{"title":"Single Image 3D Beard Face Reconstruction Approaches","authors":"Hafiz Muhammad Umair Munir, W. S. Qureshi","doi":"10.4018/ijcps.314572","DOIUrl":"https://doi.org/10.4018/ijcps.314572","url":null,"abstract":"3D face and 3D hair reconstruction are interesting and emerging applications within the fields of computer vision, computer graphics, and cyber-physical systems. It is a difficult and challenging task to reconstruct the 3D facial model and 3D facial hair from a single photo due to arbitrary poses, facial beard, non-uniform illumination, expressions, and occlusions. Detailed 3D facial models are difficult to reconstruct because every algorithm has some limitations related to profile view, beard face, fine detail, accuracy, and robustness. The major problem is to develop 3D face with texture of large, beard, and wild poses. Mostly algorithms use convolution neural networks and deep learning frameworks to develop 3D face and 3D hair. The latest and state-of-the-art 3D facial reconstruction and 3D face hair approaches are described. Different issues, problems regarding 3D facial reconstruction, and their proposed solutions have been discussed.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133774714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Applied Holistic Mathematical Models for Dynamic Systems (AHMM4DS)","authors":"A. Trad","doi":"10.4018/ijcps.2021010101","DOIUrl":"https://doi.org/10.4018/ijcps.2021010101","url":null,"abstract":"In this article, the author presents the applied holistic mathematical model for the support of dynamic system (AHMM4DS) transformation and integration processes. The AHMM4DS is based on a mixed research method that is supported by a mainly a qualitative research approach, where the main goal is to insure a strategic business competitive advantage. The AHMM4DS uses a natural programming language (NLP) and factors to support a central reasoning engine and a distributed enterprise architecture project's (EAP) concept. This article's proof of concept (PoC) presents the transformation of a dynamic systems, where the central point is the transformation of their services. A DS is managed by a transformation manager, who uses a methodology and a framework that can support and estimate the risks of implementation of a transformation process. Then he uses it to solve various types of problems. The manager is also responsible for the implementation of the DS, and during its implementation phase a transformation framework is needed.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117260369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Shared Cybersecurity Risk Management in the Industry of Medical Devices","authors":"Maria Lai-Ling Lam, Kei-Wing Wong","doi":"10.4018/ijcps.2021010103","DOIUrl":"https://doi.org/10.4018/ijcps.2021010103","url":null,"abstract":"The cybersecurity capabilities of Class 1 medical devices must be seriously addressed when the industry moves toward Industry 4.0. Many U.S. manufacturers are not committed to cybersecurity risk management because they pursue lower cost and shorter product life cycles, do not have sufficient knowledge of operating environments of hospitals, have defensive attitudes toward vulnerability disclosure, and reap quick benefits from the low-trust level among stakeholders and the unequal power between manufacturers and distributors. Only a few large U.S. manufacturers of medical devices have set up robust secure platforms and interoperable optimal standards that can elevate the security practices of entire global supply chain of Class 1 devices. Many small and medium-sized enterprises inside and outside the U.S. need to be equipped to co-foster cybersecurity values with large manufacturers through the coordination between government and industry regulations and the support of international organizations and local government policies.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"03 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127163566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Patricia G. Foley, Kathleen M. Hargiss, Caroline Howard, Anne Pesanvento
{"title":"Security Measures in IoT Devices, Including Wireless Medical Devices: Factors Influencing the Adoption of Effective Security Measures","authors":"Patricia G. Foley, Kathleen M. Hargiss, Caroline Howard, Anne Pesanvento","doi":"10.4018/ijcps.2021010102","DOIUrl":"https://doi.org/10.4018/ijcps.2021010102","url":null,"abstract":"The exponential growth in global adoption of the internet of things (IoT) has resulted in increasing challenges to secure devices against the rapid escalation of malicious users and external attacks. Security of IoT devices is particularly critical in the medical sector, where data breaches have become common in recent years at healthcare facilities, medical laboratories, and medical insurance companies. The phenomenological study focused on the experiences of users of IoT devices and the adoption of effective security measures in IoT devices, especially wireless medical devices. The results from this research study indicated that there was a need for policymakers to be more aware of the security issues that plague some IoT devices, including the need for training to detect potential breaches and cybersecurity aberrations, improved features for protection of devices, and better password security. The study concludes with recommendations for policymakers and device manufacturers.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131020676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modern Subsampling Methods for Large-Scale Least Squares Regression","authors":"Tao Li, Cheng Meng","doi":"10.4018/IJCPS.2020070101","DOIUrl":"https://doi.org/10.4018/IJCPS.2020070101","url":null,"abstract":"Subsampling methods aim to select a subsample as a surrogate for the observed sample. As a powerful technique for large-scale data analysis, various subsampling methods are developed for more effective coefficient estimation and model prediction. This review presents some cutting-edge subsampling methods based on the large-scale least squares estimation. Two major families of subsampling methods are introduced: the randomized subsampling approach and the optimal subsampling approach. The former aims to develop a more effective data-dependent sampling probability while the latter aims to select a deterministic subsample in accordance with certain optimality criteria. Real data examples are provided to compare these methods empirically, respecting both the estimation accuracy and the computing time.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123376215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Credit Risk Assessment of Internet Financial Platforms Based on BP Neural Network","authors":"Yu Yuan, Yue Yang","doi":"10.4018/IJCPS.2020070102","DOIUrl":"https://doi.org/10.4018/IJCPS.2020070102","url":null,"abstract":"Aiming at the problem of credit risk, this paper selects key data indicators to establish an index system combining with the factors affecting the credit risk of the platform. Python crawler software was used to obtain relevant data of net lending platforms, and the crawled data of more than 1000 platforms were preprocessed. Ninety-five platforms with complete data were selected to build a BP neural network risk assessment model. The BP neural network model is used to make an empirical analysis of the risks of online lending platforms by using the data obtained, and the evaluation method of this paper is compared with the rating method of online lending sky eye. The empirical results show that the error of BP neural network can be stable at about 0.5, and the accuracy rate of evaluation is as high as 95.45%, which is much higher than the accuracy rate of 44.21% of net loan platform. This paper provides decision support for the credit risk early warning of net loan platform.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126666852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fuzzy Control in Cyber-Physical Systems","authors":"M. Voskoglou","doi":"10.4018/IJCPS.2020070103","DOIUrl":"https://doi.org/10.4018/IJCPS.2020070103","url":null,"abstract":"Controllers are devices regulating the operation of other devices or systems. Fuzzy controllers analyze the input data in terms of variables which take on continuous values in the interval [0, 1]. Since fuzzy logic has the advantage of expressing the solution of the problems in the natural language, the use of fuzzy instead of traditional controllers makes easier the mechanization of tasks that have been already successfully performed by humans. In the present paper a theoretical fuzzy control model is developed for the braking system of autonomous vehicles, which are included among the most characteristic examples of Cyber-Physical Systems. For this, a simple geometric approach is followed using triangular fuzzy numbers as the basic tools.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126401747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Architectural Modelling of Cyber Physical Systems Using UML","authors":"K. Sridhar Patnaik, I. Snigdh","doi":"10.4018/ijcps.2019070102","DOIUrl":"https://doi.org/10.4018/ijcps.2019070102","url":null,"abstract":"Cyber-physical systems (CPS) is an exciting emerging research area that has drawn the attention of many researchers. However, the difficulties of computing and physical paradigm introduce a lot of trials while developing CPS, such as incorporation of heterogeneous physical entities, system verification, security assurance, and so on. A common or unified architecture plays an important role in the process of CPS design. This article introduces the architectural modeling representation of CPS. The layers of models are integrated from high level to lower level to get the general Meta model. Architecture captures the essential attributes of a CPS. Despite the rapid growth in IoT and CPS a general principled modeling approach for the systematic development of these new engineering systems is still missing. System modeling is one of the important aspects of developing abstract models of a system wherein, each model represents a different view or perspective of that system. With Unified Modeling Language (UML), the graphical analogy of such complex systems can be successfully presented.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133508263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
J. SowmyaB., Chetan Shetty, S. Seema, K. Srinivasa
{"title":"An Image Processing and Machine Learning Approach for Early Detection of Diseased Leaves","authors":"J. SowmyaB., Chetan Shetty, S. Seema, K. Srinivasa","doi":"10.4018/ijcps.2019070104","DOIUrl":"https://doi.org/10.4018/ijcps.2019070104","url":null,"abstract":"India is largely an agriculture dependent country. It contributes to almost 17% of the GDP. A wide range of crops are grown throughout the year. Extensive cultivation also makes the plants prone to a lot of diseases. There are no efficient methods to detect these diseases from its outset. People in the rural areas where most of the agriculture happens are totally helpless in situations where most of their crops have been affected by disease. Most of the diseases that plague plants leave a characteristic feature on the leaf. By applying image processing techniques like image enhancement and feature extraction one can extract the required information required to analyze the type and severity of the disease. The obtained information when fed to a classifier like support vector machine (SVM), the plant can be classified to be affected by a certain disease. One can also determine the stage of the disease (infant or mid or terminal). Crop diseases impact the livelihood of those involved in agriculture immensely. Consumption of such produce also affects the health of humans and animals. Manually monitoring these diseases requires a lot of time and expertise. Hence, utilizing image processing for the detection of diseases is a better option. It takes into consideration the features which may not be determined visually. Consider the example of tomato crop in India which is prone to a number of diseases caused by pathogens, bacteria, viruses, and phytoplasmas-like organisms. Due to this disease the framers incur a huge loss. To overcome this problem a lot research is being conducted using image processing and neural network model for automatic detection of diseases using drone technology.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127679521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fractional Order PIλDµ Control Design for a Class of Cyber-Physical Systems with Fractional Order Time-Delay models: Fractional PIλDµ Design for CPS with Time-Delay models","authors":"Marwa Boudana, S. Ladaci, Jean-Jacques Loiseau","doi":"10.4018/ijcps.2019070101","DOIUrl":"https://doi.org/10.4018/ijcps.2019070101","url":null,"abstract":"The control of cyber-physical systems (CPS) is a great challenge for researchers in control theory and engineering mainly because of delays induced by merging computation, communication, and control of physical processes. Consequently, control solutions for time-delay systems can be applied efficiently for many CPS system configurations. In this article, a fractional order PIλ and PIλDµ control design is investigated for a class of fractional order time-delay systems. The proposed control design approach is simple and efficient. The controller parameter's adjustment is achieved in two steps: first, the relay approach is used to compute satisfactory classical PID coefficients, namely kp, Ti and Td. Then, the fractional orders λ and µ are optimized using performance criteria. Simulation results show the efficiency of the proposed design technique and its ability to enhance the PID control performance.","PeriodicalId":198135,"journal":{"name":"Int. J. Cyber Phys. Syst.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123196420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}