Displaying publications 41 - 60 of 371 in total

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  1. Muhammad Naim Mazani, Shuzlina Abdul-Rahman, Sofianita Mutalib
    ESTEEM Academic Journal, 2020;16(1):74-85.
    MyJurnal
    This study presents pre-processing methods for detecting lane detection using camera and Light Detection and Ranging (LiDAR) sensor technologies. Standard image processing methods are not suitable for complicated roads with various sign on the ground. Thus, determining the right techniques for pre-processing such data would be a challenge. The objectives of this study are to pre-process the scanned images and apply the image recognition algorithm for lane detection. The study employed Canny Edge Detection and Hough Transform algorithms on several sets of images. A different region of interest was experimented to find the optimal one. The experimental results showed that the proposed algorithms could be practical in terms of effectively detecting road lines and generate lane detection.
    Matched MeSH terms: Data Collection
  2. Khairur Rijal Jamaludin, Nolia Harudin, Faizir Ramlie, Mohd Nabil Muhtazaruddin, Che Munira Che Razali, Wan Zuki Azman Wan Muhamad
    MATEMATIKA, 2020;36(1):69-84.
    MyJurnal
    Prediction analysis has drawn significant interest in numerous field. Taguchi’s T-Method is a prediction tool that developed practically but not limited to small sample analysis. It was developed explicitly for multidimensional system prediction by relying on historical data as the baseline model and adapting the signal to noise ratio (SNR) as well as zero proportional concepts in strengthening its robustness. Orthogonal array (OA) in T-Method is a variable selection optimization technique in improving the prediction accuracy as well as help in eliminating variables that may deteriorate the overall performance. However, the limitation of OA in dealing with higher multidimensionality restraint the optimization accuracy. Binary particle swarm optimization used in this study helps to cater to the limitation of OA as well as optimizing the variable selection process to better prediction accuracy. The results show that if the historical data consist of samples with higher correlation of determination (R2) value for the model creation, the optimization process in reducing the number of variables would be much reliable and accurate. Comparing between T-Method+OA and T-Method+BPSO in four different case study, it shows that T-Method+BPSO performing better with greater R2 and means relative error (MRE) value compared to T-Method+OA.
    Matched MeSH terms: Data Collection
  3. JEFFREY, YEE KHONG LOONG
    MyJurnal
    The research interview is a common method of choice for collecting data, particularly within the qualitative research tradition. This is because it lends well to the emergent nature and exploratory aims of qualitative research. Detailed accounts of what and how things happened, and who was involved, that is elaborate stories, can be located in interview responses. This is irrespective of whether or not the stories were deliberately elicited or regardless of the methodological stance adopted by the researcher. The ubiquity of stories therein signals the need for researchers using qualitative interviews to be cognizant of the narratives surrounding these stories and the analytical value they hold in their research. This paper presents the philosophical underpinnings and strategy of narrative inquiry, and illustrates how methods of collection and analysis can be shaped in concert with the methodology
    Matched MeSH terms: Data Collection
  4. Sathasivam, Saratha, Mustafa Mamat, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor
    MyJurnal
    Clonal selection algorithm and discrete Hopfield neural network are extensively employed for solving higher-order optimization problems ranging from the constraint satisfaction problem to complex pattern recognition. The modified clonal selection algorithm is a comprehensive and less iterative immune-inspired searching algorithm, utilized to search for the correct combination of instances for Very large-scale integrated (VLSI) circuit structure. In this research, the VLSI circuit framework consists of Boolean 3-Satisfiability instances with the different complexities and number of transistors are considered. Hence, a hybrid modified clonal selection algorithm with discrete Hopfield neural network is well developed to optimize the configuration of VLSI circuits with different number of electronic components such as transistors as the instances. Therefore, the performance of the developed hybrid model was assessed experimentally with the standard models, HNNVLSI-3SATES and HNNVLSI-3SATGA in term of circuit accuracy, sensitivity, robustness and runtime to complete the verification process. The results have demonstrated the developed model, HNNVLSI-3SATCSA produced a minimum error (consistently approaching 0), better accuracy (more than 80%) and faster computational time (less than 125 seconds) against changes in the complexity in term of the number of transistors. Furthermore, the developed hybrid model is able to minimize the computational burden and configurational noises for the variant of VLSI circuits.
    Matched MeSH terms: Data Collection
  5. Hamdan, Sinin, Ahmad Faudzi Musib, Musoddiq, Iran Amri, Marini Sawawi
    MyJurnal
    Gamelan in general is categorized as a group of gongs. This traditional Malay gamelan ensemble is in a slendro scale i.e. five notes per octave. The rhythms, pitch, duration and loudness classify the various groups of gongs such as bonang, kenong, gender, peking and gambang. The cast bronze peking, kenong and bonang were chosen from a range of Malay gamelan ensemble from Universiti Malaysia Sarawak (UNIMAS), Universiti Putra Malaysia (UPM), Universiti Kebangsaan Malaysia (UKM) and Universiti Teknologi Mara (UiTM). The sounds were recorded by PicoScope Oscilloscope. The PicoScope software displays waveform and spectrum in time and frequency domain respectively. The peking lowest and highest frequencies from UiTM were 293 Hz and 1867 Hz, from UPM were 644 Hz and 1369 Hz, from UKM were 1064 Hz and 2131 Hz and from UNIMAS were 1072 Hz and 2105 Hz respectively. The kenong lowest and highest frequencies from UiTM were 259 Hz and 463 Hz, from UPM were 294 Hz and 543 Hz, from UKM were 300 Hz and 540 Hz and from UNIMAS were 293 Hz and 519 Hz respectively. The fundamental frequencies of bonang from UPM were higher than that of UKM, UiTM and UNIMAS. The harmonics were not successive but interrupted by another frequency. The harmonics of each bonang was similar except for gamelan from UKM.
    Matched MeSH terms: Data Collection
  6. Al-Hadi IAA, Sharef NM, Sulaiman MN, Mustapha N, Nilashi M
    PeerJ Comput Sci, 2020;6:e331.
    PMID: 33816980 DOI: 10.7717/peerj-cs.331
    Recommendation systems suggest peculiar products to customers based on their past ratings, preferences, and interests. These systems typically utilize collaborative filtering (CF) to analyze customers' ratings for products within the rating matrix. CF suffers from the sparsity problem because a large number of rating grades are not accurately determined. Various prediction approaches have been used to solve this problem by learning its latent and temporal factors. A few other challenges such as latent feedback learning, customers' drifting interests, overfitting, and the popularity decay of products over time have also been addressed. Existing works have typically deployed either short or long temporal representation for addressing the recommendation system issues. Although each effort improves on the accuracy of its respective benchmark, an integrative solution that could address all the problems without trading off its accuracy is needed. Thus, this paper presents a Latent-based Temporal Optimization (LTO) approach to improve the prediction accuracy of CF by learning the past attitudes of users and their interests over time. Experimental results show that the LTO approach efficiently improves the prediction accuracy of CF compared to the benchmark schemes.
    Matched MeSH terms: Data Collection
  7. Noor Adilah Hamzah, Ahmad Rasdan Ismail, Nor Kamilah Makhtar, Khairul Azhar Mat Daud, Norhidayah Mat Sout
    MyJurnal
    Today, more accidents reported in school, resulting not only minor injuries but also severe injuries such as fire in schools, mercury spills and falling from high places. The study was aimed at measuring the level of occupational safety and health practices in schools. The study was conducted at 205 schools in Kelantan, Malaysia. This study is a semi-quantitative study using observation method. Data collection is conducted based on Hazard Identification, Risk Assessment and Risk Control (HIRARC) Guidelines provided by the Department of Occupational Safety and Health, Malaysia. Hazard identification, risk assessment and risk control are determined using the HIRARC form. The findings were measured by determining the discrete data according to the number of low, medium and high-risk levels found. The study found that there were two dominant hazards namely physical hazard and ergonomic hazard. Therefore, the management should increase and improve classroom safety awareness to ensure safety and health of all occupants.
    Matched MeSH terms: Data Collection
  8. Mosavi A, Shokri M, Mansor Z, Qasem SN, Band SS, Mohammadzadeh A
    Entropy (Basel), 2020 Sep 18;22(9).
    PMID: 33286810 DOI: 10.3390/e22091041
    In this study, a new approach to basis of intelligent systems and machine learning algorithms is introduced for solving singular multi-pantograph differential equations (SMDEs). For the first time, a type-2 fuzzy logic based approach is formulated to find an approximated solution. The rules of the suggested type-2 fuzzy logic system (T2-FLS) are optimized by the square root cubature Kalman filter (SCKF) such that the proposed fineness function to be minimized. Furthermore, the stability and boundedness of the estimation error is proved by novel approach on basis of Lyapunov theorem. The accuracy and robustness of the suggested algorithm is verified by several statistical examinations. It is shown that the suggested method results in an accurate solution with rapid convergence and a lower computational cost.
    Matched MeSH terms: Data Collection
  9. Jaffari R, Hashmani MA, Reyes-Aldasoro CC
    Sensors (Basel), 2021 Apr 16;21(8).
    PMID: 33923472 DOI: 10.3390/s21082803
    The segmentation of power lines (PLs) from aerial images is a crucial task for the safe navigation of unmanned aerial vehicles (UAVs) operating at low altitudes. Despite the advances in deep learning-based approaches for PL segmentation, these models are still vulnerable to the class imbalance present in the data. The PLs occupy only a minimal portion (1-5%) of the aerial images as compared to the background region (95-99%). Generally, this class imbalance problem is addressed via the use of PL-specific detectors in conjunction with the popular class balanced cross entropy (BBCE) loss function. However, these PL-specific detectors do not work outside their application areas and a BBCE loss requires hyperparameter tuning for class-wise weights, which is not trivial. Moreover, the BBCE loss results in low dice scores and precision values and thus, fails to achieve an optimal trade-off between dice scores, model accuracy, and precision-recall values. In this work, we propose a generalized focal loss function based on the Matthews correlation coefficient (MCC) or the Phi coefficient to address the class imbalance problem in PL segmentation while utilizing a generic deep segmentation architecture. We evaluate our loss function by improving the vanilla U-Net model with an additional convolutional auxiliary classifier head (ACU-Net) for better learning and faster model convergence. The evaluation of two PL datasets, namely the Mendeley Power Line Dataset and the Power Line Dataset of Urban Scenes (PLDU), where PLs occupy around 1% and 2% of the aerial images area, respectively, reveal that our proposed loss function outperforms the popular BBCE loss by 16% in PL dice scores on both the datasets, 19% in precision and false detection rate (FDR) values for the Mendeley PL dataset and 15% in precision and FDR values for the PLDU with a minor degradation in the accuracy and recall values. Moreover, our proposed ACU-Net outperforms the baseline vanilla U-Net for the characteristic evaluation parameters in the range of 1-10% for both the PL datasets. Thus, our proposed loss function with ACU-Net achieves an optimal trade-off for the characteristic evaluation parameters without any bells and whistles. Our code is available at Github.
    Matched MeSH terms: Data Collection
  10. Chong BW, Othman R, Putra Jaya R, Mohd Hasan MR, Sandu AV, Nabiałek M, et al.
    Materials (Basel), 2021 Apr 09;14(8).
    PMID: 33918757 DOI: 10.3390/ma14081866
    Concrete mix design and the determination of concrete performance are not merely engineering studies, but also mathematical and statistical endeavors. The study of concrete mechanical properties involves a myriad of factors, including, but not limited to, the amount of each constituent material and its proportion, the type and dosage of chemical additives, and the inclusion of different waste materials. The number of factors and combinations make it difficult, or outright impossible, to formulate an expression of concrete performance through sheer experimentation. Hence, design of experiment has become a part of studies, involving concrete with material addition or replacement. This paper reviewed common design of experimental methods, implemented by past studies, which looked into the analysis of concrete performance. Several analysis methods were employed to optimize data collection and data analysis, such as analysis of variance (ANOVA), regression, Taguchi method, Response Surface Methodology, and Artificial Neural Network. It can be concluded that the use of statistical analysis is helpful for concrete material research, and all the reviewed designs of experimental methods are helpful in simplifying the work and saving time, while providing accurate prediction of concrete mechanical performance.
    Matched MeSH terms: Data Collection
  11. Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Bergauer T, Dragicevic M, et al.
    Phys Rev Lett, 2020 Aug 07;125(6):061801.
    PMID: 32845700 DOI: 10.1103/PhysRevLett.125.061801
    The first observation of the tt[over ¯]H process in a single Higgs boson decay channel with the full reconstruction of the final state (H→γγ) is presented, with a significance of 6.6 standard deviations (σ). The CP structure of Higgs boson couplings to fermions is measured, resulting in an exclusion of the pure CP-odd structure of the top Yukawa coupling at 3.2σ. The measurements are based on a sample of proton-proton collisions at a center-of-mass energy sqrt[s]=13  TeV collected by the CMS detector at the LHC, corresponding to an integrated luminosity of 137  fb^{-1}. The cross section times branching fraction of the tt[over ¯]H process is measured to be σ_{tt[over ¯]H}B_{γγ}=1.56_{-0.32}^{+0.34}  fb, which is compatible with the standard model prediction of 1.13_{-0.11}^{+0.08}  fb. The fractional contribution of the CP-odd component is measured to be f_{CP}^{Htt}=0.00±0.33.
    Matched MeSH terms: Data Collection
  12. Hayashi Y, Shirotori K, Kosugi A, Kumada S, Leong KH, Okada K, et al.
    Pharmaceutics, 2020 Jun 28;12(7).
    PMID: 32605318 DOI: 10.3390/pharmaceutics12070601
    We previously reported a novel method for the precise prediction of tablet properties (e.g., tensile strength (TS)) using a small number of experimental data. The key technique of this method is to compensate for the lack of experimental data by using data of placebo tablets collected in a database. This study provides further technical knowledge to discuss the usefulness of this prediction method. Placebo tablets consisting of microcrystalline cellulose, lactose, and cornstarch were prepared using the design of an experimental method, and their TS and disintegration time (DT) were measured. The response surfaces representing the relationship between the formulation and the tablet properties were then created. This study investigated tablets containing four different active pharmaceutical ingredients (APIs) with a drug load ranging from 20-60%. Overall, the TS of API-containing tablets could be precisely predicted by this method, while the prediction accuracy of the DT was much lower than that of the TS. These results suggested that the mode of action of APIs on the DT was more complicated than that on the TS. Our prediction method could be valuable for the development of tablet formulations.
    Matched MeSH terms: Data Collection
  13. SAUD AMERROUF SIAN, TERRY LUCAS
    MyJurnal
    When we heard Retro design, people will think about the fashion, music, poster, style and trend of the 1940s to1980s. The trend retro-futurism, however, is entirely different. It is a trend that was created by writers, artists and film directors in the past and is closely related to science fiction. This research concentrates on investigating the characteristics of retro-futurism and how it can be used to incorporate its features into building design for 3D animation. An exploratory method was used to analyse the architectural design of the past. The gathered information could give some insights and understanding of what retro-futurism is and the reason behind why the architectural design in the previous era was created that way. The process and challenges of implementing retro-futurism visual style are also discussed. As the result of the collected data, developing a design with the aesthetic of retro-futurism become more accessible and well-planned.
    Matched MeSH terms: Data Collection
  14. Nurhafizah Moziyana Mohd Yusop, Nooraida Samsudin, Nooraida Samsudin, Anis Shahida Mokhta, Siti Rohaidah Ahmad, Mohd Fahmi Mohammad Amran, et al.
    MyJurnal
    Euler method is a numerical order process for solving problems with the Ordinary Differential Equation (ODE). It is a fast and easy way. While Euler offers a simple procedure for solving ODEs, problems such as complexity, processing time and accuracy have driven others to use more sophisticated methods. Improvements to the Euler method have attracted much attention resulting in numerous modified Euler methods. This paper proposes Cube Polygon, a modified Euler method with improved accuracy and complexity. In order to demonstrate the accuracy and easy implementation of the proposed method, several examples are presented. Cube Polygon’s performance was compared to Polygon’s scheme and evaluated against exact solutions using SCILAB. Results indicate that not only Cube Polygon has produced solutions that are close to identical solutions for small step sizes, but also for higher step sizes, thus generating more accurate results and decrease complexity. Also known in this paper is the general of the RL circuit due to the ODE problem.
    Matched MeSH terms: Data Collection
  15. Jayaprakasam S, Abdul Rahim SK, Leow CY, Ting TO
    PLoS One, 2017;12(5):e0175510.
    PMID: 28464000 DOI: 10.1371/journal.pone.0175510
    Collaborative beamforming (CBF) with a finite number of collaborating nodes (CNs) produces sidelobes that are highly dependent on the collaborating nodes' locations. The sidelobes cause interference and affect the communication rate of unintended receivers located within the transmission range. Nulling is not possible in an open-loop CBF since the collaborating nodes are unable to receive feedback from the receivers. Hence, the overall sidelobe reduction is required to avoid interference in the directions of the unintended receivers. However, the impact of sidelobe reduction on the capacity improvement at the unintended receiver has never been reported in previous works. In this paper, the effect of peak sidelobe (PSL) reduction in CBF on the capacity of an unintended receiver is analyzed. Three meta-heuristic optimization methods are applied to perform PSL minimization, namely genetic algorithm (GA), particle swarm algorithm (PSO) and a simplified version of the PSO called the weightless swarm algorithm (WSA). An average reduction of 20 dB in PSL alongside 162% capacity improvement is achieved in the worst case scenario with the WSA optimization. It is discovered that the PSL minimization in the CBF provides capacity improvement at an unintended receiver only if the CBF cluster is small and dense.
    Matched MeSH terms: Data Collection
  16. Ahmed AA, Xue Li C
    J Forensic Sci, 2018 Jan;63(1):112-121.
    PMID: 28397244 DOI: 10.1111/1556-4029.13506
    Cloud storage service allows users to store their data online, so that they can remotely access, maintain, manage, and back up data from anywhere via the Internet. Although helpful, this storage creates a challenge to digital forensic investigators and practitioners in collecting, identifying, acquiring, and preserving evidential data. This study proposes an investigation scheme for analyzing data remnants and determining probative artifacts in a cloud environment. Using pCloud as a case study, this research collected the data remnants available on end-user device storage following the storing, uploading, and accessing of data in the cloud storage. Data remnants are collected from several sources, including client software files, directory listing, prefetch, registry, network PCAP, browser, and memory and link files. Results demonstrate that the collected remnants data are beneficial in determining a sufficient number of artifacts about the investigated cybercrime.
    Matched MeSH terms: Data Collection
  17. Fakhrul Syafiq, Huzaifah Ismail, Hazleen Aris, Syakiruddin Yusof
    MyJurnal
    Widespread use of mobile devices has resulted in the creation of large amounts of data. An example of such data is the one obtained from the public (crowd) through open calls, known as crowdsourced data. More often than not, the collected data are later used for other purposes such as making predictions. Thus, it is important for crowdsourced data to be recent and accurate, and this means that frequent updating is necessary. One of the challenges in using crowdsourced data is the unpredictable incoming data rate. Therefore, manually updating the data at predetermined intervals is not practical. In this paper, the construction of an algorithm that automatically updates crowdsourced data based on the rate of incoming data is presented. The objective is to ensure that up-to-date and correct crowdsourced data are stored in the database at any point in time so that the information available is updated and accurate; hence, it is reliable. The algorithm was evaluated using a prototype development of a local price-watch information application, CrowdGrocr, in which the algorithm was embedded. The results showed that the algorithm was able to ensure up-to-date information with 94.9% accuracy.
    Matched MeSH terms: Data Collection
  18. Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Asilar E, Bergauer T, et al.
    Phys Rev Lett, 2018 Oct 05;121(14):141801.
    PMID: 30339440 DOI: 10.1103/PhysRevLett.121.141801
    This Letter presents the observation of the rare Z boson decay Z→ψℓ^{+}ℓ^{-}. Here, ψ represents contributions from direct J/ψ and ψ(2S)→J/ψX, ℓ^{+}ℓ^{-} is a pair of electrons or muons, and the J/ψ meson is detected via its decay to μ^{+}μ^{-}. The sample of proton-proton collision data, collected by the CMS experiment at the LHC at a center-of-mass energy of 13 TeV, corresponds to an integrated luminosity of 35.9  fb^{-1}. The signal is observed with a significance in excess of 5 standard deviations. After subtraction of the ψ(2S)→J/ψX contribution, the ratio of the branching fraction of the exclusive decay Z→J/ψℓ^{+}ℓ^{-} to the decay Z→μ^{+}μ^{-}μ^{+}μ^{-} within a fiducial phase space is measured to be B(Z→J/ψℓ^{+}ℓ^{-})/B(Z→μ^{+}μ^{-}μ^{+}μ^{-})=0.67±0.18(stat)±0.05(syst).
    Matched MeSH terms: Data Collection
  19. Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Asilar E, Bergauer T, et al.
    Phys Rev Lett, 2018 Sep 21;121(12):121801.
    PMID: 30296133 DOI: 10.1103/PhysRevLett.121.121801
    The observation of the standard model (SM) Higgs boson decay to a pair of bottom quarks is presented. The main contribution to this result is from processes in which Higgs bosons are produced in association with a W or Z boson (VH), and are searched for in final states including 0, 1, or 2 charged leptons and two identified bottom quark jets. The results from the measurement of these processes in a data sample recorded by the CMS experiment in 2017, comprising 41.3  fb^{-1} of proton-proton collisions at sqrt[s]=13  TeV, are described. When combined with previous VH measurements using data collected at sqrt[s]=7, 8, and 13 TeV, an excess of events is observed at m_{H}=125  GeV with a significance of 4.8 standard deviations, where the expectation for the SM Higgs boson is 4.9. The corresponding measured signal strength is 1.01±0.22. The combination of this result with searches by the CMS experiment for H→bb[over ¯] in other production processes yields an observed (expected) significance of 5.6 (5.5) standard deviations and a signal strength of 1.04±0.20.
    Matched MeSH terms: Data Collection
  20. Md Jais Ismail
    MyJurnal
    This study is designed in qualitative form which focuses on musical coordination skill that is sing and
    clapping rhythm simultaneously in meter . The researcher used one of music teaching method which
    is Dalcroze Approach as an intervention in this study. Dalcroze Approach is a method which relates
    musical concepts with movement. Research sample is among Year 4 students aged 10 years old from
    different sex and race. Data have been collected through observation and interview. A comprehension
    exam is conducted as a supplementary data collection. Findings show the students have achieved good
    result in music coordination skill after the implementation of the Dalcroze Approach. Observation
    revealed that all the students have increase their coordination skill in singing and clapping the rhythm simultaneously. Interview which is conducted on students found 60 percent of them are very confident
    to do the skill as well. The result of comprehension exam shows 73 percent of students score A which
    can be described as excellent. Researcher wish to have further study in developing the music
    coordination skill by improving the intervention of the study.
    Matched MeSH terms: Data Collection
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