ppxscal/embedding_network huggingface dataset:
Concept maps and case-based reasoning: a perspective for the intelligent teaching/learning systems
Authors: Maikel León Espinosa, Natalia Martínez Sánchez, Zoila Zenaida García Valdivia
Venue: Proceedings of the 2007 Euro American conference on Telematics and information systems (2007)

The use of present pedagogical methods and Information and Communication Technologies produce a new quality that favors the task of generating, transmitting and sharing knowledge. That is the case of the pedagogical effect that produces the use of the Concept Maps, which are considered a learning technique as a way to increase meaningful learning in the sciences. It is also used for the knowledge management as an aid to personalize the learning process, to exchange knowledge, and to learn how to learn. Concept Mapping provides a framework for making this internal knowledge explicit in a visual form that can easily be examined and shared. Concept Maps are relevant since they can be retrieved or adapted to new problems. In the other hand, Case-Based Reasoning as a technique in Artificial Intelligence plays an important role in knowledge retrieval and reuse of memories. In this paper the authors present a new approach to elaborate Intelligent Teaching/Learning Systems, where the techniques of Concept Maps and Artificial Intelligence are combined, using the Case-Based Reasoning as theoretical framework for the Student Model. The proposed model has been implemented in the computational system HESEI, which has been successfully used in the teaching/learning process by laymen in the Computer Science field.
Scalable packet classification by TCAM entry encryption algorithm
Authors: Chun-Liang Lee, Pi-Chung Wang
Venue: Journal of High Speed Networks (2007)

Ternary content-addressable memory (TCAM) has been widely used to perform fast packet classification due to its ability of solving the problem in O(1) time without considering the number of entries, mask continuity and their lengths. However, it also comes with several shortcomings, such as the limited number of entries, expensive cost and power consumption. We propose an efficient algorithm to reduce the required TCAM bits by encoding the IP address portion of the policies. With the proposed scheme, the achieved compression ratio can be as small as 9% for IPv6 policies. Moreover, the TCAM throughput is improved by a factor of 175% with pipelining design. Obviously, the proposed scheme is attractive for the forthcoming IPv6.
How To Construct Randolli Functions
Authors: O. Goldreich
Venue: Proceedings of the 25th Annual Symposium onFoundations of Computer Science, 1984 (1984)

This paper develops a constructive theory of randomness for functions based on computational complexity. We present a deterministic polynomial-time algorithm that transforms pairs (g,r), where g is any one-way (in a very weak sense) function and r is a random k-bit string, to polynomial-time computable functions f/sub r/:{1,..., 2/sup k} /spl I.oarr/ {1, ..., 2/sup k/}. These f/sub r/'s cannot be distinguished from random functions by any probabilistic polynomial time algorithm that asks and receives the value of a function at arguments of its choice. The result has applications in cryptography, random constructions and complexity theory.
Estimation of Posterior Fossa Volume in Pediatric Patients with Chiari Malformations by the Cavalieri Principle
Authors: Chunquan Cai, Qingjiang Zhang, Changhong Shen, Weidong Yang, Ouyan Shi
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

Chiari malformations (CMs) involve pathological hindbrain abnormalities reported to be correlated with a hypoplastic posterior fossa. This study calculates posterior fossa volume estimate using MRI. A retrospective review was conducted on patients who were admitted to our hospital. Clinical and radiological assessments were performed. Posterior fossa volumes (PFV) and intracranial volumes (ICV) were measured from head MRI scans using the Cavalieri principle. Forty CMs patients with a mean age of 9.5 years were identified. The mean PFV/ICV ratio for all the CMs patients (0.103) was found to be statistically smaller than that of the control patients (0.132, p
Tagging and searching: Search retrieval effectiveness of folksonomies on the World Wide Web
Authors: P. Jason Morrison
Venue: Information Processing and Management: an International Journal (2008)

Many Web sites have begun allowing users to submit items to a collection and tag them with keywords. The folksonomies built from these tags are an interesting topic that has seen little empirical research. This study compared the search information retrieval (IR) performance of folksonomies from social bookmarking Web sites against search engines and subject directories. Thirty-four participants created 103 queries for various information needs. Results from each IR system were collected and participants judged relevance. Folksonomy search results overlapped with those from the other systems, and documents found by both search engines and folksonomies were significantly more likely to be judged relevant than those returned by any single IR system type. The search engines in the study had the highest precision and recall, but the folksonomies fared surprisingly well. Del.icio.us was statistically indistinguishable from the directories in many cases. Overall the directories were more precise than the folksonomies but they had similar recall scores. Better query handling may enhance folksonomy IR performance further. The folksonomies studied were promising, and may be able to improve Web search performance.
A New Grid Resource Management Mechanism Based on D-S Theory
Authors: Yongsheng Hao, Yuebin Xu, Guanfeng Liu, Zhenkuan Pan
Venue: Proceedings of the 2008 International Conference on Multimedia and Ubiquitous Engineering (2008)

There may be some malicious nodes in the Grid environment because the resource of nodes can access the Grid system freely. The number and qualities of this resource can be change dramatically and optionally, so it is possible to affect the utilization of Grid resource. Hence, the trust mechanism is widely used in the management of Grid. This paper proposes a new method to detect the behaviors of resource providers in Grid environments based on D-S theory. Through simulating experiments, this mechanism can record the behaviors exactly and prevent the malicious ones. Then it gives a strong support for resource scheduling in the Grid.
Coprocessor-based hierarchical trust management for software integrity and digital identity protection
Authors: Lifu Wang Partha Dasgupta
Venue: Journal of Computer Security (2008)

Malware and rootkits are serious security threats. They can be designed to be resistant to anti-virus and security software and even remain totally undetectable. This paper describes a hierarchical trust management scheme, where the root of trust is in a non-tamperable hardware co-processor on a PCI bus. The security device checks a part of the OS kernel for integrity, which in turn checks other parts until we ensure the entire system is free of rootkits. The checker can be extended to encompass all applications and anti-virus software. Our system can detect any illegal modifications to kernel, loadable kernel modules and user applications. It also provides a secure communication line for user interaction to manage legal software updates. Moreover, this device can securely perform user authentication and protect digital identity against identity theft. Our tests show that we can correctly detect different real-world and synthetic rootkits even though the host kernel is compromised.
FGS-MR: MPEG4 fine grained scalable multi-resolution layered video encoding
Authors: Siddhartha Chattopadhyay, Suchendra M. Bhandarkar, Kang Li
Venue: Proceedings of the 2006 international workshop on Network and operating systems support for digital audio and video (2006)

The MPEG-4 Fine Grained Scalability (FGS) profile aims at scalable video encoding, in order to ensure efficient video streaming in networks with fluctuating bandwidth. In order to allow very low bit rate streaming, the Base Layer of an FGS video is encoded at a very low bit rate, resulting in very low video quality. In this paper, we propose FGS-MR, which uses content aware multi-resolution video frames to obtain better video quality for a target bit rate, compared to existing MPEG-4 FGS Base Layer video encoding schemes. FGS-MR is an integrated approach that requires only encoder side modification, and is transparent to the decoder. In addition, FGS-MR can be used with any existing MPEG-4 codec which supports FGS, since it entails "smart" video preprocessing and does not involve any components from the MPEG-4 compression pipeline. FGS-MR is a mask based technique. We have demonstrated an unsupervised algorithm to automatically create the mask from a given video sequence.
Correspondence validation method for GUI operations and scenarios by operation history analysis
Authors: Junko Shirogane, Yoshiaki Fukazawa
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2008)

Interactions between users and software are usually described as scenarios so that it is easy to reflect users' viewpoints in software development. In many cases, scenarios are written in a natural language so that users can communicate with software developers smoothly. However, it is difficult to validate correspondences between the flows of operations written in scenarios and those in software. We assume that the flows of software can be expressed by the flows of Graphical User Interface (GUI) operations. In this paper, we propose a method for validating the correspondences between the flows of operations in scenarios and those of actual GUIs. This validation can be performed by analyzing the historic data of GUI operations heuristically. The label names on widgets are extracted from the histories, terms corresponding to label names on widgets are extracted from scenarios, and then the orders of appearance of label names and f terms are validated.
Adaptive runtime tuning of parallel sparse matrix-vector multiplication on distributed memory systems
Authors: Seyong Lee, Rudolf Eigenmann
Venue: Proceedings of the 22nd annual international conference on Supercomputing (2008)

Sparse matrix-vector (SpMV) multiplication is a widely used kernel in scientific applications. In these applications, the SpMV multiplication is usually deeply nested within multiple loops and thus executed a large number of times. We have observed that there can be significant performance variability, due to irregular memory access patterns. Static performance optimizations are difficult because the patterns may be known only at runtime. In this paper, we propose adaptive runtime tuning mechanisms to improve the parallel performance on distributed memory systems. Our adaptive iteration-to-process mapping mechanism balances computational load at runtime with negligible overhead (1% on average), and our runtime communication selection algorithm searches for the best communication method for a given data distribution and mapping. Actual runs on 26 real matrices show that our runtime tuning system reduces execution time up to 68.8% (30.9% on average) over a base block-distributed parallel algorithm on distributed systems with 32 nodes.
Privacy Preservation in the Publication of Trajectories
Authors: Manolis Terrovitis, Nikos Mamoulis
Venue: Proceedings of the The Ninth International Conference on Mobile Data Management (2008)

We study the problem of protecting privacy in the publication of location sequences. Consider a database of trajectories, corresponding to movements of people, captured by their transactions when they use credit or RFID debit cards. We show that, if such trajectories are published exactly (by only hiding the identities of persons that followed them),there is a high risk of privacy breach by adversaries who hold partial information about them (e.g., shop owners). In particular, we show that one can use partial trajectory knowledge as a quasi-identifier for the remaining locations in the sequence. We device a data suppression technique, which prevents this type of breach, while keeping the posted data as accurate as possible.
Functional size measurement based on problem frames: a case study
Authors: Luigi Lavazza, Vieri del Bianco
Venue: Proceedings of the 3rd international workshop on Applications and advances of problem frames (2008)

The approach to requirements modelling based on problem frames is gaining increasing attention and popularity. However, the usage of problem frames in industrial software development processes requires that some industrial practices, like cost estimation, are supported. This paper explores the possibility to apply the most popular functional measurement method, namely Function Point Analysis, to user requirements represented using problem frames. In particular, a simple problem is modelled using problem frames "both in their native notation and using UML" and its functional size in Function Points is measured. This case study indicates that it is actually possible to apply Function Point Analysis to problem frames, and provides some insight into the measurement process to be adopted.
A Framework for Requirements Engineering PRocess DEvelopment (FRERE)
Authors: Li Jiang, Armin Eberlein
Venue: Proceedings of the 19th Australian Conference on Software Engineering (2008)

Adoption of the most suitable Requirements Engineering (RE) process and selection of the most appropriate RE techniques for a given project are challenging issues for industry. In order to alleviate the problems, a Framework for RE pRocess dEvelopment (FRERE) was developed based on our research in the last six years. The overall architecture of the framework and a brief case study are presented in the paper. The framework addresses several core issues of the RE process: engineering issues, domain issues, characteristics of the software project, and issues of conformity to software process standards. FRERE consists of three parts: (1) The RE Process Knowledge Base (REPKB) which contains RE process knowledge, (2) Methodologies which provide guidance to develop a customized software process model in an iterative way; and (3) Assessment Models which provide information about the suitability of the newly developed RE process model for the software project under development.
Integrating visible, near-infrared and short wave infrared hyperspectral and multispectral thermal imagery for geologic mapping: simulated data
Authors: X. Chen, T. A. Warner, D. J. Campagna
Venue: International Journal of Remote Sensing (2007)

Hyperspectral and thermal infrared (TIR) multispectral remote sensing have great potential for surface geological mapping. This paper investigates the potential impact of combining these data on the comparative accuracy of different classification methods. A series of simulated datasets based on the characteristics of Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) and MODIS/ASTER Airborne Simulator (MASTER) sensors was created from surface reflectance and emissivity data derived from library spectra of 16 common minerals and rocks occurring in Cuprite, Nevada. System noise, illumination effects, the presence of vegetation, and spectral mixing were added to create the simulated data. Five commonly used classification algorithms, minimum distance, maximum likelihood classification, binary encoding, spectral angle mapper (SAM) and spectral feature fitting (SFF), were applied to all datasets. All the classification methods, excluding binary encoding, achieved nominal to significant improvement in overall accuracy when applied to the combined datasets in comparison to using only the AVIRIS dataset. Furthermore, certain classification methods of the combined datasets show a marked increase in individual rock or mineral class accuracies. Limestone, silicified and muscovite, for instance, show an improvement of almost 30% or greater in either producer's or user's accuracy using the combined datasets with SAM. SFF provides a great improvement in accuracy for limestone, quartz and muscovite. In terms of overall comparative accuracy for the individual and the combined datasets, maximum likelihood classification shows the best performance. For the simulated AVIRIS data, SFF was generally superior to SAM, although the accuracy of SAM applied to the combined datasets was slightly better than that of SFF. SAM applied to the combined datasets increases classification accuracy for some minerals and rocks which do not exhibit distinct absorption feature in the TIR region, while for SFF, only the accuracy of minerals and rocks with characteristic absorption features in the TIR region is improved.
Beyond Automation: Hybrid Human-Computer Decision Support Systems in Hospitals
Authors: Christoph Niemann, Torsten Eymann
Venue: Proceedings of the Fifth IEEE Workshop on Engineering of Autonomic and Autonomous Systems (2008)

Scheduling in hospitals is a decision problem that relies on encoded information (such as room assignments or diagnoses) as much as on non-encoded information (medical knowledge). To support clinical scheduling with information systems, both types of information and their respective carriers have to be incorporated in combination, thus always requiring a "human-in-the-loop'', which prohibits full autonomy. In contrast to other proposals in Autonomic Computing, this paper makes a case for a hybrid human-computer decision support system to support scheduling in hospitals that combines humans' ability to improvise and to assess a situation, with computers' ability to communicate quickly to achieve emergent self-organization. Furthermore, the paper outlines an approach to evaluate such a system.
Nonsmooth optimization through Mesh Adaptive Direct Search and Variable Neighborhood Search
Authors: Charles Audet, Vincent Béchard, Sébastien Le Digabel
Venue: Journal of Global Optimization (2008)

This paper proposes a way to combine the Mesh Adaptive Direct Search (MADS) algorithm, which extends the Generalized Pattern Search (GPS) algorithm, with the Variable Neighborhood Search (VNS) metaheuristic, for nonsmooth constrained optimization. The resulting algorithm retains the convergence properties of MADS, and allows the far reaching exploration features of VNS to move away from local solutions. The paper also proposes a generic way to use surrogate functions in the VNS search. Numerical results illustrate advantages and limitations of this method.
A theoretical framework for multiple neural network systems
Authors: Mike W. Shields, Matthew C. Casey
Venue: Neurocomputing (2008)

Multiple neural network systems have become popular techniques for tackling complex tasks, often giving improved performance compared to single network systems. For example, modular systems can provide improvements in generalisation through task decomposition, whereas multiple classifier and regressor systems typically improve generalisation through the ensemble combination of redundant networks. Whilst there has been significant focus on understanding the theoretical properties of some of these multi-net systems, particularly ensemble systems, there has been little theoretical work on understanding the properties of the generic combination of networks, important in developing more complex systems, perhaps even those a step closer to their biological counterparts. In this article, we provide a formal framework in which the generic combination of neural networks can be described, and in which the properties of the system can be rigorously analysed. We achieve this by describing multi-net systems in terms of partially ordered sets and state transition systems. By way of example, we explore an abstract version of learning applied to a generic multi-net system that can combine an arbitrary number of networks in sequence and in parallel. By using the framework we show with a constructive proof that, under specific conditions, if it is possible to train the generic system, then training can be achieved by the abstract technique described.
Design requirements and framework for a robotic infrastructure system
Authors: Joshua D. Jackson, Dale W. Callahan, Donald S. Appleby, Lea B. Callahan
Venue: Proceedings of the 5th WSEAS International Conference on Circuits, Systems, Electronics, Control & Signal Processing (2006)

Robotic Infrastructure Systems will soon become an integral part of industry, offices, and our homes. They will be able to be controlled remotely from the Internet, and have interfaces to many systems and databases. However, current robots are mostly used for stand-alone manufacturing operations, toys, and scientific research. In order to exist as part of the critical infrastructure, robots must be able to interact with multiple users, authenticate users, track usage and users, and provide feedback to the user. The critical element that will allow such functionality is the communications channel - which will most likely be the Internet. To make proper use of the Internet, system architecture and protocols must be developed to support robots and the unique functions they will provide to the users. This paper addresses the issues that must be accounted for in developing architecture for robotics within the infrastructure. These issues are the basis for design decisions in developing robotic infrastructure systems.
Definition and Evaluation of Penalty Functions in SLA Management Framework
Authors: Jacek Kosinski, Dominik Radziszowski, Krzysztof Zielinski, Slawomir Zielinski, Grzegorz Przybylski, Pawel Niedziela
Venue: Proceedings of the Fourth International Conference on Networking and Services (2008)

The paper presents an analysis of the possibilities of defining penalty functions to be used in SLA management frameworks. As a basis for the analysis, a brief survey of metrics used in SLA contracts is presented. Next, several definitions of penalty functions are proposed. The definitions are then analyzed in context of embedding them in a working SLA management framework.
Experimental demonstration of the viability of IEEE 802.11b based inter-vehicle communications
Authors: Víctor González, Alberto Los Santos, Carolina Pinart, Francisco Milagro
Venue: Proceedings of the 4th International Conference on Testbeds and research infrastructures for the development of networks & communities (2008)

This paper demonstrates experimentally the viability of the wireless technology IEEE 802.11b for inter-vehicle communications. Although IEEE802.11b was designed for low-mobility, indoor scenarios, we demonstrate that is possible to use it in high-mobility, outdoor scenarios where vehicles reach relative speeds of 260 km/h. For the first time, this demonstration takes into account both the speed and the presence/absence of line-of-sight in the IEEE 802.11b communication link. These are key aspects to the most aggressive vehicular scenarios for VANET communications, such as urban streets where the surrounding buildings produce constant signal reflections or high-speed freeways. The results obtained are part of the Virtual Sub-Centre developed in the European COM2REACT project, which is a novel building block to manage efficiently moving groups of vehicles in close proximity.
Extremal graphs with bounded densities of small subgraphs
Authors: Jerrold R. Griggs, Miklóos Simonovits, George Rubin Thomas
Venue: Journal of Graph Theory (1998)

Let Ex(n, k, &mu;) denote the maximum number of edges of an n-vertex graph in which every subgraph of k vertices has at most &mu; edges. Here we summarize some known results of the problem of determining Ex(n, k, &mu;), give simple proofs, and find some new estimates and extremal graphs. Besides proving new results, one of our main aims is to show how the classical Tur&aacute;an theory can be applied to such problems. The case &mu; = $(^{k}_{2}) - 1$ is the famous result of Tur&aacute;an. &copy; 1998 John Wiley Sons, Inc. J. Graph Theory 29: 185207, 1998