A software service supporting software quality forecasting

Software repositories such as source control, defect tracking systems and project management tools, are used to support the progress of software projects. The exploitation of such data with techniques like forecasting is becoming an increasing need in several domains to support decision-making processes. However, although there exist several statistical tools and languages supporting forecasting, there is a lack of friendly approaches that enable practitioners to exploit the advantages of creating and using such models in their dashboard tools. Therefore, we have developed a modular and flexible forecasting service allowing the interconnection with different kinds of databases/data repositories for creating and exploiting forecasting models based on methods like ARIMA or ETS. The service is open source software, has been developed in Java and R and exposes its functionalities through a REST API. Architecture details are provided, along with functionalities’ description and an example of its use for software quality forecasting.Peer ReviewedPostprint (author's final draft

Outline of the Finnish system of certified carbon footprints of food products

The basic structure of a system called Certified Footprints of Products (CFP system) is outlined in this discussion paper. The CFP system could produce strict and reliable data needed for generating product-oriented carbon footprints in Finland. Central parts of the CFP system are a national CFP programme, product category rules (PCRs), a chain or actor-wise monitoring plan, validation of the monitoring plan, and reporting and verification of data, and an ICT-system to support data sharing. The system is designed around activity-based monitoring data, and every actor would be responsible for data on its own activities. Linkages to existing environmental management systems are taken into account. The CFP system is still just a theoretical structure. It needs further development prior to full-scale introduction. For the food sector, a new architecture for data acquisition and quality assurance, development of existing mechanisms and consolidation of them in the CFP system are needed. Additional research is needed regarding emissions from agricultural production

A Cloud-based Framework for Quality Assurance and Enhancement as a Service (QAEaaS) for Universities with Blended Learning Approach

The dynamic and multi-dimensional quality assurance process for Saudi higher education institutes under the National Commission for Academic Accreditation and Assessment (NCAAA) demands an integrated framework for management and support of internal quality reviews and evidence-based self -studies in a cost-effective way. Due to cross-institutional involvement, quality assurance compliance with NCAAA standards is even more challenging for institutes offering courses with blended learning paradigm in multiple campuses. This papers proposes a Cloud-based framework to realize Quality Assurance and Enhancement as a Service (QAEaaS) to facilitate the internal quality reviews by providing efficient data management and effective communication for different stakeholders. Architecture of the proposed framework is described with respective features to cope with the identified quality assurance challenges and issues faced by the Saudi higher education institutes

SIDE – teaching support information system

The success of any information system in any area can be assessed by the voluntary accession of users. In an institution where there is a single system available to the users, this evaluation has to be done through user surveys. SIDE is a portal based on information systems architecture to support teaching, academic management of courses and the learning process, in order to support the needs of integration of information flows in several university information systems. This portal, which is in operation at the University of Trás-os-Montes e Alto Douro since 2002, allows data management coming from the operation of courses, providing to the management entities one platform to support executive and decision support. This portal proved to be an architectural solution that meets the needs of the institution where it was implemented. The longevity of its use as the main information system to support teaching in the institution proves that. However these facts are not enough to conclude about the quality of the system and the relationship with the users of the services they utilize. In order to conclude about this we proceeded to carry out an opinion survey in order to get some feedback about the usability and quality of these same services. The surveys had a good participation in terms of number of people and that allowed us to take what good conclusions

Distributed sensor architecture for intelligent control that supports quality of control and quality of service

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.The study described in this paper is a part of the coordinated project COBAMI: Mission-based Hierarchical Control. Education and Science Department Spanish Government. CICYT: MICINN: DPI2011-28507-C02-01/02 and project "Real time distributed control systems" of the Support Program for Research and Development 2012 UPV (PAID-06-12).Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE.; Simarro Fernández, R.; Benet Gilabert, G. (2015). Distributed sensor architecture for intelligent control that supports quality of control and quality of service. Sensors. 15(3):4700-4733. https://doi.org/10.3390/s150304700S4700473315

Analysis and Visualization of Urban Emission Measurements in Smart Cities

Cities worldwide aim to reduce their greenhouse gas emissions and improve air quality for their citizens. Therefore, there is a need to implement smart city approaches to monitor, model, and understand local emissions to better guide these actions. We present our approach that deploys a number of low-cost sensors through a wireless Internet of Things (IoT) backbone and is thus capable of collecting high-granular data. Based on a flexible architecture, we built an ecosystem of data management and data analytics including processing, integration, analysis, and visualization as well as decision-support systems for cities to better understand their emissions. Our prototype system has so far been tested in two Scandinavian cities. We present this system and demonstrate how to collect, integrate, analyze, and visualize real-time air quality data

A modular multipurpose, parameter centered electronic health record architecture

Health Information Technology is playing a key role in healthcare. Specifically, the use of electronic health records has been found to bring about most significant improvements in healthcare quality, mainly as relates to patient management, healthcare delivery and research support. Health record systems adoption has been promoted in many countries to support efficient, high quality integrated healthcare. The objective of this work is the implementation of an Electronic Health Record system based on a relational database. The system architecture is modular and based on the concentration of specific pathology related parameters in one module, therefore the system can be easily applied to different pathologies. Several examples of its application are described. It is intended to extend the system integrating genomic data

Multivariate data-driven decision guidance for clinical scientists

Clinical decision-support is gaining widespread attention as medical institutions and governing bodies turn towards utilising better information management for effective and efficient healthcare delivery and quality assured outcomes. Amass of data across all stages, from disease diagnosis to palliative care, is further indication of the opportunities and challenges created for effective data management, analysis, prediction and optimization techniques as parts of knowledge management in clinical environments. A Data-driven Decision Guidance Management System (DD-DGMS) architecture can encompass solutions into a single closed-loop integrated platform to empower clinical scientists to seamlessly explore a multivariate data space in search of novel patterns and correlations to inform their research and practice. The paper describes the components of such an architecture, which includes a robust data warehouse as an infrastructure for comprehensive clinical knowledge management. The proposed DD-DGMS architecture incorporates the dynamic dimensional data model as its elemental core. Given the heterogeneous nature of clinical contexts and corresponding data, the dimensional data model presents itself as an adaptive model that facilitates knowledge discovery, distribution and application, which is essential for clinical decision support. The paper reports on a trial of the DD-DGMS system prototype conducted on diabetes screening data which further establishes the relevance of the proposed architecture to a clinical context.E

Designing Business Intelligence Dashboards to Support Decision-Making in a Fishery Business

Accurate assessment and thorough analysis of managerial performance are essential in obtaining enhanced business performance. A real-time monitoring system is necessary to support the decision-making process. This study aims to design a business intelligence dashboard containing real-time monitoring of water quality to support the decision-making of the management team of an agribusiness company. Four steps were used in designing the business intelligence (BI) dashboard: (1) scope and plan, (2) analyze and define, (3) architect and design, and (4) build, test, and refine. The study started with determining the scope and plan for developing the BI dashboard to monitor the water pond’s quality in real time. The requirements of system input and output were identified in the analyze and define phase. The data warehouse model and design visualization regarding the BI dashboard were determined in the architect and design step. The system's architecture was analyzed in the final step, build and test. Three months of data collection and interviews with the management team of the fishery company were performed to support each step in BI design. This study’s outcome is a BI dashboard providing real-time monitoring that supports the management team's decision-making process. This study still considers two water quality measures; therefore, future research can be conducted using other measures. Future research can also be performed on another agribusiness company to support the decision-making process and increase competitiveness