Muhammad Asad Arshed, Shahzad Mumtaz, Muhammad Ibrahim, Saeed Ahmed, Muhammad Tahir, Muhammad Shafi
Skin cancer, particularly melanoma, has been recognized as one of the most lethal forms of cancer. Detecting and diagnosing skin lesions accurately can be challenging due to the striking similarities between the various types of skin lesions, such as melanoma and nevi, especially when examining the color images of the skin. However, early diagnosis plays a crucial role in saving lives and reducing the burden on medical resources. Consequently, the development of a robust autonomous system for skin cancer classification becomes imperative. Convolutional neural networks (CNNs) have been widely employed over the past decade to automate cancer diagnosis. Nonetheless, the emergence of the Vision Transformer (ViT) has recently gained a considerable level of popularity in the field and has emerged as a competitive alternative to CNNs. In light of this, the present study proposed an alternative method based on the off-the-shelf ViT for identifying various skin cancer diseases. To evaluate its performance, the proposed method was compared with 11 CNN-based transfer learning methods that have been known to outperform other deep learning techniques that are currently in use. Furthermore, this study addresses the issue of class imbalance within the dataset, a common challenge in skin cancer classification. In addressing this concern, the proposed study leverages the vision transformer and the CNN-based transfer learning models to classify seven distinct types of skin cancers. Through our investigation, we have found that the employment of pre-trained vision transformers achieved an impressive accuracy of 92.14%, surpassing CNN-based transfer learning models across several evaluation metrics for skin cancer diagnosis.
{"title":"Multi-Class Skin Cancer Classification Using Vision Transformer Networks and Convolutional Neural Network-Based Pre-Trained Models","authors":"Muhammad Asad Arshed, Shahzad Mumtaz, Muhammad Ibrahim, Saeed Ahmed, Muhammad Tahir, Muhammad Shafi","doi":"10.3390/info14070415","DOIUrl":"https://doi.org/10.3390/info14070415","url":null,"abstract":"Skin cancer, particularly melanoma, has been recognized as one of the most lethal forms of cancer. Detecting and diagnosing skin lesions accurately can be challenging due to the striking similarities between the various types of skin lesions, such as melanoma and nevi, especially when examining the color images of the skin. However, early diagnosis plays a crucial role in saving lives and reducing the burden on medical resources. Consequently, the development of a robust autonomous system for skin cancer classification becomes imperative. Convolutional neural networks (CNNs) have been widely employed over the past decade to automate cancer diagnosis. Nonetheless, the emergence of the Vision Transformer (ViT) has recently gained a considerable level of popularity in the field and has emerged as a competitive alternative to CNNs. In light of this, the present study proposed an alternative method based on the off-the-shelf ViT for identifying various skin cancer diseases. To evaluate its performance, the proposed method was compared with 11 CNN-based transfer learning methods that have been known to outperform other deep learning techniques that are currently in use. Furthermore, this study addresses the issue of class imbalance within the dataset, a common challenge in skin cancer classification. In addressing this concern, the proposed study leverages the vision transformer and the CNN-based transfer learning models to classify seven distinct types of skin cancers. Through our investigation, we have found that the employment of pre-trained vision transformers achieved an impressive accuracy of 92.14%, surpassing CNN-based transfer learning models across several evaluation metrics for skin cancer diagnosis.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"34 1","pages":"415"},"PeriodicalIF":0.0,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76250957","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}
In recent years, artificial intelligence (AI) has emerged as a valuable resource for teaching and learning, and it has also shown promise as a tool to help solve problems. A tool that has gained attention in education is ChatGPT, which supports teaching and learning through AI. This research investigates the difficulties faced by ChatGPT in comprehending and responding to chemistry problems pertaining to the topic of Introduction to Material Science. By employing the theoretical framework proposed by Holme et al., encompassing categories such as transfer, depth, predict/explain, problem solving, and translate, we evaluate ChatGPT’s conceptual understanding difficulties. We presented ChatGPT with a set of thirty chemistry problems within the Introduction to Material Science domain and tasked it with generating solutions. Our findings indicated that ChatGPT encountered significant conceptual knowledge difficulties across various categories, with a notable emphasis on representations and depth, where difficulties in representations hindered effective knowledge transfer.
{"title":"Artificial Intelligence Generative Tools and Conceptual Knowledge in Problem Solving in Chemistry","authors":"Wajeeh M. Daher, Hussam Diab, A. Rayan","doi":"10.3390/info14070409","DOIUrl":"https://doi.org/10.3390/info14070409","url":null,"abstract":"In recent years, artificial intelligence (AI) has emerged as a valuable resource for teaching and learning, and it has also shown promise as a tool to help solve problems. A tool that has gained attention in education is ChatGPT, which supports teaching and learning through AI. This research investigates the difficulties faced by ChatGPT in comprehending and responding to chemistry problems pertaining to the topic of Introduction to Material Science. By employing the theoretical framework proposed by Holme et al., encompassing categories such as transfer, depth, predict/explain, problem solving, and translate, we evaluate ChatGPT’s conceptual understanding difficulties. We presented ChatGPT with a set of thirty chemistry problems within the Introduction to Material Science domain and tasked it with generating solutions. Our findings indicated that ChatGPT encountered significant conceptual knowledge difficulties across various categories, with a notable emphasis on representations and depth, where difficulties in representations hindered effective knowledge transfer.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"3 1","pages":"409"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91335470","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}
In this work we combine sentiment analysis with graph theory to analyze user posts, likes/dislikes on a variety of social media to provide recommendations for YouTube videos. We focus on the topic of climate change/global warming, which has caused much alarm and controversy over recent years. Our intention is to recommend informative YouTube videos to those seeking a balanced viewpoint of this area and the key arguments/issues. To this end we analyze Twitter data; Reddit comments and posts; user comments, view statistics and likes/dislikes of YouTube videos. The combination of sentiment analysis with raw statistics and linking users with their posts gives deeper insights into their needs and quest for quality information. Sentiment analysis provides the insights into user likes and dislikes, graph theory provides the linkage patterns and relationships between users, posts, and sentiment.
{"title":"Analyzing Social Media Data Using Sentiment Mining and Bigram Analysis for the Recommendation of YouTube Videos","authors":"Ken McGarry","doi":"10.3390/info14070408","DOIUrl":"https://doi.org/10.3390/info14070408","url":null,"abstract":"In this work we combine sentiment analysis with graph theory to analyze user posts, likes/dislikes on a variety of social media to provide recommendations for YouTube videos. We focus on the topic of climate change/global warming, which has caused much alarm and controversy over recent years. Our intention is to recommend informative YouTube videos to those seeking a balanced viewpoint of this area and the key arguments/issues. To this end we analyze Twitter data; Reddit comments and posts; user comments, view statistics and likes/dislikes of YouTube videos. The combination of sentiment analysis with raw statistics and linking users with their posts gives deeper insights into their needs and quest for quality information. Sentiment analysis provides the insights into user likes and dislikes, graph theory provides the linkage patterns and relationships between users, posts, and sentiment.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"6 1","pages":"408"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76642518","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}
The prompt and accurate diagnosis of breast lesions, including the distinction between cancer, non-cancer, and suspicious cancer, plays a crucial role in the prognosis of breast cancer. In this paper, we introduce a novel method based on feature extraction and reduction for the detection of breast cancer in mammography images. First, we extract features from multiple pre-trained convolutional neural network (CNN) models, and then concatenate them. The most informative features are selected based on their mutual information with the target variable. Subsequently, the selected features can be classified using a machine learning algorithm. We evaluate our approach using four different machine learning algorithms: neural network (NN), k-nearest neighbor (kNN), random forest (RF), and support vector machine (SVM). Our results demonstrate that the NN-based classifier achieves an impressive accuracy of 92% on the RSNA dataset. This dataset is newly introduced and includes two views as well as additional features like age, which contributed to the improved performance. We compare our proposed algorithm with state-of-the-art methods and demonstrate its superiority, particularly in terms of accuracy and sensitivity. For the MIAS dataset, we achieve an accuracy as high as 94.5%, and for the DDSM dataset, an accuracy of 96% is attained. These results highlight the effectiveness of our method in accurately diagnosing breast lesions and surpassing existing approaches.
{"title":"Breast Cancer Detection in Mammography Images: A CNN-Based Approach with Feature Selection","authors":"Zahra Jafari, E. Karami","doi":"10.3390/info14070410","DOIUrl":"https://doi.org/10.3390/info14070410","url":null,"abstract":"The prompt and accurate diagnosis of breast lesions, including the distinction between cancer, non-cancer, and suspicious cancer, plays a crucial role in the prognosis of breast cancer. In this paper, we introduce a novel method based on feature extraction and reduction for the detection of breast cancer in mammography images. First, we extract features from multiple pre-trained convolutional neural network (CNN) models, and then concatenate them. The most informative features are selected based on their mutual information with the target variable. Subsequently, the selected features can be classified using a machine learning algorithm. We evaluate our approach using four different machine learning algorithms: neural network (NN), k-nearest neighbor (kNN), random forest (RF), and support vector machine (SVM). Our results demonstrate that the NN-based classifier achieves an impressive accuracy of 92% on the RSNA dataset. This dataset is newly introduced and includes two views as well as additional features like age, which contributed to the improved performance. We compare our proposed algorithm with state-of-the-art methods and demonstrate its superiority, particularly in terms of accuracy and sensitivity. For the MIAS dataset, we achieve an accuracy as high as 94.5%, and for the DDSM dataset, an accuracy of 96% is attained. These results highlight the effectiveness of our method in accurately diagnosing breast lesions and surpassing existing approaches.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"18 1","pages":"410"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89957945","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}
Asif Hussian, Abdul Mateen, Farhan Amin, Muhammad Ali Abid, S. Ullah
In the current era of ubiquitous computing and mobile technology, almost all human beings use various self-monitoring applications. Mobile applications could be the best health assistant for safety and adopting a healthy lifestyle. Therefore, persuasive designing is a compulsory element for designing such apps. A popular model for persuasive design named the Persuasive System Design (PSD) model is a generalized model for whole persuasive technologies. Any type of persuasive application could be designed using this model. Designing any special type of application using the PSD model could be difficult because of its generalized behavior which fails to provide moral support for users of health applications. There is a strong need to propose a customized and improved persuasive system design model for each category to overcome the issue. This study evaluates the PSD model and finds persuasive gaps in users of the Mobile Health Monitoring application, developed by following the PSD model. Furthermore, this study finds that users misunderstand health-related problems when using such apps. A misunderstanding of this nature can have serious consequences for the user’s life in some cases.
在当今无处不在的计算和移动技术时代，几乎所有人都在使用各种自我监控应用程序。移动应用程序可能是安全和采用健康生活方式的最佳健康助手。因此，说服性设计是设计此类应用程序的必备元素。劝导系统设计(persuasive System design, PSD)模型是一个比较流行的劝导设计模型，它是整个劝导技术的广义模型。任何类型的说服应用程序都可以使用这个模型来设计。使用PSD模型设计任何特殊类型的应用程序可能是困难的，因为它的广义行为不能为健康应用程序的用户提供道德支持。为克服这一问题，迫切需要为每个类别提出定制化和改进的说服系统设计模型。本研究评估了PSD模型，并在遵循PSD模型开发的移动健康监测应用程序的用户中发现了令人信服的差距。此外，本研究发现用户在使用此类应用程序时误解了与健康相关的问题。在某些情况下，这种性质的误解可能会对用户的生命造成严重后果。
{"title":"Health Monitoring Apps: An Evaluation of the Persuasive System Design Model for Human Wellbeing","authors":"Asif Hussian, Abdul Mateen, Farhan Amin, Muhammad Ali Abid, S. Ullah","doi":"10.3390/info14070412","DOIUrl":"https://doi.org/10.3390/info14070412","url":null,"abstract":"In the current era of ubiquitous computing and mobile technology, almost all human beings use various self-monitoring applications. Mobile applications could be the best health assistant for safety and adopting a healthy lifestyle. Therefore, persuasive designing is a compulsory element for designing such apps. A popular model for persuasive design named the Persuasive System Design (PSD) model is a generalized model for whole persuasive technologies. Any type of persuasive application could be designed using this model. Designing any special type of application using the PSD model could be difficult because of its generalized behavior which fails to provide moral support for users of health applications. There is a strong need to propose a customized and improved persuasive system design model for each category to overcome the issue. This study evaluates the PSD model and finds persuasive gaps in users of the Mobile Health Monitoring application, developed by following the PSD model. Furthermore, this study finds that users misunderstand health-related problems when using such apps. A misunderstanding of this nature can have serious consequences for the user’s life in some cases.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"8 1","pages":"412"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89124122","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}
C. Esposito, Ross Horne, L. Robaldo, B. Buelens, Elfi Goesaert
The Solid specification aims to empower data subjects by giving them direct access control over their data across multiple applications. As governments are manifesting their interest in this framework for citizen empowerment and e-government services, security and privacy represent pivotal issues to be addressed. By analysing the relevant legislation, with an emphasis on GDPR and officially approved documents such as codes of conduct and relevant security ISO standards, we formulate the primary security and privacy requirements for such a framework. The legislation places some obligations on pod providers, much like cloud services. However, what is more interesting is that Solid has the potential to support GDPR compliance of Solid apps and data users that connect, via the protocol, to Solid pods containing personal data. A Solid-based healthcare use case is illustrated where identifying such controllers responsible for apps and data users is essential for the system to be deployed. Furthermore, we survey the current Solid protocol specifications regarding how they cover the highlighted requirements, and draw attention to potential gaps between the specifications and requirements. We also point out the contribution of recent academic work presenting novel approaches to increase the security and privacy degree provided by the Solid project. This paper has a twofold contribution to improve user awareness of how Solid can help protect their data and to present possible future research lines on Solid security and privacy enhancements.
{"title":"Assessing the Solid Protocol in Relation to Security and Privacy Obligations","authors":"C. Esposito, Ross Horne, L. Robaldo, B. Buelens, Elfi Goesaert","doi":"10.3390/info14070411","DOIUrl":"https://doi.org/10.3390/info14070411","url":null,"abstract":"The Solid specification aims to empower data subjects by giving them direct access control over their data across multiple applications. As governments are manifesting their interest in this framework for citizen empowerment and e-government services, security and privacy represent pivotal issues to be addressed. By analysing the relevant legislation, with an emphasis on GDPR and officially approved documents such as codes of conduct and relevant security ISO standards, we formulate the primary security and privacy requirements for such a framework. The legislation places some obligations on pod providers, much like cloud services. However, what is more interesting is that Solid has the potential to support GDPR compliance of Solid apps and data users that connect, via the protocol, to Solid pods containing personal data. A Solid-based healthcare use case is illustrated where identifying such controllers responsible for apps and data users is essential for the system to be deployed. Furthermore, we survey the current Solid protocol specifications regarding how they cover the highlighted requirements, and draw attention to potential gaps between the specifications and requirements. We also point out the contribution of recent academic work presenting novel approaches to increase the security and privacy degree provided by the Solid project. This paper has a twofold contribution to improve user awareness of how Solid can help protect their data and to present possible future research lines on Solid security and privacy enhancements.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"51 1","pages":"411"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81798592","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}
A. Ahmed, Mohamed Bader, I. Shahin, A. B. Nassif, N. Werghi, Mohammad Basel
The Arabic language has always been an immense source of attraction to various people from different ethnicities by virtue of the significant linguistic legacy that it possesses. Consequently, a multitude of people from all over the world are yearning to learn it. However, people from different mother tongues and cultural backgrounds might experience some hardships regarding articulation due to the absence of some particular letters only available in the Arabic language, which could hinder the learning process. As a result, a speaker-independent and text-dependent efficient system that aims to detect articulation disorders was implemented. In the proposed system, we emphasize the prominence of “speech signal processing” in diagnosing Arabic mispronunciation using the Mel-frequency cepstral coefficients (MFCCs) as the optimum extracted features. In addition, long short-term memory (LSTM) was also utilized for the classification process. Furthermore, the analytical framework was incorporated with a gender recognition model to perform two-level classification. Our results show that the LSTM network significantly enhances mispronunciation detection along with gender recognition. The LSTM models attained an average accuracy of 81.52% in the proposed system, reflecting a high performance compared to previous mispronunciation detection systems.
{"title":"Arabic Mispronunciation Recognition System Using LSTM Network","authors":"A. Ahmed, Mohamed Bader, I. Shahin, A. B. Nassif, N. Werghi, Mohammad Basel","doi":"10.3390/info14070413","DOIUrl":"https://doi.org/10.3390/info14070413","url":null,"abstract":"The Arabic language has always been an immense source of attraction to various people from different ethnicities by virtue of the significant linguistic legacy that it possesses. Consequently, a multitude of people from all over the world are yearning to learn it. However, people from different mother tongues and cultural backgrounds might experience some hardships regarding articulation due to the absence of some particular letters only available in the Arabic language, which could hinder the learning process. As a result, a speaker-independent and text-dependent efficient system that aims to detect articulation disorders was implemented. In the proposed system, we emphasize the prominence of “speech signal processing” in diagnosing Arabic mispronunciation using the Mel-frequency cepstral coefficients (MFCCs) as the optimum extracted features. In addition, long short-term memory (LSTM) was also utilized for the classification process. Furthermore, the analytical framework was incorporated with a gender recognition model to perform two-level classification. Our results show that the LSTM network significantly enhances mispronunciation detection along with gender recognition. The LSTM models attained an average accuracy of 81.52% in the proposed system, reflecting a high performance compared to previous mispronunciation detection systems.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"20 1","pages":"413"},"PeriodicalIF":0.0,"publicationDate":"2023-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87023997","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}
Alexander A. Olenev, I. Kalmykov, V. Pashintsev, N. Chistousov, D. V. Dukhovnyj, N. Kalmykova
Low-orbit satellite internet (LOSI) expands the scope of the Industrial Internet of Things (IIoT) in the oil and gas industry (OGI) to include areas of the Far North. However, due to the large length of the communication channel, the number of threats and attacks increases. A special place among them is occupied by relay spoofing interference. In this case, an intruder satellite intercepts the control signal coming from the satellite (SC), delays it, and then imposes it on the receiver located on the unattended OGI object. This can lead to a disruption of the facility and even cause an environmental disaster. To prevent a spoofing attack, a satellite authentication method has been developed that uses a zero-knowledge authentication protocol (ZKAP). These protocols have high cryptographic strength without the use of encryption. However, they have a significant drawback. This is their low authentication speed, which is caused by calculations over a large module Q (128 bits or more). It is possible to reduce the time of determining the status of an SC by switching to parallel computing. To solve this problem, the paper proposes to use residue codes (RC). Addition, subtraction, and multiplication operations are performed in parallel in RC. Thus, a correct choice of a set of modules of RC allows for providing an operating range of calculations not less than the number Q. Therefore, the development of a spacecraft authentication method for the satellite internet system using RC that allows for reducing the authentication time is an urgent task.
{"title":"Improved Spacecraft Authentication Method for Satellite Internet System Using Residue Codes","authors":"Alexander A. Olenev, I. Kalmykov, V. Pashintsev, N. Chistousov, D. V. Dukhovnyj, N. Kalmykova","doi":"10.3390/info14070407","DOIUrl":"https://doi.org/10.3390/info14070407","url":null,"abstract":"Low-orbit satellite internet (LOSI) expands the scope of the Industrial Internet of Things (IIoT) in the oil and gas industry (OGI) to include areas of the Far North. However, due to the large length of the communication channel, the number of threats and attacks increases. A special place among them is occupied by relay spoofing interference. In this case, an intruder satellite intercepts the control signal coming from the satellite (SC), delays it, and then imposes it on the receiver located on the unattended OGI object. This can lead to a disruption of the facility and even cause an environmental disaster. To prevent a spoofing attack, a satellite authentication method has been developed that uses a zero-knowledge authentication protocol (ZKAP). These protocols have high cryptographic strength without the use of encryption. However, they have a significant drawback. This is their low authentication speed, which is caused by calculations over a large module Q (128 bits or more). It is possible to reduce the time of determining the status of an SC by switching to parallel computing. To solve this problem, the paper proposes to use residue codes (RC). Addition, subtraction, and multiplication operations are performed in parallel in RC. Thus, a correct choice of a set of modules of RC allows for providing an operating range of calculations not less than the number Q. Therefore, the development of a spacecraft authentication method for the satellite internet system using RC that allows for reducing the authentication time is an urgent task.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"16 1","pages":"407"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84754230","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}
Maria I. Klouvidaki, N. Antonopoulos, Georgios D. Styliaras, Andreas Kanavos
Due to COVID-19 restrictions, many restaurants were forced to discontinue in-person service, either by locking down or finding alternative methods of operation. Despite the fact that, in the United States of America, digital restaurants have already been established for many years, in Greece, this phenomenon became popular during the pandemic. These delivery-only companies operate exclusively online, allowing customers to place orders from restaurants without a physical location. This has revolutionized the process of ordering food, as customers can browse digital menus, view images, and utilize other options provided by digital food technology. As a result, customers have had new experiences with food thanks to digital eateries during the pandemic. This research study is quantitative and utilized a questionnaire distributed to 1097 participating consumers over the internet. The sample was selected using straightforward random sampling, where each member of the population had an equal and unique chance of participating in the survey. The data were collected over a period of 2 months.
{"title":"Virtual Restaurants: Customer Experience Keeps Their Businesses Alive","authors":"Maria I. Klouvidaki, N. Antonopoulos, Georgios D. Styliaras, Andreas Kanavos","doi":"10.3390/info14070406","DOIUrl":"https://doi.org/10.3390/info14070406","url":null,"abstract":"Due to COVID-19 restrictions, many restaurants were forced to discontinue in-person service, either by locking down or finding alternative methods of operation. Despite the fact that, in the United States of America, digital restaurants have already been established for many years, in Greece, this phenomenon became popular during the pandemic. These delivery-only companies operate exclusively online, allowing customers to place orders from restaurants without a physical location. This has revolutionized the process of ordering food, as customers can browse digital menus, view images, and utilize other options provided by digital food technology. As a result, customers have had new experiences with food thanks to digital eateries during the pandemic. This research study is quantitative and utilized a questionnaire distributed to 1097 participating consumers over the internet. The sample was selected using straightforward random sampling, where each member of the population had an equal and unique chance of participating in the survey. The data were collected over a period of 2 months.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"31 1","pages":"406"},"PeriodicalIF":0.0,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89624217","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}
We studied two fundamental linguistic channels—the sentences and the interpunctions channels—and showed they can reveal deeper connections between texts. The applied theory does not follow the actual paradigm of linguistic studies. As a study case, we considered the Greek New Testament, with the purpose of determining mathematical connections between its texts and possible differences in the writing style (mathematically defined) of the writers and in the reading skill required of their readers. The analysis was based on deep-language parameters and communication/information theory. To set the New Testament texts in the larger Greek classical literature, we considered texts written by Aesop, Polybius, Flavius Josephus, and Plutarch. The results largely confirmed what scholars have found about the New Testament texts, therefore giving credibility to the theory. The Gospel according to John is very similar to the fables written by Aesop. Surprisingly, the Epistle to the Hebrews and Apocalypse are each other’s “photocopies” in the two linguistic channels and not linked to all other texts. These two texts deserve further study by historians of the early Christian church literature at the level of meaning, readers, and possible Old Testament texts that might have influenced them. The theory can guide scholars to study any literary corpus.
{"title":"Linguistic Communication Channels Reveal Connections between Texts: The New Testament and Greek Literature","authors":"E. Matricciani","doi":"10.3390/info14070405","DOIUrl":"https://doi.org/10.3390/info14070405","url":null,"abstract":"We studied two fundamental linguistic channels—the sentences and the interpunctions channels—and showed they can reveal deeper connections between texts. The applied theory does not follow the actual paradigm of linguistic studies. As a study case, we considered the Greek New Testament, with the purpose of determining mathematical connections between its texts and possible differences in the writing style (mathematically defined) of the writers and in the reading skill required of their readers. The analysis was based on deep-language parameters and communication/information theory. To set the New Testament texts in the larger Greek classical literature, we considered texts written by Aesop, Polybius, Flavius Josephus, and Plutarch. The results largely confirmed what scholars have found about the New Testament texts, therefore giving credibility to the theory. The Gospel according to John is very similar to the fables written by Aesop. Surprisingly, the Epistle to the Hebrews and Apocalypse are each other’s “photocopies” in the two linguistic channels and not linked to all other texts. These two texts deserve further study by historians of the early Christian church literature at the level of meaning, readers, and possible Old Testament texts that might have influenced them. The theory can guide scholars to study any literary corpus.","PeriodicalId":13622,"journal":{"name":"Inf. Comput.","volume":"1 1","pages":"405"},"PeriodicalIF":0.0,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89709681","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}
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