ppxscal/embedding_network huggingface dataset:
An efficient spatial semi-supervised learning algorithm
Authors: Ranga Raju Vatsavai, Shashi Shekhar, Thomas E. Burk
Venue: International Journal of Parallel, Emergent and Distributed Systems (2007)

We began by developing a semi-supervised learning method based on the expectation-maximization (EM) algorithm, and maximum likelihood and maximum a posteriori classifiers (MLC and MAP). This scheme utilizes a small set of labeled and a large number of unlabeled training samples. We conducted several experiments on multi-spectral images to understand the impact of unlabeled samples on the classification performance. Our study shows that although, in general, classification accuracy improves with the addition of unlabeled training samples, it is not guaranteed to achieve consistently higher accuracies unless sufficient care is exercised when designing a semi-supervised classifier. We also extended this semi-supervised framework to model spatial context through Markov random fields (MRF). Initial experiments showed an improved accuracy of the spatial semi-supervised algorithm (SSSL) over MLC, semi-supervised, and MRF classifiers. An efficient implementation is provided so that the SSSL can be applied in production environments. We also discuss some open research problems.
Reducing index method for differential algebraic equations
Authors: M. M. Hosseini
Venue: Proceedings of the 7th WSEAS International Conference on Applied Mathematics (2005)

In [Appl. Math. Comput. In press] a reducing index method has been proposed for some cases of semi-explicit DAEs(differential algebraic equations). In this paper, this method is generalized to more cases. Also, numerical implementation of generalized method is presented by pseudospectral method. In addition, aforementioned methods will be considered by one example.
Real-Time Communication Analysis for On-Chip Networks with Wormhole Switching
Authors: Zheng Shi, Alan Burns
Venue: Proceedings of the Second ACM/IEEE International Symposium on Networks-on-Chip (2008)

In this paper, we discuss a real-time on-chip communication service with a priority-based wormhole switching policy. A novel off-line schedulability analysis approach is presented. By evaluating diverse inter-relationships among the traffic-flows, this approach can predict the packet network latency based on two quantifiable different delays: direct interference from higher priority traffic-flows and indirect interference from other higher priority traffic-flows. Due to the inevitable existence of parallel interference, we prove that the general problem of determining the exact schedulability of real-time traffic-flow over the onchip network is NP-hard. However the results presented do form an upper bound. In addition, an error in a previous published scheduling approach is illustrated and remedied. Utilizing this analysis scheme, we can flexibly evaluate at design time the schedulability of a set of traffic-flows with different QoS requirements on a real-time SoC/NoC communication platform.
Convolution of Gaussian manifolds in a differentially FED artificial neural network
Authors: R. Manjunath, K. S. Gurumurthy
Venue: Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal Processing (2003)

The problem of function approximation to map a set of data with another is challenging When they are non linearly related. A variety of solutions based on Neural Networks are found in the literature. In this paper, a new class of Artificial neural networks with differential feedback are introduced. The different orders of differentials form a manifold of hyperplanes [2]. The spectral properties of these hyperplanes are explored.
A Novel Approach for Contrast Enhancement in Biomedical Images Based on Histogram Equalization
Authors: Ali Ziaei, Hojatollah Yeganeh, Karim Faez, Saman Sargolzaei
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

This paper presents a novel technique to increase the quality of medical images based on Histogram Equalization. In the proposed method first we have applied a noise reduction method and then we apply some suitable preprocessing on histogram of the medical images and after that histogram equalization has been applied on the new histogram. Our proposed method in despite of its simplicity has better results in compare to other usual methods based on histogram equalization. The quality of resulted images after applying our proposed methods has been tested on a database (medical images) with a confirmed criterion by viewer. Also we have considered a mathematical criterion for comparing our proposed algorithm with other available methods for contrast enhancement. Results show the better efficiency of the proposed method.
Preserving Privacy in Joining Recommender Systems
Authors: Chia-Lung Albert Hsieh, Justin Zhan, Deniel Zeng, Feiyue Wang
Venue: Proceedings of the 2008 International Conference on Information Security and Assurance (isa 2008) (2008)

In the E-commerce era, recommender system is introduced to share customer experience and comments. At the same time, there is a need for E-commerce entities to join their recommender system databases to enhance the reliability toward prospective customers and also to maximize the precision of target marketing. However, there will be a privacy disclosure hazard while joining recommender system databases. In order to preserve privacy in merging recommender system databases, we design a novel algorithm based on ElGamal scheme of homomorphic encryption.
Importance sampling of products from illumination and BRDF using spherical radial basis functions
Authors: Yu-Ting Tsai, Chin-Chen Chang, Qing-Zhen Jiang, Shr-Ching Weng
Venue: The Visual Computer: International Journal of Computer Graphics (2008)

In this paper, a new approach for the importance sampling of products from a complex high dynamic range (HDR) environment map and measured bidirectional reflectance distribution function (BRDF) data using spherical radial basis functions (SRBFs) is presented. In the pre-process, a complex HDR environment map and measured BRDF data are transformed into a scattered SRBF representation by using a non-uniform and non-negative SRBF fitting algorithm. An initial guess is determined for the fitting operation. In the run-time rendering process, after the product of the two SRBFs is evaluated, this is used to guide the number of samples. The sampling is done by mixing samples from the various &#x201c;product&#x201d; SRBFs using multiple importance sampling. Hence, the proposed approach efficiently renders images with multiple HDR environment maps and measured BRDFs.
Increasing Output Compaction in Presence of Unknowns Using an X-Canceling MISR with Deterministic Observation
Authors: Ritesh Garg, Richard Putman, Nur A. Touba
Venue: Proceedings of the 26th IEEE VLSI Test Symposium (2008)

Recently, an X-canceling MISR methodology was proposed in [Touba 07] which was based on providing very high probabilistic error coverage by canceling out X's in MISR signatures. This paper investigates a new methodology for using the x-canceling MISR architecture based on deterministically observing scan cells. The two main advantages of the proposed approach are (1) it can provide a higher amount of compaction, and (2) it is effective for larger percentages of X's in the output response. Also, this paper investigates a hybrid approach that combines X-masking with an X-canceling MISR. Experimental results indicate that significant amounts of output compression can be achieved with no loss of fault coverage.
Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods
Authors: Matthias W. Seeger
Venue: The Journal of Machine Learning Research (2008)

We propose a highly efficient framework for penalized likelihood kernel methods applied to multi-class models with a large, structured set of classes. As opposed to many previous approaches which try to decompose the fitting problem into many smaller ones, we focus on a Newton optimization of the complete model, making use of model structure and linear conjugate gradients in order to approximate Newton search directions. Crucially, our learning method is based entirely on matrix-vector multiplication primitives with the kernel matrices and their derivatives, allowing straightforward specialization to new kernels, and focusing code optimization efforts to these primitives only. Kernel parameters are learned automatically, by maximizing the cross-validation log likelihood in a gradient-based way, and predictive probabilities are estimated. We demonstrate our approach on large scale text classification tasks with hierarchical structure on thousands of classes, achieving state-of-the-art results in an order of magnitude less time than previous work. Parts of this work appeared in the conference paper Seeger (2007).
Parametric prediction of heap memory requirements
Authors: Víctor Braberman, Federico Fernández, Diego Garbervetsky, Sergio Yovine
Venue: Proceedings of the 7th international symposium on Memory management (2008)

This work presents a technique to compute symbolic polynomial approximations of the amount of dynamic memory required to safely execute a method without running out of memory, for Javalike imperative programs. We consider object allocations and deallocations made by the method and the methods it transitively calls. More precisely, given an initial configuration of the stack and the heap, the peak memory consumption is the maximum space occupied by newly created objects in all states along a run from it. We over-approximate the peak memory consumption using a scopedmemory management where objects are organized in regions associated with the lifetime of methods. We model the problem of computing the maximum memory occupied by any region configuration as a parametric polynomial optimization problem over a polyhedral domain and resort to Bernstein basis to solve it. We apply the developed tool to several benchmarks.
Expertise-based peer selection in Peer-to-Peer networks
Authors: Peter Haase, Ronny Siebes, Frank van Harmelen
Venue: Knowledge and Information Systems (2008)

Peer-to-Peer systems have proven to be an effective way of sharing data. Modern protocols are able to efficiently route a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a model in which peers advertise their expertise in the Peer-to-Peer network. The knowledge about the expertise of other peers forms a semantic topology. Based on the semantic similarity between the subject of a query and the expertise of other peers, a peer can select appropriate peers to forward queries to, instead of broadcasting the query or sending it to a random set of peers. To calculate our semantic similarity measure, we make the simplifying assumption that the peers share the same ontology. We evaluate the model in a bibliographic scenario, where peers share bibliographic descriptions of publications among each other. In simulation experiments complemented with a real-world field experiment, we show how expertise-based peer selection improves the performance of a Peer-to-Peer system with respect to precision, recall and the number of messages.
Adopting pen-based technology to facilitate active learning in the classroom: is it right for you?
Authors: Archana Chidanandan, Shannon Sexton
Venue: ACM SIGCSE Bulletin (2008)

In this work, we identify factors that should be examined when considering the adoption of collaboration-facilitating software and hardware and also determine what needs to be done to facilitate the use of this technology in the classroom.
MTSS: Multitask stack sharing for embedded systems
Authors: Bhuvan Middha, Matthew Simpson, Rajeev Barua
Venue: ACM Transactions on Embedded Computing Systems (TECS) (2008)

Out-of-memory errors are a serious source of unreliability in most embedded systems. Applications run out of main memory because of the frequent difficulty of estimating the memory requirement before deployment, either because it depends on input data, or because certain language features prevent estimation. The typical lack of disks and virtual memory in embedded systems has a serious consequence when an out-of-memory error occurs. Without swap space, the system crashes if its memory footprint exceeds the available memory by even 1 byte. This work improves reliability for multitasking embedded systems by proposing MTSS, a multitask stack sharing technique. If a task attempts to overflow the bounds of its allocated stack space, MTSS grows its stack into the stack memory space allocated for other tasks. This technique can avoid the out-of-memory error if the extra space recovered is sufficient to complete execution. Experiments show that MTSS is able to recover an average of 54&percnt; of the stack space allocated to the overflowing task in the free space of other tasks. In addition, unlike conventional systems, MTSS detects memory overflows, allowing the possibility of remedial action or a graceful exit if the recovered space is not enough. Alternatively, MTSS can be used for decreasing the required physical memory of an embedded system by reducing the initial memory allocated to each of the tasks and recovering the deficit by sharing stack with other tasks. The overheads of MTSS are low: the runtime and energy overheads are 3.1&percnt; and 3.2&percnt;, on average. These are tolerable given that reliability is the most important concern in virtually all systems, ahead of other concerns, such as runtime and energy.
New technique for fixing an Ethernet IPv6 address using the fedoracore operating system
Authors: A. Aaroud, A. Jamali, N. Najib
Venue: Ubiquity (2008)

During the course to deploy Ipv6, we found several critical implementation and operational issues which distract user and possibly prevent wide deployment of Ipv6. Among the problems we noticed stateless IP autoconfiguration, which provides for each nodes connected to the network an IP address. However, two nodes may have the same address, and a network conflict appears. In this case a manual IP address, which depends on restarting Network Interface Card, is required. In this paper, we present a technique that, independently of rebooting NIC, maintain the IP address fix. Validation is done by using Fedoracore Operating System.
Symmetries of hyperbolic system of 2-dimensional quasilinear equations
Authors: Sergey I. Senashov, Alexander Yakhno, Lilia Yakhno
Venue: Proceedings of the 10th WSEAS International Conference on APPLIED MATHEMATICS (2006)

In this paper a hyperbolic system of 2-dimensional quasilinear equations is considered from the point of view of the highest symmetries. The symmetries of the first order are constructed and the theorem of the existence of the highest symmetries is formulated.
Effects of MERIS L1b radiometric calibration on regional land cover mapping and land products
Authors: R. Zurita-Milla, J. G. P. W. Clevers, M. E. Schaepman, M. Kneubuehler
Venue: International Journal of Remote Sensing (2007)

The information derived from remotely sensed data must be carefully used because there are many sources of error that potentially affect its quality. In this respect, an accurate full calibration process of any sensor is essential because it can minimise various uncertainties and errors that reduce the final quality of the products derived from remotely sensed data. This paper presents several calibration efforts performed on MERIS data and subsequently focuses on the smile effect as well as on the vicarious calibration corrections. The implications of these corrections are evaluated using a MERIS full resolution level 1b image that was acquired over The Netherlands. A thematic approach, based on regional land cover mapping using linear spectral unmixing, and a continuous approach, based on continuous variables (FAPAR, MTCI and NDVI), are used to quantify these implications. Even though MERIS has a very high radiometric quality, results point out that these radiometric effects are consistently present in the final MERIS products. We also conclude that MERIS, after including all potential corrections investigated here, does not exhibit significant (radiometric) deficiencies. However, from a strict point of view, all the proposed radiometric corrections should be applied to the data so that the retrieval of quantitative information can be done with the highest possible quality. The use of fully radiometrically corrected data will also facilitate multitemporal comparisons. Therefore, we finally conclude that a systematic application of all relevant calibration parameters will increase the long term comparability of MERIS measurements in such a way that more emphasis can be put on the retrieval of MERIS products.
The State of IT Auditing in 2007
Authors: Gary Hinson
Venue: The EDP Audit, Control, and Security Newsletter (2007)

Summing-up the state of such a broad professional field in just a few short pages is not easy so, in place of a thousand words, here is a picture. This article examines the state of IT auditing today, looking at issues such as pressures on the profession, characteristics of modern IT auditors plus the tools and techniques available to them, and ends by gazing into the crystal ball to see what might be coming next.
GreenFS: making enterprise computers greener by protecting them better
Authors: Nikolai Joukov, Josef Sipek
Venue: Proceedings of the 3rd ACM SIGOPS/EuroSys European Conference on Computer Systems 2008 (2008)

Hard disks contain data - frequently an irreplaceable asset of high monetary and non-monetary value. At the same time, hard disks are mechanical devices that consume power, are noisy, and fragile when their platters are rotating. In this paper we demonstrate that hard disks cause different kinds of problems for different types of computer systems and demystify several common misconceptions. We show that solutions developed to date are incapable of solving the power consumption, noise, and data reliability problems without sacrificing hard disk life-time, data reliability, or user convenience. We considered data reliability, recovery, performance, user convenience, and hard disk-caused problems together at the enterprise scale. We have designed GreenFS: a fan-out stackable file system that offers all-time all-data run-time data protection, improves performance under typical user workloads, and allows hard disks to be kept off most of the time. As a result, GreenFS improves enterprise data protection, minimizes disk drive-related power consumption and noise and increases the chances of disk drive survivability in case of unexpected external impacts.
Performance evaluation of VoIP over WLAN networks using Weibull distribution for canal emulation
Authors: Omar Carvalho Branquinho, Alessandra Bussolin Bandeira, Fernando Lino, Adriano Almeida Góes, Norma Reggiani
Venue: Proceedings of the 2007 Euro American conference on Telematics and information systems (2007)

This article investigates VoIP performance over WLAN (WVoIP) through qualitative and quantitative point of view, considering degradation with the mobility. The results was obtained through a channel emulator to produce the Weibull distribution. Measurements results with a robot showed that this distribution is adequate to represent WLAN environment instability. The test utilized the CODECs G711 and GSM. The article presents preliminary results that indicate the effect of the instability of wireless environment in the VoIP performance. The results indicate a significant variation of voice quality, considering the severity of the phenomena emulated. The behaviors of the CODECs are evaluated considering the different characteristics of bandwidth and robustness.
Wireless Sensor Network Industrial View? What Will Be the Killer Apps for Wireless Sensor Network?
Authors: Ming-Whei Feng
Venue: Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008) (2008)

One of the key technologies associated with ubiquitous network society services is wireless sensor network (WSN). The WSN technology incorporates multiple technology components such as wireless, sensor, and embedded system. WSN was quoted by the MIT Technology Review as one of the technologies that will create giant impact to future life styles and various industrial segments. For WSN applications, the sensor device is the key since they need to be deployed to collect environmental data for further analysis. According to the analysis report by On World, the CAGR for sensor nodes deployed worldwide will be 216%, and the revenue of sensor chips will reach US$12.1 billions in 2010. Therefore it becomes one of the most important & potential technologies.Wireless sensor network enables connectivity and intelligence for sensor applications that will provide advanced monitoring, automation, and control solutions for a range of industries. There are nearly unlimited numbers of WSN markets that have different technology considerations such as frequencies, sampling rate, topologies, sensor to use, etc. In this panel section, it is our honor to invite experts in WSN applications or industries to discuss (1) what will be the killer applications for wireless sensor network, and (2) their associated technology requirements.
From security patterns to implementation using petri nets
Authors: Viktor Horvath, Till Dörges
Venue: Proceedings of the fourth international workshop on Software engineering for secure systems (2008)

Security Patterns - the adaption of Design Patterns by Gamma et al. to security - have not quite met the expectations since Yoder and Barcalow pioneered the field. The two main reasons for this are the lack of formalisation and the fact that security often permeates all parts of a software, which is hard to encapsulate in a single pattern. This paper investigates and presents our method of using Petri nets to first model security patterns on an abstract level. Gradual and intuitive refinement of the Petri nets then permits the creation of a running Petri net implementation - very much in the sense of model driven software engineering (MDSE) and model driven security (MDS). The Petri nets are modelled and executed using Renew - both IDE and virtual machine.