bluuebunny/crossref_metadata_2025 huggingface dataset:
Lagrangian Vortex computations of turbine wakes: recent improvements using Poletto’s Synthetic Eddy Method (SEM) to account for ambient turbulence
Authors: Bex Camille Choma , Pinon Grégory , Slama Myriam , Gaston Benoist , Germain Grégory , Rivoalen Elie
Published: September 2020

This paper presents possible techniques for modelling ambient turbulence in the Lagrangian Vortex Method formalism. Due to the fact that regular Synthetic Eddy Method (SEM) already presented in previous studies is not divergence free by definition; improvements were necessary to develop a similar SEM method with such a divergence free property. The recent improvements formulated by R. Poletto give the way to such a possibility. This new Divergence Free Synthetic Eddy Method (DFSEM) is presented here in comparison with the regular SEM. Obtained numerical velocity fields are compared in terms of convergence properties, Power Spectral Density and also Taylor macro-scale. Finally, turbine wakes are computed with both the recent Poletto’s DFSEM and the regular Jarrin’s SEM to highlight differences. At this stage of development, the DFSEM seems very promising even though some improvements are still necessary.
Large-scale coherent structures in the atmosphere over a flat terrain
Authors: Alcayaga Leonardo , Larsen Gunner Chr. , Kelly Mark , Mann Jakob
Published: September 2020

Large-scale coherent motions in the atmospheric boundary layer are investigated from field measurements made with two scanning wind lidars over a two-dimensional domain covering approximately 50 km2. The size, isotropy and two-point statistics of the coherent structures, show their influence on wind field homogeneity and local conditions that wind turbines might experience within a wind farm. For neutral atmospheric stability and high wind conditions, most of these structures are observed to be narrow streaks of low streamwise momentum having positive vertical velocity component (ejections), extending several kilometers. The results shown here are consistent with numerical simulations of atmospheric flows under similar conditions, and scale experiments made in laboratories.
Downscaling and improving the wind forecasts from NWP for wind energy applications using support vector regression
Authors: Yakoub Ghali , Mathew Sathyajith , Leal Joao
Published: September 2020

The stochastic nature of wind poses challenges in the large scale integration of wind energy with the grid. Wind characteristics at a site may significantly vary with time. which will be reflected on the wind power production. Understanding and managing such variations could be challenging for wind farm owners. energy traders and grid operators. In this work. we propose models based on support vector regression (SVR) to downscale the speed and direction of wind at a specific site using both historical observed measurements and numerical weather predictions (NWP). Several meteorological variables. considered to have potential influence on the wind. were used in the feature selection for the models. The models are then optimally developed and used to predict the wind speed and direction at the site considered. In view of the two of Nord pool’s energy markets namely the intraday and day ahead markets. approaches for short-term forecasts (t + 1 hours) and medium-term recursive forecasts (t + 36 hours) were developed. The proposed SVR models are found to be accurate and efficient in correcting the NWP information and predicting the wind speed and direction for the short-term forecasts. For medium-term forecasts. the developed models could outperform the NWP. especially for the wind speed predictions.
Wind farm blockage effects: comparison of different engineering models
Authors: Branlard Emmanuel , Quon Eliot , Meyer Forsting Alexander R. , King Jennifer , Moriarty Patrick
Published: September 2020

The work presents four engineering methods to estimate the induction zone in front of a wind turbine and account for the wind farm blockage effect. The methods comprise the vortex cylinder model, vortex dipole model, self-similar model, and wake projection model. The majority of the models presented account for yaw misalignments and ground effect. Actuator disk simulations are used to verify the individual models. The performance of each model is evaluated both in terms of precision and computational time. The induction models are coupled to wake models within the FLOw Redirection and Induction in Steady State framework to provide the full velocity field within a wind farm. Sample wind farm computations are presented, and the impact of including induction effects into wind farm performance predictions is reported. The different codes are publicly available online.
Wind turbine wake characterization using the SpinnerLidar measurements
Authors: Conti Davide , Dimitrov Nikolay , Peña Alfredo , Herges Thomas
Published: September 2020

We analyze SpinnerLidar measurements of a single wind turbine wake collected at the SWiFT facility and investigate the wake behaviour under different atmospheric turbulence conditions. The derived wake characteristics include the wake deficit, wake-added turbulence and wake meandering in both lateral and vertical directions. The atmospheric stability at the site is characterized using observations from a sonic anemometer. A wake-tracking technique, based on a bi-variate Gaussian wake shape, is implemented to monitor the wake center dis-placements in time to derive quasi-steady wake deficit and turbulence profiles in a meandering frame of reference. The analysis demonstrates the influence of atmospheric stability on the wake behaviour; a faster wake deficit recovery and a higher level of turbulence mixing are observed under unstable compared to stable atmospheric conditions. We also show that the wake me-andering is driven by large-scale turbulence structures, which are characterized by increasing energy content as the atmosphere becomes more unstable. These results suggest the suitability of the dataset for wake-model calibration and provide statistics of the wake deficit, turbulence levels, and meandering, which are key aspects for load validation studies.
Code-to-code-to-experiment validation of LES-ALM wind farm simulators
Authors: Wang C , Muñóz-Simon A , Deskos G , Laizet S , Palacios R , Campagnolo F , Bottasso C L
Published: September 2020

The aim of this work is to present a detailed code-to-code comparison of two Large-Eddy Simulation (LES) solvers. Corresponding experimental measurements are used as a reference to validate the quality of the CFD simulations. The comparison highlights the effects of solver order on the solutions, and it tries to answer the question of whether a high order solver is necessary to capture the main characteristics of a wind farm. Both solvers were used on different grids to study their convergence behavior. While both solvers show a good match with experimental measurements, it appears that the low order solver is more accurate and substantially cheaper in terms of computational cost.
Quantifying the Predictability of a ‘Dunkelflaute’ Event by Utilizing a Mesoscale Model
Authors: Li Bowen , Basu Sukanta , Watson Simon J. , Russchenberg Herman W. J.
Published: September 2020

In the coming decades, both wind and solar power production will be playing increasingly important roles in Europe’s energy economy. It is absolutely essential that power grids are resilient against any unusual weather phenomena. One such meteorological phenomenon, “Dunkelflaute”, is causing serious concern to the renewable energy industry, which is primarily characterized by calm winds and overcast conditions. For example, a Dunkelflaute event happened in the Netherlands on 30th April 2018 leading to a significant shortfall in renewable energy generation requiring emergency intervention by the system operator. By analyzing this case, this paper investigates the performance of a state-of-the-art mesoscale model, Weather Research and Forecasting (WRF), in forecasting a Dunkelflaute event. Multiple WRF simulations are driven using real-time Global Forecast System (GFS) operational data over a range of prediction horizons. For comparison, a benchmark run is carried out using ERA5 reanalysis data as boundary conditions. Through validation using a variety of measured data covering onshore and offshore areas, wind speed is shown to be more predictable than cloud-cover in this particular case study.
Yaw induced wake deflection-a full-scale validation study
Authors: Larsen G.C. , Ott S. , Liew J. , van der Laan M.P. , Simon E. , Thorsen G.R. , Jacobs P.
Published: September 2020

Aerodynamic wake interactions between turbines located in wind power plants cause both a loss in power production and an increase in fatigue loading of the wind farm turbines. Yaw induced active wake deflection is one possible wind farm control strategy, which can be applied to mitigate wake effects on nearby downstream located wind turbines. In the present study three flow models of different fidelities are applied to mimic a full-scale study of wake deflection recorded by an advanced synchronised setup of two long-range pulsed scanning lidars. The investigated case studies encompass a base case with (approximately) zero yaw setting supplemented by two non-zero yaw cases of 17.5° and -14.5°, respectively. The model results are compared mutually as well as with the result of the full-scale measurement campaign.
Effect of conventionally neutral boundary layer height on turbine performance and wake mixing in offshore windfarms
Authors: Sood Ishaan , Munters Wim , Meyers Johan
Published: September 2020

In this study, we investigate the effect of conventionally neutral boundary layer height and capping inversion strength on wind farm performance. An aeroelastic multibody solver coupled with a pseudo-spectral large eddy simulation code is used to investigate the structural and aerodynamic output of wind turbines in 4 different inflow types. Farm layouts comprising of turbines in both aligned and staggered arrangements are studied. It is found that the shallower boundary layers with strong capping inversions are characterized by oscillatory structures in turbine wakes, leading to increased structural damage in downstream wind turbines due to fatigue. The power output is also observed to decrease due to poorer wake mixing.
Data-driven turbulence modeling for wind turbine wakes under neutral conditions
Authors: Steiner Julia , Dwight Richard , Viré Axelle
Published: September 2020

Currently, the state of the art in wind farm flow physics modeling are Large Eddy Simulations (LES) which resolve a large part of the spectra of the turbulent fluctuations. But this type of model requires extensive computational resources. One wind speed and direction simulation of the Lillgrund wind farm can take between 160k and 3000k processor hours depending on how the turbines are modeled [1, 2]. The next-fidelity model types are Reynolds-Averaged Navier-Stokes (RANS) models which resolve only the mean quantities and model the effect of turbulence fluctuations. These models require about two orders of magnitude less computational time, but generally do not produce accurate predictions of the mean flow field. Proposed modifications made to these models so far do not generalize well and there is room for improvement. Hence, we present the first steps towards using a data-driven approach to aid in deriving new RANS models that generalize well to different turbine types, varying atmospheric stability, and farm layouts. To do so, time-averaged LES data is used to derive corrections to existing RANS models. The approach uses a deterministic symbolic regression method to infer algebraic correction terms to the RANS turbulence transport equations. Optimal correction terms to the RANS equations are derived using a frozen approach where time-averaged flow fields from LES are injected into the RANS equations. The potential of the approach is demonstrated under neutral conditions for multi-turbine constellations at wind-tunnel scale. The results show promise, but more work is necessary to realize the full potential of the approach.
The effect of dynamic near-wake modulation on utility-scale wind turbine wake development
Authors: Abraham Aliza , Martínez-Tossas Luis A , Hong Jiarong
Published: September 2020

High-resolution field-scale experiments using flow visualization with natural snowfall and high-fidelity large eddy simulations are combined to investigate the effect of dynamic turbine operation and atmospheric conditions on wind turbine wake mixing and recovery in the wake of a 2.5 MW wind turbine. Instantaneous near-wake expansion and deflection in response to changes in blade pitch and wind direction, termed dynamic wake modulation, is quantified using both techniques, demonstrating excellent agreement. The simulations are used to extend these results by calculating the energy flux into the wake 7 rotor diameters downstream, showing that dynamic turbine-atmospheric interactions enhance mixing in the far-wake. This finding is exhibited under both uniform and turbulent inflow conditions. Under turbulent flow, a synergistic relationship is also observed between dynamic wake modulation and wake meandering, as wake recovery can be further accelerated when the two phenomena occur together. The results of this study have implications for the development of more realistic far-wake models that include the significant impact of dynamic wake modulation on wake mixing and development. Additionally, the findings from the current study can be used to develop advanced control algorithms to speed up wake breakdown and recovery, further improving wind farm efficiency.
Representation of coherent structures and turbulence spectra from a virtual SpinnerLidar for future LES wake validation
Authors: Brown Kenneth , Hsieh Alan , Herges Thomas , Maniaci David
Published: September 2020

Work has begun towards model validation of wake dynamics for the large-eddy simulation (LES) code Nalu-Wind in the context of research-scale wind turbines in a neutral atmospheric boundary layer (ABL). Interest is particularly directed at the structures and spectra which are influential for wake recovery and downstream turbine loading. This initial work is to determine the feasibility of using nacelle-mounted, continuous-wave lidars to measure and validate wake physics via comparisons of full actuator line simulation results with those obtained from a virtual lidar embedded within the computational domain. Analyses are conducted on the dominant large-scale flow structures via proper orthogonal decomposition (POD) and on the various scales of wake-added turbulence through spectral comparisons. The virtual lidar adequately reproduces spatial structures and energies compared to the full simulation results. Correction of the higher-frequency turbulence spectra for volume-averaging attenuation was most successful at locations where mean gradients were not severe. The results of this work will aid the design of experiments for validation of high-fidelity wake models.
Aboveground carbon loss associated with the spread of ghost forests as sea levels rise
Authors: Smart Lindsey S , Taillie Paul J , Poulter Benjamin , Vukomanovic Jelena , Singh Kunwar K , Swenson Jennifer J , Mitasova Helena , Smith Jordan W , Meentemeyer Ross K
Published: September 2020

Coastal forests sequester and store more carbon than their terrestrial counterparts but are at greater risk of conversion due to sea level rise. Saltwater intrusion from sea level rise converts freshwater-dependent coastal forests to more salt-tolerant marshes, leaving ‘ghost forests’ of standing dead trees behind. Although recent research has investigated the drivers and rates of coastal forest decline, the associated changes in carbon storage across large extents have not been quantified. We mapped ghost forest spread across coastal North Carolina, USA, using repeat Light Detection and Ranging (LiDAR) surveys, multi-temporal satellite imagery, and field measurements of aboveground biomass to quantify changes in aboveground carbon. Between 2001 and 2014, 15% (167 km2) of unmanaged public land in the region changed from coastal forest to transition-ghost forest characterized by salt-tolerant shrubs and herbaceous plants. Salinity and proximity to the estuarine shoreline were significant drivers of these changes. This conversion resulted in a net aboveground carbon decline of 0.13 ± 0.01 TgC. Because saltwater intrusion precedes inundation and influences vegetation condition in advance of mature tree mortality, we suggest that aboveground carbon declines can be used to detect the leading edge of sea level rise. Aboveground carbon declines along the shoreline were offset by inland aboveground carbon gains associated with natural succession and forestry activities like planting (2.46 ± 0.25 TgC net aboveground carbon across study area). Our study highlights the combined effects of saltwater intrusion and land use on aboveground carbon dynamics of temperate coastal forests in North America. By quantifying the effects of multiple interacting disturbances, our measurement and mapping methods should be applicable to other coastal landscapes experiencing saltwater intrusion. As sea level rise increases the landward extent of inundation and saltwater exposure, investigations at these large scales are requisite for effective resource allocation for climate adaptation. In this changing environment, human intervention, whether through land preservation, restoration, or reforestation, may be necessary to prevent aboveground carbon loss.
Best practice of start up in Indonesia
Authors: Siswanto V K , Ulfa Aulia B , Dadiara A R , Adlina Y Y N , Dzaki H M
Published: September 2020

Industry 4.0 which encourages the whole world to develop its industry based on digital technology, the internet with conventional industry is an opportunity that must be taken by Indonesia. The implementation of industry 4.0 in Indonesia today is the emergence of digital start-ups which have become Unicorns with valuations above USD 1 billion or equivalent to IDR 13.5 trillion. Currently the Indonesian government has encouraged the development of digital start-up which aims to boost the economy and create jobs. But what’s currently happening is even the biggest investment in unicorns that have succeeded in coming from foreigners. In addition, 93 percent of products sold online are imported. The city of Surabaya, which hosts the Startup Nations Summit (SNS), is a case study location that is most suitable for further developing the potential of the creative industry. Therefore the problem raised is how the development of a digital start-up in order to become a creative economic booster by examining UNICORN’s Best Practice that has been successful in Indonesia. This research was conducted using qualitative descriptive analysis techniques and content analysis in order to identify potentials strategies for developing digital start-ups to become creative economic boosters. Based on the results of content analysis conducted on five unicorn startups in Indonesia, three factors of development that need to be considered are human resources (innovating to solve problems, high commitment to become better, good management and quality human resources), good marketing factors, and capital that is easily accessible.
Compressive Failure of Rattan Reinforced Soil Mixture
Authors: Shien Ng Kok , Dexter Delia Evodius , Yee Ming Chew
Published: September 2020

Natural fibrous materials such as coir, jute and kenaf have been used as reinforcement to increase the compressive strength of soft soil. This study introduces a new natural fibrous material namely rattan as the reinforcement for soft soil. The main objective is to determine the compressive failure of soft soil reinforced with rattan. Unconfined Compression Test was conducted according to BS1377-7:1990 standard testing procedures. The first series of testing was conducted on inclusion of different content of rattan strip (0 %, 0.5 %, 1.0 %, 1.5 % and 2.0 %) in soft soil. The second testing series is conducted on inclusion of different length of rattan strip (2 cm, 3 cm, 4 cm, 5 cm and 6 cm) in soft soil. The samples are all prepared at optimum moisture content (27 %) and maximum dry density (1.435 Mg/cm3). Mix performances were obtained where inclusion of rattan can be either beneficial or detrimental depending on the content and the length of the rattan. Rattan fiber of 0.5 % and length of 4 cm seems to be the optimum value in achieving higher compressive strength. Generally, the reinforced soil using rattan strip shows more plastic and ductile behavior.
Study of Performance Aeration Rate Effects on Iron and Manganese Removal in Groundwater Using Gravitational Aeration Tower System (GATS)
Authors: Radzi E Z , Ngimran F N , Hamdan R , Wahab M S , Sahdan M Z , Madun A
Published: September 2020

Groundwater is one of the significant sources for water supply for various purpose. However, it is easier to get in contact with contaminants such as iron and manganese. Iron and manganese contaminant can be treated by aeration process before goto post-filtration system. The aeration process as pre-treatment has done it by using Gravitational Aeration Tower System (GATS). The aeration performance in this experiment has controlled the airflow and water flowrate to observers iron and manganese removal from groundwater than compare the water quality based on the guideline National Drinking Water Quality Standards by Ministry of Health Malaysia. The study has been carried out at the existing tube well in the Research Centre for Soft Soils (RECESS), Universiti Tun Hussein Onn Malaysia (UTHM). The system started from pumping out the groundwater from the tube well and flows it through GATS with a different flow rate of 5.0 L/min and 10.0 L/min, and an airflow rate 0.5 L/min and 1.5 L/min. The sampling of groundwater was taken at before and after the aeration process through GATS and analyze the parameter such as pH, dissolved oxygen (DO), iron and manganese. The results show that pH was in the range of 6.90 to 7.01 and the DO value before GATS maximum is 3.64 mg/L but after aerated with GATS is 6.67 mg/L. Hence, the maximum iron removal efficiency is 10.63%, and the maximum manganese removal efficiency is 14.25%. Aeration process by GATS shows that suitable for DO value increasing than can remove iron and manganese in groundwater.
SCAVS: Implement Sine Cosine Algorithm for generating Variable t-way test suite
Authors: Altmemi Jalal M , Othman R R , Ahmad R
Published: September 2020

Exhaustive testing occurs between interaction elements (i.e., factor and level). In reality, The software system is often impractical because of other constraints, such as cost and time restrictions. The t -way testing (where t indicates the interaction strength) is one of the powerful software, and practical test techniques apply to detect interaction errors between components (i.e., produce quality minimized test cases). The t-way testing is highly complicated (NP-hard). Therefore, many Meta-heuristic algorithms are used to solve combinatorial problems successfully. In general, one of the most effective optimizations algorithm-based techniques SCA. With respect mentioned above, this paper discusses the implementation Sine Cosine Algorithm for generating a variable strength t-way test suite called SCAVS. The results of the experiments showed that SCAVS outperformed and yielded better test sets than other existing other strategies.
Quantification of Soil N, P and K Balance In Peat Soils: Influence of Fluctuating Water Table
Authors: Qursyna Boll Kassim Nur , Yaacob Adzmi
Published: September 2020

This study intends to develop the soil N, P and K balance in peat soils by quantifying the input, internal flow and output of the nutrients under different water table conditions, with and without the pineapple crops uptake. The soil samples for each water table conditions were analyzed for total-N, mineral-N, available-P and exchangeable K. Results showed that pineapple of the variety Moris requires high input of N and K compare to P. Without crops uptake, all treatments indicate positive soil nutrient balance where the treatment with fluctuating water table between 40-80 cm depth showed highest positive balances. In contrast, negative nutrient balance occurred in the presence of uptake by pineapple, where treatment with fluctuating water table between 0-40 cm recorded the highest nutrient deficiency. It is suggested that fluctuating water table influence the soil nutrient dynamics and soil nutrient balance and in this case act as the main pathways of nutrient loss through leaching.
From interactive teaching to immersive learning: Higher Education 4.0 via 360-degree videos and virtual reality in Malaysia
Authors: Adnan A H M
Published: September 2020

Higher Education 4.0 deals with the spread of technologies and espouses the notion that today’s learners need to be trained and not merely taught by rote and memorisation drills. The present is a period whereby data and information must be made accessible and open 24/7 so that learners can learn about how to find knowledge rather than to wait to be spoon-fed from their instructor’s textbooks. Higher Education 4.0 is contingent upon the concept of ‘immersive learning’ to afford learners with an educational atmosphere that is exceedingly interactive at the physical and virtual levels. Hence, immersive learning experiences could replicate possible scenarios that learners will face in real life and impart specific techniques or skills based on their different academic syllabuses. Employing immersive learning experiences that incorporate 360-degree real life videos and VR technologies to remote teach advanced communication skills to technical and vocational students at several public universities in Malaysia, this research paper highlights the fact that novel learning technologies and immersive learning experiences are not merely fads of Higher Education 4.0. Rather, they are glimpses of tomorrow’s world, based on quantitative and qualitative data collected from end-users (Malaysian university students) of a learning innovation initiative called ‘ELSA 360°-Videos’.
Digital Backpropagation Based on DOPC in Fiber Impairments Mitigation
Authors: Lawan S H , Mohd Noor M Y , Farabi M A , Supa’at A S M , Babale S A , Mohammed S G , Daura L U
Published: September 2020

This paper presents the study on the impact of the nonlinear phase shift on the performance of optical transmission systems and its suppression using digital backpropagation (DBP) technique. The proposed DBP employed digital optical phase conjugation (DOPC) at the receiver and a virtual fiber, thereby having the combined benefits of DBP and optical phase conjugation. Optical signal propagation was achieved by solving the nonlinear Schrödinger equation (NLSE) using the split-step Fourier method (SSFM). Implementation of DBP was conducted on 100-Gbps, DP-16QAM systems and it has demonstrated its efficacy in suppressing nonlinear phase shift, by improving the minimum bit error rate (BER) from 1 × 10−2 to 6.1 × 10−5.
Optimization of Two-Dimensional Finite Element on Primary Bone Type-7 Fracture Model
Authors: Mansor N N , Ishak M I , Daud R
Published: September 2020

Optimization works is an important method for Finite Element (FE) analysis to get better accuracy in simulation study before proceed for further analysis. In this present work, convergence study of local crack tip meshing involving radius of first row element, a/n (DELR) and number of crack tip element (NTHET) is employed on single edge crack in homogenous properties of human cortical bone. Mode I and Mode II Type -7 penetration were determined by using FE analysis and compared with the experimental results. Based on the results, a good agreement is found between numerical and experimental results. The first section in your paper
Motorcyclist Perceptions on Road Safety Considering Awareness, Riding Behavior, and Risk-Taking Behavior, as Latent Variables
Authors: Alvisyahri Alvisyahri , Anggraini Renni , Sugiarto Sugiarto
Published: September 2020

World Health Organization (WHO) reported in 2018, as many as 74% of the death tolls of road users in Indonesia derived from motorcycle riders. Factors causing traffic accidents originate commonly from humans, vehicles, and roads, in which human factor stands on top. One of the most significant contributor areas to traffic accidents in Indonesia was Aceh Province, because of risky riding behavior. This study aimed to investigate the motorcyclist perception toward road safety according to awareness, riding behavior, and risk-taking behavior, as latent variables. Primary data was collected by distributing questionnaires among motorcyclists in Banda Aceh City, Aceh Province. The questionnaire structure consisted of 2 parts, i.e., motorcyclist characteristics and motorcyclist perceptions using latent variables. The analysis utilized the Confirmatory Factor Analysis of the Structural Equation Model. The results showed that the risk-taking behavior was positively influenced by riding behavior, and the awareness of motorcycle rider affected the riding behavior positively. In terms of indicator affecting the latent variable was, parking close to the intersection showed the highest contribution to riding behavior. In sum, the model constitutes as good fit.
Analysis of the Trans Koetaradja bus services considering latent variables of bus line services
Authors: Irvansyah R , Sugiarto S , Achmad A , Fahlevi H
Published: September 2020

The Government of Aceh delivers a transport policy measure to combat autos dependency and severe traffic within the city by reforming conventional urban public transportation to modern bus system so-called the Trans Koetaradja (TK). The most critical issue for urban bus system is in how to maintenance existing users and attract new ridership’s. In this case, perceived service quality (PSQ) elements such as the easiness, comfort, and safety of bus system has an importance rule in determining user’s satisfaction. The PSQ is used in public transport planning and operation as a tool to establish the level of overall user’s satisfaction towards public transport services. Therefore, this study aims to examine the PSQ of the TK bus services by considering unobserved variable such as psychological indicators related to the bus line services from TK’s users. Revealed preference survey within 3 lines of TK was conducted in the mid of 2019. On board survey with a total of 450 samples were distributed and valid used in this study. The multivariate analysis of structural equation modelling so-called confirmatory factor analysis (CFA) is used to deeply explore the behavioral intention of TK users toward the bus service attributes. The CFA result depicts that PSQ resulted to higher user’s satisfaction has significantly statistical relationship with the user intention to the bus services variables of “obedience when stopped”, “driver appearance”, “air condition”, “bus arrival time” and “the satisfaction of supporting bus facilities”.
Interactive model for DNA specificity and selectivity and biosensor validation
Authors: Dhahi Th. S. , Adam Tijjan , Hashim U.
Published: September 2020

Specific and selective detection of biomolecule has become major research quest of scientist community, most diseases are curable however, early specific detection and selective nature determine this capabilities, thus need rogue sensor specificity and selectivity testing. Sensor specificity/selectively largely depend on the robust validation approach adopted. This paper presents the interactive Model for DNA Specificity and Selectivity in Biosensor Validation. The partial charge induced due to hybridization of complementary ssDNAs caused a significant change in the conductance of sensor specific potential. The interactive model of inorganic and organic behaviour was calculated based on first principle. The partial charge due to ssDNA and dsDNA molecule was computed using molecular dynamics (MD) simulation. The results show that, the full and identification of compliment, mismatched with precise sequence of acid bonds with specific time response of 1016 and 1020 for 0.0095 ns, 0.008nS respectively. With this fast and accurate response, the model could be used for the biosensor validation.
Correlation Impact by Random Forest Towards Prediction of Phishing Website
Authors: Mardhiah Ishak Ainin , Mustapha Aida , Zulkarnain Syed Idrus Syed , Helmy Abd Wahab Mohd , Mostafa Salama A
Published: September 2020

Phishing is an online identity theft that lure unsuspecting victims into phishing website that asks for their personal information such as financial credentials or online access. The most obvious phishing attacks use spam emails to lure victims into visiting its phishing website. The less obvious attack is when a phisher spoofes legitimate sites to bring the victims to the phishing website by presenting a visually similar websites. To address this issue, this paper focuses on the effectiveness of the Random Forest algorithm in predicting a website whether a phishing or lieitimate website. The prediction model is developed using the classfication methodology and the results revealed that the prediction accuracy of Random Forest in only 66.66%. This is due to potential high correlation among the features when training the dataset since each Random Tree in the forest should protect each other from individual errors. In the future, this project is hoped to investigate features selection of the same dataset because the phishing website prediction model requires features that at least some predictive power.
Crude Oil Price Forecasting Using Hybrid Support Vector Machine
Authors: Jo Xian Lee , Ismail Shuhaida , Mustapha Aida , Helmy Abd Wahab Mohd , Zulkarnain Syed Idrus Syed
Published: September 2020

Crude oil price is strongly impacting the world economy. However, it is very fluctuated and difficult for investor to make decision. Hence, forecasting is one of the ways to minimizing risks arise from indecision on future. This paper will apply Support Vector Machine (SVM) and Artificial Neural Network (ANN) and a proposed hybrid model name Empirical mode decomposition-Support Vector Machine (EMD-SVM) forecasting crude oil price. After obtaining the forecasting result, performance evaluation is carry out to show which method can better forecast the crude oil price. The result shows that the performance of cruel oil price forecasting can be significantly increased by using the proposed hybrid EMD-SVM model. Thus proven the hybrid model are out-perform than individual forecasting model.
A New Perspective on Visualising EEG Signal of Post-Stroke Patients
Authors: QiHan PW , Alipal J , Suberi AAM , Fuad N , Helmy Abd Wahab Mohd , Zulkarnain Syed Idrus Syed
Published: September 2020

To date, numerous methods have been developed in response to the EEG signal classification of post-stroke patients, among which feature extraction methods are of particular interest. This paper presents a new perspective on the visualisation of the EEG signal of different post-stroke patients in the image representation that can be used to assist in the classification phase. The new perspective for extracting and visualising EEG sub-band features considers the sequential application of power spectral density (PSD) represented in the kernel distribution estimation (KDE) of the PSD manifold. Experiments conducted on 45 post-stroke patients; 14 early, 17 intermediate and 14 advanced patients demonstrated the potential of the proposed perspective to estimate significant parameters under spectral pattern image representation. Visual representation of this new approach shows that the pattern and relationship of post-stroke patients can be clearly visualised. Significant performance can be achieved by classifying post-stroke patients into early-advanced or early intermediate classes as they reach a perfect dissimilarity score, r = 1.00. In the meantime, the absence of beta or theta in pairs has relatively consistent performance in classifying post-stroke patients using sub-bands, and the combination of the two has shown the worst results among other pairs. This paradigm should be included in the future context of the EEG signal classification of post-stroke classes, which could better explain the importance of image representation while improving the accuracy of the specified network.
A Review of Human Graphology Analysis and Brainwaves
Authors: Akila N F , M Nasir E M N E , Fuad N , Helmy Abd Wahab Mohd , Zulkarnain Syed Idrus Syed
Published: September 2020

This paper will do a study about brain, electroencephalograph (EEG) and also brainwriting. There are four types of frequency bands produces by human brain like delta, alpha, beta and theta. Every bands have their own spectrum of frequency where it be used for analysing brain activities. Electroencephalogram (EEG) is a method to measure signal by studying and evaluating the pattern of the brainwaves. The neuron will transfer the signals in the brain and the populations of neurons form pattern of network that form a brainwaves detectable in EEG. While graphology analysis is about the handwriting pattern that will illustrate the personality traits of the person. Everything that is written by the hand is processed from brain where is can give certain frequency bands or waveform for the personality.
A Study of Named Data Networking as Communication Protocol for Multi-hop Wireless Ad Hoc Network
Authors: Muchtar Farkhana , Lukuman Saheed Ajibade , Helmy Abd Wahab Mohd , Zulkarnain Syed Idrus Syed
Published: September 2020

Named Data Networking (NDN) has been repeatedly quoted in numerous past and existing literature reviews to have replaced Host Centric Networking (HCN) due to its ability to solve energy efficiency issues inherent in Multi-hop Wireless Ad-hoc Networks (WAHN). However, this claim is proven to be wholly unsubstantiated and is not justified by academic proof in said articles. Therefore, this study take the initiative to fill in this gap by presenting a comparative study of NDN based MWAHN and HCN based MWAHN through the use of real implementation by measuring two parameter metric that are related to energy efficiency, namely energy consumption and file transfer completion time. For this study, NDN-based MWAHN is compared with two type of actively developed HCN routing protocol implementation, namely Babeld and BMX6. The results obtained from this experiment is crucial for MWAHN researchers to gain better understanding of the real potential of the NDN based routing that can be used as a solution for energy consumption issues that exist in wireless multi-hop ad-hoc network.
Bluetooth Based Indoor Navigation System
Authors: Uttraphan C. , Abdul Aziz F. , Helmy Abd Wahab Mohd , Zulkarnain Syed Idrus Syed
Published: September 2020

The navigation system has been around for many years in terms of map and simple navigation control, and only recently has technology caught up in the idea of the interconnected world, allowing full assist of navigating from one point to another becomes reality. Recently, the architecture of the shopping stores is getting more and more complex and it is hard for the consumers to find their desired store. As the satellite signal cannot be used inside the building, hence, in this project, we propose an indoor navigation system by using the Bluetooth low energy (BLE) signal. The BLE signal is emitted from every BLE beacon in the building and the receiver which is the smartphone will determine which of the beacon is the closest to the receiver and determine the user location. This technique is called fingerprint which is usually used for BLE beacon. The verification tests have been performed in UTHM where the lecture hall complex was used for the test. The results show that the proposed system is able to navigate to the destination accurately.
A Review: An Evaluation of Current Artificial Intelligent Methods in Traffic Flow Prediction
Authors: Rusyaidi Muhammad , Ibrahim Zunaidi
Published: September 2020

Modelling the flow of traffic is a growing issue for several city and traffic issues, using artificial intelligence to engineer as a better traffic system is the focus of artificial intelligence research. This paper, therefore, compares, analyzes and evaluates machine learning and deep learning in autonomous vehicle traffic flow prediction. Methods of machine learning and deep learning used by other researchers will be compared to each other to give results and suggestions based on their methods evaluation. The paper concludes with suggestions as to where the method would provide the most appropriate and effective technique for modern smart transport systems.
Modeling and Simulation of Blood Flow Analysis on Simplified Aneurysm Models
Authors: Sheh Hong Lim , Azrul Hisham Mohd Adib Mohd , Uzair Matalif Muhammad , Shafie Abdullah Mohd , Hartini Mohd Taib Nur , Hassan Radhiana
Published: September 2020

Nowadays, the cerebral aneurysm is an abnormal focal dilation of a brain artery which is considered as a serious and potentially life-threatening condition. The rupture of an aneurysm causes subarachnoid hemorrhage (SAH) and is associated with high rates of morbidity and mortality. A better understanding of the mechanisms underlying aneurysm pathophysiology is crucial for the development of new preventive procedures and therapeutic strategies. This study focuses on the modeling and simulation of the blood flow analysis using simplified aneurysm models to perform early prediction on the geometrical effects of hemodynamics. The investigation involves three simplified models of aneurysms reconstructed using Solidworks 2019, in which the aneurysms are developed at the bifurcation. The qualitative comparison of the hemodynamics between three models was obtained and the geometrical effects were evaluated. The results show that the differences in shape and geometry on aneurysms affect the hemodynamics trend and are capable to apply for further understanding of problems regarding hemodynamics in the patient.
Design Woodball Line Detection and Monitoring System: A Preliminary Study
Authors: Chandrasegaran Janathnan , Azani Mustafa Wan , Aminudin Jamlos Mohd , Zulkarnain Syed Idrus Syed
Published: September 2020

This paper entails the incorporation of electronics in the sports of woodball. The decisions made by the referees in most sports nowadays are with the use of electronic technologies to assist them. For instance, the goal-line technology in football and the electronic line judge in tennis is some of the recent advances in electronic technologies that have revolutionized sports as we know it. The woodball line detection and monitoring system serves a similar purpose where it assists the referee in making decisions and modernize the sports of woodball. The current woodball sports depend entirely on referees to give out decisions. The line detection technology helps to notify the referee if the woodball is Out of Bounds (OB) whereas the monitoring system notifies the player, referee and the audience whether the gating is successful or not. However, manual assistance from the referee is still needed for starting the play after a successful gating because the player is not allowed to touch the woodball during the entire game.
Exploratory of Electrical Learning Kit for STEM Application
Authors: Basar M.F. , Zulkarnain I. A. , Razik N.H.A. , Zakaria Z. , Mustafa W.A. , Zulkarnain Syed Idrus Syed , Aminudin Jamlos Mohd
Published: September 2020

Throughout the year, the implementation of the traditional approach (lecture-based) in the teaching and learning process seems to be less effective in increasing the interest among students towards the STEM subjects. Conversely, the use of practical learning method emphasizes on the psychomotor domain so that readers gain a clearer and more effective understanding. Thus, the aim of this paper is to investigate and exploratory the unique approach in implementation the learning kit where the students will increase their understanding towards the fundamental of electrical engineering. The effects that influenced the development process of learning kit is discussed and provided the ideas to build a quality learning kit for students who involved in STEM.
UAV Based Image Acquisition Data for 3D Model Application
Authors: Saifizi M. , Azani Mustafa Wan , Syahirah Mohammad Radzi Nur , Aminudin Jamlos Mohd , Zulkarnain Syed Idrus Syed
Published: September 2020

The UAV mapping has a huge potential for a number of sectors including construction, agriculture, mining, infrastructure inspection and real estate. The demand for high quality aerial data capture from UAVs or unmanned aerial vehicle (UAV) is growing fast and increase rapidly. In civil application, UAVs are used as an assisting tools for a large scale aerial mapping of the building which in general it’s a challenging task for surveyor to do because of the unreachable access area, time consuming and often cost expensive due to the limited resources and equipment. In this thesis, the UAV based mapping is introduce to overcome this problem. The selected place to do the research is the building around Taman Sri Layang, Mentakab Pahang. A flight mission plan was developed in two path that is path A and path B and uploaded in UAV. In this study, the DJI Mavic Pro drone is used to do the mapping process. Besides that, the UAV will capture and collecting visual image when flying from different flight path. Both flight path covers 6 acres area, with 80% overlap and 70% side lap. The total picture is captured using path A and path B around 157 and 147 figures respectively.
Multiple Fusions Approach for Keystroke Dynamics Verification System with Soft Biometrics
Authors: Noorulfakhri Yaacob Mohd , Zulkarnain Syed Idrus Syed , Azani Mustafa Wan , Aminudin Jamlos Mohd , Helmy Abd Wahab Mohd
Published: September 2020

Computer security is a process that controls the entire information system, including network, system and hardware. Important information that must be controlled in a system is the data or information contained in a system. Various methods have been used to ensure that only users with legitimate access to data can use a system. Usernames and passwords have been a common practice by many systems as the first requirement to be fulfilled to access the system, but some systems use the secondary verification for additional confirmation. In this article, Keystroke Dynamics has been used as the user’s second level authentication for the systems that use the keyboard to login into a system. A common problem of system intrusions is that the system fails to identify the user who signs in using the keyboard when the login is correct. There is a possibility that someone else tries to break into the system. To ensure and improve users’ recognition who use the keyboard to enter their logins into the system, Keystroke Dynamics is used as a next-level verification if the login is correct. Soft biometrics is used in the user authentication process using KD method in this study. The soft biometric elements used in this study are culture, gender, educational level (CGPA - Cumulative Grade Point Average) and region of birth (ROB). All of these four soft biometric elements are expected to enhance capabilities in the user authentication process.
Analysis of Rectangular Flexible Horizontal Piezoelectric Cantilever Beam Base on ANSYS
Authors: Deraman A S , Niirmel R , Mohamad M R
Published: September 2020

This paper presents the analysis of energy harvester by using rectangular flexible piezoelectric cantilever beam in which applied on sea wave. The limitation of blade design is it only focus on single direction flow of sea wave motion. The finite element model is constructed by using ANSYS to optimize the blade design to maximize the output power. The analysis of rectangular flexible piezoelectric design shows the ability to generate variable of electric power from minimum 20 µW up to 141.30 µW, with dimension of width, length, height of piezo is 10 mm, 30 mm, 0.10 mm and amplitude of sea wave surface of 1.5 m respectively.