Prioritizing User Requirements for Agile Software Development

Sachdeva, S.K.; Arya, Akshay; Paygude, Priyanka; Chaudhary, Snehal; Idate, Sonali

doi:10.1109/icacct.2018.8529454

Cited by 7 publications

(5 citation statements)

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“…Using pop dance motion sequences, Labuguen et al evaluated the precision of markerless 3D skeleton pose estimation and showed great accuracy with their suggested approaches [38] [39]. BlazePose has benefits over OpenPose in terms of accuracy and speed, according to Mroz et al, comparison of the two programs [40] [41].…”

Section: Literature Reviewmentioning

confidence: 99%

Web Service Implementation “AI Yoga Trainer Using Human Pose Estimation” for Web Discovery

Milind Gayakwad

2024

jes

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This research work is to create a application as web service to make it available on web for web service discovery. The most significant yoga stance is well-known on a global scale and supports the health advantages advocated by the ancient sages. OpenPose estimates that computer vision technology can help yoga practitioners achieve the greatest form and alignment. The integration of the OpenCV, Python, and MediaPipe frameworks is the main emphasis of this research project in order to develop an OpenPose estimation system for yoga poses. A camera is used to capture the yoga practitioner's motions, and a deep learning model is used to predict the important body parts. The algorithm then looks at these essential aspects to determine if the practitioner is doing the pose correctly or whether any adjustments are needed. The device gives the practitioner immediate feedback, allowing them to modify their alignment and posture as necessary. The OpenPose estimate system can help with the practice of yoga by offering detailed visualizations of the essential body parts throughout each posture in addition to providing real-time feedback Practitioners may more clearly understand the right form and alignment and make the required adjustments by utilizing this visualization. Additionally, the OpenPose estimation system enables the tracking of development over time. Practitioners who want to practice alone at home or may not have access to an instructor can also benefit from it. This paper offers a MediaPipe, OpenCV, and Python-based OpenPose estimation system for yoga positions. For optimal form and alignment, the tool may offer real-time feedback and visual representations of key body parts throughout each position. It is useful tool for yoga teachers and students, enhancing yoga's safety and efficacy while supporting the practice.

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Section: Literature Reviewmentioning

confidence: 99%

Web Service Implementation “AI Yoga Trainer Using Human Pose Estimation” for Web Discovery

Milind Gayakwad

2024

jes

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“…A Tabela 4 apresenta as técnicas, sua frequência e estudos associados. O envolvimento do cliente na definição objetiva da prioridade, evitando erros na obtenção de informações que podem levar a necessidade de retrabalho é discutido em grande parte dos estudos [4,20,33,37]. A pluralidade de técnicas de priorização chama atenção.…”

Section: P1 -Práticas áGeis E Técnicas De Erunclassified

“…Pode-se destacar também a presença de testes de aceitação declarados em 13 estudos, para verificar se as funcionalidades implementadas estão de acordo com os requisitos levantados [28], ou ainda os critérios de aceitação listados nas histórias de usuário. A gerência de requisitos e mudanças também está presente na literatura de ER ágil, sendo mencionado por 21 estudos [2,[4][5][6]9,18,20,21,24,[27][28][29][30][31][32][33][34][35]37,39,41]. Isto se deve ao fato de que as equipes ágeis devem estar em busca de estratégias para compreender adequadamente as mudanças de domínio do problema e a necessidade do surgimento de novos requisitos ao longo de todo ciclo de vida do projeto [4].…”

Section: P1 -Práticas áGeis E Técnicas De Erunclassified

“…Classificamos todos os artigos incluídos em uma das facetas do tipo de pesquisa derivadas de Wieringa et al [44], tais como: pesquisa de avaliação, proposta de solução, pesquisa de validação, artigos filosóficos, artigos de opinião e artigos de experiência pessoal. Nossa RSL verificou que pesquisas de avaliação foram majoritárias com um total de 21 artigos [2-4, 6, 11, 16, 18, 20, 21, 23, 26-29, 32-34, 36, 38, 41, 42] e que propostas de solução ocorreram em 7 estudos [13,14,19,30,31,35,37]. Pesquisas de validação e artigos de experiência ocorreram em [5,24] e [9,39] respectivamente.…”

Section: P3 -Caracterização Da Pesquisa Em Er áGilunclassified

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Engenharia de Requisitos Ágil: Extensão de uma Revisão Sistemática da Literatura

Menezes,

Sampaio,

Marinho

2021

Anais Do Workshop Em Engenharia De Requisitos

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Nowadays, the daily routine of software engineers is determined by agile methods practices, motivating questions about how to adopt a more flexible and dynamic Requirements Engineering (RE), distinct from the traditional model. What makes suitable to exploring the advances of agile RE in diverse and challenging environments. Therefore, this paper aims on identifying and understanding the current scenario regarding practices and techniques within Agil RE, as well as its challenges and lessons learned. An extension of a systematic literature review study was conducted to carry out this analysis and the evidence is synthesized from sources published between 2017 and 2020. In addition, the work delivers a compiled of practices, observing the different contexts of projects and organizations.

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“…Representative Studies: Cite studies that are emblematic of the use and evaluation of each ML technique in SEE[37].This table synthesizes a vast amount of information into a comparative format, helping identify which ML techniques have shown promise in SEE, under what conditions, and their relative performance. It's essential to critically assess each study's context, such as the project types and sizes it was evaluated on, to ensure the findings apply to your specific area of interest in SEE[38].Software Effort Estimation (SEE) relies heavily on datasets for developing and validating models, especially when employing Machine Learning (ML) techniques[39][40]. Below is an illustrative table showcasing a few wellknown SEE datasets, their volume (i.e., number of projects or data points), sources, and other relevant details[45].…”

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confidence: 99%

Novel Approach to Design a Model for Software Effort Estimation Using Linear Regression

Sachin Wakurdekar,

2024

jes

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Estimation of an effort is necessary to decide the time and cost needed for the completion of the project. Making judgments with a high degree of uncertainty is a serious issue in the field of software engineering. Software quality forecasting calls for highly precise technologies and expert knowledge. The forecast of software effort based on past data from software development metrics could, instead, be aided by AI-based predictive models, which have a high degree of accuracy. Using a linear regression model, we developed a software effort estimation model in this study to forecast this effort. A non-parametric linear regression approach based on K-Nearest Neighbors was used to create this statistical model (KNN). So, with a 76% coefficient of determination, our findings indicate the potential for applying AI algorithms to predict the software engineering work prediction problem.

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Prioritizing User Requirements for Agile Software Development

Cited by 7 publications

References 13 publications

Web Service Implementation “AI Yoga Trainer Using Human Pose Estimation” for Web Discovery

Web Service Implementation “AI Yoga Trainer Using Human Pose Estimation” for Web Discovery

Engenharia de Requisitos Ágil: Extensão de uma Revisão Sistemática da Literatura

Novel Approach to Design a Model for Software Effort Estimation Using Linear Regression

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