Security incidents affecting information systems in cyberspace keep on rising. Researchers have raised interest in finding out how to manage security incidents. Various solutions proposed do not effectively address th...Security incidents affecting information systems in cyberspace keep on rising. Researchers have raised interest in finding out how to manage security incidents. Various solutions proposed do not effectively address the problematic situation of security incidents. The study proposes a human sensor web Crowd sourcing platform for reporting, searching, querying, analyzing, visualizing and responding to security incidents as they arise in real time. Human sensor web Crowd sourcing security incidents is an innovative approach for addressing security incidents affecting information systems in cyberspace. It employs outsourcing collaborative efforts initiatives outside the boundaries of the given organization in solving a problematic situation such as how to improve the security of information systems. It was managed by soft systems methodology. Moreover, security maturity level assessment was carried out to determine security requirements for managing security incidents using ISO/IEC 21827: Systems security engineering capability maturity model with a rating scale of 0 - 5. It employed descriptive statistics and non-parametric statistical method to determine the significance of each variable based on a research problem. It used Chi-Square Goodness of Fit Test (X2) to determine the statistical significance of result findings. The findings revealed that security controls and security measures are implemented in ad-hoc. For managing security incidents, organizations should use human sensor web Crowd sourcing platform. The study contributes to knowledge base management learning integration: practical implementation of Crowd sourcing in information systems security.展开更多
Human Activity Recognition (HAR) is an important way for lower limb exoskeleton robots to implement human-computer collaboration with users. Most of the existing methods in this field focus on a simple scenario recogn...Human Activity Recognition (HAR) is an important way for lower limb exoskeleton robots to implement human-computer collaboration with users. Most of the existing methods in this field focus on a simple scenario recognizing activities for specific users, which does not consider the individual differences among users and cannot adapt to new users. In order to improve the generalization ability of HAR model, this paper proposes a novel method that combines the theories in transfer learning and active learning to mitigate the cross-subject issue, so that it can enable lower limb exoskeleton robots being used in more complex scenarios. First, a neural network based on convolutional neural networks (CNN) is designed, which can extract temporal and spatial features from sensor signals collected from different parts of human body. It can recognize human activities with high accuracy after trained by labeled data. Second, in order to improve the cross-subject adaptation ability of the pre-trained model, we design a cross-subject HAR algorithm based on sparse interrogation and label propagation. Through leave-one-subject-out validation on two widely-used public datasets with existing methods, our method achieves average accuracies of 91.77% on DSAD and 80.97% on PAMAP2, respectively. The experimental results demonstrate the potential of implementing cross-subject HAR for lower limb exoskeleton robots.展开更多
In this work, an electrochemical sensor was fabricated for determination of an anthracycline, doxorubicin(DOX) as a chemotherapy drug in plasma based on multi-walled carbon nanotubes modified platinum electrode(Pt/MWC...In this work, an electrochemical sensor was fabricated for determination of an anthracycline, doxorubicin(DOX) as a chemotherapy drug in plasma based on multi-walled carbon nanotubes modified platinum electrode(Pt/MWCNTs). DOX was effectively accumulated on the surface of modified electrode and generated a pair of redox peaks at around 0.522 and 0.647 V(vs. Ag/Ag Cl) in Britton Robinson(B-R) buffer(p H 4.0, 0.1 M). The electrochemical parameters including p H, type of buffer, accumulation time, amount of modifier and scan rate were optimized. Under the optimized conditions, there was a linear correlation between cathodic peak current and concentration of DOX in the range of 0.05–4.0 μg/m L with the detection limit of 0.002 μg/m L. The number of electron transfers(n) and electron transfer-coefficient(α) were estimated as 2.0 and 0.25, respectively. The constructed sensor displayed excellent precision, sensitivity, repeatability and selectivity in the determination of DOX in plasma. Moreover, cyclic voltammetry studies of DOX in the presence of DNA showed an intercalation mechanism with binding constant(K_b) of 1.12×10~5L/mol.展开更多
Low Resolution Thermal Array Sensors are widely used in several applications in indoor environments. In particular, one of these cheap, small and unobtrusive sensors provides a low-resolution thermal image of the envi...Low Resolution Thermal Array Sensors are widely used in several applications in indoor environments. In particular, one of these cheap, small and unobtrusive sensors provides a low-resolution thermal image of the environment and, unlike cameras;it is capable to detect human heat emission even in dark rooms. The obtained thermal data can be used to monitor older seniors while they are performing daily activities at home, to detect critical situations such as falls. Most of the studies in activity recognition using Thermal Array Sensors require human detection techniques to recognize humans passing in the sensor field of view. This paper aims to improve the accuracy of the algorithms used so far by considering the temperature environment variation. This method leverages an adaptive background estimation and a noise removal technique based on Kalman Filter. In order to properly validate the system, a novel installation of a single sensor has been implemented in a smart environment: the obtained results show an improvement in human detection accuracy with respect to the state of the art, especially in case of disturbed environments.展开更多
Non-equilibrium thermal and biothermal radiation generated by heated solid materials and hematothermal living organisms are studied by water conductometric sensors. Engineering aspects and physical features of develop...Non-equilibrium thermal and biothermal radiation generated by heated solid materials and hematothermal living organisms are studied by water conductometric sensors. Engineering aspects and physical features of developed water conductometric sensors are given. Procedure and measuring technique are described. Our experiments show the anomalous behavior of water conductivity and associated differential parameters under water heating by biological objects compared with traditional heating sources. Water response to human action strongly depends on psychophysiological and psychoemotional state of the person. Moreover the responses to the action by left and right human hands are substantially different and as a rule are specific to the gender. The possible physicochemical mechanisms of such anomalous water behavior are studied. It is suggested that the observed effects are associated with resonant excitation of vibration-rotation energy levels of water under the influence of bioradiation generated by human organism consisting of approximately 70% water. The results obtained have good perspectives for future applications in different fields of human activity.展开更多
文摘Security incidents affecting information systems in cyberspace keep on rising. Researchers have raised interest in finding out how to manage security incidents. Various solutions proposed do not effectively address the problematic situation of security incidents. The study proposes a human sensor web Crowd sourcing platform for reporting, searching, querying, analyzing, visualizing and responding to security incidents as they arise in real time. Human sensor web Crowd sourcing security incidents is an innovative approach for addressing security incidents affecting information systems in cyberspace. It employs outsourcing collaborative efforts initiatives outside the boundaries of the given organization in solving a problematic situation such as how to improve the security of information systems. It was managed by soft systems methodology. Moreover, security maturity level assessment was carried out to determine security requirements for managing security incidents using ISO/IEC 21827: Systems security engineering capability maturity model with a rating scale of 0 - 5. It employed descriptive statistics and non-parametric statistical method to determine the significance of each variable based on a research problem. It used Chi-Square Goodness of Fit Test (X2) to determine the statistical significance of result findings. The findings revealed that security controls and security measures are implemented in ad-hoc. For managing security incidents, organizations should use human sensor web Crowd sourcing platform. The study contributes to knowledge base management learning integration: practical implementation of Crowd sourcing in information systems security.
文摘Human Activity Recognition (HAR) is an important way for lower limb exoskeleton robots to implement human-computer collaboration with users. Most of the existing methods in this field focus on a simple scenario recognizing activities for specific users, which does not consider the individual differences among users and cannot adapt to new users. In order to improve the generalization ability of HAR model, this paper proposes a novel method that combines the theories in transfer learning and active learning to mitigate the cross-subject issue, so that it can enable lower limb exoskeleton robots being used in more complex scenarios. First, a neural network based on convolutional neural networks (CNN) is designed, which can extract temporal and spatial features from sensor signals collected from different parts of human body. It can recognize human activities with high accuracy after trained by labeled data. Second, in order to improve the cross-subject adaptation ability of the pre-trained model, we design a cross-subject HAR algorithm based on sparse interrogation and label propagation. Through leave-one-subject-out validation on two widely-used public datasets with existing methods, our method achieves average accuracies of 91.77% on DSAD and 80.97% on PAMAP2, respectively. The experimental results demonstrate the potential of implementing cross-subject HAR for lower limb exoskeleton robots.
基金the research council of Gachsaran Branch, Islamic Azad University, Iran for supporting this project under Grant no. 25518
文摘In this work, an electrochemical sensor was fabricated for determination of an anthracycline, doxorubicin(DOX) as a chemotherapy drug in plasma based on multi-walled carbon nanotubes modified platinum electrode(Pt/MWCNTs). DOX was effectively accumulated on the surface of modified electrode and generated a pair of redox peaks at around 0.522 and 0.647 V(vs. Ag/Ag Cl) in Britton Robinson(B-R) buffer(p H 4.0, 0.1 M). The electrochemical parameters including p H, type of buffer, accumulation time, amount of modifier and scan rate were optimized. Under the optimized conditions, there was a linear correlation between cathodic peak current and concentration of DOX in the range of 0.05–4.0 μg/m L with the detection limit of 0.002 μg/m L. The number of electron transfers(n) and electron transfer-coefficient(α) were estimated as 2.0 and 0.25, respectively. The constructed sensor displayed excellent precision, sensitivity, repeatability and selectivity in the determination of DOX in plasma. Moreover, cyclic voltammetry studies of DOX in the presence of DNA showed an intercalation mechanism with binding constant(K_b) of 1.12×10~5L/mol.
文摘Low Resolution Thermal Array Sensors are widely used in several applications in indoor environments. In particular, one of these cheap, small and unobtrusive sensors provides a low-resolution thermal image of the environment and, unlike cameras;it is capable to detect human heat emission even in dark rooms. The obtained thermal data can be used to monitor older seniors while they are performing daily activities at home, to detect critical situations such as falls. Most of the studies in activity recognition using Thermal Array Sensors require human detection techniques to recognize humans passing in the sensor field of view. This paper aims to improve the accuracy of the algorithms used so far by considering the temperature environment variation. This method leverages an adaptive background estimation and a noise removal technique based on Kalman Filter. In order to properly validate the system, a novel installation of a single sensor has been implemented in a smart environment: the obtained results show an improvement in human detection accuracy with respect to the state of the art, especially in case of disturbed environments.
文摘Non-equilibrium thermal and biothermal radiation generated by heated solid materials and hematothermal living organisms are studied by water conductometric sensors. Engineering aspects and physical features of developed water conductometric sensors are given. Procedure and measuring technique are described. Our experiments show the anomalous behavior of water conductivity and associated differential parameters under water heating by biological objects compared with traditional heating sources. Water response to human action strongly depends on psychophysiological and psychoemotional state of the person. Moreover the responses to the action by left and right human hands are substantially different and as a rule are specific to the gender. The possible physicochemical mechanisms of such anomalous water behavior are studied. It is suggested that the observed effects are associated with resonant excitation of vibration-rotation energy levels of water under the influence of bioradiation generated by human organism consisting of approximately 70% water. The results obtained have good perspectives for future applications in different fields of human activity.
