Abstract: This paper presents a taxonomy of non-technical skills, communicative intentions, and behavior for an individual acting as a medical coordinator. In medical emergency situations, a leader among the group is imperative to both patient health and team emotional and mental health. Situational Leadership is used to make clear and easy-to-follow guidelines for behavior depending on circumstantial factors. Low-level leadership behaviors belonging to two different styles, directive and supporting, are identified from literature and are included in the proposed taxonomy. The high-level information in the taxonomy consists of the necessary non-technical skills belonging to a medical coordinator: situation awareness, decision making, task management, and teamwork. Finally, communicative intentions, dimensions, and functions are included. Thus this work brings high-level and low-level information - medical non-technical skills, communication capabilities, and leadership behavior - into a single versatile taxonomy of behavior.
Abstract: The color theory of good and evil is the association of colors to the omnipresent concept of good and evil, where human behavior and perception can be highly influenced by seeing black and white, making these connotations almost dangerously distinctive where they can be very hard to distinguish. This theory is a human construct that dates back to ancient Egypt and has been used since then in almost all forms of communication and expression, such as art, fashion, literature, and religious manuscripts, helping the implantation of preconceived ideas that influence behavior and society. This is a mixed-methods research that uses both surveys to collect quantitative data related to the theory and a vignette to collect qualitative data by using a scenario where participants aged between 18-25 will style two characters of good and bad characteristics with color contrasting clothes, both yielding results about the nature of the preconceived perceptions associated with ‘black and white’ and ‘good and evil’, illustrating the important role of media and communications in human behavior and subconscious, and also uncover how far this theory goes in the age of social media enlightenment.
Abstract: Shenzhen is a modern city of China's reform and opening-up policy, the development of urban morphology has been established on the administration of the Chinese government. This city`s planning paradigm is primarily affected by the spatial structure and human behavior. The subjective urban agglomeration center is divided into several groups and centers. In comparisons of this effect, the city development law has better to be neglected. With the continuous development of the internet, extensive data technology has been introduced in China. Data mining and data analysis has become important tools in municipal research. Data mining has been utilized to improve data cleaning such as receiving business data, traffic data and population data. Prior to data mining, government data were collected by traditional means, then were analyzed using city-relationship research, delaying the timeliness of urban development, especially for the contemporary city. Data update speed is very fast and based on the Internet. The city's point of interest (POI) in the excavation serves as data source affecting the city design, while satellite remote sensing is used as a reference object, city analysis is conducted in both directions, the administrative paradigm of government is broken and urban research is restored. Therefore, the use of data mining in urban analysis is very important. The satellite remote sensing data of the Shenzhen city in July 2018 were measured by the satellite Modis sensor and can be utilized to perform land surface temperature inversion, and analyze city heat island distribution of Shenzhen. This article acquired and classified the data from Shenzhen by using Data crawler technology. Data of Shenzhen heat island and interest points were simulated and analyzed in the GIS platform to discover the main features of functional equivalent distribution influence. Shenzhen is located in the east-west area of China. The city’s main streets are also determined according to the direction of city development. Therefore, it is determined that the functional area of the city is also distributed in the east-west direction. The urban heat island can express the heat map according to the functional urban area. Regional POI has correspondence. The research result clearly explains that the distribution of the urban heat island and the distribution of urban POIs are one-to-one correspondence. Urban heat island is primarily influenced by the properties of the underlying surface, avoiding the impact of urban climate. Using urban POIs as analysis object, the distribution of municipal POIs and population aggregation are closely connected, so that the distribution of the population corresponded with the distribution of the urban heat island.
Abstract: The human behaviors during evacuations are quite complex. One of the critical behaviors which affect the efficiency of evacuation is route choice. Therefore, the respective simulation modeling work needs to function properly. In this paper, Simulation of Urban Mobility’s (SUMO) current dynamic route modeling during evacuation, i.e. the rerouting functions, is examined with a real case study. The result consistency of the simulation and the reality is checked as well. Four influence factors (1) time to get information, (2) probability to cancel a trip, (3) probability to use navigation equipment, and (4) rerouting and information updating period are considered to analyze possible traffic impacts during the evacuation and to examine the rerouting functions in SUMO. Furthermore, some behavioral characters of the case study are analyzed with use of the corresponding detector data and applied in the simulation. The experiment results show that the dynamic route modeling in SUMO can deal with the proposed scenarios properly. Some issues and function needs related to route choice are discussed and further improvements are suggested.
Abstract: The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.
Abstract: In this paper, we present a human behavior modeling approach in videos scenes. This approach is used to model the normal behaviors in the conference halls. We exploited the Probabilistic Latent Semantic Analysis technique (PLSA), using the 'Bag-of-Terms' paradigm, as a tool for exploring video data to learn the model by grouping similar activities. Our term vocabulary consists of 3D spatio-temporal patch groups assigned by the direction of motion. Our video representation ensures the spatial information, the object trajectory, and the motion. The main importance of this approach is that it can be adapted to detect abnormal behaviors in order to ensure and enhance human security.
Abstract: The objective of this study is to investigate the effect of the excessive use of smartphones. Smartphones have enormous effects on the human body in that some musculoskeletal disorders (MSDs) and health problems might evolve. These days, there is a wide use of the smartphones among all age groups of society, thus, the focus on smartphone effects on human behavior and health, especially on the young and elderly people, becomes a crucial issue. This study was conducted in Jordan on smartphone users for different genders and ages, by conducting a survey to collect data related to the symptoms and MSDs that are resulted from the excessive use of smartphones. A total of 357 responses were used in the analysis. The main related symptoms were numbness, fingers pain, and pain in arm, all linked to age and gender for comparative reasons. A statistical analysis was performed to find the effects of extensive usage of a smartphone for long periods of time on the human body. Results show that the significant variables were the vision problems and the time spent when using the smartphone that cause vision problems. Other variables including age of user and ear problems due to the use of the headsets were found to be a border line significant.
Abstract: This paper addresses the shortcomings of architectural computation tools in representing human behavior in built environments, prior to construction and occupancy of those environments. Evaluating whether a design fits the needs of its future users is currently done solely post construction, or is based on the knowledge and intuition of the designer. This issue is of high importance when designing complex buildings such as hospitals, where the quality of treatment as well as patient and staff satisfaction are of major concern. Existing computational pre-occupancy human behavior evaluation methods are geared mainly to test ergonomic issues, such as wheelchair accessibility, emergency egress, etc. As such, they rely on Agent Based Modeling (ABM) techniques, which emphasize the individual user. Yet we know that most human activities are social, and involve a number of actors working together, which ABM methods cannot handle. Therefore, we present an event-based model that manages the interaction between multiple Actors, Spaces, and Activities, to describe dynamically how people use spaces. This approach requires expanding the computational representation of Actors beyond their physical description, to include psychological, social, cultural, and other parameters. The model presented in this paper includes cognitive abilities and rules that describe the response of actors to their physical and social surroundings, based on the actors’ internal status. The model has been applied in a simulation of hospital wards, and showed adaptability to a wide variety of situated behaviors and interactions.
Abstract: In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.
Abstract: In this paper, we propose the variational EM inference
algorithm for the multi-class Gaussian process classification model
that can be used in the field of human behavior recognition. This
algorithm can drive simultaneously both a posterior distribution of a
latent function and estimators of hyper-parameters in a Gaussian
process classification model with multiclass. Our algorithm is based
on the Laplace approximation (LA) technique and variational EM
framework. This is performed in two steps: called expectation and
maximization steps. First, in the expectation step, using the Bayesian
formula and LA technique, we derive approximately the posterior
distribution of the latent function indicating the possibility that each
observation belongs to a certain class in the Gaussian process
classification model. Second, in the maximization step, using a derived
posterior distribution of latent function, we compute the maximum
likelihood estimator for hyper-parameters of a covariance matrix
necessary to define prior distribution for latent function. These two
steps iteratively repeat until a convergence condition satisfies.
Moreover, we apply the proposed algorithm with human action
classification problem using a public database, namely, the KTH
human action data set. Experimental results reveal that the proposed
algorithm shows good performance on this data set.
Abstract: Health of a person plays a vital role in the collective
health of his community and hence the well-being of the society as a
whole. But, in today’s fast paced technology driven world, health
issues are increasingly being associated with human behaviors – their
lifestyle. Social networks have tremendous impact on the health
behavior of individuals. Many researchers have used social network
analysis to understand human behavior that implicates their social
and economic environments. It would be interesting to use a similar
analysis to understand human behaviors that have health
implications. This paper focuses on concepts of those behavioural
analyses that have health implications using social networks analysis
and provides possible algorithmic approaches. The results of these
approaches can be used by the governing authorities for rolling out
health plans, benefits and take preventive measures, while the
pharmaceutical companies can target specific markets, helping health
insurance companies to better model their insurance plans.
Abstract: There has been a significant decline in active travel
and a massive increase in the use of car dependent travel in many
countries during the past two decades. Evidential risks for people’s
physical and mental health problems are correlated with this
increased use of motorized travel. These health related problems
range from overweight and obesity to increased air pollution. In
response to these rising concerns health professionals, traffic planers,
local authorities and others have introduced a variety of initiatives to
counterbalance the dominance of cars for daily journeys.
However, the nature of travel behavior change interventions,
which aim to reduce car use, are very complex and challenging
regarding their interactions with human behavior. To change travel
behavior at least two aspects have to be taken into consideration.
First, how to alter attitudes and perceptions toward the sustainable
and healthy modes of travel, in competition with experiences of
private car use. And second, how to make these behavior change
processes irreversible and sustainable. There are no comprehensive
models available to guide policy interventions to increase the level of
success of travel behavior change interventions across both these
dimensions.
A comprehensive theoretical framework is required in the effort to
optimize how to facilitate and guide the processes of data collection
and analysis to achieve the best possible guidelines for policy
makers. Regarding the gaps in the travel behavior change research
literature, this paper attempted to identify and suggest a
multidimensional framework in order to facilitate planning the
implemented travel behavior change interventions. A structured
mixed-method model is suggested to improve the analytic power of
the results according to the complexity of human behavior.
In order to recognize people’s attitudes towards a specific travel
mode, the Theory of Planned Behavior (TPB) was operationalized.
But in order to capture decision making processes the Transtheoretical
model of Behavior Change (TTM) was also used.
Consequently, the combination of these two theories (TTM and TPB)
has resulted in a synthesis with appropriate concepts to identify and
design an implemented travel behavior change interventions.
Abstract: Although there had been a many studies that shows
the impact of air pollution on physical health, comparatively less was
known of human behavioral responses and annoyance impacts.
Annoyance caused by air pollution is a public health problem because
it can be an ambient stressor causing stress and disease and can affect
quality of life. The objective of this work is to evaluate the
annoyance caused by air pollution in two different industrialized
urban areas, Dunkirk (France) and Vitoria (Brazil). The populations
of these cities often report feeling annoyed by dust. Surveys were
conducted, and the collected data were analyzed using statistical
analyses. The results show that sociodemographic variables,
importance of air quality, perceived industrial risk, perceived air
pollution and occurrence of health problems play important roles in
the perceived annoyance. These results show the existence of a
common problem in geographically distant areas and allow
stakeholders to develop prevention strategies.
Abstract: Nations are still finding it quite difficult to win mega
sport competitions despite the major contribution of sport to society
in terms of social and economic development, personal health, and in
education. Even though the world of sports has been transformed into
a huge global economy, it is important to note that the first step of
sport is usually its introduction to children at school through physical
education or PE. In other words, nations who do not win mega sport
competitions also suffer from a weak and neglected PE system. This
problem of the neglect of PE systems is the main motivation of this
research aimed at examining the factors affecting the perceived
awareness of physical education teachers on the ICTs that are
adoptable for the teaching and learning of physical education. Two
types of research objectives will materialize this aim: relevant
theories will be identified in relation to the analysis of the perceived
ICT awareness of PE teachers and subsequent models will be
compiled and designed from existing literature; the empirical testing
of such theories and models will also be achieved through the survey
of PE teachers from the Camperdown magisterial district of the
KwaZulu-Natal province of South Africa. The main hypothesis at the
heart of this study is the relationship between the demographics of PE
teachers, their behavior both as individuals and as social entities, and
their perceived awareness of the ICTs that are adoptable for PE, as
postulated by existing literature; except that this study categorizes
human behavior under performance expectancy, computer attitude,
and social influence. This hypothesis was partially confirmed by the
survey conducted by this research in the sense that performance
expectancy and teachers’ age, gender, computer usage, and class size
were found to be the only factors affecting their awareness of ICTs
for physical education.
Abstract: FengShui, an old Chinese discipline, dates back to
more than 5000 years, is one of the design principles that aim at
creating habitable and sustainable spaces in harmony with nature by
systematizing data within its own structure. Having emerged from
Chinese mysticism and embodying elements of faith in its principles,
FengShui argues that the positive energy in the environment channels
human behavior and psychology. This argument is supported with the
thesis of quantum physics that ‘everything is made up of energy’ and
gains an important place.
In spaces where living and working take place with several
principles and systematized rules, FengShui promises a happier, more
peaceful and comfortable life by influencing human psychology, acts,
and soul as well as the professional and social life of the individual.
Observing these design properties in houses, workplaces, offices, the
environment, and daily life as a design paradigm is significant. In this
study, how FengShui, a Central Asian culture emanated from Chinese
mysticism, shapes design and how it is used as an element of
sustainable design will be explained.
Abstract: Around the world, there are frequent incidents of natural disasters, such as earthquakes, tsunamis, floods, and snowstorms, as well as manmade disasters such as fires, arsons, and acts of terror. These diverse and unpredictable adversities have resulted in a number of fatalities and injuries. If disaster occurrence can be assessed quickly and information such as the exact location of the disaster and evacuation routes can be provided, victims can promptly move to safe locations, minimizing losses. This paper proposes a behavior analysis method based on a nine degrees-of-freedom (9-DOF) sensor that is effective for the emergency rescue evacuation support system (ERESS), which is being researched with an objective of providing evacuation support during disasters. Based on experiments performed using the acceleration sensor and the gyroscope sensor in the 9-DOF sensor, data are analyzed for human behavior regarding stationary position, walking, running, and during emergency situation to suggest guidelines for system judgment. Using the results of the experiments performed to determine disaster occurrence, it was confirmed that the proposed method quickly determines whether a disaster has occurred.
Abstract: Social ideology, cultural values and principles shaping environment are inferred by environment and structural characteristics of construction site. In other words, this inference manifestation also indicates ideology and culture of its foundation and also applies its principles and values and somehow plays an important role in Cultural Revolution. All human behaviors and artifacts are affected and being influenced by culture. Culture is not abstract concept, it is a spiritual domain that an individual and society grow and develop in it. Social behaviors are affected by environmental comprehension, so the architecture work influences on its audience and it is the environment that fosters social behaviors. Indeed, sustainable architecture should be considered as background of culture for establishing optimal sustainable culture. Since unidentified architecture roots in cultural non identity and abnormalities, so the society possesses identity characteristics and life and as a consequence, the society and architecture are changed by transformation of life style. This article aims to investigate the interaction of architecture, society, environment and sustainable architecture formation in its cultural basis and analyzes the results approaching behavior and sustainable culture in recent era.
Abstract: The history of technology and banking is examined as
it relates to risk and technological determinism. It is proposed that
the services that banks offer are determined by technology and that
banks must adopt new technologies to be competitive. The adoption
of technologies paradoxically forces the adoption of other new
technologies to protect the bank from the increased risk of
technology. This cycle will lead to bank examiners and regulators to
focus on human behavior, not on the ever changing technology.
Abstract: The values of managers and employees in organizations are phenomena that have captured the interest of researchers at large. Despite this attention, there continues to be a lack of agreement on what values are and how they influence individuals, or how they are constituted in individuals- mind. In this article content-based approach is presented as alternative reference frame for exploring values. In content-based approach human thinking in different contexts is set at the focal point. Differences in valuations can be explained through the information contents of mental representations. In addition to the information contents, attention is devoted to those cognitive processes through which mental representations of values are constructed. Such informational contents are in decisive role for understanding human behavior. By applying content-based analysis to an examination of values as mental representations, it is possible to reach a deeper to the motivational foundation of behaviors, such as decision making in organizational procedures, through understanding the structure and meanings of specific values at play.
Abstract: Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.