of reconfigurable hardware for AR have been explored by Luk et al. [4]. However, the wide majority of AR systems have been based so far on PCs or workstations.