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The purpose of this paper is to explore the actual walking distance to public transport (PuT) stations and to report passenger perceptions on route choice.

A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). It can determine the interrelation between the accessibility of the transit service and evaluation on walking distance acceptance. Statistical analysis and geo-spatial approach were completed for obtaining major findings.

Statistical and geo-spatial analysis shows that respondents living in low-density areas walk longer than residents living in nearby inner city areas. In terms of PuT modes, residents walk longer for suburban train and subway/metro (U-Bahn) than for bus/tram services. Transit users accept a longer walking distance to reach a train station than other PuT modes and they choose the most direct and quickest route to reach PuT stations.

Findings of this study would help to formulate future strategies and standards for the sustainable planning of public transportation systems in the context of Munich and many other cities around the globe with similar conditions. However, future research should be conducted using a large-scale survey for evaluating the comprehensive picture of walking patterns to PuT stations. Accessibility to PuT stations can also be modeled and evaluated by adopting open data and voluntary social media information. Unfortunately, this study only presents a partial evaluation of walking focused on accessibility at selected PuT stations in different settings of the urban fabric.

This empirical study can be considered as an initial finding in the favor of the city transport authority to provide a design scale for improved accessibility of transit users; however, further investigation should be conducted using a large-scale survey for evaluating the comprehensive walking patterns.

A systematic case study has been conducted after administrating a tailor-made paper-based intercept survey in a German city (Munich). Findings of this study would help to formulate future strategies and standard for the sustainable planning of the public transportation system in the context of Munich and many other cities in the globe with similar conditions.

Mobile phone-based human activity recognition (HAR) consists of inferring user’s activity type from the analysis of the inertial mobile sensor data. This paper aims to mainly introduce a new classification approach called adaptive k-nearest neighbors (AKNN) for intelligent HAR using smartphone inertial sensors with a potential real-time implementation on smartphone platform.

The proposed method puts forward several modification on AKNN baseline by using kernel discriminant analysis for feature reduction and hybridizing weighted support vector machines and KNN to tackle imbalanced class data set.

Extensive experiments on a five large scale daily activity recognition data set have been performed to demonstrate the effectiveness of the method in terms of error rate, recall, precision, F1-score and computational/memory resources, with several comparison with state-of-the art methods and other hybridization modes. The results showed that the proposed method can achieve more than 50% improvement in error rate metric and up to 5.6% in F1-score. The training phase is also shown to be reduced by a factor of six compared to baseline, which provides solid assets for smartphone implementation.

This work builds a bridge to already growing work in machine learning related to learning with small data set. Besides, the availability of systems that are able to perform on flight activity recognition on smartphone will have a significant impact in the field of pervasive health care, supporting a variety of practical applications such as elderly care, ambient assisted living and remote monitoring.

The purpose of this study is to build and test an accurate offline model by using only a compact training data that can reduce the computational and memory complexity of the system. This provides grounds for developing new innovative hybridization modes in the context of daily activity recognition and smartphone-based implementation. This study demonstrates that the new AKNN is able to classify the data without any training step because it does not use any model for fitting and only uses memory resources to store the corresponding support vectors.

The purpose of this paper is to focus on ethical and judicial themes related to technology and the older adults.

Different consecutive phases in technology design and allocation will be discussed from a range of perspectives.

Longevity is one of the greatest achievements of contemporary science and a result of development of social relations. Currently, various non-communicable diseases affect older adults and impose the greatest burden on global health. There is a great emphasis across Europe on caring for the older person in their own homes. Technology has a mediating role in determining the possibilities for good quality of life (QOL). The concept of assisting the older adult through the use of technology so as to access healthcare services has enormous potential. Although the potential of technology in healthcare is widely recognised, technology use can have its downsides. Professionals need to be aware of the risks, namely, those related to the privacy of the older person, which may accompany technology use.

By 2050, there will be more people aged over 65 than there are children. This phenomenon of global ageing constitutes a massive challenge in the area of health protection.

Professionals need to be aware of the risks, for example, related to the privacy of the older person, that may accompany technology use.

There is a great emphasis across Europe on caring for the older person in their own homes. Technology has a mediating role in determining the possibilities for QOL.

The concept of assisting the older adult through the use of technology to avail of healthcare has enormous potential. Assistive technology, social media use and augmentative and alternative communication can have a positive effect on the QOL of older people, as long as they are supported enough in use of these technologies. However, ethical and juridical considerations are at stake as well.

This study aimed to develop the construct validity for the Malay version of the Paffenbarger physical activity questionnaire (PPAQ) by adapting the original questionnaire to suit the local context.

The PPAQ was adopted and translated into the Malay language and modified to reach good content agreement among a panel of experts. A total of 65 participants aged 22–55 years old, fluent and literate in the Malay language were selected. Principal component analysis (PCA) was used to investigate construct validity. Reliability of this adapted instrument was analyzed according to types of variables.

The panel of experts reached a consensus that the final four items chosen in the adapted Malay version of PPAQ were valid and supported by a good content validity index (CVI). In total, two domains consonant with the operational domain definition were identified by PCA. Based on scores from intensity and duration of exercise, the study further divided the group into who were physically active and those who chose the unstructured physical activity. Relative reliability after a 14-day interval demonstrated moderate strength of agreement with an acceptable range of measurement error.

PPAQ has been used worldwide but was less familiar in the local context. The Malay-four item PPAQ will provide the locally validated version of physical activity questionnaire. In addition, the authors have improved the original PPAQ by dividing the question items into two distinct domains which will effectively identify those who are physically active and those who are involved in unplanned exercise. Nevertheless, further research is recommended in bigger and heterogeneous samples along with a number of reliability tests.

To the authors’ knowledge, this is the first study to assess internal structure of the four-item version of PPAQ. This analysis successfully identified two components with eigenvalue more than one in the Malay four-item PPAQ. Based on this, the authors were able to separate pool of population into two groups, which are physically active and unplanned exercise (involved in unstructured exercise). The ability of the validated questionnaire to divide the population into various intensities of physical activity is a novel one, which may be useful in many public health studies where high intensity of physical activity; hence, greater energy expenditure is associated with increased longevity, better health benefit and improved cognitive function.

In addition, the second domain “unplanned exercise” was successfully grouped together. Implication of the unplanned exercise component is to identify pool of population with active lifestyle awareness and choose the unstructured exercise instead of vigorous and formal exercising. Even though the amount of intensity and duration of incidental exercise does not reach recommended public health recommendation, it has been proven that preferred healthier lifestyle is positively associated with better cognition in later life.

The adapted Malay version of PPAQ has sound psychometric properties and could assist in differentiating groups of population based on their physical activity.

When security managers choose to deploy a smart lock activation system, the number of units needed and their location needs to be established. This study aims to present the results of a penetration test involving smart locks in the context of building security. The authors investigated how the amount of effort an employee has to invest in complying with a security policy (i.e. walk from the office to the smart key activator) influences vulnerability. In particular, the attractiveness of a no-effort alternative (i.e. someone else walking from your office to the key activators to perform a task on your behalf) was evaluated. The contribution of this study relates to showing how experimental psychology can be used to determine the cost-benefit analysis (CBA) of physical building security measures.

Twenty-seven different “offenders” visited the offices of 116 employees. Using a script, each offender introduced a problem, provided a solution and asked the employee to hand over their office key.

A total of 58.6 per cent of the employees handed over their keys to a stranger; no difference was found between female and male employees. The likelihood of handing over the keys for employees close to a key activator was similar to that of those who were further away.

The results suggest that installing additional key activators is not conducive to reducing the building’s security vulnerability associated with the handing over of keys to strangers.

No research seems to have investigated the distribution of smart key activators in the context of a physical penetration test. This research highlights the need to raise awareness of social engineering and of the vulnerabilities introduced via smart locks (and other smart systems).

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.

Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).

Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.

Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.

The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.

By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.

Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.

This review aims to identify the commonly used nature-based therapies, the cohorts that benefit from these interventions, and the potential environmental impact of nature-based therapies.

An integrative review methodology was taken. The literature was analysed and synthesised through thematic analysis.

Three themes emerged from the analysis: categories of nature-based therapies; benefits of nature-based therapies; and the gains from nature-based therapies are not universal. Evidence of physiological, psychological, social, vocational and quality of life benefits from participation in nature-based therapies was evident in the literature. However, there was insufficient empirical evidence of the benefits for the environment.

Occupational therapists assist populations across the life course. Consequentially, they can be found working in a diverse range of clinical contexts. This review asserts that nature-based therapies could be a positive addition in many of these contexts. Further, while engagement in activities in natural environments is frequently used by occupational therapists practicing within institution environments, there is evidence to support its use in community service models and potentially in public health strategies.

This integrative review brings together evidence on a diverse range of nature-based therapies, cohorts, associated benefits and factors that influence these. The lack of empirical evidence on the benefits of nature-based therapies for the environment is acknowledged as a gap in the literature

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

This paper evaluates an alternative queuing concept for marine container terminals that utilize a truck appointment system (TAS). Instead of having all lanes providing service to trucks with appointments, this study considers the case where walk-in lanes are provided to serve those trucks with no appointments or trucks with appointments but arrived late due to traffic congestion.

To enable the analysis of the proposed alternative queuing strategy, the queuing system is shown mathematically to be stationary. Due to the complexity of the model, a discrete event simulation (DES) model is used to obtain the average waiting number of trucks per lane for both types of service lanes: TAS-lanes and walk-in lanes.

The numerical experiment results indicated that the considered queuing strategy is most beneficial when the utilization of the TAS lanes is expected to be much higher than that of the walk-in lanes.

The novelty of this study is that it examines the scenario where trucks with appointments switch to the walk-in lanes upon arrival if the TAS-lane server is occupied and the walk-in lane server is not occupied. This queuing strategy/policy could reduce the average waiting time of trucks at marine container terminals. Approximation equations are provided to assist practitioners calculate the average truck queue length and the average truck queuing time for this type of queuing system.