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Towards the applied Hybrid Model in Requirements Prioritization

Procedia Computer Science 2016年 91卷 909-918页

作者： Rômulo Santos Adriano Albuquerque Plácido Rogerio Pinheiro University of Fortaleza Graduate Program in Applied Informatics Av. Washington Soares 1321 - Bl J Sl 30 Fortaleza 60.811-905 Brazil

Although there are numerous prioritization techniques, few satisfy the quality criteria such as scalability, efficiency and easiness of usage. This research presents a case study of Commercial Off-The-Shelf (COTS) software requirements prioritization to be potentially used by thousands of users. The HCV(Hierarchical Cumulative Voting) requirements prioritization technique was addressed and applied through a web questionnaire directly to potential users to analyze the benefit of the requirement criteria. Another aspects discussed were volatility of the requirements and market competition. In the end, eighty respondents sent in the questionnaire and a score of requirements in ratio scale of measurement was obtained, and the criteria have been consolidated through the Macbeth approach. It was found that the method could respond positively to the needs and characteristics of Market-Driven Software Development, in similar situations to those described.

关键词： Multicriteria Analysis Requirements Prioritization Hierarchical Cumulative Voting

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A Methodology for Risk Management of Generative AI based Systems

A Methodology for Risk Management of Generative AI based Sys...

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International Conference on Software, Telecommunications and Computer Networks (SoftCOM)

作者： Raimir Holanda Filho Daniel Colares Postgraduate Program in Applied Informatics University of Fortaleza Fortaleza Brazil

ISBN: (数字)9789532901382

ISBN: (纸本)9798350354614

This paper addresses cybersecurity challenges in integrating Generative Artificial Intelligence (GenAI) into applications. It proposes a risk analysis approach that focuses on identifying threats and vulnerabilities exploited by malicious actors, which is validated through a case study on prompt injection attacks. The results demonstrated the efficacy of our approach in identifying and quantifying vulnerabilities in Large Language Models (LLMs).

关键词： Generative AI Computational modeling Large language models Software Computer networks Telecommunications Risk management Computer crime Best practices

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A Machine Learning Application for Smart Government: Dashboards for Effective Taxation of Property Taxes

A Machine Learning Application for Smart Government: Dashboa...

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IEEE International Smart Cities Conference (ISC2)

作者： Lara S. Furtado Virginia Queiroz Cecília Carvalho Filipe F. Damasceno Antonio A. F. Oliveira Vladia Pinheiro Masters in City Science University of Fortaleza Fortaleza Brazil Graduate Program of Applied Informatics University of Fortaleza Fortaleza Brazil Secretariat of Finance of the Municipality of Fortaleza Fortaleza Brazil

ISBN: (数字)9798350364316

ISBN: (纸本)9798350364323

Smart Government initiatives aim to enhance governmental services by strategically applying digital technologies. Property tax assessment, a crucial aspect of government revenue, often faces challenges due to outdated methods and complex evaluation models. The procedures to estimate property values are time consuming since mass estimation must evaluate dozens of building features, some of which may not completely influence market values. For government appraisers, making sense of millions of spatial data is cumbersome and prone to error. This paper proposes a comprehensive framework integrating Machine Learning (ML), dashboards, and Geographic Information Systems to address these challenges. By leveraging ML algorithms, interactive dashboards, and geospatial data, tax agencies can streamline property assessment processes, improve accuracy, and facilitate real-time decision-making. A case study in fortaleza, Brazil, demonstrates the framework's effectiveness in enhancing land value assessment and property taxation within the Smart Governance context. This paper provides insights into the benefits and challenges of implementing such a framework and underscores its potential to revolutionize property tax assessment practices.

关键词： Machine learning algorithms Smart cities Government Evaluation models Finance Machine learning Spatial databases Real-time systems Geospatial analysis Faces

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Dealing the Selection of Project Management through Hybrid Model of Verbal Decision Analysis

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Procedia Computer Science 2013年 17卷 332-339页

作者： Plácido Rogerio Pinheiro Thais Cristina Sampaio Machado Isabelle Tamanini University of Fortaleza (UNIFOR) Graduate Program in Applied Informatics Av. Washington Soares 1321 - Bl J Sl 30 - 60.811-905 Fortaleza Brazil

The decision may be defined as a result of a process of choice, given an identified problem or when the decision maker faces an opportunity of creation, optimization or improvement in an environment. Considering that agile methodologies, in focus Framework SCRUM, are always more popular in Development Software Companies, and noticing that the mentioned companies cannot always apply every characteristics of the framework, this paper presents an hybrid application of methodologies from Verbal Decision Analysis (VDA) framework to select some of the SCRUM approaches to be applied in the company, considering the elicitation of preferences of a decision maker. The work intends to provide an evaluation of Project Management approaches applied in the Software Development and examine them toward to identify which are the most preferable ones, aided by the application of a hybrid model of decision making. The hybrid model aims at classifying alternatives using ORCLASS method, through the developed software, and ranking them using a Verbal Decision Analysis method (ZAPROS III-i). Afterward, Specific Practices (SP) of Capability Maturity Model Integration (CMMi) level 2 were chosen, and approaches to attend the SP's were ranked from the most preferable to the least preferable ones, aiming to help enterprises which are not able to reach a complete CMMi qualification.

关键词： Verbal Decision Analysis ZAPROS III-i ORCLASS Project Management Specific Practices Capability Maturity Model Integration

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The health of things for classification of protein structure using improved grey wolf optimization

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The Journal of Supercomputing 2018年第2期76卷 1226-1241页

作者： Prerna Sharma Apoorva Gupta Aastha Aggarwal Deepak Gupta Ashish Khanna Aboul Ella Hassanien Victor Hugo C. de Albuquerque Maharaja Agrasen Institute of Technology GGSIPU Dwarka India Faculty of Computers and Information Cairo University Cairo Egypt Graduate Program in Applied Informatics University of Fortaleza Fortaleza Brazil

In the field of computational biology, prediction of high-resolution protein structure is regarded as a major challenge. Physical and chemical properties of the protein structure determine its quality and differentiate native structures from predicted structures. Various machine learning classification models are studied with six physical and chemical properties to classify the root mean square deviation of the protein structure. This work proposes an improved version of a meta-heuristic technique named grey wolf optimization (IGWO), which is an extension of traditional grey wolf optimization (GWO) for the feature selection. The proposed novel IGWO ascertains optimal subset of features, and further, four machine learning classifiers have been used for efficient prediction of protein structure. Artificial neural network classifier predicts the protein structure with a maximum approximate accuracy of 91%. The experimental result reveals that the proposed meta-heuristic technique is stable enough to maximize the accuracy and minimize the number of optimal features. In this paper, the result of the proposed technique has been compared with other related evolutionary techniques and the proposed optimizer outperforms all other techniques. The dataset used in the study is available at http://***/RMSDClassification-DS.

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Adaptive optimal multi key based encryption for digital image security

Adaptive optimal multi key based encryption for digital imag...

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作者： Shankar, K. Lakshmanaprabu, S.K. Gupta, Deepak Khanna, Ashish de Albuquerque, Victor Hugo C. School of Computing Kalasalingam Academy of Research and Education Krishnankoil India B. S. Abdur Rahman Crescent Institute of Science and Technology Chennai India Maharaja Agrasen Institute of Technology Delhi India Graduate Program in Applied Informatics University of Fortaleza Fortaleza Brazil

The security of digital images is an essential and challenging task on shared communication Model. Generally, high secure working environment and data are also secured with an encryption and decryption method by using secret and public keys. In this paper, the innovative encryption technique for image security, ie, Multiple key-based Homomorphic Encryption (MHE) technique is proposed. For increasing the security level of encryption and decryption processes, the optimal key is selected using Adaptive Whale Optimization (AWO) algorithm. Fitness function was considered for optimization as PSNR of plain and cipher images. The original image was transformed into blocks and then rearranged utilizing encryption process, this work achieved maximum security, much better than other encryption techniques. From the outcomes, one can achieve incredible quality of the proposed model, the maximum PSNR, and the minimum MSE contrasted with other encryption schemes. © 2018 John Wiley & Sons, Ltd.

关键词： Cryptography

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Applying multi-criteria decision analysis to global software development with scrum project planning

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6th International Conference on Rough Sets and Knowledge Technology, RSKT 2011

作者： Almeida, Luis Henrique Pinheiro, Plácido Rogério Albuquerque, Adriano Bessa CPQi IT Offshore Solutions Av. Washington Soares 909 60.811-341 Fortaleza Brazil University of Fortaleza Graduate Program in Applied Computer Science Av. Washington Soares 1321 60811-905 Fortaleza Brazil

ISBN: (纸本)9783642244247

Distributed Software Development (DSD) projects have become a common reality for many organizations. Scrum is a consolidated Agile methodology and has been increasingly used in a distributed fashion. As distance makes difficult to interact and to cooperate effectively, it is paramount to use methodologies like Scrum that emphasizes communication, reduces coordination and control overhead. Successfully planning and managing the combined use of DSD and Scrum is a complex task and requires carefully planning. Despite the importance and complexity of this type of problem, there seems to be a lack of reports, in the literature, of models that could support managers dealing with such decision context. This paper applies a multi-criteria decision model on the choice of DSD Scrum project plans that have a better chance of success. The model, presented in [1], was developed using cognitive mapping and MACBETH[2]. The application of the model is demonstrated, followed by conclusion and future work. © 2011 Springer-Verlag.

关键词： Project management

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Model-Based Analysis of Microservice Resiliency Patterns

Model-Based Analysis of Microservice Resiliency Patterns

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Working IEEE/IFIP Conference on Software Architecture

作者： Nabor C. Mendonca Carlos M. Aderaldo Javier Camara David Garlan Post Graduate Program in Applied Informatics University of Fortaleza Brazil Post Graduate Program in Applied Informatics University of Fortaleza CE Brazil University of York York UK School of Computer Science Carnegie Mellon University Pittsburgh PA USA

ISBN: (数字)9781728146591

ISBN: (纸本)9781728146607

Microservice application developers try to mitigate the impact of partial outages typically by implementing service-to-service interactions that use well-known resiliency patterns, such as Retry, Fail Fast, and Circuit Breaker. However, those resiliency patterns-as well as their available open-source implementations-are often documented informally, leaving it up to application developers to figure out when and how to use those patterns in the context of a particular microservice application. In this paper, we take a first step towards improving on this situation by introducing a model checking-based approach in which we use the PRISM probabilistic model checker to analyze the behavior of the Retry and Circuit Breaker resiliency patterns as continuous-time Markov chains (CTMC). This approach has enabled us to quantify the impact of applying each resiliency pattern on multiple quality attributes, as well as to determine how to best tune their parameters to deal with varying service availability conditions, in the context of a simple client-service interaction scenario.

关键词： Circuit breakers Resilience Integrated circuit modeling Probabilistic logic Transient analysis Circuit faults Analytical models

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A Multi-criteria Decision Model for Planning Inter-organizational Global Agile Software Development Projects

A Multi-criteria Decision Model for Planning Inter-organizat...

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作者： Almeida, Luis Henrique Albuquerque, Adriano Pinheiro, Plácido Rogério CPQi IT Offshore Solutions R. Chico Lemos 946 60822-780 Fortaleza Brazil Graduate Program in Applied Computer Science University of Fortaleza Av. Washington Soares 1321 60811-905 Fortaleza Brazil

ISBN: (纸本)9783642358784

Inter-organizational Global Software Development (GSD) has become a common reality for many projects. It is well established that distance makes difficult to interact and to cooperate effectively. Scrum, a consolidated Agile methodology, emphasizes communication, reduces coordination and control overhead and has been increasingly used in a distributed fashion. Successfully planning and managing the combined use of GSD and Scrum is a complex task and requires carefully planning. Despite the importance and complexity of this type of problem, there seems to be a lack of reports, in the literature, of models that could support managers dealing with these decision contexts. This paper presents a multi-criteria decision model for planning and fine-tuning such project plans. This model was developed using cognitive mapping and MACBETH [1]. The application of the model is demonstrated, followed by conclusion and future work. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Project management

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Requirements Prioritization in Market-Driven Software: A Survey Based on Large Numbers of Stakeholders and Requirements

Requirements Prioritization in Market-Driven Software: A Sur...

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International Conference on the Quality of Information and Communications Technology (QUATIC)

作者： Jorge Rômulo Frota Dos Santos Adriano Bessa Albuquerque Plácido Rogério Pinheiro Grad. Program in Appl. Inf. Universidade de Fortaleza Fortaleza CE BR Graduate Program in Applied Informatics University of Fortaleza Fortaleza Ceara Brazil

The launch of commercial off-the-shelf (COTS) software on the market requires careful planning, which incorporates a requirements prioritization process. Although there are numerous prioritization techniques, few satisfy quality criteria such as scalability, efficiency and ease of use. This research presents a survey of COTS software requirements prioritization to be potentially used by thousands of users. The HCV (Hierarchical Cumulative Voting) requirements prioritization technique was addressed and applied through a web questionnaire directly to potential users. At the end, 80 respondents sent the questionnaire and a score of requirements in ratio scale of measurement was obtained. It was found that the technique applied can respond positively to the needs and characteristics of Market-Driven Software Development, in similar situations to those described.

关键词： Software Stakeholders Credit cards Planning Scalability Finance Internet

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