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1.
ACM/IEEE Workshop on Computer Architecture Education (WCAE) ; 2021.
Article in English | English Web of Science | ID: covidwho-1883155

ABSTRACT

The COVID-19 pandemic necessitated courses being moved online and preferably made asynchronous. This was particularly challenging for small liberal arts colleges, whose faculty and students are used to close interaction. This paper describes the set of interactive asynchronous mini-lectures and online lab assignments used for an undergraduate computer architecture course at Mills College. The materials, which follow best practices for active learning, are available online for faculty at other institutions to use and modify under a Creative Commons license. We also discuss the pros and cons of making the course self-paced.

2.
IEEE Region 10 Conference (TENCON) ; : 11-16, 2021.
Article in English | English Web of Science | ID: covidwho-1883151

ABSTRACT

This descriptive study determined the predictors that influenced the online academic self-concept of 484 computing students. It was shown the participants of this study did not experience technical barriers. However, they perceived they had an intermittent Internet connection. There was almost an equal number of participants in terms of access or lack thereof to a personal physical learning space for online classes. It was revealed they prefer to be assisted by their teachers or their classmates to understand the course content. They perceived online learning as more difficult than the face-to-face mode and they would achieve a lower grade in online learning. They had low perceptions of their abilities for coping with online learning and had a negative interest in it. Pearson correlation analysis showed academic self-concept in terms of abilities and interests had a significant moderate positive relationship with perceived online academic performance. Multiple regression analyses showed personal learning space and year level were consistent predictors of online academic self-concept. Recommendations and implications are offered.

3.
IEEE Region 10 Conference (TENCON) ; : 429-434, 2021.
Article in English | English Web of Science | ID: covidwho-1883150

ABSTRACT

COVID-19, particularly vaccines, have caused an 'infodemic' online;a rapid and vast spread of unreliable information. While vaccines can minimize the detrimental effects of COVID-19, misinformation, fearmongering, and 'anti-vax' movements have fostered opposition which is especially prevalent on Twitter. Understanding public emotions related to vaccines is an important, yet inconsistent, area of research. To resolve some of the inconsistencies in the field, we develop and apply two integrated emotion detection models to a longitudinal sample of COVID-19 vaccine related tweets (n = 823,748). Contrary to prior research, which concluded that positive emotions are the most dominant emotion (e.g., trust and happiness), the balanced emotion model (consisting of eight emotions) shows that fear (41%) is the most dominant emotion. The extended emotion model (consisting of sixteen emotions) shows various negative emotions such as panic (27%), fear (22%), and shame (37%) as the dominant emotions in the tweet hashtag groups such as COVID-19, Vaccine, and Anti-vaxxers.

4.
IEEE Region 10 Conference (TENCON) ; : 620-625, 2021.
Article in English | English Web of Science | ID: covidwho-1883149

ABSTRACT

Currently, much medical personnel died because of being infected by COVID-19 and because of low personal protective facilities and the duties of medical personnel that must carry out to deliver the logistics to patients and make many contacts between the medical personnel and patients of COVID-19. Mobile robots are considered the right solution to complete this problem. With mobile robots, hospitals or the place of isolation can minimize contact between medical personnel and patients of COVID-19 by carrying out the logistic delivery task. To deliver the logistic, a mobile robot must have low-level control, and the mechanism to carry out the workpiece also have the mechanism to open the door. The mechanism to carry out the workpiece is a system to pick up and place the rack of logistics from one place to another. In this study, the low-level control was applied using a PID control with the parameter's value k(p)=500, t(i)=0.001, and t(d)=0.001 and teleoperation to control the mobile robot manually, so the mobile robot was able to move and carry out the load with the maximum value is 13 kg also open the door. Based on the results of the tests that have been carried out, the mobile robot with the proposed low-level control and the object management system can do the delivery task to reduce contact between medical personnel and patients of COVID-19, also the mobile robot can be controlled manually.

5.
IEEE Region 10 Conference (TENCON) ; : 750-755, 2021.
Article in English | English Web of Science | ID: covidwho-1883148

ABSTRACT

This paper presents a systematic literature review and bibliometric analyses of Scopus-indexed documents in social media analytics in health during the CoVid-19 pandemic that used artificial intelligence methodologies. From the 179 extracted Scopus-indexed publications in August 2021, 128 were left after removing 51 documents using the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) procedure. Analyses and visualizations using VOSviewer reveal research productivity, affiliation and collaboration networks, and the corresponding relationship between research productivity and the research networks. Conclusions and recommendations for future work are presented to further nurture the current research environment of social media analytics through artificial intelligence methodologies.

6.
IEEE Region 10 Conference (TENCON) ; : 556-561, 2021.
Article in English | English Web of Science | ID: covidwho-1883147

ABSTRACT

The lockdown as a countermeasure at the onset of the COVID-19 pandemic gained diverse responses globally. Many turned to Social Media platforms such as Twitter to express their sentiments on health crisis-related concerns. This study magnified the collective support-related Twitter content posted by users within the Philippines at the beginning of the pandemic. Collective Support expressions were collected using the Twitter Python Library and examined using content analysis. The primary goal is to elicit insights to understand the Filipinos' social/collective behaviors and how they were manifested at the onset of the COVID-19 lockdown. Hofstede's and Triandis' Theory of Collectivism primarily guided the direction of the study towards the affirmation of the Philippines as a collectivistic nation as demonstrated in the Collective Support Tweets classified under the following identified themes: (1) Language of Appreciation, Tribute, Support, covering the most significant percentage with 38.96% of the collective support tweets;(2) Friendly Reminders with 28.91%;(3) Acts of Community Service comprising 20.31%;and (4) Encouraging Words forming 11.82%. Given the Filipino's traditional familial and community-oriented culture, their collectivistic behavior shall naturally be conveyed irrespective of location, technology, and other relevant settings. However, considering the Twitter dataset under study, the technology shaped cultural implications based on the shared Twitter content in the Philippines. Further, it has affirmed the Philippines' collectivistic culture in accordance with the indicators under Hofstede's and Triandis' Theory of Collectivism.

7.
IEEE Region 10 Conference (TENCON) ; : 586-590, 2021.
Article in English | English Web of Science | ID: covidwho-1883146

ABSTRACT

COVID-19, a new coronavirus disease, is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and was declared a pandemic by the World Health Organization (WHO). Since its outbreak in December 2019, the total number of affected cases reported worldwide has exceeded 215 million, and reported death cases are 4.49 million as of August 2021. The early detection of the disease is necessary to treat the infected people and control the spreading of the disease. In this report, a convolutional neural network-based methodology is introduced to detect and distinguish the infection caused by SARS-CoV-2 from common viral Pneumonia through Chest X-ray images. The method consists of four convolutional layers with dense connections along with ReLU activation functions for image classification. The images are collected from the internet to create the entire dataset and are classified as COVID Pneumonia, non-COVID Pneumonia, and normal. The method produces a training accuracy of 97.61% and validation accuracy of 96.98%.

8.
IEEE Region 10 Conference (TENCON) ; : 839-844, 2021.
Article in English | English Web of Science | ID: covidwho-1883145

ABSTRACT

The challenges of internationalization, the diversion to outcome-based education, and the emergence of the COVID-19 pandemic triggered a growing demand for quality educators. Hence, educational institutions shall ensure continuous evaluation of faculty performance and use its data as a tool to capacitate learning providers and enhance instruction in the classroom. Using the identified performance indicators, this study aims to elicit insights from the dataset extracted from the Faculty Performance Evaluation System (FPES) of the Camarines Sur Polytechnic Colleges (CSPC) to understand how the students perceived their respective instructors' performance levels prior to and at the onset of the COVID-19 pandemic. Generated patterns were uncovered using descriptive analysis based on the students' ratings. Meanwhile, the students' comments, suggestions, and recommendations were analyzed using Sentiment Analysis through TextBlob. The same dataset was further examined to recommend a prescribed action using a supervised learning method (Decision Tree Algorithm). With 98% model accuracy, faculty performance testing dataset were provided with prescribed actions with the following rules: Outstanding & Very Satisfactory Ratings = Re-Hire/No Action Needed;Satisfactory = Mentorship;Unsatisfactory & Poor = Re-Training & Re-Evaluation. The study discovered a decline in the faculty performance evaluation results at the onset of the COVID-19 pandemic. However, the students' sentiments were considerate to the faculty's endeavor as most of its polarity scores fell under "positive." Recommendations to strengthen and boost faculty performance were incorporated based on the findings of the prescriptive analysis.

9.
IEEE Region 10 Conference (TENCON) ; : 658-663, 2021.
Article in English | English Web of Science | ID: covidwho-1883144

ABSTRACT

Despite the widespread success of online shopping, it is not available to all consumer types. In this sense, visually impaired and elderly users, in particular, frequently face daunting barriers. Due to the inaccessibility and difficulty of current online shopping mobile applications, millions of visually impaired and elderly people are unable to benefit from the convenience provided by online shopping. Developing ideas that inspire people is really essential for visually impaired and elderly people to engage in social life. Generic product explanations, unhelpful images, and visually appealing user experiences are provided to average eyes in online shopping, and they are incompatible with visually impaired people, even with visually impaired assistive devices. Due to visual barriers and inaccessible user experiences, the visually impaired are struggling to do online shopping independently. During this COVID-19 pandemic situation, online shopping is one of the better ways to meet everyone's needs and wants. Ordinary individuals can meet their needs and desires, but the visually impaired and elderly people who live alone find it difficult to manage their daily life. Therefore, we have come up with a solution for this by having an online shopping mobile application. Our objective with this application is to assist visually impaired and elderly individuals in meeting their underlying needs and to help them in this pandemic situation. This paper presents an online shopping mobile application for visually impaired and elderly people that allows them to shop online in a variety of convenient ways.

10.
IEEE Region 10 Conference (TENCON) ; : 293-298, 2021.
Article in English | English Web of Science | ID: covidwho-1883143

ABSTRACT

In this paper, we compare the three countries, India, Japan, and Indonesia's Twitter topics concerning COVID-19. The tweet data were collected from the period of April 2021 to June 2021. The damage of COVID-19 in India and Indonesia was unprecedented in our human beings history. Unexpectedly we could collect Tweets concerning the pandemic. From the data, we would like to extract unexpected topics to prepare for future challenges from humanitarian standpoints. In Japan, the female suicide rate raised significantly. In India, the Joint Entrance Examination were cancelled due to the pandemic, which caused irregular educational systems timeline for Indian students which might create a lot of concerns in future. In Indonesia, Tweets during the peak period on June 2021 have shown some record of discussion on the scarcity of oxygen tubes at isolation houses during the surge of COVID-19 pandemic cases. The results of the analysis showed us the growing fear of the infection, the situation of lack of oxygen tubes, the sad news of the increase in suicides in Japan, the confusion of the entrance examination system nationwide in India, and services related to the distribution of subsidies from the government in Indonesia.

11.
Photonics and Electromagnetics Research Symposium (PIERS) ; : 2885-2891, 2021.
Article in English | English Web of Science | ID: covidwho-1883140

ABSTRACT

This paper aims to show the capability of the Huygens Principle-based microwave imaging for use in Lung COVID-19 infection detection. Frequency-domain measurements have been performed in an anechoic chamber using two Microstrip antennas operating at frequency range of 1 to 5 GHz, in a multi-bistatic fashion, employing dedicated phantoms that mimic the dimensions and the dielectric properties of a human torso, containing a target mimicking an infection. A Multi-layered elliptically-shaped torso-mimicking phantom having the circumference of 82 cm has been constructed;the external layer mimics the dielectric properties of a combination of muscle, fat and rib bone tissues, the inner layer mimics the dielectric properties of lung (inflated). A cylindrically-shaped tube of water has been positioned inside the inner layer to dielectrically mimic the infection. The S-21 signals have been used for image reconstruction (after removing artifacts), obtaining detection with a signal to clutter ratio of 7 dB. Our results confirm that Huygens based technique can be successfully used for lung infection detection even if antennas and phantom are in free space, i.e., no coupling liquid is required.

12.
Photonics and Electromagnetics Research Symposium (PIERS) ; : 1961-1966, 2021.
Article in English | English Web of Science | ID: covidwho-1883139

ABSTRACT

Wuhai City is an important coal resource area in Inner Mongolia Autonomous Region. High-intensity underground mining will cause large land subsidence. Differential SAR Interferometry (D-InSAR) is a popular monitoring method of land subsidence in recent years. This paper uses two-pass D-InSAR method to monitor land subsidence in Wuhai City. The experimental data selects 7 scenes of C-band Sentinel-1A images from September 2019 to March 2020. The final deformation results are shown in the Figure 3. The two-pass D-InSAR processing flow includes data focusing, baseline estimation, interferogram generation, adaptive filtering and coherence generation, phase unwrapping, orbit refining and re-flattening, deformation map generation. The result shows: During the monitoring time, the most serious subsidence areas are concentrated near the mine clusters on the east and west sides of Wuhai City. Maximum settlement value up to 242 mm. The subsidence values in heavy industrial and residential areas are slightly smaller compared to the former. Settlement values are generally ranged from 56 to 87 mm. The settlement is lightest in the southern part of Hainan district. It indicates that mining can greatly accelerate surface subsidence. Meanwhile, human activities and groundwater extraction can increase subsidence. From the perspective of time, Settlement in Wuhai City is more pronounced during September to December 2019 but it decreases sharply in January 2020.This should be related to the outbreak of COVID-19. The subsidence value increased slightly from February to March 2020, which showed that the epidemic had been preliminarily controlled and people began to return to work.

13.
Photonics and Electromagnetics Research Symposium (PIERS) ; : 2678-2686, 2021.
Article in English | English Web of Science | ID: covidwho-1883138

ABSTRACT

UV exposure cabinet is usually used for aging samples in various scientific fields such as chemistry, biology, historical objects, and coating scopes. In our case study, these kinds of cabinets were prepared to be used in the disinfection field. To have such an appropriate effect, there should be - as possible - a uniform exposing dose along with the whole irradiated area inside the cabinet. The proposed exposing cabinet consists of ten parallel UVC fluorescent lamps at the top and bottom of the cabinet's internal surface (group (A)). To enhance the irradiance and uniformity, two additional UVC lamps supported the UV lamps set (group (B)). The average values of irradiance and uniformity for the two groups, (A) and (B), were recorded. The results showed that the uniformity over the irradiated area improved by approximately 16.6%. When applying two collections of covid19 scan samples (coll (a) and coll (b)), the results showed that in the case of coll (b) with a group (B), the annihilation of the virus was succeeded almost along the irradiated area, which is much better than that what noticed in case of coll (a). Depending on the results, this paper discusses how the proposed enhancement technique used inside the exposing cabinets may help in the COVID-19 epidemic in disinfection purposes.

14.
12th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP) ; : 52-55, 2021.
Article in English | English Web of Science | ID: covidwho-1883137

ABSTRACT

The outbreak of COVID-19 calls for the improvement of infectious disease dynamics model to meet the requirements of future infectious disease's prediction and risk assessment. On the basis of SEIR model, a new transmission dynamics model named as SSEIR is proposed. In order to describe the dynamics evolution of the SSEIR model, a new set of ordinary differential equations (ODE) is constructed. The SSEIR dynamics model is used to simulate and predict the progress of pandemic situation inWuhan, China. Because that the suspected people have different dynamics characteristics from the susceptible people and the exposed people, this paper put them in a new independent category. To describe the dynamics evolution of SSEIR model, a new set of ordinary differential equations (ODE) is constructed. The SSEIR model can be used to simulate and predict the progress of infectious diseases.

15.
5th International Conference on Vision, Image and Signal Processing (ICVISP) ; : 206-211, 2021.
Article in English | English Web of Science | ID: covidwho-1883123

ABSTRACT

With increasing physical threats in recent years targeted at critical infrastructures, it is crucial to establish a reliable threat monitoring system integrating video surveillance and digital sensors based on cutting-edge technologies. A physical threat monitoring solution unifying the floorplan, cameras, and sensors for smart buildings has been set up in our study. Computer vision and deep learning models are used for video streams analysis. When a threat is detected by a rule engine based on the real-time analysis results combining with feedback from related digital sensors, an alert is sent to the Video Management System so that human operators can take further action. A physical threat monitoring system typically needs to address complex and even destructive incidents, such as fire, which is unrealistic to simulate in real life. Restrictions imposed during the Covid-19 pandemic and privacy concerns have added to the challenges. Our study utilises the Unreal Engine to simulate some typical suspicious and intrusion scenes with photorealistic qualities in the context of a virtual building. Add-on programs are implemented to transfer the video stream from virtual PTZ cameras to the Milestone Video Management System and enable users to control those cameras from the graphic client application. Virtual sensors such as fire alarms, temperature sensors and door access controls are implemented similarly, fulfilling the same programmatic VMS interface as real-life sensors. Thanks to this simulation system's extensibility and repeatability, we have consolidated this unified physical threat monitoring system and verified its effectiveness and user-friendliness. Both the simulated Unreal scenes and the software add-ons developed during this study are highly modulated and thereby are ready for reuse in future projects in this area.

16.
International Conference on Maintenance and Intelligent Asset Management (ICMIAM) ; 2021.
Article in English | English Web of Science | ID: covidwho-1883122

ABSTRACT

With the outbreak of COVID-19 all over the world, it has become increasingly important to understand and effectively manage air quality in enclosed environments. The effect of HVAC (Heating, Ventilation, and Air Conditioning) systems in airborne disease transmission is crucial especially in confined public places such as hospitals, buses, and railway coaches. Computational Fluid Dynamics has become an important tool for studying and understanding the behaviors of fluid flow especially aerosol transport in such enclosed spaces. The current paper focuses on simulating the behavior of air in the indoor environment of a railway coach under four different conditions. These are where the rail coach has no occupants and with three occupants with the effect of three and six different HVAC supply air inlet conditions explored. The results show that without occupants, the air from the inlet spreads into the coach with relatively low velocity and maintains its speed throughout the coach until at the outlet where it speeds up. With occupants in the coach, the incoming air was observed to spread wide and exits the coach with much higher velocity. This is due to the reduced available flow area occasioned by the occupants, and this information will be useful in further studies with aerosol transport within the coach.

17.
IEEE International Conference on Mechatronics and Automation (IEEE ICMA) ; : 950-955, 2021.
Article in English | English Web of Science | ID: covidwho-1883121

ABSTRACT

Due to the COVID-19 epidemic, there has been a high demand for non-contact diagnostic equipment that can reduce exposure and cross-infection. A non-contact medical detection robot is a type of diagnostic equipment and medical service robot with a wide application prospect. However, few non-contact medical detection robots have been designed to collect patients' physiological parameters when they are in inconvenient situations, such as bedridden, during clinical usage. A six-degree-of-freedom (six-DOF) face tracking method based on a six-DOF robot is proposed in this paper. In the proposed system, a face detector equipped with a camera attached to the robot's wrist is used to obtain the real-time face depth and attitude information. The optimal target attitude of the camera is calculated according to the constraints in the base coordinate system. A closed-loop controller is designed to control the robot to reach the target position and posture smoothly. The experiment with a six-DOF robot has verified that the proposed system can achieve the real-time tracking of human faces by a camera. The proposed method can also be used in many other scenarios where six-DOF face tracking is required by robots.

18.
IEEE International Conference on Mechatronics and Automation (IEEE ICMA) ; : 65-70, 2021.
Article in English | English Web of Science | ID: covidwho-1883120

ABSTRACT

The 2022 Winter Olympics bid success promoted the development of the ice and snow sports in China. The emergence of indoor skiing system drives the ski and snow sports into a highly developed period especially at the normal prevention and control stage of COVID-19. However, the conventional indoor skiing system is insufficient in sports experience and inability to track the skier trajectory and attitude for training. Fortunately, the Ultra-Wide Band (UWB) and Micro Inertial Navigation System (MINS) are widely used in indoor environments due to high-precision positioning and low-cost priorities. UWB presents high accuracy in positioning, while it is easily to be disturbed by the Non Line of Sight (NLOS) and multipath effects. Meanwhile, the MINS error would accumulate with time. Therefore, this paper proposed a MINS/UWB integration algorithm to implement the trajectory and attitude measurement of the skier with low-cost. Meanwhile, the MINS/UWB based Extended Kalman Filter (EKE) is designed with sequential algorithm for skiing. Finally, both the indoor positioning experiment and the intelligent skiing system verification experiment were carried out to verify the accuracy of MINS/UWB integration system. Experimental results show the MINS/UWB integration technology could locate effectively When the UWB signal is intermittently blocked.

19.
2nd International Conference on Big Data and Artificial Intelligence and Software Engineering (ICBASE) ; : 673-678, 2021.
Article in English | English Web of Science | ID: covidwho-1883119

ABSTRACT

Electromyography has been extensively used in a variety of fields. By using feature extraction to detect and analyze the surface EMG signal of Electromyography, muscle fatigue caused by daily life workout could be detected more timely. Here we intend to utilize this feature of using feature extraction on electromyography to offer professional advice for at home work out due to the deduction of outing caused by COVID-19. In this work, multiple time window (MTW) features have been used to distinguish the surface electromyography (sEMG) signals between muscle fatigue during arm movements by using Python. The sEMG signals are monitored from the biceps muscle of 3 healthy subjects. 4 window functions named boxcar function, hamming function, blackman function, and kaiser function and 24 features are extracted. 4 classifiers named Decision Tree, Random Forest, Support Vector Machine, and Naive Bayes are used in this research. The classifier using MTW features compared with the classifier without MTW feature. The Random Forest classifier has the greatest accuracy of 95.16%.

20.
2nd International Conference on Big Data and Artificial Intelligence and Software Engineering (ICBASE) ; : 157-161, 2021.
Article in English | English Web of Science | ID: covidwho-1883118

ABSTRACT

Accurate facial recognition can effectively help the population combat the disease by offering risk-free phone usage, access controls, etc. In the era of COVID-19, a mask has become a necessity. However, masks may reduce the accuracy of face recognition to some degree. Thus, it is necessary to use deep learning to increase face recognition accuracy by recovering the face with a mask. For this purpose, this study proposed an AI-based model based on Pix2pix and U-net generator for restoring face mask images using the paired image database. In the training step, we used two adversarial models, including one generator and one discriminator. Then they are extended to a conditional model, which will be piped to the Pix2pix algorithm once again. U-Net was built in the training of the generator. The loss curves of generator and discriminators show that as iteration time increases, the loss of fake discriminator becomes lower stably. In contrast, the loss of real discriminator has the same tendency. In the meantime, the loss of generator shows an increased tendency. The result indicates that our model can help build reliable face mask restoration for daily use, which helps to improve the recognition accuracy of the face with a mask.

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