Suitable Services Research Articles

Emotion Recognition in Natural Language Processing: Understanding How AI Interprets the Emotional Tone of Text

Emotion recognition is one of the newest transformational tools in the area of (Natural Language Processing) NLP for AI to make out the emotional feel of text with great accuracy. While analyzing unstructured data, such as customer feedback, social media posts, and reviews, algorithms within NLP detect emotions like anger, happiness, sadness, and frustration. This helps the firms to understand their customers more emotionally and helps them develop suitable products, services, and strategies for engagement. AI-powered emotion detection enhances customer support systems through personalized service interactions and faster grievance redressal. It also supports marketing functions through trend identification and prediction of customer behavior. The satisfaction of users will improve, brand loyalty will be created, and competitiveness will increase as the companies use more and more emotion-aware systems. These come with their own challenges to be faced very seriously: cultural differences, interpretation of context, and data privacy. This article focuses on methodologies of emotion recognition in NLP, various applications, and ethical use, pointing out impacts on customer experience management and future directions in AI-driven sentiment analysis.

A REVIEW ON SMART HOME DESIGN AND TECHNOLOGY FOR ELDERLY

The global elderly population is rapidly increasing, presenting significant challenges in providing suitable housing and care services, particularly in Eastern and South-Eastern Asia. This study explores the potential of smart home technologies, Internet of Things (IoT), and artificial intelligence (AI) in addressing the needs of the aging population, focusing on enhancing quality of life and supporting aging in place. The research examines three key areas: (a) architectural design considerations for elderly-friendly smart homes, emphasizing ergonomics, accessibility, and psychological well-being, (b) integration of IoT technologies for health monitoring, safety features, and emergency response systems, and (c) the role of AI in predictive healthcare and enhancing overall care delivery. The study also addresses ethical considerations, implementation challenges, and the importance of user-centered design in the adoption of these technologies.

Teacher educators’ subjective theories on education for sustainable development in higher education

In educational settings, educators’ individual perceptions of theories and concepts (e.g. about teaching and learning) are crucial for their professional performance. Thus, regarding education for sustainable development (ESD), it is vital to focus on teacher educators’ (TEs’) perceptions of this concept. As ESD is a comparatively young and dynamic field of research, not all academic lecturers are familiar with it. Therefore, it cannot be assumed that they all have a well-founded or similar understanding of it. In this study, we surveyed TEs’ perceptions of ESD and provided further insight into the understanding and application of ESD in teacher education, thereby contributing to the professional development of TEs in the context of ESD. We characterised the presented perceptions as subjective theories and used the research programme subjective theories (RPST) procedure to describe them. We found that aspects of instrumental and emancipatory ESD and transformative learning were mixed in the subjective theories. Moreover, the TEs in our study presented learning objectives and methods that could be assigned to the key competencies of ESD in higher education. Our results serve to describe TEs more precisely and thus enrich the basis for their involvement in ESD implementation processes and suitable support services.

Perceptions of New Jersey Teachers About Mental Health and School Services Offered During the COVID-19 Pandemic

During the COVID-19 pandemic, the New Jersey Safe Schools Program (NJSS) surveyed a subset of newer NJ high school (HS) teachers who completed NJSS work-based learning supervisory trainings from October 2021 to June 2023. The purpose of this study was to gain insight on NJ HS teacher perceptions of school provided mental health services, and well-being supports received during the COVID-19 pandemic. Via online surveys, teachers anonymously identified who should be responsible for supporting mental well-being in schools, satisfaction with existing mental health services, and self-care practices implemented during the COVID-19 pandemic. Of the 114 HS teachers surveyed, nearly 70% would recommend existing school mental health services to colleagues, 53% would like an increase in mental health and counseling services available at their school, and 44% would like their schools to improve mental health literacy. This study presents insight into the needs teachers expressed for appropriate school mental health support and services. Data will inform guidance for how to better address identified needs, including employee wellness, and creating positive social and emotional school environments. School districts should prioritize the implementation of suitable and equitable school-based mental health services to teachers and students alike to promote healthy and productive school environments.

Cloud Platform Business Scenario Modeling Based on Multi-Model Fusion Recommendation Algorithm

In the era of cloud computing, businesses are increasingly relying on cloud platforms to streamline their operations and deliver services efficiently. Recommendation systems play a pivotal role in suggesting suitable services and resources to enhance user experience and optimize resource allocation. This paper presents a novel approach, the Multi-Model Fusion Recommendation Algorithm (MMFRA), which integrates multiple recommendation models using advanced fusion techniques to enhance the accuracy of recommendations in cloud platform business scenarios. The implementation process of MMFRA involves combining diverse recommendation models, such as collaborative filtering, content-based filtering, and matrix factorization, into a unified framework that leverages their strengths while mitigating individual limitations. This fusion process is designed to achieve higher precision in service recommendations by considering various aspects of user behavior and preferences. Through a comprehensive evaluation in a simulated cloud platform environment, MMFRA demonstrates superior performance in terms of recommendation accuracy and user satisfaction. The proposed algorithm offers significant potential for enhancing the effectiveness of cloud platform services, ultimately benefiting both service providers and users.

The Norwegian educational and psychological counselling service (EPS) as an ‘inclusion agent’ in schools?

ABSTRACT This article focuses on the schools’ support service related to the Nordic ambition of inclusive education. This ambition entails a somewhat conflicted mandate, which both the schools and the support service find demanding to ensure in their collaboration. As a framework for discussing challenges and opportunities linked to a case study in Norway, the article also shows how this appears in Sweden and Denmark. The question is whether it is possible, through new forms of meetings, to develop an innovative collaboration on inclusive practice between the Norwegian Educational and Psychological Counselling Service and schools. The article builds on selected data from a larger project, using a cross-unit analysis to compare experiences from two different types of collaboration meetings in two different Norwegian municipalities. By this, we have searched for an understanding of the central prerequisites to succeed. The most significant finding is the importance of a leadership which is, under innovative conditions, capable of creating necessary psychological safety to develop the meetings towards real professional learning communities. Finally, the apparently persistent challenges of designing a suitable support service to realise inclusive education in the Nordic countries are discussed in light of a current Norwegian strategy called ‘The Competence Boost for Special Education and Inclusive Practice’.

Factors influencing an advanced nursing practice service for people with intellectual disabilities

Abstract Background People with intellectual disabilities (PWID) have less access to preventive healthcare services and are therefore more likely to suffer from certain chronic diseases. Advanced Practice Nursing (APN) can be a suitable approach for this group. However, APN is not yet widespread in all European countries. This intervention focuses on PWID in Hamburg, Germany, who receive case management and prevention focusing on stress, nutrition, mobility and addiction through community-based APN to improve their health status. We aimed to explore the facilitators, barriers and experiences of stakeholders in the context of the APN intervention. Methods We conducted 90 semi-structured problem-centered interviews with PWID, family members, professional caregivers and prevention service providers in 2023 and 2024. We employed convenience sampling. Data were analyzed by qualitative content analysis with mixed inductive-deductive coding using MAXQDA. Results Overall interviewees were satisfied with the intervention. It was reported that the clients exercised more, ate healthier, learned techniques to reduce stress and coped better with addiction. In addition, barriers to preventive services were reduced. We identified factors that positively influenced the success of the intervention: good interprofessional collaboration, successful relationship building with clients, concise goal setting and target group-specific work materials. Barriers were: neglect of the professional care network, difussion of agreements, lack of available prevention services, and communication problems. The results are preliminary. Conclusions This is one of the first evaluation studies of an APN intervention for PWID in Germany. The results show that this new form of care can be implemented if the relevant stakeholders work together and good relationships with the clients are established. Specific goals should be defined and the professional carergivers should develop a community network. Key messages • APN is a suitable approach for disease prevention and health promotion for people with intellectual disabilities, given interprofessional collaboration and a well-established relationship with clients. • Preventive healthcare for the target group is difficult to implement if the stakeholders do not work together and if there are insufficient suitable preventive services available in the community.

Making the most of a captive audience: Do specialist teams in custodial settings offer a way to assist people to access the NDIS?

AbstractWhile the National Disability Insurance Scheme (NDIS) has been operating in Australia for 10 years, numerous eligible people with disability have not accessed the scheme, many of whom are in prison. The South Australian Government, in partnership with the National Disability Insurance Agency (NDIA), implemented a pilot programme to assist people in prison to access the NDIS as having NDIS supports on release may reduce the risk of returning to custody. This qualitative study, drawing on interviews with 20 stakeholders, explores the enablers and barriers of assisting people with disability in prison access the NDIS. Our findings show that while custodial settings provide opportunities to assist people with disability to have their eligibility for the NDIS assessed, prisons are difficult settings in which to undertake subsequent assessment and planning processes to determine the supports available on release. People with disability exiting prison also face significant challenges accessing suitable accommodation and support services, particularly when their needs are complex. Further work is required to ensure planning and assessment processes meet the needs of this group. The findings provide useful insights to both justice and other institutional settings and respond to many of the questions raised by recent public inquiries and reviews.

Frequent callers contacting the Norwegian national emergency medical number 113: a retrospective study

BackgroundCalling for help is the first link in the chain of survival; however, few studies have investigated the challenges faced by frequent callers (FCs) to emergency medical communication centres (EMCCs). This study aimed to explore the characteristics of FCs and the nature of their calls to the Bergen EMCC, Norway.MethodsThis was a retrospective analysis of all emergency calls to the Bergen EMCC over three consecutive years (2019–2021). Bergen is the second-largest city in Norway, and the Bergen EMCC and ambulance services are part of the specialist medical service, covering a population of 460,000. The Bergen EMCC receives approximately 60,000 emergency calls per year. The study population comprised all adults identified during emergency medical calls. FCs were defined as individuals who registered five or more calls over 12 consecutive months during the three-year period.ResultsThe analysis included approximately 50,000 individuals, who made > 90,000 calls during the study period. Of those, 1,594 (3.2%) were FCs, accounting for approximately one in four (21,339 of 90,085, 23.7%) calls. The FCs included more men (882 of 1,594 (55.3%) vs. 24,204 of 47,564 (50.9%)) and registered a lower proportion of calls with an acute degree of urgency (6,051 of 21,339 calls (28.4%) vs. 30,276 of 68,746 calls (44.0%)). Calls from FCs showed an even occurrence throughout the week, peaking between 19:00 h and 20:00 h. Compared with calls from non-FCs, calls from FCs had a higher proportion of ‘no response/verbal referral to local emergency medical department’ and involved a lower proportion of hospital transfers. The EMCC most frequently used the medical criterion ‘Mental health problems/suicide’ for calls from FCs.ConclusionsFCs were common, and more often men. The EMCC dispatched ambulances or admitted patients to hospitals less frequently following these calls. Many of these situations could be handled in other parts of the healthcare system, reducing the burden on EMCCs, and providing more suitable services for FCs. Thus, EMCCs should identify and adjust patient management to match their actual needs.

Emerging challenges in the application of artificial intelligence for the eye disease screening in Chinese primary healthcare institutions

Breakthroughs have been achieved recently in the application of artificial intelligence (AI) for the eye disease screening in Chinese primary healthcare institutions, but challenges have also emerged. First, AI software has continuously evolved, expanding the range of eye diseases that can be screened, enhancing diagnostic accuracy, and progressing towards predicting the course of eye diseases. However, inadequate infrastructure such as 5G and a shortage of specialized personnel have hindered the coverage of screenings. Second, while the cost-effectiveness of AI is well-established, new screening models have impacted the equity of screenings. It is essential to tailor AI application models to the specific context of China. Third, AI screening guidelines have been increasingly improved, providing direction for AI development and reference for the promotion and application of AI technologies. Nonetheless, high-quality empirical research is urgently needed to provide scientific evidence for policymaking related to AI in the eye disease screening. Therefore, it is suggested to develop multimodal AI models that integrate basic data such as symptoms and medical history with simple ophthalmic examinations, to accelerate the construction of infrastructure like 5G and focus on cultivating interdisciplinary talents, to explore suitable service systems and models for the large-scale eye disease screening tailored to local conditions, and to conduct long-term, multi-center, empirical studies.

A configurational impact assessment of pet tourism destination visit intention: application of TPB, servicescapes, and loss-aversion under prospect theory

ABSTRACT As the number of pet lovers is increasing, the tourism industry has become keenly interested in pet-friendly business environments. This study aimed to explain pet owners’ intentions to visit a pet tourism destination using diverse determinants, which were applied in three theoretical frameworks. Data were collected from a sample of 349 pet owners. Among the meaningful results, pet owners chose pet tourism destinations that offered physical environment attributes. Their intentions were salient to overcoming perceived behavioural control issues or perceived risks. Overall, pet owners revealed a strong intention to visit pet tourism accommodation if the destination provided suitable facilities or services. The results of this study are of academic and industrial significance because they relate to a new niche market: pet lovers and pet-friendly tourism businesses.

Rancang Bangun Sistem Informasi Pelayanan Kesehatan Berbasis Website Pada Salvio Medical Information

In an era of rapid advances in Information Technology, health is an important aspect of human life. Clinics and hospitals compete to meet patient expectations, but often patients struggle to find suitable services, wasting valuable time. A common problem faced by many visitors to Bali is the confusion of finding a hospital or clinic that suits their needs. Salvio Medical Information, as a healthcare institution in Bali, faces similar challenges with a lack of a comprehensive information system. This can result in errors in data management, difficulties in accessing information, as well as delays in service to guests who need health care. Therefore, this research aims to design a website-based healthcare information system for Salvio Medical Information. The development approach uses the Extreme Programming model to enable rapid software development. Thus, this research is expected to make a significant contribution to efforts to develop health services that are more efficient and able to better meet the needs of patients. The expected result is a web-based health service information system that is built using the PHP programming language with the help of the Laravel framework and the extreme programming method. Where in the system built custemer can place orders through the website and the admin can manage service content and partner content on the website.

An innovative approach for QoS-aware web service composition using whale optimization algorithm

With the proliferation of services and the vast amount of data produced by the Internet, numerous services with comparable functionalities but varying Quality of Service (QoS) attributes are potential candidates for meeting user needs. Consequently, the selection of the most suitable services has become increasingly challenging. To address this issue, a synthesis of multiple services is conducted through a composition process to create more sophisticated services. In recent years, there has been a growing interest in QoS uncertainty, given its potential impact on determining an optimal composite service, where each service is characterized by multiple QoS properties (e.g., response time and cost) that are frequently subject to change primarily due to environmental factors. Here, we introduce a novel approach that depends on the Multi-Agent Whale Optimization Algorithm (MA-WOA) for web service composition problem. Our proposed algorithm utilizes a multi-agent system for the representation and control of potential services, utilizing MA-WOA to identify the optimal composition that meets the user’s requirements. It accounts for multiple quality factors and employs a weighted aggregation function to combine them into a cohesive fitness function. The efficiency of the suggested method is evaluated using a real and artificial web service composition dataset (comprising a total of 52,000 web services), with results indicating its superiority over other state-of-the-art methods in terms of composition quality and computational effectiveness. Therefore, the proposed strategy presents a feasible and effective solution to the web service composition challenge, representing a significant advancement in the field of service-oriented computing.

RANCANG BANGUN APLIKASI MARKETPLACE PENATU MOBILE WEB BERBASIS RESPONSIVE WEB DAN FRAMEWORK EXPRESS.JS

This research developed a mobile web marketplace application for laundry services to address user difficulties such as finding the nearest location, managing physical receipts, and obtaining service information. Utilizing a responsive web design approach and flexbox techniques, the front end of the application was designed to be optimal across various devices. The back end was built using Express.js with the controller-middleware-route concept to maintain code organization. Furthermore, the Geocoding API and Distance Matrix API were implemented to calculate the distance between customers and laundry services. Testing was conducted using black box testing by developers and usability testing by participants. The results indicated that the front end of the application provided an optimal user experience with an overall satisfaction rate of 89.57%, and the back end was effective in managing data with middleware features and the integration of the Geocoding API and Distance Matrix API, achieving a usability satisfaction rate of 89.22%. This research demonstrates that the responsive mobile web application is effective and efficient in assisting users in finding suitable laundry services, thereby enhancing convenience and service efficiency.

Service Selection under Uncertainty

Cloud computing has emerged as a popular computing paradigm, providing scalable and pay-per-use services to execute a variety of tasks. However, selecting the most suitable cloud services for a client can be challenging, as it involves taking into account the service characteristics and a set of client restrictions. In this paper, we formalize the problem of Service Selection under Uncertainty (SSuU) as an optimization problem. Our goal is to allocate tasks to appropriate cloud services while considering the probability of Service Level Agreement (SLA) violations and a set of client restrictions. We introduce an efficient dynamic programming approach to calculate the probability of SLA violations incrementally over time. We prove that the SSuU problem is strongly NP-complete, and propose an Integer Linear Programming (ILP) formulation and an Iterated Local Search-based algorithm for tackling it. To facilitate evaluation, we also introduce a set of benchmark instances for the SSuU problem. We extensively evaluate our proposed solutions on 94 input instances and compare them to the exact method (i.e., which always produces the optimal solution). Our results demonstrate that the metaheuristic approach is significantly faster and leads to exact solutions in the great majority of the evaluation scenarios.

Fast Algorithms for Computing Fixed-Length Round Trips in Real-World Street Networks

This paper proposes and evaluates algorithms for calculating round trips of a prescribed length on directed street networks. This problem has several real-world applications, such as designing jogging routes and cycling tours. In this work, we focus specifically on methods that avoid the need to download, process, and store large map databases. At the same time, we aim for our methods to be fast, accurate, and capable of handling a wide range of prescribed distances, from just a few meters to many kilometres. To achieve this, our overall strategy involves using a small number of calls to a suitable online mapping service to collect relevant structural information for the problem at hand. All remaining computations are then performed locally on the client. Empirically, we demonstrate that our suggested techniques outperform existing open-source algorithms in terms of both accuracy and runtime requirements. Our most successful approach is based on multi-objective local search, utilizing specialized neighbourhood operators that exploit the underlying graph-theoretical properties of this problem, resulting in runtimes of around 2–3 s on a typical desktop computer.

Affordability, Accessibility, and Quality of Maternal Health Care Services and Level of Satisfaction of Mothers in Rural Areas in China

Objective: This study aimed to understand the affordability, accessibility, and quality of maternal and child health services for postpartum mothers, and their impact on satisfaction. Methods: The study utilized the Anderson model and revised the Maternal Pregnancy and Perinatal Health Service Questionnaire. A survey was conducted among 289 mothers aged 20–49 in Feicheng City. Results: Regarding accessibility, most respondents (133) reported that travel time to healthcare services exceeded 60 minutes, while 99 respondents indicated a travel time of 16–30 minutes. The issue of affordability was highlighted, with 86.85% of participants perceiving maternal healthcare services as costly, indicating a significant financial burden. More than 50% of respondents were satisfied with two specific dimensions (P < 0.05) regarding the quality of maternal healthcare services. Conclusion: The study found that accessibility, affordability, and quality significantly affect mothers’ satisfaction with maternal health services. Future research should focus on developing more suitable service pathways for rural mothers.

A Review on Financial Literacy for Farmer-educate to Empower

The volume of farming community in the world ranges upto 30% [1]. India is a significant global contributor in the agriculture industry. Agriculture and allied sectors are the main source of livelihood to about 55% of India’s population. Of the country's population engaged in agriculture and related sectors, 69% live in rural areas, with the majority of these people being farmers [2]. Although, India is having top standings in terms of highest milk production, livestock population etc., but on the ground reality farmers face many constraints hindering the sustainability in production and productivity of agriculture sector. Among several constraints exist, financial literacy poses to be one of the major constraints hindering farmers growth. Financial inclusion and, eventually, financial stability were seen as much aided by financial literacy in India. Among all farming households, about 27-37% are financially literate and have access to official credit sources [3]. Recognizing the importance of agriculture and allied sector in India’s development, the Government, Reserve Bank of India (RBI) and many financial research institutes in collaboration with farmer-oriented universities like agriculture, veterinary and allied universities have played an important role for catering to the increasing awareness on financial literacy and access to credit services among farmers as there exist visible lacunae in achieving improved farmers economy [4]. The financial literacy was found to have direct impact on socio-economic factors and hence protocols containing suitable delivery services that addressing financial concepts results in producing beneficial effect and long-term sustainability on farming communities [5].

Selection of third-party logistics in supply chain finance under probabilistic complex hesitant fuzzy sets and distance measures

Financial institutions attach great importance to the multiple attribute decision-making (MADM) problems of selecting an effective third-party logistics (3PL) service provider in supply chain finance. A suitable 3PL service provider can not only assist financial institutions in carrying out supply chain finance activity but can also replace financial institutions in supervising the operation of a target financing supply chain, therefore minimizing financial institutions' operating risks. However, there is no sufficient study on the selection of a 3PL service provider. Hence, the objective of this paper is to establish an innovative concept of the “probabilistic complex hesitant fuzzy set” (PCHFS), which is a hybrid structure of the complex hesitant fuzzy set and the probabilistic fuzzy set to manage complex information in real-decision theory. This paper examines the periodicity of probabilistic fuzzy information and extends the range from [0,1] to the unit disc in the complex plane to provide more ability to describe the full meaning of the information in a mathematical model. Based on the internal structure of the set and to find the degree of discrimination between the pairs of PCHFSs, the generalized distance measures and modified generalized distance measures are defined. Several properties and their relationships between them are derived in detail. Also, several cases of the proposed measures are exposed, which reduces them to the existing studies. Furthermore, based on these proposed measures, a multiple-attribute decision-making (MADM) approach is established in an uncertain environment, and several numerical examples are given to examine the feasibility and validity of the explored measures. Finally, the modified and parameterized distance measures based on PCHFSs are verified by comparing them with some existing measures.

How to Meet Elders’ Needs: A Strategy for Community Healthcare Service

The elderly care services model based on community involvement is a significant approach to address challenges posed by aging populations. Nevertheless, there is a noticeable gap in effectively gauging the actual needs and preferences of the elderly regarding these services, which is particularly prevalent in developing regions like China. Therefore, we conducted a comprehensive analysis through literature reviews; data surveys; and interviews with 16 elderly individuals, their family members, and caregivers in a community in Shenyang City. Additionally, a Delphi test was conducted to identify the specific needs related to elderly care services. Next, the Kano model explored the genuine needs of the elderly for community-based care services. This model helped us understand how various factors of demand influence satisfaction levels of the elderly, and we designed a service blueprint based on these findings. The study involved 102 participants. Our findings revealed that the extent to which different service needs are met varyingly impact elderly users’ satisfaction. Catering to these needs in a targeted manner enhances the adaptability of services and boosts the subjective satisfaction of the elderly. Consequently, future research should focus on developing suitable community elderly care service plans that are more aligned with their needs.