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Journal articles on the topic 'Microsoft Azure Face API'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Akpur, Akın, Burhanettin Zengin, and Tuna Çakar. "Havayolu Reklamlarında İzleyicilerin Duygu Ölçümü: Microsoft Azure Face API ile Yüz Kodlama Uygulaması." İstanbul Gelişim Üniversitesi Sosyal Bilimler Dergisi 12, no. 1 (2025): 190–202. https://doi.org/10.17336/igusbd.1434670.

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Amaç: Havayolu işletmeleri, müşterilerini uçuşlara çekmek ve marka imajlarını güçlendirmek için sık sık reklam kampanyaları düzenlerler. Ancak, reklam kampanyalarının etkinliği geleneksel yöntemlerle ölçüldüğünde sınırlı kalabilmektedir. Bu çalışmanın amacı yüz kodlama teknolojisinin havayolu reklamlarında duygu ölçüm performansının değerlendirilmesidir. Yöntem: Bu çalışma deneysel bir tasarıma sahip olup laboratuvar ortamında 40 denek ile yapılmıştır. Microsoft Azure Face API uygulamasından elde edilen sayısal duygu verileri istatistik paket program aracılığı ile analiz edilmiştir. Bulgular:

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Domínguez-Ramírez, Omar Arturo, and Arturo Austria-Cornejo. "Sistema de Reconocimiento de Patrones de Rostros en la Nube." Pädi Boletín Científico de Ciencias Básicas e Ingenierías del ICBI 7, no. 13 (2019): 54–61. http://dx.doi.org/10.29057/icbi.v7i13.3540.

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El presente trabajo comprende la implementación de algoritmos de alto desempeño para reconocimiento y detección de rostros, con interactividad en la Nube empleando la plataforma Microsoft Azure. Para su implementación, se analizan técnicas biométricas utilizadas hoy en día para el reconocimiento de patrones de rostros y se plantea de manera general considerar la existencia de ruido en las imágenes a analizar al compararlas con las bases de datos tomando en cuenta la alineación, normalización y escalado de cada una de las imágenes probadas. Para ello, se han llevado a cabo experimentos diferenc

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Dorfman, Robert, Irene Chang, Sean Saadat, and Jason Roostaeian. "Making the Subjective Objective: Machine Learning and Rhinoplasty." Aesthetic Surgery Journal 40, no. 5 (2019): 493–98. http://dx.doi.org/10.1093/asj/sjz259.

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Abstract Background Machine learning represents a new frontier in surgical innovation. The ranking Convolutional Neural Network (CNN) is a novel machine learning algorithm that helps elucidate patterns and features of aging that are not always appreciable with the human eye. Objectives The authors sought to determine the impact of aesthetic rhinoplasty on facial aging employing a multidimensional facial recognition and comparison software. Methods A retrospective chart review and subsequent analysis was carried out on all female patients who underwent open rhinoplasty with the senior author fr

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Gómez Fernández, Juan F., Eduardo Candón Fernández, and Adolfo Crespo Márquez. "A Structured Data Model for Asset Health Index Integration in Digital Twins of Energy Converters." Energies 18, no. 12 (2025): 3148. https://doi.org/10.3390/en18123148.

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A persistent challenge in digital asset management is the lack of standardized models for integrating health assessment—such as the Asset Health Index (AHI)—into Digital Twins, limiting their extended implementation beyond individual projects. Asset managers in the energy sector face challenges of digitalization such as digital environment selection, employed digital modules (absence of an architecture guide) and their interconnection, sources of data, and how to automate the assessment and provide the results in a friendly decision support system. Thus, for energy systems, the integration of

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Dimić, Slađana. "SISTEM ZA BEZBEDNU KOMUNIKACIJU DVA KORISNIKA PUTEM RAZMENE PORUKA." Zbornik radova Fakulteta tehničkih nauka u Novom Sadu 35, no. 04 (2020): 794–97. http://dx.doi.org/10.24867/07oi01dimic.

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Cilj ovog rada jeste da se obezbedi sigurna komunikacija u vidu razmene mail-a dva korisnika preko Web aplikacije i Microsoft Outlook-a, klijenta Microsoft Exchange-a. Za ovu komunikaciju potrebno je registrovati novu aplikaciju na Microsoft Azure portalu koja ima identifikatore neophodne za dobavljanje Bearer tokena. Bearer token sluzi da se klijent, u ovom slučaju razvijena Web aplikacija, autentifikuje servisu. Klijent je tada u mogućnosti da, preko Microsoft Graph RESTful Web API-a, potraži sve korisnike određene grupe registrovane na Azure Active Directory-u i pošalje mail odabranom kori

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Olimova, Muxlisa Vohidjon qizi. "SUN'IY INTELLEKT YORDAMIDA ISHLAB CHIQILGAN ZAMONAVIY TEXNOLOGIYALARNING TAHLILI." Innovative Development in Educational Activities 2, no. 15 (2023): 113–22. https://doi.org/10.5281/zenodo.8249653.

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<em>Sun’iy intellekt (SI) bizning yashash, ishlash sharoitimizda va o‘zaro munosabatlarimizda inqilob yasadi. SI texnologiyasi rivojlanishda davom etar ekan, uning nima ekanligini, turli SI tizimlari qanday ishlashini va ularning maqsadlari, ijobiy va salbiy tomonlarini tushunish juda muhimdir. Algoritmlar sehrli kuchga ega emas va inson aralashuvisiz yo‘q joydan qaror qabul qila olmaydi. Agar siz yuqori sifatli moslashtirilgan ma’lumotlarni taqdim qilmasangiz, hatto eng yetuk algoritm ham sizga mukammal natijani bermaydi. Ushbu maqolada sun’iy intellekt dunyosi v

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Chode, Balaji. "AI-Driven Risk-Adaptive Authorization for Multi-Tenant Cloud APIs - Microsoft Azure." International Journal of Computer Science and Data Engineering 2, no. 3 (2025): 1–11. https://doi.org/10.55124/csdb.v2i3.254.

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Application Programming Interfaces (APIs) have become the nervous system of modern financial-services platforms; yet fractured authorization logic remains a dominant breach vector, exposing organizations to data exfiltration, fraudulent transactions and regulatory fines. We introduce a cloud-native Contextual Authorization Framework (CAF) embedded in an enterprise Shared Services Platform (SSP) that supports more than 200 customers facing and internal micro-services worldwide. CAF sits behind Azure API Management, authenticates callers via OAuth 2.0 / OpenID Connect, and merges an ensemble mac

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Wahyutama, Aria Bisma, and Mintae Hwang. "Auto-Scoring Feature Based on Sentence Transformer Similarity Check with Korean Sentences Spoken by Foreigners." Applied Sciences 13, no. 1 (2022): 373. http://dx.doi.org/10.3390/app13010373.

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This paper contains the development of a training service for foreigners to help them increase their ability to speak Korean. The service developed in this paper is implemented in the form of a mobile application that shows specific Korean sentences to the user for them to record themselves speaking the sentence. The objective is to generate the score automatically based on how similar the recorded voice with the actual sentence using Speech-To-Text (STT) engines and Sentence Transformers. The application is developed by selecting the four most commonly known STT engines with similar features,

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Савчук, Т. О., та І. П. Пастух. "РОЗПІЗНАВАННЯ ЕМОЦІЙ УЧАСНИКІВ ВІДЕОКОНФЕРЕНЦІЙ В MICROSOFT TEAMS". Таврійський науковий вісник. Серія: Технічні науки, № 6 (13 лютого 2023): 18–24. http://dx.doi.org/10.32851/tnv-tech.2022.6.3.

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Запропоновано інформаційну технологію розпізнавання емоцій учасників відеоконференцій у Microsoft Teams за рахунок використання нейронної згорткової мережі та засобів технології Azure, а також розроблено її структуру та структуру компонентів платформи Azure. Проаналізовано засоби-аналоги та виявлено їх переваги і недоліки. Проаналізовано узагальнений метод розпізнавання емоцій учасників відеоконфернецій, визначено його недоліки та запропоновано удосконалений метод розпізнавання емоцій учасників відеоконференцій у Microsoft Teams, що дало можливість автоматизувати роботу користувача та отримува

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Chode, Balaji. "AI-DRIVEN CENTRAL AUTHORIZATION FRAMEWORK FOR ZERO-TRUST API SECURITY ON MICROSOFT AZURE." INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN MANAGEMENT 14, no. 1 (2023): 1–18. https://doi.org/10.34218/ijaiap_04_01_001.

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Wyman, Austin, and Zhiyong Zhang. "API Face Value." Journal of Behavioral Data Science 3, no. 1 (2023): 1–11. http://dx.doi.org/10.35566/jbds/v3n1/wyman.

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Emotion recognition application programming interface (API) is a recent advancement in computing technology that synthesizes computer vision, machine-learning algorithms, deep-learning neural networks, and other information to detect and label human emotions. The strongest iterations of this technology are produced by technology giants with large, cloud infrastructure (i.e., Google, and Microsoft), bolstering high true positive rates. We review the current status of applications of emotion recognition API in psychological research and find that, despite evidence of spatial, age, and race bias

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Syeda, Zeba Kauser. "Evaluating Image Processing Capabilities in the Cloud: A Comparative Study of Microsoft Azure and Google Cloud." International Journal for Research in Applied Science and Engineering Technology 13, no. 1 (2025): 778–86. https://doi.org/10.22214/ijraset.2025.66452.

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Cloud computing is a transformative paradigm that enables the distribution of processing power, application execution, and storage across networks of remote computer systems. This model allows for the flexible allocation and release of IT resources over the internet, offering an affordable solution for both businesses and individuals. Through cloud services, users can access a variety of offerings, such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Desktop as a Service (DaaS), with pricing based on actual usage. In an increasingly compet

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Venkata, Raman Immidisetti. "Seamless VMware Workload Migration to Microsoft Azure Using Zerto: A Hypervisor-Based Replication Approach." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 8, no. 5 (2022): 1–6. https://doi.org/10.5281/zenodo.14944996.

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The adoption of hybrid cloud architectures is strategic for enterprises integrating on-premises VMware environments with Microsoft Azure for enhanced scalability, flexibility, and disaster recovery (DR). Organizations face challenges migrating workloads to different Azure regions due to conflicts between Azure Site Recovery (ASR) and Azure Migrate, which use agent-based replication. These conflicts cause operational inefficiencies, replication failures, and data inconsistencies, complicating cloud migration efforts. This study investigates Zerto as an efficient alternative for workload migrati

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Sethi, KrishnaKanta, and Prof Subhashree Shukla. "Android Application for Hospital Executive." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 07 (2025): 1–9. https://doi.org/10.55041/ijsrem51320.

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- Hospitals are complex systems requiring timely, data-driven decision-making to manage operations, resources, and patient care efficiently. This thesis presents the development of a secure and real-time Android application for hospital executives. The system integrates HL7 message feeds, SQL databases, and RESTful APIs hosted on Microsoft Azure. Through this mobile app, executives can access key performance indicators such as patient admissions, discharges, census data, and diagnosis trends. The application ensures secure role-based access and real-time synchronization. Performance testing re

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Issa, Reda, Mohamed M. Badr, Omar Shalash, et al. "A Data-Driven Digital Twin of Electric Vehicle Li-Ion Battery State-of-Charge Estimation Enabled by Driving Behavior Application Programming Interfaces." Batteries 9, no. 10 (2023): 521. http://dx.doi.org/10.3390/batteries9100521.

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Accurately estimating the state-of-charge (SOC) of lithium-ion batteries (LIBs) in electric vehicles is a challenging task due to the complex dynamics of the battery and the varying operating conditions. To address this, this paper proposes the establishment of an Industrial Internet-of-Things (IIoT)-based digital twin (DT) through the Microsoft Azure services, incorporating components for data collection, time synchronization, processing, modeling, and decision visualization. Within this framework, the readily available measurements in the LIB module, including voltage, current, and operating

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Buja, Atdhe. "PROACTIVE MONITORING FOR SMEs USING APPINSIGHT." International Journal of Advanced Research in Computer Science 13, no. 5 (2022): 1–8. http://dx.doi.org/10.26483/ijarcs.v13i5.6901.

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Data Security is a worldwide concern mostly for small medium enterprise (SMEs) and frameworks, approaches, methods are constantly evolving that has a connection with cloud computing, information systems, artificial intelligence, blockchain. Many developers, administrators or product teams running blind. Those are not knowing of problems with their application or do not have the information to fix the problems. The things which can go wrong with web and mobile applications or services is unlimited like dependency failures, resources, and crashes. Main argument is an evaluation of benefits by us

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Ravinder Ramidi. "Cloud-Based API Gateways for Seamless Multi-Platform Integration." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 2466–503. https://doi.org/10.32628/cseit25112723.

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Cloud-based API gateways offer vital solutions for integrating systems across diverse environments in today's multi-cloud landscape. These gateways provide centralized control for managing, securing, and optimizing API traffic across distributed systems, addressing challenges organizations face when operating across multiple platforms. Key gateway functions include request routing, protocol translation, authentication, rate limiting, caching, lifecycle management, and monitoring capabilities. Major providers—AWS, Azure, and Google Cloud—offer solutions with unique strengths suitable for differ

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Горман, Д. О., та Т. О. Коротєєва. "Адаптування користувацьких сервісів для зберігання даних у процесі розроблення програмного забезпечення". Scientific Bulletin of UNFU 33, № 6 (2023): 62–68. http://dx.doi.org/10.36930/40330608.

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Подано розробку та результати оцінювання нової бібліотечної архітектури для зберігання даних у форматі ключ-значення, яка використовує зовнішні кінцеві точки користувацьких API. Це дасть змогу полегшити та здешевити процес збереження даних і конфігурації сховища завдяки можливості безоплатного використання публічних API та мінімізації взаємодії з складною інфраструктурою хмарних провайдерів. Розроблена архітектура дає змогу зберегти модульність внутрішніх компонент, забезпечити безпеку збережених даних, оптимізувати процес зберігання даних і спростити налаштування для розробників. Проаналізова

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Yang, Jeong, and Anoop Abraham. "Analyzing the Features, Usability, and Performance of Deploying a Containerized Mobile Web Application on Serverless Cloud Platforms." Future Internet 16, no. 12 (2024): 475. https://doi.org/10.3390/fi16120475.

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Serverless computing services are offered by major cloud service providers such as Google Cloud Platform, Amazon Web Services, and Microsoft Azure. The primary purpose of the services is to offer efficiency and scalability in modern software development and IT operations while reducing overall costs and operational complexity. However, prospective customers often question which serverless service will best meet their organizational and business needs. This study analyzed the features, usability, and performance of three serverless cloud computing platforms: Google Cloud’s Cloud Run, Amazon Web

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Abdelghany, Ahmed, Mohamed Gamal, Dr Tarek Aly, and Prof Dr Mervat Gheith. "Governance for Azure and AWS Cloud Services." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 3185–97. http://dx.doi.org/10.22214/ijraset.2024.60595.

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Abstract: These days, cloud computing services are utilized in all business, academic, and governmental domains to build IT infrastructure. Cloud computing services are one IT solution that is becoming more and more popular among different types of enterprises. Cloud computing services face many challenges, like how to protect and raise user knowledge. These problems and difficulties also pertain to cloud computing services, which could result in a number of important risk areas. One of the problems is not being aware of the hazards associated with cloud computing services and the controls tha

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Srinivas, Adilapuram. "Seamlessly Connecting Mainframes to the Cloud for Scalable, Agile and Future-Ready Solutions." European Journal of Advances in Engineering and Technology 7, no. 3 (2020): 63–69. https://doi.org/10.5281/zenodo.14631287.

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Mainframes handle critical operations but often face challenges. They lack scalability and struggle with agility. Modern cloud analytics remains largely untapped. These limitations reduce their effectiveness in today’s data-driven environment. Hybrid IT architecture offers a solution. By connecting mainframes to platforms like AWS, Azure, and GCP, enterprises can unlock their full potential. Secure connectivity enables seamless data exchange. Tools like IBM z/OS Connect facilitate API enablement. Cloud-native services provide scalable compute, data lakes, and AI/ML integration. This arti

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Hiden, Hugo, Simon Woodman, Paul Watson, and Jacek Cala. "Developing cloud applications using the e-Science Central platform." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1983 (2013): 20120085. http://dx.doi.org/10.1098/rsta.2012.0085.

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This paper describes the e-Science Central (e-SC) cloud data processing system and its application to a number of e-Science projects. e-SC provides both software as a service (SaaS) and platform as a service for scientific data management, analysis and collaboration. It is a portable system and can be deployed on both private (e.g. Eucalyptus) and public clouds (Amazon AWS and Microsoft Windows Azure). The SaaS application allows scientists to upload data, edit and run workflows and share results in the cloud, using only a Web browser. It is underpinned by a scalable cloud platform consisting

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Mbaya, Emmanuel Baldwin, Babatunde Alao, Philip Ewejobi, Innocent Nwokolo, Victoria Oguntosin, and Emmanuel Adetiba. "NaijaCovidAPI: an application programming interface for retrieval of COVID19 data from the Nigerian Center for Disease Control web platform." F1000Research 10 (December 2, 2021): 1227. http://dx.doi.org/10.12688/f1000research.74998.1.

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Background: In this work, a COVID19 Application Programming Interface (API) was built using the Representational State Transfer (REST) API architecture and it is designed to fetch data daily from the Nigerian Center for Disease Control (NCDC) website. Methods: The API is developed using ASP.NET Core Web API framework using C# programming language and Visual Studio 2019 as the Integrated Development Environment (IDE). The application has been deployed to Microsoft Azure as the cloud hosting platform and to successfully get new data from the NCDC website using Hangfire where a job has been sched

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Solovei, Olha, Tetiana Honcharenko, and Anatolii Fesan. "Technologies to manager big data of urban building projects." Management of Development of Complex Systems, no. 60 (November 29, 2024): 121–28. https://doi.org/10.32347/2412-9933.2024.60.121-128.

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The transformation of the construction industry according to the Construction 4.0 concept is possible with the availability of technology for managing big data of construction projects, where the task of managing big data includes tasks: collection; processing; renewal; backup and save data. Today, the information technologies of urban construction projects are a complex of integrated software complexes, and the data of construction projects remain stored in various data repositories, which makes it difficult, and sometimes impossible, to use them for project implementation. The choice of big

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Mihail Mateev. "Comparative Analysis on Implementing Embeddings for Image Analysis." Journal of Information Systems Engineering and Management 10, no. 17s (2025): 89–102. https://doi.org/10.52783/jisem.v10i17s.2710.

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This research explores how artificial intelligence enhances construction maintenance and diagnostics, achieving 95% accuracy on a dataset of 10,000 cases. The findings highlight AI's potential to revolutionize predictive maintenance in the industry. The growing adoption of image embeddings has transformed visual data processing across AI applications. This study evaluates embedding implementations in major platforms, including Azure AI, OpenAI's GPT-4 Vision, and frameworks like Hugging Face, Replicate, and Eden AI. It assesses their scalability, accuracy, cost-effectiveness, and integration f

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Malighetti, Clelia, Simona Sciara, Alice Chirico, and Giuseppe Riva. "Emotional Expression of #body on Instagram." Social Media + Society 6, no. 2 (2020): 205630512092477. http://dx.doi.org/10.1177/2056305120924771.

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Our aim was to explore emotions in Instagram images marked with hashtags referring to body image–related components using an artificial intelligence–based discrete emotional analysis. A total of 500 Instagram photos marked by specific hashtags related to body image components were analyzed and specific discrete emotions expressed in each picture were detected using the Emotion application program interface API from Microsoft Azure Cognitive Service. Results showed that happiness and neutrality were the most intense and recognizable emotions expressed in all images. Happiness intensity was sign

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Holilah, Holilah, Husyen Ali Alhabsy, Tb Muhammad Farhan Adnan, et al. "Aplikasi Kebugaran Defense In Depth Untuk Aplikasi Kebugaran Perusahaan Start-Up Menggunakan Microsoft Azure." Jurnal Ilmiah Sains dan Teknologi 9, no. 1 (2025): 10–19. https://doi.org/10.47080/saintek.v9i1.3867.

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A start-up company in the fitness and health sector has developed an innovative virtual training platform. The platform allows users to take live fitness classes via their computer, tablet or smartphone, leveraging artificial intelligence (AI) and high-quality video streaming for an interactive and personalized training experience. The platform consists of three main components: the frontend layer (web and mobile applications), the backend layer (application servers), and the data storage layer (cloud database). As the popularity of these platforms increases, companies face challenges in manag

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Nonaka, Fumiaki, Shinya Kawashiri, and Atsushi Kawakami. "Next-generation rheumatoid arthritis specialized telemedicine enabled by IoT and AI." Impact 2021, no. 8 (2021): 58–60. http://dx.doi.org/10.21820/23987073.2021.8.58.

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Ageing populations in developed countries place strain on healthcare systems and when ageing populations live far away from the specialists they require to treat their chronic diseases, the logistics can be challenging to say the least. This is a particularly acute issue in Japan, which is made up of small islands. The COVID-19 pandemic has served to emphasise the need for better systems for remote medical consultations. Dr Fumiaki Nonaka at Goto Chuou Hospital and Professor Atsushi Kawakami and Dr Shinya Kawashiri at Nagasaki University Hospital have collaborated with Microsoft to create the

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K., Edison, and Sani U. "Students’ Attendance Management in Higher Institutions Using Azure Cognitive Service and Opencv Face Detection & Recognition Attendance System." British Journal of Computer, Networking and Information Technology 5, no. 1 (2022): 43–55. http://dx.doi.org/10.52589/bjcnit-alqqmeee.

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This research aimed at studying the current methods of attendance used at higher institutions of learning in Uganda and the feasibility of using facial biometrics as a new method of capturing attendance. Facial biometrics is distinct from other biometrics because it can be carried out without the consent of the person involved. As a result, the researcher developed a face recognition attendance system using OpenCV and Microsoft Azure CS. Questionnaires, interviews, and observations were used to capture data for the research. The data were analyzed using SPSS to get the requirements and systems

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Chandra, T. Bharath. "Bridging the Visual Gap: Integrating Vision Language Models (VLM) and Artificial Intelligence (AI) with Enterprise Resource Planning (ERP) Software System." International Research Journal of Innovations in Engineering and Technology 09, Special Issue ICCIS (2025): 200–205. https://doi.org/10.47001/irjiet/2025.iccis-202532.

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Abstract - Businesses generate vast visual data (e.g., quality check photos, warehouse snapshots, invoices, customer images), but traditional Enterprise Resource Planning (ERP) systems, built for structured data, cannot process it. This study explores integrating Vision Language Models (VLMs), AI combining computer vision and language processing, with ERPs to automate tasks like quality control, inventory monitoring, and document processing. We assess integration feasibility with Microsoft Dynamics 365 Business Central, Salesforce, and SAP S/4HANA, proposing an API-driven system architecture.

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Roe, Charlotte, Madison Lowe, Benjamin Williams, and Clare Miller. "Public Perception of SARS-CoV-2 Vaccinations on Social Media: Questionnaire and Sentiment Analysis." International Journal of Environmental Research and Public Health 18, no. 24 (2021): 13028. http://dx.doi.org/10.3390/ijerph182413028.

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Vaccine hesitancy is an ongoing concern, presenting a major threat to global health. SARS-CoV-2 COVID-19 vaccinations are no exception as misinformation began to circulate on social media early in their development. Twitter’s Application Programming Interface (API) for Python was used to collect 137,781 tweets between 1 July 2021 and 21 July 2021 using 43 search terms relating to COVID-19 vaccines. Tweets were analysed for sentiment using Microsoft Azure (a machine learning approach) and the VADER sentiment analysis model (a lexicon-based approach), where the Natural Language Processing Toolki

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Ravichandra Mulpuri. "Comprehensive Review of Multi-cloud Architecture for Salesforce in Enterprise Environments." International Journal of Science and Research Archive 15, no. 3 (2025): 1825–38. https://doi.org/10.30574/ijsra.2025.15.3.1967.

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The adoption of multicloud architectures is rapidly increasing as enterprises seek flexibility, scalability, and optimization across diverse workloads. This paper examines the integration of Salesforce, a leading cloud-based CRM platform, within multicloud environments, particularly in large enterprise settings. It explores how Salesforce can operate seamlessly alongside platforms such as AWS, Microsoft Azure, and Google Cloud to support real-time data synchronization, resource allocation, and system interoperability. Key integration techniques discussed include API-based communication (REST,

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Ravi Teja Balla. "Oracle Fusion Cloud: Empowering Intelligent Integration for Digital-First Enterprises." Global Journal of Engineering and Technology Advances 23, no. 3 (2025): 264–70. https://doi.org/10.30574/gjeta.2025.23.3.0199.

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This article presents a comprehensive overview of Oracle Fusion Cloud as a strategic integration backbone for digital-first enterprises. In today's interconnected economy, organizations face challenges with siloed operations and fragmented data architectures that hinder visibility, efficiency, and innovation. The article explores how Oracle Fusion Cloud addresses these challenges through a modular ecosystem that enables holistic integration, enterprise extensibility, business process automation, and actionable intelligence. It examines enterprise-grade integration patterns, including event-dri

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M, Dr Ramakrishna, and Akshay Bharadhwaj. "Tracking Realness Using Smart Technology." International Journal of Innovative Research in Information Security 11, no. 02 (2025): 153–56. https://doi.org/10.26562/ijiris.2025.v1102.14.

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Computer vision technologies along with deep learning algorithms have boosted the creation of deepfakes by making manipulated multimedia data more authentic. Extremely believable forged media objects now enable scammers to distribute deceptive information while executing financial schemes. This paper presents Tracking Realness Using Smart Technology as a complete image and video authentication system which operates at scale. Our system follows successive steps beginning with video-to-image conversion through discrete frame extraction followed by MTCNN and Azure Vision API face detection for do

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Rehman, Rizwan Ur, Uzair Khaleeq uz Zaman, Shahid Aziz, et al. "Process Parameter Optimization of Additively Manufactured Parts Using Intelligent Manufacturing." Sustainability 14, no. 22 (2022): 15475. http://dx.doi.org/10.3390/su142215475.

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Additive manufacturing is the technique of combining materials layer by layer and process parameter optimization is a method used popularly for achieving the desired quality of a part. In this paper, four input parameters (layer height, infill density, infill pattern, and number of perimeter walls) along with their settings were chosen to maximize the tensile strength for a given part. Taguchi DOE was used to generate an L27 orthogonal array which helped to fabricate 27 parts on the Ender 3 V2 fused deposition modeling (FDM) printer. The ultimate testing machine was used to test all 27 samples

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Dr., Juby Mathew, Sen Easow Neil, Shankar Rajalakshmi, Babu Nandhu, and Pratap Singh Rudra. "Career Finder: AI powered career guider." International Journal on Emerging Research Areas (IJERA) 05, no. 01 (2025): 174–77. https://doi.org/10.5281/zenodo.15187120.

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This paper discusses the overall design, development, and deployment of an AI-based career recommendation system, organized into four interdependent modules: User Interface (UI) Design and Development, Backend Development and API Management, AI Model Integration and Recommendation Engine, and Database and Deployment. The platform leverages cutting-edge technologies such as React.js for a dynamic front-end, Flask for robust backend API development, OpenAI GPT-based models (or alternatives like Hugging Face Transformers or LLaMA) for personalized career insights, and MongoDB for scalable da

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Macedo, Eric, Liu Haoran, Zihao Fan, Marcus Navarro, José Guilherme Peixoto, and Romain Coulon. "Building a Radionuclide Metrology Algorithm Comparison Platform (NuCodeComP): Insights from Rapid Integration with Microsoft PowerApps." EPJ Web of Conferences 323 (2025): 11003. https://doi.org/10.1051/epjconf/202532311003.

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An essential step in radionuclide activity measurement comparisons is the counting signal processing performed by laboratory-specific software. This has led to initiatives comparing software performance using a unique dataset from a list-mode data structure, as defined in IEC 63047:2021. A virtual Radionuclide Metrology Algorithm Comparison Platform was developed at BIPM to ensure a FAIR approach and facilitate broader laboratory participation. Beyond presenting the final product, this work highlights key insights from its development. The platform was designed to be reliable, adaptable, and f

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Chaudhari, V. J. "Currency Recognition App." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 435–37. http://dx.doi.org/10.22214/ijraset.2021.34982.

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Visually Impaired & foreign people are those people who have vision impairment or vision loss. Problems faced by visually impaired in performing daily activities are in great number. They also face a lot of difficulties in monetary transactions. They are unable to recognize the paper currencies due to similarity of paper texture and size between different categories. This money detector app helps visually impaired patients to recognize and detect money. Using this application blind people can speak and give command to open camera of a smartphone and camera will click picture of the note an

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Lorido-Botran, Tania, and Muhammad Khurram Bhatti. "ImpalaE: Towards an optimal policy for efficient resource management at the edge." Journal of Edge Computing 1, no. 1 (2022): 43–54. http://dx.doi.org/10.55056/jec.572.

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Edge computing is an extension of cloud computing where physical servers are deployed closer to the users in order to reduce latency. Edge data centers face the challenge of serving a continuously increasing number of applications with a reduced capacity compared to traditional data center. This paper introduces ImpalaE, an agent based on Deep Reinforcement Learning that aims at optimizing the resource usage in edge data centers. First, it proposes modeling the problem as a Markov Decision Process, with two optimization objectives: reducing the number of physical servers used and maximize numb

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Santos, Marcela, and Reinaldo Gomes. "Strengthening Trust in Virtual Trusted Platform Modules: Integrity-Based Anchoring Mechanism for Hyperconverged Environments." Applied Sciences 15, no. 10 (2025): 5698. https://doi.org/10.3390/app15105698.

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Virtual Trusted Platform Modules (vTPMs) are widely adopted in commercial cloud platforms such as VMware Cloud, Google Cloud, Microsoft Azure, and Amazon AWS. However, as software-based components, vTPMs do not provide the same security guarantees as hardware TPMs. The existing solutions attempt to mitigate this limitation by anchoring vTPMs to physical TPMs, but such approaches often face challenges in heterogeneous environments and in failure recovery or migration scenarios. Meanwhile, the evolution of data center architectures toward hyperconverged infrastructures introduces new opportuniti

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Vamsi Krishna, M., A. Bhargav Reddy, and V. Sandeep. "Facial recognition enabled smart door unlock system." International Journal of Engineering & Technology 7, no. 2.7 (2018): 183. http://dx.doi.org/10.14419/ijet.v7i2.7.10289.

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To verify that our daily life is going in a secure way. Lot of research programmers are going on in this entire society. The turning point comes through the internet of things, industry has been emerged with the lots of elements provided from IOT. We can able to connect our daily life things or objects with this had successfully evolved lots of things. This Facial recognition door unlock system is a process is which will detect the face and identifies the among people. People are having different types of face cut, in that particularly there are many unique faces which are different from each

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Narendra Kumar Reddy Choppa, John Wesley Sajja, and Govindaraja Babu Komarina. "From complexity to clarity: Generative AI in data analytics." World Journal of Advanced Research and Reviews 26, no. 3 (2025): 349–61. https://doi.org/10.30574/wjarr.2025.26.3.2071.

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The rapid pace of digital transformation has established data analytics as a critical driver of organizational success, yet traditional methods often face challenges in complexity, scalability, and accessibility. This article explores how Generative AI, augmented by AI agents, transforms data analytics by streamlining workflows, enhancing decision-making, and delivering personalized analytics experiences across the analytical lifecycle. Leveraging cloud-native architectures, edge computing, and integration with enterprise platforms like SAP S/4HANA, Microsoft Fabric, Power BI, and Azure AI Fou

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A., Jangili*1 S. Ramakrishnan2 S. Seth3. "Harnessing Data Analytics for Improving Management Information Systems (MIS) in Healthcare." International Journal of Pharmaceutical Sciences 3, no. 1 (2025): 1787–95. https://doi.org/10.5281/zenodo.14709903.

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Data-driven strategies are being used more and more by healthcare systems to boost patient outcomes, increase operational effectiveness, and optimize resource management. Finding inefficiencies, forecasting patient needs, and assisting with evidence-based decision-making have all been made possible by data analytics. However, small and medium-sized healthcare facilities face barriers such as limited financial resources, inadequate technical infrastructure, and insufficient expertise that prevent them from leveraging these advancements. The above problems require a proposal to design light clou

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Didok, V., and M. Pan. "IMPLEMENTATION OF DIGITAL TWINS BASED ON GPT-3.5 FOR ENHANCING ENGLISH LANGUAGE LEARNING IN HIGHER EDUCATION INSTITUTIONS." Municipal economy of cities 6, no. 187 (2024): 8–11. https://doi.org/10.33042/2522-1809-2024-6-187-8-11.

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This paper presents the development of an interactive web-based platform aimed at enhancing English language learning through the utilization of digital twins, powered by the GPT-3.5 model. The platform integrates three primary services essential for language learning: vocabulary acquisition, grammar checking, and conversational practice via simulated interlocutors, offering a dynamic, personalized learning experience. Detailed technical aspects of the system’s architecture are discussed, highlighting the implementation of the Model-View-Controller (MVC) framework, which ensures modularity and

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Guillot, Jordan, Brenda Miao, Arvind Suresh, et al. "Constructing adverse event timelines for patients receiving CAR-T therapy using large language models." Journal of Clinical Oncology 42, no. 16_suppl (2024): 2555. http://dx.doi.org/10.1200/jco.2024.42.16_suppl.2555.

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2555 Background: Chimeric antigen receptor T (CAR-T) therapy is associated with a high risk of severe adverse events often only detailed in clinical notes. Monitoring them demands significant time and effort for manual chart review. Recent developments in large language modeling (LLMs) show promise for large-scale information extraction from clinical text. We performed a pilot study to evaluate the capability of the GPT-4 LLM to extract adverse events documented in the progress reports. Methods: We extracted progress notes within 30 days of any CAR-T administration from the UCSF deidentified c

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Dierks, Ludwig, Ian Kash, and Sven Seuken. "On the Cluster Admission Problem for Cloud Computing." Journal of Artificial Intelligence Research 71 (May 5, 2021): 1–40. http://dx.doi.org/10.1613/jair.1.12346.

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Cloud computing providers face the problem of matching heterogeneous customer workloads to resources that will serve them. This is particularly challenging if customers, who are already running a job on a cluster, scale their resource usage up and down over time. The provider therefore has to continuously decide whether she can add additional workloads to a given cluster or if doing so would impact existing workloads’ ability to scale. Currently, this is often done using simple threshold policies to reserve large parts of each cluster, which leads to low efficiency (i.e., low average utilizati

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Alam, Md Azad. "FACIAL RECOGNITION ATTENDANCE SYSTEM." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29448.

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Colleges have historically faced a great deal of difficulty with student attendance, necessitating a large time and effort investment from staff in manual tracking. Even though they are in place, the existing biometric attendance systems are not entirely automated, which causes delays in processing fingerprints, maintenance issues, and inefficiencies in time. Given that almost everyone has a smartphone and is continuously online in this day and age, a more simplified method is necessary. This study suggests using sophisticated object identification algorithms to check attendance using faculty

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Nath, Yamuna, Ashok Nath Yogi, Bibechana Paudel, Rabita Bhandari, Ashok k. Yadav, and Suraksha Acharya. "PROFITABILITY AND PRODUCTIVITY OF POTATO IN DARCHULA DISTRICT OF NEPAL." Agribusiness Management In Developing Nations 8, no. 2 (2024): 78–87. https://doi.org/10.26480/amdn.02.2024.78.87.

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Potato is considered a staple food in the Hill region of Nepal. It is considered a major crop (in cropping pattern) of the households in Api-himal RM, Naugadh VDC, Marma RM of Darchula District. The potato produced in these areas has a good quality reputation and is the major source of income. There are very few research studies that have assessed the profitability of potatoes in these areas. So, this study aimed to assess the profitability and productivity of potatoes in Darchula District of Nepal. The three areas were purposively selected as they have much better potato production in compari

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Kosarevskyi, Bohdan, and Artem Tetskyi. "Modern approaches to deploying the infrastructure of mobile intelligent systems." INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, no. 2(32) (June 30, 2025): 33–48. https://doi.org/10.30837/2522-9818.2025.2.033.

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Subject matter: The infrastructure of mobile intelligent systems (MIS) for monitoring critical assets using groups of unmanned aerial vehicles (UAVs), integrating edge and cloud computing, load balancing methods, and cybersecurity mechanisms. Goal: To investigate the efficiency of automated resource management in MIS through adaptive scaling, heuristic optimization, and failure prediction methods to enhance system reliability and performance. Tasks To design an MIS architecture with hybrid distribution of computations between edge and cloud components; to evaluate the impact of resource balanc

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Martseniuk, Y. V. "EXPLORING THE EFFECTIVENESS OF USING CENTRALIZED CONFIGURATION STORAGE TO SECURELY MANAGE CLOUD SERVICES INFRASTRUCTURE." Computer systems and network 7, no. 1 (2025): 218–34. https://doi.org/10.23939/csn2025.01.218.

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In the current context of widespread adoption of cloud technologies such as AWS, GCP, and Azure, organizations face challenges in centralized management of cloud resources, including ensuring security standards, monitoring service metrics, optimizing costs, and managing configurations. The main issue lies in the differences in the architecture of services provided by various cloud vendors, which complicates the integration and standardization of processes in multi-cloud environments. This article focuses on analyzing the issues of centralized configuration management using the Configuration Ma

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