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Technologies, Volume 12, Issue 1

January 2024 - 12 articles

Cover Story: Cognitive decline poses a public health challenge; thus, early detection is crucial to initiate timely interventions and improve patient outcomes. However, conventional diagnosis methods often rely on personal interpretations or biases, may not detect the early stages of cognitive decline, or involve invasive procedures. Our paper addresses this gap by presenting a non-invasive solution using deep neural networks to detect the higher fragmentation of daily life activity from wearable and IoT devices data and graph learning to analyze the structural well-being information of assessment questionnaires. The evaluation, conducted in a simulated environment with a large synthetic dataset, demonstrates the potential of our approach as a supportive tool for early cognitive decline detection in patient assessments. View this paper
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Articles (12)

  • Article
  • Open Access
6 Citations
3,548 Views
26 Pages

Multi-Arm Trajectory Planning for Optimal Collision-Free Pick-and-Place Operations

  • Daniel Mateu-Gomez,
  • Francisco José Martínez-Peral and
  • Carlos Perez-Vidal

This article addresses the problem of automating a multi-arm pick-and-place robotic system. The objective is to optimize the execution time of a task simultaneously performed by multiple robots, sharing the same workspace, and determining the order o...

  • Article
  • Open Access
11 Citations
13,466 Views
28 Pages

In recent years, drones have become increasingly popular tools in criminal investigations, either as means of committing crimes or as tools to assist in investigations due to their capability to gather evidence and conduct surveillance, which has bee...

  • Article
  • Open Access
9 Citations
3,898 Views
16 Pages

A Miniaturized Antenna for Millimeter-Wave 5G-II Band Communication

  • Manish Varun Yadav,
  • Chandru Kumar R,
  • Swati Varun Yadav,
  • Tanweer Ali and
  • Jaume Anguera

This article introduces a miniaturized antenna for 5G-II band millimeter-wave communication. The antenna’s performance is meticulously examined through comprehensive simulations carried out using CST Microwave Studio, employing an FR-4 substrat...

  • Article
  • Open Access
3 Citations
3,854 Views
22 Pages

In contemporary society, “Indoor Generation” is becoming increasingly prevalent, and spending long periods of time indoors affects well-being. Therefore, it is essential to research biophilic indoor environments and their impact on occupa...

  • Article
  • Open Access
14 Citations
4,590 Views
16 Pages

Towards a Bidirectional Mexican Sign Language–Spanish Translation System: A Deep Learning Approach

  • Jaime-Rodrigo González-Rodríguez,
  • Diana-Margarita Córdova-Esparza,
  • Juan Terven and
  • Julio-Alejandro Romero-González

People with hearing disabilities often face communication barriers when interacting with hearing individuals. To address this issue, this paper proposes a bidirectional Sign Language Translation System that aims to bridge the communication gap. Deep...

  • Article
  • Open Access
1 Citations
2,499 Views
18 Pages

This paper proposes extended-window algorithms for model prediction and applies them to optimize hybrid power systems. We consider a hybrid power system comprising solar panels, batteries, a fuel cell, and a chemical hydrogen generation system. The p...

  • Review
  • Open Access
7 Citations
3,909 Views
39 Pages

This manuscript provides a comprehensive exploration of Probabilistic latent semantic analysis (PLSA), highlighting its strengths, drawbacks, and challenges. The PLSA, originally a tool for information retrieval, provides a probabilistic sense for a...

  • Article
  • Open Access
25 Citations
7,263 Views
23 Pages

A Novel Machine Learning-Based Prediction Method for Early Detection and Diagnosis of Congenital Heart Disease Using ECG Signal Processing

  • Prabu Pachiyannan,
  • Musleh Alsulami,
  • Deafallah Alsadie,
  • Abdul Khader Jilani Saudagar,
  • Mohammed AlKhathami and
  • Ramesh Chandra Poonia

Congenital heart disease (CHD) represents a multifaceted medical condition that requires early detection and diagnosis for effective management, given its diverse presentations and subtle symptoms that manifest from birth. This research article intro...

  • Article
  • Open Access
3 Citations
4,034 Views
15 Pages

Graph Learning and Deep Neural Network Ensemble for Supporting Cognitive Decline Assessment

  • Gabriel Antonesi,
  • Alexandru Rancea,
  • Tudor Cioara and
  • Ionut Anghel

Cognitive decline represents a significant public health concern due to its severe implications on memory and general health. Early detection is crucial to initiate timely interventions and improve patient outcomes. However, traditional diagnosis met...

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Technologies - ISSN 2227-7080Creative Common CC BY license