Cyberspace is extremely dynamic,with new attacks arising daily.Protecting cybersecurity controls is vital for network security.Deep Learning(DL)models find widespread use across various fields,with cybersecurity being...Cyberspace is extremely dynamic,with new attacks arising daily.Protecting cybersecurity controls is vital for network security.Deep Learning(DL)models find widespread use across various fields,with cybersecurity being one of the most crucial due to their rapid cyberattack detection capabilities on networks and hosts.The capabilities of DL in feature learning and analyzing extensive data volumes lead to the recognition of network traffic patterns.This study presents novel lightweight DL models,known as Cybernet models,for the detection and recognition of various cyber Distributed Denial of Service(DDoS)attacks.These models were constructed to have a reasonable number of learnable parameters,i.e.,less than 225,000,hence the name“lightweight.”This not only helps reduce the number of computations required but also results in faster training and inference times.Additionally,these models were designed to extract features in parallel from 1D Convolutional Neural Networks(CNN)and Long Short-Term Memory(LSTM),which makes them unique compared to earlier existing architectures and results in better performance measures.To validate their robustness and effectiveness,they were tested on the CIC-DDoS2019 dataset,which is an imbalanced and large dataset that contains different types of DDoS attacks.Experimental results revealed that bothmodels yielded promising results,with 99.99% for the detectionmodel and 99.76% for the recognition model in terms of accuracy,precision,recall,and F1 score.Furthermore,they outperformed the existing state-of-the-art models proposed for the same task.Thus,the proposed models can be used in cyber security research domains to successfully identify different types of attacks with a high detection and recognition rate.展开更多
In this paper, to effectively treat chronic disorders and improve the standard of care, effective communication between patients and healthcare professionals was essential. The aim of the study was to review the liter...In this paper, to effectively treat chronic disorders and improve the standard of care, effective communication between patients and healthcare professionals was essential. The aim of the study was to review the literature on how good communication might improve treatment outcomes for Kenyan patients with chronic and terminal illnesses and to determine whether Cybernetic electronic communication can improve those outcomes even more. We uncovered the history of treatment outcomes for chronic and terminal diseases in this research study, both with and without communication at the core of the patient’s care plan. We discussed the importance of good communication in the treatment of patients with chronic and terminal illnesses and why it is a momentous endeavor comparable to medical diagnosis and treatment for the long-term health of patients. To locate pertinent material for the background literature study, we carried out a comprehensive literature search. Although the preliminary literature review was a continuation of the introduction research, it also highlighted the paucity of local Kenyan literature and suggested that improved communication might help patients with chronic and terminal illnesses have better treatment outcome. Methodology maintained the literature search, as a systematic literature review focused on core of the study, making separate sections of the same body necessary. This ensured that a methodological literature search section is as comprehensive as possible. We used an integrated PRISM model to limit a comprehensive literature search and a systematic literature review design as part of the overall process. Non-probability sampling and snowball approaches on literary papers over the previous 17 years were used in this arrangement. Since this was a multidisciplinary study, the four experts who also serve as authors were chosen from within their respective fields of expertise to design the study. They created search strategies, generated key words, looked up keywords in database engines, assessed the results of the literature using the PRISMA logical model, looked over successful literature, and triangulated their findings. The conclusions of the experts individually revealed a convergence of thoughts, beliefs, and practices across. The study concluded that even though there isn’t much research done in Kenya on the same subject;what is available illustrates how crucial good communication is for patients with chronic illnesses. The study’s findings also highlighted the positive effects of effective communication between patients and healthcare professionals on treatment plan adherence, patient satisfaction, and overall health outcomes. The results also noted that in order to improve patient care and outcome, Kenyan healthcare workers should underscore developing their communication skills. The study also found that the incorporation of cybernetics is crucial if a truly effective communication is required so as to enable centered care for patients with long-term diseases in Kenya. The goal of the Cybernetics is to activate genuinely effective communication in the care of Patients with long-term disease in Kenya. This study is organized to begin with an abstract, followed by keywords, an introduction, literature review, methodology, findings, discussion, and finally conclusions.展开更多
Over the course of the past 70 years, the objectives of CA （cellular automata） research shifted from speculative and illustrative purposes without immediate goals outside of given implementations to the more utilita...Over the course of the past 70 years, the objectives of CA （cellular automata） research shifted from speculative and illustrative purposes without immediate goals outside of given implementations to the more utilitarian scientific and engineering objectives of simulating, controlling and predicting other phenomena. Looking back at our own 10-year history of CA related work, however, we recognize a generally inverse tendency from utilitarian objectives to finding more illustrative and speculative value. In this paper, we present a reflection on our own body of CA work, and we discuss the qualities of the various outcomes and insights we gained from a second-order cybernetic perspective. We argue that much of our own CA work may best be understood as creating machines for showing and for repurposing that allow their observers to gain new （second-order cybernetic） ways of seeing from interacting with them.展开更多
The landmark book of Hsue-Shen Tsien, ＇Engineering Cybernetics＇, gave birth 60 years ago to an engineering science of interrelations and synthetic behaviors. Clothing the bare bones of Norbert Wiener＇s conception o...The landmark book of Hsue-Shen Tsien, ＇Engineering Cybernetics＇, gave birth 60 years ago to an engineering science of interrelations and synthetic behaviors. Clothing the bare bones of Norbert Wiener＇s conception of cybernetics, the book delineates for the new science the requirement （of having direct impacts on engineering applications）, the aim （of encapsulating engLneering principles and concepts）, the problems （of analysis, design, and uncertainty）, the tools （of basic and advanced mathematics）, and the scope （systems that are single input and output or multiple input and output, linear or nonlinear, deterministic or stochastic）. The book is a showcase of originality, critical thinking and foresights. In particular, the author calls into question the basic assumption that ＇the properties and characteristics of the system to be controlled were always assumed to be known＇ and points out that, in reality, ＇large unpredictable variations of the system properties may occur＇. Sixty years later, the full spectrum of Tsien＇s prophetic ideas is yet to be fully grasped and engineering cybernetics, as Tsien envisioned, is still in the making.展开更多
Software cybernetics explores the interplay between control theory/engineering and software theory/engineering. The controlled Markov chains (CMC) approach to software testing follows the idea of software cybernetics ...Software cybernetics explores the interplay between control theory/engineering and software theory/engineering. The controlled Markov chains (CMC) approach to software testing follows the idea of software cybernetics and treats software testing as a control problem. The software under test serves as a controlled object and the software testing strategy serves as the corresponding controller. The software under test and the software testing strategy make up a closed-loop feedback control system, and the theory of controlled Markov chains can be used to design and optimize software testing strategies in accordance with testing/reliability goals given a priori. In this paper we apply the CMC approach to the optimal stopping problem of multi-project software testing. The problem under consideration assumes that a single stopping action can stop testing of all the software systems under test simultaneously. The theoretical results presented in this paper describe how to test multiple software systems and when to stop testing in an optimal manner. An illustrative example is used to explain the theoretical results. The study of this paper further justifies the effectiveness of the CMC approach to software testing in particular and the idea of software cybernetics in general.展开更多
A cybernetics model of manufacturing execution system(MES CM) was proposed and studied from the viewpoint of cybernetics.Combining with the features of manufacturing system, the MES CM was modeled by"generalized ...A cybernetics model of manufacturing execution system(MES CM) was proposed and studied from the viewpoint of cybernetics.Combining with the features of manufacturing system, the MES CM was modeled by"generalized modeling"method that is discussed in large-scale system theory.The mathematical model of MES CM was constructed by the generalized operator model, and the main characteristics of MES CM were analyzed.展开更多
Increasing carbon emissions from large-scale human activities have contributed to global climate change, which has resulted in an increase in significant human crises. Therefore, as carbon abatement is a public good, ...Increasing carbon emissions from large-scale human activities have contributed to global climate change, which has resulted in an increase in significant human crises. Therefore, as carbon abatement is a public good, coping with climate change is also a public-good; however, it suffers from many free-rider incentives, leading to a tragedy of the commons. Overcoming this challenge from a systemic perspective, requires that all sectors such as industry, government, and citizens on global, national, and regional levels engage in low-carbon development and the implementation of fair and efficient climate policies. Through a theoretical exploration of carbon abatement and a systemic description of low-carbon systems, this paper developed a cybernetic framework for coping with climate change, which consists of a cloud platform for data analysis, meta-synthetic engineering for decision support, a polycentric approach to extensive consultation and various functional goal achievement modules. On this basis, by combining the ＂invisible hand＂ and ＂visible hand＂ and by integrating negotiation at the global level, cooperation at the national level and knowledge at the local level, a multilevel policymaking model is proposed to address complex climate change problems. This cybernetic paradigm based innovative approach could provide valuable illumination to stakeholders seeking to cope with climate change.展开更多
Background Cervical cancer is a prominent disease in women,with a high mortality rate worldwide.This cancer continues to be a challenge to concisely diagnose,especially in its early stages.The aim of this study was to...Background Cervical cancer is a prominent disease in women,with a high mortality rate worldwide.This cancer continues to be a challenge to concisely diagnose,especially in its early stages.The aim of this study was to pro-pose a unique cybernetic system which showcased the human-machine collaboration forming a superintelligence framework that ultimately allowed for greater clinical care strategies.Methods In this work,we applied machine learning(ML)models on 650 patients’data collected from Hospital Universitario de Caracas in Caracas,Venezuela,where ethical approval and informed consent were granted.The data were hosted at the University of California at Irvine(UCI)database for cancer prediction by using data purely from a patient questionnaire that include key cervical cancer drivers such as questions on sexually transmitted diseases and time since first intercourse in order to design a clinical prediction machine that can predict various stages of cervical cancer.Two contrasting methods are explored in the design of a ML-driven prediction machine in this study,namely,a probabilistic method using Gaussian mixture models(GMM),and fuzziness-based reasoning using the fuzzy c-means(FCM)clustering on the data from 650 patients.Results The models were validated using a K-Fold validation method,and the results show that both meth-ods could be feasibly deployed in a clinical setting,with the probabilistic method(produced accuracies of 80+%/classifier dependent)allowing for more detail in the grading of a potential cervical cancer prediction,albeit at the cost of greater computation power;the FCM approach(produced accuracies around 90+%/classifier dependent)allows for a more parsimonious modelling with a slightly reduced prediction depth in comparison.As part of the novelty of this work,a clinical cybernetic system is also proposed to host the prediction machine,which allows for a human-machine collaborative interaction and an enhanced decision support platform to aug-ment overall care strategies.Conclusion The present study showcased how the use of prediction machines can contribute towards early de-tection and prioritised care of patients with cervical cancer,while also allowing for cost-saving benefits when compared with routine cervical cancer screening.Further work in this area would now involve additional vali-dation of the proposed clinical cybernetic loop and further improvement to the prediction machine by exploring non-linear dimensional embedding and clustering methods.展开更多
文摘Cyberspace is extremely dynamic,with new attacks arising daily.Protecting cybersecurity controls is vital for network security.Deep Learning(DL)models find widespread use across various fields,with cybersecurity being one of the most crucial due to their rapid cyberattack detection capabilities on networks and hosts.The capabilities of DL in feature learning and analyzing extensive data volumes lead to the recognition of network traffic patterns.This study presents novel lightweight DL models,known as Cybernet models,for the detection and recognition of various cyber Distributed Denial of Service(DDoS)attacks.These models were constructed to have a reasonable number of learnable parameters,i.e.,less than 225,000,hence the name“lightweight.”This not only helps reduce the number of computations required but also results in faster training and inference times.Additionally,these models were designed to extract features in parallel from 1D Convolutional Neural Networks(CNN)and Long Short-Term Memory(LSTM),which makes them unique compared to earlier existing architectures and results in better performance measures.To validate their robustness and effectiveness,they were tested on the CIC-DDoS2019 dataset,which is an imbalanced and large dataset that contains different types of DDoS attacks.Experimental results revealed that bothmodels yielded promising results,with 99.99% for the detectionmodel and 99.76% for the recognition model in terms of accuracy,precision,recall,and F1 score.Furthermore,they outperformed the existing state-of-the-art models proposed for the same task.Thus,the proposed models can be used in cyber security research domains to successfully identify different types of attacks with a high detection and recognition rate.
文摘In this paper, to effectively treat chronic disorders and improve the standard of care, effective communication between patients and healthcare professionals was essential. The aim of the study was to review the literature on how good communication might improve treatment outcomes for Kenyan patients with chronic and terminal illnesses and to determine whether Cybernetic electronic communication can improve those outcomes even more. We uncovered the history of treatment outcomes for chronic and terminal diseases in this research study, both with and without communication at the core of the patient’s care plan. We discussed the importance of good communication in the treatment of patients with chronic and terminal illnesses and why it is a momentous endeavor comparable to medical diagnosis and treatment for the long-term health of patients. To locate pertinent material for the background literature study, we carried out a comprehensive literature search. Although the preliminary literature review was a continuation of the introduction research, it also highlighted the paucity of local Kenyan literature and suggested that improved communication might help patients with chronic and terminal illnesses have better treatment outcome. Methodology maintained the literature search, as a systematic literature review focused on core of the study, making separate sections of the same body necessary. This ensured that a methodological literature search section is as comprehensive as possible. We used an integrated PRISM model to limit a comprehensive literature search and a systematic literature review design as part of the overall process. Non-probability sampling and snowball approaches on literary papers over the previous 17 years were used in this arrangement. Since this was a multidisciplinary study, the four experts who also serve as authors were chosen from within their respective fields of expertise to design the study. They created search strategies, generated key words, looked up keywords in database engines, assessed the results of the literature using the PRISMA logical model, looked over successful literature, and triangulated their findings. The conclusions of the experts individually revealed a convergence of thoughts, beliefs, and practices across. The study concluded that even though there isn’t much research done in Kenya on the same subject;what is available illustrates how crucial good communication is for patients with chronic illnesses. The study’s findings also highlighted the positive effects of effective communication between patients and healthcare professionals on treatment plan adherence, patient satisfaction, and overall health outcomes. The results also noted that in order to improve patient care and outcome, Kenyan healthcare workers should underscore developing their communication skills. The study also found that the incorporation of cybernetics is crucial if a truly effective communication is required so as to enable centered care for patients with long-term diseases in Kenya. The goal of the Cybernetics is to activate genuinely effective communication in the care of Patients with long-term disease in Kenya. This study is organized to begin with an abstract, followed by keywords, an introduction, literature review, methodology, findings, discussion, and finally conclusions.
文摘Over the course of the past 70 years, the objectives of CA （cellular automata） research shifted from speculative and illustrative purposes without immediate goals outside of given implementations to the more utilitarian scientific and engineering objectives of simulating, controlling and predicting other phenomena. Looking back at our own 10-year history of CA related work, however, we recognize a generally inverse tendency from utilitarian objectives to finding more illustrative and speculative value. In this paper, we present a reflection on our own body of CA work, and we discuss the qualities of the various outcomes and insights we gained from a second-order cybernetic perspective. We argue that much of our own CA work may best be understood as creating machines for showing and for repurposing that allow their observers to gain new （second-order cybernetic） ways of seeing from interacting with them.
文摘The landmark book of Hsue-Shen Tsien, ＇Engineering Cybernetics＇, gave birth 60 years ago to an engineering science of interrelations and synthetic behaviors. Clothing the bare bones of Norbert Wiener＇s conception of cybernetics, the book delineates for the new science the requirement （of having direct impacts on engineering applications）, the aim （of encapsulating engLneering principles and concepts）, the problems （of analysis, design, and uncertainty）, the tools （of basic and advanced mathematics）, and the scope （systems that are single input and output or multiple input and output, linear or nonlinear, deterministic or stochastic）. The book is a showcase of originality, critical thinking and foresights. In particular, the author calls into question the basic assumption that ＇the properties and characteristics of the system to be controlled were always assumed to be known＇ and points out that, in reality, ＇large unpredictable variations of the system properties may occur＇. Sixty years later, the full spectrum of Tsien＇s prophetic ideas is yet to be fully grasped and engineering cybernetics, as Tsien envisioned, is still in the making.
基金supported by the National Outstanding Youth Foundation of China,the"863"Programme of China and the Aviation Science Foundation of China.
文摘Software cybernetics explores the interplay between control theory/engineering and software theory/engineering. The controlled Markov chains (CMC) approach to software testing follows the idea of software cybernetics and treats software testing as a control problem. The software under test serves as a controlled object and the software testing strategy serves as the corresponding controller. The software under test and the software testing strategy make up a closed-loop feedback control system, and the theory of controlled Markov chains can be used to design and optimize software testing strategies in accordance with testing/reliability goals given a priori. In this paper we apply the CMC approach to the optimal stopping problem of multi-project software testing. The problem under consideration assumes that a single stopping action can stop testing of all the software systems under test simultaneously. The theoretical results presented in this paper describe how to test multiple software systems and when to stop testing in an optimal manner. An illustrative example is used to explain the theoretical results. The study of this paper further justifies the effectiveness of the CMC approach to software testing in particular and the idea of software cybernetics in general.
文摘A cybernetics model of manufacturing execution system(MES CM) was proposed and studied from the viewpoint of cybernetics.Combining with the features of manufacturing system, the MES CM was modeled by"generalized modeling"method that is discussed in large-scale system theory.The mathematical model of MES CM was constructed by the generalized operator model, and the main characteristics of MES CM were analyzed.
文摘Increasing carbon emissions from large-scale human activities have contributed to global climate change, which has resulted in an increase in significant human crises. Therefore, as carbon abatement is a public good, coping with climate change is also a public-good; however, it suffers from many free-rider incentives, leading to a tragedy of the commons. Overcoming this challenge from a systemic perspective, requires that all sectors such as industry, government, and citizens on global, national, and regional levels engage in low-carbon development and the implementation of fair and efficient climate policies. Through a theoretical exploration of carbon abatement and a systemic description of low-carbon systems, this paper developed a cybernetic framework for coping with climate change, which consists of a cloud platform for data analysis, meta-synthetic engineering for decision support, a polycentric approach to extensive consultation and various functional goal achievement modules. On this basis, by combining the ＂invisible hand＂ and ＂visible hand＂ and by integrating negotiation at the global level, cooperation at the national level and knowledge at the local level, a multilevel policymaking model is proposed to address complex climate change problems. This cybernetic paradigm based innovative approach could provide valuable illumination to stakeholders seeking to cope with climate change.
文摘Background Cervical cancer is a prominent disease in women,with a high mortality rate worldwide.This cancer continues to be a challenge to concisely diagnose,especially in its early stages.The aim of this study was to pro-pose a unique cybernetic system which showcased the human-machine collaboration forming a superintelligence framework that ultimately allowed for greater clinical care strategies.Methods In this work,we applied machine learning(ML)models on 650 patients’data collected from Hospital Universitario de Caracas in Caracas,Venezuela,where ethical approval and informed consent were granted.The data were hosted at the University of California at Irvine(UCI)database for cancer prediction by using data purely from a patient questionnaire that include key cervical cancer drivers such as questions on sexually transmitted diseases and time since first intercourse in order to design a clinical prediction machine that can predict various stages of cervical cancer.Two contrasting methods are explored in the design of a ML-driven prediction machine in this study,namely,a probabilistic method using Gaussian mixture models(GMM),and fuzziness-based reasoning using the fuzzy c-means(FCM)clustering on the data from 650 patients.Results The models were validated using a K-Fold validation method,and the results show that both meth-ods could be feasibly deployed in a clinical setting,with the probabilistic method(produced accuracies of 80+%/classifier dependent)allowing for more detail in the grading of a potential cervical cancer prediction,albeit at the cost of greater computation power;the FCM approach(produced accuracies around 90+%/classifier dependent)allows for a more parsimonious modelling with a slightly reduced prediction depth in comparison.As part of the novelty of this work,a clinical cybernetic system is also proposed to host the prediction machine,which allows for a human-machine collaborative interaction and an enhanced decision support platform to aug-ment overall care strategies.Conclusion The present study showcased how the use of prediction machines can contribute towards early de-tection and prioritised care of patients with cervical cancer,while also allowing for cost-saving benefits when compared with routine cervical cancer screening.Further work in this area would now involve additional vali-dation of the proposed clinical cybernetic loop and further improvement to the prediction machine by exploring non-linear dimensional embedding and clustering methods.
