In support of hydrocarbon exploration and discovery using clouds

Seismic data gathered from the Hydrocarbon Exploration and Discovery Operation is essential to identify possible hydrocarbon existence in a geologically surveyed area. However, the discovery operation takes a long time to be completed and computational processing of the acquired data is often delayed. Hydrocarbon exploration may end up needlessly covering an area without any hydrocarbon traces due to lack of immediate feedback from geophysical experts. This feedback can only be given when the acquired seismic data is computationally processed, analysed and interpreted. In response, we propose a comprehensive model to facilitate Hydrocarbon Exploration and Discovery Operation using encryption, decryption, satellite transmission and clouds. The model details the logical design of Seismic Data Processing (SDP) that exploits clouds and the ability for geophysical experts to provide on-line decisions on how to progress the hydrocarbon exploration operation at a remote location. Initial feasibility assessment was carried out to support our model. The SDP, data encryption and encryption for the assessment were carried out on a private cloud. The assessment shows that the overall process of hydrocarbon exploration from data acquisition, satellite data transmission through to SDP could be executed in a short time and at low costs.

Internet and distributed computing advancements : theoretical frameworks and practical applications

This book is a vital compendium of chapters on the latest research within the field of distributed computing, capturing trends in the design and development of Internet and distributed computing systems that leverage autonomic principles and techniques. The chapters provided within this collection offer a holistic approach for the development of systems that can adapt themselves to meet requirements of performance, fault tolerance, reliability, security, and Quality of Service (QoS) without manual intervention.

Network and traffic engineering in emerging distributed computing applications

This book focuses on network management and traffic engineering for Internet and distributed computing technologies, as well as present emerging technology trends and advanced platform

Bacterial biosensors for measuring availability of environmental pollutants

Biosensors are projected to find many applications due to their high selectivity and sensitivity, rapid reaction, economy and ease of handling in field measurements. Even though biosensors for a wide range of environmental pollutants have been extensively reported in the literature, the decision to develop a suitable biosensing system that can be approved by a regulatory perspective for environmental applications is fraught with technical issues. These issues mainly concern the biological recognition element, the physico-chemical transducer and the interfaces between the biological and the physical components, but also aspects of fluidics, electronics, and software for data processing. This article focused on the development of microbial-based biosensors for environmental applications especially metal contaminants such as arsenic.

Reading ancient coins: automatically identifying denarii using obverse legend seeded retrieval

The aim of this paper is to automatically identify a Roman Imperial denarius from a single query photograph of its obverse and reverse. Such functionality has the potential to contribute greatly to various national schemes which encourage laymen to report their finds to local museums. Our work introduces a series of novelties: (i) this is the first paper which describes a method for extracting the legend of an ancient coin from a photograph; (ii) we are also the first to suggest the idea and propose a method for identifying a coin using a series of carefully engineered retrievals, each harnessed for further information using visual or meta-data processing; (iii) we show how in addition to a unique standard reference number for a query coin, the proposed system can be used to extract salient coin information (issuing authority, obverse and reverse descriptions, mint date) and retrieve images of other coins of the same type.

Disputes resolution : can Bim help overcome barriers?

Many researchers consider disputes as part of the project lifecycle. Although preventative actions exist, it is not utterly possible to avoid them. Once the disputes arise, an appropriate resolution technique should be adopted. Common perception is referring to a resolution method either internally or via a third party; which may also be binding by law. The resolution process requires attention to the disputed claims. Hence, deep investigation of the claims and choosing the appropriate method is crucial for the successful project delivery and reputation of the industry.

Preparation of disputed claims and resolution process also faces many debates. Conducting To effective dispute resolution requires attention to proper preparation and presentation of the incurred events. All the required information should be acquired to estimate and present the claim, for a smooth settlement. As an integrated digital model of the project, BIM, stores all the information of the projects in detail. Retrieval of the required information for the disputed issues can easily be obtained from the model. It is also possible to embed the construction schedule, change orders and variations, specifications and financial data such as cash flow along with the multidisciplinary drawings. As this model stores all the information at every particular time and phase, disputes can be concluded quick and accurate.

In this research, using a case study and literature review, disputes and resolution processes are deeply studied. A BIM model is created to investigate benefits on overcoming the challenges; during claiming, and resolution of the disputes. It is seen that the claims are prepared faster and more accurate in a visualized environment provided by BIM. Furthermore, substantiating and presenting the disputes for the resolution purpose was incomparable to the traditional methods. The conclusions recommend that; even the project did not adopt a BIM model earlier; it can be created for a smooth process, during claiming and resolution of disputes.

Classification of neural action potentials using mean shift clustering

 Understanding neural functions requires the observation of the activities of single neurons that are represented via electrophysiological data. Processing and understanding these data are challenging problems in biomedical engineering. A microelectrode commonly records the activity of multiple neurons. Spike sorting is a process of classifying every single action potential (spike) to a particular neuron. This paper proposes a combination between diffusion maps (DM) and mean shift clustering method for spike sorting. DM is utilized to extract spike features, which are highly capable of discriminating different spike shapes. Mean shift clustering provides an automatic unsupervised clustering, which takes extracted features from DM as inputs. Experimental results show a noticeable dominance of the features extracted by DM compared to those selected by wavelet transformation (WT). Accordingly, the proposed integrated method is significantly superior to the popular existing combination of WT and superparamagnetic clustering regarding spike sorting accuracy.

Multi-dimensional liquid chromatography and metabolomics, are two dimensions better than one?

 While data processing methods in metabolomic studies often work with 'n' number of dimensions, analytical techniques, with the notable exception of NMR, have mostly stuck only to one. Peak overlap continues to be a problem and there is an ever-present demand to maximize the number of metabolites that can be separated and identified in a single run. One method that might help to overcome these issues is multidimensional liquid chromatography, which uses two columns of different phases. A sequential collection of aliquots is made from the first column and reinjected onto a second, and the resulting data are then plotted in 2D or 3D space. The total peak capacity of such a system is the combined peak capacities of each column. The 'offline' version of this technique, using a fraction collector, was introduced over 30 years ago but with recent advances in instrumentation and software, particularly the 'online' approach using automated switching valves, has led to increasing interest in the technique. Both offline and online methods can be carried out as a comprehensive procedure, or via 'heart-cutting', in which only specific peaks are analysed in the second dimension. Past applications include proteomics, natural product chemistry, forensic science and pharmaceutical analysis. These successes are likely to be built on in the future as new column chemistries and bio-informatic approaches are developed. In this review an overview of the theory of twodimensional liquid chromatography is presented, its potential in the field of metabolomics is assessed and predictions for future research directions are made.

A framework for convergence of cloud services and Internet of things

Today, Cloud Computing and the Internet of things are two "major forces" that drive the development of new Information Technology (IT) solutions. Many Internet of things (IoT) based large-scale applications rely on a cloud platform for data processing and storage. However, big data generated or collected by large-scale geo-distributed devices needs to be transferred to the cloud, often becoming a bottleneck for the system. In this paper, we propose a framework that integrates popular cloud services with a network of loT devices. In the framework, novel methods have been designed for reliable and efficient data transportation. This framework provides a convergence of cloud services and devices that will ease the development of loT based, cloud-enabled applications. We have implemented a prototype of the framework to demonstrate the convergence of popular cloud services and IoT technologies.