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Nawi, Rosmamalmi Mat,Noah, Shahrul Azman Mohd,Zakaria, Lailatul Qadri Korea Institute of Science and Technology Informat 2021 Journal of Information Science Theory and Practice Vol.9 No.2
Recommender Systems have gained immense popularity due to their capability of dealing with a massive amount of information in various domains. They are considered information filtering systems that make predictions or recommendations to users based on their interests and preferences. The more recent technology, Linked Open Data (LOD), has been introduced, and a vast amount of Resource Description Framework data have been published in freely accessible datasets. These datasets are connected to form the so-called LOD cloud. The need for semantic data representation has been identified as one of the next challenges in Recommender Systems. In a LOD-enabled recommendation framework where domain awareness plays a key role, the semantic information provided in the LOD can be exploited. However, dealing with a big chunk of the data from the LOD cloud and its integration with any domain datasets remains a challenge due to various issues, such as resource constraints and broken links. This paper presents the challenges of interconnecting and extracting the DBpedia data with the MovieLens 1 Million dataset. This study demonstrates how LOD can be a vital yet rich source of content knowledge that helps recommender systems address the issues of data sparsity and insufficient content analysis. Based on the challenges, we proposed a few alternatives and solutions to some of the challenges.
Quality of Life by Stage of Cervical Cancer among Malaysian Patients
Azmawati, Mohammed Nawi,Najibah, Endut,Ahmad Zailani Hatta, Mohd Dali,Norfazilah, Ahmad Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.13
Stage of cervical cancer may adversely affect the quality of life (QOL) among patients. The objective of this study was to predict the QOL among cervical cancer patients by the stage of their cancer. A cross-sectional study from September 2012 until January 2013 was conducted among cervical cancer patients who completed treatment. All patients completed a interviewer-guided questionnaire comprising four sections: (A) socio-demographic data, (B) medical history, (C) QOL measured by general health status questionnaire (QLQ-30) and (D) cervical cancer specific module CX-24 (EORTC) was used to measured patient's functional, symptom scale and their global health status. Results showed that global health status, emotional functioning and pain score were higher in stage III cervical cancer patients while role functioning was higher in stage I cervical cancer patients. Patients with stage IV cancer have a lower mean score in global health status (adjusted b-22.0, 95 CI% -35.6, -8.49) and emotional functioning (adjusted b -22.5, 95CI% -38.1, -6.69) while stage III had lower mean score in role functioning (adjusted b -14.3, 95CI% -25.4, -3.21) but higher mean score in pain (adjusted b 22.1, 95 CI% 8.56, 35.7). In conclusion, stage III and IV cervical cancers mainly affect the QOL of cervical cancer patients. Focus should be given to these subgroups to help in improving the QOL.
Women's Knowledge, Attitudes, and Practices about Breast Cancer in a Rural District of Central India
Gangane, Nitin,Ng, Nawi,Sebastian, Miguel San Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.16
Background: Breast cancer accounted for almost 25% of all cancers in women globally in 2012. Although breast cancer is the most prevalent cancer in India, there is no organised national breast cancer screening programme. Local studies on the burden of breast cancer are essential to develop effective context-specific strategies for an early detection breast cancer programme, considering the cultural and ethnic heterogeneity in India. This study examined the knowledge, attitudes, and practices about breast cancer in rural women in Central India. Materials and Methods: This community-based cross sectional study was conducted in Wardha district, located in Maharashtra state in Central India in 2013. The sample included 1000 women (609 rural, 391 urban) aged 13-50 years, selected as representative from each of the eight development blocks in the district, using stratified cluster sampling. Trained social workers interviewed women and collected demographic and socio-economic data. The instrument also assessed respondents' knowledge about breast cancer and its symptoms, risks, methods of screening, diagnosis and treatment, as well as their attitudes towards breast cancer and selfreported practices of breast cancer screening. Chi-square and t-test were applied to assess differences in the levels of knowledge, attitude, and practice (the outcome variables) between urban and rural respondents. Multivariable linear regression was conducted to analyse the relationship between socio-demographic factors and the outcome variables. Results: While about two-thirds of rural and urban women were aware of breast cancer, less than 7% in rural and urban areas had heard about breast self-examination. Knowledge about breast cancer, its symptoms, risk factors, diagnostic modalities, and treatment was similarly poor in both rural and urban women. Urban women demonstrated more positive attitudes towards breast cancer screening practices than their rural counterparts. Better knowledge of breast cancer symptoms, risk factors, diagnosis, and treatment correlated significantly with older age, higher levels of education, and being office workers or in business. Conclusions: Women in rural Central India have poor knowledge about breast cancer, its symptoms and risk factors. Breast self-examination is hardly practiced, though the willingness to learn is high. Positive attitudes towards screening provide an opportunity to promote breast self-examination.
Auto-Encoder Variants for Solving Handwritten Digits Classification Problem
Muhammad Aamir,Nazri Mohd Nawi,Hairulnizam Bin Mahdin,Rashid Naseem,Muhammad Zulqarnain 한국지능시스템학회 2020 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGE Vol.20 No.1
Auto-encoders (AEs) have been proposed for solving many problems in the domain of machine learning and deep learning since the last few decades. Due to their satisfactory performance, their multiple variations have also recently appeared. First, we introduce the conventional AE model and its different variant for learning abstract features from data by using a contrastive divergence algorithm. Second, we present the major differences among the following three popular AE variants: sparse AE (SAE), denoising AE (DAE), and contractive AE (CAE). Third, the main contribution of this study is performing the comparative study of the aforementioned three AE variants on the basis of their mathematical modeling and experiments. All the variants of the standard AE are evaluated on the basis of the MNIST benchmark handwritten digit dataset for classification problem. The observed output reveals the benefit of using the AE model and its variants. From the experiments, it is concluded that CAE achieved better classification accuracy than those of SAE and DAE.
Potts Model with Next-nearest-neighbor Ternary Interactions on an Arbitrary-order Cayley Tree
Nasir Ganikhodjaev,Ashraf Mohamed Nawi,Mohd Hirzie Mohd Rodzhan 한국물리학회 2012 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.61 No.7
We study the phase diagrams for the Potts model with restricted competing nearest-neighbor interactions <i>J</i><sub>1</sub> and ternary interactions <i>J<sub>pt</sub></i> on a Cayley tree of arbitrary order <i>k</i>. At vanishing temperature, the phase diagram is fully determined for all values and signs of <i>J<sub>pt</sub></i>/<i>J</i><sub>1</sub> and <i>T</i>/<i>J</i><sub>1</sub>. The phase diagrams are obtained from stability conditions, and characteristic points in the iteration scheme are numerically analyzed. The wavevectors versus temperature are plotted for some critical points in the modulated phases. Then, we using the Lyapunov exponent to verify the stability of the periods.
Noor Nazihah Bahrudin,Mohd Asri Nawi 한국화학공학회 2018 Korean Journal of Chemical Engineering Vol.35 No.7
Titanium dioxide (TiO2) and powdered activated carbon (PAC) were fabricated via a layer by layer arrangement on a glass plate using a dip-coating technique for the photocatalytic-adsorptive removal of phenol. Thinner TiO2 layer coated on PAC sub-layer has larger surface area and better phenol removal than the thicker TiO2 layer. The system obeyed the Langmuir isotherm model, which exhibited a homogeneous and monolayer adsorption with a maximum capacity of 27.8mg g1. The intra-particle diffusion was the rate-limiting step as the linear plot crossed the origin, while the adsorption was unfavorable at elevated temperature. Under light irradiation, the TiO2/PAC system removed phenol two-times more effectively than the TiO2 monolayer due to the synergistic effect of photocatalysis by TiO2 top layer and adsorption by PAC sub-layer. The COD removal of phenol was rapid for 10mg L1 of concentration and under solar light irradiation. It was shown that the PAC sub-layer plays a significant role in the total removal of phenol by providing the adsorption sites and slowing down the recombination rate of charge carriers to improve the TiO2 photocatalytic oxidation performance.