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The neural network techniques are developed for artificial sequences based on approximate models of proteins. We only encode the hydrophobicity of the amino acid side chains without attempting to model the secondary structure. We use our approach to obtain a large set of sequences with known 3-D structures for training the neural network. By employing recurrent neural networks we describe a way to augment a neural network to deal with sequences of realistic length and long-distant interactions between the sequence regions., Comment: 10 pages, 4 postscript figures

In recent years, precision agriculture is becoming very popular. The introduction of modern information and communication technologies for collecting and processing Agricultural data revolutionise the agriculture practises. This has started a while ago (early 20th century) and it is driven by the low cost of collecting data about everything; from information on fields such as seed, soil, fertiliser, pest, to weather data, drones and satellites images. Specially, the agricultural data mining today is considered as Big Data application in terms of volume, variety, velocity and veracity. Hence it leads to challenges in processing vast amounts of complex and diverse information to extract useful knowledge for the farmer, agronomist, and other businesses. It is a key foundation to establishing a crop intelligence platform, which will enable efficient resource management and high quality agronomy decision making and recommendations. In this paper, we designed and implemented a continental level agricultural data warehouse (ADW). ADW is characterised by its (1) flexible schema; (2) data integration from real agricultural multi datasets; (3) data science and business intelligent support; (4) high performance; (5) high storage; (6) security; (7) governance and monitoring; (8) consistency, availability and partition tolerant; (9) cloud compatibility. We also evaluate the performance of ADW and present some complex queries to extract and return necessary knowledge about crop management., Comment: 13 pages, 11 figures. arXiv admin note: text overlap with arXiv:1905.12411

Laser scanning (also known as Light Detection And Ranging) has been widely applied in various application. As part of that, aerial laser scanning (ALS) has been used to collect topographic data points for a large area, which triggers to million points to be acquired. Furthermore, today, with integrating full wareform (FWF) technology during ALS data acquisition, all return information of laser pulse is stored. Thus, ALS data are to be massive and complexity since the FWF of each laser pulse can be stored up to 256 samples and density of ALS data is also increasing significantly. Processing LiDAR data demands heavy operations and the traditional approaches require significant hardware and running time. On the other hand, researchers have recently proposed parallel approaches for analysing LiDAR data. These approaches are normally based on parallel architecture of target systems such as multi-core processors, GPU, etc. However, there is still missing efficient approaches/tools supporting the analysis of LiDAR data due to the lack of a deep study on both library tools and algorithms used in processing this data. In this paper, we present a comparative study of software libraries and algorithms to optimise the processing of LiDAR data. We also propose new method to improve this process with experiments on large LiDAR data. Finally, we discuss on a parallel solution of our approach where we integrate parallel computing in processing LiDAR data.

Industrial Control Systems (ICS) are used worldwide in critical infrastructures. An ICS system can be a single embedded system working stand-alone for controlling a simple process or ICS can also be a very complex Distributed Control System (DCS) connected to Supervisory Control And Data Acquisition (SCADA) system(s) in a nuclear power plant. Although ICS are widely used to-day, there are very little research on the forensic acquisition and analyze ICS artefacts. In this paper we present a case study of forensics in ICS where we de-scribe a method of safeguarding important volatile artefacts from an embedded industrial control system and several other sources

Nowadays, financial data analysis is becoming increasingly important in the business market. As companies collect more and more data from daily operations, they expect to extract useful knowledge from existing collected data to help make reasonable decisions for new customer requests, e.g. user credit category, churn analysis, real estate analysis, etc. Financial institutes have applied different data mining techniques to enhance their business performance. However, simple ap-proach of these techniques could raise a performance issue. Besides, there are very few general models for both understanding and forecasting different finan-cial fields. We present in this paper a new classification model for analyzing fi-nancial data. We also evaluate this model with different real-world data to show its performance.

Today, a mobile phone is not just a phone but it is a computer that you can also use for calling someone. Besides, in criminal investigations the importance of evidence from the mobile phone is increasing as more and more phones are seized at the Digital Forensic Department of the police. Indeed, the amount of memory cards of these mobile phones that need to be investigated separately is also increasing. Possible reasons are that the mobile phone investigation software does not support the specific mobile phone or the specific, for that investigation, artefacts. Sometimes the software investigates just the internal memory of the mobile phone and not the data which is written on the memory card. Fact is also that although the mobile phone was investigated by the dedicated software, the possibility that the associated memory card contains additional important information is evident. The current procedure to get all of the usable information from a memory card of a mobile phone is very time-consuming process and not user friendly. In this paper, we present a new single tool to simplify the investigation of a memory card from a mobile phone. We also test our tool with WhatsApp application installed on the memory card from different mobile phones.

In this paper we proposed a hierarchical P2P network based on a dynamic partitioning on a 1-D space. This hierarchy is created and maintained dynamically and provides a gridmiddleware (like DGET) a P2P basic functionality for resource discovery and load-balancing.This network architecture is called TreeP (Tree based P2P network architecture) and is based on atessellation of a 1-D space. We show that this topology exploits in an efficient way theheterogeneity feature of the network while limiting the overhead introduced by the overlaymaintenance. Experimental results show that this topology is highly resilient to a large number ofnetwork failures.

During the last decade there has been a huge interest in Grid technologies, and numerous Grid projects have been initiated with various visions of the Grid. While all these visions have the same goal of resource sharing, they differ in the functionality that a Grid supports, the grid characterisation, programming environments, etc. In this paper we present a new Grid system dedicated to deal with data issues, called DGET (Data Grid Environment and Tools). DGET is characterized by its peer-to-peer communication system and entity-based architecture, therefore, taking advantage of the main functionality of both systems; P2P and Grid. DGET is currently under development and a prototype implementing the main components is in its first phase of testing. In this paper we limit our description to the system architectural features and to the main differences with other systems.

In this paper we present a method to study the folding structure of a simple model consisting of two kinds of monomers, hydrophobic and hydrophilic. This method has three main steps: an efficient simulation method to bring an open sequence of homopolymer to a folded state, the application of a painting method called (regular hull) to the folded globule and the refolding process of the obtained copolymer sequence. This study allows us to suggest a theoretical function of disorder distribution for copolymer sequences that give rise to a compacted and well micro-phase separated globule., Comment: 11 pages incl. 6 PS figures. Paper presented at the International Conference on Morphology and Kinetics of Phase Separating Complex Fluids, Messina, Italy, June 1997