Characteristics Of Human Behavior Research Articles

A multibiometric system based on the fusion of fingerprint, finger-vein, and finger-knuckle-print

Authentication systems play an essential role in our lives today. Human biological, behavioral, and morphological characteristics are usually used in an authentication system in a vast scope of applications ranging from unlocking consumer devices to surveillance and forensic analysis and offered an alternative to credit cards, ID cards, passports, driving licenses, etc. Unibiometric systems, which use a single biometric modality, suffer from some drawbacks such as low protection of user’s privacy against attacks. Multibiometric systems, which fuse features of biometric characteristics, can cope with unibiometric systems’ drawbacks and improve security and recognition accuracy. However, some main questions such as ‘what is the optimal number of biometric modalities?’, ‘how much accuracy do we need for our system?’, and ‘how much money do we want to invest for our system?’ have to be considered and answered before designing and implementing a multibiometric system. Unfortunately, the existing multibiometric systems have not considered and responded to all questions. Furthermore, identification mode for multibiometric systems is a challenging task and almost all of them have focused on verification mode. In this paper, we only consider a finger and employ the maximum possible modalities of the finger, i.e., fingerprint, finger-vein, and finger-knuckle-print, to increase user-friendliness and reducing the cost of implementation of the system. The proposed system only uses three cameras to capture all contactless fingerprint, finger-vein, and finger-knuckle images. Also, we propose an algorithm that makes enable the system to work in identification mode. The experiments on established databases exhibit that our proposed algorithm significantly increases recognition accuracy.

Вихрь в демонологических представлениях украинцев

The article deals the beliefs about the whirlwind in Ukrainian demonology. On the basis of the empiric materials the аuthor considered the features of human behavior at a meeting with whirlwind and consequent after contact’s with him; retraces whirlwind’s connection with other mythological characters – a devil, a sorcerer, a witch, self-murderer spirits and others.

Human Behavior During Emergency Evacuation: Cell Transmission Model

This paper presents an extended cell transmission model to simulate an emergency evacuation of crowd in a supermarket scenario. The supermarket scenario with a daily shopping, an emergency exit and multiple parallel shelves is discretized into a set of regular hexagonal cells. First, we verify the validity of the model by comparing the results of the model with actual data obtained from a reported pedestrian evacuation experiment. To improve the realism of the simulation, we then include three characteristics of human behavior, the unadventurous effect, inertial effect, and panic psychology, in the model as parameters and apply the extended model to the supermarket scenario. By analyzing the pedestrian density distribution, fundamental diagrams, route choice, and total evacuation time, we determine that the parameters have a significant influence on the evacuation process. By establishing a minimization model, we confirm that the total evacuation time is the least when the pedestrians’ familiarity with the emergency exit is close to the ratio of the width of the emergency exit to the total width of the two exits. Moreover, by comparing two different methods to choose exits, we can conclude that the approach, by which all pedestrians choose the closer exit, is not always the most efficient evacuation strategy. This study is conducive to devise evacuation plans and design exit layouts in facilities similar to supermarkets.

Robustness for Authentication of the Human Using Face, Ear, and Gait Multimodal Biometric System

Biometrics is the science that deals with personal human physiological and behavioral characteristics such as fingerprints, handprints, iris, voice, face recognition, signature recognition, ear recognition, and gait recognition. Recognition using a single trait has several problems and multimodal biometrics system is one of the solutions. In this work, the novel and imperative biometric feature gait is fused with face and ear biometric features for authentication and to overcome problems of the unimodal biometric recognition system. The authors have also applied various normalization methods to sort out the best solution for such a challenge. The feature fusion of the proposed multimodal biometric system has been tested using Min-Max and Z-score techniques. The computed results demonstrate that Z-Score outperforms the Min-Max technique. It is deduced that the Z-score is a promising method that generates a high recognition rate of 95% and a false acceptance rate of 10%.

Бездействие в гражданском праве: определение понятия

The article is devoted to the identification of signs of such form of civil law behavior as inaction. Based on these signs the author formulates the definition of inaction in civil law. The need for a definition of this concept is due to the absence of the study of this civil law behavior form, as well as its generally accepted interpretation, in the civil doctrine. The author studies general signs of behavior, allocated in the sciences that study human behavior, the study of signs of legal behavior, allocated in the legal science, attempts to interpret these signs in relation to the concept of inaction in civil law, as well as identifies the specifics of such inaction. It is proved that the opinion generally accepted in the legal doctrine, that inaction is a manifestation of passivity, is not confirmed by psychological characteristics of human behavior, and the absence of observable acts of behavior does not indicate the lack of such behavior activity. The stage character of choosing the form of external manifestation of behavioral model is considered and the stages of the process of formation of inaction mechanism in civil law are determined. Following the results of the study the definition of inaction in civil law has been given.

Human Behavior Feature Representation and Recognition Based on Depth Video

With the continuous development of computer artificial intelligence technology, various applications based on artificial intelligence emerge in an endless stream, among which video image recognition technology is the most widely used in life. This article starts from the process of image recognition, based on the composite characteristics of artificial intelligence and video images, to discuss human gesture recognition technology.This article uses the feature extraction algorithm for image composite feature extraction as a method, and conducts human body movement collection experiments, analyzes the database and The gesture recognition step. This paper mainly introduces the extraction method of image composite features and the basic requirements of gesture recognition, and through the algorithm calculation of feature extraction, the function of human gesture recognition video and image composite features is completed, and the human action collection experiment is carried out to confirm. The results of images and data show the advantages of the algorithm support used in this article. We will Dmti. MsHOG is compared with other methods in the three subsets. In terms of the accuracy of all tests, our method performs better than other methods. The results show that the MSHOG (Multi-scale Histogram of Oriented Gradients) descriptor can represent the unique characteristics of human behavior, reflecting the effectiveness of our proposed method. In particular, this method achieved 100% recognition accuracy in Test, with an average recognition accuracy of 94.91%, which is significantly better than existing methods.

EXPLORING SPATIAL PARAMETERS TO EVALUATE HUMAN WALKING ACCESSIBILITY OF URBAN GREEN SPACE

Abstract. With the growth of urban population and the increasing urban density, urban green space has become a kind of precious and limited resources. It not only has a positive impact on the health of urban residents with high work-life pressure but also offers opportunities as part of blue-green solutions for sustainable urban water management. Therefore, to effectively utilise the limited green spaces, experts are exploring a way of organising the green space layout to balance human needs and other urban developing requirements (e.g., in this case, urban stormwater management) within the certain common area. With this target, translating the space accessibility to human and other urban developments on green space into space parameter is a critical step to organize space model for the multi-functional green space. Although there are plenty of existing spatial parameters developed for evaluating human accessibility (such as travel distance, land-use, spatial connectivity etc.), there isn’t a way to organize them to satisfy the diverse evaluation needs from different research purposes. Besides, most of them are suitable for analyzing space on a city scale or at least a precinct scale in a 2D model. To the accurate design on a micro-scale, it is still a big challenge. The reason is some parameters for city analysis don’t work on a micro-scale, and some parameters should be reorganised in the evaluation algorithm or should include more micro-scale factors. Thus, this paper, based on the characteristics of human behaviour, redefines the complex concept- accessibility and develop measurable parameters with feasible factors on micro-scale. Overall, this paper presents: (1) a new definition of walking accessibility of green space; (2) evaluation criteria (3) parameters (depth and Integration) reflecting connectivity criteria (4) Parameters (travel time and speed, slope, direction changes) relating travel distance criteria with updated evaluation algorithm and factors. This paper aims at useful spatial parameters and evaluation measures that are applicable to integrate human needs within multi-functional green space design, especially green stormwater management design.

The Economics of Hypergamy

Partner selection is a vital feature of human behavior with important consequences for indi-viduals, families, and society. Hypergamy occurs when a husband's earning capacity system-atically exceeds that of his wife. We provide a theoretical framework that rationalizes hy-pergamy even in the absence of gender differences in the distribution of earnings capacity. Using parental earnings rank, a predetermined measure of earnings capacity that solves the simultaneity problem of matching affecting earnings outcomes, we show that hypergamy is an important feature of Norwegian mating patterns. A vignette experiment identifies gender differences in preferences that can explain the observed patterns.

Azure-winged magpies\u2019 decisions to share food are contingent on the presence or absence of food for the recipient

Helping others is a key feature of human behavior. However, recent studies render this feature not uniquely human, and describe discoveries of prosocial behavior in non-human primates, other social mammals, and most recently in some bird species. Nevertheless, the cognitive underpinnings of this prosociality; i.e., whether animals take others’ need for help into account, often remain obscured. In this study, we take a first step in investigating prosociality in azure-winged magpies by presenting them with the opportunity to share highly desired food with their conspecifics i) in a situation in which these conspecifics had no such food, ii) in a situation in which they too had access to that highly desired food, and iii) in an open, base-line, situation where all had equal access to the same food and could move around freely. We find that azure-winged magpies regularly share high-value food items, preferably with, but not restricted to, members of the opposite sex. Most notably, we find that these birds, and specifically the females, seem to differentiate between whether others have food or do not have food, and subsequently cater to that lack. Begging calls by those without food seem to function as cues that elicit the food-sharing, but the response to that begging is condition-dependent. Moreover, analyses on a restricted dataset that excluded those events in which there was begging showed exactly the same patterns, raising the possibility that the azure-winged magpies might truly notice when others have access to fewer resources (even in the absence of vocal cues). This sharing behavior could indicate a high level of social awareness and prosociality that should be further investigated. Further studies are needed to establish the order of intentionality at play in this system, and whether azure-winged magpies might be able to attribute desire states to their conspecifics.

Chronic Maternal Tobacco Smoke Exposure and/or Alpha-Lipoic Acid Treatment Causes Long-Term Deterioration of Testis and Sexual Behavior in Adult Male Rats

BackgroundTobacco use during pregnancy is known to have several negative effects on the offspring's reproductive health in the long term. The use of alpha-lipoic acid (ALA) as a dietary supplement during pregnancy has increased greatly in recent years and has been known to have positive effects on various pregnancy outcomes including miscarriage, diabetic embryopathy, preterm delivery, and congenital malformations. AimTo evaluate the effects of tobacco smoke exposure (TSE) on sexual behavior, reproductive parameters, and testicles in adult male rats and to reveal the possible role of ALA administration on these parameters. MethodsPregnant rats (n = 7 per group) were treated with tobacco smoke (TS), ALA (20 mg/kg), and TS + ALA for a total of 11 weeks. The following parameters were compared with 8 control rats: puberty parameters, sexual behavior; levels of serum gonadotropins and testosterone, total antioxidant status, and total oxidant status; the expression of the apoptotic protease-activating factor-1 and caspase 9 mRNA levels in the testis; and assessment of immunohistochemistry and terminal deoxynucleotidyl transferase dUTP nick end labeling assay of testis. Main Outcome MeasureSexual behavior, changes in puberty parameters, and hormonal and genetic alterations were the outcomes analyzed in this study. ResultsMaternal TSE caused a significant decrease in the number of intromissions compared to the control group. Similarly, ALA decreased erectile function in sexual behavior by decreasing the number of intromissions and intromission ratio in the ALA group compared to the control group. In addition, TSE and ALA treatment caused an impairment of some consummatory sexual behaviors. Also, in parallel with this inhibitory effect, the age of pubertal onset was significantly delayed in the TS + ALA group compared to other groups. Also, histopathological changes in testicular tissue, oxidative stress markers, apoptotic index, and mRNA levels of apoptosis-related genes increased in all treatment groups. Clinical ImplicationsThe use of ALA and/or tobacco products during pregnancy may adversely affect the reproductive health of male newborns in the long term. Strengths & LimitationsTo the best of our knowledge, this study is the first to show the effects of maternal ALA treatment and/or TSE on the sexual behavior and reproductive parameters in male rats; however, the study is based on an animal model, and the present findings partially reflect the characteristics of human sexual behavior. ConclusionMaternal TSE and/or ALA treatment may impair sexual behavior in adulthood in male rats because of testicular damage caused by oxidative stress during gonadal development.Yardimci A, Akkoc RF, Tektemur A, et al. Chronic Maternal Tobacco Smoke Exposure and/or Alpha-Lipoic Acid Treatment Causes Long-Term Deterioration of Testis and Sexual Behavior in Adult Male Rats. J Sex Med 2020;17:1835–1847.

Dissociable Neural Systems Support the Learning and Transfer of Hierarchical Control Structure.

Humans can draw insight from previous experiences to quickly adapt to novel environments that share a common underlying structure. Here we combine functional imaging and computational modeling to identify the neural systems that support the discovery and transfer of hierarchical task structure. Human subjects (male and female) completed multiple blocks of a reinforcement learning task that contained a global hierarchical structure governing stimulus-response action mapping. First, behavioral and computational evidence showed that humans successfully discover and transfer the hierarchical rule structure embedded within the task. Next, analysis of fMRI BOLD data revealed activity across a frontoparietal network that was specifically associated with the discovery of this embedded structure. Finally, activity throughout a cingulo-opercular network supported the transfer and implementation of this discovered structure. Together, these results reveal a division of labor in which dissociable neural systems support the learning and transfer of abstract control structures.SIGNIFICANCE STATEMENT A fundamental and defining feature of human behavior is the ability to generalize knowledge from the past to support future action. Although the neural circuits underlying more direct forms of learning have been well established over the last century, we still lack a solid framework from which to investigate more abstract, higher-order human learning and knowledge generalization. We designed a novel behavioral paradigm to specifically isolate a learning process in which previous knowledge, rather than directly indicating the correct action, instead guides the search for the correct action. Moreover, we identify that this learning process is achieved via the coordinated and temporally specific activity of two prominent cognitive control brain networks.

The influence of human behavioral characteristics on soundscape perception in urban parks: Subjective and observational approaches

With an emphasis on the role of parks in urban environments, studies on soundscape, which assess sound quality, have focused on human perception. In particular, various studies have been conducted on the relationship between human behavioral characteristics and their sound environment. However, there is still insufficient research on human behavioral characteristics in the context of urban parks. The purpose of this study was to investigate the effect of human behavioral characteristics on perceptions of soundscapes in urban parks. Participants were asked to subjectively evaluate the soundscapes of three parks in Paris, France, using three cognitive stages: indicators (perceived audio and visual elements), emotions (semantic expression), and cognition (overall quality of the park’s soundscape). The human behavioral characteristics that the participants witnessed were categorized into whether there was social interaction, whether people remained in the park or were passing through, and what kind of activities took place. To secure high ecological validity, audio-visual information was provided to the participants using virtual reality equipment. The results demonstrated that sounds made by other people decreased the perceived tranquility or peacefulness while the experience of the park as being dynamic and lively increased. We also found that the primary determinant of park preferences was not the type of human activities but the presence or absence of people.

Human movement characteristics during emergency evacuations in a virtual environment

This study presents an evacuation experiment to test individual behavior in an interactive virtual environment. A total of 68 test scenarios were established, and 122 participants were recruited to take part in all the test scenarios. The results show that individual attributes, such as sex, education background, age, and evacuation experience, have a correlation with the participants’ ability of escaping in the virtual evacuation environment. Specifically, younger men with higher education level and evacuation experience may have a better ability of escaping. The comparison of the evacuation paths, directions, and times among 8 scenarios with different sets reveals that people prefer to select the shortest route, but keep away from the fire source as much as possible if a fire happens. On the other hand, other people compete with the individual for the available evacuation resources, but when the exit location is unknown, other people may help individuals find the exit. In addition, the visibility decreases in case of fire, which is the most difficult condition for escaping with the longest movement distance and most evacuation time. This study will be useful to understand the human behavior and movement characteristics during evacuation by using a cheap and safe method.

Video Human Behavior Recognition Based on ISA Deep Network Model

Vision-based behavior recognition is the analysis and recognition of human behavior in video. It has been widely used in many aspects such as multimedia information retrieval, behavior monitoring, and robot perception. This paper uses the Independent Subspace Analysis (ISA) deep network model feature extraction method, which is based on the ISA model and neural network theory, and combines data preprocessing methods, [Formula: see text]-means clustering methods, and Support Vector Machine (SVM) classifiers to achieve video classification and identification of human behavior. The ISA-based deep network model feature extraction method is an unsupervised learning method that can obtain behavior characteristics with good invariance and characterization capabilities in video human behavior. The experiment was conducted on the basis of the Hollywood2 human behavior data set. This experiment was compared with other commonly used human behavior feature extraction and recognition methods. The experimental results validated the effectiveness and advantages of this method in the classification and recognition of human behavior.

Multidisciplinary Nature of the Psycholinguistic Discourse Neuroeconomics

Introduction. The article is devoted to the issues of multidisciplinary interaction in new scientific fields, which involve a wide variety of convergences, no matter how strange at first glance they may seem. One of these phenomena is the interaction of psycholinguistics and neuroeconomics.
 The goal. The article examines the transition of modern science to multidisciplinary discourse, which makes it necessary to conceptualize and possibly operationalize methods of psycholinguistics. The conceptualization of new areas of neuroeconomics, in a psycholinguistic context, presupposes a certain mental experience that includes, in addition to the processes of creating new concepts and contextual economic knowledge, also defining the role of interests, intentions, emotions in human economic activity.
 Methods. Multivariate analysis, comparative analysis, extrapolation.
 Results. It is proved that in recent decades the development of new areas of economic science, namely those related to the development of neuroeconomics, has significantly expanded the field of psycholinguistics. The production of new paradigms of economic theory, the formation of the corresponding definitions, objects requires the design and definition of them both in form and in content. It considers the need for a theoretical and orderly definition of the functional meaning of the psycholinguistic context of new definitions, the result of which can be a conceptual system for communication between specialists in various fields of science at the level of their professional understanding. It seems that the central issues in the psycholinguistic discourse of neuroeconomics have become the relationship between economics, psychology, linguistics and psycholinguistics. Such connection is undoubtedly of a multidisciplinary nature, which contributes to the deepening of the relationship between scientific thought, culture and language and became the impetus for understanding the nature of human cognition at a higher, multidisciplinary level of development of science. This is a necessary component for understanding the meanings and structure of concepts, terms and definitions, as well as communications at a higher scientific level.
 Conclusions. It is concluded that new areas of neuroeconomics such as behavioral economics, behavioral finance, emotional economics, psychological economics, have become areas of economic theory that, explicitly or implicitly, take into account the psychological characteristics of human perception and behavior in the process of economic activity. These definitions catalyze the theoretical integration of various scientific fields, and, above all, psycholinguistic science.

Vaccination behavior by coupling the epidemic spreading with the human decision under the game theory

When confronting the epidemics or pandemics, there often exists an interplay between epidemic incidence and the vaccination strategies of individuals. Recently, the characteristics of human behaviors, such as imitating nature or bandwagon effect, have been proven critical to the final herd immunity. In this paper, by establishing a two-layered multiplex network model which combines SIR epidemic process, vaccination decision-making and imitating human nature, we discover that imitating behavior would restrain the increase of herd immunity, which is verified by Monte Carlo simulations and mean-field equations, respectively. Interestingly, a suitable quantity of conformity motivated individual, counter-intuitively, could be beneficial to save the social costs. At the same time, we analytically determine the precise conditions for the minimum total social costs. The current results can help to understand the behavior of social group in depth and then explore public attitudes concerning the vaccine, which usually has a tremendous impact on social vaccine take-up within the population.

Behavioral feature recognition of multi-task compressed sensing with fusion relevance in the Internet of Things environment

With the development of electronic and communication technologies, wireless sensors have been widely used. Human behavior recognition based on micro-inertial sensor is an important application of the Internet of Things, and it has received increasing attention. This paper first introduces the theory of compressed sensing and sparse representation to solve the problem of sensor behavior classification. Aiming at the problem of multi-sensor behavior recognition, an effective result fusion method is proposed. By analyzing the multi-task behavior recognition process, the residual model is introduced to effectively integrate the multi-task results and fully exploit the data information. Secondly, in view of the fact that the characteristics of sensor behavior recognition mostly use the time–frequency domain characteristics of digital signal processing, this paper proposes an association feature. In a multi-sensor system, there is a correlation between sensor data at different locations according to human behavior characteristics. The combination of different position sensor information better reflects the human motion characteristics. This feature can effectively mine the potential information in the existing data and improve the behavior recognition rate. Finally, in order to enhance the robustness of the wearable sensing behavior recognition system, the system structure is optimized and analyzed, and the fusion problem of multi-sensor nodes is further studied. In the established decision fusion framework, the adaptive logarithmic optimization pool is used to make decision fusion for the classification posterior probability output of each node, and finally the class of behavior is discriminated. The experimental results show that the proposed method can effectively improve the performance of behavior recognition.

Further Understanding Videos through Adverbs: A New Video Task

Video understanding is a research hotspot of computer vision and significant progress has been made on video action recognition recently. However, the semantics information contained in actions is not rich enough to build powerful video understanding models. This paper first introduces a new video semantics: the Behavior Adverb (BA), which is a more expressive and difficult one covering subtle and inherent characteristics of human action behavior. To exhaustively decode this semantics, we construct the Videos with Action and Adverb Dataset (VAAD), which is a large-scale dataset with a semantically complete set of BAs. The dataset will be released to the public with this paper. We benchmark several representative video understanding methods (originally for action recognition) on BA and action recognition. The results show that BA recognition task is more challenging than conventional action recognition. Accordingly, we propose the BA Understanding Network (BAUN) to solve this problem and the experiments reveal that our BAUN is more suitable for BA recognition (11% better than I3D). Furthermore, we find these two semantics (action and BA) can propel each other forward to better performance: promoting action recognition results by 3.4% averagely on three standard action recognition datasets (UCF-101, HMDB-51, Kinetics).

A Universal Control Scheme of Human-Like Steering in Multiple Driving Scenarios

To incorporate the inherent superiorities of an experienced, proficient driver, a human-like control scheme for automated steering systems is proposed in this paper based on the concept of “staying within the safety zone”. Designed in the precognitive architecture, the novel control scheme takes into account key characteristics of human steering behaviors in high-speed conditions by determining the steering activation and the steering intensity based on the inversed-time-to-lane-crossing (iTLC), generating smooth, moderate steering actions to maintain the vehicle within a predefined safety zone. The proposed control scheme provides a universal solution for steering control in multiple driving scenarios by accordingly allocating the safety zone to ensure the driving safety therein. A simulator experiment was conducted to test both the fully autonomous and the driver-in-the-loop performance of the proposed control scheme in lane keeping and lane changing. A traditional error-minimizing control algorithm was implemented as a comparison. Results indicate that the novel scheme outperforms the conventional control schemes by yielding higher steering performance, lower steering effort, and higher robustness, proving the benefits of imitating the patterns of human control behaviors in the control algorithm of an automated steering system.

Field experiments on longitudinal characteristics of human driver behavior following an autonomous vehicle

Although mixed traffic, including both autonomous vehicles (AV) and human-driven vehicles (HV), is expected to prevail in the foreseeable future, our current understanding of the longitudinal characteristics of mixed traffic is limited and, in particular, lacks evidence from field experiments. To bridge this gap, we designed and conducted a set of field experiments to reveal differences in car-following behaviors between a human driver following-AV and following-HV on both constant speed traffic characteristics with discrete speeds ({10,20,…,60}km/h) and dynamic car-following behaviors with continuous speeds (within 0–60 km/h) in both the indifferentiable and differentiable appearance settings of the AV. We recruited 10 drivers for the experiment (14 runs for each driver and collected position and speed data of the tested vehicles along their complete trajectories based on vehicle gaps, headways, and standard deviations of vehicle speed. A K-means clustering algorithm was applied to classify drivers based on their responses in following-AV vs. following-HV with both constant speed and dynamic speed characteristics. The analyses of the differentiable appearance setting show that different drivers exhibit different behaviors in following-AV vs. following-HV: some are AV-believers, some are AV-skeptics, and the others are insensitive. Yet in the indifferentiable appearance setting, there is no significant difference between following a lead AV and following a lead HV. This reveals that drivers’ response to the lead vehicle depends on their subjective trusts on AV technologies rather than the actual driving behavior. The results suggest that, depending on the characteristics and composition of the drivers, classic car-following behavior in pure HV traffic may need to be updated for modeling mixed traffic in the near future.