Health-Care Providers' and Parents' Perspectives on Complementary Alternative Medicine in Children with Cancer in Indonesia

Susilawati, Dwi,Sitaresmi, Mei,Handayani, Krisna,Ven, Peter van de,Sutaryo, Sutaryo,Kaspers, Gertjan,Mostert, Saskia Asian Pacific Journal of Cancer Prevention 2016 Asian Pacific journal of cancer prevention Vol.17 No.7

Background: Complementary alternative medicine (CAM) use in children with cancer is widespread. Health-care providers (HCP) need to acknowledge and address this need. This study explored and compared perspectives on CAM of HCP and parents of young patients with cancer in Indonesia. Materials and Methods: We conducted a cross-sectional study using semi-structured questionnaires in HCP and parents of childhood cancer patients at an Indonesian academic hospital. Results: A total of 351 respondents participated: 175 HCP (response rate 80%) and 176 parents (response rate 80%). Parents were more likely than HCP to think that chemotherapy can cure cancer (80% compared to 69%, P=0.013). Nearly half of all parents (46%) and HCP (45%) doubted whether CAM can cure cancer. Parents were more likely than HCP to think that CAM can be helpful in childhood cancer treatment (54% compared to 35%, P=0.003). The most recommended CAM by HCP was self-prayer (93%). Reasons for recommending CAM were: hope for improvement of the child's condition (48%), patient wants to stop treatment (42%). Most discouraged CAM by HCP was by old-smart people (70%), the reasons being: lack of evidence for usefulness (77%), lack of CAM knowledge (75%). The proportion thinking that patients were unlikely to raise the CAM topic if they perceived that doctors were skeptical was higher in parents than in HCP (52% versus 1%) (P<0.001). Most HCP (71%) and parents (77%) acknowledged that their knowledge about safety and efficacy of CAM was inadequate (P=ns). The proportion that wanted to learn or read more about CAM was higher among parents than HCP (48% compared to 31%, P=0.002). Conclusions: HCP and parents have different perspectives on CAM use in children with cancer. HCP should enhance their CAM knowledge and encourage open communication about CAM with parents. If doctors' skepticism is perceived, parents are unlikely to raise CAM as a topic.

Copper/Nickel/Manganese Doped Cerium Oxides Based Catalysts for Hydrogenation of CO2

Susilawati Toemen,Wan Azelee Wan Abu Bakar,Rusmidah Ali 대한화학회 2014 Bulletin of the Korean Chemical Society Vol.35 No.8

The recycling technology by the catalytic conversion is one of the most promising techniques for the CO2 treatment of coal burning power plant flue gases. The conversion of CO2 to valuable product of CH4 can be used as a fuel to run the turbine for electricity generation. Through this technique, the amount of coal needed for the combustion in a gas turbine can be reduced as well as CO2 emissions. Therefore, a series of catalysts based on cerium oxide doped with copper, nickel and manganese were prepared by impregnation method. From the characterization analysis, it showed that the prepared catalysts calcined at 400 oC were amorphous in structure with small particle size in the range below 100 nm. Meanwhile, the catalyst particles were aggregated and agglomerated with higher surface area of 286.70 m2g−1. By increasing the calcination temperature of catalysts to 1000 oC, the particle sizes were getting bigger (> 100 nm) and having moderate crystallinity with lower surface area (67.90 m2g−1). From the catalytic testing among all the prepared catalysts, Mn/Ce-75/Al2O3 calcined at 400 oC was assigned as the most potential catalyst which gave 49.05% and 56.79% CO2 conversion at reaction temperature of 100 oC and 200 oC, respectively.

Copper/Nickel/Manganese Doped Cerium Oxides Based Catalysts for Hydrogenation of CO₂

Toemen, Susilawati,Bakar, Wan Azelee Wan Abu,Ali, Rusmidah Korean Chemical Society 2014 Bulletin of the Korean Chemical Society Vol.35 No.8

The recycling technology by the catalytic conversion is one of the most promising techniques for the $CO_2$ treatment of coal burning power plant flue gases. The conversion of $CO_2$ to valuable product of $CH_4$ can be used as a fuel to run the turbine for electricity generation. Through this technique, the amount of coal needed for the combustion in a gas turbine can be reduced as well as $CO_2$ emissions. Therefore, a series of catalysts based on cerium oxide doped with copper, nickel and manganese were prepared by impregnation method. From the characterization analysis, it showed that the prepared catalysts calcined at $400^{\circ}C$ were amorphous in structure with small particle size in the range below 100 nm. Meanwhile, the catalyst particles were aggregated and agglomerated with higher surface area of $286.70m^2g^{-1}$. By increasing the calcination temperature of catalysts to $1000^{\circ}C$, the particle sizes were getting bigger (> 100 nm) and having moderate crystallinity with lower surface area ($67.90m^2g^{-1}$). From the catalytic testing among all the prepared catalysts, Mn/Ce-75/$Al_2O_3$ calcined at $400^{\circ}C$ was assigned as the most potential catalyst which gave 49.05% and 56.79% $CO_2$ conversion at reaction temperature of $100^{\circ}C$ and $200^{\circ}C$, respectively.

Greenhouses Gas Production from Different Soil Types and Water Managements under Defined Laboratory Condition

Helena Lina Susilawati,Kazuyuki Inubushi 한국토양비료학회 2014 한국토양비료학회 학술발표회 초록집 Vol.2014 No.6

Reducing Egypt Rock Phosphate Use in Zea Mays Cultivation on an Acid Soil Using Clinoptilolite Zeolite

Nur Aainaa Hasbullah,Ahmed Osumanu Haruna,Susilawati Kasim,Nik Muhamad Ab. Majid 한국토양비료학회 2014 한국토양비료학회 학술발표회 초록집 Vol.2014 No.6

다중 카메라 네트워크 가상의 관심선(Line of Interest)을 활용한 건물 내 재실자 인원 계수 방법론 개발

천휘경,박찬혁,지석호,노명일,Connie Susilawati 대한토목학회 2023 대한토목학회논문집 Vol.43 No.5

건물에서 재난이 발생할 경우, 건물 내 인원을 신속히 구조하여 사상자를 최소화하는 것은 단연 최우선순위가 된다. 이러한 구조활동을 위해서는 건물 내 어디에 몇 명이 있는지를 알아야 하는데, 실시간으로 알기가 어렵다 보니 주로 건물주나 경비원 등 관계자의 진술이나 층별면적, 수용인원과 같은 기초자료에 의존하는 실정이다. 따라서 빠르고 정확하게 재실 인원 정보를 파악하여 현장에 대한 불확실성을 낮추고 골든타임 내 효율적인 구조활동을 지원하는 것이 반드시 필요하다. 본 연구는 컴퓨터 비전 알고리즘을 활용하여 이미 건물에 설치되어 있는 여러 대의 CCTV가 촬영한 이미지로부터 건물 위치별 재실인원을 계수하는 방법론을 제시한다. 계수 방법론은 (1) 카메라별 관심선(LOI) 설정을 통한 다중 카메라 네트워크 환경 구축, (2) 딥러닝을 활용한 모니터링 구역 내 사람 탐지 및 추적, (3) 다중 카메라 네트워크 환경을 고려한 인원 합산 세 단계로 구성된다. 제안된 방법론은 5층 건물을 대상으로 세 개의 시간대별로 수행된 현장 실험을 통해 검증되었다. 최종 결과는 89.9%의 정확도로 재실자를 인식하는 것으로 나타났으며, 층별, 구역별 합산 결과도 93.1%, 93.3%의 정확도로 우수했다. 층별 평균 MAE와 RMSE는 각각 0.178과 0.339이었다. 이처럼 실시간으로 제공하는 건물 내 재실자 정보는 초기 재난대응 단계에 신속하고 정확한 구조활동을 지원할 수 있다. In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

Spatial ability and anatomy learning performance among dental students

Sarilita Erli,Lita Yurika Ambar,Firman Dani Rizali,Wilkinson Tracey,Susilawati Sri,Saptarini Risti,Aripin Dudi,Sjamsudin Endang 한국의학교육학회 2022 Korean journal of medical education Vol.34 No.4

Purpose: Spatial perception is an essential skill for professional dentists. The objective of this study was to observe the spatial ability, as well as anatomy module grades, of dental students at a dental education center in Indonesia and relate these to gender and cohort.Methods: A cross-sectional study was carried out where dental students in years (cohorts) 1, 2, 4–6 were invited to take the Revised Purdue Spatial Visualization Test (PSVT-R) and the redrawn Vandenberg and Kuse Mental Rotation Test (MRT) in order to assess spatial ability. In addition, the 1st- and 2nd-year dental students carried out gross anatomy assessments. Spatial ability test results were compared using an independent t-test to detect gender differences, one-way analysis of variance to inspect cohort differences, and correlation relative to anatomy module scores.Results: A total of 326 dental students voluntarily participated. Statistically significant gender differences were found in both spatial ability tests in the overall sample (PSVT-R: p<0.001; MRT: p=0.001). When the 1st- and 2nd-year dental students were pooled, significant gender differences were detected, in which males scored higher than females in both spatial ability tests (PSVT-R: p<0.001; MRT: p=0.003). In anatomy, however, females scored higher than the males (p=0.005). In addition, there were weak to moderate, but significant correlations between spatial ability tests and anatomy scores.Conclusion: This study indicated that spatial ability may not be the only factor predicting the academic performance of dental students. However, dental students with low spatial ability scores may need supplementary educational techniques when learning specific spatial tasks.

The Contribution of Feature Selection and Morphological Operation For On-Line Business System’s Image Classification

Mokhairi Makhtar,Nur Shazwani Kamarudin,Syed Abdullah Fadzli,Mumtazimah Mohamad,Fatma Susilawati Mohamad,Mohd Fadzil Abdul Kadir 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.11

Automatic image annotation is one of crucial and attractive field of image retrieval. Classification process is part of the important phase in automatic image annotation (AIA). With the explosive growth of methods in this research area, this paper proposes 5 processing steps before image annotation using Amazon dataset, i.e., image segmentation, object identification, feature extraction, feature selection and image features classification. A lot of research has been done in creating numbers of different approaches and algorithm for image segmentation. Otsu is one of the most well known method in image segmentation region based. The proposed model aims to provide the highest accuracy after undergo those processing steps. This paper conducted several experiments for image classification starting from image segmentation in order to demonstrate usefulness and competiveness among different type of classifiers. It also target to study the effect of morphological operation and feature selection to the accuracy. For the classification experiment, it was tested using four types of classifiers: BayesNet, NaiveBayesUpdateable, RandomTree and IBk.

Lived Experiences of Indonesian Nurses Working in Remote Areas: A Descriptive Qualitative Study

Ivanna Christina Pardosi,Rica Silvia Siburian,Vania Naomi Silalahi,Juniarta,Novita Susilawati Barus 한국간호과학회 2023 한국간호과학회 학술대회 Vol.2023 No.11

Optimization and physicochemical studies of alumina supported samarium oxide based catalysts using artificial neural network in methanation reaction

Salmiah Jamal Mat Rosid,Azman Azid,Aisyah Fathiah Ahmad,Nursyamimi Zulkurnain,Susilawati Toemen,Wan Azelee Wan Abu Bakar,Ahmad Zamani Ab Halim,Wan Nur Aini Wan Mokhtar,Sarina Mat Rosid 대한환경공학회 2023 Environmental Engineering Research Vol.28 No.1

Developed countries are increasing their demand for natural gas as it is an industrial requirement for fuel transportation. Most of modern society relies heavily on vehicles. However, the presence of CO₂ gas has led to the categorization of sour natural gas which reduces the quality and price of natural gas. Therefore, the catalytic methanation technique was applied to convert carbon dioxide (CO₂) to methane (CH₄) gas and reduce the emissions of CO₂ within the environment. In this study, samarium oxide supported on alumina doped with ruthenium and manganese was synthesized via wet impregnation. X-ray diffraction (XRD) analysis revealed samarium oxide, Sm₂O₃ and manganese oxide, MnO₂ as an active species. The reduction temperature for active species was at a low reaction temperature, 268.2℃ with medium basicity site as in Temperature Programme Reduction (TPR) and Temperature Programme Desorption (TPD) analyses. Field Emission Scanning Electron Microscopy (FESEM) analysis showed an agglomeration of particle size. The characterised potential catalyst of Ru/Mn/Sm (5:35:60)/Al₂O₃ (RMS 5:35:60) calcined at 1,000℃ revealed 100% conversion of CO₂ with 68.87% CH₄ formation at the reaction temperature of 400℃. These results were verified by artificial neural network (ANN) with validation R² of 0.99 indicating all modelling data are acceptable.