Real-Time Driver’s Monitoring Mobile Application through Head Pose, Drowsiness and Angry Detection

The current driver's monitoring system requires a set-up that includes the usage of a variety of camera equipment behind the steering wheel. It is highly impractical in a real-world environment as the set-up might cause annoyance or inconvenience to the driver. This project proposes a framework of using mobile devices and cloud services to monitor the driver's head pose, detect angry expression and drowsiness, and alerting them with audio feedback. With the help of a phone camera functionality, the driver’s facial expression data can be collected then further analyzed via image processing under the Microsoft Azure platform. A working mobile app is developed, and it can detect the head pose, angry emotion, and drowsy drivers by monitoring their facial expressions. Whenever an angry or drowsy face is detected, pop-up alert messages and audio feedback will be given to the driver. The benefit of this mobile app is it can remind drivers to drive calmly and safely until drivers manage to handle their emotions where anger or drowsy is no longer detected. The performance of the mobile app in classifying anger emotion is achieved at 96.66% while the performance to detect driver’s drowsiness is 82.2%. On average, the head pose detection success rate across the six scenarios presented is 85.67%

Anger Detection in Monitoring Drivers’ Facial Expression using Mobile App

Current facial detection requires experimental set-up which includes usage of variety of camera equipment behind the steering-wheel. This is highly impractical in real-world environment as the set-up might cause annoyance or inconvenience to the driver. Next, steering wheel vibration might induce confusion in drivers. This is because vibrating steering wheel can be caused by faulty brakes, wheel alignment and punctured tires. In order to detect driver’s angry facial expression, image processing algorithm will be applied and implemented in this project. Besides that, an audio feedback feature through mobile application will be implemented as well. With the help of phone camera, driver’s facial expression data can be collected then further analysed via image processing under Microsoft Azure platform. In the end of this project, a working Mobile App should be able to be implemented that can detect angry drivers through monitoring their facial expression. Whenever an angry face is detected, pop-up alert messages and audio feedback will keep reminding drivers to drive calm and safe until drivers manage to handle their emotions where anger is no longer detected

A comparative study of physicochemical and antioxidant properties integrated with chemometrics on enzymatic hydrolysates of selected fruit seeds

Fruit seed is one of the by-products of fruit processing that is currently underexploited. In this study, the crude water extracts of guava, longan, and rockmelon seeds were hydrolyzed using enzymes bromelain and alcalase. Their yields (2.47–57.02), TPC (15.53–127.99 mg GAE/g), TFC (18.03–115.15 mg QE/g), protein (14.04–178.60 mg/g), and peptide (23.55–203.97 mg/g) contents were reported. Among the guava seed samples, bromelain hydrolysate (G2) had the highest FRAP (121.489 mg Fe(II)/g), ABTS (IC50 1.713 mg/mL) and DPPH (IC50 0.158 mg/mL) values. Similarly, bromelain hydrolysate of rockmelon seed (R2) exhibited higher FRAP (41.511 mg Fe(II)/g) and ABTS (IC50 2.605 mg/mL) values than the crude extract. However, longan seed crude extract (L1) exhibited higher antioxidant activity than its hydrolysates. Furthermore, chemometric analysis revealed multifaceted relationship among physicochemical and antioxidant parameters, in which L1, bromelain (L2) and alcalase hydrolysates (L3) of longan seed, guava seed crude extract (G1), and G2 associated positively with TPC, TFC, and reducing antioxidant power. Overall, longan and guava seed extracts (L1, G1) and hydrolysates (L2, L3, G2) can be potentially used as antioxidant ingredients for food product development

Robust Design of Docking Hoop for Recovery of Autonomous Underwater Vehicle with Experimental Results

Control systems prototyping is usually constrained by model complexity, embedded system configurations, and interface testing. The proposed control system prototyping of a remotely-operated vehicle (ROV) with a docking hoop (DH) to recover an autonomous underwater vehicle (AUV) named AUVDH using a combination of software tools allows the prototyping process to be unified. This process provides systematic design from mechanical, hydrodynamics, dynamics modelling, control system design, and simulation to testing in water. As shown in a three-dimensional simulation of an AUVDH model using MATLAB™/Simulink™ during the launch and recovery process, the control simulation of a sliding mode controller is able to control the positions and velocities under the external wave, current, and tether forces. In the water test using the proposed Python-based GUI platform, it shows that the AUVDH is capable to perform station-keeping under the external disturbances

Abstract T P118: Participation in Extended Activities of Daily Living is an Important Determinant of Long-Term Quality of Life in Stroke Patients after an Early Supported Discharge Program

Objective: We previously found stroke patients who underwent home therapy in our Early Supported Discharge (ESD) program had excellent improvement in basic activities of daily living (ADL). Their extended ADL remained impaired after ESD but showed significant improvement after 1 year. We hypothesize that improvement in extended ADL is an important determinant of long-term quality of life (QOL) in this group of stroke patients. Methods: Consecutive stroke patients enrolled in an ESD program in a tertiary hospital in Singapore from August 2007 to July 2012 were recruited. Basic and extended ADL functions were assessed using the Functional Independence Measure (FIM) and Frenchay Activities Index (FAI) respectively, pre- and post-ESD. FAI and SF-36 were administered via telephone interview 1 year after stroke onset. Multiple linear regression analyses with the 8 scales of SF-36 were carried out to determine their associations with variables including age, sex, FIM pre-ESD, FIM change (pre- to post-ESD), premorbid FAI, FAI post-ESD and FAI change (post-ESD to 1 year follow-up). Results: Data from 243 patients (60.9% male, mean age 64.7, SD11.8 years) were available for analysis. They received an average of 7.5 home therapy sessions. FIM improved from 100(17) pre-ESD to 115(15) post-ESD. FAI was 21.7(9.4) premorbid, 11.1(7.6) post-ESD and 17.9(10.3) at 1 year. Multiple regression analyses revealed 8 models which were statistically significant and explained 10-50% of the variance in SF-36 scales. In particular, 50% of the variance in Physical Functioning can be explained by the following factors: female gender (β=-.20, p&lt;.001), FIM pre-ESD (β=.28, p&lt;.001), FIM change (β=.15, p&lt;.01), FAI post-ESD (β=.28, p&lt;.001) and FAI change (β=.40, p&lt;.001). Improvement in FAI scores from post-ESD to 1 year follow-up was positively associated with all 8 scales of SF-36 at 1 year. Conclusion: Compared to improvement in basic ADL after ESD, continued improvement in extended ADL including leisure, work and outdoor activities is a more important determinant of long-term QOL after stroke. Facilitating stroke patients in extended ADL participation and community reintegration after ESD is therefore a potentially important but currently neglected aspect in ESD for stroke patients. </jats:p

Educational environments in Asian medical schools: A cross‐national comparison between Malaysia, Singapore, and China.

Introduction: Perceptions of the educational environment (EE) represent an important source of information on medical students' learning experience. Understanding and addressing these perceptions can help inform initiatives designed to improve the learning experience and educational outcomes, while comparison of student perceptions across medical schools can provide an added perspective. The aim of the study was to compare the EEs of three Asian medical schools: Royal College of Surgeons in Ireland and University College Dublin Malaysia Campus, Yong Loo Lin School of Medicine, Singapore and Xiangya School of Medicine, China.Methods: Medical students in the clinical years (N = 1063) participated in a cross-sectional study using the Dundee Ready Educational Environment Measure (DREEM). Data were analyzed using SPSS version 22.Results: There were significant differences between the three medical schools in the total DREEM scores (F [2, 1059] = 38.29, p Discussion: Total DREEM scores at the three medical schools are similar to those reported from other undergraduate settings. However, significant variations occurred in perceptions of the EE, as students progressed through the clinical years. Greater attention to the learning environment and the curriculum may improve students' educational experience.</p

Novel use of natural language processing for registry development in peritoneal surface malignancies

Background: Traditional methods of research registry development for rare conditions such as peritoneal surface malignancies (PSM) are often hindered by poor patient accrual and need for significant manpower resources. We develop a novel pipeline using natural language processing (NLP) to accelerate this process and demonstrate its real-world application in the identification of PSM patients, as well as characterisation of referral patterns in this cohort. Materials and methods: A training set comprising 100 radiological reports of abdomen and pelvis computed tomography scans was used to develop a rule-based NLP system able to classify reports based on the presence or absence of PSM. The algorithm was applied to a test set of 10,261 reports to identify all patients with PSM for registry creation. The registry was subsequently linked to electronic medical records, and the referral patterns of patients evaluated. Results: The algorithm identified 251 reports as positive for PSM from a total of 10,261 reports, of which 239 were concordant with manual review. Performance was excellent with a specificity of 90%, positive predictive value of 95%, and accuracy of 96%. From these, 228 unique patients were identified for registry inclusion after corroboration with pathological findings. Only 27.6% of patients were found to have been referred to and reviewed by PSM specialist surgeons. For those without a PSM specialist consult, 39.4% were managed by medical oncology, 11.5% by colorectal surgery, 7.3% by gastroenterology, 5.4% by internal medicine, and 29.1% by various other miscellaneous medical and surgical subspecialties. Conclusion: NLP is a useful tool in automated pipelines that can greatly contribute to registry creation, as well as research and quality improvement efforts

Cytokeratin-14 contributes to collective invasion of salivary adenoid cystic carcinoma

Collective invasion of cells plays a fundamental role in tissue growth, wound healing, immune response and cancer metastasis. This paper aimed to investigate cytokeratin-14 (CK14) expression and analyze its association with collective invasion in the invasive front of salivary adenoid cystic carcinoma (SACC) to uncover the role of collective invasion in SACC. Here, in the clinical data of 121 patients with SACC, the positive expression of CK14 was observed in 35/121(28.93%) of the invasive front of SACC. CK14 expression in the invasive front, local regional recurrence and distant metastasis were independent and significant prognostic factors in SACC patients. Then, we found that in an ex vivo 3D culture assay, CK14 siRNA receded the collective invasion, and in 2D monolayer culture, CK14 overexpression induced a collective SACC cell migration. These data indicated that the presence of characterized CK14+ cells in the invasive front of SACC promoted collective cell invasion of SACC and may be a biomarker of SACC with a worse prognosis