Proceedings of the 26th Pan-Hellenic Conference on Informatics最新文献

Analyzing the impact and application of Augmented Reality in Education: The case of students with special educational needs 增强现实技术在教育中的影响与应用分析——以特殊教育需求学生为例

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3575999

Andrianthi Kapetanaki, Akrivi Krouska, C. Troussas, C. Sgouropoulou

引用次数: 0

An MDP approach to transmission scheduling in WPCN networks WPCN网络传输调度的MDP方法

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3575988

M. Koutsioumpos, E. Zervas, Efstathios Hadjiefthymiades, L. Merakos

引用次数: 0

Quantum Key Distribution: Basic Protocols and Threats 量子密钥分发:基本协议和威胁

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3576022

Maria Sabani, I. Savvas, D. Poulakis, Georgios C. Makris

引用次数: 1

Modular, low-cost, open-source lab platform for Electronic Engineering & Mechatronics 模块化、低成本、开源的电子工程与机电一体化实验室平台

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3575991

Ioannis G. Chaidoulis, N. Karanikolas, Sarantos Psycharis

引用次数: 0

Research of Implementation Methods for Quantum Machine Learning and Their Development on QPU 量子机器学习实现方法的研究及其在QPU上的发展

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3576023

V. Potapov, S. Gushanskiy

引用次数: 0

On the Effective Representation of Quantum Data for Classical Machine Learning Problems 经典机器学习问题中量子数据的有效表示

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3576021

I. Savvas, Andrey Chernov, O. Kartashov, G. Beliavsky, M. Butakova

{"title":"On the Effective Representation of Quantum Data for Classical Machine Learning Problems","authors":"I. Savvas, Andrey Chernov, O. Kartashov, G. Beliavsky, M. Butakova","doi":"10.1145/3575879.3576021","DOIUrl":"https://doi.org/10.1145/3575879.3576021","url":null,"abstract":"There is no doubt that quantum computing has opened up new horizons and perspectives in many fields, including scientific research. With the advancement of technology and quantum computers, we can now conduct new kinds of scientific experiments: observing quantum properties of individual systems, atoms, electrons and photons as well as influencing and controlling quantum systems. Quantum mechanics describes the properties of quantum systems by their quantum states. Unlike in classical mechanics, quantum states themselves cannot be directly observed in experiments, so many-body dynamics mathematical simulations are useful. Even though many-body dynamics problems can be solved for limited cases, but when we consider real-world pieces of matter this leads to computation-intensive calculations that are beyond classic digital computers. The memory and time needed to describe the quantum state of a many-body system scales exponentially with the size of the system. This has led physics communities to focus their attention on the algorithms underlying modern machine learning with the goal of making progress in quantum matter research. As a consequence, the successful application of machine learning requires effective and informative data representation. This paper discusses some novel aspects of applying classical machine learning algorithms to quantum data derived from measurements associated with quantum systems in many-body simulation problems. In this paper, we investigate and experimentally demonstrate one of the effective methods of the quantum data representation suited for the classical machine learning applications based on quantum classical shadows.","PeriodicalId":164036,"journal":{"name":"Proceedings of the 26th Pan-Hellenic Conference on Informatics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124165207","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}

引用次数: 0

Prototyping a Digital Twin System for Environmental Education 环境教育数字孪生系统原型设计

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3576018

Andreas Komninos, Georgios Tsigkas

{"title":"Prototyping a Digital Twin System for Environmental Education","authors":"Andreas Komninos, Georgios Tsigkas","doi":"10.1145/3575879.3576018","DOIUrl":"https://doi.org/10.1145/3575879.3576018","url":null,"abstract":"Our time is characterized by big sprawling urban complexes that a majority of the human population chooses to live where interactions with the environment seem to be vanishing from our day to day lives. Our relationship with the planet’s natural ecosystem is paramount to our survival and well-being, a relationship that begins to form during our childhood years. Considering the above we propose a novel system which aims to give the ability to children to interact with the natural environment even when they have no access to it, from the classrooms in which they spend considerable parts of their lives. Specifically the proposed system is based on the technology of the Digital Twin, a core pillar of the 4th Industrial Revolution, and is comprised of a smart birdhouse and an electronic Digital Twin. The smart birdhouse can be deployed in a natural environment and collect atmospheric data like humidity and temperature values as well as record audio and pictures of possible bird visitors. At the same time the collected data will be available to the end user through a dashboard platform for atmospheric parameters and the digital electronic twin which will play the collected sound or pictures. With the above system we aim to achieve a greater and meaningful engagement of children with their natural habitat even when their urban environment makes it impractical or unfeasible.","PeriodicalId":164036,"journal":{"name":"Proceedings of the 26th Pan-Hellenic Conference on Informatics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127915451","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}

引用次数: 0

A combination of a Proximity technique and Weighted average for LP Problems LP问题的接近技术与加权平均的结合

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3575990

Dimitris G. Tsarmpopoulos, Eirini I. Nikolopoulou, Christina D. Nikolakakou, G. Androulakis

引用次数: 1

An exact based approach for the Post Enrollment Course Timetabling Problem 入学后课程排课问题的一种基于精确的方法

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3575970

Angelos Dimitsas, Vasileios Nastos, Christos G Gogos, Christos Valouxis

引用次数: 0

Developing a Domain-Specific Lexicon for the Greek Language 为希腊语开发一个特定领域的词典

Proceedings of the 26th Pan-Hellenic Conference on Informatics Pub Date : 2022-11-25 DOI: 10.1145/3575879.3576004

Kyriakos Skoularikis, I. Savvas, G. Garani, George Kakarontzas

{"title":"Developing a Domain-Specific Lexicon for the Greek Language","authors":"Kyriakos Skoularikis, I. Savvas, G. Garani, George Kakarontzas","doi":"10.1145/3575879.3576004","DOIUrl":"https://doi.org/10.1145/3575879.3576004","url":null,"abstract":"We live in a society where a massive quantity of data is generated daily on online social network platforms. This enormous data contains vital opinion-related information that many companies and other scientific and commercial industries are trying to exploit for their benefits. For that purpose, sentiment analysis is required. Sentiment analysis or opinion mining is the branch of data analytics for extracting sentiments from messages expressed by users on a particular subject. Although, in the past years a considerable research has been made for the English language, the works of Sentiment Analysis in Greek language is not so popular, due to smaller user base. In this work, we provide a method to create domain-specific dictionaries given a corpus of tweets in the Greek language. In those Lexicons, we take into consideration the significance of each word for the specific domain, by introducing a new attribute Weightw. Also, we deploy a hybrid framework which utilizes the newly created domain-specific Lexicon with the Naïve Bayes classifier to analyze and predict the sentiment of each tweet. Our framework has the ability to merge the better of the two basic concepts, the Lexicon and Machine Learning method, and demonstrates the significance of the words for domain-specific Lexicon, for achieving optimal results when performing Sentiment Analysis.","PeriodicalId":164036,"journal":{"name":"Proceedings of the 26th Pan-Hellenic Conference on Informatics","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124578876","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}

引用次数: 0