Pub Date : 2022-01-01DOI: 10.13052/jicts2245-800X.1034
Woongsik Kim
As the life expectancy of human increases, having a long and healthy life, Well-Aging, Wellness, and Anti-Aging become more important. There is a paradigm shift from diagnosis and treatment in the healthcare field to prognosis and prevention in daily life. The human part with the most capillary blood vessels is the inside of human eyes or the fundus oculi. These capillary blood vessels show characteristic changes prior to chronic diseases such as diabetes or hypertension. In this study, a system is being developed to regularly collect data from the user, convert them into a database, and analyze to inform and warn any characteristic changes to users as they occur, such that users can proactively take care of their own eyes.
{"title":"The Implementation of Ocular Health Service System Using Android Platform","authors":"Woongsik Kim","doi":"10.13052/jicts2245-800X.1034","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1034","url":null,"abstract":"As the life expectancy of human increases, having a long and healthy life, Well-Aging, Wellness, and Anti-Aging become more important. There is a paradigm shift from diagnosis and treatment in the healthcare field to prognosis and prevention in daily life. The human part with the most capillary blood vessels is the inside of human eyes or the fundus oculi. These capillary blood vessels show characteristic changes prior to chronic diseases such as diabetes or hypertension. In this study, a system is being developed to regularly collect data from the user, convert them into a database, and analyze to inform and warn any characteristic changes to users as they occur, such that users can proactively take care of their own eyes.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 3","pages":"427-437"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255395/10255418.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68169375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.13052/jicts2245-800X.1015
Aaloka Anant;Ramjee Prasad
Privacy becomes the most important topic as user's data gets more and more widely used and exchanged across internet. Edge devices are replacing traditional monitoring and maintenance strategy for daily used items in households as well as industrial establishments. The usage of technology is getting more and more pervasive. 6G further increases the importance of edge devices in a network as network speeds increase, making the edge device much more powerful element in the network. Edge devices would have massive store and exchange of personal data of the individual. Data privacy forms the primary requirement for accessing data of individuals. Paper presents a novel concept on combination of techniques including cryptography, randomization, pseudonymization and others to achieve anonymization. It investigates in detail how the privacy relevant data of individuals can be protected as well as made relevant for research. It arrives at an interesting and unique approach for privacy preservation on edge devices opening up new business opportunities and make the data subject in charge of their data.
{"title":"Privacy Preservation for Enterprises Data in Edge Devices","authors":"Aaloka Anant;Ramjee Prasad","doi":"10.13052/jicts2245-800X.1015","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1015","url":null,"abstract":"Privacy becomes the most important topic as user's data gets more and more widely used and exchanged across internet. Edge devices are replacing traditional monitoring and maintenance strategy for daily used items in households as well as industrial establishments. The usage of technology is getting more and more pervasive. 6G further increases the importance of edge devices in a network as network speeds increase, making the edge device much more powerful element in the network. Edge devices would have massive store and exchange of personal data of the individual. Data privacy forms the primary requirement for accessing data of individuals. Paper presents a novel concept on combination of techniques including cryptography, randomization, pseudonymization and others to achieve anonymization. It investigates in detail how the privacy relevant data of individuals can be protected as well as made relevant for research. It arrives at an interesting and unique approach for privacy preservation on edge devices opening up new business opportunities and make the data subject in charge of their data.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 1","pages":"85-104"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255387/10255388.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68134611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.13052/jicts2245-800X.1025
Mohammad Zubair Khan;R. Mangayarkarasi;C. Vanmathi;M. Angulakshmi
A high level of glucose in the blood over a long period creates diabetes disease. Undiagnosed diabetes may trigger other complications such as cardiovascular disease, nerve damage, renal failure, and so on. There are many factors age, blood pressure, food habits, lifestyle changes are some of the reasons for diabetes. With increasing cases of diabetes in the smart Internet world, there is a need for an automated prediction system to facilitate the patients, to get know, whether they are affected by the disease or not. There are many diabetes prediction software that is already in use, still, the accurateness of a diabetes prediction is not complete. This paper presents a robust framework (PSO-NNDP), employs a novel hybrid feature selector to improvise the neural-based diabetes prediction system. The novel hybrid feature selector presented in this paper comprises the merits of the correlation coefficient, F-score, and particle swarm optimization methods to influence the feature selection process. The reliability of the proposed framework has been experimented on the benchmarking dataset. By establishing the clear steps, for the replacement of missing values, removal of outliers, the proposed framework obtains 99.5% accuracy. Moreover, the experimented machine learning models also show a great improvement upon the usage of the proposed feature selector.
{"title":"Bio-Inspired PSO for Improving Neural Based Diabetes Prediction System","authors":"Mohammad Zubair Khan;R. Mangayarkarasi;C. Vanmathi;M. Angulakshmi","doi":"10.13052/jicts2245-800X.1025","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1025","url":null,"abstract":"A high level of glucose in the blood over a long period creates diabetes disease. Undiagnosed diabetes may trigger other complications such as cardiovascular disease, nerve damage, renal failure, and so on. There are many factors age, blood pressure, food habits, lifestyle changes are some of the reasons for diabetes. With increasing cases of diabetes in the smart Internet world, there is a need for an automated prediction system to facilitate the patients, to get know, whether they are affected by the disease or not. There are many diabetes prediction software that is already in use, still, the accurateness of a diabetes prediction is not complete. This paper presents a robust framework (PSO-NNDP), employs a novel hybrid feature selector to improvise the neural-based diabetes prediction system. The novel hybrid feature selector presented in this paper comprises the merits of the correlation coefficient, F-score, and particle swarm optimization methods to influence the feature selection process. The reliability of the proposed framework has been experimented on the benchmarking dataset. By establishing the clear steps, for the replacement of missing values, removal of outliers, the proposed framework obtains 99.5% accuracy. Moreover, the experimented machine learning models also show a great improvement upon the usage of the proposed feature selector.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"179-199"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10254730.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.13052/jicts2245-800X.1044
Zhendong Feng;Wei Liu;Yinghuai Yu
With the rapid popularization and development of smart phones and other technological devices, pictures have become the main media for people to record information. However, the traditional mobile photo album has many problems. First of all, with the development of the times, the higher the pixel of the image, the larger the memory required. Obviously, the traditional file storage structure can no longer meet the storage of users' massive photos. Secondly, people store a large number of face images in mobile phones, so there is a strong demand for face recognition and classification management based on different faces. Third, in the face of the management of massive photos, general image recognition and classification is also a very demanding function. In response to the call of “deeply implementing the digital economy strategy” in today's era, our team makes full use of the functions of the cloud platform and a large number of industrial resources, and integrates independent optimization algorithms to develop an intelligent cloud album management system that realizes intellectualization and application innovation. SE-ResNeXt algorithm is the core algorithm of this system, which can recognize and extract effective information from massive images in various application scenarios, and help users to intelligently and automatically classify and manage images according to different contents. This paper deeply studies the Intelligent Cloud album management system based on SE-ResNeXt. The system is built by nginx+uwsgi+django+vue as a whole. It has the functions of intelligent classification, face recognition, cloud storage and so on. It aims to provide users with simpler, more intimate and more intelligent album management services.
{"title":"Smart Album Management System Based on SE-ResNeXt","authors":"Zhendong Feng;Wei Liu;Yinghuai Yu","doi":"10.13052/jicts2245-800X.1044","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1044","url":null,"abstract":"With the rapid popularization and development of smart phones and other technological devices, pictures have become the main media for people to record information. However, the traditional mobile photo album has many problems. First of all, with the development of the times, the higher the pixel of the image, the larger the memory required. Obviously, the traditional file storage structure can no longer meet the storage of users' massive photos. Secondly, people store a large number of face images in mobile phones, so there is a strong demand for face recognition and classification management based on different faces. Third, in the face of the management of massive photos, general image recognition and classification is also a very demanding function. In response to the call of “deeply implementing the digital economy strategy” in today's era, our team makes full use of the functions of the cloud platform and a large number of industrial resources, and integrates independent optimization algorithms to develop an intelligent cloud album management system that realizes intellectualization and application innovation. SE-ResNeXt algorithm is the core algorithm of this system, which can recognize and extract effective information from massive images in various application scenarios, and help users to intelligently and automatically classify and manage images according to different contents. This paper deeply studies the Intelligent Cloud album management system based on SE-ResNeXt. The system is built by nginx+uwsgi+django+vue as a whole. It has the functions of intelligent classification, face recognition, cloud storage and so on. It aims to provide users with simpler, more intimate and more intelligent album management services.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 4","pages":"563-582"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254731/10254732.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68009004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.13052/jicts2245-800X.10211
Nguyen Viet Lam;Bui Huy Khoi
The paper was conducted to understand the factors affecting the student's learning location. The official study carried out an online survey through Google forms using a questionnaire with the participation of 125 samples. The Bayesian Model Selection shows that 03 factors are affecting student studying location (SSL), which are Students' perception (PP), Price perception (PRI), Perception of universities in a big city (UNI). From the results, we have proposed many implications for improving student learning. This study uses the optimal choice of Bayesian Model Selection for the student learning location. Students' perceptions (PP), price perceptions (PRI), and university perceptions in big cities (UNI) all have a 97.1 percent impact on student studying places (SSL). Model 1 is the best option by BIC, and four variables have a probability of 100%.
{"title":"Bayesian Model Average for Student Learning Location","authors":"Nguyen Viet Lam;Bui Huy Khoi","doi":"10.13052/jicts2245-800X.10211","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.10211","url":null,"abstract":"The paper was conducted to understand the factors affecting the student's learning location. The official study carried out an online survey through Google forms using a questionnaire with the participation of 125 samples. The Bayesian Model Selection shows that 03 factors are affecting student studying location (SSL), which are Students' perception (PP), Price perception (PRI), Perception of universities in a big city (UNI). From the results, we have proposed many implications for improving student learning. This study uses the optimal choice of Bayesian Model Selection for the student learning location. Students' perceptions (PP), price perceptions (PRI), and university perceptions in big cities (UNI) all have a 97.1 percent impact on student studying places (SSL). Model 1 is the best option by BIC, and four variables have a probability of 100%.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"305-317"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10255436.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.13052/jicts2245-800X.1024
A. Dalvin Vinoth Kumar
Diabetes is a one of the major issue that all people in the world currently face. Diabetes is caused by excessive amounts of sugar in the blood. Once diabetes is diagnosed, it is not completely curable, but it can be controlled with proper medication, exercise and a balanced diet. Diabetes affects the vital organs of the body such as the heart, kidneys, brain and eyes. The diabetes mellitus and its complications can be determined using a variety of pathological tests, such as patients' symptoms and blood sugar, urine and lipid profile. The use of fuzzy logic in diagnosis is very common and useful because it combines the knowledge and experience of the physician into ambiguous sets and rules. Most of the researchers proposed methods to diagnosis the diabetes mellitus but still it in their infancy level. This work proposed a fuzzy based system for diagnosing diabetes disease. The usage of pesticides in agriculture by farmers is treated as one of the dependent variable for predication. The empirical zif's law is used to compute the frequency of farmers using pesticides are predicated as diabetic. The output of the proposed system proved that the fuzzy based prediction model diagnosis the disease accurately.
{"title":"Fuzzy Based Predication Technique for Diabetics Association Analysis for Salem District Farmers","authors":"A. Dalvin Vinoth Kumar","doi":"10.13052/jicts2245-800X.1024","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1024","url":null,"abstract":"Diabetes is a one of the major issue that all people in the world currently face. Diabetes is caused by excessive amounts of sugar in the blood. Once diabetes is diagnosed, it is not completely curable, but it can be controlled with proper medication, exercise and a balanced diet. Diabetes affects the vital organs of the body such as the heart, kidneys, brain and eyes. The diabetes mellitus and its complications can be determined using a variety of pathological tests, such as patients' symptoms and blood sugar, urine and lipid profile. The use of fuzzy logic in diagnosis is very common and useful because it combines the knowledge and experience of the physician into ambiguous sets and rules. Most of the researchers proposed methods to diagnosis the diabetes mellitus but still it in their infancy level. This work proposed a fuzzy based system for diagnosing diabetes disease. The usage of pesticides in agriculture by farmers is treated as one of the dependent variable for predication. The empirical zif's law is used to compute the frequency of farmers using pesticides are predicated as diabetic. The output of the proposed system proved that the fuzzy based prediction model diagnosis the disease accurately.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"165-178"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10255437.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
6G is one of the key cornerstone elements of the futuristic smart system setup - the others being cloud computing, big data, wearable devices and Artificial Intelligence. Also, smart offices and homes have become even more popular than before, because of the advancement in computer vision and Machine Learning (ML) technologies. Recognition of human actions and situations are fundamental components of such systems, especially in complex environments like healthcare, for example at the dentist clinic, where we need cues such as eye movement to distinguish procedures being undertaken. In this work, we compare models based on hierarchical modelling and machine learning to identify the dental procedure. We used the objects seen while following the eye trajectories and focussed on elements including material used for treatment, equipment involved and the teeth conditions i.e. symptoms. Our experiments showed that using Artificial Neural Network (ANN) increased the accuracy of prediction compared to hierarchical modelling. Our experiments show an improvement in accuracy for each of the constituent parameters i.e., symptom (ANN: 95.58% vs. Hierarchical: 45.68%), material (ANN: 86.32% vs. Hierarchical: 45.18%) and equipment (ANN: 92.65% vs. Hierarchical: 59.39%).
{"title":"Comparative Techniques Using Hierarchical Modelling and Machine Learning for Procedure Recognition in Smart Hospitals","authors":"Shaheena Noor;Muhammad Aamir;Najma Ismat;Muhammad Imran Saleem","doi":"10.13052/jicts2245-800X.1023","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1023","url":null,"abstract":"6G is one of the key cornerstone elements of the futuristic smart system setup - the others being cloud computing, big data, wearable devices and Artificial Intelligence. Also, smart offices and homes have become even more popular than before, because of the advancement in computer vision and Machine Learning (ML) technologies. Recognition of human actions and situations are fundamental components of such systems, especially in complex environments like healthcare, for example at the dentist clinic, where we need cues such as eye movement to distinguish procedures being undertaken. In this work, we compare models based on hierarchical modelling and machine learning to identify the dental procedure. We used the objects seen while following the eye trajectories and focussed on elements including material used for treatment, equipment involved and the teeth conditions i.e. symptoms. Our experiments showed that using Artificial Neural Network (ANN) increased the accuracy of prediction compared to hierarchical modelling. Our experiments show an improvement in accuracy for each of the constituent parameters i.e., symptom (ANN: 95.58% vs. Hierarchical: 45.68%), material (ANN: 86.32% vs. Hierarchical: 45.18%) and equipment (ANN: 92.65% vs. Hierarchical: 59.39%).","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"145-164"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10254661.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.13052/jicts2245-800X.1014
Ana Koren;Ramjee Prasad
Millions of wearable devices with embedded sensors (e.g., fitness trackers) are present in daily lives of its users, with the number growing continuously, especially with the approaching 6G communication technology. These devices are helping their users in monitoring daily activities and promoting positive health habits. Potential integration of such collected data into central medical system would lead to more personalized healthcare and an improved patient-physician experience. However, this process is met with several challenges, as medical data is of a highly sensitive nature. This paper focuses on the security and privacy issues for such a process. After providing a comprehensive list of security and privacy threats relevant to data collection and its handling within a Central Health Information system, the paper addresses the challenges of designing a secure system and offeres recommendations, solutions and guidelines for identified pre-6G and 6G security and privacy issues.
{"title":"IoT Health Data in Electronic Health Records (EHR): Security and Privacy Issues in Era of 6G","authors":"Ana Koren;Ramjee Prasad","doi":"10.13052/jicts2245-800X.1014","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1014","url":null,"abstract":"Millions of wearable devices with embedded sensors (e.g., fitness trackers) are present in daily lives of its users, with the number growing continuously, especially with the approaching 6G communication technology. These devices are helping their users in monitoring daily activities and promoting positive health habits. Potential integration of such collected data into central medical system would lead to more personalized healthcare and an improved patient-physician experience. However, this process is met with several challenges, as medical data is of a highly sensitive nature. This paper focuses on the security and privacy issues for such a process. After providing a comprehensive list of security and privacy threats relevant to data collection and its handling within a Central Health Information system, the paper addresses the challenges of designing a secure system and offeres recommendations, solutions and guidelines for identified pre-6G and 6G security and privacy issues.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 1","pages":"63-84"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255387/10255403.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68134610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.13052/jicts2245-800X.1012
Peter Lindgren
In the last few years businesses have been motivated and pushed by governments and global society on innovating and developing Green Business Models. However, Reconfiguring, designing and developing green business models to become efficient and valuing Green Business Models have shown to be much more complex than expected. It includes balancing monetary and non monetary value formulas of business models in symbiosis. Not just for the single business - but for businesses in their entire value network. This includes security challenges related to securing that green business models really are green - and not based on greenwashing. As green business models demand in long term perspective a very open business model innovation approach, it calls for stronger and new security technologies. Protection of IPR's of Business Models and businesses competences, so they are not one to one copied with out giving value back to “the Business Model designer” and the rightful original owner of the business models is a major security challenge related to green business models. Green Business Models and Green business Model Innovation calls therefore for new and more advanced security approach, technologies and understanding. Previous business model innovation security practice and systems cannot fully offer these solutions - but 6G of wide-area wireless security technologies - as an umbrella - gives hope and can potentially play major role with new security technologies supported by AI, AR and blockchain technologies. This evolvement is highly and urgent needed to support the success of our society's green transformation. The paper document through Nordic green business model cases some of the above mention security challenges that green business models and green business model innovation stand in front of and need to innovate solutions for. The paper discuss and propose how 6G and related technologies could help.
{"title":"6G Technologies - How Can It Help Future Green Business Model Innovation","authors":"Peter Lindgren","doi":"10.13052/jicts2245-800X.1012","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1012","url":null,"abstract":"In the last few years businesses have been motivated and pushed by governments and global society on innovating and developing Green Business Models. However, Reconfiguring, designing and developing green business models to become efficient and valuing Green Business Models have shown to be much more complex than expected. It includes balancing monetary and non monetary value formulas of business models in symbiosis. Not just for the single business - but for businesses in their entire value network. This includes security challenges related to securing that green business models really are green - and not based on greenwashing. As green business models demand in long term perspective a very open business model innovation approach, it calls for stronger and new security technologies. Protection of IPR's of Business Models and businesses competences, so they are not one to one copied with out giving value back to “the Business Model designer” and the rightful original owner of the business models is a major security challenge related to green business models. Green Business Models and Green business Model Innovation calls therefore for new and more advanced security approach, technologies and understanding. Previous business model innovation security practice and systems cannot fully offer these solutions - but 6G of wide-area wireless security technologies - as an umbrella - gives hope and can potentially play major role with new security technologies supported by AI, AR and blockchain technologies. This evolvement is highly and urgent needed to support the success of our society's green transformation. The paper document through Nordic green business model cases some of the above mention security challenges that green business models and green business model innovation stand in front of and need to innovate solutions for. The paper discuss and propose how 6G and related technologies could help.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 1","pages":"11-37"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10255387/10255425.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68134612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.13052/jicts2245-800X.1021
Armend Salihu;Hamdi Hoti
The purpose of this study is to analyse the impact of the risk significance of audit results, the quality of the recommendations given on how easy it is to implement them, and the added benefit to the organization in implementing the recommendations. After a comprehensive literature review, the study provides a statistical analysis through a questionnaire that has been distributed to investigate the effect of Risk Significance, Ease of Implementation, and the Added Value on the implementation of the recommendations within organizations. Regarding the results obtained from the questionnaire, all Cronbach's Alpha values are within the acceptable level, whereas the first three variables (Implementation of Recommendations, Risk Significance and Ease of Implementation) have a strong positive correlation between each other. There is a weak positive correlation between Added Value of Recommendations with other variables. In the regression analysis was found that all independent variables have a positive effect on the depended variable.
{"title":"Managers' Perception on the IT Audit Recommendations: The Effect of Risk Significance, Ease of Implementation and Added Value on Implementation of Recommendations","authors":"Armend Salihu;Hamdi Hoti","doi":"10.13052/jicts2245-800X.1021","DOIUrl":"https://doi.org/10.13052/jicts2245-800X.1021","url":null,"abstract":"The purpose of this study is to analyse the impact of the risk significance of audit results, the quality of the recommendations given on how easy it is to implement them, and the added benefit to the organization in implementing the recommendations. After a comprehensive literature review, the study provides a statistical analysis through a questionnaire that has been distributed to investigate the effect of Risk Significance, Ease of Implementation, and the Added Value on the implementation of the recommendations within organizations. Regarding the results obtained from the questionnaire, all Cronbach's Alpha values are within the acceptable level, whereas the first three variables (Implementation of Recommendations, Risk Significance and Ease of Implementation) have a strong positive correlation between each other. There is a weak positive correlation between Added Value of Recommendations with other variables. In the regression analysis was found that all independent variables have a positive effect on the depended variable.","PeriodicalId":36697,"journal":{"name":"Journal of ICT Standardization","volume":"10 2","pages":"105-124"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/10251929/10254727/10254728.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68110517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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