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Publications

2018

Process Approach for Information Systems in Health Care: A Systematic Review and PRISMA Method

Authors
Guetibi, S; El Hammoumi, M; Brito, AC;

Publication
PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND INFORMATION MANAGEMENT (ICSIM 2018) / WORKSHOP 2018 INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (ICBDSC 2018)

Abstract
Hospital Information System is the most fragile component of the health care system in the countries in development process. The modernization of the health care system does not integrate a rigid reflection on the installation of these tools into hospitals, which remain foreign with the strategies of these countries. The main objective of this research is to present a systematic review on the relationship between process approach and continuous improvement with the development and continuity of hospital information systems. Hospital Information System and its sustainability are key factors for the functioning of services in Hospital Institutions which requires principles respect of quality management as the process approach among others. The main question to be treated in this paper is " Which reasons have been given for the views that the process approach is or isn't helping to have and give a Hospital Information System in continuous development?", in order to contribute to the systematization of knowledge in this area, the main objective of this research is to present a systematic review on the relationship between process approach and continuous improvement with the development and continuity of hospital information systems. The systematic review methodology was the PRISMA Statement (R), the search granted to find 7735 based on defined key-words, and after a preliminary examination, according to the exclusion conditions and the eligibility criteria 20 papers were considered relevant to a more detailed study. After an analysis of all relevant documents we have tried to reveal the important gap, which we will try to explore more in future investigations.

2018

Automatic Identification of Pollen in Microscopic Images

Authors
Santos, EMDS; Marcal, ARS;

Publication
VIPIMAGE 2017

Abstract
A system for the identification of pollen grains in bright-field microscopic images is presented in this work. The system is based on segmentation of raw images and binary classification for 3 types of pollen grain. The segmentation method developed tackles a major difficulty of the problem: the existence of clustered pollen grains in the initial binary images. Two different SVM classification kernels are compared to identify the 3 pollen types. The method presented in this paper is able to provide a good estimate of the number of pollen grains of Olea Europea (relative error of 1.3%) in microscopic images. For the two others pollen types tested (Corylus and Quercus), the results were not as good (relative errors of 14.5% and 20.3%, respectively).

2018

Modeling lean manufacturing success

Authors
Ghobakhloo, M; Fathi, M; Fontes, DBMM; Ching, NT;

Publication
JOURNAL OF MODELLING IN MANAGEMENT

Abstract
Purpose The purpose of this study is to contribute to the existing knowledge about the process of achieving Lean Manufacturing (LM) success. Design/methodology/approach This study uses interpretive structural modeling and captures the opinions of a group of LM experts from a world-class Japanese automobile manufacturer, to map the interrelationships among potential determinants of LM success. This study further uses the data from a survey of 122 leading automobile part manufacturers by performing structural equation modeling to empirically test the research model proposed. Findings Management support and commitment, financial resources availability, information technology competence for LM, human resources management, production process simplicity, supportive culture and supply chain-wide integration are the key determinants that directly or indirectly determine the level of achievement of LM success. Research limitations/implications The determinants of LM success as experienced by Asian automobile manufacturers might be different from determinants of LM success as experienced by Western automobile manufacturers. An interesting direction for future research would be to capture the experts' inputs from Western automobile manufacturers to complement the findings of this study. Practical implications The practical contribution of this study lays in the development of linkages among various LM success determinants. Utility of the proposed interpretive structural modeling and structural equation modeling methodologies imposing order, direction and significance of the relationships among elements of LM success assumes considerable value to the decision-makers and LM practitioners. Originality/value Building on opinions of a group of LM experts and a case study of leading auto part manufacturers, the present study strives to model the success of LM, a topic that has received little attention to date.

2018

CENTERIS 2018 - International Conference on ENTERprise Information Systems / ProjMAN 2018 - International Conference on Project MANagement / HCist 2018 - International Conference on Health and Social Care Information Systems and Technologies 2018, Lisbon, Portugal

Authors
Quintela Varajão, JE; Cruz Cunha, MM; Martinho, R; Rijo, R; Peres, E;

Publication
CENTERIS/ProjMAN/HCist

Abstract

2018

Global-Local View: Scalable Consistency for Concurrent Data Types

Authors
Akkoorath, DD; Brandão, J; Bieniusa, A; Baquero, C;

Publication
Euro-Par

Abstract
Concurrent linearizable access to shared objects can be prohibitively expensive in a high contention workload. Many applications apply ad-hoc techniques to eliminate the need for synchronous atomic updates, which may result in non-linearizable implementations. We propose a new model which leverages such patterns for concurrent access to objects in a shared memory system. In this model, each thread maintains different views on the shared object: a thread-local view and a global view. As the thread-local view is not shared, it can be updated without incurring synchronization costs. These local updates become visible to other threads only after the thread-local view is merged with the global view. This enables better performance at the expense of linearizability. We discuss the design of several datatypes and evaluate their performance and scalability compared to linearizable implementations.

2018

Detection of BCG bacteria using a magnetoresistive biosensor: A step towards a fully electronic platform for tuberculosis point-of-care detection

Authors
Barroso, TG; Martins, RC; Fernandes, E; Cardoso, S; Rivas, J; Freitas, PP;

Publication
BIOSENSORS & BIOELECTRONICS

Abstract
Tuberculosis is one of the major public health concerns. This highly contagious disease affects more than 10.4 million people, being a leading cause of morbidity by infection. Tuberculosis is diagnosed at the point-of-care by the Ziehl-Neelsen sputum smear microscopy test. Ziehl-Neelsen is laborious, prone to human error and infection risk, with a limit of detection of 10(4) cells/mL. In resource-poor nations, a more practical test, with lower detection limit, is paramount. This work uses a magnetoresistive biosensor to detect BCG bacteria for tuberculosis diagnosis. Herein we report: i) nanoparticle assembly method and specificity for tuberculosis detection; ii) demonstration of proportionality between BCG cell concentration and magnetoresistive voltage signal; application of multiplicative signal correction for systematic effects removal; iv) investigation of calibration effectiveness using chemometrics methods; and v) comparison with state-of-the-art point-of-care tuberculosis biosensors. Results present a clear correspondence between voltage signal and cell concentration. Multiplicative signal correction removes baseline shifts within and between biochip sensors, allowing accurate and precise voltage signal between different biochips. The corrected signal was used for multivariate regression models, which significantly decreased the calibration standard error from 0.50 to 0.03 log(10) (cells/mL). Results show that Ziehl-Neelsen detection limits and below are achievable with the magnetoresistive biochip, when pre-processing and chemometrics are used.

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