Query: Cloud Computing Adoption: A Short Review of Issues and Challenges

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Above the Clouds: A Berkeley View of Cloud Computing <=SEP=> Cloud Computing, the long-held dream of computing as a utility, has the potential to transform a large part of the IT industry, making software even more attractive as a service and shaping the way IT hardware is designed and purchased. Developers with innovative ideas for new Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. They need not be concerned about overprovisioning for a service whose popularity does not meet their predictions, thus wasting costly resources, or underprovisioning for one that becomes wildly popular, thus missing potential customers and revenue. Moreover, companies with large batch-oriented tasks can get results as quickly as their programs can scale, since using 1000 servers for one hour costs no more than using one server for 1000 hours. This elasticity of resources, without paying a premium for large scale, is unprecedented in the history of IT. Cloud Computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the datacenters that provide those services. The services themselves have long been referred to as Software as a Service (SaaS). The datacenter hardware and software is what we will call a Cloud. When a Cloud is made available in a pay-as-you-go manner to the general public, we call it a Public Cloud; the service being sold is Utility Computing. We use the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public. Thus, Cloud Computing is the sum of SaaS and Utility Computing, but does not include Private Clouds. People can be users or providers of SaaS, or users or providers of Utility Computing. We focus on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SaaS Users. From a hardware point of view, three aspects are new in Cloud Computing.

Cloud Computing - The Business Perspective <=SEP=> If cloud computing (CC) is to achieve its potential, there needs to be a clear understanding of the various issues involved, both from the perspectives of the providers and the consumers of the technology. There is an equally urgent need for understanding the business-related issues surrounding CC. We interviewed several industry executives who are either involved as developers or are evaluating CC as an enterprise user. We identify the strengths, weaknesses, opportunities and threats for the industry. We also identify the various issues that will affect the different stakeholders of CC. We issue a set of recommendations for the practitioners who will provide and manage this technology. For IS researchers, we outline the different areas of research that need attention so that we are in a position to advise the industry in the years to come. Finally, we outline some of the key issues facing governmental agencies who will be involved in the regulation of cloud computing.

Service-Oriented Cloud Computing Architecture <=SEP=> Cloud computing is getting popular and IT giants such as Google, Amazon, Microsoft, IBM have started their cloud computing infrastructure. However, current cloud implementations are often isolated from other cloud implementations. This paper gives an overview survey of current cloud computing architectures, discusses issues that current cloud computing implementations have and proposes a Service-Oriented Cloud Computing Architecture (SOCCA) so that clouds can interoperate with each other. Furthermore, the SOCCA also proposes high level designs to better support multi-tenancy feature of cloud computing.

The Case for Energy-Proportional Computing <=SEP=> Energy-proportional designs would enable large energy savings in servers, potentially doubling their efficiency in real-life use. Achieving energy proportionality will require significant improvements in the energy usage profile of every system component, particularly the memory and disk subsystems.

The Chinese Wall Security Policy <=SEP=> Everyone who has seen the movie Wall Street wi~l have seen a commercial security policy in action. The recent work of Clark and Wilson and the WIPCIS initiative (the Workshop on Integrity Policy for Computer Information Systems) has drawn attention to the existence of a wide range of commercial security policies which are both significantly different from each other and quite alien to current “military” thin king as implemented in products for the security mari<et place. This paper presents a basic mathematical theory which implements one such policy, the Chinese Wall, and shows that it cannot be correctly represented by a 13e11-LaPadula model. The Chinese Wall policy combines commercial discretion with legally enforceable mandatory con trols. It is required in the operation of many financial services organizations and is, therefore, perhaps as significant t to the financial world as Bel!-LaPadula ’s policies are to the military. MIRQK?LK7T,K2N Until recently, military security policy thinking has dominated the direction of computer security research both in the US and the UK. Clark and Wilson’s seminal paper [1] has, however, drawn attention to the fact that commercial security needs are just as important as those of the de fence community and, through the WIPCIS initiative [2], that the problems of the commercial community are at least as diverse and relevant to the computer scientist. There are many well defined commercial security policies covering all aspects of Clark and Wilson’s model [3]. One of these, the Chinese Wall security policy is perhaps as significant to some parts of the commercial world as Bell and LaPadula’s policies [4, 5] are to the military. It can be most easily visualized as the code of practice that must be followed by a market analyst working for a financial institution providing corporate business services. Such an analyst must uphold the confidentiality of information provided to him by his firm’s clients; this means he cannot advise corporations where he has insider knowledge of the plans, status or standing of a competitor. However, the analyst is free to advise corporations which are not in competition with each other, and also to draw on general market information. Many other instances of Chinese Walls are found in the financial world. Unlike Bell and LaPadula, access to data is not constrained by attributes of the data in question but by what data the subject already holds access rights to. Essentially, datasets are grouped into “conf I ict of interest classes” and by mandatory ruling all subject= are allowed access to at most one dataset belonging to each such conflict of inte rest class; the actual choice of dataset is totally unrestrained provided that this mandatory rule is satisfied. We assert that such policies cannot be correctly model led by Bell -LaPadula. It should be noted that in the United Kingdom the Chinese Wall requirements of the UK Stock Exchange [6] have the authority of law [7] and thus represent a mandatory security policy whether implemented by manual or automated means. Furthermore, correct implementation of this policy is important to English Financial Institutions since it provides a legitimate defence against certain penal classes of offence under their Iak[.

Investigating learner attitudes toward e-books as learning tools: based on the activity theory approach <=SEP=> Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content.

Sport motivation scale-6 (SMS-6): A revised six-factor sport motivation scale <=SEP=> Background and Purpose: The sport motivation scale (SMS; [Pelletier, L. G., Fortier, M. S., Vallerand, R. J., Tuson, K. M., Brière, N. M., & Blais, M. R. (1995). Toward a new measure of intrinsic motivation, extrinsic motivation, and amotivation in sports: The sport motivation scale (SMS). Journal of Sport and Exercise Psychology, 17, 35–53]) was developed to measure an athlete’s motivation toward sport participation. However, the SMS does not measure the most autonomous form of extrinsic motivation, integrated regulation, which is inconsistent with self-determination theory (SDT; [Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behaviour. New York: Plenum Press]) upon which the instrument is based. Moreover, several studies (e.g., [Martens, M. P., & Webber, S. N. (2002). Psychometric properties of the sport motivation scale: An evaluation with college varsity athletes from the U.S. Journal of Sport and Exercise Psychology, 24, 254–270]) have questioned the factorial validity of the SMS. Hence, the purpose of this study was to develop a revised version of the SMS, including integrated regulation. Method: In Stage 1, the factorial validity of the SMS was examined using confirmatory factor analysis (CFA) on data collected from 614 Australians (elite athletes and university students). In Stage 2, the scale was revised by including integrated regulation items and replacing problematic items through an iterative process using CFA for data collected from 557 Australian university students. Concurrent validity of the revised scale was examined by evaluating correlations with the dispositional flow scale-2 (DFS-2) [Jackson, ARTICLE IN PRESS www.elsevier.com/locate/psychsport 1469-0292/$ see front matter r 2007 Published by Elsevier Ltd. doi:10.1016/j.psychsport.2006.12.005 Corresponding author. Tel.: +61 7 33656765; fax: +61 7 33656877. E-mail addresses: cmallett@hms.uq.edu.au (C. Mallett), masato@hms.uq.edu.au (M. Kawabata), newc@psy.uq.edu.au (P. Newcombe), andres.otero@gmail.com (A. Otero-Forero). Author's personal copy S. A., & Eklund, R. C. (2004). The flow scales manual. Morgantown, WV: Fitness Information Technology]. Results: The revision led to development of a six-factor 24-item scale (SMS-6) that indicated a more parsimonious and improved fitting model consistent with SDT. Correlations between the SMS-6 and DFS-2 factors support the concurrent validity of the revised scale. Conclusion: From statistical and theoretical viewpoints, the revised SMS-6 was preferable to the original SMS, except for the discriminant validity issue of identification regulation. Further examination of the instrument is necessary by cross-validating the findings from this study. r 2007 Published by Elsevier Ltd.

Understanding semantic change of words over centuries <=SEP=> In this paper, we propose to model and analyze changes that occur to an entity in terms of changes in the words that co-occur with the entity over time. We propose to do an in-depth analysis of how this co-occurrence changes over time, how the change influences the state (semantic, role) of the entity, and how the change may correspond to events occurring in the same period of time. We propose to identify clusters of topics surrounding the entity over time using Topics-Over-Time (TOT) and k-means clustering. We conduct this analysis on Google Books Ngram dataset. We show how clustering words that co-occur with an entity of interest in 5-grams can shed some lights to the nature of change that occurs to the entity and identify the period for which the change occurs. We find that the period identified by our model precisely coincides with events in the same period that correspond to the change that occurs.

2.4 to 61 GHz Multiband Double-Directional Propagation Measurements in Indoor Office Environments <=SEP=> This paper presents the details and results of double-directional propagation measurements carried out in two indoor office environments: a semi-open, cubicle-type office space and a more traditional work environment with closed offices. The measurements cover seven frequency bands from 2.4 to 61 GHz, permitting the propagation characteristics to be compared over a wide range of candidate radio frequencies for next-generation mobile wireless systems, including ultra high frequency and millimeter-wave bands. A novel processing algorithm is introduced for the expansion of multiband measurement data into sets of discrete multipath components. Based on the resulting multipath parameter estimates, models are presented for frequency-dependent path loss, shadow fading, copolarization ratio, delay spread, and angular spreads, along with their interfrequency correlations. Our results indicate a remarkably strong consistency in multipath structure over the entire frequency range considered.

A Robust Digital Image Watermarking Scheme Using Hybrid DWT-DCT-SVD Technique <=SEP=> Protection of digital multimedia content has become an increasingly important issue for content owners and service providers. As watermarking is identified as a major technology to achieve copyright protection, the relevant literature includes several distinct approaches for embedding data into a multimedia element (primarily images, audio, and video). In this paper, we present a hybrid watermarking scheme based on Discrete Wavelet Transform – Discrete Cosine Transform – Singular Value Decomposition (DWT-DCT-SVD). Robustness is achieved by taking DCT of the DWT coefficients of the HL band of DWT. After applying DCT we map the DCT coefficients in a zig – zag order into four quadrants and apply the SVD to each quadrant. These four quadrants represent frequency bands from the lowest to the highest. The singular values in each quadrant are then modified by the singular values of the DWT-DCT transformed visual watermark. We show that embedding data in lowest frequencies is resistant to most of the attacks and some attacks are resistant to other frequency bands.

Filing, piling, and everything in between: The dynamics of E-mail inbox management <=SEP=> Managing the constant flow of incoming messages is a daily challenge faced by knowledge workers who use technologies such as e-mail and other digital communication tools. This study focuses on the most ubiquitous of these technologies, e-mail, and unobtrusively explores the ongoing inbox-management activities of thousands of users worldwide over a period of 8 months. The study describes the dynamics of these inboxes throughout the day and the week as users strive to handle incoming messages, read them, classify them, respond to them in a timely manner, and archive them for future reference, all while carrying out the daily tasks of knowledge workers. It then tests several hypotheses about the influence of specific inbox-management behaviors in mitigating the causes of e-mail overload, and proposes a continuous index that quantifies one of these inbox-management behaviors. This inbox clearing index (ICI) expands on the widely cited trichotomous classification of users into frequent filers, spring cleaners, and no filers, as suggested by Whittaker and Sidner (1996). We propose that the ICI allows shifting the focus, from classifying users to characterizing a diversity of user behaviors and measuring the relationships between these behaviors and desired outcomes.

A Symbolic Approach for Explaining Errors in Image Classification Tasks <=SEP=> Machine learning algorithms, despite their increasing success in handling object recognition tasks, still seldom perform without error. Often the process of understanding why the algorithm has failed is the task of the human who, using domain knowledge and contextual information, can discover systematic shortcomings in either the data or the algorithm. This paper presents an approach where the process of reasoning about errors emerging from a machine learning framework is automated using symbolic techniques. By utilizing spatial and geometrical reasoning between objects in a scene, the system is able to describe misclassified regions in relation to its context. The system is demonstrated in the remote sensing domain where objects and entities are detected in satellite images.

Survey propagation: An algorithm for satisfiability <=SEP=> We study the satisfiability of randomly generated formulas formed by M clauses of exactly K literals over N Boolean variables. For a given value of N the problem is known to be most difficult when α = M/N is close to the experimental threshold αc separating the region where almost all formulas are SAT from the region where all formulas are UNSAT. Recent results from a statistical physics analysis suggest that the difficulty is related to the existence of a clustering phenomenon of the solutions when α is close to (but smaller than) αc. We introduce a new type of message passing algorithm which allows to find efficiently a satisfying assignment of the variables in this difficult region. This algorithm is iterative and composed of two main parts. The first is a message-passing procedure which generalizes the usual methods like Sum-Product or Belief Propagation: It passes messages that may be thought of as surveys over clusters of the ordinary messages. The second part uses the detailed probabilistic information obtained from the surveys in order to fix variables and simplify the problem. Eventually, the simplified problem that remains is solved by a conventional heuristic. © 2005 Wiley Periodicals, Inc. Random Struct. Alg., 27, 201–226, 2005

5G security architecture and light weight security authentication <=SEP=> The concept of future 5G (the 5th generation of mobile networks) widely spreads in industry, but the related standards are still unclear. The definition of 5G is to provide adequate RF coverage, more bits/Hz and to interconnect all wireless heterogeneous networks to provide seamless, consistent telecom experience to the user. In this paper we have surveyed 5G network architecture and proposed a multi-tier security architecture and a lightweight authentication measure for 5G. The proposed scheme aims at achieving fast authentication and minimizing the packet transmission overhead without compromising the security requirements.

Rumors Detection in Sina Weibo Based on Text and User Characteristics <=SEP=> M414 such as Twitter and Sina Weibo have brought convenience to people in recent years, but there are a large number of internet rumors bring serious harm to us. Because of the fuzziness and concealment of rumors, the automatic identification of microblog rumors is very difficult, which brings great challenges to microblog's supervision. In this paper, for the text information of rumors, we construct a new emotional classification method, and use this method to analyze the emotional orientation of comments, and then calculate the proportion of negative emotional comments. Combined with user information at the same time, we analyze retweet-list and comment-list, and then judge whether there are authoritative users who participated in the spread of rumors. Moreover, we extract features from the information of user and calculate the user's reputation value. Finally, we use the training classifier to detect microblog rumors. Experimental results illustrate the efficacy and efficiency of the proposed new features in microblog rumors detection.

High-order entropy-compressed text indexes <=SEP=> We present a novel implementation of compressed suffix arrays exhibiting new tradeoffs between search time and space occupancy for a given text (or sequence) of <i>n</i> symbols over an alphabet σ, where each symbol is encoded by lg|σ| bits. We show that compressed suffix arrays use just nH<inf>h</inf> + σ bits, while retaining full text indexing functionalities, such as searching any pattern sequence of length <i>m</i> in <i>O</i>(<i>m</i> lg |σ| + polylog(<i>n</i>)) time. The term H<inf>h</inf> ≤ lg |σ| denotes the hth-order empirical entropy of the text, which means that our index is nearly optimal in space apart from lower-order terms, achieving asymptotically the empirical entropy of the text (with a multiplicative constant 1). If the text is highly compressible so that H<inf>n</inf> = o(1) and the alphabet size is small, we obtain a text index with o(m) search time that requires only o(n) bits. Further results and tradeoffs are reported in the paper.

MBMF: Model-Based Priors for Model-Free Reinforcement Learning <=SEP=> Reinforcement Learning is divided in two main paradigms: model-free and model-based. Each of these two paradigms has strengths and limitations, and has been successfully applied to real world domains that are appropriate to its corresponding strengths. In this paper, we present a new approach aimed at bridging the gap between these two paradigms. We aim to take the best of the two paradigms and combine them in an approach that is at the same time dataefficient and cost-savvy. We do so by learning a probabilistic dynamics model and leveraging it as a prior for the intertwined model-free optimization. As a result, our approach can exploit the generality and structure of the dynamics model, but is also capable of ignoring its inevitable inaccuracies, by directly incorporating the evidence provided by the direct observation of the cost. As a proof-of-concept, we demonstrate on simulated tasks that our approach outperforms purely model-based and model-free approaches, as well as the approach of simply switching from a model-based to a model-free setting.

Variable flux permanent magnet synchronous machine (VF-PMSM) design to meet electric vehicle traction requirements with reduced losses <=SEP=> Variable flux permanent magnet synchronous machines (VF-PMSMs) in which the magnetization state (MS) of low coercive force (low-Hc) permanent magnets can be actively controlled to reduce losses in applications that require wide-speed operation have been proposed recently. While prior focus has been on achieving MS manipulation without over-sizing the inverter and obtaining higher torque capability, this paper extends the design objectives to include the power requirements of an electric vehicle traction motor over its entire speed range. Finite element methods are used to study the effect of combinations of low-Hc and high-Hc permanent magnets arranged in either series or parallel on the performance of VF-PMSMs. It is shown that while both configurations help improve the torque density, only the series configuration can help improve the high speed power capability. Experimental results showing the variable MS property, torque-speed capability and loss reduction capability of a series magnet configuration VF-PMSM test machine are presented.

Sudoku Squares and Chromatic Polynomials <=SEP=> T he Sudoku puzzle has become a very popular puzzle that many newspapers carry as a daily feature. The puzzle consists of a 9×9 grid in which some of the entries of the grid have a number from 1 to 9. One is then required to complete the grid in such a way that every row, every column, and every one of the nine 3× 3 sub-grids contain the digits from 1 to 9 exactly once. The sub-grids are shown in Figure 1.

Simultaneous algebraic reconstruction technique (SART): a superior implementation of the art algorithm. <=SEP=> In this paper we have discussed what appears to be a superior implementation of the Algebraic Reconstruction Technique (ART). The method is based on 1) simultaneous application of the error correction terms as computed by ART for all rays in a given projection; 2) longitudinal weighting of the correction terms back-distributed along the rays; and 3) using bilinear elements for discrete approximation to the ray integrals of a continuous image. Since this implementation generates a good reconstruction in only one iteration, it also appears to have a computational advantage over the more traditional implementation of ART. Potential applications of this implementation include image reconstruction in conjunction with ray tracing for ultrasound and microwave tomography in which the curved nature of the rays leads to a non-uniform ray density across the image.

Finding Steiner Forests in Planar Graphs <=SEP=> Several routing problems such as VLSI river routing and single-layer routing can be formulated as a problem of finding a Steiner forest in a planar (grid) graph. Given an unweighted planar graph G together with nets of terminals, our problem is to find a Steiner forest, i.e., vertex-disjoint trees, each of which interconnects all the terminals of a net. This paper gives an efficient algorithm to solve the problem for the case all terminals lie on two face boundaries of G. Also obtained is an algorithm for finding a maximum number of internally vertexdisjoint paths connecting two specified vertices in a planar graph G. Both run in 0( nlog n) time if G has n vertices.

Causality in thought. <=SEP=> Causal knowledge plays a crucial role in human thought, but the nature of causal representation and inference remains a puzzle. Can human causal inference be captured by relations of probabilistic dependency, or does it draw on richer forms of representation? This article explores this question by reviewing research in reasoning, decision making, various forms of judgment, and attribution. We endorse causal Bayesian networks as the best normative framework and as a productive guide to theory building. However, it is incomplete as an account of causal thinking. On the basis of a range of experimental work, we identify three hallmarks of causal reasoning-the role of mechanism, narrative, and mental simulation-all of which go beyond mere probabilistic knowledge. We propose that the hallmarks are closely related. Mental simulations are representations over time of mechanisms. When multiple actors are involved, these simulations are aggregated into narratives.

Get Out of my Picture! Internet-based Inpainting <=SEP=> We present a method to replace a user specified target region of a photograph by using other photographs of the same scene downloaded from the Internet via viewpoint invariant image search. Each of the retrieved images is first geometrically then photometrically registered with the query photograph. Geometric registration is achieved using multiple homographies and photometric registration is performed using a global affine transformation on image intensities. Each retrieved image proposes a possible solution for the target region. In the final step we combine these proposals into a single visually consistent result, using a Markov random field optimisation to choose seams between proposals, followed by gradient domain fusion. We demonstrate removal of objects and people in challenging photographs of Oxford landmarks containing complex image structures.

Biodegradable polymeric nanoparticles based drug delivery systems. <=SEP=> Biodegradable nanoparticles have been used frequently as drug delivery vehicles due to its grand bioavailability, better encapsulation, control release and less toxic properties. Various nanoparticulate systems, general synthesis and encapsulation process, control release and improvement of therapeutic value of nanoencapsulated drugs are covered in this review. We have highlighted the impact of nanoencapsulation of various disease related drugs on biodegradable nanoparticles such as PLGA, PLA, chitosan, gelatin, polycaprolactone and poly-alkyl-cyanoacrylates.

DeepBE: Learning Deep Binary Encoding for Multi-label Classification <=SEP=> The track 2 and track 3 of ChaLearn 2016 can be considered as Multi-Label Classification problems. We present a framework of learning deep binary encoding (DeepBE) to deal with multi-label problems by transforming multi-labels to single labels. The transformation of DeepBE is in a hidden pattern, which can be well addressed by deep convolutions neural networks (CNNs). Furthermore, we adopt an ensemble strategy to enhance the learning robustness. This strategy is inspired by its effectiveness in fine-grained image recognition (FGIR) problem, while most of face related tasks such as track 2 and track 3 are also FGIR problems. By DeepBE, we got 5.45% and 10.84% mean square error for track 2 and track 3 respectively. Additionally, we proposed an algorithm adaption method to treat the multiple labels of track 2 directly and got 6.84% mean square error.

Deep neural architectures for large scale android malware analysis <=SEP=> Android is arguably the most widely used mobile operating system in the world. Due to its widespead use and huge user base, it has attracted a lot of attention from the unsavory crowd of malware writers. Traditionally, techniques to counter such malicious software involved manually analyzing code and figuring out whether it was malicious or benign. However, due to the immense pace at which newer malware families are surfacing, such an approach is no longer feasible. Machine learning offers a way to tackle this issue of speed by automating the classification task. While several efforts have been made to use traditional machine learning techniques to Android malware detection, no reasonable effort has been made to utilize the newer, deep learning models in this domain. In this paper, we apply several deep learning models including fully connected, convolutional and recurrent neural networks as well as autoencoders and deep belief networks to detect Android malware from a large scale dataset of more than 55 GBs of Android malware. Further, we apply Bayesian machine learning to this problem domain to see how it fares with the deep learning based models while also providing insights into the dataset. We show that we are able to achieve better results using these models as compared to the state-of-the-art approaches. Our best model gets an F1 score of 0.986 with an AUC of 0.983 as compared to the existing best F1 score of 0.875 and AUC of 0.953.

Temporal Information Extraction <=SEP=> Research on information extraction (IE) seeks to distill relational tuples from natural language text, such as the contents of the WWW. Most IE work has focussed on identifying static facts, encoding them as binary relations. This is unfortunate, because the vast majority of facts are fluents, only holding true during an interval of time. It is less helpful to extract PresidentOf(Bill-Clinton, USA) without the temporal scope 1/20/93 1/20/01. This paper presents TIE, a novel, information-extraction system, which distills facts from text while inducing as much temporal information as possible. In addition to recognizing temporal relations between times and events, TIE performs global inference, enforcing transitivity to bound the start and ending times for each event. We introduce the notion of temporal entropy as a way to evaluate the performance of temporal IE systems and present experiments showing that TIE outperforms three alternative approaches.

A comparison of Haar-like, LBP and HOG approaches to concrete and asphalt runway detection in high resolution imagery <=SEP=> In this article, the three most used object detection approaches, Linear Binary Pattern cascade, Haarlike cascade, and Histogram of Oriented Gradients with Support Vector Machine are applied to automatic runway detection in high resolution satellite imagery and their results are compared. They have been employed predominantly for human feature recognition and this paper tests theirs applicability to runways. The results show that they can be indeed employed for this purpose with LBP and Haar approaches performing better than HOG+SVM.

Life beyond Distributed Transactions: an Apostate's Opinion <=SEP=> Many decades of work have been invested in the area of distributed transactions including protocols such as 2PC, Paxos, and various approaches to quorum. These protocols provide the application programmer a façade of global serializability. Personally, I have invested a nontrivial portion of my career as a strong advocate for the implementation and use of platforms providing guarantees of global serializability. My experience over the last decade has led me to liken these platforms to the Maginot Line. In general, application developers simply do not implement large scalable applications assuming distributed transactions. When they attempt to use distributed transactions, the projects founder because the performance costs and fragility make them impractical. Natural selection kicks in... 1 The Maginot Line was a huge fortress that ran the length of the Franco-German border and was constructed at great expense between World War I and World War II. It successfully kept the German army from directly crossing the border between France and Germany. It was quickly bypassed by the Germans in 1940 who invaded through Belgium. This article is published under a Creative Commons License Agreement (http://creativecommons.org/licenses/by/2.5/). You may copy, distribute, display, and perform the work, make derivative works and make commercial use of the work, but you must attribute the work to the author and CIDR 2007. 3 Biennial Conference on Innovative DataSystems Research (CIDR) January 7-10, Asilomar, California USA. Instead, applications are built using different techniques which do not provide the same transactional guarantees but still meet the needs of their businesses. This paper explores and names some of the practical approaches used in the implementations of large-scale mission-critical applications in a world which rejects distributed transactions. We discuss the management of fine-grained pieces of application data which may be repartitioned over time as the application grows. We also discuss the design patterns used in sending messages between these repartitionable pieces of data. The reason for starting this discussion is to raise awareness of new patterns for two reasons. First, it is my belief that this awareness can ease the challenges of people hand-crafting very large scalable applications. Second, by observing the patterns, hopefully the industry can work towards the creation of platforms that make it easier to build these very large applications.

Lane detection using spline model <=SEP=> In this paper, a Catmull±Rom spline-based lane model which describes the perspective eect of parallel lines has been proposed for generic lane boundary. Since Catmull±Rom spline can form arbitrary shapes by dierent sets of control points, it can describe a wider range of lane structures compared with other lane models, i.e. straight and parabolic models. Moreover, the lane detection problem has been formulated here as the problem of determining the set of control points of lane model. The proposed algorithm ®rst detects the vanishing point (line) by using a Hough-like technique and then solves the lane detection problem by suggesting a maximum likelihood approach. Also, we have employed a multi-resolution strategy for rapidly achieving an accurate solution. This coarse-to-®ne matching oers us an acceptable solution at an aordable computational cost, and thus speeds up the process of lane detection. As a result, the proposed method is robust to noise, shadows, and illumination variations in the captured road images, and is also applicable to both the marked and the unmarked roads. Ó 2000 Elsevier Science B.V. All rights reserved.