ppxscal/embedding_network huggingface dataset:
A spatially-adaptive neural network approach to regularized image restoration
Authors: Alex S. Palmer, Moe Razaz, Danilo P. Mandic
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2002)

When using a regularized approach for image restoration there is always a compromise between image sharpness and noise suppression. Since noise is removed at the cost of edges and detail within the image, there is a need to introduce algorithms which exhibit some kind of memory and cater for the spatial structure of an image. To this cause, we introduce an efficient restoration algorithm, based on a modified adaptive Hopfield neural network. The algorithm is capable of spatially regularizing an image and thereby preserving data fidelity around edges while simultaneously suppressing noise in more noticeable areas such as smooth regions. The proposed method demonstrates an improvement in restoration quality over existing adaptive and non-adaptive approaches. This is illustrated with simulations on benchmark images under varying noise levels.
Calculation of Performance of UHVDC Grounding Electrode under the Consideration of the Self-Resistivity of Electrode
Authors: Jianwu Wang, Xishan Wen, Zhongdong Du
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

The performance parameters of UHVDC cirque grounding electrode are computed by 3D finite element method when self-resistance of grounding electrode is involved in. This paper compare grounding performance of single-cirque, double-cirques and three-cirques grounding electrode on condition of same electrode length. At the same time, because double-layer soil can instead of a majority of uneven soil, so a series of influencing factor of grounding performance such as electrode's depth of burial, top-layer soil resistivity and bottom-layer soil resistivity are analyzed when considered uneven soil model.
Merging distributed database summaries
Authors: Mounir Bechchi, Guillaume Raschia, Noureddine Mouaddib
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

The database summarization system coined S<scp>aint</scp>E<scp>ti</scp>Q provides multi-resolution summaries of structured data stored into acentralized database. Summaries are computed online with a conceptual hierarchical clustering algorithm. However, most companies work in distributed legacy environments and consequently the current centralized version of S<scp>aint</scp>E<scp>ti</scp>Q is either not feasible (privacy preserving) or not desirable (resource limitations). To address this problem, we propose new algorithms to generate a single summary hierarchy given two distinct hierarchies, without scanning the raw data. The Greedy Merging Algorithm (GMA) takes all leaves of both hierarchies and generates the optimal partitioning for the considered data set with regards to a cost function (compactness and separation). Then, a hierarchical organization of summaries is built by agglomerating or dividing clusters such that the cost function may emphasize local or global patterns in the data. Thus, we obtain two different hierarchies according to the performed optimisation. However, this approach breaks down due to its exponential time complexity. Two alternative approaches with constant time complexity w.r.t. the number of data items, are proposed to tackle this problem. The first one, called Merge by Incorporation Algorithm (MIA), relies on the S<scp>aint</scp>E<scp>ti</scp>Q engine whereas the second approach, named Merge by Alignment Algorithm (MAA), consists in rearranging summaries by levels in a top-down manner. Then, we compare those approaches using an original quality measure in order to quantify how good our merged hierarchies are. Finally, an experimental study, using real data sets, shows that merging processes (MIA and MAA) are efficient in terms of computational time.
Locking and Deadlock Detection in Distributed Data Bases
Authors: D. A. Menasce
Venue: IEEE Transactions on Software Engineering (1979)

This paper descrbes two protocols for the detection of deadlocks in distributed data bases-a hierarchically organized one and a distributed one. A graph model which depicts the state of execution of all transactions in the system is used by both protocols. A cycle in this graph is a necessary and sufficient condition for a deadlock to exist. Nevertheless, neither protocol requires that the global graph be built and maintained in order for deadlocks to be detected. In the case of the hierarchical protocol, the communications cost can be optimized if the topology of the hierarachy is appropriately chosen.
Machine learning-based receiver operating characteristic (ROC) curves for crisp and fuzzy classification of DNA microarrays in cancer research
Authors: Leif E. Peterson, Matthew A. Coleman
Venue: International Journal of Approximate Reasoning (2008)

Receiver operating characteristic (ROC) curves were generated to obtain classification area under the curve (AUC) as a function of feature standardization, fuzzification, and sample size from nine large sets of cancer-related DNA microarrays. Classifiers used included k-nearest neighbor (kNN), naive Bayes classifier (NBC), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), learning vector quantization (LVQ1), logistic regression (LOG), polytomous logistic regression (PLOG), artificial neural networks (ANN), particle swarm optimization (PSO), constricted particle swarm optimization (CPSO), kernel regression (RBF), radial basis function networks (RBFN), gradient descent support vector machines (SVMGD), and least squares support vector machines (SVMLS). For each data set, AUC was determined for a number of combinations of sample size, total sum[-log(p)] of feature t-tests, with and without feature standardization and with (fuzzy) and without (crisp) fuzzification of features. Altogether, a total of 2,123,530 classification runs were made. At the greatest level of sample size, ANN resulted in a fitted AUC of 90%, while PSO resulted in the lowest fitted AUC of 72.1%. AUC values derived from 4NN were the most dependent on sample size, while PSO was the least. ANN depended the most on total statistical significance of features used based on sum[-log(p)], whereas PSO was the least dependent. Standardization of features increased AUC by 8.1% for PSO and -0.2% for QDA, while fuzzification increased AUC by 9.4% for PSO and reduced AUC by 3.8% for QDA. AUC determination in planned microarray experiments without standardization and fuzzification of features will benefit the most if CPSO is used for lower levels of feature significance (i.e., sum[-log(p)]~50) and ANN is used for greater levels of significance (i.e., sum[-log(p)]~500). When only standardization of features is performed, studies are likely to benefit most by using CPSO for low levels of feature statistical significance and LVQ1 for greater levels of significance. Studies involving only fuzzification of features should employ LVQ1 because of the substantial gain in AUC observed and low expense of LVQ1. Lastly, PSO resulted in significantly greater levels of AUC (89.5% average) when feature standardization and fuzzification were performed. In consideration of the data sets used and factors influencing AUC which were investigated, if low-expense computation is desired then LVQ1 is recommended. However, if computational expense is of less concern, then PSO or CPSO is recommended.
Leveraging e-transportation in real-time traffic evacuation management
Authors: Georgiana L. Hamza-Lup, Kien A. Hua, Rui Peng
Venue: Electronic Commerce Research and Applications (2007)

As part of intelligent transportation systems, Internet-connected sensors and cameras have become ubiquitous along roads and highways, enabling many novel e-transportation applications. In this research, we leverage this emerging technology to improve the surface transportation aspect of homeland security, by enhancing its support for evacuation in case of terrorist attacks or other unpredictable disasters. In particular, we extend our existing work on developing a Smart Traffic Evacuation Management System (STEMS), by proposing more efficient evacuation algorithms that dynamically generate evacuation plans for both single and multiple incidents scenarios, based on real-time traffic information obtained from sensor data available through the Web.
Yield-driven near-threshold SRAM design
Authors: Gregory K. Chen, David Blaauw, Trevor Mudge, Dennis Sylvester, Nam Sung Kim
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

Voltage scaling is desirable in SRAM to reduce energy consumption. However, commercial SRAM is prone to functional failures when Vdd is scaled. Several SRAM designs scale Vdd to 200--300mV to minimize energy per access, but these designs do not consider SRAM robustness, limiting them to small arrays and sensor type applications. We examine the effects on area and energy for a differential 6T, single-ended 6T with power rail collapsing and an 8T bitcell as Vdd is scaled and the bitcells are sized appropriately to maintain robustness. SRAM robustness is examined using importance sampling to reduce simulation runtime. At high voltages, the differential 6T bitcell is the smallest for the same failure rate, but the 8T bitcell is smaller when Vdd is scaled below 450mV. For Vdd below Vth, bitcells must be sized greatly to retain robustness and large arrays become impractical. The differential 6T and 8T designs have the lowest dynamic energy consumption, and the single-ended 6T design has the lowest leakage. The supply voltage for minimum energy operation depends on cache configuration and can be well above Vth for large caches with low dynamic activity.
Web Based Injury Surveillance System (WBISS) for Road Traffic Injuries
Authors: Achala Upendra Jayatilleke, Chandrajith Ashuboda Marasinghe, Shinji Nakahara, St Nandasara, Achini Jayatilleke, Masamine Jimba
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Road traffic injuries are a major, but neglected public health problem in Sri Lanka. As their economic costs are high and emergency trauma care is lacking in the country, the prevention of the road traffic injuries is extremely important. To prevent road traffic injuries, accurate information are mandatory on modes, patterns and trends of crashes and injuries. However, existing surveillance systems in Sri Lanka carry enormous deficiencies in receiving, recording and disseminating information of road traffic crashes and injuries. Hence, we designed a web based injury surveillance system (WBISS) to overcome these deficiencies and to improve the inter-sector coordination for road traffic injury prevention in Sri Lanka. We adopted to WHO injury surveillance guidelines and used standard injury scales in designing this system. The system utilizes available resources without causing extra burden to government of Sri Lanka. This WBISS collects data on road traffic injuries from hospitals and relevant police stations. Data will be entered online to a web based data base. WBISS will provide accurate, complete, timely data on patterns and determinants of road traffic injuries and will help to implement timely interventions. This system will also aid the frequent updating of the knowledge on road traffic injuries in the country. WBISS can be used worldwide. Other developing countries can also share the same system.
Analysis of Logic Circuits with Faults Using Input Signal Probabilities
Authors: K. P. Parker
Venue: IEEE Transactions on Computers (1975)

A probabilistic treatment of general combinational networks has been developed. Using the notions of the probability of a signal and signal independence, algorithms have been presented to calculate the probability of the output of a logic circuit being 1. Simplifications to the algorithm result when sets of input probabilities are given the same value, and this process called bundling is described in the paper. Finally, a series of examples illustrate the application of the probabilistic approach to the analysis of faulty logic circuits.
A Hybrid Algorithm Based on Particle Swarm Optimization and Simulated Annealing for Job Shop Scheduling
Authors: Hongwei Ge, Wenli Du, Feng Qian
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

In this paper, an effective hybrid algorithm based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) is proposed for solving the minimum makespan problem of the job shop scheduling problem (JSSP). The hybrid algorithm combines the high global search efficiency of PSO with the powerful ability to avoid being trapped in local minimum of SA. In the particle swarm system, a novel concept for the distance and velocity of a particle is proposed to pave the way for the job-shop scheduling problem, and then the formulations of the novel PSO algorithm for the JSSP is also presented. In the simulated annealing process, a new solution in the neighborhood of the original one is generated by using a designed ë search. The hybrid algorithm is examined using a set of benchmark instances with various sizes and levels of hardness and compared with other approaches reported in some existing literatures. The computational results validate the effectiveness of the proposed approaches.
Resilient rights protection for sensor streams
Authors: Radu Sion, Mikhail Atallah, Sunil Prabhakar
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Today's world of increasingly dynamic computing environments naturally results in more and more data being available as fast streams. Applications such as stock market analysis, environmental sensing, web clicks and intrusion detection are just a few of the examples where valuable data is streamed. Often, streaming information is offered on the basis of a non-exclusive, single-use customer license. One major concern, especially given the digital nature of the valuable stream, is the ability to easily record and potentially "re-play" parts of it in the future. If there is value associated with such future re-plays, it could constitute enough incentive for a malicious customer (Mallory) to duplicate segments of such recorded data, subsequently re-selling them for profit. Being able to protect against such infringements becomes a necessity. In this paper we introduce the issue of rights protection for discrete streaming data through watermarking. This is a novel problem with many associated challenges including: operating in a finite window, single-pass, (possibly) high-speed streaming model, surviving natural domain specific transforms and attacks (e.g.extreme sparse sampling and summarizations), while at the same time keeping data alterations within allowable bounds. We propose a solution and analyze its resilience to various types of attacks as well as some of the important expected domain-specific transforms, such as sampling and summarization. We implement a proof of concept software (wms.*) and perform experiments on real sensor data from the NASA Infrared Telescope Facility at the University of Hawaii, to assess encoding resilience levels in practice. Our solution proves to be well suited for this new domain. For example, we can recover an over 97% confidence watermark from a highly down-sampled (e.g. less than 8%) stream or survive stream summarization (e.g. 20%) and random alteration attacks with very high confidence levels, often above 99%.
Privacy-preserving remote diagnostics
Authors: Justin Brickell, Donald E. Porter, Vitaly Shmatikov, Emmett Witchel
Venue: Proceedings of the 14th ACM conference on Computer and communications security (2007)

We present an efficient protocol for privacy-preserving evaluation of diagnostic programs, represented as binary decision trees or branching programs. The protocol applies a branching diagnostic program with classification labels in the leaves to the user's attribute vector. The user learns only the label assigned by the program to his vector; the diagnostic program itself remains secret. The program's owner does not learn anything. Our construction is significantly more efficient than those obtained by direct application of generic secure multi-party computation techniques. We use our protocol to implement a privacy-preserving version of the Clarify system for software fault diagnosis, and demonstrate that its performance is acceptable for many practical scenarios.
The production of peer-to-peer video-streaming networks
Authors: Dafu Lou, Yongyi Mao, Tet H. Yeap
Venue: Proceedings of the 2007 workshop on Peer-to-peer streaming and IP-TV (2007)

We introduce the notions of production and saturation time for peer-to-peer real-time video-streaming networks. Due to the fact that video-streaming is divided into small blocks to transmit, production, adopted from economics, is defined as the number of users that have obtained video block m by time t. Saturation time refers to the time when the system leaves the state where there have been more users requesting block m than the number of users that the system could have supplied. Based on those two notions, we provide a lower bound on the achievable production functions. Simulation results are provided for a heuristic protocol which appears to confirm the lower bound in terms of production and saturation time. The analysis results have also been confirmed by simulation using a stochastic model.
MCS
Venue: IEEE Computer Graphics and Applications (1982)

The largest, most advanced CAD/CAM software package available to industry . . . an integrated design, management information and manufacturing system. It provides the capabilities for engineers to fully automate the design and manufacturing of a product. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Dynamic Restructuring in an Experimental Operating System
Authors: H. Goullon
Venue: IEEE Transactions on Software Engineering (1978)

A well-structured system can easily be understood and modified. Moreover, it may lend itself even to dynamic modification: under special conditions, the possibility of changing system parts while the system is running can be provided at little additional cost. Our approach to the design of dynamically modifiable systems is based on the principle of data abstraction applied to types and modules. It allows for dynamic replacement or restructuring of a module's implementation if this does not affect its specification (or if it leads to some kdnd of compatible specification). The fundamental principles of such "replugging" are exhibited, and the implementation of a replugging facility for an experimental operating system on a PDP-11/40E is described.
An Experimental Study in Domain Engineering
Authors: Eduardo Santana de Almeida, Alexandre Alvaro, Vinicius Cardoso Garcia, Daniel Lucredio
Venue: Proceedings of the 33rd EUROMICRO Conference on Software Engineering and Advanced Applications (2007)

This paper reports on an experimental study in trying to analyze a domain engineering process in order to evaluate its efficiency and difficulties of using it in a domain engineering project. The study discusses since its definition until the lessons learned.
Attention driven reference resolution in multimodal contexts
Authors: J. D. Kelleher
Venue: Artificial Intelligence Review (2006)

In recent years a number of psycholinguistic experiments have pointed to the interaction between language and vision. In particular, the interaction between visual attention and linguistic reference. In parallel with this, several theories of discourse have attempted to provide an account of the relationship between types of referential expressions on the one hand and the degree of mental activation on the other. Building on both of these traditions, this paper describes an attention based approach to visually situated reference resolution. The framework uses the relationship between referential form and preferred mode of interpretation as a basis for a weighted integration of linguistic and visual attention scores for each entity in the multimodal context. The resulting integrated attention scores are then used to rank the candidate referents during the resolution process, with the candidate scoring the highest selected as the referent. One advantage of this approach is that the resolution process occurs within the full multimodal context, in so far as the referent is selected from a full list of the objects in the multimodal context. As a result situations where the intended target of the reference is erroneously excluded, due to an individual assumption within the resolution process, are avoided. Moreover, the system can recognise situations where attention cues from different modalities make a reference potentially ambiguous.
Routing Mechanism for Reliable Sensor Network Applications
Authors: Jiann-Liang Chen, Huan-Wen Tzeng, Chia-Ping Lai
Venue: Proceedings of the Second International Conference on Systems and Networks Communications (2007)

A sensor node is naturally exposed to various sources of unreliable communication channels and node failures. Sensor nodes have many failure modes, and each failure degrades the network performance. This work develops a novel mechanism based on a hybrid cluster-based routing protocol to specify the best reliable routing path for sensor networking. Table-driven intra-cluster routing and on-demand inter-cluster routing are combined by changing the relationship between clusters for sensor networks. Applying a reliable routing mechanism in sensor networks can improve routing reliability, maintain low packet loss, minimize management overhead and save energy consumption. Simulation results indicate that the reliability of the proposed routing mechanism is around 25% higher than that of the Dynamic Source Routing and Ad hoc On-demand Distance Vector routing mechanisms.
A Dynamic Combination Forecast Model for Analysis Transport Volume Time Series
Authors: Lili Qu, Yan Chen, Ming Yang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

A dynamic combined forecasting model for transport freight volume time series prediction is established. The time-varying combined weights are computed with the Bayesian posterior probability based on each local predictor's performance. This method's forecast performance is reliable, because it tracks the real-time prediction precision of the combined models and adjusts their credit values (weights) according to their past predictive error. The forgetting factor is proposed as a threshold in order to avoid the singular forecasting model's performance change so intensely over different time intervals as to cause unimaginable effect to the latter online weights computation. In error evaluation system, the performance of the proposed dynamic combination forecast model outperforms the singular predictor used respectively as well as some conventional combination forecasting methods.
Compressed Aggregations for mobile OLAP Dissemination
Authors: Ilias Michalarias, Arkadiy Omelchenko
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

As wireless network infrastructure becomes more re- liable, an increasing number of traditional desktop ap- plications, beyond common web browsing, migrate to portable devices. Since ubiquitous access has become a critical success factor for most enterprises, business mobile information systems become a necessity. This paper deals with the case of mobile access to multidi- mensional data. We introduce the m-Dwarf, a com- pressed data cube physical structure, which has no loss of semantic information and is explicitly designed for mobile applications. m-Dwarfs are integrated in a mo- bile OLAP dissemination system. Experimental eval- uation reveals a substantial reduction of access time, energy consumption and bandwidth utilization.