Java-based Tool Research Articles

A Bibliometric Review of Type-3 Fuzzy Logic Applications

In this paper, we provide an overview of type-3 fuzzy logic systems (T3FLSs) and their applications in a general way. The contribution of this paper is to analyze and review, in the best way possible, applications in several fields utilizing type-3 fuzzy logic systems. Recently, many algorithms are receiving more and more attention in this area, and for this reason, an overview of this field is important. This article provides an overview of the most important applications in which intelligent computing methods based on T3FLSs are used. The main goal of this paper is to thoroughly explore these applications and identify emerging scientific trends in the adoption of intelligent methods, particularly those involving T3FLSs. To achieve this, we use the VosViewer software to construct and visualize bibliometric networks. VosViewer is a free, Java-based tool designed for analyzing and visualizing bibliometric data. This program is used for the creation of maps of papers, authors, etc., and the development of maps for keywords, countries, research groups, and more.

Application of machine learning-based read-across structure-property relationship (RASPR) as a new tool for predictive modelling: Prediction of power conversion efficiency (PCE) for selected classes of organic dyes in dye-sensitized solar cells (DSSCs).

The application of various in-silico-based approaches for the prediction of various properties of materials has been an effective alternative to experimental methods. Recently, the concepts of Quantitative structure-property relationship (QSPR) and read-across (RA) methods were merged to develop a new emerging chemoinformatic tool: read-across structure-property relationship (RASPR). The RASPR method can be applicable to both large and small datasets as it uses various similarity and error-based measures. It has also been observed that RASPR models tend to have an increased external predictivity compared to the corresponding QSPR models. In this study, we have modeled the power conversion efficiency (PCE) of organic dyes used in dye-sensitized solar cells (DSSCs) by using the quantitative RASPR (q-RASPR) method. We have used relatively larger classes of organic dyes-Phenothiazines (n=207), Porphyrins (n=281), and Triphenylamines (n=229) for the modelling purpose. We have divided each of the datasets into training and test sets in 3 different combinations, and with the training sets we have developed three different QSPR models with structural and physicochemical descriptors and validated them with the corresponding test sets. These corresponding modeled descriptors were used to calculate the RASPR descriptors using a Java-based tool RASAR Descriptor Calculator v2.0 (https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home), and then data fusion was performed by pooling the previously selected structural and physicochemical descriptors with the calculated RASPR descriptors. Further feature selection algorithm was employed to develop the final RASPR PLS models. Here, we also developed different machine learning (ML) models with the descriptors selected in the QSPR PLS and RASPR PLS models, and it was found that models with RASPR descriptors superseded in external predictivity the models with only structural and physicochemical descriptors: RMSEP reduced for phenothiazines from 1.16-1.25 to 1.07-1.18, for porphyrins from 1.60-1.79 to 1.45-1.53, for triphenylamines from 1.27-1.54 to 1.20-1.47.

Design of a multi-epitope-based peptide vaccine against the SARS-CoV-2 Omicron variant using bioinformatics approach

SARS-CoV-2, a member of the coronavirus family, is an RNA virus characterized by a single-stranded genome and is responsible for the development of COVID-19. The emergence of the Omicron variant of SARS-CoV-2 in 2021 marked a significant variation recognized by the World Health Organization. The primary objective of this study is to investigate the spike glycoprotein of the Omicron variant of SARS-CoV-2 and identify potential immunogenic epitopes in order to design multi-epitope vaccine constructs. Among the other major structural proteins of the coronavirus, the spike glycoprotein stands out as the largest. Importantly, individuals who have recovered from SARS-CoV-2 and COVID-19 were found to possess antibodies that target the spike glycoprotein. This article asserts that the vaccine presented in this study has the potential to elicit immune responses against previous variants, including the Omicron variant, as well as future variations. This is attributed to the utilization of a Java-based tool, which facilitated the identification of conserved epitopes with high immunogenicity scores, ensuring their non-toxic and non-allergenic properties. Our analysis provides strong evidence for the conservation of these epitopes across all coronavirus sequences detected in various countries since the beginning of the pandemic. The vaccine was subsequently constructed by integrating the identified conserved epitopes with linkers and adjuvants. The vaccine was subsequently evaluated through computational tests to assess their efficacy and performance. Communicated by Ramaswamy H. Sarma

Rating-Based Recommender System Based on Textual Reviews Using IoT Smart Devices

Recommender system (RS) is a unique type of information clarification system that anticipates the user's evaluation of items from a large pool based on the expectations of a single stakeholder. The proposed system is highly useful for getting expected meaning suggestions and guidance for choosing the proper product using artificial intelligence and IoT (Internet of Things) such as chatbot. The current proposed technique makes it easier for stakeholders to make context-based decisions that are optimal rather than reactive, such as which product to buy, news classification based on high filtering views, highly recommended wanted music to choose, and desired product to choose. Recommendation systems are a critical tool for obtaining verified information and making accurate decisions. As a result, operational efficiency would skyrocket, and the risk to the company that uses a recommender system would plummet. This proposed solution can be used in a variety of applications such as commercial hotels OYO and other hotels, hospitals (GYAN), public administrative applications banks HDFC, and ICICI to address potential questions on the spot using intelligence computing as a recommendation system. The existing RS is considering a few factors such as buying records, classification or clustering items, and user's geographic location. Collaborative filtering algorithms (CFAs) are much more common approaches for cooperating to mesh the respective documents they retrieved from the historical data. CFAs are distinguished in plenty of features that are uncommon from other algorithms. In this existing system classification, precision and efficiency and error rate are statistical measurements that need to be enhanced according to the current need to fit for global requirements. The proposed work deals with enhancing accuracy levels of text reviews with the recommender system while interacting by the numerous users for their domains. The authors implemented the recommender system using a user-based CF method and presented the significance of collaborative filtering on the movie domain with a recommender system. This whole experiment has been implanted using the RapidMiner Java-based tool. Results have been compared with existing algorithms to differentiate the efficiency of the current proposed approach.

A Tool to Automate Student UML diagram Evaluation

Unified modelling language (UML) is the accepted standard and modelling language for modeling in software development process. UML is widely used by most course tutors in teaching modules of software engineering and system analysis and design. Students taking such courses do submit assignments with UML diagrams such as use case, class, sequence, activity and so on. Different versions of such diagrams produced by the students for a given problem have to be assessed by the course tutor which is a challenging and time-consuming task. This paper presents a java-based tool which is developed based on a simple yet effective algorithm developed by the authors that will read student and tutors solution diagrams as inputs and evaluate and grade the diagrams automatically. The output of the tool is the score of the student diagram in respect of lecturer’s final solution. The output is presented in two feedback files, one containing students’ score for the lecturers and the other to be send to the student to note the areas that were incorrect. The tool has been tested and evaluated using a simple and assumed UML class diagram. The result shows that the tool functions effectively and can produce detail feedbacks for both students and tutors. The outcome of this paper contributes towards automating UML diagram evaluations.

Social Internet of Things: vision, challenges, and trends

IoT describes a new world of billions of objects that intelligently communicate and interact with each other. One of the important areas in this field is a new paradigm-Social Internet of Things (SIoT), a new concept of combining social networks with IoT. SIoT is an imitation of social networks between humans and objects. Objects like humans are considered intelligent and social. They create their social network to achieve their common goals, such as improving functionality, performance, and efficiency and satisfying their required services. Our article’s primary purpose is to present a comprehensive review article from the SIoT system to analyze and evaluate the recent works done in this area. Therefore, our study concentrated on the main components of the SIoT (Architecture, Relation Management, Trust Management, web services, and information), features, parameters, and challenges. To gather enough information for better analysis, we have reviewed the articles published between 2011 and December 2019. The strengths and weaknesses of each article are examined, and effective evaluation parameters, approaches, and the most used simulation tools in this field are discussed. For this purpose, we provide a scientific taxonomy for the final SIoT structure based on the academic contributions we have studied. Ultimately we observed that the evaluation parameters are different in each element of the SIoT ecosystem, for example for Relation Management, scalability 29% and navigability 22% are the most concentrated metrics, in Trust Management, accuracy 25%, and resiliency 25% is more important, in the web service process, time 23% and scalability 16% are the most mentioned and finally in information processing, throughput and time 25% are the most investigated factor. Also, Java-based tools like Eclipse has the most percentage in simulation tools in reviewed literature with 28%, and SWIM has 13% of usage for simulation.

NGS‐Integrator: A Tool for Combining Information from Multiple Genome‐Wide NGS Data Tracks Using Minimum Bayes Factors

Genome‐wide studies that generate multiple high‐throughput next‐generation sequencing (NGS) datasets to identify genomic DNA elements for gene transcription require data integration methods to minimize complexity and false‐positive findings. This can involve integration of multiple genome‐wide data generated from same type or different types of high‐throughput NGS techniques. Since several strategies to integrate multiple genome‐wide NGS datasets based on peak calling tools have been developed, these conventional methods are typically applied to individual replicates and not the aggregate data from multiple data.NGS‐integrator, a Java‐based tool, integrates genome‐wide NGS datasets into a single data track for a genome browser based on minimum Bayes Factor (MBF) calculated from the signal‐to‐noise ratio. NGS‐integrator consists of two elements, “Calculator” and “Integrator”. The “Calculator” element calculates the complement of MBF at each genomic position, estimating the median of the noise values across a sliding window straddling the position at which signal value is being calculated. This calculation assumes that the features being detected are relatively sparsely represented along the genome, allowing the median to be representative of the true noise level. The “Integrator” element calculates the joint probability between the multiple NGS data tracks based on the complement of MBF calculated with ‘Calculator’. We used NGS‐integrator to integrate data from three types of data generated in our laboratory in cultured mpkCCD kidney cells, viz. ChIP‐Seq for the transcription factor ELF1, ATAC‐Seq, and ChIP‐Seq for the histone modification H3K27Ac and RNA polymerase II.Support or Funding InformationThe work was supported by the Division of Intramural Research, National Heart, Lung, and Blood Institute projects ZIA‐HL001285 (to MAK) and ZIA‐HL006129 (to MAK). BW was supported by the NHLBI Summer Internship Program (June–August 2018).This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

A Rigorous Framework for Specification, Analysis and Enforcement of Access Control Policies

Access control systems are widely used means for the protection of computing systems. They are defined in terms of access control policies regulating the access to system resources. In this paper, we introduce a formally-defined, fully-implemented framework for specification, analysis and enforcement of attribute-based access control policies. The framework rests on FACPL, a language with a compact, yet expressive, syntax for specification of real-world access control policies and with a rigorously defined denotational semantics. The framework enables the automated verification of properties regarding both the authorisations enforced by single policies and the relationships among multiple policies. Effectiveness and performance of the analysis rely on a semantic-preserving representation of FACPL policies in terms of SMT formulae and on the use of efficient SMT solvers. Our analysis approach explicitly addresses some crucial aspects of policy evaluation, such as missing attributes, erroneous values and obligations, which are instead overlooked in other proposals. The framework is supported by Java-based tools, among which an Eclipse-based IDE offering a tailored development and analysis environment for FACPL policies and a Java library for policy enforcement. We illustrate the framework and its formal ingredients by means of an e-Health case study, while its effectiveness is assessed by means of performance stress tests and experiments on a well-established benchmark.

On the reliability of measurements for a stent positioning simulation system

Background and objectiveComputer aided simulations are useful to support the physician in many steps of the surgical activity, but also in pre-surgical patient classification and in post-surgical diagnosis and treatment decisions. At a broader level, computerized technologies and infrastructures permeate every aspect of the medical activity, from patient management to surgery and patients’ follow up with outcomes analyses. Radiography assisted surgery is often used in hemodynamic surgery to study and support cardio-circulatory stents positioning with the use of radioscopy coupled with contrast liquid injected into the vessels. Computer based surgery instruments (both software and hardware) are used to support clinicians during interventions, e.g., to reduce radioscopy time exposure, to minimize errors and to estimate tissues and organs dimension. In this paper we present the use of a newly developed system which supports physicians during transcatheter percutaneous coronary interventions. MethodsThis paper presents a Java-based tool which acquires images from angiographic equipment during surgery procedures. An high performance image acquisition module has been used and a stent simulation environment module is available to simulate stent positioning and to measure vessels. Operators may acquire images, perform measurements and simulations on DICOM images. We performed tests off-line on images to validate the reliability of the tool. Real cases and on line tests have been performed by operators showing the robustness of the system to be used in surgery room. The system has been integrated in the surgery room control panel and allows (i) vascular images acquisition, (ii) vessels and coronary measurement and (iii) stent positioning simulations. The tool is an aid for the physician for both measuring tissues or lesions and for defining the stent's geometry and position before its deployment in the patient's vessels. ResultsExperiments have been performed on lesions and vessels by different operators using the system and an available commercial system, on both real patient cases and synthetic images designed with a CAD. It has been tested on 76 images extracted from real angiography cases and on 11 synthetic images created by using CAD. Five different operators performed 2128 measurements for the real cases images (for both Cartesio and CAAS tools) and 112 for the synthetic dataset. Results show the efficacy of the system compared with the commercial one by means of several statistical tests. ConclusionsThe proposed system is a reliable tool for hemodynamic surgery and can be used both for decision support in stent positioning procedures and for didactic training of new physicians.

Two Faces of the Framework for Analysis and Prediction, Part 2 - Research

Continuing Two Faces of the Framework for Analysis and Prediction, Part 1 - Education, this article overviews the successful applications of the Framework for Analysis and Prediction (FAP) – a Java-based tool dedicated to time-series analysis – in research, highlighting the influence applications had on subsequent development and enhancements of the FAP software. Research applications include applications in data mining (development of a new time-series representation and various interactions between time-series distance measures and classification) and multidisciplinary research (in psychology, medicine, emotion recognition and agent-based distributed computing). DOI: http://dx.doi.org/10.5755/j01.itc.47.3.18747

Two Faces of the Framework for Analysis and Prediction, Part 1 - Education

With the ever-increasing amounts of data being generated in all walks of life and work, data analysis tools are gaining in importance and becoming essential in many application scenarios, including commerce, healthcare, research, and education. One important type of data are time series, which can be viewed as chronologically arranged arrays of numerical values that describe a sequences of quantitative observations (e.g. in medical examinations, scientific and engineering experiments, etc.). In this article we survey the successful applications of the Framework for Analysis and Prediction (FAP) – a Java-based tool dedicated to time-series analysis – in the area of education. Its utilization in this domain spans the development of several graphical user interfaces, as well as student projects illustrating and enhancing the capabilities of the system in the domains of time-series reconstruction, medicine (diagnosis), finance (stock value prediction) and psychology.DOI: http://dx.doi.org/10.5755/j01.itc.47.2.18746

A Novel Color Analysis Technique for Differentiation of Mix Grass Cover under Shade and without Shade in Green Infrastructures

Abstract Color analysis was found to be a low-cost and noninvasive technique to distinguish plant and soil, crop and weed, living and dead plant, diseased and healthy leaves, and human and plant in field and automatic seedling transplantation systems. However, color analysis was rarely utilized to differentiate various types of shade by grass cover. The main objective of this study was to quantify and differentiate mix grass cover under shade and light in a green infrastructure. The spatial heterogeneity of mix grass species in the selected site was categorized into three different portions, i.e., (1) mix grass cover under tree shade (MUT); (2) mix grass cover under self-shade (MUS); and (3) mix grass cover without shade (MWS). Field monitoring was conducted for about six months to validate the color analysis technique. A java-based image analysis tool, ImageJ, was used for color analysis. Lab color space was adopted for the present study, which identifies the spatial heterogeneity of mix grass cover based on lightness variation of green color. L describes lightness, and a and b represent the color opponents green–red and blue–yellow. ImageJ categorizes L, a, and b using 256 segments on a scale varying between 0 and 255. The range of L values for MUT, MUS, and MWS were found to lie within 20–91, 92–162, and 162–233, respectively. Ranges of a and b values were found to be 0–134 and 154–255, respectively, for the three categories of mix grass. Proportions of MUT, MUS, and MWS were found to vary within 0.2–3.0 %, 0–53 %, and 12–49 %, respectively. Variation in MUT and MWS proportions was found to be consistent with change in rainfall depth during the dry period. However, MUT and MWS were found to change with respect to shoot growth rate during the wet period. The MUS proportion variation trend was not found to be consistent with rainfall depth or shoot growth during the wet period.

Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

A Comprehensive Image Steganography Tool using LSB Scheme

As a consequence of the fact, transmitting data has been fast and easy these days due to the development of the Internet. Where internet is the most important medium for confidential and non-confidential communications. Security is the major matter for these communications and steganography is the art of hiding and transmitting secret messages through carriers without being exposed. This paper presents a secured model for communication using image steganography. The main concern is to create a Java-based tool called IMStego that hides information in images using Least Significant Bit (LSB) algorithm (1-LSB) and modified Least Significant one Bit algorithm, i.e. Least Significant 2 Bits algorithm (2-LSB). IMStego is a more comprehensive security utility where it provides user-friendly functionality with interactive graphical user interface and integrated navigation capabilities. It provides the user with two operations, which are hiding secret data into images and extracting hidden data from images using 1-LSB or 2LSB algorithm. IMStego tool hides secrete information in color static images with formats BMP and PNG.

A Modular Simulation Tool of an Orchestrator for Allocating Virtual Resources in SDN

 Abstract—Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) are technologies for enabling innovative network architectures. Nevertheless, a fundamental problem in instantiation of Virtual Networks (VNs), performed by NFV, is an optimal allocation of resources offered by one or more SDN domain networks. The process of instantiation of VNs is performed in several phases, including splitting and mapping algorithms. For each one of these phases, researchers have developed algorithms, being possible to obtain different results combining them. This paper introduces a modular and flexible graphical discrete event simulation tool for solving the complete virtual resource allocation in SDN domain networks problem. A Java-based tool has been developed to integrate existing and future algorithms related to each phase of the process. The simulator is a test-bed in which researchers can select the appropriate algorithm in each phase and display the results in a graphical form, while obtaining a performance evaluation of the selected and proposed algorithms.

Monitoring method call sequences using annotations

In this paper we introduce JMSeq, a Java-based tool for monitoring sequences of method calls. JMSeq provides a simple but expressive language to specify the observables of a Java program in terms of sequences of possibly nested method calls. Similar to many monitoring-oriented environments, verification in JMSeq is done at runtime; unlike all other approaches based on aspect-oriented programming, JMSeq uses code annotation rather than instrumentation, and therefore is suitable for component-based software verification.

Evaluating genome architecture of a complex region via generalized bipartite matching

With the remarkable development in inexpensive sequencing technologies and supporting computational tools, we have the promise of medicine being personalized by knowledge of the individual genome. Current technologies provide high throughput, but short reads. Reconstruction of the donor genome is based either on de novo assembly of the (short) reads, or on mapping donor reads to a standard reference. While such techniques demonstrate high success rates for inferring 'simple' genomic segments, they are confounded by segments with complex duplication patterns, including regions of direct medical relevance, like the HLA and the KIR regions.In this work, we address this problem with a method for assessing the quality of a predicted genome sequence for complex regions of the genome. This method combines two natural types of evidence: sequence similarity of the mapped reads to the predicted donor genome, and distribution of reads across the predicted genome. We define a new scoring function for read-to-genome matchings, which penalizes for sequence dissimilarities and deviations from expected read location distribution, and present an efficient algorithm for finding matchings that minimize the penalty. The algorithm is based on a formal problem, first defined in this paper, called Coverage Sensitive many-to-many min-cost bipartite Matching (CSM). This new problem variant generalizes the standard (one-to-one) weighted bipartite matching problem, and can be solved using network flows. The resulting Java-based tool, called SAGE (Scoring function for Assembled GEnomes), is freely available upon request. We demonstrate over simulated data that SAGE can be used to infer correct haplotypes of the highly repetitive KIR region on the Human chromosome 19.

EScience Infrastructure for sharing neuroimaging data and running validated analysis pipelines on a high performance cloud

eScience Infrastructure for sharing neuroimaging data and running validated analysis pipelines on a high performance cloud

EDUCACIÓN A DISTANCIA DEL PROFESORADO DE CIENCIAS EN EL DESARROLLO DE LABORATORIOS VIRTUALES

Two distance courses on the implementation of interactive virtual-labs are presented in this manuscript. Their audience is Science teachers who wish to make efficient use of interactive simulation in their classes. The first course, entitled “Laboratorios virtuales interactivos: un enfoque creativo para la ensenanza de las Ciencias en el aula y a traves de Internet”, is part of the Continuing Education Program offered by UNED, the National Open University of Spain. The second course is a concise version of the first one. It is a free online course, written in English language, entitled “Virtual-lab implementation with Ejs”. This web-based course got the second award in the “Best Designed Course” competition of the 6th International Conference on Virtual University (December 2005, Bratislava, Slovak Republic). The simulation environment used to implement the virtual-labs is Easy Java Simulations (Ejs): a freeware, open source, Java-based tool conceived to be used by people with little programming skills. Online course website: http://www.euclides.dia.uned.es/simulab-pfp.

A Cloud Computing System to Quickly Implement New Microarray Data Pre-processing Methods

Background: Pre-processing, including normalization of raw microarray data is crucial to microarray-related data analysis. It takes time and effort to build newly-developed algorithms into commercial software or locally developed systems. While most new algorithms emerge in the form of sharable R packages, it can be difficult for many biologists to apply them as soon as they are available. Currently, we rely on statisticians and experienced programmers to develop and implement code to access those R packages. Therefore, we need a robust procedure to quickly implement pre-processing methods as they appear. The newly emerging cloud computing concept has directed us toward a new way for providing an easily accessible service to the biologists without requiring them to have any programming knowledge in R. Results: Based on our earlier Java-based software tool JavaStat, we developed an internet based application prototype to upload data and carry out pre-processing applications that include normalization, statistical analyses and plots. More im-portantly, R packages, e. g., for newly-developed normalization methods, and GC-robust multichip algorithm (RMA) for exon arrays, can be easily incorporated into the system with limited inputs from a biologist or a programmer. The data are stored in the cloud and the R code runs on server. Conclusion: The newly emerged cloud computing concept provides us a new way to provide an easily accessible and up-to-date service to biologists, as evidenced by our JavaStat system to incorporate new pre-processing package as they ap-pear. Users can access the application with a newly incorporated module through the Web. We expect this and other simi-lar systems greatly decrease turn-around time, improve accessibility of newly developed R model for pre-processing algo-rithms.