2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)最新文献

{"title":"Semi-Decentralized File Sharing as a Service","authors":"Vasileios Argyropoulos, Efthymios Alepis, C. Patsakis","doi":"10.1109/IISA56318.2022.9904336","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904336","url":null,"abstract":"Files are the most widely used format for recording data in the modern world. Files are either exchanged through a storage medium or transported from one computer to another via a file sharing platform. In the latter case, most services are centralised meaning that a file copy is freely available to the platform provider exposing users to the risk of sensitive information leakage. Alternatively, some protocols ensure that a third party will not be able to maintain a copy of the data. This work presents a solution to this problem, providing a Peer-to-Peer, semi-decentralized file sharing system as a service enabling the end-user to share any file in a secure manner and ensuring no usable copy of the file is stored anywhere but the sender’s and recipient’s file system while the recipient can ensure that the file has not been tampered with in any way using digital signatures. A microservice-based novel application has been developed that implements this functionality while abstracting the complexity to a simple browser-based user interface.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122140133","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":"Discrete event simulation of an automated warehouse inspection system with drones","authors":"I. P. Antoniades, I. Stamelos","doi":"10.1109/IISA56318.2022.9904417","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904417","url":null,"abstract":"A discrete event simulation model was designed and implemented in order to test and optimize the operation of a prototypical automated warehouse inspection system based on drones and wireless communications. The system prototype, which included both hardware and software parts, was developed and presented elsewhere. We applied the simulation model under realistic conditions particular for a specific warehouse originally used for testing the said system prototype. We test various ”whatif” scenarios by varying a couple of key control parameters with the purpose of demonstrating how discrete event simulation is useful not only for testing such a system but also for aiding design and system parameterization for optimal performance and efficiency.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124972051","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":"An intelligent decision support model for staff selection based on the application of the Fuzzy Delphi Method and the Fuzzy Analytical Hierarchical Process","authors":"Antonios Paraskevas, Konstantinos Zagoris, S. Chatzichristofis","doi":"10.1109/IISA56318.2022.9904358","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904358","url":null,"abstract":"Businesses today are required to operate in an ever-changing business environment characterized by complexity and uncertainty, in which the ability to make effective decisions is of particular importance. Furthermore, it is now indisputable that in the modern work environment, the difference between successful and unsuccessful organizations is determined by people, the so-called human resources. In this light, the proper selection of staff by the management of an organization is a critical parameter of competitiveness, productivity, and efficiency. Because of the above, the present work presents a comprehensive methodological approach to the issue that focuses on the multi-criteria nature of the problem. The proposed conceptual framework is based on the Fuzzy Analytical Hierarchical Process (FAHP), which uses the theory of fuzzy Logic and is considered appropriate in terms of the high degree of uncertainty about decision-making. The paper aims to define and analyze the criteria related to the modern administrative skills required by managers for the successful fulfillment of administrative practices. To this end, our methodology extends the Fuzzy Analytical Hierarchical Process by introducing the Fuzzy Delphi Method (FDM) technique. In this way, we can take into account the significance of each decision-maker and their particular preferences through the relative importance of decision-makers per evaluation criterion. As a case study, it was chosen to apply our method to a real institution and specifically at the Neapolis University Pafos, Cyprus, in a real case of the selection of academic staff. By using the Fuzzy Analytical Hierarchical Process, the candidates to fill the vacancy are ranked in order of priority, thus providing an appropriate tool at the institution’s disposal (and possibly a company or organization) to obtain the most appropriate decision for the problem under study.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129500828","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":"Kernels on Attributed Networks for Community Detection","authors":"C. Pizzuti, Annalisa Socievole","doi":"10.1109/IISA56318.2022.9904348","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904348","url":null,"abstract":"Community detection is a primary problem in the study of complex networks. When graphs are enriched with attributes, it has been found that this additional information can help in better understanding the ties among the actors composing the network and provides a deeper insight into group organization. The paper proposes the investigation of a multiobjective genetic algorithm for attributed networks extended with kernel functions for computing node similarity both in terms of structure and features. The commute-time kernel, based on the concept of random walk, is first applied to the adjacency matrix of the graph and then four kernels are applied for computing the similarity between nodes while simultaneously optimizing structure and feature dimensions. Simulations on both synthetic and real-world citation networks show that kernels effectively improve the quality of the resulting partitions.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128971167","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":"Quantum Machine Learning for Audio Classification with Applications to Healthcare","authors":"Michael Esposito, Glen S. Uehara, A. Spanias","doi":"10.1109/IISA56318.2022.9904377","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904377","url":null,"abstract":"Accessible rapid COVID-19 testing continues to be necessary and several studies involving deep neural network (DNN) methods for detection have been published. As part of a sponsored NSF I/UCRC project, our team explored the use of deep learning algorithms for recognizing COVID-19 related cough audio signatures. More specifically, we have worked with several DNN algorithms and cough audio databases and reported results with the VGG-13 architecture. In this paper, we report a study on the use of quantum neural networks for audio signature detection and classification. A hybrid quantum neural network (QNN) model for COVID-19 cough classification is developed. The design of the QNN simulation architecture is described and results are given with and without quantum noise. Comparative results between classical and quantum neural network methods for COVID-19 audio detection are also presented.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"1967 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130473646","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":"A Hybrid Data Model for the Assessment of Border Control Technologies","authors":"G. Gkioka, B. Magoutas, E. Bothos, G. Mentzas","doi":"10.1109/IISA56318.2022.9904400","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904400","url":null,"abstract":"The increasing demand for traveler clearance at international border crossing points (BCPs) has motivated research for finding more efficient solutions. Automated border control (ABC) is emerging as a solution to enhance the convenience of travelers, the throughput of BCPs, and national security. In recent years, focus has been placed on the use and acceptance of these technologies, in order to understand the barriers to use and the acceptance problems people experience. Despite the growing interest in novel Smart Border Control (SBC) technologies and in the assessment of their usability and acceptance, there are currently no standardized ways to capture the data needed to assess their acceptance. This paper provides a review concerning recent approaches in data and ontology modelling in addition to relevant to the border control domain data models and ontologies. We then explain in detail the application of a hybrid approach, both knowledge-based and data-driven, in order to derive the core entities, attributes and relationships among them. Moreover, we propose a data model which aims to capture the data needed for the border control technologies assessment. Finally, the data model is evaluated by domain experts and the results are presented and discussed.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116726480","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":"Design of a Modular Integrated System for Augmented Tourism Destinations","authors":"Yorghos Voutos, Stergios Palamas, Phivos Mylonas","doi":"10.1109/IISA56318.2022.9904373","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904373","url":null,"abstract":"In the tourism sector, identifying and promoting relevant attractions and points of interest to visitors, especially through AR/VR technologies, has been proven to enhance the on-site overall visiting experience. Throughout this paper, the use of multimedia, augmented and virtual reality content is presented, as a means to improve the experience of both on-site and remote (website) visitors. Therefore, a generally applicable platform, consisting of interconnected modules and based on open source technologies is proposed, which in turn allows the end-users to provide their own content and stakeholders to gather meaningful metrics and feedback.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133551352","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":"A Comparative Analysis of VirusTotal and Desktop Antivirus Detection Capabilities","authors":"Christian Leka, Christoforos Ntantogian, Stylianos Karagiannis, E. Magkos, Vassilios S. Verykios","doi":"10.1109/IISA56318.2022.9904382","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904382","url":null,"abstract":"VirusTotal has been widely used and being adopted by researchers mainly for the classification of files as malicious or not. Unfortunately, it is not well understood how reliable the results from the antivirus engines on VirusTotal are, especially compared to their desktop counterparts. In this paper, we shed light on the blackbox testing functionality of VirusTotal by evaluating the detection results of VirusTotal antivirus engines and their equivalent desktop versions. Based on our results, we arrive to the conclusion that there are discrepancies between the engines on VirusTotal and the desktop engines. In general, the malware detection rate of the engines on VirusTotal is lower compared to desktop products. This is mainly attributed to the fact that VirusTotal engines do not take advantage of cloud-based detection deteriorating their performance.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"297 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123121650","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":"E-Privacy Issues in the Smart Cities Environment","authors":"Anna Papaiakovou, C. Nika, D. Vergados","doi":"10.1109/IISA56318.2022.9904395","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904395","url":null,"abstract":"In today’s smart city era, security and privacy are challenges that everyone, especially those involved in building smart cities in the Information and Communication Technology (ICT) sector, must grasp and train. In a smart city, it is critical for citizens, professionals, students, and visitors to have a secure environment. Governments have gradually begun to embrace smart city ideas in order to improve and thereby elevate their residents’ living standards. The collecting, storage, processing, and interchange of personal data raises several critical privacy and security issues. As a result, only a strong and up-to-date legal framework will be able to cover the gap in protection left by the new communications services.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123945163","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":"Analysis and Prediction of Air Pollutant Indices using Bidirectional-Convolutional LSTMs","authors":"Georgios Karampelas, D. Sotiropoulos","doi":"10.1109/IISA56318.2022.9904392","DOIUrl":"https://doi.org/10.1109/IISA56318.2022.9904392","url":null,"abstract":"Air pollution is a crucial issue that affects people’s health and simultaneously the planet’s future. Forecasting is a key role for preventing and preparing the public to combat it. Meteorological forecasting is a key approach to the problem that uses numerous practices. Some of the most well-known are Regressions analysis and Neural Networks. Both use historical datasets in order to determine forthcoming pollution levels. For Neural Networks the LSTMs, Conv1D and Transformers are some of the best tools to tackle such important issues. This paper presents an alternative solution for time series prediction for air pollution using a BiLSTM-Conv1D neural network which rivals other models on their performance.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129365580","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}