Browse Items (11810 total)
Sort by:
-
Humanizing technology: The impact of emotional intelligence on healthcare user experience
This investigation underscores the importance of humanizing technology within the healthcare sector, with a specific focus on the significant role of emotional intelligence in shaping the interactions between patients and healthcare providers, particularly in the context of advancing healthcare technology. By integrating empathy into medical interfaces and devices, the user experience is fundamentally grounded in human aspects. The study delves into firsthand experiences of patients using emotionally intelligent healthcare solutions that not only meet their medical needs but also address the emotional complexities of illness and recovery. The integration of emotional sensitivity in medical technology strives to enhance patient comfort and foster more open and communicative relationships between healthcare providers and recipients. Moreover, the research presents a framework for emotional intelligence in healthcare technology, encompassing elements such as emotional recognition, response, and management. This framework is designed to promote a culture of patient understanding and support, enabling healthcare technology to adapt to the emotional requirements of patients. In the ever-evolving healthcare landscape,it is essential to recognize the profound impact of embedding empathy in medical technology, ultimately shaping a more empathetic future for healthcare interactions. 2024 by IGI Global. -
Humanizing the Workplace Through STARA: Examining the Roles of Perceived Usefulness and Perceived Organizational Support
This manuscript examines the transformative role of Smart Technology, Artificial Intelligence, Robotics, And Algorithms (STARA) in influencing the trajectory of the future of work, emphasizing the imperative of humanizing the workplace to ensure the longevity of business sustainability. Centred on primary data, a comprehensive literature review scrutinizes modular integrations and explanations, focusing on key variables such as Perceived Usefulness and Perceived Organizational Support. The research employs a conceptual framework to delineate the interplay between STARA, Perceived Usefulness, and Perceived Organizational Support. Methodologically, the research design and data collection methods are detailed, emphasizing the modular integration of measurement instruments. The results are presented, amalgamating crucial findings on the influence of STARA on repercussions for the future of work, emphasizing the incorporation of STARA to foster a more human-centric work environment for business sustainability. Practical suggestions are outlined for companies, accentuating integration opportunities. The conclusion emphasizes the importance of STARA in shaping the future of work, setting the stage for forthcoming research efforts in this dynamic domain. STARA, Future of Work, Perceived Usefulness, Perceived Organizational Support, Workplace Innovation, Business Sustainability. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Humanoid robot system for assisting elder people /
Patent Number: 202041027734, Applicant: Dr.S Balamurugan.
The present invention based on a humanoid robot for assisting elder people based on their necessity the robot has a four-wheel with two arms which rotate all directions. It will help all time it has combined artificial intelligent it which updates every human activity day by day based on their activities the robot will work and update their behavioral and it will work accordingly. -
Humour as a Moderator Between Hassles and Well-Being
Humour is a universal phenomenon that offers several physiological and psychological benefits across cultures. The objectives of this study were to examine the relationships between daily hassles, humour and well-being; and to investigate the moderating effect of humour on the relationship between hassles and well-being. A correlational design was adopted to collect data from 644 participants (men = 300, women = 344), aged between 18 and 58years using purposive and snowballing sampling techniques. The Daily Hassles Scale, Sense of Humour Questionnaire (SHQ-R) and the Personal Well-Being IndexAdult (PWI-A) were administered to the sample. The self-report measures were appropriately scored and the collective data were analyzed. Statistical analyses revealed a positive relationship between sense of humour and well-being. A negative relationship was observed between sense of humour and hassles; and between well-being and hassles. Further, sense of humour was found to be moderating the relationship between daily hassles and well-being. This study highlights the role of humour in softening the impact of hassles on the well-being of the Indian population. This strengthens the construct of humour in the context of positive psychology. The Author(s) under exclusive licence to National Academy of Psychology (NAOP) India 2024. -
Humour as a moderator of stress and defence based coping mechanisms among the youth of Kerala, India
The goal of this study was to examine the effect of the moderators of adaptive and maladaptive humour on stress and on the four levels of defence based coping mechanism amongst the youth of Kerala, India. Four hundred and fifty-three youth between the age of 18 and 40, selected from two different cities of North Kerala, India (Calicut, Malappuram) and Central Kerala, India (Cochin, Trissur), were asked to fill out three questionnaires assessing stress, coping and humour. Pearson's test of product-moment correlation indicated that stress had a positive and moderate statistically significant correlation with the first three levels of defence based coping mechanism (pathological defences, immature defences and neurotic defences). Furthermore, there was a positive and weak statistically significant correlation between stress and level-IV coping (mature defences). When positive and moderate correlation was found for stress with maladaptive humour, no significant correlation was found with adaptive humour. When coping was studied in relationship with humour, a negative and weak statistically significant correlation was found for level-I coping (pathological defences) with adaptive humour, whereas a positive and moderate statistically significant correlation was found with maladaptive humour. Here level-IV coping (mature defences) was found to have a positive and moderate statistically significant relationship with adaptive and maladaptive humour. Moderator analysis showed that maladaptive humour moderated the association between stress and four levels of defence based coping mechanism. The study implied that youth should be trained to use more of mature means of coping and adaptive humour styles in life. Universiti Putra Malaysia Press -
Humour as a tool for brand recall. Understanding the concept through five star advertisements /
Advertisements are considered as one of the effective tool of promoting a service or product. Though it has high impact on people it uses different appeals to attract the viewers. One of the effective appeals used by advertisers is humour. Humour has been used widely in advertisements since years. Everyone likes humour and the concept behind using humour in advertisements is clearly based on the people’s psychology. The researcher tries to find out whether humour is used as a tool for brand recall or not by using different qualitative and quantitative methods. -
Hunter Prey Optimization for Optimal Allocation of Photovoltaic Units in Radial Distribution System for Real Power Loss and Voltage Stability Optimization
Renewable Energy (RE) based Distribution Generation (DG), is a widely accepted eco-friendly alternative to conventional energy production. On the basic note, a DG is used to provide a part of or all of a customers real power demand and/or as a standby supply, and of all various existing types of DG technologies, Photovoltaic (PV) type distribution generation is considered for the study. The location of distributed generation is defined as the installation and operation of electric power generation modules connected directly to the distribution network or the network on the customer side of the meter, hence signifying the optimal location and size of the DGs used. This paper proposes a new algorithm of Hunter-Prey Optimization (HPO) to determine the optimal allocation of PV integration in the radial distribution systems (RDS). HPO is a new population-based algorithm inspired by the hunting behavior of a carnivore. The optimal sizing and siting of the PVs are determined by the proposed algorithm of HPO and are tested in MATLABR2021b on standard IEEE-33 and 69 test bus systems. On the basic of comparative study with literature, HPO is performed efficiently for solving multi-variable complex optimization problem. Also, the performance of RDSs is significantly improved with optimal PV allocations. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
HunterPrey Optimization Algorithm for Optimal Allocation of PV, DSTATCOM, and EVCS in Radial Distribution Systems
This research article instigates a seminal approach for optimizing reactive power in renewable energy sources (RES) and electric vehicles (EVs) coalescing distribution systems, using the innovative HunterPrey Optimization (HPO) algorithm in conjunction with DSTATCOM as a reactive power compensator. The proposed methodology aims to minimize losses, enhance voltage stability, and improve overall system performance by simultaneously optimizing reactive power flows in photovoltaic RES (PV_DG), EV charging stations (EVCS), and DSTATCOMs within the distribution system. Simulations carried on IEEE-33, IEEE-69, and IEEE-118 test bus systems in MATLAB environment demonstrate that the HPO-based approach achieves a 91.47% and 96.61% reduction in real power losses and an improvement in voltage profile with a minimum voltage value of 0.991 and 0.994 p.u. (respectively for IEEE-33 and 69 bus systems), compared to traditional algorithms. These results highlight the lofty performance of the HPO method, effectively addressing the challenges posed by the integration of RES and EVs along with DSTATCOM. 2024 John Wiley & Sons Ltd. -
Hybrid (ND-Co3O4/EG) nanoliquid through a permeable cylinder under homogeneous-heterogeneous reactions and slip effects
Modeling and computations are performed to study the ND-Co3O4/EG hybrid nanoliquid mixed convective flow past a vertical porous cylinder. The flow analysis and formulation are given accounting for slip effects and homogeneous-heterogeneous reaction impacts. The governing complex equations formed with prescribed boundary conditions are simplified into self-similar equations through the use of suitable transformations. The numerical solutions of the drag coefficient, Nusselt number, liquid velocity, liquid temperature, and the liquid concentration are explored through graphs with the setting of pertaining parameter values. From the results, it is noticed that an ND-Co3O4/EG nanofluid plays a more impressive role in the process of energy transfer than a Co3O4/EG nanofluid. Further, it is found that the heterogeneous reaction parameter decreases the concentration whereas multiple slips enhance the temperature. 2020, Akadiai Kiad Budapest, Hungary. -
Hybrid AI architecture for analysis of charging profile of electric vehicles /
Patent Number: 202131040276, Applicant: Shovon Nandi.
As a result of the development of electric vehicles with longer trip ranges (EVs), they will travel through various networks serviced by different utilities. We thus introduce an architecture that can provide roaming cars with charge service. In addition, although the energy internet allows energy and information flow, its roaming service is not smooth since its core design supports the internet. -
Hybrid AI Talent Acquisition Model: An Opinion Mining and Topic based approach
Artificial Intelligence models have found their usage in the human resource domain. In this paper, job reviewers' opinions on online discussion boards have been captured. The relative importance of factors has been established through an extensive literature review. First, LDA Topic modelling by adopting PCA is performed on unstructured text data has been analyzed. Second, sentiment analysis using the Li-Hu method has been employed to understand job seekers' satisfaction with job portals. The proposed model, 'Hybrid AI Talent Acquisition Model,' follows a novel approach to streamlining the jobseeker opinion related to online outlets. 2022 IEEE. -
Hybrid AODV: An Efficient Routing Protocol for Manet Using MFR and Firefly Optimization Technique
A MANET is a category of ad hoc protocol that could vary positions and track itself on the flutter. It utilizes wireless connections that are attached to several networks. They include wirelessly in a self-configured, self-healing network while not having permanent communication linked in a collection of mobile networks. The network topology of nodes typically varies in MANET, and nodes are free to stir errantly and independently as a router as they accelerate traffic to more nodes within the network. Ad hoc on-demand distance vector (AODV) was employed for node selection to attain the shortest path strategy in existing techniques. In the proposed system, the hybrid AODV (HAODV) technique incorporates the MFR (Most Forward within Radius) technique to detect the shortest path routing algorithm. The MFR method was deployed for selecting the neighbor node, while HAODV was deployed to find the shortest path. To find the shortest path based on the updating equation, the Firefly algorithm is also implemented into the Hybrid AODV. The proposed work's performance is calculated by different network parameters like the end to end delay, average routing overhead, throughput, and packet delivery ratio. After comparing AODV and DSR algorithms, the proposed algorithm (HAODV) shows improvement in packet delivery ratio, end-To-end delay, Routing overhead, and throughput. 2021 World Scientific Publishing Company. -
Hybrid Approach for Multi-Classification of News Documents Using Artificial Intelligence
In the context of news articles, text classification is essential for organizing and retrieving useful information from massive amounts of textual data. Effectively categorizing news titles has gotten more challenging due to the development of online news outlets and the ongoing production of news. A multi-text classification technique primarily targeted at news titles is shown. The suggested approach automates the classification of news titles into predetermined classes or subjects by combining deep learning approaches and natural language processing (NLP) algorithms. Data preprocessing, which includes text normalization, tokenization, and feature extraction, is the first step in the procedure. This prepares the raw news titles for deep learning models. 2024 IEEE. -
Hybrid Approach for Predicting Heart Disease Using Optimization Clustering and Image Processing
Heart disease (cardiovascular disease) is one of the core issues prevalent in this generation. Every year, millions of people die due to various heart diseases. The problem occurs due to hereditary or changes in life styles. Various data mining techniques are used in order to predict heart diseases. Data mining increases the accuracy, precision, and sensitivity of the model being used. In the proposed hybrid approach for predicting heart disease using optimization clustering and image processing (Hy-OCIP) model, a hybrid approach is used to predict heart diseases with the help of optimization, clustering, and image processing. After the heart image is being processed, centroid clustering is used for clustering the processed imaged into a set of chromosomes for optimization. The optimization method used for our model is genetic algorithm. The same methods are performed for both, a healthy and a heart patient. As a result, the model used in this research is able to distinguish between a normal patient and a heart patient by a hybrid combination of image processing, clustering, and optimization. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Hybrid Approach to Document Anomaly Detection: An Application to Facilitate RPA in Title Insurance
Anomaly detection (AD) is an important aspect of various domains and title insurance (TI) is no exception. Robotic process automation (RPA) is taking over manual tasks in TI business processes, but it has its limitations without the support of artificial intelligence (AI) and machine learning (ML). With increasing data dimensionality and in composite population scenarios, the complexity of detecting anomalies increases and AD in automated document management systems (ADMS) is the least explored domain. Deep learning, being the fastest maturing technology can be combined along with traditional anomaly detectors to facilitate and improve the RPAs in TI. We present a hybrid model for AD, using autoencoders (AE) and a one-class support vector machine (OSVM). In the present study, OSVM receives input features representing real-time documents from the TI business, orchestrated and with dimensions reduced by AE. The results obtained from multiple experiments are comparable with traditional methods and within a business acceptable range, regarding accuracy and performance. 2020, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature. -
Hybrid approach: Naive bayes and sentiment VADER for analyzing sentiment of mobile unboxing video comments
Revolution in social media has attracted the users towards video sharing sites like YouTube. It is the most popular social media site where people view, share and interact by commenting on the videos. There are various types of videos that are shared by the users like songs, movie trailers, news, entertainment etc. Nowadays the most trending videos is the unboxing videos and in particular unboxing of mobile phones which gets more views, likes/dislikes and comments. Analyzing the comments of the mobile unboxing videos provides the opinion of the viewers towards the mobile phone. Studying the sentiment expressed in these comments show if the mobile phone is getting positive or negative feedback. A Hybrid approach combining the lexicon approach Sentiment VADER and machine learning algorithm Naive Bayes is applied on the comments to predict the sentiment. Sentiment VADER has a good impact on the Naive Bayes classifier in predicting the sentiment of the comment. The classifier achieves an accuracy of 79.78% and F1 score of 83.72%. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Hybrid architecture of digital filter for multi-standard transceivers
This paper addresses on three different architectures of digital decimation filter design of a multi-standard RF transceivers. Instead of using single stage decimation filter network, the filters are implemented in multiple stages using FPGA to optimize the area and power. The proposed decimation filter architectures reflect the considerable reduction in area & power consumption without degradation of performance. First, the types of decimation filter architectures are tested and implemented using conventional binary number system. Then the two different encoding schemes i. e. Canonic Signed Digit (CSD) and Minimum Signed Digit (MSD) are used for filter coefficients and then the architecture performances are tested using FPGA. The results of CSD and MSD based architectures show a considerable reduction in the area & power against the conventional number system based filter design implementation. The implementation results reflect that considerable reduction in area of 25. 64% and power reduction of 16. 45% are achieved using hybrid architecture. Research India Publications. -
Hybrid architecture of Multiwalled carbon nanotubes/nickel sulphide/polypyrrole electrodes for supercapacitor
A hybrid electrode structure consisting of amino functionalised multi-walled carbon nanotube, nickel sulphide, and polypyrrole is successfully synthesized using a two-step synthesis such as hydrothermal and in-situ polymerization method. The resulting MWCNT/NiS/PPy composite exhibits a distinct tube-in-tube morphology with excellent stratification. The combination of different components and the unique structure of the composite contribute to its impressive specific capacitance of 1755 F g?1 at 3 A g?1. The prepared ternary composite enables ample exposure of numerous active sites while improving structural stability, ultimately leading to enhanced energy storage capabilities. They do this by combining the advantages of constituent components, a hierarchical assembly approach, and an integrated composite structure. Furthermore, even after undergoing 10,000 charge-discharge cycles, the supercapacitor retains more than 97% of columbic efficiency. An asymmetric coin cell was fabricated using MWCNT/NiS/PPy//AC device which delivered an energy density and power density of 33.12 Wh Kg?1 and 6750 W kg?1 respectively. These findings highlight the exceptional potential of the fabricated device for future applications in hybrid energy storage systems. 2024 Elsevier Ltd -
Hybrid area explorationbased mobility-assisted localization with sectored antenna in wireless sensor networks
In common practice, sensor nodes are randomly deployed in wireless sensor network (WSN); hence, location information of sensor node is crucial in WSN applications. Localization of sensor nodes performed using a fast area exploration mechanism facilitates precise location-based sensing and communication. In the proposed localization scheme, the mobile anchor (MA) nodes integrated with localization and directional antenna modules are employed to assist in localizing the static nodes. The use of directional antennas evades trilateration or multilateration techniques for localizing static nodes thereby resulting in lower communication and computational overhead. To facilitate faster area coverage, in this paper, we propose a hybrid of max-gain and cost-utilitybased frontier (HMF) area exploration method for MA node's mobility. The simulations for the proposed HMF area explorationbased localization scheme are carried out in the Cooja simulator. The paper also proposes additional enhancements to the Cooja simulator to provide directional and sectored antenna support. This additional support allows the user with the flexibility to feed radiation pattern of any antenna obtained either from simulated data of the antenna design simulator, ie, high frequency structure simulator (HFSS) or measured data of the vector network analyzer (VNA). The simulation results show that the proposed localization scheme exhibits minimal delay, energy consumption, and communication overhead compared with other area explorationbased localization schemes. The proof of concept for the proposed localization scheme is implemented using Berkeley motes and customized MA nodes mounted with indigenously designed radio frequency (RF) switch feed network and sectored antenna. 2019 John Wiley & Sons, Ltd. -
Hybrid Bacterial Foraging Optimization with Sparse Autoencoder for Energy Systems
The Internet of Things (IoT) technologies has gained significant interest in the design of smart grids (SGs). The increasing amount of distributed generations, maturity of existing grid infrastructures, and demand network transformation have received maximum attention. An essential energy storing model mostly the electrical energy stored methods are developing as the diagnoses for its procedure was becoming further compelling. The dynamic electrical energy stored model using Electric Vehicles (EVs) is comparatively standard because of its excellent electrical property and flexibility however the chance of damage to its battery was there in event of overcharging or deep discharging and its mass penetration deeply influences the grids. This paper offers a new Hybridization of Bacterial foraging optimization with Sparse Autoencoder (HBFOA-SAE) model for IoT Enabled energy systems. The proposed HBFOA-SAE model majorly intends to effectually estimate the state of charge (SOC) values in the IoT based energy system. To accomplish this, the SAE technique was executed to proper determination of the SOC values in the energy systems. Next, for improving the performance of the SOC estimation process, the HBFOA is employed. In addition, the HBFOA technique is derived by the integration of the hill climbing (HC) concepts with the BFOA to improve the overall efficiency. For ensuring better outcomes for the HBFOA-SAE model, a comprehensive set of simulations were performed and the outcomes are inspected under several aspects. The experimental results reported the supremacy of the HBFOA-SAE model over the recent state of art approaches. 2023 CRL Publishing. All rights reserved.