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This paper seeks to identify, clarify, and perhaps rehabilitate the virtual reality metaphor as applied to the goal of understanding consciousness. Some proponents of the metaphor apply it in a way that implies a representational view of experience of a particular, extreme form that is indirect, internal and inactive (what we call "presentational virtualism"). In opposition to this is an application of the metaphor that eschews representation, instead preferring to view experience as direct, external and enactive ("enactive virtualism"). This paper seeks to examine some of the strengths and weaknesses of these virtuality-based positions in order to assist the development of a related, but independent view of experience: virtualist representationalism. Like presentational virtualism, this third view is representational, but like enactive virtualism, it places action centre stage, and does not require, in accounting for the richness of visual experience, global representational "snapshots" corresponding to the entire visual field to be tokened at any one time.

A critique of some central themes in Pentti Haikonen's recent book, Consciousness and Robot Sentience, is offered. Haikonen maintains that the crucial question concerning consciousness is how the inner workings of the brain or an artificial system can appear, not as inner workings, but as subjective experience. It is argued here that Haikonen's own account fails to answer this question, and that the question is not in fact the right one to ask anyway. It is argued that making the required changes to the question reveals an important lacuna in Haikonen's explanation of consciousness.

Aim: This study evaluates perception toward facial appearance in dentofacial deformity and the need for orthognathic surgery among the public with and without dental backgrounds.

Materials and Methods: A questionnaire consisting of 12 facial photographs of cases with dentofacial deformity or malocclusion in varying severity was used. A hundred individuals were selected to answer the questionnaire. The perception of facial appearance (FAS), treatment need score (TNS), and knowledge regarding dentofacial deformity were used for the evaluation.

Results: Significant differences were found between dental and non-dental when the respondents’ knowledge in all the questionnaire items ($p<0$.05) was assessed. However, no significant difference was found in the mean of FAS and TNS in all the presented cases (normal, borderline, severe). Pearson correlation between perceived FAS and TNS was statistically negative for severe and normal cases, whereby a decrease in FAS for severe cases showed an increase in TNS, and an increase in FAS for normal cases showed a decrease in TNS.

Conclusion: Respondents with dental background had sound knowledge of dentofacial deformity. A poorly attractive respondent with dentofacial deformity showed a greater need for orthognathic surgery.

Path planning plays an integral role in mission planning for ground vehicle operations in urban areas. Determining the optimum path through an urban area is a well-understood problem for traditional ground vehicles; however, in the case of autonomous unmanned ground vehicles (UGVs), additional factors must be considered. For an autonomous UGV, perception algorithms rather than platform mobility will be the limiting factor in operational capabilities. For this study, perception was incorporated into the path planning process by associating sensor error costs with traveling through nodes within an urban road network. Three common perception sensors were used for this study: GPS, LIDAR, and IMU. Multiple set aggregation operators were used to blend the sensor error costs into a single cost, and the effects of choice of aggregation operator on the chosen path were observed. To provide a robust path planning ability, a fuzzy route planning algorithm was developed using membership functions and fuzzy rules to allow for qualitative route planning in the case of generalized UGV performance. The fuzzy membership functions were then applied to several paths through the urban area to determine what sensors were optimized in each path to provide a measure of the UGV’s performance capabilities. The research presented in this paper shows the impacts that sensing/perception has on ground vehicle route planning by demonstrating a fuzzy route planning algorithm constructed by using a robust rule set that quantifies these impacts.

We propose semantic grid, a spatial 2D map of the environment around an autonomous vehicle consisting of cells which represent the semantic information of the corresponding region such as car, road, vegetation, bikes, etc. It consists of an integration of an occupancy grid, which computes the grid states with a Bayesian filter approach, and semantic segmentation information from monocular RGB images, which is obtained with a deep neural network. The network fuses the information and can be trained in an end-to-end manner. The output of the neural network is refined with a conditional random field. The proposed method is tested in various datasets (KITTI dataset, Inria-Chroma dataset and SYNTHIA) and different deep neural network architectures are compared.

Many studies have compared the Russian and Chinese projects currently underway in the Central Asian region, namely the Eurasian Economic Union (EAEU) and the Silk Road Economic Belt (SREB), both of which seek to increase integration with Central Asian states. Yet little attention has been paid to how these endeavors are perceived locally by Central Asians themselves. This article aims to fill this gap by presenting the findings of a comparative discourse analysis of perceptions of Russia and China in online Russian-language media in Kyrgyzstan. The research reveals that while Russia’s role in the region has been seen primarily in political terms and China’s role chiefly in economic terms, these perceptions are changing, and that a growing percentage of articles are devoted to economics in the case of Russia and politics in the case of China. Another finding from this research is that China receives a greater percentage of positive coverage than Russia. It is suggested that as two important poles in the emerging multi-polar world, China and Russia should ensure their respective projects complement, rather than conflict, with one another in the region.

Cryptocurrency is a digital currency designed for use in transactions just like regular money. To safeguard its exchanges, restrict the development of a specific kind of cryptocurrency, and keep track of each and every transaction across the entire network, it uses blockchain and cryptography. Even after a decade of existence, cryptocurrency has not established a reputation as a new age currency system among the majority of countries in the world, and people are still dubious about its value despite being loaded with numerous cutting-edge technologies and having a sizable market presence everywhere. Cryptocurrencies have been around for almost 10 years, but it is still unclear whether they will ever become a real currency or if they will stay a component of investment portfolios. Since Odisha is a backward state, a study has been done to determine the level of awareness and perception of cryptocurrencies in its cities.

Electric vehicle (EV) market in Thailand is still limited due to lack of government support, lack of charging infrastructure, lack of EV knowledge and skills, high vehicle prices, and limited battery capacities. This research examines and ranks factors influencing EV manufacturing and purchasing in Thailand utilizing the analytic hierarchy process (AHP) method. Six factors with 14 sub-factors form the manufacturers’ hierarchy model. Four factors with 25 sub-factors are, on the other hand, in the consumers’ hierarchy model. The data used in the analysis are gathered through interviews of EV experts and consumers. The results demonstrate that the Government Support factor is the most significant factor perceived by manufacturers, especially in terms of taxes and subsidies. Battery cost is also found an important concern in EV production. On the other hand, Individual Judgment and EV Performance factors are the two most significant factors from consumers’ perspectives. The focus should be on the vehicle price and battery issues, with specific consideration to driving range and charging time. Consumers also request the government to provide adequate charging stations to facilitate the use of EVs. The government may promote the EV market through a number of subsidies and tax reduction campaigns. Engineering and production managers may, on the other hand, focus on technical issues of battery performance to increase driving ranges and decrease charging time to attract more EV consumers.

Healthcare improvement relating to basic hospital service attributes is one of the most fundamental driving forces to uplifting in economic and social transition for developing countries in an emerging context. The purpose of this paper is to measure patients’ trio need satisfaction toward doctor service quality (DSQ), nurse caring quality (NCQ), and hospital environment quality (HEQ) and compare the effects of perceived, expected, and service quality gap on patient satisfaction. Multiple regression analysis was used to explain the patient satisfaction. The result shows that the perceived service quality (67.3%) and the service quality gap (50.8%) can better explain patient satisfaction than the expected service quality (3.0%). Both perception and gap model show that DSQ, NCQ, and HEQ are significant predictors of patient satisfaction, where NCQ is the most important dimension in explaining patient satisfaction. This study focuses on patient need satisfaction research by being one of the few empirical studies relating to the most basic hospital service quality attributes, contributing to the development of hospital service quality in a developing context of Bangladesh.

Using an online survey with about 650 persons living in urban areas in Vietnam and working in different job positions, this chapter aimed to explore how they perceived various measures in containing COVID-19 and how they complied with and evaluated different government policies in controlling the pandemic. In particular, we disaggregated data of the urban workers into gender (male vs. female), job positions (wage-earners vs. other), social insurance participation (mandatory, voluntary, and non-participating), and self-rated health (good vs. bad). We found that the respondents highly appreciated the government with the provided information of COVID-19 and the implemented policies to contain the pandemic. People showed quite good compliance with the national social distancing policies since they went out of their homes mostly for essential work, while very rarely for other reasons or non essential work. We could see various differences in perceptions and compliance levels of the respondents in terms of age, gender, residential area, and health status. Based on those findings along with the existing studies, we recommended that appropriate measures stabilising social and economic activities within the country should be continuously implemented so as to maintain or alternate jobs for people working in severely affected economic sectors. Also, providing accessible and affordable healthcare measures to all people, especially for poor and informal workers who are particularly risky to infectious diseases, should also be given great consideration. Sufficient goods and services for people to meet their basic needs during social distancing should be continuously maintained.

After limb amputation a perception that the amputated limb is still there will always occur. It follows a specific pattern that is related with body image (Neuromatrix and Neurosignature theory by Melzack) called phantom limb sensation. Phantom limb pain is a different condition. It is highly variable, very individual and have a correlation with the experience of pain in the same limb before amputation. Phantom limb phenomenon is a continuing memory with or without pain of self-body perception or body image that is not there any more, modulated by neurohormones and neurotransmitters to reach homeostasis balance. The reactivation of pre-amputation pain memory (engram) is stronger in a diabetic limb amputee compared with a traumatic limb amputee because of longer pre-amputation pain experience. The prevention strategy of phantom pain in diabetics is very important. All steps must be taken to prevent this from happening, through good and careful management in the pre-amputation stage.

This paper describe CAILS, an experimental Computer Assisted Iconic Language System which deals with three specific areas in communication: Cross-linguistic, visual/spatial concept representation and visual educational technique. Designed for interpersonal communication, this system functions with generally comprehensible visual referents. Each area has some specific syntax which is clear and easy to learn. CAILS takes advantage of visual memory of the user. The basic idea of this system is that an individual can, using basic visual references, compose a message, represent a concept and teach a rule. The specificity of the images eliminates ambiguity. For convenience, we classified visual references or «words» in the following categories: Hands, Movements, Expression, and Pictures.

When properly use, CAILS produce « iconic message objects» which may be presented to the intended recipient

This paper presents several results regarding the lateral and longitudinal control systems that have been applied for the automation of an articulated bus, using a rolling wheeled box system with special design that moves inside a guide rail. Nowadays, transport systems are achieving major advances by the incorporation of automation based technologies. Recent developments of electronic instrumentation and actuation systems and the increasing speed of processors allows for the implementation of real-time systems. The automation of an articulated bus provides combined advantages of both conventional bus and train, because it can ascend slopes of 15% and turn on curves of low radius. This transport modality is an interesting, low cost and friendly option. In this paper an experimental setup for the development of lateral and longitudinal control of the articulated bus is presented. Comprised by an experimental mobile platform (articulated bus) fully instrumented and a ground test area of asphalt roads inside CSIC installations, this experimental facility allows full testing of automatic driving systems.

This paper discusses the problem of multisensor perception for autonomous stair climbing. The perception system is mounted on the Messor six-legged walking robot. The robot, due to its static stability while walking, is able to traverse obstacles in urban space, especially stairs. Messor while climbing stairs uses an adaptive algorithm, which exploits on-line perception of the stair geometry and robot pose with regard to the stair. The ascent procedure consist of three main parts. The first – preparation – measurements are performed in order to obtain information about the geometry of the stairs. The second – climbing – ascending each stair with correction of the robot orientation and horizontal position on the stairs. The third – landing – detection of the last stair and the end of the stair climbing procedure. The paper is focused on the multisensor system and the perception algorithms.

Modern walking robots are able to negotiate rough terrain. However there are still open topics, especially when there is a need to climb or descend an obstacle. This article presents the perception system for descending stairs with the sixlegged walking robot. The perception system for stair descent differs much from that used for stair climbing, while during the descent most of the surfaces of the step suffer from occlusions. Author describes the solution to this problem. The perception system consists of two sensors. Namely a video camera and a force sensor at the tip of the leg for active haptic sensing. The monocular vision system gives the scale of the stairs and the active haptic sensing system provides the additional information to obtain the real geometry of the obstacle. In the presented paper experiments were performed on the walking robot Messor. The article describes the monocular vision system and the method for obtaining the geometry of stairs. Next the ways of improving the accuracy of the system are presented.

Symmetry plays a fundamental role in aiding the visual system, to organize its environmental stimuli and to detect visual patterns of natural and artificial objects. Various kinds of symmetry exist, and we will discuss how internal symmetry due to textures influences the choice of direction in visual tasks. Two experiments are presented: the first, with human subjects, deals with the effect of textures on preferences for a pointing direction. The second emulates the performances obtained in the first through the use of an algorithm based on a physic metaphor. Results from both experiments are shown and comment.

Improving accessibility to rail systems for persons with disabilities is a governmental assignment to the Swedish Transport Administration. In this paper, we address this issue and discuss on how to obtain quality assured measurements of accessibility. We focus mainly on the accessibility definition, the validity of the measurements and the measurement uncertainty. By defining an accessibility measure that is multiplicative, we obtain a measure that represents the different barriers persons can face when travelling.

This article focuses on the influence of walking speed and direction of the robot movement on the tactile ground classification. The perception system comprise force/torque sensor mounted on the foot of a six-legged robot. The force/torque signals are registered during the negotiation of several terrains. Next, based on the statistical or spectral analysis of the signal the robot is able to classify the terrain. In this paper we are concentrated on the influence of the walking speed and the direction of the robot movement on the classification performance. The results obtained proved that it is possible to learn the characteristics of the terrain using generalized classifier, which is trained on the dataset containing measurements acquired for the whole range of the selected gait parameter.