Platform-independent Application Research Articles

MIA is an open-source standalone deep learning application for microscopic image analysis

In recent years, the amount of data generated by imaging techniques has grown rapidly, along with increasing computational power and the development of deep learning algorithms. To address the need for powerful automated image analysis tools for a broad range of applications in the biomedical sciences, the Microscopic Image Analyzer (MIA) was developed. MIA combines a graphical user interface that obviates the need for programming skills with state-of-the-art deep-learning algorithms for segmentation, object detection, and classification. It runs as a standalone, platform-independent application and uses open data formats, which are compatible with commonly used open-source software packages. The software provides a unified interface for easy image labeling, model training, and inference. Furthermore, the software was evaluated in a public competition and performed among the top three for all tested datasets.

EZRVS: An AI-Based Web Application to Significantly Enhance Seismic Rapid Visual Screening of Buildings

ABSTRACT The buildings’ damages due to the recent worldwide earthquakes have highlighted the vulnerability of the existing constructions and the significance of seismic retrofitting. Many of the currently operational buildings need further evaluation to minimize seismic damage and improve performance. Precise and comprehensive building evaluation would not be feasible due to the great expenditure it requires, which is why Rapid Visual Screening (RVS) techniques are to be used to predict the level of seismic damage to the buildings that should have otherwise been evaluated using accurate assessments. Pre-earthquake building screening is thus carried out to identify the buildings with high seismic vulnerability and prioritize those that require more accurate analysis. The present study takes advantage of FEMA-154 and an artificial neural network model with a noticeable accuracy of 83% to predict the level of damage to reinforced concrete buildings and is the first to consider the two parameters of potential earthquake magnitude and the distance of the building from the earthquake epicenter. A web-based, responsive, and platform-independent application called EZRVS (available at http://www.seismohub.com/) has been developed that implemented the proposed methodology.

A Platform Independent Web-Application for Short-Term Electric Power Load Forecasting on a 33/11 kV Substation Using Regression Model

Short-term electric power load forecasting is a critical and essential task for utilities of the electric power industry for proper energy trading and that enable the independent system operator to operate the network without any technical and economical issues. In this paper, machine learning model such as linear regression model is used to forecast the active power load one hour and one day ahead. Real time active power load data to train and test the machine learning model is collected from a 33/11 kV substation located in Telangana State, India. Based on the simulation results, it is observed that linear regression model can forecast the load with less mean absolute error i.e. 0.042 with training data and 0.045 with testing data in comparison with support vector regressor model for an hour ahead operation. Whereas in the case of the day ahead operation, linear regression model can forecast the load with less mean absolute error i.e. 0.055 with training data and 0.057 with testing data in comparison with support vector regressor model. A platform independent web application is developed to help the operators of the 33/11 kV substation which is located in Godishala, Telangana State, India.

Structuring Cyber-Physical Systems for Distributed Control with IEC 61499 Standard

With the constant growth in size and complexity of modern industrial applications, it is not suitable to use a unique and centralized controller device for the whole process. Thus, automation solutions need to be designed by distributing control execution across different devices. Cyber-Physical Systems (CPSs) are designed to solve networked embedded systems complexities. The IEC 61499 standard fosters developing distributed control applications by defining a platform-independent application model that can be mapped to numerous hardware components. Therefore, a relevant research topic is how to solve the design complexities of industrial CPSs by applying modeling techniques. In that context, this paper proposes an IEC 61499-based model for CPSs to distribute the complexity of control software over numerous small devices. The approach enables the creation of a comprehensive structure that can combine design, simulation, and distributed deployment of automation software. The proposed scheme is validated through a packet sorting system implemented in a commercial IDE platform.

Coinnet: platform independent application to recognize Indian currency notes using deep learning techniques

In India, nearly 12 million visually impaired people had difficulty in identifying the currency notes. There is a need to develop an application that can recognize the currency note and provide a vocal message. In this paper, a novel lightweight Convolutional Neural Network (CNN) model is developed for efficient web and mobile applications to recognize the Indian currency notes. A new dataset for Indian currency notes has been created to train, validate, and test the CNN model. This CNN based web and mobile applications will provide a text and audio output based on the recognized currency note. The proposed model is developed using TensorFlow and improved by selection of optimal hyperparameter value, and compared with existing well known CNN architectures using transfer learning. Based on the results it has been observed that proposed model perform well over six widely used existing architectures in terms of training and testing accuracy.

Application Development wtih Service Oriented Architecture

Today, it is one of the most invested areas of organizations to ensure the interoperability of existing corporate applications and newly developed or purchased applications. Developed systems are designed to be shaped according to the needs of the businesses that use it. Classical systems are automation systems that operate from point to point and from other platforms in the enterprise without interaction. Unlike these, the service-oriented architecture (SOA) contains a structure that is ready to interact. In this study, a system has been designed in order to reduce the integration costs between the applications in the long term by using SOA approach, to shorten the business processes in the institution and to reduce the economic costs. In the project, work pieces were published as a method of service over the service layer. Thus, the platform independent main application is accessible to each work piece. At the same time, these work pieces can come together and be reconfigured according to the request of the enterprise. Some of the advantages achieved by using SOA are: Providing improved work processes for services and actors, ensuring collaboration, utilizing from existing and reuse with savings, providing business flexibility by responding to changing business needs.

Ontology-based model-driven design of distributed control applications in manufacturing systems

Integration of system design models with software design has been employed as a common paradigm for model-driven design of control applications of distributed automation systems. However, there is still a lack of efficient methods to automatically project the system design to the control dimension. In this study, ontology modelling and reasoning is exploited to bridge the system design in SysML and control application design in IEC 61499 specific to the manufacturing domain. First, a manufacturing ontology (MFO) is formally defined, based on which the system design can be enriched and verified. Second, a distributed control ontology (DCO) is proposed to correlate the enriched system design and control application design such that automated inference between them can be achieved. Finally, an IEC 61499 model is generated from the platform-independent control application design in DCO. The approach is implemented by an ontology-based framework leveraging semantic web technologies. A CNC bending machine is used as a case study to illustrate the workflow and potential usage of the generated models.

VIOLA-A Multi-Purpose and Web-Based Visualization Tool for Neuronal-Network Simulation Output.

Neuronal network models and corresponding computer simulations are invaluable tools to aid the interpretation of the relationship between neuron properties, connectivity, and measured activity in cortical tissue. Spatiotemporal patterns of activity propagating across the cortical surface as observed experimentally can for example be described by neuronal network models with layered geometry and distance-dependent connectivity. In order to cover the surface area captured by today's experimental techniques and to achieve sufficient self-consistency, such models contain millions of nerve cells. The interpretation of the resulting stream of multi-modal and multi-dimensional simulation data calls for integrating interactive visualization steps into existing simulation-analysis workflows. Here, we present a set of interactive visualization concepts called views for the visual analysis of activity data in topological network models, and a corresponding reference implementation VIOLA (VIsualization Of Layer Activity). The software is a lightweight, open-source, web-based, and platform-independent application combining and adapting modern interactive visualization paradigms, such as coordinated multiple views, for massively parallel neurophysiological data. For a use-case demonstration we consider spiking activity data of a two-population, layered point-neuron network model incorporating distance-dependent connectivity subject to a spatially confined excitation originating from an external population. With the multiple coordinated views, an explorative and qualitative assessment of the spatiotemporal features of neuronal activity can be performed upfront of a detailed quantitative data analysis of specific aspects of the data. Interactive multi-view analysis therefore assists existing data analysis workflows. Furthermore, ongoing efforts including the European Human Brain Project aim at providing online user portals for integrated model development, simulation, analysis, and provenance tracking, wherein interactive visual analysis tools are one component. Browser-compatible, web-technology based solutions are therefore required. Within this scope, with VIOLA we provide a first prototype.

Synapse: Synthetic application profiler and emulator

Motivated by the need to emulate workload execution characteristics on high-performance and distributed heterogeneous resources, we introduce Synapse. Synapse is used as a proxy application (or "representative application") for real workloads, with the advantage that it can be tuned in different ways and dimensions, and also at levels of granularity that are not possible with real applications. Synapse has a platform-independent application profiler, and has the ability to emulate profiled workloads on a variety of resources. Experiments show that the automated profiling performed using Synapse captures an application's characteristics with high fidelity. The emulation of an application using Synapse can reproduce the application's execution behavior in the original run-time environment, and can also reproduce those behaviors on different run-time environments.

Evolving large scale healthcare applications using open standards

Abstract Electronic Health Records (EHRs) are becoming more prevalent in health care. Worldwide exchange of healthcare data demands adherence to semantic interoperable standards to overcome the language and platform barriers. Various healthcare organizations in developing countries such as, India adopt their own independent information systems without adhering to standard guidelines. Thus, this tends to sacrifice interoperability. This affects permanent persistence of longitudinal health records for future reference and research purpose. Current research implements a standard based clinical application to be used for healthcare domain in India. The study has been done for enhancing the data quality through standardization. It aims at providing a generic permanent persistence to track life-long interoperable health records of patients. This is the first effort for exploring its adoption for various regional languages in India. The user interfaces have been generated for various Indian languages for testing on a sample set of archetypes. The clinical application deployed in ‘Hindi’ language can be easily deployed for other people in ‘Tamil’ language, while maintaining semantic interoperability. The persistence will also be maintained, with the same meaning (of data) for both the regions. Implementing these standard based healthcare applications helps in reducing the costs while enhancing patient care. Thus, this study aims to build a standard based, and platform independent healthcare application to provide support for interoperability, usability and generic persistence.

DockingApp: a user friendly interface for facilitated docking simulations with AutoDock Vina.

Molecular docking is a powerful technique that helps uncover the structural and energetic bases of the interaction between macromolecules and substrates, endogenous and exogenous ligands, and inhibitors. Moreover, this technique plays a pivotal role in accelerating the screening of large libraries of compounds for drug development purposes. The need to promote community-driven drug development efforts, especially as far as neglected diseases are concerned, calls for user-friendly tools to allow non-expert users to exploit the full potential of molecular docking. Along this path, here is described the implementation of DockingApp, a freely available, extremely user-friendly, platform-independent application for performing docking simulations and virtual screening tasks using AutoDock Vina. DockingApp sports an intuitive graphical user interface which greatly facilitates both the input phase and the analysis of the results, which can be visualized in graphical form using the embedded JMol applet. The application comes with the DrugBank set of more than 1400 ready-to-dock, FDA-approved drugs, to facilitate virtual screening and drug repurposing initiatives. Furthermore, other databases of compounds such as ZINC, available also in AutoDock format, can be readily and easily plugged in.

ArAR — A software tool to promote the robust comparison of K–Ar and 40Ar/39Ar dates published using different decay, isotopic, and monitor-age parameters

The comparison of K–Ar and 40Ar/39Ar geochronologic data published by different laboratories is markedly hindered by the inconsistent use of the parameters necessary to convert isotopic analyses to dates. This problem is particularly acute when we try to evaluate the significance of datasets obtained prior to the development of community consensus values for basic decay constants, isotopic abundances, and the ages of common monitor minerals. Unfortunately, the effect of using different parameters for the same dataset can sometimes exceed the quoted analytical precision of derived dates. We created the Argon Age Recalculator, or ArAR, to help researchers account for such discrepancies in a simple, efficient manner, allowing for more robust comparisons among datasets and more effective compilation of existing datasets using self-consistent parameter sets. ArAR is freely available as a platform independent executable application at: http://group18software.asu.edu.

Detection and Visualization of Android Malware Behavior

Malware analysts still need to manually inspect malware samples that are considered suspicious by heuristic rules. They dissect software pieces and look for malware evidence in the code. The increasing number of malicious applications targeting Android devices raises the demand for analyzing them to find where the malcode is triggered when user interacts with them. In this paper a framework to monitor and visualize Android applications’ anomalous function calls is described. Our approach includes platform-independent application instrumentation, introducing hooks in order to trace restricted API functions used at runtime of the application. These function calls are collected at a central server where the application behavior filtering and a visualization take place. This can help Android malware analysts in visually inspecting what the application under study does, easily identifying such malicious functions.

Design and implementation of data acquisition system for magnets of SST-1

Abstract The magnet system of the Steady-State Superconducting Tokamak-1 at the Institute for Plasma Research, Gandhinagar, India, consists of sixteen toroidal field and nine poloidal field. Superconducting coils together with a pair of resistive PF coils, an air core ohmic transformer and a pair of vertical field coils. These magnets are instrumented with various cryogenic compatible sensors and voltage taps for its monitoring, operation, protection, and control during different machine operational scenarios like cryogenic cool down, current charging cycles including ramp up, flat top, plasma breakdown, dumping/ramp down and warm up. The data acquisition system for these magnet instrumentation have stringent requirement regarding operational flexibility, reliability for continuous long term operation and data visualization during operations. A VME hardware based data acquisition system with ethernet based remote system architecture is implemented for data acquisition and control of the complete magnet operation. Software application is developed in three parts namely an embedded VME target, a network server and a remote client applications. A target board application implemented with real time operating system takes care of hardware configuration and raw data transmission to server application. A java server application manages several activities mainly multiple client communication over ethernet, database interface and data storage. A java based platform independent desktop client application is developed for online and offline data visualization, remote hard ware configuration and many other user interface tasks. The application has two modes of operation to cater to different needs of cool-down and charging operations. This paper describes application architecture, installation and commissioning and operational experience from the recent campaigns of SST-1.

TUIT, a BLAST-Based Tool for Taxonomic Classification of Nucleotide Sequences

Pyrosequencing of 16S ribosomal RNA (rRNA) genes has become the gold standard in human microbiome studies. The routine task of taxonomic classification using 16S rRNA reads is commonly performed by the Ribosomal Database Project (RDP) II Classifier, a robust tool that relies on a set of well-characterized reference sequences. However, the RDP II Classifier may be unable to classify a significant part of the data set due to the absence of proper reference sequences. The taxonomic classification for some unclassified sequences might still be performed using BLAST searches against large and frequently updated nucleotide databases. Here we introduce TUIT (Taxonomic Unit Identification Tool)-an efficient open source and platform-independent application that can perform taxonomic classification on its own or can be used in combination with the RDP II Classifier to maximize the taxonomic identification rate. Using a set of simulated DNA sequences, we demonstrate that the algorithm performs taxonomic classification with high specificity for sequences as short as 125 base pairs. TUIT is applicable for 16S rRNA gene sequence classification; however, it is not restricted to 16S rRNA sequences. In addition, TUIT may be used as a complementary tool for effective taxonomic classification of nucleotide sequences generated by many current platforms, such as Roche 454 and Illumina. Stand-alone TUIT is available online at http://sourceforge.net/projects/tuit/.

Disulfide by Design 2.0: a web-based tool for disulfide engineering in proteins

BackgroundDisulfide engineering is an important biotechnological tool that has advanced a wide range of research. The introduction of novel disulfide bonds into proteins has been used extensively to improve protein stability, modify functional characteristics, and to assist in the study of protein dynamics. Successful use of this technology is greatly enhanced by software that can predict pairs of residues that will likely form a disulfide bond if mutated to cysteines.ResultsWe had previously developed and distributed software for this purpose: Disulfide by Design (DbD). The original DbD program has been widely used; however, it has a number of limitations including a Windows platform dependency. Here, we introduce Disulfide by Design 2.0 (DbD2), a web-based, platform-independent application that significantly extends functionality, visualization, and analysis capabilities beyond the original program. Among the enhancements to the software is the ability to analyze the B-factor of protein regions involved in predicted disulfide bonds. Importantly, this feature facilitates the identification of potential disulfides that are not only likely to form but are also expected to provide improved thermal stability to the protein.ConclusionsDbD2 provides platform-independent access and significantly extends the original functionality of DbD. A web server hosting DbD2 is provided at http://cptweb.cpt.wayne.edu/DbD2/.

Analysing diversity and community structures usingPCR‐RFLP: a new software application

Restriction fragment length polymorphism tools is an R application which supports a complete workflow of polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), dealing with the problems which accompany analysis when PCR-RFLP is used in diversity studies. Large numbers of different RFLP samples obtained from multiple electrophoresis runs might lead to limitations or misidentifications due to the need for band matching in most existing software applications. Due to the common problem of variation in the density of bands (i.e. distances between bands or visual intensity) in the electropherograms, it is desirable to have options for handling samples with uncertain or faint bands. As a further step in the workflow, scientists often use DNA sequencing to identify individual genotypes, so that the use of specific software to combine these tasks might be helpful. With this background, we here present an application that supports a complete workflow, starting with the analysis of single species samples by PCR-RFLP, to PCR-RFLP genotype identification based on a reference data set and DNA sequencing followed by similarity analysis. RFLPtools is a freely available, platform-independent application which provides analysis functions for DNA fragment molecular weights (e.g. by RFLP analysis), including similarity calculations without the need for band matching. As it is written for the statistical software R, other statistical analyses might also be easily applied.

An efficient simulator of 454 data using configurable statistical models

BackgroundRoche 454 is one of the major 2nd generation sequencing platforms. The particular characteristics of 454 sequence data pose new challenges for bioinformatic analyses, e.g. assembly and alignment search algorithms. Simulation of these data is therefore useful, in order to further assess how bioinformatic applications and algorithms handle 454 data.FindingsWe developed a new application named 454sim for simulation of 454 data at high speed and accuracy. The program is multi-thread capable and is available as C++ source code or pre-compiled binaries. Sequence reads are simulated by 454sim using a set of statistical models for each chemistry. 454sim simulates recorded peak intensities, peak quality deterioration and it calculates quality values. All three generations of the Roche 454 chemistry ('GS20', 'GS FLX' and 'Titanium') are supported and defined in external text files for easy access and tweaking.ConclusionsWe present a new platform independent application named 454sim. 454sim is generally 200 times faster compared to previous programs and it allows for simple adjustments of the statistical models. These improvements make it possible to carry out more complex and rigorous algorithm evaluations in a reasonable time scale.

A Measurable Approach for Access and Control Modeling in SOA

Service oriented architects (SOA) is considered as an extensible, robust and platform independent web application architect. However, problems in security guard for service access remains unresolved especially for the measurable one. we proposed a novel access control model, which we called SACM: Service Access Control Model, specially for SOA. Our model is mainly based on the role access policy, extended with trust authority transition and integration mechanism, to fulfill an extensive and measurable access control modeling approach with Crypto-CCS.

Interfacing neuroVIAS and NEST

Our framework (neuroVIAS) integrates neuroimaging, brain-mapping, neuroanatomic ontologies and tracing-based connectivity data and allows to analyze these data in multiple modalities. Most of the data has been gathered from real brains, such as the information about connections between structures at different levels of resolution. These information include features like strength, inhibition or excitation. It is intended to use the collected data as an input for the simulation of neuronal networks with sophisticated simulation environments like NEST. As a starting point, a graphical user interface in neuroVIAS has been developed, that allows the specification of a simulation according to NEST guidelines based on filtering mechanisms of the rat connectome. neuroVIAS is a platform independent JAVA application allowing the administration of multiple ontologies of different nervous systems. Neurohistological, stereotacticand image processing methods were used to obtain image data at high spatial resolution of a whole Wistar rat brain. Computer vision methods are used to obtain estimations of cells numbers in the mapped brain regions (Fig. ​(Fig.1).1). Additionally, 25000 connectivities were extracted from 420 tracing publications and imported in the neuroVIAS framework (Fig. ​(Fig.2).2). The 5000 neuroanatomic terms are organized hierarchically allowing the definition of scale dependent sets of brain regions for simulation. Additionally, attributes can be defined and assigned to the terms. Two types of attribute definitions are available: a hierarchical approach, where attributes can be organized in a hierarchy and a free configurable table method to define complex parameter sets. These parameters can be used for simulation studies. Using the spatial position of brain regions it is possible to compute distances in the neuronal network and including this information in the network simulation. Figure 1 Overview of a rat brain section. The magnification shows the amygdala with annotations. Cell locations in the cell estimation are assigned to mapped brain regions. Figure 2 a) A hierarchy preserving connectivity visualization of the site-symmetric ontology. b) Magnification of the amygdala with edge bundled connectivities. In this contribution we present the interface that allows the definition of parameters and adaption of new parameters for simulations in NEST. This open framework approach integrating relevant neuroimaging, mapping, ontology, connectivity data and different possibilities to administer brain region dependent sets of parameters for large scale simulations offers the opportunity to analyze dynamics of single regions and region ensembles of a realistic rat brain neuronal network.