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Fulltext Bellagio Declaration on high-quality health systems: from a quality moment to a quality movement

Al-Janabi A, Al-Wahdani B, Ammar W, Arsenault C, Asiedu EK, Etiebet MA, et al.

Lancet Glob Health, 2018 11;6(11):e1144-e1145.
PMID: 30196091 DOI: 10.1016/S2214-109X(18)30372-3
Matched MeSH terms: Goals*
Fulltext Effect of inductive coil shape on sensing performance of linear displacement sensor using thin inductive coil and pattern guide

Misron N, Ying LQ, Firdaus RN, Abdullah N, Mailah NF, Wakiwaka H

Sensors (Basel), 2011;11(11):10522-33.
PMID: 22346656 DOI: 10.3390/s111110522

This paper discusses the effect of inductive coil shape on the sensing performance of a linear displacement sensor. The linear displacement sensor consists of a thin type inductive coil with a thin pattern guide, thus being suitable for tiny space applications. The position can be detected by measuring the inductance of the inductive coil. At each position due to the change in inductive coil area facing the pattern guide the value of inductance is different. Therefore, the objective of this research is to study various inductive coil pattern shapes and to propose the pattern that can achieve good sensing performance. Various shapes of meander, triangular type meander, square and circle shape with different turn number of inductive coils are examined in this study. The inductance is measured with the sensor sensitivity and linearity as a performance evaluation parameter of the sensor. In conclusion, each inductive coil shape has its own advantages and disadvantages. For instance, the circle shape inductive coil produces high sensitivity with a low linearity response. Meanwhile, the square shape inductive coil has a medium sensitivity with higher linearity.

Matched MeSH terms: Goals
Generalized pustular psoriasis: A global Delphi consensus on clinical course, diagnosis, treatment goals and disease management

Puig L, Choon SE, Gottlieb AB, Marrakchi S, Prinz JC, Romiti R, et al.

J Eur Acad Dermatol Venereol, 2023 Apr;37(4):737-752.
PMID: 36606566 DOI: 10.1111/jdv.18851

BACKGROUND: Generalized pustular psoriasis (GPP) is a rare and highly heterogeneous skin disease, characterized by flares of neutrophilic pustules and erythema. As a rare disease with few clinical studies and no standardized management approaches, there is a paucity of knowledge regarding GPP.
OBJECTIVES: Conduct a Delphi panel study to identify current evidence and gain advanced insights into GPP.
METHODS: A systematic literature review was used to identify published literature and develop statements categorized into four key domains: clinical course and flare definition; diagnosis; treatment goals; and holistic management. Statements were rated on a Likert scale by a panel of dermatologists in two rounds of online questionnaires; the threshold for consensus was agreement by ≥80%.
RESULTS: Twenty-one panellists reached consensus on 70.9%, 61.8%, 100.0% and 81.8% of statements in the 'clinical course and flare definition', 'diagnosis', 'treatment goals' and 'holistic management of GPP' domains, respectively. There was clear consensus on GPP being phenotypically, genetically and immunologically distinct from plaque psoriasis. Clinical course is highly variable, with an extensive range of complications. Clinical and histologic features supporting GPP diagnosis reached high levels of agreement, and although laboratory evaluations were considered helpful for diagnosis and monitoring disease severity, there was uncertainty around the value of individual tests. All acute and long-term treatment goals reached consensus, including rapid and sustained clearance of pustules, erythema, scaling and crust, clearance of skin lesions and prevention of new flares. Potential triggers, associated comorbidities and differential diagnoses achieved low rates of consensus, indicating that further evidence is needed.
CONCLUSIONS: Global consensus between dermatologists was reached on clinically meaningful goals for GPP treatment, on key features of GPP flares and on approaches for assessing disease severity and multidisciplinary management of patients. On this basis, we present a management algorithm for patients with GPP for use in clinical practice.

Matched MeSH terms: Goals*
Frequency analysis of maximum daily rainfalls via L-moment approach

Ani Shabri, Nor Atiqah Mohd Ariff

Sains Malaysiana, 2009;38.

Knowledge related to distributions of rainfall amounts are of great importance for the design of water related structures. The greater problem facing hydrologists and engineers identifying the best distribution form for regional data. The main goal of the study is to perform regional frequency analysis of maximum daily rainfalls selected each year among daily rainfalls measured over stations in Selangor and Kuala Lumpur by using the L-moment method. Several distributions were taken into account in this study which include two-parameter normal (NOM), lognormal (LN2), three-parameter lognormal (LN3), logistic (LOG), generalized logistic (GLO), extreme value type I (EV1), generalized extreme value (GEV) and generalized Pareto (GPA) distribution. The most suitable distribution was determined according to the mean absolute deviation index (MADI), mean square deviation index (MSDI) and the L-moment ratio diagram. The result of this study showed that the GLO distribution is the most suitable distribution to fit the data of maximum daily rainfalls for stations in Selangor and Kuala Lumpur.

Matched MeSH terms: Goals
Improving Pipelined Time Stepping Algorithm for Distributed Memory Multicomputers

Ng KF, Norhashidah Mohd Ali

Sains Malaysiana, 2010;39.

Time stepping algorithm with spatial parallelisation is commonly used to solve time dependent partial differential equations. Computation in each time step is carried out using all processors available before sequentially advancing to the next time step. In cases where few spatial components are involved and there are relatively many processors available for use, this will result in fine granularity and decreased scalability. Naturally one alternative is to parallelise the temporal domain. Several time parallelisation algorithms have been suggested for the past two decades. One of them is the pipelined iterations across time steps. In this pipelined time stepping method, communication however is extensive between time steps during the pipelining process. This causes a decrease in performance on distributed memory environment which often has high message latency. We present a modified pipelined time stepping algorithm based on delayed pipelining and reduced communication strategies to improve overall execution time on a distributed memory environment using MPI. Our goal is to reduce the inter-time step communications while providing adequate information for the next time step to converge. Numerical result confirms that the improved algorithm is faster than the original pipelined algorithm and sequential time stepping algorithm with spatial parallelisation alone. The improved algorithm is most beneficial for fine granularity time dependent problems with limited spatial parallelisation.

Matched MeSH terms: Goals
The central role of national programme management for the achievement of malaria elimination: a cross case-study analysis of nine malaria programmes

Smith Gueye C, Newby G, Tulloch J, Slutsker L, Tanner M, Gosling RD

Malar J, 2016 Sep 22;15(1):488.
PMID: 27659770

A malaria eradication goal has been proposed, at the same time as a new global strategy and implementation framework. Countries are considering the strategies and tools that will enable progress towards malaria goals. The eliminating malaria case-study series reports were reviewed to identify successful programme management components using a cross-case study analytic approach.

Matched MeSH terms: Goals
Global Goals and Global Sustainability

Bhore SJ

Int J Environ Res Public Health, 2016 10 07;13(10).
PMID: 27739416

On 25 September 2015, the United Nations (UN) member countries adopted an ambitious 17 Sustainable Development Goals (SDGs) aiming to 'transform the world' in the next 15 years. [...].

Matched MeSH terms: Goals*
Mental health and wellbeing in the Sustainable Development Goals

Izutsu T, Tsutsumi A, Minas H, Thornicroft G, Patel V, Ito A

Lancet Psychiatry, 2015 Dec;2(12):1052-4.
PMID: 26613844 DOI: 10.1016/S2215-0366(15)00457-5
Matched MeSH terms: Goals*
Asia-pacific ready to act on mental health target in the SDGs

Minas H, Izutsu T, Tsutsumi A, Kakuma R, Lopez AD

Lancet Psychiatry, 2015 Mar;2(3):199-201.
PMID: 26359888 DOI: 10.1016/S2215-0366(14)00124-2
Matched MeSH terms: Goals*
Fulltext A railway rescheduling model with priority setting

Shuib, A., Alwadood, Z.

Pertanika Journal of Science & Technology, 2017;25(2):649-660.
MyJurnal

This paper presents a mathematical approach to solve railway rescheduling problems. The approach assumes that the trains are able to resume their journey after a given time frame of disruption whereby The train that experiences disruption and trains affected by the incident are rescheduled. The approach employed mathematical model to prioritise certain types of train according the railway operator’s requirement. A pre-emptive goal programming model was adapted to find an optimal solution that satisfies the operational constraints and the company’s stated goals. Initially, the model minimises the total service delay of all trains while adhering to the minimum headway requirement and track capacity. Subsequently, it maximises the train service reliability by only considering the trains with delay time window of five minutes or less. The model uses MATLAB R2014a software which automatically generates the optimal solution of the problem based on the input matrix of constraints. An experiment with three incident scenarios on a double-track railway of local network was conducted to evaluate the performance of the proposed model. The new provisional timetable was produced in short computing time and the model was able to prioritise desired train schedule.

Matched MeSH terms: Goals
Statistical models for brain signals with properties that evolve across trials

Ombao H, Fiecas M, Ting CM, Low YF

Neuroimage, 2018 Oct 15;180(Pt B):609-618.
PMID: 29223740 DOI: 10.1016/j.neuroimage.2017.11.061

Most neuroscience cognitive experiments involve repeated presentations of various stimuli across several minutes or a few hours. It has been observed that brain responses, even to the same stimulus, evolve over the course of the experiment. These changes in brain activation and connectivity are believed to be associated with learning and/or habituation. In this paper, we present two general approaches to modeling dynamic brain connectivity using electroencephalograms (EEGs) recorded across replicated trials in an experiment. The first approach is the Markovian regime-switching vector autoregressive model (MS-VAR) which treats EEGs as realizations of an underlying brain process that switches between different states both within a trial and across trials in the entire experiment. The second is the slowly evolutionary locally stationary process (SEv-LSP) which characterizes the observed EEGs as a mixture of oscillatory activities at various frequency bands. The SEv-LSP model captures the dynamic nature of the amplitudes of the band-oscillations and cross-correlations between them. The MS-VAR model is able to capture abrupt changes in the dynamics while the SEv-LSP directly gives interpretable results. Moreover, it is nonparametric and hence does not suffer from model misspecification. For both of these models, time-evolving connectivity metrics in the frequency domain are derived from the model parameters for both functional and effective connectivity. We illustrate these two models for estimating cross-trial connectivity in selective attention using EEG data from an oddball paradigm auditory experiment where the goal is to characterize the evolution of brain responses to target stimuli and to standard tones presented randomly throughout the entire experiment. The results suggest dynamic changes in connectivity patterns over trials with inter-subject variability.

Matched MeSH terms: Goals
Fulltext The advantages of concept mapping care plan in clinical practices

Rusnani Ab Latif, Akehsan Dahlan, Zamzaliza Abdul Mulud, Mohd Zarawi Mat Nor

The Malaysian Journal of Nursing, 2017;9(2):52-57.
MyJurnal

Excellence in academic and practical skills is the main goal of most nursing educators. It is a tool to measure the level of success of the nurse educators. Concept mapping care plan is related to the expectation that today's nursing students must master a constantly expanding body of knowledge and apply complex skills in rapidly changing environment. Concept mapping care plan was developed by researcher and validated by ten expert panels using three rounds of Delphi technique. It was used to evaluate academic performance of nursing students at clinical practice. Concept mapping care plan is a good assessment tool to nursing educators to prepare nursing students for better critical thinking and expected to function effectively after graduation. The goal of concept mapping care plan as a teaching strategy during the clinical practices, help the students to integrate the knowledge from theory and implementing this knowledge in the clinical setting. Researcher believes that concept mapping care plan can be as a replacement of nursing process that have been practiced before in the clinical setting. In addition, through concept mapping care plan provides an opportunity for students to broaden their knowledge and become more creative.

Matched MeSH terms: Goals
Fulltext Advocating collaborative teaching and learning in dentistry

Mas Suryalis Ahmad

Malaysian Dental Journal, 2016;39(1):1-8.
MyJurnal

Collaborative teaching is an educational approach that seeks to involve participation of teachers and learners in achieving learning goals and outcomes in an interactive manner (1). Such approach has been effective in equipping students with knowledge and/or skills via high levels of learning, while allowing interpersonal development such as teamwork, time management, as well as communication and written competencies (2, 3). (Copied from article)

Matched MeSH terms: Goals
Fulltext An accurate rejection model for false positive reduction of mass localisation in Mammogram

Ashwaq Qasem, Siti Norul Huda Sheikh Abdullah, Shahnorbanun Sahran, Rizuana Iqbal Hussain, Fuad Ismail

Pertanika Journal of Science & Technology, 2017;25(106):49-62.
MyJurnal

The false positive (FP) is an over-segment result where the noncancerous pixel is segmented as a cancer pixel. The FP rate is considered a challenge in localising masses in mammogram images. Hence, in this article, a rejection model is proposed by using a supervised learning method in mass classification such as support vector machine (SVM). The goal of the rejection model which is based on SVM is the reduction of FP rate in segmenting mammogram through the Chan-Vese method, which is initialised by the marker controller watershed (MCWS) algorithm. The MCWS algorithm is utilised for segmentation of a mammogram image. The segmentation is subsequently refined through the Chan-Vese method, followed by the development of the proposed SVM rejection model with different window size as well as its application in eliminating incorrect segmented nodules. The dataset comprised of 57 nodules and 113 non-nodules and the study successfully proved the effectiveness of the SVM rejection model to decrease the FP rate.

Matched MeSH terms: Goals
Efficient Deployment of Multi-UAVs in Massively Crowded Events

Sawalmeh A, Othman NS, Shakhatreh H

Sensors (Basel), 2018 Oct 26;18(11).
PMID: 30373204 DOI: 10.3390/s18113640

In this paper, the efficient 3D placement of UAV as an aerial base station in providing wireless coverage for users in a small and large coverage area is investigated. In the case of providing wireless coverage for outdoor and indoor users in a small area, the Particle Swarm Optimization (PSO) and K-means with Ternary Search (KTS) algorithms are invoked to find an efficient 3D location of a single UAV with the objective of minimizing its required transmit power. It was observed that a single UAV at the 3D location found using the PSO algorithm requires less transmit power, by a factor of 1/5 compared to that when using the KTS algorithm. In the case of providing wireless coverage for users in three different shapes of a large coverage area, namely square, rectangle and circular regions, the problems of finding an efficient placement of multiple UAVs equipped with a directional antenna are formulated with the objective to maximize the coverage area and coverage density using the Circle Packing Theory (CPT). Then, the UAV efficient altitude placement is formulated with the objective of minimizing its required transmit power. It is observed that the large number of UAVs does not necessarily result in the maximum coverage density. Based on the simulation results, the deployment of 16, 19 and 26 UAVs is capable of providing the maximum coverage density of 78.5%, 82.5% and 80.3% for the case of a square region with the dimensions of 2 km × 2 km, a rectangle region with the dimensions of 6 km × 1.8 km and a circular region with the radius of 1.125 km, respectively. These observations are obtained when the UAVs are located at the optimum altitude, where the required transmit power for each UAV is reasonably small.

Matched MeSH terms: Goals
Fulltext Employment of patients with multiple sclerosis: the influence of psychosocial-structural coping and context

Vijayasingham L, Mairami FF

Degener Neurol Neuromuscul Dis, 2018;8:15-24.
PMID: 30050385 DOI: 10.2147/DNND.S131729

Patients with multiple sclerosis tend to report higher levels of work difficulties and negative outcomes, such as voluntary and involuntary work termination and reduced work participation. In this article, we discuss the complex interactions of disease, personal coping strategies, and social and structural factors that contribute to their work experiences and outcomes. An overview of the coping strategies and actions that leverage personal and context-level factors and dynamics is also provided to support the overall goal of continued work in patients with MS.

Matched MeSH terms: Goals
Arrhythmia detection using deep convolutional neural network with long duration ECG signals

Yıldırım Ö, Pławiak P, Tan RS, Acharya UR

Comput Biol Med, 2018 11 01;102:411-420.
PMID: 30245122 DOI: 10.1016/j.compbiomed.2018.09.009

This article presents a new deep learning approach for cardiac arrhythmia (17 classes) detection based on long-duration electrocardiography (ECG) signal analysis. Cardiovascular disease prevention is one of the most important tasks of any health care system as about 50 million people are at risk of heart disease in the world. Although automatic analysis of ECG signal is very popular, current methods are not satisfactory. The goal of our research was to design a new method based on deep learning to efficiently and quickly classify cardiac arrhythmias. Described research are based on 1000 ECG signal fragments from the MIT - BIH Arrhythmia database for one lead (MLII) from 45 persons. Approach based on the analysis of 10-s ECG signal fragments (not a single QRS complex) is applied (on average, 13 times less classifications/analysis). A complete end-to-end structure was designed instead of the hand-crafted feature extraction and selection used in traditional methods. Our main contribution is to design a new 1D-Convolutional Neural Network model (1D-CNN). The proposed method is 1) efficient, 2) fast (real-time classification) 3) non-complex and 4) simple to use (combined feature extraction and selection, and classification in one stage). Deep 1D-CNN achieved a recognition overall accuracy of 17 cardiac arrhythmia disorders (classes) at a level of 91.33% and classification time per single sample of 0.015 s. Compared to the current research, our results are one of the best results to date, and our solution can be implemented in mobile devices and cloud computing.

Matched MeSH terms: Goals
Customer Satisfaction and Expectation Approach on Regular Travel Package in Quality Service by Design Using Fuzzy Logic Controller

Mohammad Nasir Saludin, Rika Fatimah Panjaitan

Sains Malaysiana, 2004;33.

There are a lot of factors and conditions to be considered by tour and travel companies when designing quality product due to the fact that the product being sold is intangible and their ultimate goal is to sustain customers' loyalty. Fuzzy Logic Controller (FLC) has been observed to be compatible to this 'intangible' factor thus giving better result when compared to other methods. By using FLC, all communications are clear and have precise meaning.

Matched MeSH terms: Goals
Fulltext Knowledge Preserving OSELM Model for Wi-Fi-Based Indoor Localization

Al-Khaleefa AS, Ahmad MR, Isa AAM, Esa MRM, Aljeroudi Y, Jubair MA, et al.

Sensors (Basel), 2019 May 25;19(10).
PMID: 31130657 DOI: 10.3390/s19102397

Wi-Fi has shown enormous potential for indoor localization because of its wide utilization and availability. Enabling the use of Wi-Fi for indoor localization necessitates the construction of a fingerprint and the adoption of a learning algorithm. The goal is to enable the use of the fingerprint in training the classifiers for predicting locations. Existing models of machine learning Wi-Fi-based localization are brought from machine learning and modified to accommodate for practical aspects that occur in indoor localization. The performance of these models varies depending on their effectiveness in handling and/or considering specific characteristics and the nature of indoor localization behavior. One common behavior in the indoor navigation of people is its cyclic dynamic nature. To the best of our knowledge, no existing machine learning model for Wi-Fi indoor localization exploits cyclic dynamic behavior for improving localization prediction. This study modifies the widely popular online sequential extreme learning machine (OSELM) to exploit cyclic dynamic behavior for achieving improved localization results. Our new model is called knowledge preserving OSELM (KP-OSELM). Experimental results conducted on the two popular datasets TampereU and UJIndoorLoc conclude that KP-OSELM outperforms benchmark models in terms of accuracy and stability. The last achieved accuracy was 92.74% for TampereU and 72.99% for UJIndoorLoc.

Matched MeSH terms: Goals
Fulltext Bipedal humanoid robot

Zayer, Iman, Aris, I.B., Marhaban, M.H, Ishak, A.J

The Pertanika Journal of Scholarly Research Reviews, 2018;4(3):0-0.
MyJurnal

The new millennium witnessed increasing attention to the field of robotics, especially the development of humanoid bipedal robot. Attention is noticed from the increasing number of publications as a result of a multitude of humanoid projects for commercial and academic goals. This paper briefly visits the recent activities in this field, highlighting the importance and motivation behind adopting bipedal humanoid projects, particularly underlining biologically inspired design concept, bipedal locomotion and communication. Ultimately, emphasising on power-efficient design. The problem of endurance and effective duty cycle were presented. Finally, potential future application for the humanoid robot was briefly listed.

Matched MeSH terms: Goals

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