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A smart sound fingerprinting system for monitoring elderly people living alone
Get PDFThere is a sharp increase in the number of old people living alone throughout the world. More often than not, such people require continuous and immediate care and attention in their everyday lives, hence the need for round the clock monitoring, albeit in a respectful, dignified and non-intrusive way. For example, continuous care is required when they become frail and less active, and immediate attention is required when they fall or remain in the same position for a long time. To this extent, various monitoring technologies have been developed, yet there are major improvements still to be realised.
Current technologies include indoor positioning systems (IPSs) and health monitoring systems. The former relies on defined configurations of various sensors to capture a person's position within a given space in real-time. The functionality of the sensors varies depending on receiving appropriate data using WiFi, radio frequency identification (RFIO), ultrawide band (UWB), dead reckoning (OR), infrared indoor (IR), Bluetooth (BLE), acoustic signal, visible light detection, and sound signal monitoring. The systems use various algorithms to capture proximity, location detection, time of arrival, time difference of arrival angle, and received signal strength data. Health monitoring technologies capture important health data using accelerometers and gyroscope sensors. In some studies, audio fingerprinting has been used to detect indoor environment sound variation and have largely been based on recognising TV sound and songs. This has been achieved using various staging methods, including pre-processing, framing, windowing, time/frequency domain feature extraction, and post-processing. Time/frequency domain feature extraction tools used include Fourier Transforms (FTs}, Modified Discrete Cosine Transform (MDCT}, Principal Component Analysis (PCA), Mel-Frequency Cepstrum Coefficients (MFCCs), Constant Q Transform (CQT}, Local Energy centroid (LEC), and Wavelet transform. Artificial intelligence (Al) and probabilistic algorithms have also been used in IPSs to classify and predict different activities, with interesting applications in healthcare monitoring. Several tools have been applied in IPSs and audio fingerprinting. They include Radial Basis Kernel (RBF), Support Vector Machine (SVM), Decision Trees (DTs), Hidden Markov Models (HMMs), Na'ive Bayes (NB), Gaussian Mixture Modelling (GMM), Clustering algorithms, Artificial Neural Networks (ANNs), and Deep Learning (DL). Despite all these attempts, there is still a major gap for a completely non-intrusive system capable of monitoring what an elderly person living alone is doing, where and for how long, and providing a quick traffic-like risk score prompting, therefore immediate action or otherwise.
In this thesis, a cost-effective and completely non-intrusive indoor positioning and activity-monitoring system for elderly people living alone has been developed, tested and validated in a typical residential living space. The proposed system works based on five phases:
(1)Set-up phase that defines the typical activities of daily living (TADLs).
(2)Configuration phase that optimises the implementation of the required sensors in exemplar flat No.1.
(3)Learning phase whereby sounds and position data of the TADLs are collected and stored in a fingerprint reference data set.
(4)Listening phase whereby real-time data is collected and compared against the reference data set to provide information as to what a person is doing, when, and for how long.
(5)Alert phase whereby a health frailty score varying between O unwell to 10 healthy is generated in real-time. Two typical but different residential flats (referred to here are Flats No.1 and 2) are used in the study.
The system is implemented in the bathroom, living room, and bedroom of flat No.1, which includes various floor types (carpet, tiles, laminate) to distinguish between various sounds generated upon walking on such floors. The data captured during the Learning Phase yields the reference data set and includes position and sound fingerprints. The latter is generated from tests of recording a specific TADL, thus providing time and frequency-based extracted features, frequency peak magnitude (FPM), Zero Crossing Rate (ZCR), and Root Mean Square Error (RMSE). The former is generated from distance measurement. The sampling rate of the recorded sound is 44.1kHz. Fast Fourier Transform (FFT) is applied on 0.1 seconds intervals of the recorded sound with minimisation of the spectral leakage using the Hamming window. The frequency peaks are detected from the spectrogram matrices to get the most appropriate FPM between the reference and sample data. The position detection of the monitored person is based on the distance between that captured from the learning and listening phases of the system in real-time.
A typical furnished one-bedroom flat (flat No.2) is used to validate the system. The topologies and floorings of flats No.1 and No.2 are different. The validation is applied based on "happy" and "unusual" but typical behaviours. Happy ones include typical TADLs of a healthy elderly person living alone with a risk metric higher than 8. Unusual one's mimic acute or chronic activities (or lack thereof), for example, falling and remaining on the floor, or staying in bed for long periods, i.e., scenarios when an elderly person may be in a compromised situation which is detected by a sudden drop of the risk metric (lower than 4) in real-time.
Machine learning classification algorithms are used to identify the location, activity, and time interval in real-time, with a promising early performance of 94% in detecting the right activity and the right room at the right time
Digital Education Resource Mining for Decision Support
Get PDFNowadays education becomes a competitive and challenging domain, both nationally and internationally in terms of quality, visibility, experience of academic delivery affecting institutions, applicants, regulatory bodies. Currently data becomes more available for the general and public use, and plays also an increasingly significant role in decision support for education topics. For example, world university rankings (WUR) such as Quacquarelli Symonds (QS), Central World University Rankings (CWUR), Times Higher Education (Times) and national university rankings (e.g. the Guardian newspaper Best UK Universities and the Complete University Guide league tables) have published their data for many years now and are increasingly used in such decision making processes by institutions and general public
Ethical Human Resource Management and Employee Welfare: Empirical Perspectives from the Bangladeshi RMG Sector
Get PDFThis study explores employee welfare and working conditions in relation to ethical HRM practices from the employees’ perspective in the Bangladeshi Ready-Made Garment (RMG) sector. This research is inspired by the need to understand the challenges that employees face in their practical work settings and the unfair Human Resource Management (HRM) process that they experience in their work.
The interpretivist philosophical approach and the qualitative research approach have been adopted in this research study, while the semi-structured interview method has been applied for primary-data collection. A total of 25 semi-structured interviews with General Employees, Informal Representative Leaders, Employees, Middle and Senior Managers have been undertaken in this process. Five focus-group discussions have also been applied to corroborate the data generated from the 25 semi-structured interviews. The case-study strategy has also been implemented as a research strategy and thematic analysis has been applied to the data-analysis process.
The findings of this research study show the need for deeper understanding and application of ethical HRM practices in particular national and sectoral contexts, specifically in the Bangladeshi RMG sector. These ethical HRM practices include, but are not limited to, the initiation of rights-based understanding and respect-based perception, the inclusion of welfare facilities, the implementation of a fair payment policy, the equitable recruitment and selection policy, and the initiation and equality of training and development facilities. These new ethical understandings contribute to the field of ethical HRM in the context of the development of employee welfare and decent working conditions in this sector
Exploring the drivers of customers’ brand attitudes of online travel agency services: A text-mining based approach
Get PDFYesThis paper aims to explore the important qualitative aspects of online user-generated-content that reflects customers’ brand-attitudes. Additionally, the qualitative aspects can help service-providers understand customers’ brand-attitudes by focusing on the important aspects rather than reading the entire review, which will save both their time and effort. We have utilised a total of 10,000 reviews from TripAdvisor (an online-travel-agency provider). This study has analysed the data using statistical-technique (logistic regression), predictive-model (artificial-neural-networks) and structural-modelling technique to understand the most important aspects (i.e. sentiment, emotion or parts-of-speech) that can help to predict customers’ brand-attitudes. Results show that sentiment is the most important aspect in predicting brand-attitudes. While total sentiment content and content polarity have significant positive association, negative high-arousal emotions and low-arousal emotions have significant negative association with customers’ brand attitudes. However, parts-of-speech aspects have no significant impact on brand attitude. The paper concludes with implications, limitations and future research directions
Championing mental health at work: emerging practice from innovative projects in the UK
Get PDFYesThis paper examines the value of participatory approaches within interventions aimed at promoting mental health and wellbeing in the workplace. Specifically the paper explores data from the thematic evaluation of the Mental Health and Employment project strand within the Altogether Better programme being implemented in England in the Yorkshire and Humber region, which was funded through the BIG Lottery and aimed to empower people across the region to lead better lives. The evaluation combined a systematic evidence review with semi-structured interviews across mental health and employment projects. Drawing on both evaluation elements, the paper examines the potential of workplace-based 'business champions' to facilitate organizational culture change within enterprises within a deprived regional socio-economic environment. First, the paper identifies key policy drivers for interventions around mental health and employment, summarizes evidence review findings and describes the range of activities within three projects. The role of the 'business champion' emerged as crucial to these interventions and therefore, secondly, the paper examines how champions' potential to make a difference depends on the work settings and their existing roles, skills and motivation. In particular, champions can proactively coordinate project strands, embed the project, encourage participation, raise awareness, encourage changes to work procedures and strengthen networks and partnerships. The paper explores how these processes can facilitate changes in organizational culture. Challenges of implementation are identified, including achieving leverage with senior management, handover of ownership to fellow employees, assessing impact and sustainability. Finally, implications for policy and practice are discussed, and conclusions drawn concerning the roles of champions within different workplace environments.This work was supported as part of the evaluation of the Altogether Better programme, which is funded through the UK BIG Lottery fund and aims to empower people across the Yorkshire and Humber region of the UK to lead healthier lives
Independent oversight of the auditing profession: A review of the literature
Get PDFYesThis paper reviews the literature on the independent oversight of auditing from 2003 to 2018 and
provides several research opportunities for filling the identified gaps in that literature. Our review
classifies the literature into three themes: (1) the development of independent audit oversight; (2)
the effects of independent audit oversight; and (3) the interface between the independent audit
oversight authorities and the global audit networks. The paper finds different effects of the
independent audit oversight. Positively, it enhances the capital markets by adding more credibility
to the published information. Auditors become more conservative about accepting or continuing
to work with high-risk clients. At the same time, while audit fees have increased as a result of the
additional requirements of independent audit regulation, non-audit fees from audit clients have
decreased significantly. Negatively, independent oversight has increased audit concentration and
resulted in insufficient choice of auditors in most audit markets
An improved distortion compensation approach for additive manufacturing using optically scanned data
Get PDFYesThis paper presents an improved mathematical model for calculation of distortion vectors of two aligned surface meshes. The model shows better accuracy when benchmarked to an existing model with exceptional mathematical conditions, such as sharp corners and small radii. The model was implemented into a developed distortion compensation digital tool and applied to an industrial component. The component was made of Inconel 718 and produced by laser powder bed fusion 3D printing technology. The digital tool was utilised to compensate the original design geometry by pre-distortion of its original geometry using the developed mathematical model. The distortion of an industrial component was reduced from approximately ±400 µm to ±100 µm for a challenging thin structure subjected to buckling during the build process
Impact assessment of social media usage in B2B marketing: A review of the literature and a way forward
Get PDFYesAlthough various critical elements, such as media publicity, word of mouth, legislation, and environmental factors, are not under the control of a company, they play a significant role in influencing its brand image. Uncertainty over how different social networking sites can support brands is one of the crucial reasons for the delayed acceptance of social media (SM) in business-to-business (B2B) transactions. SM possesses immense potential in relation to gathering customer data and assisting B2B marketers. Therefore, this study reviewed SM usage in the B2B context, based on 294 selected articles. The methodology included bibliometric analysis to identify the impact of SM usage in the B2B domain and content analysis to perform a thematic assessment. Our analysis found that many B2B firms cannot leverage SM’s potential to its fullest compared to business-to-customer (B2C) firms. However, SM can help B2B marketers build their brand presence and trust globally, ultimately helping them find potential customers and build relationships with global supply chain providers
Polymers and boron neutron capture therapy(BNCT): a potent combination
Get PDFYesBoron neutron capture therapy (BNCT) has a long history of unfulfilled promises for the treatment of aggressive cancers. In the last two decades, chemists, physicists, and clinical scientists have been coordinating their efforts to overcome practical and scientific challenges needed to unlock its full therapeutic potential. From a chemistry point of view, the two current small-molecule drugs used in the clinic were developed in the 1950s, however, they both lack some of the essential requirements for making BNCT a successful therapeutic modality. Novel strategies are currently used to design new drugs, more selective towards cancer cells and tumours, as well as able to deliver high boron contents to the target. In this context, macromolecules, including polymers, are promising tools to make BNCT an effective, accepted, and front-line therapy against cancer. In this review, we will provide a brief overview of BNCT, and its potential and challenges, and we will discuss the most promising strategies that have been developed so far
A Review of Modelling of the FCC Unit—Part II: The Regenerator
Get PDFYesHeavy petroleum industries, including the Fluid Catalytic Cracking (FCC) unit, are among some of the biggest contributors to global greenhouse gas (GHG) emissions. The FCC unit's regenerator is where these emissions originate mostly, meaning the operation of FCC regenerators has come under scrutiny in recent years due to the global mitigation efforts against climate change, affecting both current operations and the future of the FCC unit. As a result, it is more important than ever to develop models that are accurate and reliable at predicting emissions of various greenhouse gases to keep up with new reporting guidelines that will help optimise the unit for increased coke conversion and lower operating costs. Part 1 of this paper was dedicated to reviewing the riser section of the FCC unit. Part 2 reviews traditional modelling methodologies used in modelling and simulating the FCC regenerator. Hydrodynamics and kinetics of the regenerator are discussed in terms of experimental data and modelling. Modelling of constitutive parts that are important to the FCC unit, such as gas-solid cyclones and catalyst transport lines, are also considered. This review then identifies areas where the current generation of models of the regenerator can be improved for the future. Parts 1 and 2 are such that a comprehensive review of the literature on modelling the FCC unit is presented, showing the guidance and framework followed in building models for the unit