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This paper describes using a mobile robot, equipped with some sonar sensors and an odometer, to test navigation through the use of a cognitive map. The robot explores an office environment, computes a cognitive map, which is a network of ASRs [36, 35], and attempts to find its way home.
Ten trials were conducted and the robot found its way home each time. From four random positions in two trials, the robot estimated the home position relative to its current position reasonably accurately.
Our robot does not solve the simultaneous localization and mapping problem and the map computed is fuzzy and inaccurate with much of the details missing.
In each homeward journey, it computes a new cognitive map of the same part of the environment, as seen from the perspective of the homeward journey. We show how the robot uses distance information from both maps to find its way home.
When animals (including humans) first explore a new environment, what they remember is fragmentary knowledge about the places visited. Yet, they have to use such fragmentary knowledge to find their way home. Humans naturally use more powerful heuristics while lower animals have shown to developa varietyof methodsthat tend to utilize two key pieces of information,namely distance and orientation information.
Their methods differ depending on how they sense their environment.
Could a mobile robot be used to investigate the nature of such a process, commonly referred to in the psychological literature as cognitive mapping? What might be computed in the initial explorations and how is the resulting “cognitive map” be used to return home?
In this paper, we presented a novel approach using a mobile robot to do cognitive mapping. Our robot computes a “cognitive map” and uses distance and orientation information to find its way home.
The process developed provides interesting insights into the nature of cognitive mapping and encourages us to use a mobile robot to do cognitive mapping in the future, as opposed to its popular use in robot mapping.
We propose a reinforcement learning approach to heating control in home automation, that can acquire a set of rules enabling an agent to heat a room to the desired temperature at a defined time while conserving as much energy as possible. Experimental results are presented that show the feasibility of our method.
The IT architecture for meter reading and utility services is at the core of new business models and has a decisive role as an enabler for resource efficiency measures. The communication architecture used by those services has significant impact on cost, flexibility and speed of new service rollout. This article describes how the dominant system model for meter reading came about, what alternative models exist, and what trade-offs those models have for rollout of new services by different stakeholders. Control of a self learning home automation system by dynamic tariff information (Real-Time-Pricing) is given as an application example.
Background
Joint contractures are frequent conditions in individuals in geriatric care settings and are associated with activity limitations and participation restrictions. As such, relevant intervention programs should address these aspects, and the effectiveness of such programs should be determined by assessing improvement in activities and participation. However, no patient-centred and psychometrically sound outcome measures for this purpose are available so far.
Objectives
The objectives of this study were to develop and to validate a new outcome measure, the PaArticular Scales, to quantify activities and participation in older individuals with joint contractures. Specific aims were (A) to operationalize the content of an International Classification of Functioning, Disability and Health-based standard set towards meaningful questions and to combine them to a questionnaire and (B) to assess the psychometric properties of the developed questionnaire, in detail to evaluate test–retest reliability, objectivity, internal consistency reliability and criterion validity.
Design
Operationalization was reached by an expert consensus conference and a subsequent expert Delphi survey. Psychometric properties were assessed in a cross-sectional study.
Settings
Nursing homes, geriatric rehabilitation facilities.
Participants
23 experts (nurses, physicians, physical and occupational therapists) participated in the consensus conference and the Delphi survey. A total of 191 individuals with joint contractures (as confirmed by physician, nurse or physical therapist) between 65 and 102 years, living in nursing homes or as patients in geriatric rehabilitation were enrolled in the cross-sectional study.
Methods
Rasch Partial Credit Modelling.
Results
The consensus conference and Delphi survey resulted in a questionnaire with 86 items of the International Classification of Functioning, Disability and Health. Test–retest-reliability among those was acceptable (Cohen's weighted kappa: 0.779). The Rasch analysis revealed two independent interval-scaled scales with 24 items for the Activities scale and 11 items for the Participation scale with high internal consistency reliability. Cronbach's alpha was 0.96 for the Activities scale and 0.92 for the Participation scale. Criterion validity was −0.40 and −0.30 for the Activities scale and for the Participation scale, respectively.
Conclusions
The PaArticular Scales, a new patient-centred and psychometric sound outcome measures to comprehensively assess the impact of joint contractures in geriatric care, are available now. These developed scales will serve as primary outcomes in a scheduled evaluation of a complex intervention to improve participation and quality of life in nursing home residents with joint contractures.
Generating a more detailed understanding of domestic electricity demand is a major topic for energy suppliers and householders in times of climate change.
Over the years there have been many studies on consumption feedback systems to inform householders, disaggregation algorithms for Non-Intrusive-Load-Monitoring (NILM), Real-Time-Pricing (RTP) to promote supply aware behavior through monetary incentives and appliance usage prediction algorithms. While these studies are vital steps towards energy awareness, one of the most fundamental challenges has not yet been tackled: Automated detection of start and stop of usage cycles of household appliances. We argue that most research efforts in this area will benefit from a reliable segmentation method to provide accurate usage information.
We propose a SVM-based segmentation method for home appliances such as dishwashers and washing machines. The method is evaluated using manually annotated electricity measurements of five different appliances recorded over two years in multiple households.
Objectives
The objective of this study was to assess the objectivity, cross-cultural validity, and convergent validity of the Vestibular Activities and Participation (VAP) questionnaire among four countries, Germany, United States, Jordan, and Saudi Arabia.
Study Design and Setting
This was a cross-sectional study conducted in four specialized outpatient dizziness clinics in Germany, United States, Jordan, and Saudi Arabia.
Results
A total of 453 participants were included in the study. The Rasch analysis revealed two separate subscales. Subscale 1 items included focusing attention, lying down, standing, bending, lifting and carrying objects, and sports. Subscale 2 items included walking long distances, climbing, running, moving around within buildings other than home, using transportation, and driving. The Pearson product–moment correlation between the Dizziness Handicap Inventory and the summary score of the VAP subscale 1 was 0.66 and was 0.64 for subscale 2.
Conclusion
Owing to its shortness and intercultural adaptability, the new two-scale version of the VAP questionnaire lends itself to clinical practice and research across countries to estimate the effect of vertigo and dizziness on activity limitation and participation restrictions. Psychometrically sound summary scores can be calculated. More extended versions of the VAP can be used for comprehensive clinical assessment where summary scores are not needed or a more detailed documentation is warranted.
The annual instructional virtual team Project X brings together professors and students from across the globe to engage in client projects. The 2020 project was challenged by the global disruption of the COVID-19 pandemic. This paper draws on a quantitative dataset from a post-project survey among 500 participating students and a qualitative narrative inquiry of personal experiences of the faculty members. The findings reveal how innovative use of a variety of collaboration and communication technologies helped students and their professors in building emotional connection and compassion to support each other in the midst of the crisis, and to accomplish the project despite connectivity disruptions. The results suggest that the role of an instructor changed to a coach and mentor, and technology was used to create a greater sense of inclusion and co-presence in student-faculty interactions. Ultimately, the paper highlights the role of technology to help the participants navigate sudden crisis affecting a global online instructional team project. The adaptive instructional teaching strategies and technologies depicted in this study offer transformative potential for future developments in higher education.
When animals (including humans) first explore a new environment, what they remember is fragmentary knowledge about the places visited. Yet, they have to use such fragmentary knowledge to find their way home.
Humans naturally use more powerful heuristics while lower animals have shown to develop a variety of methods that tend to utilize two key pieces of information, namely distance and orientation information.
Their methods differ depending on how they sense their environment. Could a mobile robot be used to investigate the nature of such a process, commonly referred to in the psychological literature as cognitive mapping? What might be computed in the initial explorations and how is the resulting “cognitive map” be used for localization?
In this paper, we present an approach using a mobile robot to generate a “cognitive map”, the main focus being on experiments conducted in large spaces that the robot cannot apprehend at once due to the very limited range of its sensors. The robot computes a “cognitive map” and uses distance and orientation information for localization.
Background
A multitude of different rehabilitation interventions and other specific health care services are offered for individuals with disorders of consciousness in long-term care settings. To investigate the association of those services and patient-relevant outcomes, a specific instrument to document the utilization of those services is needed. The purpose of this study was to develop such a questionnaire administered to caregivers in epidemiological studies or patient registries in Germany.
Methods
The development process of the RECAPDOC questionnaire was carried out in three steps. Step 1 consisted of a systematic literature review and an online-based expert survey to define the general content. Step 2 was an expert interview to evaluate the preliminary content of the questionnaire. Step 3 was a pretest including cognitive interviews with caregivers. After each step, the results were combined into a new version of the questionnaire.
Results
The first version of the questionnaire included items on utilization of medical care, medical aids, nursing and therapeutic care. The results of the expert interview led to the integration of five new items and the modification of six other items. The pretest led to some minor modifications of the questionnaire since it was rated as feasible and acceptable. The final questionnaire consisted of 29 items covering the domains “living situation”, “social insurance status”, “utilisation of home health care”, “domestic services”, “outpatient health care”, “specific diagnostic measures”, “adaptive technologies”, “medical aids” and “utilization of therapies”. Also the experience of family support and multidisciplinary collaboration of health professionals is covered.
Conclusions
The developed questionnaire is a first step to make the situation of patients with disorders of consciousness in the long-term care setting accessible for evaluation in epidemiological studies and in the context of patient registries. However, further reliability and validity studies are needed.