ppxscal/embedding_network huggingface dataset:
Local and Global Features Extracting and Fusion for Microbial Recognition
Authors: Li Xiaojuan, Chen Cunshe, Liang Anbo, Shi Yan
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

It is presented that extraction of global and local feature based on digital microbial image analysis and fusion local and global features for microbe recognition. The global features are extracted by invariant moments and co-occurrence matrix, in which invariant moments computation is simplified by computing geometric moment and central moment based on the edge of microbe instead of the field of it. Curvature changing detection for microbe is characterized as local features by Wavelet Transform. Min-Max was applied for normalization and after the fusion of normalized global match degree and normalized local match degree, the recognition result is the class that included the template image corresponding to the largest fused match degree. The experimental results show that fusing local and global features is effective for microbe image analysis and recognition.
Scalability problems of simple genetic algorithms
Authors: Dirk Thierens
Venue: Evolutionary Computation (1999)

Scalable evolutionary computation has. become an intensively studied research topic in recent years. The issue of scalability is predominant in any field of algorithmic design, but it became particularly relevant for the design of competent genetic algorithms once the scalability problems of simple genetic algorithms were understood. Here we present some of the work that has aided in getting a clear insight in the scalability problems of simple genetic algorithms. Particularly, we discuss the important issue of building block mixing. We show how the need for mixing places a boundary in the GA parameter space that, together with the boundary from the schema theorem, delimits the region where the GA converges reliably to the optimum in problems of bounded difficulty. This region shrinks rapidly with increasing problem size unless the building blocks are tightly linked in the problem coding structure. In addition, we look at how straightforward extensions of the simple genetic algorithm---namely elitism, niching, and restricted mating are not significantly improving the scalability problems.
Extending query translation to cross-language query expansion with markov chain models
Authors: Guihong Cao, Jianfeng Gao, Jian-Yun Nie, Jing Bai
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

Dictionary-based approaches to query translation have been widely used in Cross-Language Information Retrieval (CLIR) experiments. However, translation has been not only limited by the coverage of the dictionary, but also affected by translation ambiguities. In this paper we propose a novel method of query translation that combines other types of term relation to complement the dictionary-based translation. This allows extending the literal query translation to related words, which produce a beneficial effect of query expansion in CLIR. In this paper, we model query translation by Markov Chains (MC), where query translation is viewed as a process of expanding query terms to their semantically similar terms in a different language. In MC, terms and their relationships are modeled as a directed graph, and query translation is performed as a random walk in the graph, which propagates probabilities to related terms. This framework allows us to incorporating different types of term relation, either between two languages or within the source or target languages. In addition, the iterative training process of MC allows us to attribute higher probabilities to the target terms more related to the original query, thus offers a solution to the translation ambiguity problem. We evaluated our method on three CLIR benchmark collections, and obtained significant improvements over traditional dictionary-based approaches.
A neural-network-based approach to detecting rectangular objects
Authors: Mu-Chun Su, Chao-Hsin Hung
Venue: Neurocomputing (2007)

Many man-made objects are composed of a number of some simple geometric shapes such as lines, circles, rectangles, etc. Therefore, the detection of rectangular objects is an important issue to some practical applications such as the detection of buildings and vehicles in aerial imagery, the detection of license plates in car images, etc. Several methods have been proposed for solving the problem of the detection of rectangular objects. While some approaches are based on the detecting lines, some approaches are based on the Hough transform. Each approach has its own advantages and disadvantages (e.g., computational load). In this paper, we propose a class of neural networks with a special type of neural junctions for the detection of rectangular objects. The proposed neural networks can be trained in either an unsupervised mode or a batch mode. In contrast to some popular clustering algorithms such as the fuzzy c-means algorithm and the fuzzy c-rectangular shells algorithm, our approach is not based on minimizing an objective function but based on the idea of competitive learning. Based on the idea of competitive learning, the computational load can be decreased. Several data sets were tested to illustrate the effectiveness of our proposed approach.
A Method of Clustering Combination Applied to Satellite Image Analysis
Authors: Ivan O. Kyrgyzov, Henri Maitre, Marine Campedel
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

An algorithm for combining results of different clusterings is presented in this paper, the objective of which is to find groups of patterns which are common to all clusterings. The idea of the proposed combination is to group those samples which are in the same cluster in most cases. We formulate the combination as the resolution of a linear set of equations with binary constraints. The advantage of such a formulation is to provide an objective function for the combination. To optimize the objective function we propose an original unsupervised algorithm. Furthermore, we propose an extension adapted in case of a huge volume of data. The combination of clusterings is performed on the results of different clustering algorithms applied to SPOT5 satellite images and shows the effectiveness of the proposed method.
The Design and Evaluation of Techniques for Route Diversity in Distributed Hash Tables
Authors: Cyrus Harvesf, Douglas M. Blough
Venue: Proceedings of the Seventh IEEE International Conference on Peer-to-Peer Computing (2007)

We present a replica placement scheme for any distributed hash table that uses a prefix-matching routing scheme and evaluate the number of replicas necessary to produce a desired number of disjoint routes. We show through simulation that this placement can make a significant improvement in routing robustness over other placements. Furthermore, we consider another route diversity mechanism that we call neighbor set routing and show that, when used with our replica placement, it can successfully route messages to a correct replica even with a quarter of the nodes in the system failed at random. Finally, we demonstrate a family of replica query strategies that can trade off response time and system load. We present a hybrid query strategy that keeps response time low without producing too high a load.
What do we know about the h index?
Authors: Lutz Bornmann, Hans-Dieter Daniel
Venue: Journal of the American Society for Information Science and Technology (2007)

Jorge Hirsch (2005a, 2005b) recently proposed the h index to quantify the research output of individual scientists. The new index has attracted a lot of attention in the scientific community. The claim that the h index in a single number provides a good representation of the scientific lifetime achievement of a scientist as well as the (supposed) simple calculation of the h index using common literature databases lead to the danger of improper use of the index. We describe the advantages and disadvantages of the h index and summarize the studies on the convergent validity of this index. We also introduce corrections and complements as well as single-number alternatives to the h index.
An Ontology Framework for EC Automated Negotiation Protocol
Authors: Shujuan Ji, Qijia Tian, Yongquan Liang, Hongmei Yang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

Negotiation protocol is one of the cores of agent-mediated automated negotiation in future electronic commerce. Nowadays, most of the negotiation protocols are hard-coded into agent. Thus agent can only use the single protocol during its lifecycle or go off line to be reprogrammed with another one. To realize a flexible approach that permits agent to negotiate with arbitrary negotiation mechanism, we propose an ontology framework. This framework comprises two levels: the abstract level and the implementation level. In the abstract level, an extended Colored Petri net (ECPN) is used to represent and verify the concepts and their relationships obtained from the requirement analysis phase; in the implementation level, these concepts and relationships are transformed into classes, properties and individuals using Protégé. Furthermore, the inconsistency, which may exist among these classes, properties and individuals, is tested using RACER and the tools offered by Protégé. At last, we create an API program for this ontology.
Improving evolutionary class testing in the presence of non-public methods
Authors: Stefan Wappler, Ina Schieferdecker
Venue: Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering (2007)

Automating the generation of object-oriented unit tests is a challenging task. This is mainly due to the complexity and peculiarities that the principles of object-orientation imply. One of these principles is the encapsulation of class members which prevents non-public methods and attributes of the class under test from being freely accessed. This paper suggests an improvement of our automated search-based test generation approach which particularly addresses the test of non-public methods. We extend our objective functions by an additional component that accounts for encapsulation. Additionally, we propose a modification of the search space which increases the efficiency of the approach. The value of the improvement in terms of achieved code coverage is demonstrated by a case study with 7 real-world test objects. In contrast to other approaches which break encapsulation in order to test non-public methods, the tests generated by our approach inherently guarantee that class invariants are not violated. At the same time, refactorings of the encapsulated class members will not break the generated tests
Application of bacterial foraging technique trained artificial and wavelet neural networks in load forecasting
Authors: M. Ulagammai, P. Venkatesh, P. S. Kannan, Narayana Prasad Padhy
Venue: Neurocomputing (2007)

A new load forecasting (LF) approach using bacterial foraging technique (BFT) trained wavelet neural network (WNN) is proposed in this paper. Artificial neural network (ANN) is combined with wavelet transform called wavelet neural network is applied for LF. The parameters of translation and dilation in the wavelet nodes and the weighting factors in the weighting nodes are tuned using BFT optimization. With the advantages of global search abilities of BFT as well as the multiresolution and localizing natures of wavelets, the networks are constructed which identifies the inherent non-linear characteristics of power system loads. The proposed approach is validated with Tamil Nadu Electricity Board (TNEB) system, India. The comparison of Delta Rule and BFT-based LF for different periods are depicted with their mean absolute percentage errors (MAPE).
Contextualized Videos: Combining Videos with Environment Models to Support Situational Understanding
Authors: Yi Wang David M. Krum, Enylton M. Coelho Doug A. Bowman
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

Multiple spatially-related videos are increasingly used in security, communication, and other applications. Since it can be difficult to understand the spatial relationships between multiple videos in complex environments (e.g. to predict a person&#x2019;s path through a building), some visualization techniques, such as video texture projection, have been used to aid spatial understanding. In this paper, we identify and begin to characterize an overall class of visualization techniques that combine video with 3D spatial context. This set of techniques, which we call contextualized videos, forms a design palette which must be well understood so that designers can select and use appropriate techniques that address the requirements of particular spatial video tasks. In this paper, we first identify user tasks in video surveillance that are likely to benefit from contextualized videos and discuss the video, model, and navigation related dimensions of the contextualized video design space. We then describe our contextualized video testbed which allows us to explore this design space and compose various video visualizations for evaluation. Finally, we describe the results of our process to identify promising design patterns through user selection of visualization features from the design space, followed by user interviews.
Proceedings of the 4th ACM workshop on Geographical information retrieval
Venue: Workshop On Geographic Information Retrieval (2007)

We take great pleasure in welcoming you all to the Workshop on Geographic Information Retrieval (GIR'07). This is the fourth in a series of workshops on GIR, which have been held alternately at SIGIR and CIKM since 2004. The workshops are now becoming firmly established, together with GeoCLEF, as a forum for the exchange of information on the development and success of new techniques within the field of Geographic Information Retrieval. We are delighted to see a vibrant mix of regulars and newcomers at this year's workshop having received submissions from an increasing breadth of groups and locations, demonstrating that interest in GIR continues to grow. The call for papers resulted in an interesting variety of short and long papers related to differing aspects of GIR, including the analysis of geographic needs and the development of ontologies to support GIR, through to the perennial problems of unambiguously identifying geographic locations within text documents; the application of techniques to intelligently deal with and process user queries; the mining and exploitation of geographic information and a wide range of examples of the application of GIR. All papers were reviewed by at least two members of the programme committee. The 12 long and 9 short papers that were selected for presentation provide new insights into the state of the art in GIR and cast new light on the major challenges. We hope that the workshop will succeed not only in its aim of reporting on where we are now, but also on how we in the academic research community can set a distinctive, relevant and above all exciting research agenda for the coming year.
Efficient Surface Reconstruction using Generalized Coulomb Potentials
Authors: Andrei C. Jalba Jos B. T. M. Roerdink
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

We propose a novel, geometrically adaptive method for surface reconstruction from noisy and sparse point clouds, without orientation information. The method employs a fast convection algorithm to attract the evolving surface towards the data points. The force field in which the surface is convected is based on generalized Coulomb potentials evaluated on an adaptive grid (i.e., an octree) using a fast, hierarchical algorithm. Formulating reconstruction as a convection problem in a velocity field generated by Coulomb potentials offers a number of advantages. Unlike methods which compute the distance from the data set to the implicit surface, which are sensitive to noise due to the very reliance on the distance transform, our method is highly resilient to shot noise since global, generalized Coulomb potentials can be used to disregard the presence of outliers due to noise. Coulomb potentials represent long-range interactions that consider all data points at once, and thus they convey global information which is crucial in the fitting process. Both the spatial and temporal complexities of our spatially-adaptive method are proportional to the size of the reconstructed object, which makes our method compare favorably with respect to previous approaches in terms of speed and flexibility. Experiments with sparse as well as noisy data sets show that the method is capable of delivering crisp and detailed yet smooth surfaces.
Comparing Local and Global Software Effort Estimation Models -- Reflections on a Systematic Review
Authors: Stephen G. MacDonell, Martin J. Shepperd
Venue: Proceedings of the First International Symposium on Empirical Software Engineering and Measurement (2007)

BACKGROUND: the availability of multi-organisation data sets has made it possible for individual organisations to build and apply management models, even if they do not have data of their own. In the absence of any data this may be a sensible option, driven by necessity. However, if both cross-company (or global) and within-company (or local) data are available, which should be used in preference? PROBLEM: several research papers have addressed this question but without any apparent convergence of results. METHOD: we conduct a systematic review of empirical studies comparing global and local effort prediction systems. RESULTS: we located 10 relevant studies: 3 supported global models, 2 were equivocal and 5 supported local models. CONCLUSION: the studies do not have converging results. A contributing factor is that they have utilised different local and global data sets and different experimental designs thus there is substantial heterogeneity. We identify the need for common response variables and for common experimental and reporting protocols.
A Semi-automated Negotiation Process to Improve the Usability for Online Marketplaces
Authors: Lung Ngai, Phil Mak, Wan-Cheng Ni, Lian-Chen Liu, Cheng Wu
Venue: Proceedings of the 7th IEEE International Conference on Computer and Information Technology (2007)

Online marketplaces leverage information technology to bring together buyers and sellers, with greater effectiveness at massive scales; however, conflicts related to product prices are usually the bottlenecks of trading efficiency within these online marketplaces. An Embedded negotiation support function allows buyers and sellers to negotiate product prices via system interfaces; hence it would lead to greater trading efficiency. However, traditional negotiation process demands lengthy user engagement time with complicated procedures. A semi-automated negotiation process is proposed to reduce the human engagement time with simple procedures. Experimental results show that, the new approach will not damage the original negotiation success rate. In the future, it is important to implement an actual semi-automated negotiation support system for further evaluations.
Tutorial on separation results in process calculi via leader election problems
Authors: Maria Grazia Vigliotti, Iain Phillips, Catuscia Palamidessi
Venue: Theoretical Computer Science (2007)

We compare the expressive power of process calculi by studying the problem of electing a leader in a symmetric network of processes. We consider the @p-calculus with mixed choice, separate choice and internal mobility, value-passing CCS and Mobile Ambients, together with other ambient calculi (Safe Ambients, the Push and Pull Ambient Calculus and Boxed Ambients). We provide a unified approach for all these calculi using reduction semantics.
Finding structure in noisy text: topic classification and unsupervised clustering
Authors: Prem Natarajan, Rohit Prasad, Krishna Subramanian, Shirin Saleem, Fred Choi, Rich Schwartz
Venue: International Journal on Document Analysis and Recognition (2007)

This paper addresses two types of classification of noisy, unstructured text such as newsgroup messages: (1) spotting messages containing topics of interest, and (2) automatic conceptual organization of messages without prior knowledge of topics of interest. In addition to applying our hidden Markov model methodology to spotting topics of interest in newsgroup messages, we present a robust methodology for rejecting messages which are off-topic. We describe a novel approach for automatically organizing a large, unstructured collection of messages. The approach applies an unsupervised topic clustering procedure to generate a hierarchical tree of topics.
An effective method for state-of-charge estimation in wireless sensor networks
Authors: Christian Behrens, Ole Bischoff, Steffen Paul, Rainer Laur
Venue: Proceedings of the 5th international conference on Embedded networked sensor systems (2007)

This poster shows the work-in-progress results of an effective method for predicting the residual battery energy in WSN nodes including the battery behavior. This method uses a hybrid approach consisting of a deterministic part by counting credit points for any operation of the sensor node and a model-based State-of-Charge (SoC) estimation based on battery voltage and temperature. It is applied for Li-Ion accumulators on modified Tmote Sky motes. For demonstration purposes the method is used for cluster head selection in a cluster-based topology formation algorithm to ensure equal distribution of the cluster head role among the network nodes based on the residual energy.
Unidirectional Transport of Rights and Take-Grant Control
Authors: A. Lockman
Venue: IEEE Transactions on Software Engineering (1982)

One of the most critical and least understood aspects of protection is the exercise of control over the movement of rights between the subjects of a system. The conventional Take-Grant mechanism for exercising such control suffers from a puzzling and unfortunate limitation: it cannot enforce strictly unidirectional channels for the flow of rights. That is, if rights can be moved directly or indirectly from some subject p to another subject q, then one cannot prevent rights from flowing in the opposite direction, from q to p. This property limits the applicability of this mechanism and therefore that of any protection scheme utilizing it. We analyze the nature and ramifications of this limitation and demonstrate that its root cause is the fact that (under this mechanism) a right possessed by a sender suffices to authorize a movement of rights. We propose an alternative, "Take-Receive," model in which this limitation is eliminated, thus enabling the implementation of more useful protection disciplines. We prove this result by analyzing tl-e dynamic behavior of the proposed model.