17 research outputs found
An evaluation of Student Practical Online Application System (SPOA) developed using User Centered Design (UCD) / Muhammad Izzuddin Khairul Annuar Lim
No full textPractical training is the medium for the students to apply the knowledge they gain in the classroom to be apply in the real job situation. This is to help the student to be more prepared in working environment after finish their studies. Faculty Computer and Mathematical Sciences (FSKM) still does not have any web-based system to handle or manage their practical student efficiently. They still using the manual paper-based form and student need to write their practical report in a paper based. So, the author will develop and design the student practical online application system (SPOA) by using user-cantered design (UCD) as the guideline and evaluate the usability of the system according to the user perspective. The UCD process is an iterative process which is after the SPOA system prototype been completed, the prototype will be evaluated and if there is any usability problem discover, the problem will be fixed and evaluated again until the system is ease to use. The UCD process has four phases that being used in this project which are understand user need, establish requirement, prototyping alternative designs and evaluate designs. The outcome of this project is the usability testing result and the comparison from using manual system and by using web-based automated system. Last but not least, there is only a few usability problem been discover by the usability testing participants and the participants agree that using web-based Student Practical Online Application System (SPOA) more facilitate the practical training process in the future. For future enhancement, this system can be enhanced by expending the scope and target area of the research. Instead of focusing on student from one faculty, this system can be introduce to others faculty in UiTM
Preliminary studies of the impact of synthesis method on Reduced Graphene Oxide-Titanium Composite
No full textThere are two current major challenges aroused by the continued usage of fossil fuels as the energy source, which are the production of high levels of carbon dioxide (CO₂), resulting in global warming, and concerning the use of energy resources. There is a clear need to explore new prospects for CO₂ capture to prevent it from penetrating into the atmosphere. Carbon Capture and Conversion (CCC) method is one of the alternative solutions in carbon management. The synthesized reduced graphene oxide-Titanium (rGO-TiO₂) composites used in this preliminary study is the CCC material which will potentially capture the carbon dioxide (CO₂) and convert it into a hydrocarbon fuel such as methane. The aim of this preliminary study is to examine the impact of synthesis method and raw material to synthesize the rGO-TiO₂ composite. The photocatalytic activity was measured by using the Gas Chromatograph (GC) while the optical properties were measured by using Electrochemical Impedance Spectroscopy (EIS) and fluorescent spectrometer (PL). The EIS, PL and GC results confirms that the synthesize method and raw materials were affect the optical properties and the photocatalytic performance of the rGO-TiO₂. The rGO-TiO₂(H1) which was synthesized using the TBT powder via Hydrothermal method shows the best electrical properties and lowest recombination rate of the photogenerated electron-hole pairs compared to the other samples. The rGO-TiO₂(H1) also shows the highest photoreduction performance with 0.722 ųmol/gcat methane yield
PROSES PENYUTRADARAAN DALAM FILM DOKUMENTER “Merawat Hujan”
No full textThis work raises the issue of how a community that processes rainwater as an alternative to clean water will be packaged through a documentary film. The writer as a director will see how the directing process in a documentary film. This work is carried out in the Jombang area as one of the areas that has drought problems and limited clean water stocks during the dry season. This film tells how the role of the Air Kita community in socializing the use of rainwater and also the achievements of the community after moving for almost 7 years. In the directing process, there are several stages carried out by the author to create a documentary film with observation techniques, starting from pre-production, namely researching issues both from the internet and field research, observing and discussing stages with sources, making treatment or scenario scripts and preparing shooting schedules. The production stage is taking pictures that have been planned at the pre-production stage in accordance with the concept, namely taking the activities of the Air Kita community and interviews with our water community. Other supporting data such as interviews with the environmental agency and stakeholders of our water community as another point of view about our Water Community and the post-production stage, namely editing the images and compiling them into a unified documentary film
Perancangan Serial Animasi Sanggramawijaya
No full textPenelitian ini merespon atas kebutuhan film animasi di Indonesia terutama yang mengangkat konten lokal sejarah dan kebudayaan yang dinilai kurang dalam kuantitas sehingga menimbulkan kurangnya kualitas karena kurang adanya kompetisi dalam industri animasi. Untuk memenuhi tujuan dari penelitian ini, penulis melakukan metode penelitian secara kualitatif dengan melakukan wawancara kepada Guru Besar sejarah dan pelaku animasi yang sudah menekuni bidangnya sejak lama. Selain itu dilakukan observasi terhadap beberapa film animasi untuk dipelajari secara teknis pembuatannya. Wujud akhir dari perancangan ini adalah sebuah visual storytelling yang menampilkan preview dari serial animasi yang bercerita tentang berdirinya kerajaan Majapahit dengan gaya cerita yang lebih informal, sehingga penikmatnya bukan hanya dari mereka yang ingin mengetahui sejarah, namun juga dari segi hiburan.
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This research responds to the needs of animated films in Indonesia, especially with local content and cultural history which are considered less in quantity, causing a lack of quality because of the lack of competition in the animation industry. For the purposes of this study, the author conducted qualitative research methods such as an interview to Professor of history and animator from animation industry who has been in this field for a long time. In addition, the observation to several animated films to be studied in technical preparation and production. Final output of this design is a visual storytelling that shows a preview of the animated series that tells the story of the founding of the kingdom of Majapahit which style of the story is presented are more informal, so that the audiences are not only from those who wish to know the history, but also in terms of entertainment
Biofingerprint detection of corona virus using Raman spectroscopy: a novel approach
No full textAbstract Coronavirus disease-19 (COVID-19) is caused by SARS-CoV-2, a highly contagious respiratory virus that has caused a global pandemic. Despite the urgent need for effective diagnostic screening technologies, ideal methods for COVID-19 detection have not yet been developed. To address this issue, we developed a Raman spectroscopy technique for rapid and sensitive on-site detection of SARS-CoV-2, utilizing the unique spectral fingerprint of molecular vibrations. The proposed technique is non-invasive and label-free that enables the detection of molecular vibrations, providing a unique spectral fingerprint for different molecules. Raman spectra from 75 positive and 75 negative swab samples were analyzed, processed by smoothening and baseline correction of spectral data. The peaks in the processed data were detected and assigned based on literature peak, with peaks specific to positive samples used for detection with minimal false positives. These peaks were attributed to various molecules, including amino acids in proteins, glycoproteins, lipids, and protein structures. Our Raman spectroscopy technique provides a reliable and non-invasive approach for the detection of SARS-CoV-2, with potential to expand to other infectious agents. This method has significant implications for global health, aiding in effective control measures against COVID-19
Effect of monsoonal clustering for pm10 concentration Prediction in Keningau, Sabah using principal component analysis
No full textParticulate matter (PM) has caught scientific attention in scientific research due to its harmful effect on human health. While prediction is essential for future development in Keningau, temporal clustering in Keningau has yet to be studied. Thus, this research aims to determine whether monsoonal clustering is required for meteorological and pollutant concentration data collected in Keningau. Missing data is first imputed using Nearest Neighbour Method (NNM). Then, wind direction and wind speed are converted into northern (Wy) and eastern (Wx) component of wind speed. Data is then temporal clustered based on monsoonal season (NEM, IM4, SWM, IM10). Both clustered and unclustered data are analysed using principal component (PC) analysis (PCA). The findings revealed that humidity in PC1 with average EV (explained variation) of 93.92 ± 0.52 contribute the most variation of PM10, followed by Wx in PC2 with average EV of 3.51 ± 0.48. Regression analysis shows that humidity and PM10 are negatively moderate to strongly correlated except for IM4 (intermonsoon April), which may be due to dry climate during the season. As for Wx, it has weak correlation with PM10. This may be due to location of Keningau at western part of Crocker range. However, the spread of PM10 due to eastern wind causes weak to zero correlation. Due to consideration of dry climate as revealed by the findings from IM4 cluster, there is need for data collected by Keningau to be clustered by monsoon
Pattern Recognition for Human Diseases Classification in Spectral Analysis
No full textPattern recognition is a multidisciplinary area that received more scientific attraction during this period of rapid technological innovation. Today, many real issues and scenarios require pattern recognition to aid in the faster resolution of complicated problems, particularly those that cannot be solved using traditional human heuristics. One common problem in pattern recognition is dealing with multidimensional data, which is prominent in studies involving spectral data such as ultraviolet visible (UV/Vis), infrared (IR), and Raman spectroscopy data. UV/Vis, IR, and Raman spectroscopy are well-known spectroscopic methods that are used to determine the atomic or molecular structure of a sample in various fields. Typically, pattern recognition consists of two components: exploratory data analysis and classification method. Exploratory data analysis is an approach that involves detecting anomalies in data, extracting essential variables, and revealing the data’s underlying structure. On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. This article discusses the fundamental assumptions, benefits, and limitations of some well-known pattern recognition algorithms including Principal Component Analysis (PCA), Kernel PCA, Successive Projection Algorithm (SPA), Genetic Algorithm (GA), Partial Least Square Regression (PLS-R), Linear Discriminant Analysis (LDA), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Partial Least Square-Discriminant Analysis (PLS-DA) and Artificial Neural Network (ANN). The use of UV/Vis, IR, and Raman spectroscopy for disease classification is also highlighted. To conclude, many pattern recognition algorithms have the potential to overcome each of their distinct limits, and there is also the option of combining all of these algorithms to create an ensemble of methods
Pattern Recognition for Human Diseases Classification in Spectral Analysis
No full textPattern recognition is a multidisciplinary area that received more scientific attraction during this period of rapid technological innovation. Today, many real issues and scenarios require pattern recognition to aid in the faster resolution of complicated problems, particularly those that cannot be solved using traditional human heuristics. One common problem in pattern recognition is dealing with multidimensional data, which is prominent in studies involving spectral data such as ultraviolet-visible (UV/Vis), infrared (IR), and Raman spectroscopy data. UV/Vis, IR, and Raman spectroscopy are well-known spectroscopic methods that are used to determine the atomic or molecular structure of a sample in various fields. Typically, pattern recognition consists of two components: exploratory data analysis and classification method. Exploratory data analysis is an approach that involves detecting anomalies in data, extracting essential variables, and revealing the data’s underlying structure. On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. This article discusses the fundamental assumptions, benefits, and limitations of some well-known pattern recognition algorithms including Principal Component Analysis (PCA), Kernel PCA, Successive Projection Algorithm (SPA), Genetic Algorithm (GA), Partial Least Square Regression (PLS-R), Linear Discriminant Analysis (LDA), K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Partial Least Square-Discriminant Analysis (PLS-DA) and Artificial Neural Network (ANN). The use of UV/Vis, IR, and Raman spectroscopy for disease classification is also highlighted. To conclude, many pattern recognition algorithms have the potential to overcome each of their distinct limits, and there is also the option of combining all of these algorithms to create an ensemble of methods
Author’s Worldview on The Effects of Conspiracy and Terrorism in Society as Represented in the Novel Deus Ex: Black Light by James Swallow
No full textTerrorism and conspiracy theory are popular topics in the narrative of modern literary works. Creating a literary narrative in a literary work requires both intrinsic elements and extrinsic elements. The intrinsic elements in a literary narrative lies within the literary work itself while extrinsic elements are influenced by outside forces. This study aims to analyze the extrinsic elements and establish the author’s worldview regarding terrorism and conspiracy theory inside the novel Deus Ex: Black Light by the author, James Swallow. In addition, this study also aims to find representations of the author’s worldview in society to determine its relevancy within the real world. This study uses Lucien Goldmann’s Genetic Structuralism, the Psychology of Terrorism by Randy Borum, and the Psychology of Conspiracy Theory by Jan Willem van Prooijen. Using Genetic Structuralism, this study collected 10 data from the novel and establishes 9 author’s worldviews from the 10 data, with 5 data used as a basis for 4 author’s worldviews regarding terrorism and another 5 data used as a basis for 5 author’s worldviews regarding conspiracy theory. All 9 author’s worldviews have their own real cases to represent their presence in society, correlating the narrative of the novel with society. The relevancy of the author’s worldview in society is also determined, with most of them being relevant in recent years with most cases representing the author’s worldview being no older than 10 years old
