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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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).
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.
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.
The main purpose of this article is to introduce the technique of panel data analysis in econometrics modeling. The elasticity of labour, capital and economic of scale for twenty two food manufacturing firms covering from 1989 to 1993 is estimated using the Cobb-Douglas model. The three main techniques of panel data analysis discussed are least square dummy variables (LSDV), analysis of covariance (ANCOVA) and generalized least square (GLS). Ordinary Least Square (OLS) method is included as the basis of comparison.
A search for the Higgs boson decaying to two oppositely charged muons is presented using data recorded by the CMS experiment at the CERN LHC in 2016 at a center-of-mass energy sqrt[s]=13 TeV, corresponding to an integrated luminosity of 35.9 fb^{-1}. Data are found to be compatible with the predicted background. For a Higgs boson with a mass of 125.09 GeV, the 95% confidence level observed (background-only expected) upper limit on the production cross section times the branching fraction to a pair of muons is found to be 3.0 (2.5) times the standard model expectation. In combination with data recorded at center-of-mass energies sqrt[s]=7 and 8 TeV, the background-only expected upper limit improves to 2.2 times the standard model value with a standard model expected significance of 1.0 standard deviation. The corresponding observed upper limit is 2.9 with an observed significance of 0.9 standard deviation. This corresponds to an observed upper limit on the standard model Higgs boson branching fraction to muons of 6.4×10^{-4} and to an observed signal strength of 1.0±1.0(stat)±0.1(syst).
Clustering is basically one of the major sources of primary data mining tools. It makes
researchers understand the natural grouping of attributes in datasets. Clustering is an
unsupervised classification method with the major aim of partitioning, where objects in the
same cluster are similar, and objects which belong to different clusters vary significantly,
with respect to their attributes. However, the classical Standardized Euclidean distance,
which uses standard deviation to down weight maximum points of the ith features on the
distance clusters, has been criticized by many scholars that the method produces outliers,
lack robustness, and has 0% breakdown points. It also has low efficiency in normal
distribution. Therefore, to remedy the problem, we suggest two statistical estimators
which have 50% breakdown points namely the Sn and Qn estimators, with 58% and 82%
efficiency, respectively. The proposed methods evidently outperformed the existing methods
in down weighting the maximum points of the ith features in distance-based clustering
analysis.
A search is presented for a narrow resonance decaying to a pair of oppositely charged muons using sqrt[s]=13 TeV proton-proton collision data recorded at the LHC. In the 45-75 and 110-200 GeV resonance mass ranges, the search is based on conventional triggering and event reconstruction techniques. In the 11.5-45 GeV mass range, the search uses data collected with dimuon triggers with low transverse momentum thresholds, recorded at high rate by storing a reduced amount of trigger-level information. The data correspond to integrated luminosities of 137 and 96.6 fb^{-1} for conventional and high-rate triggering, respectively. No significant resonant peaks are observed in the probed mass ranges. The search sets the most stringent constraints to date on a dark photon in the ∼30-75 and 110-200 GeV mass ranges.