Search Results (373)

Background: Traditionally, auditory rehabilitation in people with hearing loss has sought training in auditory skills to achieve an understanding of sound messages for communication. Assistive or supportive technology is limited to hearing aids that transmit sound through the air or bone to be used by the individual, and only in recent times have technologies for rehabilitation, of high cost and difficult access, begun to be used, employed by audiology professionals. Objective: The objective of this study was to compile the evidence reported in the literature on the use of technology in auditory rehabilitation for the improvement of hearing skills in people with hearing loss, beyond hearing aids and cochlear implants. Method: A systematic review of the literature was conducted between 2018 and 2024 in PubMed, Scopus, and Web of Science databases, using as search terms Technology AND “Auditory Rehabilitation” validated in DeCS and MeSH thesauri; the PICO method was used to propose the research question, and the PRISMA strategy was used for the inclusion or exclusion of the articles to be reviewed. Results: In the first search, 141 documents were obtained. Subsequently, inclusion criteria, such as development with vibrotactile stimulation, Information and Communication Technologies (ICTs), among others, and exclusion criteria, such as those related to cochlear implants and air conduction hearing aids, were applied, and finally, articles related to natural language processing, and other systematic reviews were excluded so that the database was reduced to 14 documents. To this set, due to their relevance, two papers were added, for a total of sixteen analyzed. Conclusions: There are solutions ranging from the use of smartphones for telehealth to solutions with multiple technologies, such as the development of virtual environments with vibrotactile feedback. Hearing-impaired people and even professionals in this area of healthcare have a high level of acceptance of the use of technology in rehabilitation. Finally, this article highlights the crucial role of technology in auditory rehabilitation, with solutions that improve hearing skills and the positive acceptance of these tools by patients and audiology professionals. Full article

In the context of increasing digitization, integrating ICT technologies, artificial intelligence, and remote working is altering residential mobility patterns and housing preferences. This study examines the housing market’s impact, focusing on how residential affordability affects residential choices, using a case study of the Metropolitan City of Florence. The analysis employs a methodology centered on the Debt-to-Income Ratio (DTI), which cross-references real estate market values (source: Agenzia delle Entrate and leading real estate portals) with household income brackets to identify affordable areas. The results reveal a clear divide: households with incomes below EUR 26,000 per year (representing about 69% of the population) are excluded from the central urban property market. This evidence confirms regional and national trends, emphasizing a growing mismatch between housing costs and disposable incomes. The study concludes that affordability is a technical–financial parameter and a valuable tool for supporting inclusive urban planning. Its application facilitates the orientation of effective public policies and the identification of socially sustainable housing solutions. Full article

The demographic shift toward an aging population calls for innovative strategies to ensure independence, health, and quality of life in later years. In this context, Ambient Assisted Living (AAL) solutions, supported by Information and Communication Technologies (ICTs), offer promising advances for non-invasive and continuous support. Commonly, ICTs are evaluated only from the perspectives related to key performance indicators (KPIs); nevertheless, the design and implementation of such technologies must account for important psychological, social, and ethical dimensions. Radar-based sensing systems are emerging as an option due to their unobtrusive nature and capacity to operate without direct user interaction. This work explores how radar technologies, particularly those operating in the millimeter wave (mmWave) spectrum, can provide core key value indicators (KVIs) essential to aging societies, such as human dignity, trustworthiness, fairness, and sustainability. Through a review of key application domains, the paper illustrates the practical contributions of mmWave radar in Ambient Assisting Living (AAL) contexts, underlining how its technical attributes align with the complex needs of elderly care environments and produce value for society. This work uniquely integrates key value indicator (KVI) frameworks with mmWave radar capabilities to address unmet ethical needs in the AAL domain. It advances existing literature by proposing a value-driven design approach that directly informs technical specifications, enabling the alignment of engineering choices with socially relevant values and supporting the development of technologies for a more inclusive and ethical society. Full article

Decision-making is a fundamental challenge in science and engineering, mainly when subjective factors influence the process. This paper introduces a decision support model based on the Analytic Hierarchy Process (AHP) that was specifically adapted for binary decisions and we term Binary AHP. The model facilitates structured decision-making when evaluating two opposing alternatives, such as yes/no scenarios. To demonstrate its applicability, we applied the Binary AHP model to a real-world case in the Brazilian public sector, where agencies must determine whether a technological solution qualifies as an Information and Communication Technology (ICT) solution. This classification is crucial since it directly impacts procurement policies and regulatory compliance. Our results show that Binary AHP enhanced the decision consistency, transparency, and reproducibility, and reduced the subjective discrepancies between the evaluators. Additionally, by inverting the priority vectors, the model allowed for a comparative analysis of both decision alternatives, thus offering more profound insights into the classification process. This study highlights the flexibility of AHP-based decision support methodologies and proposes a structured approach to refining binary decision frameworks in complex, multi-criteria environments. Full article

Small and medium-sized enterprises (SMEs) face unique challenges that can be effectively addressed through the adoption of data mining and business intelligence (BI) tools. This systematic literature review scrutinizes the deployment and efficacy of BI and data mining technologies across SME sectors, assessing their impact on operational efficiency, strategic decision-making, and market competitiveness. Therefore, drawing from a methodologically rigorous analysis of 93 scholarly articles published between 2014 and 2024, the review elucidates the evolving landscape of BI tools and techniques that have shaped SME practices. It reveals that advanced analytics such as predictive modeling and machine learning are increasingly being adopted, though significant gaps remain, particularly shaped by economic factors. The utilization of BI and data mining enhances decision-making processes and enables SMEs to adapt effectively to market dynamics. Despite these advancements, SMEs encounter barriers such as technological complexity, high implementation costs, and substantial skills gaps, impeding effective utilization. Our review, grounded in the analysis of business intelligence tools used indicates that dashboards (31.18%) and clustering techniques (10.75%) are predominantly utilized, highlighting their strategic importance in operational settings. However, a considerable number of studies (66.67%) do not specify the BI tools or data mining techniques employed, pointing to a need for more detailed methodological transparency in future research. The predominant focus on the ICT and manufacturing sectors underscores the industrial context sector specific applicability of these technologies, with ICT accounting for 45.16% and manufacturing 22.58% of the studies. We advocate for targeted educational programs, development of user-friendly and cost-effective BI solutions, and strategic partnerships to facilitate knowledge transfer and technological empowerment in SMEs. Empirical research validating the impacts of BI and data mining on SME performance is crucial, providing a directional pathway for future academic inquiries and policy formulation. Full article

This paper addresses the critical issue of selecting the optimal solar tracking configuration for maximum energy generation, given the increasing demand for sustainable energy solutions in information and communication technology (ICT) facilities. The main goal is to thoroughly evaluate and compare seven different solar tracking configurations across technical, economic, and environmental dimensions: No Tracking (NT), Monthly Adjusted Horizontal Axis (MAHA), Weekly Adjusted Horizontal Axis (WAHA), Daily Adjusted Horizontal Axis (DAHA), Continuously Adjusted Horizontal Axis (CAHA), Continuously Adjusted Vertical Axis (CAVA), and Dual Axis with Continuous Adjustment (DACA). This study utilizes the HOMER simulation program to evaluate its energy and hydrogen production, emissions, and cost-effectiveness performance. Key findings indicate solar tracking improves energy efficiency, with optimal capacity factors of 18.2% and 17.7% for CAHA and DAHA configurations, respectively. Although load-following strategies increase reliability, there is a trade-off between capital costs and energy costs. In addition, an MCDM approach helps to consolidate the evaluation, resulting in CAVA being ranked as the most preferable option. The study contributes to informed decision-making for energy systems in ICT facilities by emphasizing the significance of considering a variety of criteria and evaluation techniques to address complex energy challenges. Full article

This study examined the socioeconomic factors that influence the adoption of information and communication technologies (ICTs) in enhancing farm productivity among farmers in Ba Province, Fiji. A structured questionnaire survey was administered to a sample of 320 randomly selected farmers across the province’s 16 mainland districts. The analysis demonstrated that, although farmers possessed conventional ICTs, there was no direct correlation between ownership and actual utilisation. Significant determinants affecting ICT use were identified as education, experience, type of farming, and business model. These findings underscore critical implications for both policy and theoretical frameworks, emphasising essential factors to consider in the implementation of ICT solutions for agricultural practitioners. Full article

The use of iteration is fundamental in the field of design, as it allows for the exploration of multiple options and the development of innovative solutions. This research analyzes how iteration, combined with Information and Communications Technology (ICT), especially 3D printing, facilitates the development of creativity in higher-level students, specifically Industrial Designers. A qualitative approach was employed, using an action-research methodological strategy with a field journal to document student activities during the iterative process. The results indicate that group dynamics enhance iteration by facilitating the exchange of ideas; therefore, the incorporation of activities that adopt constant feedback is necessary to refine initial concepts and integrate new perspectives. Additionally, the use of technology, such as 3D printing, drives the creative process by encouraging students to continue developing their ideas through physical iteration, allowing them to materialize and improve their concepts. The creative process only needs to be stimulated through different methodological strategies, both analog and digital, in and outside the classroom, with the use of technologies as essential learning tools. Full article

Chemical doping is a well-established technique for increasing the electrical conductivity of polyconjugated polymers, and its effectiveness can be assessed through IR spectroscopy, thanks to the rise of the so-called IRAVs (infrared activated vibrations), which prove the formation of polarons on the polymer chain. While the mechanism of the IRAVs activation has been widely explored in the past, several peculiar features remain unclear. Changes in the Raman spectrum of doped polymers (RaAV, Raman activated vibrations) are widely used as well for monitoring the doping process, but the interpretation is often limited to purely empirical correlations. By means of an experimental campaign on doped regio-regular poly(3-hexylthiophene-2,5-diyl) (P3HT) samples in chloroform solution and on the solid samples cast from the same solutions, this paper presents for the first time a thorough comparative analysis of IRAVs and RaAVs, aiming at a unified description of the structure of doped P3HT. In particular, we will discuss the effect of the doping level on the vibrational features of the polymer and the dopant so that spectroscopic markers can be found to be used in the identification of the presence of ICT (integer charge transfer) complexes in different doping regimes. This study demonstrates that combining IR, Raman, and UV-Vis-NIR spectroscopies provides a powerful, complementary set of tools to diagnose not only the doping level but also the detailed molecular and supramolecular structure of the doped P3HT, useful for the development of structure/properties relationships in the perspective of the optimization of the charge transport performances. Full article

This study presents analysis and optimization of a standalone hybrid renewable energy system (HRES) for Adama Science and Technology University’s ICT center in Ethiopia. The proposed hybrid system combines photovoltaic panels, wind turbines, a battery bank, and a diesel generator to ensure reliable and sustainable power. The objectives are to minimize the system’s total annualized cost and loss of power supply probability, while energy reliability is maintained. To optimize the component sizing and energy management strategy of the HRES, we formulated a mathematical model that incorporates the variability of renewable energy and load demand. This optimization problem is solved using a hybrid genetic algorithm (HGA). Simulation results indicate that the HGA yielded the best solution, characterized by the levelized cost of energy of USD 0.2546/kWh, the loss of power supply probability of 0.58%, and a convergence time of 197.2889 s. Full article

β-galactosidase (β-Gal) has emerged as a pivotal biomarker for the comprehensive investigation of diseases associated with cellular senescence. The development of a fluorescent sensor is of considerable importance for precisely detecting the activity and spatial distribution of β-Gal. In this study, we developed two excited-state-altering responsive fluorescent sensors (TF1 and TF2) for ratiometric detection of β-Gal. Two TCF dyes, composed of tricyanofuran (TCF) and naphthol units, feature electron “pull–push” systems and are quenched fluorescence by β-Gal. Upon β-Gal hydrolysis, a significant ratiometric shift in absorption from ca. 475 nm to 630 nm is observed, accompanied by the emergence of a fluorescence signal at ca. 660 nm. The enzyme-responsive optical red-shifts are attributed to the excited-state transition from intramolecular charge transfer (ICT) state to local excited (LE) state, which was confirmed by density functional theory (DFT) calculations. Both fluorescent sensors display exceptional sensitivity and selectivity for the response of β-Gal in PBS solution and are capable of tracking β-Gal within senescent A549 cells. This study introduces a framework for developing multimodal optical probes by systematically modulating excited-state properties, demonstrating their utility in senescence studies, diagnostic assay design, and therapeutic assessment. Full article

With the advent of Industry 5.0, the electrical sector has been endowed with intelligent devices that are propelling high penetration of distributed energy microgeneration, VPP, smart buildings, and smart plants and imposing new challenges on the sector. This new environment requires a smarter network, including transforming the simple electricity customer into a “smart customer” who values the quality of energy and its rational use. The SPG (smart power grid) is the perfect solution for meeting these needs. It is crucial to understand energy use to guarantee quality of service and meet data security requirements. The use of simulations to map the behavior of complex infrastructures is the best strategy because it overcomes the limitations of traditional analytical solutions. This article presents the ICT laboratory structure developed within the Department of Electrical Engineering of the Polytechnic School of the Universidade de São Paulo (USP). It is based on an architecture that utilizes LTE/EPC wireless technology (4G, 5G, and B5G) to enable machine-to-machine communication (mMTC) between SPG elements using edge computing (MEC) resources and those of smart city platforms. We evaluate this proposal through simulations using data from real and emulated equipment and co-simulations shared by SPG laboratories at POLI-USP. Finally, we present the preliminary results of integration of the power laboratory, network simulation (ns-3), and a smart city platform (InterSCity) for validation and testing of the architecture. Full article

Contemporary ports are facing a variety of challenges due to technological advancements, economic pressures, and changing policies. Key issues include the effects of globalization, rapid advancements in information and communication technologies (ICTs), and the changing nature of port services. In order to tackle these challenges and achieve operational excellence, adapt to the shifting of activities, and meet new business demands, smart ports have been proposed as a comprehensive solution. These challenges arise because port success is often measured by traditional metrics such as port size and performance. To accurately assess the intelligence of a port, there is a need for a systematic and scientifically sound smart port evaluation method. This paper provides an overview of the concept of a smart port and develops a multi-criteria assessment framework of port smartness based on neutrosophic cognitive maps (NCMs). The unique and valuable characteristic of NCMs lies in their ability to manage the uncertainty associated with the relationship between two concepts, indicating their effects on each other in neutral states. This structure enables the NCM to provide results with a greater degree of sensitivity than fuzzy cognitive maps (FCMs) and allows for a greater degree of freedom of intuition for an expert to express not only the potential impacts but also the uncertainty associated with those impacts. Our methodology can make decisions using incomplete, uncertain, and inconsistent data during the assessment process, providing a rigorous quantitative framework for the assessment of port “smartness”. The proposed solution has the potential to act as a valuable tool in a group decision support environment and can be used to accelerate an organization’s development, improve productivity, and reinforce efforts to achieve strategic and sustainability objectives. To achieve this, an appropriate framework for such a methodology is demonstrated through an illustrative example offering actionable insights for improving port operations. Full article

Indium phosphide (InP) semiconductor technology is being explored for radiofrequency (RF) applications, targeting frequencies exceeding 100 GHz, to support the next generation of 6G communication systems. When taking into account sustainability in designing this future generation, growing concerns are emerging regarding the environmental impact of communication networks and the reliance on raw materials for the production of Information and Communication Technologies (ICTs). The extraction, processing, and manufacturing of such materials and semiconductor technologies result in environmental impacts, but these impacts remain insufficiently documented. Firstly, this study evaluates the environmental impacts of manufacturing indium phosphide (InP) wafers based on industrial data and those of InP-based heterojunction bipolar transistors (HBTs) based on early-stage research data. Secondly, this study attempts to highlight the challenges posed by the increasing demand for high-tech solutions, involving raw materials, by evaluating the potential demand for indium for RF 6G applications, with a deployment scenario. Full article

Precision beekeeping focuses on ICT approaches to collect data through various IoT solutions and systems, providing detailed information about individual bee colonies and apiaries at a local scale. Since the flight radius of honeybees is equal to several kilometers, it is essential to explore the specific conditions of the selected area. To address this, the aim of this study was to explore the potential of using crowdsourced data combined with geographic information system (GIS) solutions to support beekeepers’ decision-making on a larger scale. This study investigated possible methods for processing open geospatial data from the OpenStreetMap (OSM) database for the environmental analysis and assessment of the suitability of selected areas. The research included developing methods for obtaining, classifying, and analyzing OSM data. As a result, the structure of OSM data and data retrieval methods were studied. Subsequently, an experimental spatial data classifier was developed and applied to evaluate the suitability of territories for beekeeping. For demonstration purposes, an experimental prototype of a web-based GIS application was developed to showcase the results and illustrate the general concept of this solution. In conclusion, the main goals for further research development were identified, along with potential scenarios for applying this approach in real-world conditions. Full article