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This study aims to compare the level of needs for home-care robots amongst older adults, family caregivers and home-care staff and clarify the factors constituting these needs.

A cross-sectional, anonymous questionnaire survey was administered. It included 52 items related to needs for home-care robots rated on a four-point Likert scale. Means and standard deviations were calculated, and the Kruskal-Wallis test was performed for each item. Factor analysis was conducted on the needs of home-care staff.

Responses from 79 older adults, 54 family caregivers and 427 home-care staff were analysed. For all three groups, the level of agreement was high for the following needs: to inform family and support personnel immediately when older adults fall, about their location in case of natural disasters and about mismanagement of fire by older adults with dementia. For family caregivers and home-care staff, the level of need concerning monitoring was higher than for older adults. Extracted using factor analysis, the six factors representing the essential needs for home-care robots were risk minimisation, daily monitoring of the physical condition, supporting activities of daily living (ADL) and instrumental ADL, pre-empting problems, communication and miscellaneous support.

The results showed that the education of caregivers and the co-design process of robot development should involve home-care staff, older adults and family caregivers, which are important for making decisions about the use of home-care robots for older adults.

The aim of this paper is to develop autonomous mobile home healthcare robots, which are capable of observing patients’ motions, recognizing the patients’ behaviours based on observation data, and providing automatically calling for medical personnel in emergency situations. The robots to be developed will bring about cost‐effective, safe and easier at‐home rehabilitation to most motor‐function impaired patients (MIPs).

The paper has developed following programs/control algorithms: control algorithms for a mobile robot to track and follow human motions, to measure human joint trajectories, and to calculate angles of lower limb joints; and algorithms for recognizing human gait behaviours based on the calculated joints angle data.

A Hidden Markov Model (HMM) based human gait behaviour recognition taking lower limb joint angles and body angle as input was proposed. The proposed HMM based gait behaviour recognition is compared with the Nearest Neighbour (NN) classification methods. Experimental results showed that a human gait behaviour recognition using HMM can be achieved from the lower limb joint trajectory with higher accuracy than compared classification methods.

The research addresses human motion tracking and recognition by a mobile robot. Human gait behaviour recognition is HMM based lower limb joints and body angle data from extracted from kinect sensor at the mobile robot.

It is widely agreed that amputees have to rely on visual input to monitor and control the position of the prosthesis while reaching and grasping because of the lack of proprioceptive feedback. Therefore, visual information has been a prerequisite for prosthetic hand biofeedback studies. This is why, the underlying characteristics of other artificial feedback methods used to this day, such as auditive, electro‐tactile, or vibro‐tactile feedback, has not been clearly explored. The purpose of this paper is to explore whether it is possible to use audio feedback alone to convey more than one independent variable (multichannel) simultaneously, without relying on the vision, to improve the learning of a new perceptions, in this case, to learn and understand the artificial proprioception of a prosthetic hand while reaching.

Experiments are conducted to determine whether the audio signals could be used as a multi‐variable dynamical sensory substitution in reaching movements without relying on the visual input. Two different groups are tested, the first one uses only audio information and the second one uses only visual information to convey computer‐simulated trajectories of two fingers.

The results show that it is possible to use auditive feedback to convey artificial proprioceptive information instead of vision as a guide, thus assist users by internalizing new perceptions.

This way, the strong and weak points of auditive feedback can be observed and can be used to improve future feedback systems or schemes, which can integrate different feedback methods to provide more information to the user.

Many mobile devices today are equipped with diversified sensors that enable the acquisition of rich user context (e.g. GPS location, phone activity) for application utilization. With the growing usage of mobile devices in daily life, the problem of conveniently and promptly searching a piece of content that a user has viewed on his/her device before becomes more and more crucial. This paper aims to propose a context‐based query processing framework called UCQP that supports unstructured queries for content search in a user's access history.

Beyond the keywords related to the content properties, a context query in the framework is specified with freeform phrases that describe high‐level mobile contexts of the user at a previous time when the user viewed the searched content.

Experimental results on a prototype system of the framework illustrate its good accuracy and small response time.

To tolerate the incompleteness and inaccuracy in user query texts caused by fading human memory, the authors develop several semantic query parsers that are tailored for different types of contexts using natural language processing and information retrieval techniques. The authors further propose a similarity model to rank the multiple result contents of a query by comparing context entities specified in the query and historical context values associated with each result.

The rapid proliferation of mobile context aware applications has resulted in an increased research interest towards developing specialized context data management strategies for mobile entities. The purpose of this paper is to aim to develop a new way to model mobile entities and manage their contexts accordingly.

This paper proposes the concept of “Mobile Space” to model mobile entities and presents strategies to manage the various contexts associated therein. To handle availability related issues, two system services are designed: the “Availability Updating Service” which is an identifier based mechanism and is designed to keep track of mobile objects and handle availability related issues, and the “Application Callback Service” which is a publish/subscribe based mechanism to handle application disruptions and interruptions arising due to mobility.

The paper presents a detailed study of the proposed framework and a description of the underlying services and the components therein to validate the framework. Experimental results carried out in WiFi and 3G environments indicate that the proposed techniques can support mobile applications and minimize application disruptions with minimal overhead.

The proposed context management framework is generic in nature and is not designed for a specific class of applications. Any mobile context aware application can leverage on the framework and utilize the provided functionalities to manage application disruptions. Also, the decoupling of mobile application layer and the underlying context data management layer renders context data management layer transparent to the application design.

Vehicles estimation can be used in evaluating traffic conditions and facilitating traffic control, which is an important task in intelligent transportation system. The paper aims to propose a vehicle-counting method based on the analysis of surveillance videos.

The paper proposes a novel two-step method using low-rank representation (LRR) detection and locality-constrained linear coding (LLC) classification to count the number of vehicles in traffic video sequences automatically. The proposed method is based on an offline training to understand an LLC-based classifier with extracted features for vehicle and pedestrian classification, followed by an online counting algorithm to count the number of vehicles detected from the image sequence.

The proposed method allows delivery estimation (counting the number of vehicles at each frame only) and total number estimation of vehicles shown in the scene. The paper compares the proposed method with other similar methods on three public data sets. The experimental results show that the proposed method is competitive and effective in terms of computational speed and evaluation accuracy.

The proposed method does not consider illumination. Hence, the results might be unsatisfactory under low-lighting condition. Therefore, researchers are encouraged to add a term that controls the illumination changes into the energy function of vehicle detection in future work.

The paper bridges the gap between LRR detection and vehicle counting by taking advantage of existing LLC classification algorithm to distinguish different moving objects.

Construction enterprises are achieving the goal of production safety by increasingly focusing on the critical factor of “human” and the impact of individual characteristics on safety performance. Emotional intelligence is categorized into three models: skill-based, trait-based and emotional learning systems. However, the mechanism of action and the internal relationship between emotional intelligence and safety performance must be further studied. This study intends to examine the internal mechanism of emotional intelligence on safety performance in construction projects, which would contribute to the safety management of construction enterprises.

A structural equation model exploring the relationship between emotional intelligence and safety performance is developed, with political skill introduced as an independent dimension, situational awareness presented as a mediator, and management safety commitment introduced as a moderator. Data were collected by a random questionnaire and analyzed by SPSS 24.0 and AMOS 26.0. The structural equation model tested the mediation hypothesis, and the PROCESS macro program tested the moderated mediation hypothesis.

The results showed that construction workers' emotional intelligence directly correlates with safety performance, and situational awareness plays a mediating role in the relationship between emotional intelligence and the safety performance of construction workers. Management safety commitment weakens the positive predictive relationships between emotional intelligence and situational awareness and between emotional intelligence and safety performance.

This research reveals a possible impact of emotional intelligence on safety performance. Adding political skills to the skill-based model of emotional intelligence received a test pass. Political skill measures the sincere and cooperative skills of construction workers. Using people as a critical element plays a role in the benign mechanism of “Emotional Intelligence – Situational Awareness – Safety Performance.” Improving emotional intelligence skills through training, enhancing situational awareness, understanding, anticipation and coordination and activating management environment factors can improve safety performance. Construction enterprises should evaluate and train workers' emotional intelligence to improve workers' situational awareness and safety performance.

In order to find a way to create the artistic conception of modern landscape space, the spatial analysis of Daguanyuan is carried out from the perspective of literature in order to find out the method of creating the artistic conception of modern landscape space. Adopting the method of general to special, from theory to practice, the argument with special significance is analyzed from the most common phenomena, and this argument is applied to the method of practical cases. The results show that Daguanyuan space in literature needs the audience's ability to understand words, the perception of space in film and television needs the audience's strong memory and imaginative thinking, while the perception of Daguanyuan space in garden art needs only basic discrimination ability. After analyzing the effect of Daguanyuan space construction from the literary perspective, it is believed that the writing techniques of starting point - development - climax - ending, wanting to carry forward first and restraining first, and reserving foreshadows in literature can be used for reference in modern landscape design.

The purpose of this paper is to explore how the Chaozhou-speaking communities in northeast Guangdong Province dealt with new barriers of border control during the 1950s, and how they circumvented these institutional obstacles to leave China for Hong Kong and Southeast Asia. The emigration process was reshaped by new social and political forces in Maoist China. How did the Chaoshan people apply for the travel permit to leave China? How did they enter the hosting countries? How did the emigration experience influence the identity formation of Chaoshan Chinese in the 1950s?

This paper draws on archival sources, memoirs and interviews to demonstrate the ways in which Chaoshan people pursued new strategies of emigration during the 1950s.

In Maoist China, the application for an entry-exit permit was a rather complicated bureaucratic process for ordinary people. One needs to consider the class status, geographical origins and overseas connections of the applicants as well as the changing official policies toward overseas Chinese.

This paper emphasizes on the impacts of emigration experience on the identity formation of Chaoshan people and the incremental transformation of these emigrant communities in Guangdong Province.

This scholarly finding throws light on the transformation of Chaoshan from a fluid, mobile maritime environment to an increasingly state-centric agrarian society during the 1950s.

This paper is an original scholarly study of the history of Chaoshan communities in South China and their emigration to Southeast Asia.