bluuebunny/crossref_metadata_2025_split huggingface dataset:
Educational Program to Improve Drug Adherence in Pediatric Epilepsy Patients and Caregivers in Limited Resource Area
Authors: Saengow Vitchayaporn Emarach , Pavarojkit Pavaree , Phonsing Sukussara 
Published: August 2019

AbstractPoor drug adherence can lead to poor seizure control in pediatric epilepsy patients. Patients' knowledge about drug compliance is the cornerstone to improving drug adherence. In the past, several educational programs have involved multidisciplinary teams, including many specialists, who were recruited to spread and improve awareness about good drug adherence; however, there are few studies conducted in a limited resource country. This paper aims to outline a new program created by our clinicians. The epilepsy alert system (EAS) is an accessible educational program for pediatric epilepsy patients and caregivers, which is suitable for limited resource areas and evaluates the benefit of EAS on drug adherence. The EAS consists of a 20-minute-long educational program, co-led by a pediatric neurologist, a pediatrician, and a pharmacist, using simple tools such as an epilepsy diary and an epilepsy card. Epileptic children aged 1 month to 15 years who visited a pediatric epilepsy clinic between August 1, 2017 and September 30, 2018 were included. Drug adherence was evaluated using the four-item Morisky's Medication Adherence Scale. Comparison of drug adherence occurred prior to and at a 3- and 6-month follow-up, after participants received the educational program. A total of 108 patients were enrolled. Of these, the participants' mean age was 7 years and 6 months. Males constituted 59.3% of the cohort. The most common seizure type is focal epilepsy and 22.4% of the cohort had intractable epilepsy. 41% of participants had a “poor” adherence at baseline. After recruited to EAS, the poor drug adherence was significantly decreased to 23 and 14% at the 3- and 6-month follow-up, respectively. EAS is a suitable educational program for clinicians to employ when trying to improve drug adherence in pediatric epilepsy patients and caregivers in a limited resource area.
Bauaktivitäten Deutscher Kliniken: Leichte Stagnation
Authors: Kucera Martin 
Published: August 2019

Es gibt immer weniger Krankenhäuser in Deutschland. Wie steht es mit den Bauaktivitäten im Gesundheitswesen? Der Münchner Informationsdienstleister Schwab Marketing registriert in seiner aktuellen Marktstudie für 2019 erneut einen Anstieg der Baumaßnahmen – allerdings weniger als noch vor einem Jahr.
When metaphors become cognitive locks: occupational pension reform in Norway
Authors: Hagelund Anniken , Grødem Anne Skevik 
Published: August 2019

ABSTRACTThe reform of the Norwegian pension system in the early 2000s sparked off a need to reform occupational pensions. In the private sector, this was done in negotiations in 2008. In the public sector, a similar attempt in 2009 failed, and the process was only finalized in 2018. We aim to show how discourse, and the way the issues were framed through narratives and metaphors, affected the reform processes in 2008/2009. We outline the significance of different constellation of actors in the two sectors, and show how this affected the ability to achieve common understandings (coordinative discourse) and popular support (communicative discourse). We then focus in particular on one popular metaphor, namely the toiler, and show how toilers emerged in different guises in both the private and public sector negotiations. A clear notion of what the toiler needed was constructed during the private-sector negotiations. When negotiations moved to the public sector, and a different type of toiler entered the picture, key reform architects were unable to adjust. The metaphor of the toiler ended up as a ‘cognitive lock’ that hampered rather than promoted reform in the public sector.
Differences in visceral adipose tissue and biochemical cardiometabolic risk markers in elite rugby union athletes of Caucasian and Polynesian descent
Authors: Zemski Adam J. , Keating Shelley E. , Broad Elizabeth M. , Marsh Damian J. , Hind Karen , Walters Kylie J. , Slater Gary J. 
Published: August 2019

AbstractPolynesian individuals are leaner with greater musculature than Caucasians of an equivalent size, and this genetically different morphology provides a physique that is often compatible with success in a number of sports, including rugby union. Evidence indicates that Polynesians have greater stores of absolute and relative abdominal fat mass and this is known to confer cardiometabolic risk. The aims of this study were to (1) explore the relationship between ethnicity, visceral adipose tissue (VAT), and cardiometabolic disease risk markers in elite Caucasian and Polynesian rugby union athletes, and (2) assess the impact of a pre‐season training programme on these markers. Twenty‐two professional rugby union athletes of Caucasian (n = 11) and Polynesian (n = 11) descent underwent physique assessment via surface anthropometry, dual‐energy X‐ray absorptiometry, and magnetic resonance imaging before and after an 11‐week pre‐season. A fasted blood test was undertaken at both time points. Compared to Caucasians, at baseline Polynesians displayed significantly higher VAT (771 ± 609 cm3 vs 424 ± 235 cm3; p = 0.043), triglycerides (1.0 ± 0.9 mmol/L vs 0.6 ± 0.2 mmol/L; p = 0.050), and low‐density lipoprotein cholesterol (3.1 ± 0.9 mmol/L vs 2.3 ± 0.7 mmol/L; p = 0.019). Similar changes were observed in both groups over the pre‐season period in VAT and blood biochemical markers. Polynesian rugby union athletes were more likely than Caucasians to exhibit risk factors associated with cardiometabolic disease, such as elevated VAT and unfavourable lipid profiles. Further longitudinal research is required to identify and explain the short‐ and long‐term risk of cardiometabolic disease in athletes of Polynesian descent.
Power law error growth in multi-hierarchical chaotic systems—a dynamical mechanism for finite prediction horizon
Authors: Brisch Jonathan , Kantz Holger 
Published: August 2019

Abstract
We propose a dynamical mechanism for a strictly finite prediction horizon, i.e. a scenatio of chaotic motion where asymptotically a more precise knowledge of the initial condition does note translate into a longer closeness of the forecast to the truth. For this, we propose a class of hierarchical dynamical systems which possess a scale dependent error growth rate in the form of a power law. Actually, this is motivated by and consistent with well known hierarchies of patterns in atmospheric dynamics. This scale dependent error growth rate in form of a power law translates in power law error growth over time instead of exponential error growth as in conventional chaotic systems. The consequence is a strictly finite prediction horizon, since in the limit of infinitesimal errors of initial conditions, the error growth rate diverges and hence additional accuracy is not translated into longer prediction times. By re-analyzing data of the National Center for Environmental Protect Global Forecast System, a weather prediction model, published by Harlim et al (2005 Phys. Rev. Lett.
94 228501) we show that such a power law error growth rate can indeed be found in numerical weather forecast models and estimate it average maximal prediction horizon to about 15 d.
Parameter identification and state-of-charge estimation approach for enhanced lithium–ion battery equivalent circuit model considering influence of ambient temperatures*
Authors: Pang Hui , Mou Lian-Jing , Guo Long 
Published: August 2019

Abstract
It is widely accepted that the variation of ambient temperature has great influence on the battery model parameters and state-of-charge (SOC) estimation, and the accurate SOC estimation is a significant issue for developing the battery management system in electric vehicles. To address this problem, in this paper we propose an enhanced equivalent circuit model (ECM) considering the influence of different ambient temperatures on the open-circuit voltage for a lithium–ion battery. Based on this model, the exponential-function fitting method is adopted to identify the battery parameters according to the test data collected from the experimental platform. And then, the extended Kalman filter (EKF) algorithm is employed to estimate the battery SOC of this battery ECM. The performance of the proposed ECM is verified by using the test profiles of hybrid pulse power characterization (HPPC) and the standard US06 driving cycles (US06) at various ambient temperatures, and by comparing with the common ECM with a second-order resistance capacitor. The simulation and experimental results show that the enhanced battery ECM can improve the battery SOC estimation accuracy under different operating conditions.
Comparison of crash behaviour prediction of a car crash box using initial and updated finite element model
Authors: Abdullah N.A.Z. , Sani M.S.M. , Salwani M.S. 
Published: August 2019

Abstract
Topic of crashworthiness is gaining popularity as vehicle safety is becoming main concern to the vehicle manufacturers worldwide. Due to this factor, energy absorbing members on vehicle such as crash box is researched by many which lead to various strategies of design optimization has been carried out in order to seek a good energy absorber on vehicle. Among the popular method of determining the crash performance of a structure is by using dynamic analysis in computational finite element model (FEM). However, since finite element analysis (FEA) is only an approximation method which in many cases can be less reliable, model updating method is often suggested to improve its reliability. This study seeks to investigate the crash behaviour of initial and updated crash box model. The velocity of impactor, the deformation, collapse distance and energy transferred to the two models of crash box are compared. The findings show that the initial and updated model of the crash box in this study, do have different crash behaviour. However, the difference level is relatively small. The investigation on the method of validation for the updated model in terms of crash behaviour is highly recommended.
A Comparative Study of CWELD and ACM2 Element Connectors on the Dynamic Behaviour of a Laser Spot Welded Hat-Plate Structure under Initial Stress Influence
Authors: Peter C , Rani M N Abdul , Hashim H , Yunus M A , Machmud M.N , Mohd Zin M S 
Published: August 2019

Abstract
Analytical modelling of the dynamic behaviour of a laser spot welded structure can be developed using two element connectors which are CWELD and ACM2. In the presence of initial stress in the structure, the performance of these two connectors can be different. In order to properly investigate the dynamic behaviour of the structure, the difference of these two element connectors in representing the laser spot welded in the structure should be evaluated. The finite element method was used to develop the welded structure comprising two structural components. The element connectors were then used to represent the laser spot welds in the structure. Normal modes analysis was performed on the FE model of the welded structure to calculate the modal parameters. Experimental modal analysis was carried out to measure the modal parameters of the physical welded structure. The modal parameters calculated from the two different FE models were evaluated by the experimental counterparts in terms of natural frequencies, mode shapes and MAC value. The accumulated error registered from all 6 modes from the CWELD element connector FE model is 10.59%. Meanwhile, the accumulated error calculated from all 6 modes of the ACM2 element connectors based FE model is 26.67%. It was found that the FE model with CWELD element connectors has shown a good correlation with the physical welded structure. The findings can have an important effect on how analytical modelling of the dynamic behaviour of the welded structure under initial stress can be effectively and accurately carried out.
Identifying the Appropriate Frequency Response Function Driving Point of a Car Door Using Finite Element Analysis and Modal Testing
Authors: Iskandar Mirza W I I Wan , Rani M N Abdul , Musa M F , Yunus M A , Peter C , Shah M A S Aziz 
Published: August 2019

Abstract
Identifying the appropriate frequency response function (FRF) driving point of complex structures is crucial to experimental modal analysis (EMA), but it is often found to be challenging and problematic. Traditionally, EMA analysts tend to place a reference sensor at several potential driving points and excite the points during testing. However, the approach is time-consuming. The aim of this work is to demonstrate an effective procedure for identifying the appropriate FRF driving point of a complex structure using finite element pre-test analysis and modal testing. The demonstration is performed on a car door structure comprising several geometrically complex structural components. The effective impedance method (EIM) is used to identify thirty potential driving points from the finite element model of the car door. The FRF data of the driving points is derived by using the FRF synthesis method and the derived data is compared with the EMA FRF data for validation purposes. Using EIM, three appropriate driving points covering all the modes required within the frequency of interest that is 0 to 100Hz has been successfully identified. The achievement suggests that the use of the effective impendence method for identifying the appropriate driving points is highly dependent on the accuracy and reliability of the finite element model.
Noise Source Identification of Automotive Radiator by Using Sound Intensity Mapping Method
Authors: Razak N F D , Sani M S M , Azmi W H , Zhang B 
Published: August 2019

Abstract
Automotive radiator played an essential role as a heat exchanger that exchange the circulated heated coolant inside the engine compartment to return into its ambient temperature. Radiator cooling fan that attached at the back of radiator, is a device that work to regulate the coolant temperature when the heated coolant is passed inside the radiator tubes. It produces external flow of air that passes through the fins and tubes of the radiator. However, this external flow contributes high noise level into the system. In consequence of this risk, a detailed experimental study on noise analysis to identify the location of maximum sound pressure level (SPL) generated by variations of cooling fan speed by using sound intensity mapping method is presented. Ethylene Glycol (EG)-water based was used as working fluid operate with engine temperature range from 80 to 90 °C. The cooling fan speed of radiator cooling fan were varied from 750 to 1250 rpm and the water flowrates were 8.0, 11.0, and 14.0 l/min. The results indicate that the noise level is increasing with the fan speed. However, there is no significance difference of change in coolant flow rate and type of coolant fluids to the noise level. The location of maximum sound pressure level is identified and the higher SPL value most located on the blade trailing edge of the suction surface with highest SPL value of 81 db for 1250 rpm fan speed. The project delivers the reliable input for the engineering practice to reduce automotive radiator noise level.
Potential of Using Natural Fiber for Building Acoustic Absorber: A Review
Authors: Taiwo Esan Martins , Yahya Khairulzan , Haron Zaiton 
Published: August 2019

AbstractSustainability is one of the significant goals in the evaluation and promotion of building materials in the current society. This paper presents an evaluation of the potential of natural fiber for building acoustics absorber. This was done by comparing all aspects of sustainability including economy, social and environmental needs between the natural and synthetic fibers. Some features of natural fibers such as light weight, bio-degradability, low-cost, carbon-dioxide neutral, low consumption of energy and health aspects has been the major factors that contributed to its use in many construction applications. In addition to that, previous researches showed that sound absorbing materials with natural fibers have good acoustic properties in high frequency range similar with those synthetic fiber. However, high water absorption, prone to termite attack, less fire resistance and low strength are remaining the issues militating against the natural fiber for building acoustic absorber. Despite that, natural fibers have already been proven alternatives to synthetic fiber in building acoustic absorber thereby alleviating some sustainability issues associated with the use of synthetics materials in building acoustics.
Joining Strategy Analysis of Structural Dynamic in Top Hat Plate of Dissimilar Materials
Authors: Nazri N.A. , Sani M.S.M. 
Published: August 2019

Abstract
Structural dynamic can be described as a study regarding analysis of model under exertion of dynamic loading. Joining in structure such as riveting, welding and soldering were strongly effects the structural dynamic properties. The aim of this paper is to conduct various joining strategy analysis in finite element software by using top hat plate structure in car as a model and result is compared with experimental data. Normal mode analysis with free-free boundary condition is applied. Resistance spot welding (RSW) technique is selected to weld flange part in top hat plate between dissimilar materials which is mild steel 1010 and stainless steel 304 with specified parameters applied. Modal testing via impact hammer test is carried out at the welded top hat plate for experimental analysis purpose. Correlation in between FEA and EMA results need to be conducted. By selecting identified parameters to execute model updating on the structure using sensitivity analysis method, the discrepancies in natural frequencies were reduced between FEA and EMA. CWELD element was chosen to represent weld model for spot weld joints due to its accurate prediction of frequencies and mode shapes compare to other weld modelling. As a closure, connection in structure parts play significant role in structural dynamics and model updating is one of successful method to lessen the discrepancies between FEA and EMA.
Model Updating of Frame Structure with Bolted Joints
Authors: Izham M.H.N. , Sani M.S.M. 
Published: August 2019

Abstract
Experimental analysis is often viewed as an important source of reference compared to finite element due to the accuracy of giving reliable data. Currently, finite element analysis is widely used as an early adoption in development, hence trusting the finite element data is crucial for the user. Finite element analysis often shows discrepancies to the test result. The complexity of the joints (bolted) might cause the discrepancies to occur. This study aims to reduce the discrepancies between the experimental and numerical analysis on a frame structure with bolted joints by model updating. Model updating is a process of making adjustment to certain parameters of finite element model to reduce discrepancy between analytical predictions of finite element analysis (FEA) and experimental results. Modal properties (natural frequencies, mode shapes, and damping ratio) of a frame structure with bolted joints are determined using both experimental modal analysis (EMA) and finite element analysis (FEA). Both data obtained is correlated before optimising the properties with sensitivity analysis. Joint strategy of this paper is focusing on RBE2, CBAR and CELAS element. CELAS was selected to represent the bolted modelling due to its lowest percentage average of 2.03% compares to CBAR 6.55% or RBE2 3.56%. Selected parameters were identified by performing a sensitivity analysis and the discrepancies was reduced by performing model updating procedure.
Predicting the Dynamic Stiffness of a Glove Material using Mechanical Impedance Model
Authors: Razali K. A. Md , Samin R. , As’arry A. , Jalil N. A. A. 
Published: August 2019

Abstract
Anti-vibration glove has been developed to be able to attenuate vibration transmitted to the hand. However, the performance depends on lots of factors such as the contact area and contact force. In addition, the materials used in gloves are commonly made of foam and gel, which produce complex response when these factors are changed. This study aimed to predict the dynamic stiffness of a glove based on the measured transmissibility and apparent mass, using mechanical impedance model. This is used so that the dynamic response of the material can be well understood when parameters such as contact area and contact force are changed. The mechanical impedance model has previously been used to predict transmissibility and showed prediction that is comparable to the measured transmissibility. Measured transmissibilities and apparent masses of the hand of five subjects were used in the model to predict the dynamic stiffness of the glove material. The predicted dynamic stiffness was then compared to the dynamic stiffness measured experimentally. The results showed that the predicted dynamic stiffnesses were similar to the measured dynamic stiffness. In conclusion, the mechanical impedance model is able to predict dynamic stiffness of the glove material.
Stability analysis of regenerative vibration in turning operation using I-kaz3DTM signal processing approach
Authors: Samin R , Nuawi M Z , Haris S M , Ghani J A 
Published: August 2019

Abstract
This paper presents a stability analysis to predict regenerative vibration during turning process. Although the stability of machining process has been widely studied in metal cutting it still presents a challenge as surface roughness, tool wear and productivity have to be considered. If the tool is vibrating as it removes material, these vibrations are imprinted on the workpiece surface as a wavy profile. However, the relative phasing between the surface waviness from one pass to the next determines the level of force variation and whether the operation is stable or unstable. Then we investigate the unstable and stable phenomena during the machining process by discussing the number of time-domain simulation to determine the force and surface roughness values these stability thresholds. A signal processing was carried out using I-Kaz3D technique to identify the effect between the unstable and stable phenomena. The results show that the relationship between I-kaz3D coefficients and surface roughness values can be considered very highly correlated.
Training Feedforward Neural Networks for Structural Health Monitoring of an Aircraft Structure
Authors: Rahman Tuan A Z , Rezali K A M , Jalil N A Abdul , As’arry A , Kamil Raja 
Published: August 2019

Abstract
In the past decades, structural health monitoring (SHM) has become an emerging research area for globally monitoring expensive aircraft and bridge structures. This paper presents the application of stochastic fractal search (SFS) algorithm and its chaotic-enhanced variants to train feedforward neural networks (FNNs) for monitoring an aircraft structure based on vibration data. An experimental spectral testing was carried out to obtain the normal and damaged condition data of a laboratory stiffened panel structure which imitated wingbox of an aircraft. Added mass as pseudo-fault was employed to simulate damage condition with three different damage levels at three different locations. Vibration signature features were generated based on measured frequency response functions (FRFs) and principle component analysis (PCA). Then, metaheuristic-based FNNs approach were applied to localize and predict the severity of damage on the structure. The results reveal that the proposed approach produces high classification and localization accuracy as parameters of the FNNs were optimized systematically using metaheuristic algorithms. In conclusion, the Sine chaos-enhanced SFS algorithm highlights better convergence performance and results accuracy compared to other contested metaheuristic approaches.