Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Databases and Information Systems (34)
- Education (19)
- Medicine and Health Sciences (15)
- Artificial Intelligence and Robotics (11)
- Social and Behavioral Sciences (11)
-
- Engineering (9)
- Theory and Algorithms (8)
- Computer Engineering (6)
- Analytical, Diagnostic and Therapeutic Techniques and Equipment (5)
- Dentistry (5)
- Electrical and Computer Engineering (5)
- Art and Design (4)
- Arts and Humanities (4)
- Communication (4)
- Game Design (4)
- Health Information Technology (4)
- Higher Education (3)
- Mathematics (3)
- Medical Specialties (3)
- Online and Distance Education (3)
- Psychology (3)
- Cardiology (2)
- Diseases (2)
- Educational Technology (2)
- Law (2)
- Programming Languages and Compilers (2)
- Public Affairs, Public Policy and Public Administration (2)
- Social Media (2)
- Keyword
-
- COVID-19 (4)
- Philippines (4)
- CNN (3)
- Classification (3)
- Convolutional neural networks (3)
-
- Game-based learning (3)
- Mobile learning (3)
- Mobile-assisted language learning (3)
- Support vector machine (3)
- Algorithm (2)
- Approximation (2)
- Artificial intelligence (2)
- Artificial neural network (2)
- Biomedical image (2)
- Collaborative learning (2)
- Complexity (2)
- Deep learning (2)
- Electrocardiography (2)
- Emergency remote teaching (2)
- English comprehension (2)
- Epidemiology (2)
- Eye tracking (2)
- Feature extraction (2)
- Gamification (2)
- Higher education (2)
- Infodemiology (2)
- Link prediction (2)
- Machine Learning (2)
- Machine learning (2)
- Mobile games (2)
- Publication Year
- Publication
- Publication Type
Articles 1 - 30 of 87
Full-Text Articles in Computer Sciences
Detection Of Tooth Position By Yolov4 And Various Dental Problems Based On Cnn With Bitewing Radiograph, Kuo Chen Li, Yi-Cheng Mao, Mu-Feng Lin, Yi-Qian Li, Chiung-An Chen, Tsung-Yi Chen, Patricia Angela R. Abu
Detection Of Tooth Position By Yolov4 And Various Dental Problems Based On Cnn With Bitewing Radiograph, Kuo Chen Li, Yi-Cheng Mao, Mu-Feng Lin, Yi-Qian Li, Chiung-An Chen, Tsung-Yi Chen, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
Periodontitis is a high prevalence dental disease caused by bacterial infection of the bone that surrounds the tooth. Early detection and precision treatment can prevent more severe symptoms such as tooth loss. Traditionally, periodontal disease is identified and labeled manually by dental professionals. The task requires expertise and extensive experience, and it is highly repetitive and time-consuming. The aim of this study is to explore the application of AI in the field of dental medicine. With the inherent learning capabilities, AI exhibits remarkable proficiency in processing extensive datasets and effectively managing repetitive tasks. This is particularly advantageous in professions demanding …
A High-Accuracy Detection System: Based On Transfer Learning For Apical Lesions On Periapical Radiograph, Yueh Chuo, Wen-Ming Lin, Tsung-Yi Chen, Mei-Ling Chan, Yu-Sung Chang, Yan-Ru Lin, Yuan-Jin Lin, Yu-Han Shao, Chiung-An Chen, Patricia Angela R. Abu
A High-Accuracy Detection System: Based On Transfer Learning For Apical Lesions On Periapical Radiograph, Yueh Chuo, Wen-Ming Lin, Tsung-Yi Chen, Mei-Ling Chan, Yu-Sung Chang, Yan-Ru Lin, Yuan-Jin Lin, Yu-Han Shao, Chiung-An Chen, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
Apical Lesions, one of the most common oral diseases, can be effectively detected in daily dental examinations by a periapical radiograph (PA). In the current popular endodontic treatment, most dentists spend a lot of time manually marking the lesion area. In order to reduce the burden on dentists, this paper proposes a convolutional neural network (CNN)-based regional analysis model for spical lesions for periapical radiographs. In this study, the database was provided by dentists with more than three years of practical experience, meeting the criteria for clinical practical application. The contributions of this work are (1) an advanced adaptive threshold …
Missing Teeth And Restoration Detection Using Dental Panoramic Radiography Based On Transfer Learning With Cnns, Shih-Lun Chen, Tsung-Yi Chen, Yen-Cheng Huang, Chiung-An Chen, He-Sheng Chou, Ya-Yun Huang, Wei-Chi Lin, Tzu-Chien Li, Jia-Jun Yuan, Patricia Angela R. Abu
Missing Teeth And Restoration Detection Using Dental Panoramic Radiography Based On Transfer Learning With Cnns, Shih-Lun Chen, Tsung-Yi Chen, Yen-Cheng Huang, Chiung-An Chen, He-Sheng Chou, Ya-Yun Huang, Wei-Chi Lin, Tzu-Chien Li, Jia-Jun Yuan, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
Common dental diseases include caries, periodontitis, missing teeth and restorations. Dentists still use manual methods to judge and label lesions which is very time-consuming and highly repetitive. This research proposal uses artificial intelligence combined with image judgment technology for an improved efficiency on the process. In terms of cropping technology in images, the proposed study uses histogram equalization combined with flat-field correction for pixel value assignment. The details of the bone structure improves the resolution of the high-noise coverage. Thus, using the polynomial function connects all the interstitial strands by the strips to form a smooth curve. The curve solves …
A Low-Power Passive Uhf Tag With High-Precision Temperature Sensor For Human Body Application, Liang-Hung Wang, Zheng Pan, Hao Jiang, Hua-Ling Lai, Qi-Peng Ran, Patricia Angela R. Abu
A Low-Power Passive Uhf Tag With High-Precision Temperature Sensor For Human Body Application, Liang-Hung Wang, Zheng Pan, Hao Jiang, Hua-Ling Lai, Qi-Peng Ran, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
Radio frequency identification (RFID) tags are widely used in various electronic devices due to their low cost, simple structure, and convenient data reading. This topic aims to study the key technologies of ultra-high frequency (UHF) RFID tags and high-precision temperature sensors, and how to reduce the power consumption of the temperature sensor and the overall circuits while maintaining minimal loss of performance. Combined with the biomedicine, an innovative high-precision human UHF RFID chip for body temperature monitoring is designed. In this study, a ring oscillator whose output frequency is linearly related to temperature is designed and proposed as a temperature-sensing …
Three-Heartbeat Multilead Ecg Recognition Method For Arrhythmia Classification, Liang-Hung Wang, Yan-Ting Yu, Wei Liu, Lu Xu, Chao-Xin Xie, Tao Yang, I-Chun Kuo, Xin-Kang Wang, Jie Gao, Patricia Angela R. Abu
Three-Heartbeat Multilead Ecg Recognition Method For Arrhythmia Classification, Liang-Hung Wang, Yan-Ting Yu, Wei Liu, Lu Xu, Chao-Xin Xie, Tao Yang, I-Chun Kuo, Xin-Kang Wang, Jie Gao, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
Electrocardiogram (ECG) is the primary basis for the diagnosis of cardiovascular diseases. However, the amount of ECG data of patients makes manual interpretation time-consuming and onerous. Therefore, the intelligent ECG recognition technology is an important means to decrease the shortage of medical resources. This study proposes a novel classification method for arrhythmia that uses for the very first time a three-heartbeat multi-lead (THML) ECG data in which each fragment contains three complete heartbeat processes of multiple ECG leads. The THML ECG data pre-processing method is formulated which makes use of the MIT-BIH arrhythmia database as training samples. Four arrhythmia classification …
Clinical Interactions In Electronic Medical Records Towards The Development Of A Token-Economy Model, Nicole Allison S. Co, Jason Limcaco, Hans Calvin L. Tan, Ma. Regina Justina E. Estuar, Christian E. Pulmano, Dennis Andrew Villamor, Quirino Sugon Jr, Maria Cristina G. Bautista, Paulyn Jean Acacio-Claro
Clinical Interactions In Electronic Medical Records Towards The Development Of A Token-Economy Model, Nicole Allison S. Co, Jason Limcaco, Hans Calvin L. Tan, Ma. Regina Justina E. Estuar, Christian E. Pulmano, Dennis Andrew Villamor, Quirino Sugon Jr, Maria Cristina G. Bautista, Paulyn Jean Acacio-Claro
Graduate School of Business Publications
The use of electronic medical records (EMRs) plays a crucial role in the successful implementation of the Universal Healthcare Law which promises quality and affordable healthcare to all Filipinos. Consequently, the current adoption of EMRs should be studied from the perspective of the healthcare provider. As most studies look into use of EMRs by doctors or patients, there are very few that extend studies to look at possible interaction of doctor and patient in the same EMR environment. Understanding this interaction paves the way for possible incentives that will increase the use and adoption of the EMR. This study uses …
Supporting Mastery Learning Through A Multiple-Submission Policy For Assignments In A Purely Online Programming Class, Joseph Benjamin R. Ilagan, Marianne Kayle Amurao, Jose Ramon Ilagan
Supporting Mastery Learning Through A Multiple-Submission Policy For Assignments In A Purely Online Programming Class, Joseph Benjamin R. Ilagan, Marianne Kayle Amurao, Jose Ramon Ilagan
Quantitative Methods and Information Technology Faculty Publications
The Learning Edge Momentum (LEM) theory suggests that once students fall behind, it gets more difficult to catch up with the course material. It then becomes increasingly more difficult to connect new, higher-level concepts to those solid edges of knowledge with mastery of basic concepts. Learning for Mastery (LFM) acknowledges that students learn at different paces by allowing students unable to master tests the first time to catch up eventually. This paper describes how an online introductory Python programming course offered to business students followed a multiple-submission policy for assignments to support LFM. The multiple submission policy contributed to the …
Construction Of A Repeatable Framework For Prostate Cancer Lesion Binary Semantic Segmentation Using Convolutional Neural Networks, Ian Vincent O. Mirasol, Patricia Angela R. Abu, Rosula Sj Reyes
Construction Of A Repeatable Framework For Prostate Cancer Lesion Binary Semantic Segmentation Using Convolutional Neural Networks, Ian Vincent O. Mirasol, Patricia Angela R. Abu, Rosula Sj Reyes
Department of Information Systems & Computer Science Faculty Publications
Prostate cancer is the 3rd most diagnosed cancer overall. Current screening methods such as the prostate-specific antigen test could result in overdiagonosis and overtreatment while other methods such as a transrectal ultrasonography are invasive. Recent medical advancements have allowed the use of multiparametric MRI — a noninvasive and reliable screening process for prostate cancer. However, assessment would still vary from different professionals introducing subjectivity. While con-volutional neural network has been used in multiple studies to ob-jectively segment prostate lesions, due to the sensitivity of datasets and varying ground-truth established used in these studies, it is not possible to reproduce and …
Non-Parametric Stochastic Autoencoder Model For Anomaly Detection, Raphael B. Alampay, Patricia Angela R. Abu
Non-Parametric Stochastic Autoencoder Model For Anomaly Detection, Raphael B. Alampay, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
Anomaly detection is a widely studied field in computer science with applications ranging from intrusion detection, fraud detection, medical diagnosis and quality assurance in manufacturing. The underlying premise is that an anomaly is an observation that does not conform to what is considered to be normal. This study addresses two major problems in the field. First, anomalies are defined in a local context, that is, being able to give quantitative measures as to how anomalies are categorized within its own problem domain and cannot be generalized to other domains. Commonly, anomalies are measured according to statistical probabilities relative to the …
Predicting Pair Success In A Pair Programming Eye Tracking Experiment Using Cross-Recurrence Quantification Analysis, Maureen M. Villamor, Maria Mercedes T. Rodrigo
Predicting Pair Success In A Pair Programming Eye Tracking Experiment Using Cross-Recurrence Quantification Analysis, Maureen M. Villamor, Maria Mercedes T. Rodrigo
Department of Information Systems & Computer Science Faculty Publications
Pair programming is a model of collaborative learning. It has become a well-known pedagogical practice in teaching introductory programming courses because of its potential benefits to students. This study aims to investigate pair patterns in the context of pair program tracing and debugging to determine what characterizes collaboration and how these patterns relate to success, where success is measured in terms of performance task scores. This research used eye-tracking methodologies and techniques such as cross-recurrence quantification analysis. The potential indicators for pair success were used to create a model for predicting pair success. Findings suggest that it is possible to …
Service Contracting As A Policy Response For Public Transport Recovery During The Covid-19 Pandemic: A Preliminary Evaluation, Varsolo Sunio, Wilhansen Joseph Li, Joemier Pontawe, Albert Dizon, Joel Bienne Valderrama, Agnes Robang
Service Contracting As A Policy Response For Public Transport Recovery During The Covid-19 Pandemic: A Preliminary Evaluation, Varsolo Sunio, Wilhansen Joseph Li, Joemier Pontawe, Albert Dizon, Joel Bienne Valderrama, Agnes Robang
Department of Information Systems & Computer Science Faculty Publications
We examine and assess the service contracting (SC) program implemented for the first time in Metro Manila, Philippines as a response to the impact of the pandemic on road-based public transport sector. We develop an evaluation framework, consisting of three indicators: social amelioration, increase in transport supply and performance improvement. These indicators are the purported objectives of SC. Using a mix of qualitative and quantitative methods, our evaluation suggests that although SC has brought positive impact in terms of the first two indicators, there is no robust evidence so far that may suggest that SC has improved the performance of …
The Uses Of A Dual-Band Corrugated Circularly Polarized Horn Antenna For 5g Systems, Chih-Kai Liu, Wei-Yuan Chiang, Pei-Zong Rao, Pei-Hsiu Hung, Shih-Hung Chen, Chiung-An Chen, Liang-Hung Wang, Patricia Angela R. Abu, Shih-Lun Chen
The Uses Of A Dual-Band Corrugated Circularly Polarized Horn Antenna For 5g Systems, Chih-Kai Liu, Wei-Yuan Chiang, Pei-Zong Rao, Pei-Hsiu Hung, Shih-Hung Chen, Chiung-An Chen, Liang-Hung Wang, Patricia Angela R. Abu, Shih-Lun Chen
Department of Information Systems & Computer Science Faculty Publications
This paper presents the development of a wide-beam width, dual-band, omnidirectional antenna for the mm-wave band used in 5G communication systems for indoor coverage. The 5G indoor environment includes features of wide space and short range. Additionally, it needs to function well under a variety of circumstances in order to carry out its diverse set of network applications. The waveguide antenna has been designed to be small enough to meet the requirements of mm-wave band and utilizes a corrugated horn to produce a wide beam width. Additionally, it is small enough to integrate with 5G communication products and is easy …
Tooth Position Determination By Automatic Cutting And Marking Of Dental Panoramic X-Ray Film In Medical Image Processing, Yen-Cheng Huang, Chiung-An Chen, Tsung-Yi Chen, He-Sheng Chou, Wei-Chi Lin, Tzu-Chien Li, Jia-Jun Yuan, Szu-Yin Lin, Chun-Wei Li, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo
Tooth Position Determination By Automatic Cutting And Marking Of Dental Panoramic X-Ray Film In Medical Image Processing, Yen-Cheng Huang, Chiung-An Chen, Tsung-Yi Chen, He-Sheng Chou, Wei-Chi Lin, Tzu-Chien Li, Jia-Jun Yuan, Szu-Yin Lin, Chun-Wei Li, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo
Department of Information Systems & Computer Science Faculty Publications
This paper presents a novel method for automatic segmentation of dental X-ray images into single tooth sections and for placing every segmented tooth onto a precise corresponding position table. Moreover, the proposed method automatically determines the tooth’s position in a panoramic X-ray film. The image-processing step incorporates a variety of image-enhancement techniques, including sharpening, histogram equalization, and flat-field correction. Moreover, image processing was implemented iteratively to achieve higher pixel value contrast between the teeth and cavity. The next image-enhancement step is aimed at detecting the teeth cavity and involves determining the segment and points separating the upper and lower jaw, …
Teaching And Learning Under Covid-19 Public Health Edicts: The Role Of Household Lockdowns And Prior Technology Usage, Neil Guppy, David Boud, Tania Heap, Dominique Verpoorten, Uwe Matzat, Joanna Tai, Louise Lutze-Mann, Mary Roth, Patsie Polly, Jamie-Lee Burgess, Jenilyn L. Agapito, Silvia K. Bartolic
Teaching And Learning Under Covid-19 Public Health Edicts: The Role Of Household Lockdowns And Prior Technology Usage, Neil Guppy, David Boud, Tania Heap, Dominique Verpoorten, Uwe Matzat, Joanna Tai, Louise Lutze-Mann, Mary Roth, Patsie Polly, Jamie-Lee Burgess, Jenilyn L. Agapito, Silvia K. Bartolic
Department of Information Systems & Computer Science Faculty Publications
Public health edicts necessitated by COVID-19 prompted a rapid pivot to remote online teaching and learning. Two major consequences followed: households became students' main learning space, and technology became the sole medium of instructional delivery. We use the ideas of "digital disconnect" and "digital divide" to examine, for students and faculty, their prior experience with, and proficiency in using, learning technology. We also explore, for students, how household lockdowns and digital capacity impacted learning. Our findings are drawn from 3806 students and 283 faculty instructors from nine higher education institutions across Asia, Australia, Europe, and North America. For instructors, we …
Classifying Mosquito Presence And Genera Using Median And Interquartile Values From 26-Filter Wingbeat Acoustic Properties, Hernan S. Alar, Proceso L. Fernandez Jr
Classifying Mosquito Presence And Genera Using Median And Interquartile Values From 26-Filter Wingbeat Acoustic Properties, Hernan S. Alar, Proceso L. Fernandez Jr
Department of Information Systems & Computer Science Faculty Publications
Mosquitoes are known to be one of the deadliest creatures in the world. There have been several studies that aim to identify mosquito presence and species using various techniques. The most common ones involve automatic identification of mosquito species from the sounds produced by flapping its wings. The development of these important concepts and technologies can help reduce the spread of mosquito-borne diseases. This paper presents a simple model based on mean and interquartile values that aim to solve the mosquito classification. Despite its simplicity, the proposed model significantly outperforms a Convolutional Neural Network (CNN) model in identifying the mosquito …
Automated Classification Model With Otsu And Cnn Method For Premature Ventricular Contraction Detection, Liang-Hung Wang, Lin-Juan Ding, Chao-Xin Xie, Su-Ya Jiang, I-Chun Kuo, Xin-Kang Wang, Jie Gao, Pao-Cheng Huang, Patricia Angela R. Abu
Automated Classification Model With Otsu And Cnn Method For Premature Ventricular Contraction Detection, Liang-Hung Wang, Lin-Juan Ding, Chao-Xin Xie, Su-Ya Jiang, I-Chun Kuo, Xin-Kang Wang, Jie Gao, Pao-Cheng Huang, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
Premature ventricular contraction (PVC) is one of the most common arrhythmias which can cause palpitation, cardiac arrest, and other symptoms affecting the work and rest activities of a patient. However, patients hardly decipher their own feelings to determine the severity of the disease thus, requiring a professional medical diagnosis. This study proposes a novel method based on image processing and convolutional neural network (CNN) to extract electrocardiography (ECG) curves from scanned ECG images derived from clinical ECG reports, and segment and classify heartbeats in the absence of a digital ECG data. The ECG curve is extracted using a comprehensive algorithm …
Detection Of Dental Apical Lesions Using Cnns On Periapical Radiograph, Chun-Wei Li, Szu-Yin Lin, He-Sheng Chou, Tsung-Yi Chen, Yu-An Chen, Sheng-Yu Liu, Yu-Lin Liu, Chiung-An Chen, Yen-Cheng Huang, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo
Detection Of Dental Apical Lesions Using Cnns On Periapical Radiograph, Chun-Wei Li, Szu-Yin Lin, He-Sheng Chou, Tsung-Yi Chen, Yu-An Chen, Sheng-Yu Liu, Yu-Lin Liu, Chiung-An Chen, Yen-Cheng Huang, Shih-Lun Chen, Yi-Cheng Mao, Patricia Angela R. Abu, Wei-Yuan Chiang, Wen-Shen Lo
Department of Information Systems & Computer Science Faculty Publications
Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or …
The Incubation Effect Among Students Playing An Educational Game For Physics, May Marie P. Talandron-Felipe, Ma. Mercedes T. Rodrigo
The Incubation Effect Among Students Playing An Educational Game For Physics, May Marie P. Talandron-Felipe, Ma. Mercedes T. Rodrigo
Department of Information Systems & Computer Science Faculty Publications
The incubation effect (IE) is a problem-solving phenomenon composed of three phases: pre-incubation where one fails to solve a problem; incubation, a momentary break where time is spent away from the unsolved problem; and post-incubation where the unsolved problem is revisited and solved. Literature on IE was limited to experiments involving traditional classroom activities. This initial investigation showed evidence of IE instances in a computer-based learning environment. This paper consolidates the studies on IE among students playing an educational game called Physics Playground and presents further analysis to examine the incidence of post-incubation or the revisit to a previously unsolved …
Caries And Restoration Detection Using Bitewing Film Based On Transfer Learning With Cnns, Yi-Cheng Mao, Tsung-Yi Chen, He-Sheng Jhou, Szu-Yin Lin, Sheng-Yu Liu, Yu-An Chen, Yu-Lin Liu, Chiung-An Chen, Yen-Cheng Huang, Shih-Lun Chen, Chun-Wei Li, Patricia Angela R. Abu, Wei-Yuan Chiang
Caries And Restoration Detection Using Bitewing Film Based On Transfer Learning With Cnns, Yi-Cheng Mao, Tsung-Yi Chen, He-Sheng Jhou, Szu-Yin Lin, Sheng-Yu Liu, Yu-An Chen, Yu-Lin Liu, Chiung-An Chen, Yen-Cheng Huang, Shih-Lun Chen, Chun-Wei Li, Patricia Angela R. Abu, Wei-Yuan Chiang
Department of Information Systems & Computer Science Faculty Publications
Caries is a dental disease caused by bacterial infection. If the cause of the caries is detected early; the treatment will be relatively easy; which in turn prevents caries from spreading. The current common procedure of dentists is to first perform radiographic examination on the patient and mark the lesions manually. However; the work of judging lesions and markings requires professional experience and is very time-consuming and repetitive. Taking advantage of the rapid development of artificial intelligence imaging research and technical methods will help dentists make accurate markings and improve medical treatments. It can also shorten the judgment time of …
Ethics Of Ai In Education: Towards A Community-Wide Framework, Wayne Holmes, Kaska Poraysa-Pomsta, Ken Holstein, Emma Sutherland, Toby Baker, Simon Buckingham Shum, Olga C. Santos, Ma. Mercedes T. Rodrigo, Mutlu Cukurova, Ig Ibert Bittencourt, Kenneth R. Koedinger
Ethics Of Ai In Education: Towards A Community-Wide Framework, Wayne Holmes, Kaska Poraysa-Pomsta, Ken Holstein, Emma Sutherland, Toby Baker, Simon Buckingham Shum, Olga C. Santos, Ma. Mercedes T. Rodrigo, Mutlu Cukurova, Ig Ibert Bittencourt, Kenneth R. Koedinger
Department of Information Systems & Computer Science Faculty Publications
While Artificial Intelligence in Education (AIED) research has at its core the desire to support student learning, experience from other AI domains suggest that such ethical intentions are not by themselves sufficient. There is also the need to consider explicitly issues such as fairness, accountability, transparency, bias, autonomy, agency, and inclusion. At a more general level, there is also a need to differentiate between doing ethical things and doing things ethically, to understand and to make pedagogical choices that are ethical, and to account for the ever-present possibility of unintended consequences. However, addressing these and related questions is far …
Vlsi Implementation Of A Cost-Efficient Loeffler-Dct Algorithm With Recursive Cordic For Dct-Based Encoder, Rih-Lung Chung, Chen-Wei Chen, Chiung-An Chen, Patricia Angela R. Abu, Shih-Lun Chen
Vlsi Implementation Of A Cost-Efficient Loeffler-Dct Algorithm With Recursive Cordic For Dct-Based Encoder, Rih-Lung Chung, Chen-Wei Chen, Chiung-An Chen, Patricia Angela R. Abu, Shih-Lun Chen
Department of Information Systems & Computer Science Faculty Publications
This paper presents a low-cost and high-quality; hardware-oriented; two-dimensional discrete cosine transform (2-D DCT) signal analyzer for image and video encoders. In order to reduce memory requirement and improve image quality; a novel Loeffler DCT based on a coordinate rotation digital computer (CORDIC) technique is proposed. In addition; the proposed algorithm is realized by a recursive CORDIC architecture instead of an unfolded CORDIC architecture with approximated scale factors. In the proposed design; a fully pipelined architecture is developed to efficiently increase operating frequency and throughput; and scale factors are implemented by using four hardware-sharing machines for complexity reduction. Thus; the …
Stabilization Of Cultural Innovations Depends On Population Density: Testing An Epidemiological Model Of Cultural Evolution Against A Global Dataset Of Rock Art Sites And Climate-Based Estimates Of Ancient Population Densities, Richard Walker, Anders Eriksson, Camille Ruiz, Taylor Howard Newton, Francesco Casalegno
Stabilization Of Cultural Innovations Depends On Population Density: Testing An Epidemiological Model Of Cultural Evolution Against A Global Dataset Of Rock Art Sites And Climate-Based Estimates Of Ancient Population Densities, Richard Walker, Anders Eriksson, Camille Ruiz, Taylor Howard Newton, Francesco Casalegno
Department of Information Systems & Computer Science Faculty Publications
Demographic models of human cultural evolution have high explanatory potential but weak empirical support. Here we use a global dataset of rock art sites and climate and genetics-based estimates of ancient population densities to test a new model based on epidemiological principles. The model focuses on the process whereby a cultural innovation becomes endemic in a population; predicting that this cannot occur unless population density exceeds a critical threshold. Analysis of the data; using a Bayesian statistical framework; shows that the model has stronger empirical support than a proportional model; where detection is directly proportional to population density; or a …
A High-Accuracy And Power-Efficient Self-Optimizing Wireless Water Level Monitoring Iot Device For Smart City, Tsun-Kuang Chi, Hsiao-Chi Chen, Shih-Lun Chen, Patricia Angela R. Abu
A High-Accuracy And Power-Efficient Self-Optimizing Wireless Water Level Monitoring Iot Device For Smart City, Tsun-Kuang Chi, Hsiao-Chi Chen, Shih-Lun Chen, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
In this paper; a novel self-optimizing water level monitoring methodology is proposed for smart city applications. Considering system maintenance; the efficiency of power consumption and accuracy will be important for Internet of Things (IoT) devices and systems. A multi-step measurement mechanism and power self-charging process are proposed in this study for improving the efficiency of a device for water level monitoring applications. The proposed methodology improved accuracy by 0.16–0.39% by moving the sensor to estimate the distance relative to different locations. Additional power is generated by executing a multi-step measurement while the power self-optimizing process used dynamically adjusts the settings …
Detection Of Myocardial Infarction Using Ecg And Multi-Scale Feature Concatenate, Jia-Zheng Jian, Tzong-Rong Ger, Han-Hua Lai, Chi-Ming Ku, Chiung-An Chen, Patricia Angela R. Abu
Detection Of Myocardial Infarction Using Ecg And Multi-Scale Feature Concatenate, Jia-Zheng Jian, Tzong-Rong Ger, Han-Hua Lai, Chi-Ming Ku, Chiung-An Chen, Patricia Angela R. Abu
Department of Information Systems & Computer Science Faculty Publications
Diverse computer-aided diagnosis systems based on convolutional neural networks were applied to automate the detection of myocardial infarction (MI) found in electrocardiogram (ECG) for early diagnosis and prevention. However; issues; particularly overfitting and underfitting; were not being taken into account. In other words; it is unclear whether the network structure is too simple or complex. Toward this end; the proposed models were developed by starting with the simplest structure: a multi-lead features-concatenate narrow network (N-Net) in which only two convolutional layers were included in each lead branch. Additionally; multi-scale features-concatenate networks (MSN-Net) were also implemented where larger features were being …
Design And Deployment Of A Mobile Learning Cloud Network To Facilitate Open Educational Resources For Asynchronous Learning, Joselito Christian Paulus M. Villanueva, Mark Anthony V. Melendres, Catherine Genevieve B. Lagunzad, Nathaniel Joseph C. Libatique
Design And Deployment Of A Mobile Learning Cloud Network To Facilitate Open Educational Resources For Asynchronous Learning, Joselito Christian Paulus M. Villanueva, Mark Anthony V. Melendres, Catherine Genevieve B. Lagunzad, Nathaniel Joseph C. Libatique
Biology Faculty Publications
This paper describes the design and deployment of a mobile cloud network that facilitates open educational resource content distribution. The setup utilized clustered single board computers as content, communication and monitoring servers. It was installed in a Public High School where stakeholders, using their mobile devices, were given access to preloaded content via wireless local area network. Initial tests of the mobile cloud showed good network performance. Teachers were randomly selected to evaluate the content validity and delivery of the OER content. Results show that the quality of the network’s OER content is very satisfactory. This implementation shows the advantage …
Comparison Of English Comprehension Among Students From Different Backgrounds Using A Narrative-Centered Digital Game, May Marie P. Talandron-Felipe, Kent Levi A. Bonifacio, Gladys S. Ayunar, Ma. Mercedes T. Rodrigo
Comparison Of English Comprehension Among Students From Different Backgrounds Using A Narrative-Centered Digital Game, May Marie P. Talandron-Felipe, Kent Levi A. Bonifacio, Gladys S. Ayunar, Ma. Mercedes T. Rodrigo
Department of Information Systems & Computer Science Faculty Publications
This paper reports the continuation of the field testing of a narrative-centered digital game for English comprehension called Learning Likha: Rangers to the Rescue (LLRR) with a two-fold goal: first, identify the differences in terms of usage, attitudes towards, and perceptions of the English language between students from southern Philippines and the National Capital Region, and second, to determine how the LLRR in-game performance, post-test comprehension scores, engagement, and motivation of students differ between the groups. The participants who are grade school students from a province in southern Philippines answered questionnaires about their attitude towards and perception of English, played …
Introducing A Test Framework For Quality Of Service Mechanisms In The Context Of Software-Defined Networking, Josiah Eleazar T. Regencia, William Emmanuel S. Yu
Introducing A Test Framework For Quality Of Service Mechanisms In The Context Of Software-Defined Networking, Josiah Eleazar T. Regencia, William Emmanuel S. Yu
Department of Information Systems & Computer Science Faculty Publications
In traditional non-distributed networking architecture, supporting Quality of Service (QoS) has been challenging due to its centralized nature. Software-Defined Networking (SDN) provides dynamic, flexible and scalable control and management for networks. This study introduces a test framework for testing QoS mechanisms and network topologies inside an SDN environment. Class-Based Queueing QoS mechanisms are tested as an anchor to test the introduced framework. Using a previous study as a benchmark to test the introduced framework, results show that the test framework works accordingly and is capable of producing accurate results. Moreover, results in this study show that the distributed Leaf-enforced QoS …
Transactional Distances During Emergency Remote Teaching Experiences, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito
Transactional Distances During Emergency Remote Teaching Experiences, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito
Department of Information Systems & Computer Science Faculty Publications
The Transactional Distance Theory posits that successful remote learning occurs when teachers decrease psychological or transactional gaps. Narrowing the transactional distance can be achieved through a balance of appropriate course structure and dialogue, fostering healthy student autonomy in the process. This paper describes the Emergency Remote Teaching experiences of faculty and students of the Ateneo de Manila University in the Philippines. It examines these experiences in the context of the transactional distance framework. Findings show that a sudden shift to remote learning mandates greater student autonomy, which increases transactional distance. Because of this, efforts by faculty to increase student-teacher dialogue …
Activity Based Traffic Indicator System For Monitoring The Covid-19 Pandemic, Justin Junsay, Aaron Joaquin Lebumfacil, Ivan George Tarun, William Emmanuel S. Yu
Activity Based Traffic Indicator System For Monitoring The Covid-19 Pandemic, Justin Junsay, Aaron Joaquin Lebumfacil, Ivan George Tarun, William Emmanuel S. Yu
Department of Information Systems & Computer Science Faculty Publications
This study describes an activity based traffic indicator system to provide information for COVID-19 pandemic management. The activity based traffic indicator system does this by utilizing a social probability model based on the birthday paradox to determine the exposure risk, the probability of meeting someone infected (PoMSI). COVID-19 data, particularly the 7-day moving average of the daily growth rate of cases (7-DMA of DGR) and cumulative confirmed cases of next week covering a period from April to September 2020, were then used to test PoMSI using Pearson correlation to verify whether it can be used as a factor for the …
Cura Personalis: Institutionalizing Compassion During Emergency Remote Teaching, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito
Cura Personalis: Institutionalizing Compassion During Emergency Remote Teaching, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito
Department of Information Systems & Computer Science Faculty Publications
Faced with the fears and anxieties brought on by the COVID-19 crisis, educational institutions had to devise new compassion-based teaching and learning policies and approaches that recognized and provided for the pandemic’s psychological and emotional toll. This paper describes how the Ateneo de Manila University in the Philippines enacted its core value of cura personalis, care for the entire person, in the context of emergency remote teaching. We describe the circumstances that prompted the greater emphasis on compassion and the adjustments to classroom management, course content, class interactions, and assessment. Finally we describe the tradeoffs or costs of this …