Optimization of lipid production with a genome-scale model of Yarrowia lipolytica Background: Yarrowia lipolytica is a non-conventional yeast that is extensively investigated for its ability to excrete citrate or to accumulate large amounts of storage lipids, which is of great significance for single cell oil production. Both traits are thus of interest for basic research as well as for biotechnological applications but they typically occur simultaneously thus lowering the respective yields. Therefore, engineering of strains with high lipid content relies on novel concepts such as computational simulation to better understand the two competing processes and to eliminate citrate excretion. As an alternative approach to available genome scale reconstructions of Y. lipolytica, which were assembled by fully or partly automated reconstruction procedures [10, 11] , we transformed a functional and widely used scaffold of S. cerevisiae into the new reconstruction iMK735 by manually changing gene annotations, evaluating reversibilities of reactions and their compartmentalization and by adding or deleting species-specific reactions. This procedure resulted in a GSM that accurately predicts growth behavior of Y. lipolytica and can be used to simulate processes that are of importance for this yeast, like lipid production. However, further efforts regarding Genome scale models can be used for the optimization of production processes by analyzing the impact of mutations or of environmental conditions on the performance of the organism of interest. Here, we presented approaches for the latter in the context of lipid accumulation in this oleaginous yeast, which is typically accompanied by excretion of considerable amounts of citric acid. Indeed, Y. lipolytica under standard nitrogen-limiting conditions might rather be regarded as a good host for citrate production than for lipid accumulation (Fig. 2a) . We have shown that accumulation of lipid can not only be induced by depletion of nitrogen or one of the other 'typical' essential nutrients that are part of the medium, but also by reduction of oxygen supply. Furthermore, we showed that the simultaneous depletion of nitrogen and oxygen had additive effects on lipid accumulation and productivity. Since Y. lipolytica, like other oleaginous yeasts, is investigated for large scale production of TAG as feedstock for the biodiesel industry, this might be a promising approach because the reduction of aeration results in reduction of costs. Yeasts, especially Saccharomyces cerevisiae, have been used for centuries for biotechnological applications [1] . In recent years, so-called 'non-conventional' yeasts have gained considerable interest for several reasons. First, S. cerevisiae is a Crabtree positive yeast that covers most of its ATP requirement from substrate-level phosphorylation and fermentative metabolism. In contrast, most of the non-conventional yeasts, such as Yarrowia lipolytica, Kluyveromyces lactis or Pichia pastoris, have a respiratory metabolism, resulting in significantly higher biomass yields and no loss of carbon due to ethanol or acetate excretion. Second, S. cerevisiae is highly specialized and evolutionary optimized for the uptake of glucose, but performs poorly on most other carbon sources. Several nonconventional yeasts, on the other hand, are able to grow at high growth rates on alternative carbon sources, like pentoses, C1 carbon sources or glycerol, which may be available as cheap feedstock. Third, non-conventional yeasts are extensively exploited for production processes, for which the productivity of S. cerevisiae is rather low. Prominent examples are the use of P. pastoris for highlevel protein expression [2] and oleaginous yeasts for the production of single cell oils [3] .. Despite this growing interest in the development of biotechnological processes in other yeast species, the development of tools for the investigation and manipulation of these organisms still lags behind the advances in S. cerevisiae for which the broadest spectrum of methods for the engineering of production strains and the best knowledge about manipulation and cultivation are available. One such tool is the use of reconstructed metabolic networks for the computational analysis and optimization of pathways and production processes. These genomescale models (GSM) are becoming increasingly important as whole genome sequences and deduced pathways are available for many different organisms. In combination with mathematical algorithms like flux balance analysis (FBA) and variants thereof, GSMs have the potential to predict and guide metabolic engineering strategies and significantly improve their success rates [4] . FBA quantitatively simulates cellular metabolism using physicochemical constraints such as mass balance, energy balance, flux limitations and assuming a steady state [5, 6] . A major advantage of FBA is that no knowledge about kinetic enzyme constants and intracellular metabolite or protein concentrations is required. This makes FBA a widely applicable tool for the simulation of metabolic processes.. Whereas the yeast community provides continuous updates for the reconstruction of the S. cerevisiae model [7] , hardly any GSM for non-conventional yeasts are currently available. Recent attempts in this direction are the reconstructions for P. pastoris and P. stipitis [8, 9] and for the oleaginous yeast Yarrowia lipolytica, for which two GSMs have been published [10, 11] . Y. lipolytica is considered to be an excellent candidate for single-cell oil production as it is able to accumulate high amounts of neutral lipids. Furthermore, Y.lipolytica production strains efficiently excrete proteins and organic acids, like the intermediates of the tricarboxylic acid (TCA) cycle citrate, α-ketoglutarate and succinic acid [3, [12] [13] [14] . This yeast is also known to metabolize a broad range of substrates, such as glycerol, alkanes, fatty acids, fats and oils [15] [16] [17] ; the efficient utilization of glycerol as a carbon and energy source provides a major economic advantage for making high value products from cheap raw glycerol, which is available in large quantities from the biodiesel industry. Additionally, its high quality manually curated genome sequence is publicly available [18, 19] , making altogether Y. lipolytica a promising host for the biotech industry.. Y. lipolytica is known for both efficient citrate excretion and high lipid productivity under stress conditions such as nitrogen limitation. However, due to the undesired by-product citrate, processes aiming at high lipid content suffer from low yields with regard to the carbon conversion, despite the use of mutant strains with increased lipid storage properties. In this study, we reconstructed a new GSM of Y. lipolytica to analyze the physiology of this yeast and to design fermentation strategies towards optimizing the productivity for neutral lipid accumulation by simultaneously reducing the excretion of citrate. These predictions were experimentally confirmed, demonstrating that precisely defined fed batch strategies and oxygen limitation can be used to channel carbon fluxes preferentially towards lipid production.

O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B I O O O O O O O O O O O


IMAGE ERROR CONCEALMENT BASED ON QIM DATA HIDING IN DUAL-TREE COMPLEX WAVELETS Transmission of block-coded images through error-prone radio mobile channel often results in lost blocks. Error concealment (EC) techniques exploit inherent redundancy and reduce visual artifacts through post-processing at the decoder side. In this paper, we propose an efficient quantization index modulation (QIM)-based data hiding scheme using dual-tree complex wavelet transform (DTCWT) for the application of image error concealment. The goal is achieved by embedding important information (image digest) as watermark signal that is extracted from the original image itself and is used to introduce sufficient redundancy in the transmitted image. At the decoder side, the extracted image digest is used to correct the damaged regions. DTCWT offers three-fold advantages viz.(1) high embedding capacity due to inherent redundancy that leads to the better reconstruction of high volume missing data, (2) better imperceptibly after data embedding since it most closely captures human visual system (HVS) characteristics than conventional DWT and (3) better watermark decoding reliability. Simulation results duly support the claims and relative performance improvement with respect to the existing results. Transmission of digital data over unreliable network, particularly through radio mobile channel, is vulnerable to transmission error. As a matter of fact, image and video coded data suffer from block loss leading to the severe degradation on visual quality.. 1 Forward error correction (FEC), automatic repeat request (ARQ) and hybrid FEC/ARQ schemes may not be the preferable choice especially for the real time applications subject to transmission over channels with high error rates and/or with high propagation delay. Alternatively, error concealment (EC) techniques, through post-processing rather than suffering from the burden of retransmissions and consequent delay, may be adopted to reduce image distortion. A large number of different methods for image and video error concealment are reported in literature. [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] Error concealment is normally done either in spatial or in transform domain-like discrete cosine transform (DCT), discrete wavelets transform (DWT) etc. The wavelet transform, multiresolution analysis, and other space-frequency or space-scale approaches now become standard signal-processing tool for detection, denoising, compression of multimedia signals, transient detection, turbulence analysis, waveform coding, geometric representation and sharp image transition such as edges and texture segmentation etc., a few applications to mention. [22] [23] [24] [25] [26] Research work is also going on to develop newer wavelets bases like bandlet, 25 curvelet, 27-28 ridgelet, 29 divergence and curlfree wavelets 30 etc. in order to make them suitable for various typical applications. Due to its various attributes and introduction of new members in the family day-by-day, wavelets also become a natural choice from the beginning of digital watermarking research. [31] [32] [33] [34] [35] [36] Recently, Maity et al. 37 reported the scope of various wavelets in performance improvement of spread spectrum watermarking. We mention here only non-data hiding and data hiding-based error concealment methods. Pixel domain interpolation (PDI), 2 directional interpolation (DI), 3, 4 projection onto convex sets (POCS), 5 maximally smooth recovery (MSR), 6 block matching, 7 and neighborhood regions partitioned matching 8 or spectral domainlike DCT and DWT 9 are the few well known techniques for error concealment that do not use data hiding. Those schemes are not suitable where the decoder may not have sufficient computation power or is done in online. An image error concealment scheme based on QIM watermarking is proposed using DTCWT. This scheme provides better capability of error concealment than that of traditional watermarking-based method, as DTCWT offers more redundancy than conventional DWT. More number of subbands in DTCWT improves the embedding capacity, which leads to the better reconstruction of the missing data. Moreover, good directional selectivity property of DTCWT offers better reconstruction of edge information of error concealed image. Simulation results show that proposed error concealment scheme shows better performance of quality improvement even when PLR reaches 30%, compared to that of existing non-data hiding and data hidingbased error concealment methods. Simulation results also demonstrate that the proposed scheme provides significant improvement in terms of objective evaluations especially for high burst error condition due to fading. Finally, the proposed error concealment scheme can be made use for design of an adaptive data transmission scheme through the estimation of wireless channel condition using the extracted image digest.

O B I O O B B I O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O B O O O O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O B I O O O B O O O O B O O O O O O B I O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I


Story Tracker: Incremental visual text analytics of news story development Online news sources produce thousands of news articles every day, reporting on local and global real-world events. New information quickly replaces the old, making it difficult for readers to put current events in the context of the past. The stories about these events have complex relationships and characteristics that are difficult to model: they can be weakly or strongly related or they can merge or split over time. In this article, we present a visual analytics system for temporal analysis of news stories in dynamic information streams, which combines interactive visualization and text mining techniques to facilitate the analysis of similar topics that split and merge over time. Text clustering algorithms extract stories from online news streams in consecutive time windows and identify similar stories from the past. The stories are displayed in a visualization, which (1) sorts the stories by minimizing clutter and overlap from edge crossings, (2) shows their temporal characteristics in different time frames with different levels of detail, and (3) allows incremental updates of the display without recalculating the past data. Stories can be interactively filtered by their duration and connectivity in order to be explored in full detail. To demonstrate the system's capabilities for detailed dynamic text stream exploration, we present a use case with real news data about the Arabic Uprising in 2011. Understanding temporal development of unstructured and semi-structured text data streams is becoming increasingly important in many application areas, such as journalism, politics, or business intelligence. At the same time, sources of textual data, such as online news providers, are creating content in constantly growing amounts. While many automated and visual solutions that deal with the snapshots of information space already exist, few interactive systems can provide a user-friendly environment in which temporal context of these growing data collections can be successfully analyzed. The latest information coming from the news data providers prevails in the news landscape very quickly, putting the prior information out of the picture, even when it is necessary to keep the longer temporal context in mind to understand the current events. News stories that report on real-life events have characteristics that make analysis of this type of data challenging, from both the text mining and visualization perspectives. Analyzing the temporal dynamics of the news content has been the focus of data mining and visualization researchers for some time. In the area of text mining, a considerable effort has been put into modeling of topics in evolving document collections. However, little work has been devoted to analyze complex relationships that exist between news stories. In the area of visualization, topic evolution is receiving more attention recently, although most of the proposed methods do not scale well when working with data streams. We believe that evolutive aspects of news stories cannot be separated from incremental visualization methods and that these methods must be coupled with interaction techniques that will allow the user to explore the rich content of text data streams in full detail.. In this article, we propose a novel news stream visual analytics system that integrates topic evolution algorithms with interactive visualization methods at three temporal zoom levels. To support effective analysis of the growing news corpora, we combine interactive methods with incremental visualization of story development to allow exploration of news data streams from a broader temporal overview to fine-detailed level of a single article that belongs to a particular story. In this article, we have presented a visual analytics system for exploration of news stories development and their relationships. Our approach helps in understanding the evolution of long and short stories in a wide time frame, merging and splitting of stories, as well as fine-detailed analysis of story content on three different levels of detail. The incremental processing and visualization of unstructured and semi-structured text data allow the application of the system on the realworld news data streams. The global overview visualization helps in identifying the major news stories over a long period of time, and it is enriched with the interaction techniques to filter and re-rank stories on various user-adjustable criteria in order to provide a clutter-free display. Finer-granulated views that correspond to shorter time windows allow analysis of news stories with higher level of detail, up to the textual content of each news article itself. We have demonstrated the effectiveness of our approach on a realworld news stream and described the news stories and their content that were found with our system.. In the future, we plan to refine our document clustering module to enhance the informative context of story labels and test the system with sliding and dynamically adjustable time windows. Additionally, we plan to replace the splitting and merging thresholds, which are currently based on empirically adjusted values to a more refined and less data-dependent automatic algorithm. Our research efforts will continue in the direction of integrating incremental text analysis with novel visualization methods that will enable information analysts to analyze and understand growing document collections more effectively and efficiently. The visualization in our system can be seen as similar to parallel coordinates, 25 which is a well-known technique for visualizing high-dimensional data. In parallel coordinates, each attribute from the dataset is assigned an axis (coordinate), on which data points are plotted and connected for each record, creating polylines. Although several attempts for visualizing nominal data exist, 26, 27 parallel coordinates are mostly used to visualize high-dimensional numerical data. The axes are scaled to the minimum and maximum values for each attribute in order to make detection of patterns easier. The visual similarity between the two approaches exists in terms of using equidistant parallel axes as anchors for data objects; however, there are several key differences coming from the different tasks that are performed and the nature of the data that is being visualized.. Parallel coordinates are usually applied on highdimensional (usually numerical) datasets, where missing values are rare and the goal is to find patterns of similar polylines from different records. In our case, news stories can last for only 1 day or they can span over several days, with different start and end dates. Besides, the stories can split and merge, creating a more complex data structure than simple data tuples. Theoretically, we could clone each story cluster that splits into two clusters to create separate data records, but this redundancy does not seem practical and beneficial. The goal of our visualization is to (1) identify most important news stories in a longer period of time and (2) understand their development over time. This differs from pattern detection in parallel coordinates, where the user expects to find similar records across all axes.. Moreover, our ''axes'' contain ordinal data, that is, daily story clusters, which are sorted by a predefined ranking criterion (cluster strength or the number of articles in the cluster). In the interactive exploration phase, the ranking is relaxed by allowing the user to reorder clusters using an algorithm that minimizes edge crossings to improve the legibility of the visualization. This option provides better story tracking and split/merge detection.. Alternatively, we could have used equidistant points on each axis to encode cluster ranking. Since each cluster's size is mapped to its height, this would create gaps between the clusters on each axis, and the information about the absolute number of articles for each day would be lost. Our design provides visually more compact representation of the dataset. Finally, the axes in parallel coordinates can be reordered to make comparison between the neighboring axes easier. This possibility, although feasible, is not supported by the real-world tasks in our case since our attributes (i.e. axes) are days. Research on topic development, visualization, and analysis of temporal dynamics in information streams has strong connections to the fields of text mining, information visualization, and time-series analysis. A well-known initiative in text mining was topic detection and tracking (TDT), 1 which investigated methods for discovering events in broadcast news streams. Dynamic topic models 2 is another well-known approach in topic modeling, which extends Latent Dirichlet Allocation (LDA) to work with timestamped data. Although some of the important challenges were described already several years ago by Wong et al., 3 a lot of work in the field of streaming data and text visualization still has to be done. The most popular method to visualize topic trends over time is based on ThemeRiver, 4 which employs stacked graph visualization. 5, 6 Fisher et al. 7 presented a keyword tracking tool that calculates the co-occurrences of most important terms in blogs. EventRiver 8 employs bubble-like visualization of news stories extracted from the broadcast news data, while CloudLines 9 uses kernel density estimation to visualize interesting episodes in irregular news time-series data. Real-time aggregation of news articles into important threads is presented by Krstajić et al. 10 Aigner et al. 11 recently provided an extensive systematic overview of time-oriented visualization techniques. In the field of visual analytics, the recently published TIARA 12 system integrates interaction methods with text summarization and visualization based on tag clouds and stacked graphs. The work that is most closely related to ours is the one by Rose et al., 13 where a similar text flow visualization metaphor is used to show evolution of daily news themes over time. Our approach extends this line of research with improved interaction and different levels of detail for different temporal intervals and directly addresses the challenge of working with topics that split, merge, and overlap over time.

O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Estimating the Gowers Norm of Modulo Functions over Prime Fields We show a technique for estimating an upper bound of the Gowers norm of modulo functions over prime fields, which reduces the estimation to the greatest common divisor of some periodic sequences. This estimation provides inapproximability of the modulo functions by lowdegree polynomials over prime fields, which is a generalization of Viola and Wigderson's result in the case of the binary field. The Gowers norm is a measure for analyzing functions from a viewpoint of derivatives over general groups. This measure was originally introduced by Gowers [1] , [2] to give an alternative proof of Szemerédi's theorem. Remark. Throughout this paper, for any fixed n ≥ 1, we consider functions over n variables. But for simplicity, we identify n-variate functions and functions on vectors consisting of n elements.

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Research on Inventory Control Policies for Nonstationary Demand based on TOC An effective inventory replenishment method employed in the supply chain is one of the key factors to achieving low inventory while maintaining high customer delivery performance. The state of demand process is often not directly observed by the decision maker. Thus, in many literatures, the inventory control problem is a compositestate, partially observed Markov decision process (POMDP), which is an appropriate model for a number of dynamic demand problems. In practice, managers often use certainty equivalent control (CEC) policies to solve such a problem. However, in reality, Theory of Constraints (TOC) has brought a practical control policy that almost always provides much better solutions for this problem than the CEC policies commonly used in practice. In this paper, we proposed three different inventory control policies based on TOC buffer management framework, and use simulation approach to compare them with traditional adaptive (s,S,T) policy. The computational results indicate how specific problem characteristics influence the performance of whole system and demonstrate the efficiency of the proposed control policy. A supply chain is a set of nodes which consist of production plants, central warehouse, regional warehouses and points of sales. The chain links supplies and customers, beginning with the production of products by a supplier, and ending with the consumption of a product by the customer 1 . The need for regional warehouse stems from the need to supply the market very quickly. In the business market of flaming competition in recent years, companies are plagued by the fluctuations in demand and inevitably present inventory management challenges of the right inventory in the right place (node) at the right time. An effective inventory replenishment method employed in the supply chain is one of the key factors to achieving low inventory while maintaining high customer delivery performance.. Most inventory control problems exist in situations in which demand is both nonstationary and partially observed. By nonstationary, we mean that the probability distribution of the demand changes over time. Furthermore, the true underlying distribution of the demand in a period is never directly observed; it is only partially observed through the actual demand values. Under these conditions, inventory managers estimate the unknown demand distribution and typically use some type of certainty equivalent control (CEC) policywhich assumes the estimate is correct-to determine an inventory stocking level. For example, a manager may forecast the demand mean and variance over future time periods and use these estimates in a traditional inventory model to set stocking levels. The results presented in this paper demonstrate that there exist other practical suboptimal control policies to solve realistic instances of this problem without assuming such an estimate. Furthermore, these control policies achieve much better performance than the CEC policies commonly used in practice in almost all the cases that were considered. These suboptimal policies include Open-Loop Feedback Control and Limited Look-Ahead Control. Both of these policies account for more of the inherent uncertainty in the demand process and, therefore, almost always achieve lower expected cost than the CEC policies.. However, an effective replenishment method should resolve the following three basic issues: (1) how often the inventory status should be determined. (2) when a replenishment order should be placed. and (3) how large the replenishment order should be. Replenishment methods proposed in the traditional inventory theory can be classified as either continuous review systems ((s, S) or (s, Q) policy) or periodic review systems ((R, S) or (R, s, S) policy) 2 . However, researches report that order based on these replenishment methods swing due to downstream supply chain partners' fluctuation of demand. The swing is amplified as the order moves up to the supply chain. This phenomenon of demand amplification is named as bullwhip effect. Bullwhip effect causes excessive inventory, loss of revenue, and inaccurate production plans throughout supply chain systems 3 . The improvement of bullwhip effect in a supply chain is a key challenge for a manager. The Theory of Constraints-supply chain replenishment system (TOC-SCRS) is one of the solutions for the improvement of the bullwhip effect in a multi-echelon supply chain 4 . However, when the TOC-SCRS is applied in a plant or a central warehouse, the determination of RRT will encounter a conflict with the replenishment quantity. That is because the replenishment frequency depends on the set up frequency in the plant and the replenishment lead time depends on the production lead time. As we know, however, the set up frequency and the replenishment lead time in the plant depend on the production quantity (i.e., replenishment quantity). It means that the replenishment frequency and the replenishment lead time must depend on the known replenishment quantity, especially under the constraint of limited plant capacity. However, in TOC-SCRS, the replenishment quantity depends on the known parameters of the replenishment frequency and the replenishment lead time.. Therefore, this is a big conflict and an issue to apply the TOCSCRS in a plant or a central warehouse. An enhanced replenishment model for TOC-SCRS under capacity constraint is then required to be provided to solve this conflict 5 . Although TOC-SCRS concept has been implemented by a growing number of companies, its model is not described in the literatures. The model of TOC-SCRS based on previous research 6 is then modeled in this paper first. Then three different enhanced inventory control policies for TOC-SCRS under capacity constraint is then developed. A simulation comparison and its sensitivity analysis are utilized to evaluate the application of the proposed method. We proposed three different inventory control policies for nonstationary demand environment in this paper which based on TOC generic replenishment method. With the monitoring window review of the inventory target level and red buffer level, the procedure rigorously defined a means of sizing the buffer, monitoring it and correcting it when necessary adaptively. And we use simulation method to reveal the feasibility of the procedure. Adopting the proposed procedure in a specific application environment is not difficult if the variables are defined according to the application environment. Furthermore, through the comparison, we've showed that one of the proposed buffer management procedures outperforms on prior generic buffer control management in Ref. 6 and adaptive (s,S,T) policy.. Though the forecasting accuracy is not a big issue in the discussion of our paper, it's an important aspect which may greatly impact the performance of the inventory system, and then the further research could be focused in this area.

O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A framework for use of wireless sensor networks in forest fire detection and monitoring Forest fires are one of the main causes of environmental degradation nowadays. Current surveillance systems for forest fires lack in supporting real-time monitoring of every point of a region at all times and early detection of fire threats. Solutions using wireless sensor networks, on the other hand, can gather sensory data values, such as temperature and humidity, from all points of a field continuously, day and night, and, provide fresh and accurate data to the fire-fighting center quickly. However, sensor networks face serious obstacles like limited energy resources and high vulnerability to harsh environmental conditions, that have to be considered carefully. In this paper, we propose a comprehensive framework for the use of wireless sensor networks for forest fire detection and monitoring. Our framework includes proposals for the wireless sensor network architecture, sensor deployment scheme, and clustering and communication protocols. The aim of the framework is to detect a fire threat as early as possible and yet consider the energy consumption of the sensor nodes and the environmental conditions that may affect the required activity level of the network. We implemented a simulator to validate and evaluate our proposed framework. Through extensive simulation experiments, we show that our framework can provide fast reaction to forest fires while also consuming energy efficiently. Forest fires are a fatal threat throughout the world. It is reported that for the last decade, each year, a total of 2000 wild fires happened in Turkey and more than 100,000 in all countries (Republic of Turkey, 2011) . Early detection of forest fires is very important in fighting against fires. Spread features of forest fires show that, in order to put out a fire without making any permanent damage in the forest, the fire fighter center should be aware of the threat in at most 6 min after the start of the fire (National Fire Danger Rating System (NFDRS), 2011). Besides early detection capability, estimating the spread direction and speed of fire is also important in extinguishing fires.. Unreliability of human observation towers, in addition to the difficult life conditions of fire lookout personnel, has led the development and use of various technologies aiming to make the fire fighters aware of the forest fires as early as possible. Some important technologies and systems that are currently used towards this goal are: systems employing charge-coupled device (CCD) cameras and infrared (IR) detectors, satellite systems and images, and wireless sensor networks.. In a camera based system, CCD cameras and IR detectors are installed on top of towers. In case of fire or smoke activity, the cameras and detectors sense this abnormal event and report it to a control center (Aerovision Web Page, 2011; B.C. Fire Lookout Towers, 2011; Toreyin, Dedeoglu, Gudukbay, & Cetin, 2006) . However, the accuracy of such a system is highly affected by terrain, time of day, and weather conditions such as clouds, light reflections, and smoke from innocent industrial or social activities. Another alternative technology for detecting forest fires is the use of satellites and satellite images. Usually, satellites provide a complete image of the earth every 1-2 days. This long scan period, however, is not acceptable for detecting forest fires quickly. Additionally, the smallest fire size that can be detected by such a system is around 0.1 hectare, which also prevents fire detection just at the time when the fire starts, and fire localization error is about 1 km, which is not very accurate.. As a promising alternative, wireless sensor networks (WSNs) are an emerging technology that can be used for forest fire detection and related activities (Akyildiz, Su, Sankarasubramaniam, & Cayirci, 2002; Doolin & Sitar, 2006; Son, 2006; Yick, Mukherjee, & Ghosal, 2008; Yu, Wang, & Meng, 2005) . A wireless sensor network consists of small, battery-powered, and low-cost sensor nodes that have the capability of sensing, processing, and wireless communication (Shyam & Kumar, 2010) . Wireless sensor nodes that are deployed to a forest can collect data such as temperature, humidity, barometric pressure, and deliver this highly important data in raw or processed form to a center via a base station (or sink node), where incoming data can be analyzed automatically. As a result, fires and some other related events can be detected at the center without requiring manual, human-centric operations. There are, however, a lot of issues to consider and resolve in using wireless sensor networks for forest monitoring and forest fire detection. For example, the limited energy resources of sensor nodes and the though environmental conditions can limit the success of forest fire detection systems that are based on wireless sensor networks. Constant surveillance of the whole forest is required and this may cause excessive energy usage if not carefully planned. Therefore, a wireless sensor network for forest fire detection should consider several parameters and trade-offs together.. In this paper, we present a framework for the design of a wireless sensor network for forest monitoring and fire detection considering several goals simultaneously. As a part of our framework, we propose a network architecture and related protocols that will enable both rapid detection of forest fires and cautious use of energy resources. In our design, when there is no fire, the sensor network is not very aggressive in sensing and communicating various sensory data. But when there is a fire threat, the network operates in an emergency mode, and senses and communicates as fast as possible. Similarly, since the risk of fire depends on terrain, season and current weather conditions, our proposed design adapts its operation mode to the current level of risk of fire. In our proposed system design, except for the periods of forest fire, the sensor nodes mostly work in a low-duty cycle mode (regular day conditions). That is, sensor nodes will not consume much energy while the environmental conditions are normal and there is no fire. A distributed protocol to run in each sensor node considers fire threat cautiously and in case of an abnormal temperature change, informs the control center about the possibility or occurrence of fire rapidly.. Our framework includes four major components: an approach for deployment of sensor nodes, an architecture for the sensor network for fire detection, an intra-cluster communication protocol, and an inter-cluster communication protocol. We simulated our proposed design to show the validity of the protocols and to evaluate the proposal. We report the simulation results and show how the proposed framework can adapt to changing risk levels and in this way use the energy resources efficiently without harming the effectiveness of the system in detecting fires quickly.. The remainder of this paper is organized as follows. Section 2 discusses related studies on forest fire detection with wireless sensor networks. Section 3 describes the proposed framework that includes four major components mentioned above. Section 4 presents our simulation environment and experimental results. Finally, Section 5 concludes the paper and provides a discussion on future work. In this paper, we present a general framework for a wireless sensor network to be used for forest fire surveillance and detection. Our framework considers all parts of the life cycle of a wireless sensor network system that is specialized for forest fire detection. While considering the early detection of forest fires as the major goal, we also aim to construct a system that regards the low energy capacity of sensor nodes and the difficult environmental conditions that may adversely affect the network operation and performance.. Our framework incorporates the design of four main components of a wireless sensor network: the deployment scheme, the logical topology and architecture of the network, the intra-cluster communication scheme, and the inter-cluster communication scheme. Considering the system goals, several design decisions are evaluated for each part, starting from the sensor node deployment scheme and ending with cluster communication protocols.. We evaluated our proposed scheme in terms of energy consumption and effectiveness in detection fires. We observed that our system can provide both effective and efficient operation: consuming less energy without sacrificing the quick reaction capability. We conclude that season, environment, and weather adaptation is very important for a wireless sensor network and can significantly reduce energy consumption. We additionally conclude that clustered hierarchy has benefits in terms of data aggregation, management capability, energy efficiency and better coordination. Moreover, whenever possible regular deployment should be used, but when it is not possible, random deployment can be used with careful consideration of energy consumption at the nodes that are located at distant locations.. The system is open for several enhancements. Local data management and data synchronization in cluster-heads, localization of the nodes via GPS or other techniques, estimation of fire ignition location with or without GPS, dynamic route determination at the cluster-head level, dynamic cluster-head selection and forest fire spread estimation at the sink are some of the topics which can be investigated in future studies. During the last decade, quite extensive research work has been performed on wireless sensor networks, their protocols and algorithms, and their applications (Akyildiz et al., 2002; Anastasi, Conti, Di Francesco, & Passarella, 2009; Huang, Tseng, & Wu, 2007; Mainwaring, Culler, Polastre, Szewczyk, & Anderson, 2002; Yick et al., 2008) . Although these studies are not targeting specifically fire detection application, the approaches proposed are adaptable to various applications, including fire detection and monitoring. In our work, we adapt some of these existing methods (like clustering) and integrate various approaches in the literature to come up with a WSN design specifically targeting energy-efficient and effective forest fire detection.. For fire detection application of wireless sensor networks, specifically, there has been a considerable amount of work carried out as well. In one study, Doolin and Sitar (2006) provide experiments through controlled fires in San Francisco area. Their system is composed of ten sensor nodes with GPS capability. The sensor nodes are deployed with ranges up to one kilometer and they sense and forward temperature, humidity and barometric pressure values to a base station. The system was implemented and real-world observations were gathered from the field. However, because of the long distances between sensor nodes, the data arriving to the sink is not valuable enough to detect a fire quickly and forecast the spread direction of the fire. Also, with the growth of fire and burning out some of the sensor nodes, the sensor network could fail in delivering the data from all sensor nodes to the base station. Lloret, Garcia, Bri, and Sendra (2009) use a wireless local area network (WLAN) together with sensor-node technology for fire detection. The system they propose mixes multi-sensor nodes with IP-based cameras in a wireless mesh network setting in order to detect and verify a fire. When a fire is detected by a wireless multi-sensor node, the alarm generated by the node is propagated through the wireless network to a central server on which a software application runs for selecting the closest wireless camera(s). Then, real time images from the zone are streamed to the sink. Combining sensory data with images is the most important contribution of this study. Hartung and Han (2006) developed a multi-tiered portable wireless system for monitoring environmental conditions, especially for forest fires. Integrating web-enabled surveillance cameras with wireless sensor nodes, the system can provide real-time weather data from a forest. Three different sensor networks are deployed to different parts of a forest and the communication between the networks is enabled by powerful wireless devices that can send data up to ten kilometers range. The objective of the study is to determine the behavior of forest fires rather than their detection. With a wireless sensor network around an active fire, they measure the weather conditions around the fire. Webcams are also used to get visual data of the fire zone. Data gathered from the sensor nodes and the webcams are aggregated at a base station which has the capability of providing long distance communication using satellites. Periodically, the sensor nodes measure the temperature, relative humidity, wind speed and direction, and web-cams provide continuous visual data to the base station.. In all the studies discussed above (Doolin & Sitar, 2006; Hartung & Han, 2006; Lloret et al., 2009) , the sensor nodes are deployed to have quite large distances between each other and the sensory data gathered at a center is supported with visual data obtained with cameras. Our proposed system, however, considers a denser deployment strategy where the distances between neighboring sensor nodes are quite short. In this way, we are aiming to detect forest fires in a much faster way and send the related information to a center as quickly as possible. Son (2006) propose a forest fire surveillance system in South Korea in which a dynamic minimum cost path forwarding protocol is applied. After gathering data, a sink node makes several calculations regarding the relative humidity, precipitation and solar radiation, and produces a forest fire risk level. Different from this study, we propose to do in-network processing in cluster-head nodes rather than doing calculations only at a sink node. In this way, in our system, a sink node gathers filtered and processed data, not just raw data. Additionally, Son (2006) applies a minimum cost path forwarding method that causes some sensor nodes (especially the ones that are closer to the sink) to consume their energy much faster than the others. Our system, on the other hand, applies a low and fair energy consumption strategy by use of appropriate intraand inter-cluster communication protocols which take the remaining energy levels of sensor nodes into account. Yu et al. (2005) present a method which applies neural network techniques for in-network data processing in environmental sensing applications of wireless sensor networks. Several data fusion algorithms are presented in their study. Maximum, minimum and average values of temperature and humidity data are calculated by the cluster-heads. Data are propagated to the sink only if a certain threshold is exceeded. The main focus of this study is data aggregation methods, hence energy consumption and forecast capability issues are not discussed. Ngai, Zhou, Lyu, and Liu (2010) provide a general reliability-centric framework for event reporting in wireless sensor networks which can also be used in forest fire detection systems. They consider the accuracy, importance and freshness of the reported data in environmental event detection systems. They present a data aggregation algorithm for filtering important data and a delay-aware data transmission protocol for rapidly carrying the data to the sink node. Wenning, Pesch, Giel, and Gorg (2009) propose a proactive routing method for wireless sensor networks to be used in disaster detection. The protocol is developed to be aware of a node's destruction threat and it can adapt the routes in case of a sensor node's death. The method can also adapt the routing state based on a possible failure threat indicated by a sensed phenomenon.. Hefeeda and Bagheri (2009) developed a wireless sensor network for forest fire detection based on Fire Weather Index (FWI) system which is one of the most comprehensive forest fire danger rating systems in USA. The system determines the spread risk of a fire according to several index parameters. It collects weather data via the sensor nodes, and the data collected is analyzed at a center according to FWI. A distributed algorithm is used to minimize the error estimation for spread direction of a forest fire. Garcia and Serna (2008) present a simulation environment that can create a model for a fire by analyzing the data reported by sensor nodes and by using some geographical information about the area. The use of topography of the environment distinguishes the study from some other solutions. The estimation of the spread of a fire is sent to hand-held devices of fire fighters to help them in fighting against the fire in field.. The studies described above (Hefeeda & Bagheri, 2009; Ngai et al., 2010; Son, 2006; Wenning et al., 2009; Yu et al., 2005) consider and handle a single aspect of environmental monitoring and forest fire detection. In our proposed system, on the other hand, we deal with multiple parameters and trade-offs. We consider and aim both energy-efficiency and early-detection. We also incorporate environmental conditions, obstacles and features in our protocols.. There has been also a significant amount of work performed for clustering in wireless sensor networks (Abbasi & Younis, 2007; Ci, Guizani, & Sharif, 2007; Dimokas, Katsaros, & Manolopoulos, 2010; Heinzelman, Chandrakasan, & Balakrishnan, 2000; Liu, Lee, & Wang, 2007; Machado, Zhang, Wang, & Tekinay, 2010; Park, Choi, Han, & Chung, 2009; Soro & Heinzelman, 2009 ). These works, however, consider mostly how clusters are formed and maintained for various applications. They are not focusing on use of clusters for fire detection application. Therefore, their focus and scope are much different than the cluster communication protocols we are proposing in this paper. Moreover, in this paper we are not concentrating on how clusters are formed, but on how clustered hierarchy is utilized in a most efficient and effective manner for detecting and monitoring fires.

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O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Full-Text Search Engine using MySQL Abstract: In this article we will try to explain how we can create a search engine using the powerful MySQL full-text search. The ever increasing demands of the web requires cheap and elaborate search options. One of the most important issues for a search engine is to have the capacity to order its results set as relevance and provide the user with suggestions in the case of a spelling mistake or a small result set. In order to fulfill this request we thought about using the powerful MySQL full-text search. This option is suitable for small to medium scale websites. In order to provide sound like capabilities, a second table containing a bag of words from the main table together with the corresponding metaphone is created. When a suggestion is needed, this table is interrogated for the metaphone of the searched word and the result set is computed resulting a suggestion. Before the advent of the search engine, users had to search manually through dozens or hundreds of articles to find the ones that were right for them. Nowadays, in our more usercentered world, we expect the results to come to the user, not the other way around. The search engine gets the computer to do the work for the user.. Full-text search is widely used for various services of the Internet. A high-speed and a more efficient full-text search technology are necessary because of the amount of increasing handled document and corresponding document data every day [6] .. According to the MySQL manual, full-text is a "natural language search"; the words are indexed and appear to represent the row, using the columns you specified. As an example, if all your rows contain "MySQL" then "MySQL" won't match much. It's not terribly unique, and it would return too many results. However, if "MySQL" were present in only 5% of the rows, it would return those rows because it doesn't appear too often to be known as a keyword that's very used.. MySQL full-text search doesn't have too many user-tunable parameters. If you want more control over your search you will have to download the sources and compile them yourself after you've made the changes you wanted. Anyway, MySQL full-text is tuned for best effectiveness. Modifying the default behaviour in most cases can actually decrease effectiveness [1] .. Our implementation comes to bring a plus of functionality to the basic search capabilities that MySQL offers by returning better quality results to the user. For small data sets to be searched, its performance can be easily compared with the one of the more advanced dedicated full-text search engines. By using our implementation it is possible to offer a complete and powerful search option. For the future, we would like to improve the search speed by using a dedicated full-text search engine.. Another improvement we would like to implement would be a new parameter which will determine the popularity of a result based on determining if a user found what he wanted or not. This will use a combination of the time the user spent on that certain page divided by the content length, how many times the user returned to this page or if a page is or is not a stop page (which can indicate that the user found what he wanted to know).. Also, in addition to search, we would also like to implement high-speed insert and delete, allowing full-text search to be used in the same way as other types of database search in which data can be searched right after data is inserted [7] .. Another idea for future improvement is handling scientific document searches, especially mathematical text and mathematical operations [8] .. For the suggestion tool we want to improve the algorithm in such a way to be able to correct as many mistakes as possible. The primary table is the table where we keep all the data that has to be searched and ranked. Also, from this table we will create later the "bag of words" together with their metaphones in order to provide correction suggestions to the user. The primary table will consist of 6 columns, the first one being the row id and the others all being meant for full-text search. The structure of the table is:. ID -unique identifier for every row URL -the URL where the text was taken from TITLE -the title of the page the text was taken from CONTENT -everything on the page that is not part of the formatting and functionality (only text, no HTML or other scripts, including the dealers and strong text) HEADERS -H1,... contents from the page. They will have higher relevancy than STRONG and CONTENT but lower than URL and TITLE STRONG -words that appear between B or STRONG tags. They will have higher relevancy than ordinary text from CONTENT but lower than all the others.. During the construction of the table in the indexing process we decompose every page to obtain the required fields. First we will obtain the URL and the TITLE fields. After we have those two we can get rid off the head part of the web page and move on to the body. Before parsing out the entire HTML and other script tags from the text, we will have to take out the header and the strong keywords that will have a higher relevancy in our future search. After we've done that we can parse all the remaining script tags and send the resulting data into the MySQL database.. An improvement to this table would be a new column that contains all the keywords linking to this page. This way you can extend the article relevancy behind the actual page. Those linking keywords can be considered the ones between the anchor tag or the most relevant keywords from that page (calculated by their density after we've previously removed the stop words) or a combination of both. However, this approach requires many more pages to be scanned and many of them could come from outside our website.. After the first indexing is complete we can create the full-text index on the table. From now on we can make full-text searches on that table. Any new insert into the database will be attached on the fly internally by MySQL so that we don't have to worry about this [9] . The SQL syntax for doing this is: ALTER TABLE 'content' ADD FULLTEXT ('url','title', 'content','headers','strong') Searching the database is not very hard. Actually we will only use a query to apply a search on the database and let MySQL do the rest. It is a lot harder to determine the best values for the weights of the results. Depending on those constants, we will have different search results as we will show in the following examples.. In order to query the database we will use the following query. The query is virtually composed of three parts. The first part is meant to determine the relevancies of every column in part, the second one is meant for determining the matching rows and the last one is for ordering. You can see the query in Fig. 3 . The query will execute like this: first, different relevancies will be returned from the search on the individual columns. Those relevancies will be later used to calculate the order of the results. After we have got the relevancies we have to move on to the retrieval of all the rows that contain the terms that we searched. In order to do this we have to select all the matches inside the text fields ('content', 'url', 'title', 'headers', 'strong'). Once we have those results we will have to reorder them by relevance. In order to do this we will determine the ORDER BY argument using the following formula. relevance = relUrl *U + relTitle *T + relContent *C+ relHeaders *H+ relStrong *S The relevance for every column should be carefully selected in order to achieve the best result order. The URL relevance is not so important in our opinion. We have added it because all the big search engines have it. We will treat it as it would have the same relevance as the page title. The next column on the relevance scale, after the URL and the Title would be the Headers relevance.. Let's think about a certainty search. We want to search for an article about "Mysql Fulltext". The script will first determine the pages that contain the keywords inside the Title and URL of the page because those are the most suitable for us. The next in importance is the Headers column.. The last two of the columns are the Content column and the Strong column. The Strong column contains keywords that the writer of that page thought they are of a higher importance, with strong relevance to the subject. The order of the relevancies is clear. The plain content relevance is the lower one, followed by the keywords relevance (Strong), Headers, Title which is about the same to the URL relevance. The problems appear when we have to determine the best magnitude for those relevance parameters.. If the difference of the relevance parameters is too small, we will not have effective search results ordering. But if we fall into the other side, we can provide excessive ordering based only on the hierarchy we've determined for the parameters and less based on the relevancies of the results.. A schematisation of the proposed indexing and search algorithm is provided below: A) Indexing 1. The web page is processed by reading its contents. 2. The internal links from the page are determined. 3. The unique internal links and full page contents are inserted in a 'pages'

B B O O B O O O O O O O O O O O O O O B O O O O B B B O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B B O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O B O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O B O O O O O O O O O O B O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Discrete-Time Control for Rectangular Hybrid Automata Abstract. Rectangular hybrid automata model digital control programs of analog plant environments. We study rectangular hybrid automata where the plant state evolves continuously in real-numbered time, and the controller samples the plant state and changes the control state discretely, only at the integer points in time. We prove that rectangular hybrid automata have nite bisimilarity quotients when all control transitions happen at integer times, even if the constraints on the derivatives of the variables vary between control states. This is in contrast with the conventional model where control transitions may happen at any real time, and already the reachability problem is undecidable. Based on the nite bisimilarity quotients, we give an exponential algorithm for the symbolic sampling-controller synthesis of rectangular automata. We show our algorithm to be optimal by proving the problem to be EXPTIME-hard. We also show that rectangular automata form a maximal class of systems for which the sampling-controller synthesis problem can be solved algorithmically. Hybrid systems are dynamical systems with both discrete and continuous components. A paradigmatic example of a hybrid system is a digital control program for an analog plant environment, like a furnace or an airplane: the controller state moves discretely between control modes, and in each control mode, the plant state evolves continuously according to physical laws. A natural mathematical model for hybrid systems is the hybrid automaton, which represents discrete components using nite-state machines and continuous components using real-numbered variables ACH + 95]. A particularly important subclass of hybrid automata are the rectangular automata, where in each control mode v, the given n variables follow a nondeterministic di erential equation of the form dx dt 2 B(v), for an n-dimensional rectangle B(v) R n HKPV95]. Rectangular automata are useful as for two reasons. First, they can be made to approximate, arbitrarily closely, complex continuous behavior using lower and upper bounds on derivatives PBV96, HH95] . Second, they can be executed and reverse executed symbolically using polyhedral constraints to represent the possible values of variables AHH96, HHW97] . Symbolic execution stands in contrast to explicit execution, where each new state is computed individually. For systems that are reverse executable symbolically (r.e.s.), veri cation and control yield to a (semi)algorithmic approach even if the state space is in nite Hen96]. For r.e.s. systems, many model checking and controller synthesis problems can be solved by computing, using iterative approximation, certain xpoints of predecessor operators on state sets BCM + 92, MPS95] . Various xpoint computations are guaranteed to terminate in the presence of suitable nite quotient spaces. For example, r.e.s. systems with nite bisimilarity quotients allow LTL and CTL model checking, and safety controller synthesis. While rectangular automata are r.e.s., they do not necessarily have nite (time-abstract) bisimilarity quotients Hen95]; indeed, simple reachability questions are undecidable for rectangular automata HKPV95]. A noted subclass of rectangular automata with nite bisimilarity quotients are the timed automata, where all variables are clocks with derivative 1 AD94]. As a consequence, symbolic algorithms for model checking and controller synthesis are known for timed automata HNSY94, MPS95] . While previous results on timed and hybrid automata allow edge transitions (i.e., control mode switches) to occur at any real-numbered points in time, this is not necessarily a natural assumption for controller synthesis, as it permits controllers that, in a single time unit, can interact with the plant an unbounded number of times (even in nitely often, if no special care is taken AH97]). By contrast, we study the safety control problem under the assumption that while the plant evolves continuously, the controller samples the plant state discretely, at the integer points in time only. 1 This leads to the following formulation of the sampling-controller synthesis problem for rectangular automata: given a continuous-time rectangular automaton, is there a discrete-time controller that samples the automaton state at integer times and switches the control mode accordingly so that the resulting closed-loop system satis es a given invariant? To solve this problem, we study the discrete-time transition systems of rectangular automata, where all time transitions have unit duration. It should be noticed that all variables still evolve continuously, in real-numbered time; only edge transitions are restricted to discrete time. We prove that unlike in the case of dense time, the discrete-time transition system of every rectangular automaton has a nite bisimilarity quotient. 2 As a corollary, we conclude that the standard approaches to symbolic model checking and controller synthesis are guaranteed to terminate when all control switches must occur at integer times. The running times of the veri cation and control algorithms depend on the number of bisimilarity equivalence classes, which, while exponential in the description of the automaton, is less by a multiplicative exponential factor than the number of region equivalence classes used for the dense-time veri cation and control of timed automata. Thus, the often more realistic sampling-controller synthesis problem can be solved for a wider class of hybrid systems than dense-time control (rectangular vs. timed), at a smaller cost. We prove that our exponential sampling-control algorithm is optimal, by giving lower bounds on the control problem for timed and hybrid systems: we show that the safety control decision problem 1 The sampling rate of the controller may be any rational, but without loss of generality we assume it to be 1.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Solo versus collaborative writing: Discrepancies in the use of tables and graphs in academic articles Abstract The number of authors collaborating to write scientific articles has been increasing steadily. And, with this collaboration, other factors have also changed, such as the length of the articles and the number of citations. However, little is known about potential discrepancies in the use of tables and graphs between single and collaborating authors. In this paper we ask whether multi-author articles contain more tables and graphs than single-author articles and we studied 5,180 recent articles published in six science and social sciences journals. We found both that pairs and multiple-authors used significantly more tables and graphs than single authors. Such findings indicate that there is a greater emphasis on the role of tables and graphs in collaborative writing, and we discuss some of the possible causes and implications of these findings. It is a well reported fact that the numbers of authors for individual scientific articles have been increasing for a long time. Indeed, as de Solla Price (1963, p. 86-91) put it for Chemistry, perhaps tongue in cheek: "the proportion of multi-author articles has accelerated steadily and powerfully, and it is now so large that if it continues at the present rate by 1980, the singleauthor paper will be extinct." Today commentators are more circumspect. Abt (2007, p. 358) , for example, writes: "We conclude that single authored papers will decrease in frequency in the coming years, but will not disappear . . . [because] . . . the rapid increase between 1900 and 1960 did not continue, but changed into an exponential that will never reach zero." 2 Currently we estimate that about 30% of the articles in JASIST are single-authored (Cabanac & Hartley, 2013) .. The numbers of authors contributing to scientific articles covers a considerable rangefrom single-to hyper-authorship (Cronin, 2001 (Cronin, , 2005 . There are articles with over one hundred authors in some domains (e.g., see Adiga et al., 2002; Foster et al., 2004) , and, of course, there is the spectacular contribution by Aamodt et al. (2010) with its 1,055 co-authors.. Together with this increase in the numbers of authors there has been an increase in the numbers of articles about the effects of co-authorship. Table 1 lists the findings from some of these studies. Of course, many articles were published in the 1960s-90s (see Speck, Johnson, Dice, & Heaton, 1999) and these pre-date the electronic revolution that now facilitates collaborative writing today. Lewison and Hartley 2005 Of course different authors collaborate in different ways. Indeed, for the purposes of this article, it might be of interest for the reader to know that the article was initially proposed to James (Hartley) by Guillaume (Cabanac) working with Gilles (Hubert), who had suggested the study. Guillaume and Gilles carried out the data collection and analysis, and then the article was initially written in six parts. James drafted the Introduction and squabbled over various titles. Guillaume and Gilles wrote up the method, and the results section. James wrote the Discussion and the Conclusions, whilst Guillaume completed the reference section. But in all of these stages the manuscript passed backwards and forwards electronically between us numerous times with suggestions for improvement and agreement on every section. Then the final version was checked by James for appropriate English before it was checked by Gilles and Guillaume for submission by Guillaume.. Nonetheless, various patterns of collaboration do have to have certain features in common. There has to be a senior author responsible for the submission. Everyone has to agree with the final version. Different authors contribute different things -so the more authors there are the more areas there are for discussion and perhaps disputation. Some authors are seen as more expert than the others on different issues. So deciding on the order of the authors 3 on the title page can sometimes present problems (Kosmulski, 2012; Waltman, 2012) and sometimes, as here, the author who proposed the study comes last! There have to be negotiations too about the amount of detail to contain in the Introduction, the Method, the Results and the Discussion sections. There needs to be agreement over the numbers and suitability of the tables, graphs, and references. And, after submission, the criticisms of editors and referees have to be discussed and responded to by all or by a selection of the authors. 1 In this article we focus on the numbers of tables and graphs in single and co-authored articles. There have not been, as far as we are aware, any previous articles on this topic. So we have no specific hypotheses generated by earlier research, but we feel that as 'more heads are better than one' there might be more tables and graphs in articles written with more authors. The earlier research summarized in Table 1 does indeed suggest that increasing the numbers of authors appears to lead to increases in other key features in academic publications.. Accordingly we made the following predictions:. • On the use of tables: -H1: Multi-author articles feature more tables than single-author articles.. -H2: Two-author articles feature more tables than single-author articles.. • On the use of figures: -H3: Multi-author articles feature more figures than single-author articles.. -H4: Two-author articles feature more figures than single-author articles. We tested these hypotheses using the 6-step method detailed below. It relies on processing all of the articles published in each issue of selected research journals during a specific time period.. 1. Retrieve the full-text of each article and count the following: number of pages, number of authors, number of tables, and number of figures. 2. Discard articles with less than 4 pages to get rid of non-research articles, such as book reviews, editorials, errata, letters to the editor, notes, and so on. 3. Group articles according to their number of authors. We thus defined "Group 1A" and "Group 2A+" for single-author and multi-author articles, respectively. 4. Use boxplots to inspect visually the differences in the distribution of the number of tables and figures between Groups 1A and 2A+, for each journal. 5. Test the statistical significance of these differences with the non-parametric MannWhitney U test on two independent samples. The null hypothesis H 0 assumes that the distribution of the variable under study (e.g., number of tables) is not statistically significant between single-(Group 1A) and multi-author articles (Group 2A+). When H 0 is rejected, we report the level of significance of the test (two-sided) according to the classical three levels p < 0.05 denoted by * , p < 0.01 denoted by * * , and p < 0.001 denoted by * * * . 6. Further analyze the data to check if any such a difference can also be observed (or not) between single-author and two-author articles (instead of multi-author articles). This 4 analysis repeats steps 3-5 to compare the use of tables and figures among single-author articles (Group 1A) and two-author articles (Group 2A).

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Probabilistic White Matter Fiber Tracking using Particle Filtering and von Mises-Fisher Sampling Standard particle filtering technique have previously been applied to the problem of fiber tracking by Brun et al. (2002) and Bjornemo et al. (2002) . However, these previous attempts have not utilised the full power of the technique, and as a result the fiber paths were tracked in a goal directed way. In this paper we provide an advanced technique by presenting a fast and novel probabilistic method for white matter fiber tracking in diffusion weighted MRI (DWI), which takes advantage of the weighting and resampling mechanism of particle filtering. We formulate fiber tracking using a nonlinear state space model which captures both smoothness regularity of the fibers and the uncertainties in the local fiber orientations due to noise and partial volume effects. Global fiber tracking is then posed as a problem of particle filtering. To model the posterior distribution, we classify voxels of the white matter as either prolate or oblate tensors. We then construct the orientation distributions for prolate and oblate tensors separately. Finally, the importance density function for particle filtering is modeled using the von Mises-Fisher distribution on a unit sphere. Fast and efficient sampling is achieved using Ulrich-Wood's simulation algorithm. Given a seed point, the method is able to rapidly locate the globally optimal fiber and also provides a probability map for potential connections. The proposed method is validated and compared to alternative methods both on synthetic data and real-world brain MRI datasets. Diffusion tensor MRI (DTI) has become a popular tool for non-invasive exploration of the anatomical structure of the white matter in vivo (Basser et al., 1994) . It endows each voxel with a 3×3 symmetric positive-definite matrix, which characterises the local water diffusion process. It is based on a local Gaussianity assumption concerning the probability of water molecule motion in a defined time period. We have presented a new method for probabilistic white matter fiber tracking. The global tracking model is formulated using a state space framework, which is implemented by applying particle filtering to recursively estimate the posterior distribution of fibers and to locate the global optimal fiber path. Each ingredient of the tracking algorithm is detailed. For modeling the fiber orientation distribution, we classify voxels of the white matter as either prolate or oblate tensors. For pro- late tensors, the orientation distribution is theoretically formulated by combining the axially symmetric tensor model with a noise model for DWI. For oblate tensors, the orientation distribution is computed using a normal distribution of angles between fiber orientations and the smallest eigenvectors of the tensors. Fast and efficient sampling is realised using the von Mises-Fisher distribution. As a consequence, there is no need to apply MCMC sampling (Behrens et al., 2003) or to discretise the state space (Friman et al., 2006) to sample paths from the fiber orientation distribution.. Based on our experimental evaluations, the advantages of the proposed algorithm are threefold. First, unlike previous methods which are computationally very expensive, our method shows improved computational efficiency and is able to rapidly locate the global optimal fiber and to compute the connectivity map for the seed point. Second, our method can more accurately reconstruct the true fiber paths in very noisy images. It gives smaller errors between the reconstructed path and the true fiber path. Third, the proposed method is able to deal with fiber crossings because we separately model the orientation distributions for different shapes of diffusion tensors.. However, there are several ways in which the method can be further improved. For instance, our model of the orientation distribution for oblate tensors is not accurate enough to capture the complex configurations at fiber crossings. Thus, there are large uncertainties at such voxels. More sophisticated methods will have to be developed for dealing with fiber crossings in our future work. One possibility is the use of mixtures of von Mises-Fisher distributions (McGraw et al., 2006) . To validate the method in a quantitative way, real world datasets with annotated ground truth are needed. Developing simulated and real DTI sets with ground truth for validation and across-site comparison is an active area of imaging research, but to our knowledge these are not yet available to the community.

O O O O O O B I O B I I O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O