3dinfogan: 3d Models’ Reconstruction In Infogans

In computer vision and computer graphics, 3D reconstruction is the process of capturing real objects’ shapes and appearances. 3D models always can be constructed by active methods which use high-quality scanner equipment, or passive methods that learn from the dataset. However, both of these two methods only aimed to construct the 3D models, without showing what element affects the generation of 3D models. Therefore, the goal of this research is to apply deep learning to automatically generating 3D models, and finding the latent variables which affect the reconstructing process. The existing research GANs can be trained in little data with two networks called Generator and Discriminator, respectively. Generator can produce synthetic data, and Discriminator can discriminate between the generator’s output and real data. The existing research shows that InFoGAN can maximize the mutual information between latent variables and observation. In our approach, we will generate the 3D models based on InFoGAN and design two constraints, shape-constraint and parameters-constraint, respectively. Shape-constraint utilizes the data augmentation method to limit the synthetic data generated in the models’ profiles. At the same time, we also try to employ parameters-constraint to find the 3D models’ relationship corresponding to the latent variables. Furthermore, our approach will be a challenge in the architecture of generating 3D models built on InFoGAN. Finally, in the process of generation, we might discover the contribution of the latent variables influencing the 3D models to the whole network.

STROKE REHABILITATION EXERCISE KINECT GAME AS A MODALITY FOR HOME-BASED THERAPY

Traditional rehabilitation is a tedious process which is reducing the patients' motivation to perform rehabilitation exercises. Therefore, patients need a program that can entice them to do rehabilitation exercises at home. This research aims to identify the game's needs based on the traditional rehabilitation, design a prototype of a recovery game based on traditional rehabilitation, and test the effectiveness of the rehabilitation game. There are two different game types in this rehabilitation game, with three different movement types used to interact. The prototype developed based on four elements, which are the elements of rehabilitation game, type of movement rehabilitation exercises, technology constraints faced by post-stroke patients, and the basic principle of interface design. Because of patients face physical constraints, Kinect was used in this game to interact with. Using Kinect, the patient is not bound to any device to interact with the game. The game also introduces a social background that encourages patients to have a friend to play either through competition or cooperation.By evaluating by observation and interviews, the game was accepted by post-stroke patients and their family members. They also provide a suggestion for improvement in the future. The contribution of this research is to measure whether the Kinect game console and this game can help patients do additional recovery exercises at home without the supervision of the therapist

Mobile Augmented Reality Application In Medical Education In The 2010s

In the recent years, medical education is facing various difficulties. Students are struggling to visualize the internal organs and bones, it is insufficient cadaver for dissection demonstration, there are lack of equipment for training, and not enough opportunity for hands-on training. Technologies have been utilized to supplement teaching in medical education to overcome the mentioned difficulties. Augmented Reality in particular mobile Augmented Reality has shown a rise in the application of medical education in this decade. This paper aims to do a narrative review to study the overall progress and development of mobile Augmented Reality application in medical education from year 2010 to 2020. From the review done, we found that the application of mobile Augmented Reality in medical education is feasible, it is well accepted by medical students. We also identified current research gaps and potential future development of mobile Augmented Reality in medical education. It was found that there is lack of research done to study long term effect on the users. Interaction between virtual object and real-world object was lacking in some applications. More refinement and update are needed on flow, media and design of Augmented Reality application. There is also essential to study the influence of marker size or surface material.

The Influence of Technostress Factors on Information System Success

Information systems (IS) are one of the factors that catalyze the success of an organization. Apart from assisting in the delivery process, the system can also affect the nature of its users which in turn will also affect the level of delivery of the organization. Mathematical Communication Theory has stated that in the process of conveying information, there are disturbances that will disrupt the communication process and one of them is psychological disorders. Psychological disorders related to technology, ie technostress are seen as very synonymous and can affect the user’s behavior of the systems. Indirectly, it can also affect the level of productivity and quality of delivery of an organization. Ironically, studies looking at this issue are missing, hence the motivation of this paper to propose technostress factors and investigate its relationship in information system success. Therefore, the main objective of this study is to study the effect of technostress factors and its impact on the system success. This study was conducted using a quantitative approach where questionnaires are used as a medium for data collection. The results of this study prove that the dimension of psychological influence (technostress) introduced as a new dimension has had a significant impact on the information systems success. The most important contribution of this study is the combination of two fields of study, namely the field of information system and the field of psychology in producing a model of information system success that is able to measure the success of an information system more comprehensively.

Interrelated Decision-Making Model for Diabetes

Diabetes is one of the growing chronic diseases. Proper treatment is needed to produce its effects. Past studies have proposed an Interrelated Decision-making Model (IDM) as an intelligent decision support system (IDSS) solution for healthcare. This model can provide accurate results in determining the treatment of a particular patient. Therefore, the purpose of this study is to develop a diabetic IDM to see the increased decision-making accuracy with the IDM concept. The IDM concept allows the amount of data to increase with the addition of data records at the same level of care, and the addition of data records and attributes from the previous or subsequent levels of care. The more data or information, the more accurate a decision can be made. Data were developed to make diagnostic predictions for each stage of care in the development of type 2 diabetes. The development of data for each stage of care was confirmed by specialists. However, the experiments were performed using simulation data for two stages of care only. Four data sets of different sizes were provided to view changes in forecast accuracy. Each data set contained 2 data sets of primary care level and secondary care level with 4 times the change of the number of attributes from 25 to 58 and the number of records from 300 to 11,000. Data were developed to predict the level of diabetes confirmed by specialist doctors. The experimental results showed that on average, the J48 algorithm showed the best model (99%) followed by Logistics (98%), RandomTree (95%), NaiveBayes Updateable (93%), BayesNet (84%) and AdaBoostM1 (67%). Ratio analysis also showed that the accuracy of the forecast model has increased up to 49%. The MAPKB model for the care of diabetes is designed with data change criteria dynamically and is able to develop the latest dynamic prediction models effectively.v

Augmented Reality Mobile Application For Malay Heritage Museum

Lack of staffs and language barriers are two factors that limit the Malay Heritage Museum UPM staffs to handle visitors especially during peak seasons. Therefore, an augmented reality mobile application is proposed to assists and entertain visitors while touring the museum. In this work, the augmented reality will be imposed at the Malay traditional cloth and textiles section. To develop the propose application, the methodology used in this work is agile model due to its capability to ensure that the overall process can be done within a time given and also its ability to increase the standard software instantly. Agile model consists of six phases such as requirements, design, development, testing, deployment and review. The experiment was conducted on the same day and three hours were allocated for the respondent because they were having classes. The time required for one respondent to experience the MTRACR is approximately 10 minutes per person. The survey is used as a platform to get feedbacks from users. Based on the survey, it shows that all users were satisfied with the proposed application and they suggested others to use it.

Meaningful Programming Learning Using Technology Integration: Implementation And Application Level

Technology integration involves a combination of applications, media, systems, approaches and techniques guided by information and communication technology to increase student engagement and effectiveness of learning comprehension. Programming learning encounters a specific challenge related to students’ limited opportunities in dealing with real cases leading to inconsistent development of their interests and potentials. The integration of technology has a potential to provide a solution to this problem, but insuitable use of technology hinders students to gain meaningful learning and develop confidence in solving problems. This study develops a framework in the implementation of technology integration to promote meaningful learning for undergraduate students of programming courses. The study also measures the level of frequency and use of technology integration in meaningful learning of programming courses. The study identifies five main elements through literature to develop a framework namely learning technology, skills, application of technology, meaningful learning and contextual learning. Next, the measurement of the level of frequency and use of technology integration involves a sample of 109 undergraduate students in a programming course through stratified random sampling. The research framework is expected to provide guidance on the implementation of technology integration in meaningful programming learning and to measure the relevant elements. The findings of the study are expected to help educators and administrators to adopt and improve technology integration in meaningful learning for programming courses.

Explaining The Impact Of Information Technology Capabilities And Organizational Acceleration On Performance Of Banking Sector

This study aimed to explain the effect of information technology capabilities and organizational acceleration on performance with the role of innovation capacity moderator in the banking sector of Mazandaran province of Iran during 2020-21. The statistical population of the study includes 1400 people. In order to determine the sample size based on Cochran's limited formula, the number of samples in this study was set at 302, which were selected by simple random sampling. We collect the primary data through fieldwork, and the instrument of primary data collection was five-choice Likert questionnaires, and also library method was used to collect secondary data. Both content and formal methods were used for the validity of this questionnaire, and we analyzed its reliability with Cronbach's alpha that the overall reliability is equal to 0.906. Structural equation modeling using smart PLS software was also used to test the research hypotheses. The results showed that information technology capabilities and innovation capacity have a significant relationship with organizational acceleration. In addition, Organizational acceleration has a significant relationship with organizational performance, and innovation capacity in the relationship between IT capabilities also has a moderating role on organizational acceleration.

Hybridising Signaling Principle And Nielsen’s Design Guidelines In A Mobile Application

Learning via mobile phone is very common nowadays, whether at the primary or tertiary stage. The use of mobile phones is causing growing concern among the general public. Improving online education, primarily via this device, is also one of the government’s most pressing needs. Most current research on mobile learning applications pays little attention to multimedia principles, especially the Signalling principle, to improve user interaction. As a result, this project is undertaken to suggest better and more efficient mobile learning applications. The model is developed in collaboration with various stakeholders, including content experts, HCI experts, actual users, and a thorough literature review. Creating these mobile learning design guidelines is anticipated to lead to a more efficient and successful mobile learning style. According to the results of the experiments, implementing the hybridised guidelines resulted in a significant increase in Asmaul Husna Islamic knowledge among university students.

Cluster Analysis for Identifying Obesity Subrouops in Health and Nutritional Status Survey Data

This study presents the discovery of meaningful patterns (groups) from the obese samples of health and nutritional survey data by applying various clustering techniques. Due to the mixed nature of the data (qualitative and quantitative variables) in the data set, the best-suited clustering techniques with appropriate dissimilarity metrics were chosen to interpret the meaningful results. The relationships between obesity and the lifestyle affecting factors like demography, socio-economic status, physical activity, and dietary behavior were assessed using four cluster techniques namely Two-Step clustering, Partition Around Medoids (PAM), Agglomerative Hierarchical clustering and, Kohonen Self Organizing Maps (SOMs). The solutions generated by these techniques were analyzed and validated by the help of cluster validity (CV) indices and later on their associations were determined with the obesity classes to discover the pattern from the obese sample. Two-Step clustering and hierarchical clustering outperformed the other applied techniques in identifying the subgroups based on the underlying hidden patterns in the data. Based on the CV indices values and the association analysis (obesity factor with the cluster solutions), two subgroups were generated and profiles of these groups have been reported. The first group belonged to the middle-aged individuals who seem to take care of their lifestyle while the other group belonged to young-aged individuals who in contrast to the first group presented a careless lifestyle factor (i.e., physical activity and dietary behavior). The salient features of these subgroups have been reported and can be proposed for the betterment in the health care industry. The research helped in identifying the interesting subsets/groups within survey data demonstrating similar characteristics and health status (i.e., prevalence of obesity with respect to lifestyle factors like physical activity, dietary behavior etc.) which will help to suggest appropriate measures/steps to be taken by the concerned departments to counter them and prevent in the population.