Query: MOMCC: Market-oriented architecture for Mobile Cloud Computing based on Service Oriented Architecture

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Service oriented architectures: approaches, technologies and research issues <=SEP=> Service-oriented architectures (SOA) is an emerging approach that addresses the requirements of loosely coupled, standards-based, and protocol- independent distributed computing. Typically business operations running in an SOA comprise a number of invocations of these different components, often in an event-driven or asynchronous fashion that reflects the underlying business process needs. To build an SOA a highly distributable communications and integration backbone is required. This functionality is provided by the Enterprise Service Bus (ESB) that is an integration platform that utilizes Web services standards to support a wide variety of communications patterns over multiple transport protocols and deliver value-added capabilities for SOA applications. This paper reviews technologies and approaches that unify the principles and concepts of SOA with those of event-based programing. The paper also focuses on the ESB and describes a range of functions that are designed to offer a manageable, standards-based SOA backbone that extends middleware functionality throughout by connecting heterogeneous components and systems and offers integration services. Finally, the paper proposes an approach to extend the conventional SOA to cater for essential ESB requirements that include capabilities such as service orchestration, “intelligent” routing, provisioning, integrity and security of message as well as service management. The layers in this extended SOA, in short xSOA, are used to classify research issues and current research activities.

A survey of trust and reputation systems for online service provision <=SEP=> Trust and reputation systems represent a significant trend in decision support for Internet mediated service provision. The basic idea is to let parties rate each other, for example after the completion of a transaction, and use the aggregated ratings about a given party to derive a trust or reputation score, which can assist other parties in deciding whether or not to transact with that party in the future. A natural side effect is that it also provides an incentive for good behaviour, and therefore tends to have a positive effect on market quality. Reputation systems can be called collaborative sanctioning systems to reflect their collaborative nature, and are related to collaborative filtering systems. Reputation systems are already being used in successful commercial online applications. There is also a rapidly growing literature around trust and reputation systems, but unfortunately this activity is not very coherent. The purpose of this article is to give an overview of existing and proposed systems that can be used to derive measures of trust and reputation for Internet transactions, to analyze the current trends and developments in this area, and to propose a research agenda for trust and reputation systems. Josang, A., R. Ismal, and C. Boyd (2007). A Survey of Trust and Reputation Systems for Online Service Provision, Journal of Decision Support Systems, 43(2):618-644 Citation: Outline of Presentation • Section 1: Introduction • Section 2: Define trust and reputation • Section 3: Trust and Reputation relationship as security mechanisms • Section 4: Collaborative filtering and reputation • Section 5: Trust Classes • Section 6: Four categories of reputation and trust semantics • Section 7: Centralized and distributed architectures for reputation Outline of Presentation Continued • Section 8: Reputation computation methods (Day 1 Goal) • Section 9: Reputation systems used in commercial applications • Section 10: Description of main problems in reputation systems • Section 11: Ending discussion Section 1: Introduction • Online transactions differ from those of in person transactions because of the inherent asymmetry in the transaction, the seller has all the power so to say. • The nature of online transactions obscure the traditional metrics used to establish if a brick and mortar store is trustworthy. Example: a brick and mortar store takes time to establish a web site takes very little time to set up. – These reasons make it hard to determine rather or not a particular online venue is trustworthy or not and is why this trust issue is receiving so much attention from an academic point of view. • The authors of this paper wrote it in part because of the rapidly growing interest in this topic and because they felt that the prior overviews used inconsistent terminology. Section 2: Define trust and reputation • Two kinds of trust: reliability and decision trust • Reliability Trust: Trust is the subjective probability by which an individual, A, expects that another individual, B, performs a given action on which its welfare depends. • Decision Trust: Trust is the extent to which one party is willing to depend on something or somebody in a given situation with a feeling of relative security, even though negative consequences are possible. • The authors mention that the prior mentioned definitions are not as simple as they seem. – For example: Trust in an individual is not necessarily enough to enter into a state of dependence with a person. In other words, that danger might seem to the agent an intolerable risk. • The authors mentions that only a few papers deal with trust and that in economic circles there are some who reject trust as a computational model. • Someone by the name of Williamson argues that the notion of trust should be avoided when modeling economic interactions, because it adds nothing new, and that well known notions such as reliability, utility and risk are adequate ad sufficient for that purpose. • Williamson argues however that personal trust is still important for modeling, and that non-computation models for trust can be meaningful for studying certain relationships. • Concerning reputation, the authors mention two aspects: trust because of good reputation and trust despite of bad reputation. • These two statements shed light on the fact that trust is often made with outside information, knowledge about the relationship that is not general know, instincts and feelings, etc. • Reputation can also be considered as a collective measure of trustworthiness based on referrals from the community. • Research in Trust and Reputation Systems should have two foci: – Finding adequate online substitutes for traditional cues in the physical world and identifying new elements specific to the online applications which are suitable for measurements. – Taking advantage of IT and Internet to create efficient systems for collecting information and deriving measurements of trust and reputation in order to aid decision making and improve online markets. • These simple principles invite rigorous research in order to answer some fundamental questions: What information elements are most suitable for deriving measures of trust and reputation in a given application? How can these information elements be captured and collected? What are the best principles for designing such systems from a theoretic and from a usability point of view? Can they be made resistant to attacks of manipulation by strategic agents? How should users include the information provided by such systems into their decision process? What role can these systems play in the business model of commercial companies? Do these systems truly improve the quality of online trade and interactions? These are important questions that need good answers in order to determine the potential for trust and reputation systems in online environments. • According to a cited reference in the paper, Resnick, a reputation system must have the following: 1. Entities must be long lived, so that with every interaction there is always an expectation of future interactions. 2. Ratings about current interactions are captured and distributed. 3. Ratings about past interactions must guide decisions about current interactions. Example of how trust is derived. (Fig. 1 from paper) Section 3: Trust and Reputation relationship as security mechanisms • In a general sense, the purpose of security mechanisms is to provide protection against malicious parties. • In many situations we have to protect ourselves from those who offer resources so that the problem in fact is reversed. Information providers can for example act deceitfully by providing false or misleading information, and traditional security mechanisms are unable to protect against this type of threat. Trust and reputation systems on the other hand can provide protection against such threats. • To summaries this section the author basically says that a computer system that appears to have robust security appears more trust worthy to the user. Listing known security vulnerabilities and using encryption techniques make the system appear to me more trust worthy. Section 4: Collaborative filtering and reputation • Collaborative filtering systems are a mechanism that shares traits with a reputation system but they are different at the same time. • Collaborative filtering systems (henceforth CF) are a mechanism that attempts to take into consideration that different people have different tastes. • If two separate people rate two items similarly then they are called neighbours in CF terminology. • This new fact can be used to recommend to one something that the other liked, a technique called a recommender system. • This takes the opposite assumption of reputation systems which assume that all people will judge the same performance or transaction consistently. • The example provided by the article is that in CF systems users might rate a video or music file differently based on tastes but one containing a virus would be universally rated poorly. • Another caveat about CF vs reputation systems is that CF systems assume an optimistic world view and reputation systems assume a pessimistic world view. • In specifics, CF systems assume all participants are trustworthy and sincere, meaning that all participants report their genuine opinion. • Conversely, reputation system assume that participants will try to misrepresent the quality of services in order to make more profit and will lie to achieve said goals. • This duel opposing nature of these type systems can make it very advantageous to combine them as will be explored in the study of Amazon in section 9 which does this to some extent. Section 5: Trust Classes • Types of Trust classes: – Provision – Access – Delegation – Identity – Context • Paper mentions them in order to get specific about trust semantics. • Paper focuses on provision trust so it is emphasized. • Provision trust describes the relying party’s trust in a service or resource provider. It is relevant when the relying party is a user seeking protection from malicious or unreliable service providers. I extrapolated from the paper that this is the type of trust that would be studied in business through subjects like contract law. • Access trust describes trust in principals for the purpose of accessing resources owned by or under the responsibility of the relying party. This relates to the access control paradigm which is a central element in computer security. • Delegation trust describes trust in an agent (the delegate) that acts and makes decision on behalf of the relying party. • Identity trust describes the belief that an agent identity is as claimed. Identity trust systems have been discussed mostly in the information security community. An example mentioned in the paper is PGP encryption technology. • Context trust describes the extent to which the relying party believes that the necessary systems and institutions ar

Survey on Energy Consumption Entities on the Smartphone Platform <=SEP=> The full degree of freedom in mobile systems heavily depends on the energy provided by the mobile phone's batteries. Their capacity is in general limited and for sure not keeping pace as the mobile devices are crammed up with new functionalities. The discrepancy of Moore's law, offering twice the processing power at least each second year, and the development in batteries, which did not even double over the last decade, makes a shift in researchers' way of designing networks, protocols, and the mobile device itself. The bottleneck to take care of in the design process of mobile systems is not only the wireless data rate, but even more the energy limitation as the customers ask for new energy-hungry services, e.g., requiring faster connections or even multiple air interfaces, and longer standby or operational times of their mobile devices at the same time. In this survey, the energy consuming entities of a mobile device such as wireless air interfaces, display, mp3 player and others are measured and compared. The presented measurement results allow the reader to understand what the energy hungry parts of a mobile device are and use those findings for the design of future mobile protocols and applications. All results presented in this work and further results are made public on our web page [2].

Immunizing online reputation reporting systems against unfair ratings and discriminatory behavior <=SEP=> Reputation reporting systems have emerged as an important risk management mechanism in online trading communities. However, the predictive value of these systems can be compromised in situations where conspiring buyers intentionally give unfair ratings to sellers or, where sellers discriminate on the quality of service they provide to different buyers. This paper proposes and evaluates a set of mechanisms, which eliminate, or significantly reduce the negative effects of such fraudulent behavior. The proposed mechanisms can be easily integrated into existing online reputation systems in order to safeguard their reliability in the presence of potentially deceitful buyers and sellers.

Web services and business process management <=SEP=> Web services based on the service-oriented architecture framework provide a suitable technical foundation for making business processes accessible within enterprises and across enterprises. But to appropriately support dynamic business processes and their management, more is needed, namely, the ability to prescribe how Web services are used to implement activities within a business process, how business processes are represented as Web services, and also which business partners perform what parts of the actual business process. In this paper, the relationship between Web services and the management of business processes is worked out and presented in a tutorial-like manner.

An implementation of cloud-based platform with R packages for spatiotemporal analysis of air pollution <=SEP=> Recently, the R package has become a popular tool for big data analysis due to its several matured software packages for the data analysis and visualization, including the analysis of air pollution. The air pollution problem is of increasing global concern as it has greatly impacts on the environment and human health. With the rapid development of IoT and the increase in the accuracy of geographical information collected by sensors, a huge amount of air pollution data were generated. Thus, it is difficult to analyze the air pollution data in a single machine environment effectively and reliably due to its inherent characteristic of memory design. In this work, we construct a distributed computing environment based on both the softwares of RHadoop and SparkR for performing the analysis and visualization of air pollution with the R more reliably and effectively. In the work, we firstly use the sensors, called EdiGreen AirBox to collect the air pollution data in Taichung, Taiwan. Then, we adopt the Inverse Distance Weighting method to transform the sensors’ data into the density map. Finally, the experimental results show the accuracy of the short-term prediction results of PM2.5 by using the ARIMA model. In addition, the verification with respect to the prediction accuracy with the MAPE method is also presented in the experimental results.

Contrast-limited adaptive histogram equalization: speed and effectiveness <=SEP=> The Contrast-Limited Adaptive Histogram Equalization (CLARE) method for assigning displayed intensity levels in medical images, is supported by anecdotal evidence and evidence from detection experiments. Despite that, the method requires clinical evaluation and implementation achieving few-second application before it can be clinically adopted. Experiments attempting to produce this evaluation and a machine providing the required performance are

Miniature Dual-Mode Microstrip Filters <=SEP=> In order to reduce the size of dual-mode microstrip filters by keeping excellent performance, novel filter geometry is proposed. The novel filter includes a dual-mode resonator based on a meander structure. The effect of input/output feed lines located along a straight line on filter response is investigated for the dual-mode filter. The coupling between degenerate modes of the proposed dual-mode microstrip resonator is discussed depending on the perturbation size. The two dual-mode microstrip bandpass filters with real axis and imaginary axis transmission zeros (TZs) are designed, fabricated, and measured to document the validity of the description of the positive and negative coupling coefficient

EVS 25 Shenzhen , China , Nov . 5-9 , 2010 Control of A high-Performance Z-Source Inverter for Fuel Cell / Supercapacitor Hybrid Electric Vehicles <=SEP=> This paper presents a supercapacitor (SC) module connected in parallel with fuel cell (FC) stack to supply a high-performance Z-Source Inverter (HP-ZSI) feeding a three phase induction motor for hybrid electric vehicles applications. The supercapacitor is connected between the input diode and the bidirectional switch of the highperformance ZSI topology. The indirect field-oriented control (IFOC) method is used to control an induction motor speed during motoring and regenerative braking operations to produce the modulation index and a dual loop controller is used to control the Z-network capacitor voltage to produce the shoot-through duty ratio. MATLAB simulation results verified the validity of the proposed control strategy during motoring and regenerative braking operations.

How do Retailers Adjust Prices?: Evidence from Store-Level Data <=SEP=> Recent theoretical work on retail pricing dynamics suggests that retailers periodically hold sales periodic, temporary reductions in price, -even when their costs are unchanged. In this paper we extend existing theory to predict which items will go on sale, and use a new data set from the BLS to document the frequency of sales across a wide range of goods and geographic areas. We find a number of pricing regularities for the 20 categories of goods we examine. First, retailers seem to have a “regular” price, and most deviations from that price are downward. Second, there is considerable heterogeneity in sale behavior across goods within a category (e.g. cereal); the same items are regularly put on sale, while other items rarely are on sale. Third, items are more likely to go on sale when demand is highest. Fourth, for a limited number of items for which we know market shares, products with larger market shares go on sale more often. These final three observations are consistent with our theoretical result that popular products are most likely to be placed on sale.

Conditional Dynamic Mutual Information-Based Feature Selection <=SEP=> With emergence of new techniques, data in many fields are getting larger and larger, especially in dimensionality aspect. The high dimensionality of data may pose great challenges to traditional learning algorithms. In fact, many of features in large volume of data are redundant and noisy. Their presence not only degrades the performance of learning algorithms, but also confuses end-users in the post-analysis process. Thus, it is necessary to eliminate irrelevant features from data before being fed into learning algorithms. Currently, many endeavors have been attempted in this field and many outstanding feature selection methods have been developed. Among different evaluation criteria, mutual information has also been widely used in feature selection because of its good capability of quantifying uncertainty of features in classification tasks. However, the mutual information estimated on the whole dataset can not exactly represent the correlation between features. To cope with this issue, in this paper we firstly re-estimate mutual information on identified instances dynamically, and then introduce a new feature selection method based on 1194 H. Liu, Y. Mo, J. Zhao conditional mutual information. Performance evaluations on sixteen UCI datasets show that our proposed method achieves comparable performance to other wellestablished feature selection algorithms in most cases.

Learning Sparse Feature Representations for Music Annotation and Retrieval <=SEP=> We present a data-processing pipeline based on sparse feature learning and describe its applications to music annotation and retrieval. Content-based music annotation and retrieval systems process audio starting with features. While commonly used features, such as MFCC, are handcrafted to extract characteristics of the audio in a succinct way, there is increasing interest in learning features automatically from data using unsupervised algorithms. We describe a systemic approach applying feature-learning algorithms to music data, in particular, focusing on a highdimensional sparse-feature representation. Our experiments show that, using only a linear classifier, the newly learned features produce results on the CAL500 dataset comparable to state-of-the-art music annotation and retrieval systems.

Cost-Aware WWW Proxy Caching Algorithms <=SEP=> Difference between Web Caching & Conventional Paging Problems: Web caching is variable-size caching (web documents vary dramatically in size depending on the information they carry (text, image, video, etc.). Web pages take different amounts of time to download, even if they are of the same size (download latency). Access streams seen by the proxy cache are the union of web access streams from tens to thousands of users (instead of coming from a few programmed sources as in the case of virtual memory paging)

Deep into the Brain: Artificial Intelligence in Stroke Imaging <=SEP=> Artificial intelligence (AI), a computer system aiming to mimic human intelligence, is gaining increasing interest and is being incorporated into many fields, including medicine. Stroke medicine is one such area of application of AI, for improving the accuracy of diagnosis and the quality of patient care. For stroke management, adequate analysis of stroke imaging is crucial. Recently, AI techniques have been applied to decipher the data from stroke imaging and have demonstrated some promising results. In the very near future, such AI techniques may play a pivotal role in determining the therapeutic methods and predicting the prognosis for stroke patients in an individualized manner. In this review, we offer a glimpse at the use of AI in stroke imaging, specifically focusing on its technical principles, clinical application, and future perspectives.

Syntactic Stylometry: Using Sentence Structure for Authorship Attribution <=SEP=> Most approaches to statistical stylometry have concentrated on lexical features, such as relative word frequencies or type-token ratios. Syntactic features have been largely ignored. This work attempts to fill that void by introducing a technique for authorship attribution based on dependency grammar. Syntactic features are extracted from texts using a common dependency parser, and those features are used to train a classifier to identify texts by author. While the method described does not outperform existing methods on most tasks, it does demonstrate that purely syntactic features carry information which could be useful for stylometric analysis. Index words: stylometry, authorship attribution, dependency grammar, machine learning Syntactic Stylometry: Using Sentence Structure for Authorship Attribution

Cooperative flood detection using GSMD via SMS <=SEP=> This paper proposes architecture for an early warning floods system to alert public against flood disasters. An effective early warning system must be developed with linkages between four elements, which are accurate data collection to undertake risk assessments, development of hazard monitoring services, communication on risk related information and existence of community response capabilities. This project focuses on monitoring water level remotely using wireless sensor network. The project also utilizes Global System for Mobile communication (GSM) and short message service (SMS) to relay data from sensors to computers or directly alert the respective victim's through their mobile phone. It is hope that the proposed architecture can be further develop into a functioning system, which would be beneficial to the community and act as a precautionary action to save lives in the case of flood disaster.

Energy-Efficient Hierarchical Routing for Wireless Sensor Networks: A Swarm Intelligence Approach <=SEP=> Energy efficient routing in wireless sensor networks (WSNs) require non-conventional paradigm for design and development of power aware protocols. Swarm intelligence (SI) based metaheuristic can be applied for optimal routing of data, in an energy constraint WSNs environment. In this paper, we present BeeSwarm, a SI based energyefficient hierarchical routing protocol for WSNs. Our protocol consists of three phases: (1) Set-up phase-BeeCluster, (2) Route discovery phase-BeeSearch and (3) Data transmission phase-BeeCarrier. Integration of three phases for clustering, data routing and transmission, is the key aspect of our proposed protocol, which ultimately contributes to its robustness. Evaluation of simulation results show that BeeSwarm perform better in terms of packet delivery, energy consumption and throughput with increased network life compared to other SI based hierarchical routing protocols.

Children's engagement with educational iPad apps: Insights from a Spanish classroom <=SEP=> This study investigates the effects of a story-making app called Our Story and a selection of other educational apps on the learning engagement of forty-one Spanish 4–5-year-olds. Children were observed interacting in small groups with the story-making app and this was compared to their engagement with a selection of construction and drawing apps. Children’s engagement was analysed in two ways: it was categorised using Bangert-Drowns and Pyke’s taxonomy for individual hands-on engagement with educational software, and using the concept of exploratory talk as developed by Mercer et al. to analyse peer engagement. For both approaches, quantitative and qualitative indices of children’s engagement were considered. The overall findings suggested that in terms of the BangertDrowns and Pyke taxonomy, the quality of children’s individual engagement was higher with the OS app in contrast to their engagement with other app software. The frequency of children’s use of exploratory talk was similar with the OS and colouring and drawing apps, and a detailed qualitative analysis of the interaction transcripts revealed several instances of the OS and drawing apps supporting joint problem-solving and collaborative engagement. We suggest that critical indices of an app’s educational value are the extent to which the app supports opportunities for open-ended content and children’s independent use of increasingly difficult features. 2013 Elsevier Ltd. All rights reserved.

Integrating the Quality Attribute Workshop ( QAW ) and the Attribute-Driven Design ( ADD ) Method <=SEP=> ............................................................................................................vii

Action-Reaction: Forecasting the Dynamics of Human Interaction <=SEP=> Forecasting human activities from visual evidence is an emerging area of research which aims to allow computational systems to make predictions about unseen human actions. We explore the task of activity forecasting in the context of dual-agent interactions to understand how the actions of one person can be used to predict the actions of another. We model dual-agent interactions as an optimal control problem, where the actions of the initiating agent induce a cost topology over the space of reactive poses – a space in which the reactive agent plans an optimal pose trajectory. The technique developed in this work employs a kernel-based reinforcement learning approximation of the soft maximum value function to deal with the high-dimensional nature of human motion and applies a mean-shift procedure over a continuous cost function to infer a smooth reaction sequence. Experimental results show that our proposed method is able to properly model human interactions in a high dimensional space of human poses. When compared to several baseline models, results show that our method is able to generate highly plausible simulations of human interaction.

Modeling Human Education Data: From Equation-Based Modeling to Agent-Based Modeling <=SEP=> Agent-based simulation is increasingly used to analyze the performance of complex systems. In this paper we describe results of our work on one specific agent-based model, showing how it can be validated against the equation-based model from which it was derived, and demonstrating the extent to which it can be used to derive additional results over and above those that the equation-based model can provide.

LITMUS: Landslide detection by integrating multiple sources <=SEP=> Disasters often lead to other kinds of disasters, forming multi-hazards such as landslides, which may be caused by earthquakes, rainfalls, water erosion, among other reasons. Effective detection and management of multihazards cannot rely only on one information source. In this paper, we evaluate a landslide detection system LITMUS, which combines multiple physical sensors and social media to handle the inherent varied origins and composition of multi-hazards. LITMUS integrates near real-time data from USGS seismic network, NASA TRMM rainfall network, Twitter, YouTube, and Instagram. The landslide detection process consists of several stages of social media filtering and integration with physical sensor data, with a final ranking of relevance by integrated signal strength. Applying LITMUS to data collected in October 2013, we analyzed and filtered 34.5k tweets, 2.5k video descriptions and 1.6k image captions containing landslide keywords followed by integration with physical sources based on a Bayesian model strategy. It resulted in detection of all 11 landslides reported by USGS and 31 more landslides unreported by USGS. An illustrative example is provided to demonstrate how LITMUS’ functionality can be used to determine landslides related to the recent Typhoon Haiyan.

An ontology-based model to determine the automation level of an automated vehicle for co-driving <=SEP=> Full autonomy of ground vehicles is a major goal of the ITS (Intelligent Transportation Systems) community. However, reaching such highest autonomy level in all situations (weather, traffic, ...) may seem difficult in practice, despite recent results regarding driverless cars (e.g., Google Cars). In addition, an automated vehicle should also self-assess its own perception abilities, and not only perceive its environment. In this paper, we propose an intermediate approach towards full automation, by defining a spectrum of automation layers, from fully manual (the car is driven by a driver) to fully automated (the car is driven by a computer), based on an ontological model for representing knowledge. We also propose a second ontology for situation assessment (what does the automated car perceive?), including the sensors/actuators state, environmental conditions and driver's state. Finally, we also define inference rules to link the situation assessment ontology to the automation level one. Both ontological models have been built and first results are presented.

Optimization for allocating BEV recharging stations in urban areas by using hierarchical clustering <=SEP=> The Battery Electric Vehicle (BEV) prototypes are evolving into a reality in a foreseeable future. Before BEV can embark on a mass adoption by road commuters, a new infrastructure for battery charging will have to be ready in place. By 2015, access to BEV charging will be available at nearly one million charge points in the United States, as claimed by CleanMPG. Early BEV adopters will primarily charge their vehicles at home, in their private garages. However, for many Asia-Pacific regions where people live in concrete ghettos, public charging will play a more central role due to reduced access to convenient home charging. This research focuses on planning BEV charging locations to be installed in urbanized areas where they are usually characterized by dense traffic concentrations, restricted street spaces and other complex factors such as the distribution of power grids. We proposed a two-steps model that first quantified the road information into data points, and subsequently they are converged into 'demand clusters' over an urbanized area by hierarchical clustering analysis. Optimization techniques then applied on the demand clusters with the aim of meeting the supplies and demands, while at the same time certain constraints and cost factors are considered. The model is believed to be an important decision-support tool for city planning and BEV charging stations allocation.

Relevance and lexical pragmatics * <=SEP=> The goal of lexical pragmatics is to explain how linguistically specified (‘literal’) word meanings are modified in use. While lexical-pragmatic processes such as narrowing, broadening and metaphorical extension are generally studied in isolation from each other, relevance theorists (Carston 2002, Wilson & Sperber 2002) have been arguing for a unified approach. I will continue this work by underlining some of the problems with more standard treatments, and show how a variety of lexicalpragmatic processes may be analysed as special cases of a general pragmatic adjustment process which applies spontaneously, automatically and unconsciously to fine-tune the interpretation of virtually every word.

Underwater sensor networks: applications, advances and challenges. <=SEP=> This paper examines the main approaches and challenges in the design and implementation of underwater wireless sensor networks. We summarize key applications and the main phenomena related to acoustic propagation, and discuss how they affect the design and operation of communication systems and networking protocols at various layers. We also provide an overview of communications hardware, testbeds and simulation tools available to the research community.

An improvement on the Euler number computing algorithm used in MATLAB <=SEP=> Computation of the Euler number of a binary image is often necessary in image matching, image database retrieval, image analysis, pattern recognition, and computer vision. This paper proposes an improvement on the Euler number computing algorithm used in the famous image processing tool MATLAB. By use of the information obtained during processing the previous pixel, the number of times of checking the neighbor pixels for processing a pixel decrease from 4 to 2. Our method is very simple in principle, and easily implemented. The experimental results demonstrated that our method outperforms significantly conventional Euler number computing algorithms.

DIP: the Database of Interacting Proteins <=SEP=> The Database of Interacting Proteins (DIP; http://dip.doe-mbi.ucla.edu) is a database that documents experimentally determined protein-protein interactions. This database is intended to provide the scientific community with a comprehensive and integrated tool for browsing and efficiently extracting information about protein interactions and interaction networks in biological processes. Beyond cataloging details of protein-protein interactions, the DIP is useful for understanding protein function and protein-protein relationships, studying the properties of networks of interacting proteins, benchmarking predictions of protein-protein interactions, and studying the evolution of protein-protein interactions.

Effects of wine, alcohol and polyphenols on cardiovascular disease risk factors: evidences from human studies. <=SEP=> AIMS
The aim of this review was to focus on the knowledge of the cardiovascular benefits of moderate alcohol consumption, as well as to analyze the effects of the different types of alcoholic beverages.


METHODS
Systematic revision of human clinical studies and meta-analyses related to moderate alcohol consumption and cardiovascular disease (CVD) from 2000 to 2012.


RESULTS
Heavy or binge alcohol consumption unquestionably leads to increased morbidity and mortality. Nevertheless, moderate alcohol consumption, especially alcoholic beverages rich in polyphenols, such as wine and beer, seems to confer cardiovascular protective effects in patients with documented CVD and even in healthy subjects.


CONCLUSIONS
In conclusion, wine and beer (but especially red wine) seem to confer greater cardiovascular protection than spirits because of their polyphenolic content. However, caution should be taken when making recommendations related to alcohol consumption.

Powering MEMS portable devices — a review of non-regenerative and regenerative power supply systems with special emphasis on piezoelectric energy harvesting systems <=SEP=> Power consumption is forecast by the International Technology Roadmap of Semiconductors (ITRS) to pose long-term technical challenges for the semiconductor industry. The purpose of this paper is threefold: (1) to provide an overview of strategies for powering MEMS via non-regenerative and regenerative power supplies; (2) to review the fundamentals of piezoelectric energy harvesting, along with recent advancements, and (3) to discuss future trends and applications for piezoelectric energy harvesting technology. The paper concludes with a discussion of research needs that are critical for the enhancement of piezoelectric energy harvesting devices. (Some figures in this article are in colour only in the electronic version)