Activities of daily life recognition using process representation modelling to support intention analysis

Purpose – This paper aims to focus on applying a range of traditional classification- and semantic reasoning-based techniques to recognise activities of daily life (ADLs). ADL recognition plays an important role in tracking functional decline among elderly people who suffer from Alzheimer’s disease. Accurate recognition enables smart environments to support and assist the elderly to lead an independent life for as long as possible. However, the ability to represent the complex structure of an ADL in a flexible manner remains a challenge. Design/methodology/approach – This paper presents an ADL recognition approach, which uses a hierarchical structure for the representation and modelling of the activities, its associated tasks and their relationships. This study describes an approach in constructing ADLs based on a task-specific and intention-oriented plan representation language called Asbru. The proposed method is particularly flexible and adaptable for caregivers to be able to model daily schedules for Alzheimer’s patients. Findings – A proof of concept prototype evaluation has been conducted for the validation of the proposed ADL recognition engine, which has comparable recognition results with existing ADL recognition approaches. Originality/value – The work presented in this paper is novel, as the developed ADL recognition approach takes into account all relationships and dependencies within the modelled ADLs. This is very useful when conducting activity recognition with very limited features

Automatic Detection and Prediction of the Transition Between the Behavioural States of a Subject Through a Wearable CPS

The PRESLEEP project is aimed at the fine assessment and validation of the proposed proprietary methodology/technology, for the automatic detection and prediction of the transition between the behavioural states of a subject (e.g. wakefulness, drowsiness and sleeping) through a wearable Cyber Physical System (CPS). The Intellectual Property (IP) is based on a combined multi-factor and multi-domain analysis thus being able to extract a robust set of parameters despite of the, generally, low quality of the physiological signals measured through a wearable system applied to the wrist of the subject. An application experiment has been carried out at AVL, based on reduced wakefulness maintenance test procedure, to validate the algorithm’s detection and prediction capability once the subject is driving in the dynamic vehicle simulator

Exploring the Impact of Preprocessing Techniques on Retinal Blood Vessel Segmentation Using a Study Group Learning Scheme

The segmentation of retinal vessels in retinal images is vital for automated diagnosis of retinal diseases. This is a challenging task because it requires accurate manual labeling of the vessels by expert clinicians and the detection of tiny vessels is difficult due to limited samples, low contrast, and noise. In this study, we explore the use of preprocessing techniques such as contrast-limited adaptive histogram equalization (CLAHE), grad-cam analysis and min-max contrast stretching to improve the performance of a study-group learning (SGL) segmentation model. We evaluate the impact of these preprocessing techniques on the accuracy, sensitivity, specificity, AUC, IoU, and Dice scores using four publicly available datasets, DRIVE, CHASE, HRF and IOSTAR. Our findings indicate that the utilization of the Min-Max technique resulted in a notable enhancement in the accuracy of both the DRIVE and CHASE datasets, with an approximate increase of 3% and 2% respectively. Conversely, the impact of the CLAHE method was discernible solely in the DRIVE dataset, demonstrating an improvement in accuracy of 1%. In addition, our results demonstrated superior accuracy performance for both the DRIVE and CHASE datasets compared to the findings of the reviewed studies. The GitHub repo for this project is available at Link

Synthesis, Characterization and Photodegradation Studies of Copper Oxide–Graphene Nanocomposites

In this work, a simple hydrothermal method was employed to prepare a pristine sample of copper oxide (CuO) and three samples of copper oxide–graphene nanocomposites (CuO-xG) with x = 2.5, 5, and 10 mg of graphene. The synthesized samples were characterized using X-ray powder diffractometry (XRD), field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR) and ultraviolet–visible (UV-Vis) spectroscopy. The XRD patterns of CuO-xG nanocomposites exhibited the diffraction peaks related to the crystal planes of monoclinic CuO and hexagonal graphite. The surface morphology of the prepared samples was investigated using FESEM images. EDX analysis was used to investigate the chemical composition of the synthesized samples. FTIR spectroscopy identified the vibrational modes of the covalent bonds present in the samples. The allowed direct optical bandgap energy was calculated for all prepared samples using UV-Vis absorption spectra. The small bandgap of CuO-xG nanocomposites indicates their potential use as an effective photocatalyst in the presence of visible light. Photocatalytic activity of the samples was explored for the degradation of methylene blue (MB) dye contaminant under visible light irradiation. The results showed that the CuO-5G sample has the highest photodegradation efficiency (~56%)

An Analysis on Organizational Behaviours Model of Intel (M) Corporation

Models are frameworks or possible explanations why do people behave as they do at work.1 There are so many models in an organization. Different results across the organizations are caused by different in the models of organizational behaviour. The basic model of this paper is to know more about how organizational behaviour influences the Intel (M) Corporation based on the organizational behaviour model. Furthermore, this paper aims to have insights about the employees in Intel (M) Corporation which will be influenced by surroundings no matter from physically or psychologically including how company facilities and services influences the organizational behaviour in Intel (M) Corporation or the influence of motivation among employee and company performances. This paper contains a phone interview with one of the managers in Intel (M) Corporation, an American multinational technology company with its Malaysia main headquarter located in Penang to get more about the internal issues regarding organizational behaviour in the company such as overcoming of stress, design of a decision and also company culture and structure. Intel (M) Corporation has turned to be a splendid company in its working environment with both internal and external supports received from employees and the community. We will learn about the influences of Organizational Behaviours towards a company community based on Organizational Behaviour models

Exogenous melatonin enhances salt stress tolerance in tomato seedlings

Melatonin (N-acetyl-5-methoxytryptamine) is an essential molecule which regulates plant growth and development and alleviates the damaging effects of abiotic stresses. To evaluate the important functions of melatonin in response to salinity stress, the effects of exogenous melatonin on the antioxidant system and growth of tomato (Solanum lycopersicum L.) under 150 mM NaCl stress were investigated. The application of 100 μM melatonin compensated the growth inhibition caused by salt-stress. Melatonin treated seedlings had an increased fresh and dry masses of shoots and roots. The application of 1 - 200 µM melatonin notably enhanced the relative chlorophyll content (SPAD index), root characteristics, and gas exchange in tomato seedlings subjected to salt stress compared to seedlings treated with salt stress alone. Moreover, melatonin pretreatment minimized accumulation of reactive oxygen species and improved activities of antioxidative enzymes including catalase, superoxide dismutase, glutathione reductase, and ascorbate peroxidase.We would like to thank Wang Zhiwei from the College of Horticulture and Landscape Architecture, Hainan University, Haikou for his kind guidance and laboratory equipment. This program was financially supported by the Innovative Team Program of Hainan Natural Science Foundation (2018CXTD334) and the National Natural Science Foundation of China (41871041)

Eimeria species occurrence varies between geographic regions and poultry production systems and may influence parasite genetic diversity

Coccidiosis is one of the biggest challenges faced by the global poultry industry. Recent studies have highlighted the ubiquitous distribution of all Eimeria species which can cause this disease in chickens, but intriguingly revealed a regional divide in genetic diversity and population structure for at least one species, Eimeria tenella. The drivers associated with such distinct geographic variation are unclear, but may impact on the occurrence and extent of resistance to anticoccidial drugs and future subunit vaccines. India is one of the largest poultry producers in the world and includes a transition between E. tenella populations defined by high and low genetic diversity. The aim of this study was to identify risk factors associated with the prevalence of Eimeria species defined by high and low pathogenicity in northern and southern states of India, and seek to understand factors which vary between the regions as possible drivers for differential genetic variation. Faecal samples and data relating to farm characteristics and management were collected from 107 farms from northern India and 133 farms from southern India. Faecal samples were analysed using microscopy and PCR to identify Eimeria occurrence. Multiple correspondence analysis was applied to transform correlated putative risk factors into a smaller number of synthetic uncorrelated factors. Hierarchical cluster analysis was used to identify poultry farm typologies, revealing three distinct clusters in the studied regions. The association between clusters and presence of Eimeria species was assessed by logistic regression. The study found that large-scale broiler farms in the north were at greatest risk of harbouring any Eimeria species and a larger proportion of such farms were positive for E. necatrix, the most pathogenic species. Comparison revealed a more even distribution for E. tenella across production systems in south India, but with a lower overall occurrence. Such a polarised region- and system-specific distribution may contribute to the different levels of genetic diversity observed previously in India and may influence parasite population structure across much of Asia and Africa. The findings of the study can be used to prioritise target farms to launch and optimise appropriate anticoccidial strategies for long-term control