Retorik naratif dalam novel “Orang Kota Bharu”

Kajian ini merupakan penelitian secara tekstual dan kontekstual terhadap novel Orang Kota Bharu karya Sasterawan Negara S. Othman Kelantan. Tumpuan utama kajian ini adalah untuk mengenal pasti jenis retorik dan meneliti beberapa elemen retorik yang digunakan. Pengkaji memanfaatkan teori retorik moden oleh Enos dan Brown (1993) untuk menjelaskan makna kata yang halus sifatnya. Dapatan kajian menunjukkan bahawa pengarang mementingkan retorik jenis naratif untuk menyampaikan pemikiran beliau. Novel ini bertemakan sejarah masyarakat Kota Bharu selepas kemerdekaan negara dengan mengetengahkan beberapa isu politik, ekonomi, keagamaan dan sosial. Berdasarkan analisis elemen retorik, didapati pengarang memanfaatkan bahasa figuratif yang merangkumi elemen metafora, anafora, repeten, epifora, simile, personifikasi, hiperbola, dan hibrida dengan berkesan. Pemanfaatan elemen ini dalam penulisan novel menjadikan bahasa yang digunakan halus dan mendalam. Tahap pemikiran yang tinggi diperlukan untuk memastikan bahawa pembaca memahami maksud sebenar yang ingin disampaikan oleh pengarang

Titah ucapan pembukaan Dewan Undangan Negeri Kelantan oleh Sultan Muhammad V: satu analisis retorik

Kajian ini merupakan penelitian aspek retorik dalam titah ucapan KDYMM Sultan Muhammad V, Sultan Kelantan ke-29. Objektif kajian ini adalah untuk mengenal pasti teknik retorik dalam teks rasmi diraja, untuk menganalisis dan menghuraikan aspek penggunaan kosa kata, kekuatan dan keberkesanan seni pengucapan Sultan Muhammad V. Data kajian ini dianalisis secara kuantitatif untuk meneliti peratusan penggunaan teknik retorik, dan secara kualitatif, iaitu dengan huraian deskriptif teks berlandaskan prinsip ketiga teori retorik moden Enos dan Brown (1993), iaitu untuk memberikan kesan mendalam terhadap ujaran atau penulisan. Sebanyak 251 ayat telah dicerakinkan daripada tiga teks ucapan, di samping terdapat 27 jenis teknik retorik yang telah dikenal pasti dengan ditandai ungkapan tertentu berdasarkan kategori Lakuan Bahasa. Hasil kajian mendapati bahawa Sultan Muhammad V menggunakan beberapa elemen retorik dalam titah ucapannya, iaitu aliterasi, polisindeton, repitisi, soalan retorik, metafora, simile, alusi, dan kosa kata asing daripada bahasa Inggeris dan bahasa Arab. Teknik dan elemen yang dimanfaatkan dalam pengucapan ini mampu memberikan kesan terhadap kefahaman khalayak

A weighted-range classification model for localizing cell using crowdsource data

The vast amount of mobile smartphone users provides an infinite source of data for crowdsourcing. Crowdsourcing provides an economical method of gathering data to cover a large geographical area compared to traditional methods. However, the inaccurate predictions for base station localization derived from mobile crowdsourcing impacts its effectiveness for use in radio planning. Therefore, the purpose of this study is to design a model that can yield a more accurate localization through the introduction of a rule-based weighted classification. The methodology deployed is a permutation series based on fingerprint of the cell site with weightage derived from rule-based classification. DeLaunay triangulation and Voronoi diagrams are used to determine the positions of the existing base stations and the prediction of new site location respectively. The expected results are better accuracy of the classification model in the localization prediction of the base station leading to a more accurate prediction of new site location

Performance of macro clay on the porous asphalt mixture properties

Porous asphalt pavement already well known as one type of pavement since many decades, however due to lack in strength it is not been widely used in road construction especially in high stresses areas. Many research had been conducted by researchers in order to improve the durability and increase the service life of the road. One of the methods that commonly used is through asphalt modification. Objectives of this study are to discuss influence of macro-clay in terms of physical and rheological properties and their effect on performance of porous asphalt mixture. Various percentage of macro-clay (starting from 2% to 8%) was blended in an asphalt binder and compacted using the Marshall compactor. The blended asphalt was characterized using penetration, softening point test and penetration index compared with unmodified binder. Performance tests of asphalt mixture were carried out such as Los Angeles Abrasion Value (LAAV) and Stability and Flow test in order to determine the strength and durability. The results show that the addition of macro-clay would increase in softening point but decrease in binder penetration. Based on the results, while macro-clay changes physical and rheological properties of bitumen and increase stiffness, it also improves strength and durability resistance, as well. Generally, the best improvements in the modified binders were obtained with 4% of macro-clay

A systematic literature review of skyline query processing over data stream

Recently, skyline query processing over data stream has gained a lot of attention especially from the database community owing to its own unique challenges. Skyline queries aims at pruning a search space of a potential large multi-dimensional set of objects by keeping only those objects that are not worse than any other. Although an abundance of skyline query processing techniques have been proposed, there is a lack of a Systematic Literature Review (SLR) on current research works pertinent to skyline query processing over data stream. In regard to this, this paper provides a comparative study on the state-of-the-art approaches over the period between 2000 and 2022 with the main aim to help readers understand the key issues which are essential to consider in relation to processing skyline queries over streaming data. Seven digital databases were reviewed in accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) procedures. After applying both the inclusion and exclusion criteria, 23 primary papers were further examined. The results show that the identified skyline approaches are driven by the need to expedite the skyline query processing mainly due to the fact that data streams are time varying (time sensitive), continuous, real time, volatile, and unrepeatable. Although, these skyline approaches are tailored made for data stream with a common aim, their solutions vary to suit with the various aspects being considered, which include the type of skyline query, type of streaming data, type of sliding window, query processing technique, indexing technique as well as the data stream environment employed. In this paper, a comprehensive taxonomy is developed along with the key aspects of each reported approach, while several open issues and challenges related to the topic being reviewed are highlighted as recommendation for future research direction

An effective source number enumeration approach based on SEMD

In signal processing, empirical mode decomposition (EMD) first decomposes the received single-channel signal into several intrinsic mode functions (IMFs) and a residual, and then uses machine learning methods for source number enumeration. EMD, however, has an end effect that can undermine the accuracy of source number enumeration. To address this issue, this paper proposed a new EMD method named Supplementary Empirical Mode Decomposition (SEMD), which improved the accuracy by extending the signal length. The proposed method can be better applied to the modal parameter identification of non-stationary and nonlinear data in the engineering field. This method first identifies two candidate extreme points, which are the closest to the function value of the first extreme point near the endpoint. Then, on one side of the candidate point, it finds a waveform similar to that at the endpoint. Finally, the maximum and minimum points at each end of the signal will be added to extend the length of the signal. The added extreme points are candidate extreme points in similar waveforms. For the improved source number enumeration method based on SEMD, the instantaneous phase is obtained first by SEMD and Hilbert transform (HT). Then, the instantaneous phase feature is extracted to obtain a high-dimensional eigenvalue vector. Finally, the back propagation (BP) neural network is used to predict the number of sources. Experiment shows that SEMD can effectively restrain the end effect, and the source number enumeration algorithm based on SEMD has a higher correct detection probability than others

A source number enumeration method at low SNR bsed on ensemble learning

Source number estimation is one of the important research directions in array signal processing. To solve the difficulty of estimating the number of signal sources under a low signal-to-noise ratio (SNR), a source number enumeration method based on ensemble learning is proposed. This method first preprocesses the signal data. The specific process is to decompose the original signal into several intrinsic mode functions (IMF) by using Complementary Ensemble Empirical Mode Decomposition (CEEMD), and then construct a covariance matrix and perform eigenvalue decomposition to obtain samples. Finally, the source number enumeration model based on ensemble learning is used to predict the number of sources. This model is divided into two layers. First, the primary learner is trained with the dataset, and then the prediction result on the primary learner is used as the input of the secondary learner for training, and then the prediction result is obtained. Computer theoretical signals and real measured signals are used to verify the proposed source number enumeration method, respectively. Experiments show that this method has better performance than other methods at low SNR, and it is more suitable for real environment

Tobacco use and attitudes towards tobacco control activities of Malaysian dental students

Tobacco usage among dental students and the amount of training they received may have an impact on tobacco cessation activities undertaken for their patients. This study aims to assess Malaysian dental students' tobacco use, exposure to second-hand smoke and their attitude towards tobacco control activities and curriculum. This was a cross-sectional study using a self-administered questionnaire adapted from the Global Health Professions Students Survey (GHPSS). The questionnaire was distributed to all Malaysian fourth and fifth year dental students in four public dental schools (n=372), namely University of Malaya (UM), Universiti Teknologi Mara (UiTM), Universiti Kebangsaan Malaysia (UKM) and Universiti Sains Islam Malaysia (USIM). The data were analysed using descriptive and chi square tests. In total, (n=349) respondents completed the questionnaire, yielding a 93.8% response rate. Although the prevalence of Malaysian dental students who 'ever smoked' was 21.2%, the prevalence of current smokers was low (2.3%). About 62% and 39% of students reported having been exposed to second-hand smoke in public and at home, respectively. USIM students were significantly less likely to recall having received training about approaches to smoking cessation (52.9%, p < 0.001). Significantly fewer smokers than non-smokers agreed on tobacco banning policy. Regardless of their smoking status, the majority of dental students showed positive attitudes towards dentists' role in tobacco cessation. Tobacco user among Malaysian dental students was low. There were statistically significant differences between ever smokers and non-smokers' attitudes towards tobacco banning policy. The majority of dental students showed positive attitudes towards dentists' role in tobacco cessation

Classification of COVID-19 Symptoms Using Multilayer Perceptron

The COVID-19 virus had easily affected people worldwide through direct contact. Individuals diagnosed with positive COVID-19 virus may be affected with many symptoms, such as fever, tiredness, dry cough, difficulty in breathing, sore throat, chest pain, nasal congestion, runny nose, and diarrhea. An individual can also be diagnosed with COVID-19 even when he does not have any symptoms or be in contact with an infected person. Data classification was required due to the size of COVID-19 data that will be analyzed for future countermeasures determination. Some problems in data classification occurred due to unorganized data, such as time consumption, human error in complexity of symptom features and the diagnosis process data needed expert knowledge. This study aimed to use the artificial neural network (ANN) approach, which was multilayer perceptron (MLP) to classify the COVID-19 data by using patient symptom data. The MLP process involved data collection, data normalization, MLP design, MLP training, testing, and MLP verification. From the experiments, the MLP method was able to obtain an accuracy rate of 77.10%. In conclusion, the MLP method could classify the COVID-19 data and achieve a high accuracy rat

A skyline query processing approach over interval uncertain data stream with K-means clustering technique

Skyline query processing which extracts a set of interesting objects from a potentially large multidimensional dataset has attracted significant research attention in many emerging important applications. Although skyline computation has been studied extensively for data streams, there has been relatively less work on uncertain data stream. Only recently, a few methods have been proposed to process uncertain data stream, however data uncertainty in these works is restricted to objects having many instances. In contrast, there is no work that has considered uncertainty due to objects having interval values wherein the exact values of the objects are not known at the point of processing. Hence, in this paper a skyline query processing approach utilising the K-Means clustering technique is proposed to efficiently compute skyline over interval uncertain data stream