International Journal of Intelligent Information and Database Systems最新文献

Development of Wearable Embedded Hybrid Powered Energy Sources for Mobile Phone Charging System 用于手机充电系统的可穿戴嵌入式混合电源的研制

International Journal of Intelligent Information and Database Systems Pub Date : 2023-05-24 DOI: 10.11648/j.ijiis.20231202.11

Asianuba Ifeoma Benardine, Ezeofor Chukwunazo Joseph, Musa Martha Ozohu, U. Chidiebere

{"title":"Development of Wearable Embedded Hybrid Powered Energy Sources for Mobile Phone Charging System","authors":"Asianuba Ifeoma Benardine, Ezeofor Chukwunazo Joseph, Musa Martha Ozohu, U. Chidiebere","doi":"10.11648/j.ijiis.20231202.11","DOIUrl":"https://doi.org/10.11648/j.ijiis.20231202.11","url":null,"abstract":": Mobile phones are an essential part of our day to day living. The increased reliance on mobile phone devices for communication, information sharing, connectivity and entertainment calls for a greater need to keep this device in a functional condition at all times. The epileptic nature of utility power supply, non-accessibility to power in remote locations and affordability of power due to high tariffs calls for a relative option to maintain connectivity of mobile phones. This research proposes to develop wearable embedded powered energy sources for charging mobile phones as a backup for instant and seamless charging of the phone battery once it drains. Our research addresses the inability of mobile phone users to charge their flatten phone batteries conveniently and seamlessly anytime and anywhere they find themselves. The hybrid powered charging system has the ability to harvest dissipated heat within the body of the phone and heat sources from the environment using an energy harvester, alongside the second energy source provided by the solar panel. The energy harvester will serve as a cooling measure to the device to maintain a stable temperature. The entire embedded device not only serves as an alternative power supply but also a protective covering to the mobile phone.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"72 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84554498","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

Applying the Self-Organizing Map in the Classification of 195 Countries Using 32 Attributes 自组织地图在195个国家32个属性分类中的应用

International Journal of Intelligent Information and Database Systems Pub Date : 2023-03-28 DOI: 10.11648/j.ijiis.20231201.12

Adebayo Rotimi Philip

{"title":"Applying the Self-Organizing Map in the Classification of 195 Countries Using 32 Attributes","authors":"Adebayo Rotimi Philip","doi":"10.11648/j.ijiis.20231201.12","DOIUrl":"https://doi.org/10.11648/j.ijiis.20231201.12","url":null,"abstract":": Many organizations such as World Bank, UN, Wikipedia and others have tried to classify countries as under-developed, developing, developed and highly developed countries based on certain criteria but these criteria aren’t robust enough. In most cases, they used one to three criteria. This research classified 195 countries using 32 attributes (features/ criteria) with the self-organizing map (SOM) algorithm. This is a robust classification because 32 features are considered for the classification. SOM is an unsupervised learning algorithm which reduces high dimensional data to 2 dimensions. The SOM classifies the 195 countries into 5 categories, implying that it is possible to classify countries with SOM algorithm. There is no benchmark to measure the accuracy of the SOM algorithm because most classifications are based on at most three criteria which are not robust enough, but comparing the results of the SOM algorithm with these weak classifications still show the flawlessness of the SOM algorithm. This research will help scientist, students, lecturers, teachers, organizations and countries to have a robust knowledge about the state of their countries from an unbiased position and will also help organizations and countries to make concrete decisions about business establishment in viable places all over the world. The key limitation is the reliability of the data and the number of attributes, which could be increased in future researches for better results.","PeriodicalId":39658,"journal":{"name":"International Journal of Intelligent Information and Database Systems","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75517885","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

Artificial Intelligence Chatbot Advisory System 人工智能聊天机器人咨询系统

International Journal of Intelligent Information and Database Systems Pub Date : 2023-03-21 DOI: 10.11648/j.ijiis.20231201.11

Chidi Ukamaka Betrand, Oluchukwu Uzoamaka Ekwealor, Chinazo Juliet Onyema

引用次数: 1

A fire detection and localisation method based on keyframes and superpixels for large-space buildings 基于关键帧和超像素的大空间建筑火灾探测与定位方法

International Journal of Intelligent Information and Database Systems Pub Date : 2023-01-01 DOI: 10.1504/ijiids.2022.10048691

Qiansheng Fang, Zhuang Peng, P. Yan, Jing Huang

引用次数: 1

Deep belief bi-directional LSTM network-based intelligent student's performance prediction model with entropy weighted fuzzy rough set mining 基于熵加权模糊粗糙集挖掘的深度信念双向LSTM网络智能学生成绩预测模型

International Journal of Intelligent Information and Database Systems Pub Date : 2023-01-01 DOI: 10.1504/ijiids.2023.10055118

N. Sateesh, P. Rao, Davuluri Rajya Lakshmi

引用次数: 0

Intelligent computational techniques of machine learning models for demand analysis and prediction 用于需求分析和预测的机器学习模型的智能计算技术

International Journal of Intelligent Information and Database Systems Pub Date : 2023-01-01 DOI: 10.1504/ijiids.2022.10051510

G. NaveenSundar, K. A. Xavier, D. Narmadha, K. Sagayam, A. A. Jone, M. Pomplun, Hien Dang

引用次数: 0

Natural language generation from Universal Dependencies using data augmentation and pre-trained language models 使用数据增强和预训练的语言模型从通用依赖生成自然语言

International Journal of Intelligent Information and Database Systems Pub Date : 2023-01-01 DOI: 10.1504/ijiids.2023.10053426

T. Tran, Dang Tuan Nguyen

引用次数: 1

An incremental clustering using bat-spotted hyena optimiser with spark framework 一个使用蝙蝠斑鬣狗优化器和spark框架的增量集群

International Journal of Intelligent Information and Database Systems Pub Date : 2023-01-01 DOI: 10.1504/IJIIDS.2023.131414

Ch. Vidyadhari, N. Sandhya, N. Ramakrishnaiah

引用次数: 0

A collaboration of an ontology and an autoregressive model to build an efficient chatbot model 基于本体和自回归模型的高效聊天机器人模型构建

International Journal of Intelligent Information and Database Systems Pub Date : 2023-01-01 DOI: 10.1504/ijiids.2023.10059348

Pham Minh Thu Do, Ngoc Tram Anh Nguyen, Dang Huu Trong Ho, Thi Thanh Sang Nguyen

引用次数: 0

An adaptive fuzzy weight algorithm for the class imbalance learning problem 一类不平衡学习问题的自适应模糊权重算法

International Journal of Intelligent Information and Database Systems Pub Date : 2023-01-01 DOI: 10.1504/ijiids.2023.10058648

Tran Dinh Khang, Vo Duc Quang

引用次数: 0