CIIS

Often, producing large labelled datasets for supervised machine learning is difficult and expensive. In cases where the expensive part is due to labelling and obtaining ground truth, it is often comparably easy to acquire large datasets containing ...

Non-Intrusive Load Monitoring (NILM) is a technique that aims to estimate the energy consumption and operational status of individual appliances in a building by analyzing only the aggregate power usage data. This technique plays a crucial role in demand-...

The plastic industry plays a vital role in Thailand, with a significant dependence on plastic materials for a majority of industrial products. Among the various types of plastics, polypropylene (PP) emerges as the most extensively used, making it ...

Data-driven design for cities is improving the quality of everyday life of citizens and optimizes the usage of resources. A new aspect is artificial intelligence, which Smart Cities could greatly benefit from. A central problem for urban designers is ...

Social media has emerged as a significant source of big data, offering a vast amount of social data and evidence. However, much of this data remains untapped and underutilized. Nowadays, various organizations, including corporations, government agencies, ...

The present article applies unsupervised machine learning approach to identify patterns of dependence in data of biomarkers, cognitive and demographic characteristics useful for the diagnosis and treatment planning of Alzheimer disease. Two important ...

The present study seeks to improve upon the study conducted, with the researchers employing a different depth estimation computation method and an enhanced object detection model. The constituents will use their captured data with the OpenCV library to ...

A well-known combinatorial optimization issue called The Traveling Salesman issue (TSP) has applications in many fields, including drone-based delivery and monitoring systems. In this study, we examine the effectiveness of three distinct implementations ...

Energy is one of the most important topics in the modern world, as it affects various aspects of human life and the environment. The current transition era and the growing demand for energy require innovative solutions to optimize energy use and reduce ...

In recent years, wind farm layout optimization problem (WFLOP) using evolutionary algorithms has become a popular research area. However, there still lack of comparative study of effective improvement strategies for evolutionary algorithm on WFLOP. To ...

Forecasting models are used to produce Energy Planning Models (EPMs) in developing renewable energy farms. One such application is the forecasting of daily global solar radiation, which is the energy being converted into PV power. In this study, results ...

This study discussed text analysis for the preservation of minority languages. Text analysis consists of some steps for the analysis of parsing, etc., but word segmentation is necessary before their advanced analysis. We then focused on word ...

Using an AED can help patients recover normal functioning after experiencing cardiac arrhythmia, cardiac arrest, or loss of consciousness. Patients can be saved from sudden cardiac arrest by it. If the patient receives urgent help, the chances of ...

In the last years, one of the fields of artificial intelligence that has been investigated the most is nature-inspired computing. The research done on this specific topic showcases the interest that sparks in researchers and practitioners, who put their ...

Feature selection has been widely applied in machine learning applications to reduce computational time, improve learning accuracy, and better understand the data modeling process. One of the vital challenges is the correct selection of the relevant ...

This study focused on developing models for detecting fatigue in students using action units during conducting online classes. A multi-layered neural network was used as a classifier for the dataset and the parameters included were blinking frequency, ...

The usual way to quantify the performance of a novel algorithm in the field of classification, especially in time series anomaly detection, is to compare its performance against selected baseline competitors on selected data sets. There is a common ...

The most common application of artificial immune networks (AINs) is on unsupervised learning tasks. This is due to the fact that AINs are inspired by the adaptive immune system, which consists of a network of antibodies that self-organises to form a ...

YOLO is one of the most efficient algorithms that can be used for object detection in computer vision. In this study, the researchers used the YOLOv7 model to detect water hyacinths and other non-living things found in the Pasig River, Philippines. The ...

Image Scenario classification is widespread for many IoT applications. Classifying scenario helps in making proper decisions. The study aims at classifying six different scenarios using a deep neural network algorithm. The proposed InceptionV3 ...

Early diagnosis is beneficial for treating Colorectal Cancer (CRC) and can improve its curability. The traditional methods of CRC diagnosis generally rely on pathologists, but with the increasing number of CRC patients, manual diagnosis has many ...

At the moment, 2.01 billion tons of solid trash are produced annually in all cities throughout the world. Based on research findings, a typical person generates approximately 0.74 kilograms of garbage on a daily basis. The researchers decided to help the ...

The unified user profiles (UUPs) include the creation of a single account to keep all data about a user across numerous platforms or websites. This data may contain sensitive information such as private details, preferences, and authentication ...

The affordable transaction fee is crucial in establishing sustainable decentralized social media. Decentralized applications powered by smart contract blockchain rely on nodes (validators) to process transactions. The incentives in terms of fees are ...

EinStein würfelt nicht! (abbr. EWN) is a stochastic game with a die rolled in each ply which makes it full of uncertainty. It does not look easy to design a good game engine using traditional alpha-beta-based approaches. In this paper, an EWN game ...

Indoor positioning is a critical technology with a broad spectrum of applications spanning from navigation systems in smart buildings to asset tracking in industrial environments. This research paper explores the effectiveness of four prominent ...

Decentralized blockchain-based social media (BSM) applications require different moderation strategies that suit the business models. Conventional social media uses centralized universal moderation strategies, which are human-extensive and time-...