Antarctic Mapping Tools for Matlab

PurposeThe purpose of this paper Computing is a recent emerging cloud model that affords clients limitless facilities, lowers the rate of customer storing and computation and progresses the ease of use, leading to a surge in the number of enterprises and individuals storing data in the cloud. Cloud services are used by various organizations (education, medical and commercial) to store their data. In the health-care industry, for example, patient medical data is outsourced to a cloud server. Instead of relying onmedical service providers, clients can access theirmedical data over the cloud.Design/methodology/approachThis section explains the proposed cloud-based health-care system for secure data storage and access control called hash-based ciphertext policy attribute-based encryption with signature (hCP-ABES). It provides access control with finer granularity, security, authentication and user confidentiality of medical data. It enhances ciphertext-policy attribute-based encryption (CP-ABE) with hashing, encryption and signature. The proposed architecture includes protection mechanisms to guarantee that health-care and medical information can be securely exchanged between health systems via the cloud. Figure 2 depicts the proposed work's architectural design.FindingsFor health-care-related applications, safe contact with common documents hosted on a cloud server is becoming increasingly important. However, there are numerous constraints to designing an effective and safe data access method, including cloud server performance, a high number of data users and various security requirements. This work adds hashing and signature to the classic CP-ABE technique. It protects the confidentiality of health-care data while also allowing for fine-grained access control. According to an analysis of security needs, this work fulfills the privacy and integrity of health information using federated learning.Originality/valueThe Internet of Things (IoT) technology and smart diagnostic implants have enhanced health-care systems by allowing for remote access and screening of patients’ health issues at any time and from any location. Medical IoT devices monitor patients’ health status and combine this information into medical records, which are then transferred to the cloud and viewed by health providers for decision-making. However, when it comes to information transfer, the security and secrecy of electronic health records become a major concern. This work offers effective data storage and access control for a smart healthcare system to protect confidentiality. CP-ABE ensures data confidentiality and also allows control on data access at a finer level. Furthermore, it allows owners to set up a dynamic patients health data sharing policy under the cloud layer. hCP-ABES proposed fine-grained data access, security, authentication and user privacy of medical data. This paper enhances CP-ABE with hashing, encryption and signature. The proposed method has been evaluated, and the results signify that the proposed hCP-ABES is feasible compared to other access control schemes using federated learning.

Summary of United States Human Proteome Organisation (HUPO) Symposium Entitled “Standardized Clinical Proteomics Platforms”

Location‐only and use‐availability data: analysis methods converge

Raw data queries during data-intensive parallel workflow execution

Focus on software

A system based on a network of engineering workstations has been developed for data acquisition and analysis in multichannel cardiac mapping. The system consists of a microcomputer-controlled data-acquisition front end, the network of workstations, and the necessary software for display and analysis of cardiac activations. The system has been designed for ease of use in experimental and clinical studies by investigators with little computer expertise. The expandability of the system allows the accommodation of more users without major increases in cost and complexity. The network consists of monochrome, color, and high-performance graphics workstations at several campus locations. The compatibility of nodes allows the efficient and convenient sharing of software and data among groups; all of the stations have the ability to run the suite of data analysis programs. This network has proved to be extremely useful in support of research efforts, offering extensive shared file storage and software access. Each user has dedicated processing power and bit-mapped graphics capability, allowing data analysis and display program development, as well as document preparation, with little impact on others. >

The interpretation of electrochemical noise (EN) data has long been under discussion. Throughout the years, many data analysis techniques have been proposed for this purpose. As a starting point, procedures and parameters that enable identification of, or discrimination between, general and localized corrosion processes through EN are critically discussed. It is important to consider which type of information is required for a specific application. EN can be used to determine the barrier properties of a protective coating, and can therefore provide quantitative information about corrosion processes, although its most interesting ability is to provide information on corrosion characteristics. EN signals consist of a direct current (DC) component, or trend, with superimposed fluctuations. In electrochemical potential noise (EPN), this DC component represents the open corrosion potential (OCP) of the system under study. In electrochemical current noise (ECN), the DC component can e.g. be generated by electrode asymmetry. Any DC drift should be carefully removed prior to further data analysis. A procedure is introduced to accurately define the DC drift in EN signals using either of two time-frequency data analysis techniques: discrete wavelet transform (DWT) or empirical mode decomposition (EMD). Consistent and reliable information can be obtained from EN data when a data analysis procedure is selected that on the one hand has a high discrimination ability and on the other hand yields a descriptive parameter that is directly associated to the underlying physico- chemical process. Preferably, the information is obtained without the need for subjective a-priori limitations or assumptions concerning the nature of the process under investigation. These requirements are met by the Hilbert-Huang transform, which is based on the EMD. The result is a Hilbert spectrum in which local frequency information, so-called instantaneous frequencies, of EN signals, is visualized. The use of Hilbert spectra for the characterization of EN data in corrosion studies is introduced, based on the (general and localized) corrosion characteristics of carbon steel and stainless steel AISI304. A highly detailed decomposition of the original ECN and EPN data is provided in time and frequency simultaneously. This allows distinguishing between different corrosion characteristics based on their EN signals. Hilbert spectra also provide the possibility to analyze only transients present in the EN signals that originate from localized corrosion processes on AISI304. Initial identification of transients is based on the transient shape. Analysis of instantaneous frequency information present in these transients enables improved differentiation between corrosion characteristics as compared to data analysis using Hilbert spectra or energy distribution plots (determined from DWT) without transient analysis. The applicability of transient analysis through Hilbert spectra of ECN signals is further investigated for Ce-based inhibition of aluminium alloy AA2024-T3 and for detection and identification of microbiologically influenced corrosion (MIC). Transient analysis allows detection of changes in corrosion characteristics, i.e. the evolution of corrosion inhibition of AA2024-T3 by Ce-ions, with time. The initial procedure of transient detection is further developed, comprising of automatic detection of specific areas of interest in Hilbert spectra between 10E-1 Hz and 1 Hz, corresponding with the occurrence of transients in the respective ECN signals. Regarding the detection of MIC, together with monitoring of the OCP and microscopic observations, the development of ECN transients generated by localized corrosion processes could be attributed to the presence and activity of sulphate-reducing bacteria. These transients are related to the existence of pits in the carbon steel surface, underneath the attached biofilm. Finally, practical aspects and configurations for electrochemical noise measurements (ENM) are discussed. ENM can be applied in a hand-held solution, or for permanent monitoring. Analogous to the selection of the appropriate data analysis procedure to obtain the information of interest, it is important to consider the required application to select the most suitable configuration. ENM is a potentially interesting technique because of its non-intrusive nature, the robust sensor configurations, the ability to identify localized corrosion processes and ease of use. The most complicated aspect of ENM is the interpretation of the EN signals, for which the data analysis procedure can be fully automated if required.

Structuring of ecological data sets by methods of correlation and cluster analysis

The objectives of this research was to investigate : (a) the effect of ease of use to customer satisfaction, (b) the effect of web design to customer satisfaction, (c) the effect of responsiveness to customer satisfaction, (d) the effect of personalization to customer satisfaction, (e) the effect of assurance to customer satisfaction, (f) the effect of customer satisfaction to WOM , (g) the effect of customer satisfaction to intent , (h) the effect of customer satisfaction to trust . The design of this research applies a survey toward unit of analysis on website of Hotel Grand Hyatt Jakarta to interview the customers for testing hypothesis. Meanwhile the required data consist of nine variables; ease of use , web- desig n , responsiveness , personalization , assurance , customer satisfaction, WOM , intent and trust . The aggregate numbers of customer being respondent of the study are 1 75 . Data analysis used in this research was using Structural Equation Modelling (SEM) runs by AMOS 7.0 as software. The result of this research conclude that variable of ease of use , web desig n , responsiveness , personalization , and assurance attribute s had a positive effect to customer satisfaction, and variable customer satisfaction had positive effect to Customer loyalty’s dimensions, which are WOM , intent and trust. Keywords ; Perceived Quality, Customer Satisfaction, Customer Loyalty

A focus group organised by the Drug Safety Research Unit (DSRU) International Working Group (IWG) on New Developments in Pharmacovigilance discussed current challenges and opportunities in pharmacovigilance (PV), emphasising the need for a multimodal approach in data analysis and accessibility of diverse data sources for drug safety surveillance. Nine participants, selected purposefully for their multisectoral expertise in PV, discussed the value of various data types, including data from clinical trials and real-world data (RWD), each offering distinct strengths and limitations. Key challenges identified included data standardisation, quality variability, technological barriers and ethical concerns, particularly with data derived from social media. Emerging tools such as knowledge graphs were highlighted for their potential to enhance data integration and signal detection, however further research is required. The group also addressed disparities in data access, with particular attention to regulatory restrictions, limited infrastructure in low-resource settings and restricted access to industry-held data. Proposed solutions included fostering greater data transparency, establishing secure data-sharing platforms and forming collaborative consortia to facilitate responsible and ethical data use. Overall, the discussion underscored the need for improved integration, access and methodological rigour to strengthen PV practices and enhance global drug safety monitoring.

Machine learning for Big Data analytics in plants.

Reactome (http://www.reactome.org) is an open-source, expert-authored, peer-reviewed, manually curated database of reactions, pathways and biological processes. We provide an intuitive web-based user interface to pathway knowledge and a suite of data analysis tools. The Pathway Browser is a Systems Biology Graphical Notation-like visualization system that supports manual navigation of pathways by zooming, scrolling and event highlighting, and that exploits PSI Common Query Interface web services to overlay pathways with molecular interaction data from the Reactome Functional Interaction Network and interaction databases such as IntAct, ChEMBL and BioGRID. Pathway and expression analysis tools employ web services to provide ID mapping, pathway assignment and over-representation analysis of user-supplied data sets. By applying Ensembl Compara to curated human proteins and reactions, Reactome generates pathway inferences for 20 other species. The Species Comparison tool provides a summary of results for each of these species as a table showing numbers of orthologous proteins found by pathway from which users can navigate to inferred details for specific proteins and reactions. Reactome's diverse pathway knowledge and suite of data analysis tools provide a platform for data mining, modeling and analysis of large-scale proteomics data sets. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 8).

This research aims was to measure and analyze user acceptance of Sistem Informasi Koperasi (Siskop) in Koperasi Karyawan Budi Setia Jakarta, using Technology Acceptance Model (TAM). This research is quantitative research. Meanwhile, according to the the characteristics of the problem, this research included in exploratory research, descriptive research, and explanatory research. The data used in this research are primary data and secondary data, collected using several data collection techniques, such as observation, questionnaires, document review, and literature review. The variables in this research are independent variables; perceived ease of use - PEOU, intervening variables; perceived of usefullness - PU, attitude toward using - ATU, and behavioral intention to use - BIU, and the dependent variable; actual use - AU. Processing and analysis of data in this research was using descriptive statistics analysis and simple linear regression analysis, which done by the support of the Application SPSS version 21 for Windows. The results of this research are as follows 1) perceived ease of use have given positive and significant influence to perceived usefulness and attitude toward using Siskop; 2) perceived usefulness Siskop given positive and significant influence to attitude toward using Siskop, behavioral intention to use, and actual Siskop use; 3) attitude towards using Siskop positive and significant influence to behavioral intention to use Siskop. However 4) behavioral intention to use Siskop did not has a signicant influences to actual Siskop use.

Analysis of raw volume data generated from different scanning technologies faces a variety of challenges, related to search, pattern recognition, spatial understanding, quantitative estimation, and shape description. In a previous study, we found that the Volume Cracker (VC) 3D interaction (3DI) technique mitigated some of these problems, but this result was from a tethered glove-based system with users analyzing simulated data. Here, we redesigned the VC by using untethered bare-hand interaction with real volume datasets, with a broader aim of adoption of this technique in research labs. We developed symmetric and asymmetric interfaces for the Bare-Hand Volume Cracker (BHVC) through design iterations with a biomechanics scientist. We evaluated our asymmetric BHVC technique against standard 2D and widely used 3D interaction techniques with experts analyzing scanned beetle datasets. We found that our BHVC design significantly outperformed the other two techniques. This study contributes a practical 3DI design for scientists, documents lessons learned while redesigning for bare-hand trackers, and provides evidence suggesting that 3D interaction could improve volume data analysis for a variety of visual analysis tasks. Our contribution is in the realm of 3D user interfaces tightly integrated with visualization, for improving the effectiveness of visual analysis of volume datasets. Based on our experience, we also provide some insights into hardware-agnostic principles for design of effective interaction techniques.

This study aims to analyze the ease of use of e-hailing applications in Padang City using the Technology Acceptance Model approach. The population in the study were people living in Padang City who had the E-Hailing Application on their mobile phones and the number of samples in this study was 280 respondents. The research method used was quantitative with data collection through online questionnaires. Data analysis was carried out using SmartPLS 4.0.9.9 software. The results of this study indicate that: (1) Perceived Ease of Use has a positive and significant effect on Perceived Usefulness. (2) Perceived Usefulness has a positive and significant effect on Behavioral Intention to use. (3) Perceived Ease of Use has a positive and significant effect on Behavioral Intention to use. (4) Social Influence has a positive and significant effect on Behavioral Intention to use. This study concludes that benefits, ease of use, and social influence are important factors in driving the adoption of e-hailing services. These results can be a basis for application developers and policy makers in designing strategies that are more adaptive to local user needs and behavior.