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10th International Conference on the Quality of Information and Communications Technology, QUATIC 2016

作者： Da Silva, Lilian Santos Ferreira Oliveira, Sandro Ronaldo Bezerra Graduate Program in Computer Science Federal University of Pará Belém Pará Brazil

ISBN: (纸本)9781509035816

From the importance of the portfolio management process has gained by its inclusion in quality models and standards, the amount of organization looking to implement this process effectively and efficiently has increased. Thus, this research seeks to assist in the implementation of portfolio management in small and medium-sized enterprises, reducing the difficulties and excessive documentation required in traditional processes. For this, a mapping between a portfolio management process framework and agile practices was made, the result was a guide defining how to implement this process framework with agile practices, focusing on the interaction between people. © 2016 IEEE.

关键词： Investments

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A multi-criteria model for planning and fine-tuning distributed Scrum projects

A multi-criteria model for planning and fine-tuning distribu...

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6th IEEE International Conference on Global Software Engineering, ICGSE 2011

作者： Almeida, Luis Henrique Albuquerque, Adriano Bessa Pinheiro, Plácido Rogério Graduate Program in Applied Computer Science University of Fortaleza Fortaleza 60811-905 Brazil

ISBN: (纸本)9780769545035

Distributed software development is a fact of life for many projects. It is well established that distance makes difficult to interact and to cooperate effectively. Scrum emphasizes communication, reduces coordination and control overhead;therefore it has enormous potential to help the management of distributed projects and has been increasingly used. Successfully managing the combined use of DSD and Scrum is a complex task and it 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 project managers dealing with these decision contexts. This paper presents a multi-criteria decision model for planning and finetuning such project plans. This model was developed using cognitive mapping and MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique). The application of the model is demonstrated, followed by conclusion and remarks about future work. © 2011 IEEE.

关键词： Software design

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Exploring Transfer Learning Approach for Environmental Sound Classification: A Comparative Analysis

Exploring Transfer Learning Approach for Environmental Sound...

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2024 International Conference on Smart Computing, IoT and Machine Learning, SIML 2024

作者： Rochadiani, Theresia Herlina Arifin, Yulyani Suhartono, Derwin Budiharto, Widodo Bina Nusantara University Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program - Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350364101

The expansion of deep learning techniques, as well as the availability of large audio/sound datasets, have fueled tremendous breakthroughs in audio/sound classification during the last several years. The transfer learning approach has emerged as one of the primary approaches for improving the accuracy and durability of classification systems. This study conducts a comprehensive comparative analysis to determine the effectiveness and performance of this method in environment sound classification. This current investigation focuses on environmental sound classification using VGGish and YAMNet pre-trained models with the ESC-50 and BDLib2 datasets. In the ESC-50 dataset, VGGish improves accuracy to 372.22%, while YAMNet improves accuracy to 383.33% when compared to baseline models. Similarly, in the BDLib2 dataset, accuracy increases significantly to 221.43% with VGGish and 246.43% with YAMNet. Transfer learning exhibits remarkable effectiveness in enhancing model performance, with significant accuracy boosts observed in both datasets. YAMNet, designed specifically for sound classification tasks, surpasses VGGish in improving environmental sound classification performance, potentially due to its architecture's adaptability and diverse training on environmental sounds. © 2024 IEEE.

关键词： Deep learning

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Exploiting Approximations in Supervisory Control with Distinguishers

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IFAC-PapersOnLine 2018年第7期51卷 13-18页

作者： Rosa, Marcelo Teixeira, Marcelo Malik, Robi Graduate Program in Electrical Engineering Federal University of Technology Paraná Pato Branco Brazil Department of Computer Science University of Waikato Hamilton New Zealand

Distinguishers have been used in Supervisory Control Theory (SCT) of Discrete Event Systems, as a way to simplify modeling tasks. Approximations complement this approach with an alternative to also reduce synthesis effort. Despite the advantages, supervisors obtained from approximated DES plants can be suboptimal, so that the modeling structure has to be reconstructed empirically, until the proper supervisor is found. In this paper we show how to construct suitable-approximations that always lead to least restrictive controllable synthesis. A manufacturing system example is provided to illustrate the approach. © 2018

关键词： Discrete event simulation Automation Control engineering Control theory Controllability Manufacture Models Supervisory personnel Controllable synthesis Distinguishers Modeling structures Modeling task Supervisory control Supervisory control theory

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The Internet of Things: Real-Time Monitoring System for Production Machine 5

The Internet of Things: Real-Time Monitoring System for Prod...

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5th IEEE International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2021

作者： Tarigan, Masmur Heryadi, Yaya Lukas Wibowo, Antoni Suparta, Wayan Bina Nusantara University Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Department Jakarta Indonesia Jakarta Indonesia Bina Nusantara University Computer Science Department Jakarta Indonesia Faculty Of Computer Science Esa Unggul University Jakarta Indonesia

ISBN: (纸本)9781665401968

The importance of optimization in the manufacturing industry to achieve efficiency and effectiveness, especially in production machines. This research focuses on developing a real-time monitoring system based on the internet to monitor power consumption and production machines' speed accurately. The data taken by the real-time monitoring system is integrated into the ERP System, which is stored as time series data of power consumption and engine speed. The importance of making production cost estimates, especially on the power consumption of a production machine for the future, and functioning as a tool for real-time monitoring, the data obtained is processed by regression to get an estimate of the total power consumption for several expected outputs. The data is processed using a linear regression algorithm to predict power consumption at the desired speed on the intended production machine. To get a better tool than the one that existed before, the method in its development uses PIECES analysis. In its implementation, this real-time monitoring system runs according to the objectives, and the data obtained is as expected. This model was developed on production machines in the flexible packaging industry that uses rotogravure machines. It is possible that it can be used on production machines in other industries that use electrical power correlated with the speed measured based on the rotation of a motor. © 2021 IEEE.

关键词： Internet of things

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Comprehensive Analysis and Remediation of Insecure Direct Object References (IDOR) Vulnerabilities in Android APIs 1

Comprehensive Analysis and Remediation of Insecure Direct Ob...

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1st IEEE International Conference on Cryptography, Informatics, and Cybersecurity, ICoCICs 2023

作者： Yulianto, Semi Abdullah, Roni Reza Soewito, Benfano Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia National Institute of Science and Technology Faculty of Informatics Engineering Jakarta12630 Indonesia Bina Nusantara University Binus Graduate Program. Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350339437

The escalating visibility of secure direct object reference (IDOR) vulnerabilities in API security, as indicated in the compilation of OWASP Top 10 API Security Risks, highlights a noteworthy peril to sensitive data. This study explores IDOR vulnerabilities found within Android APIs, intending to clarify their inception while evaluating their implications for application security. This study combined the qualitative and quantitative approaches. Insights were obtained from an actual penetration test on an Android app into the primary reasons for IDOR vulnerabilities, underscoring insufficient input validation and weak authorization methods. We stress the frequent occurrence of IDOR vulnerabilities in the OWASP Top 10 API vulnerability list, highlighting the necessity to prioritize them in security evaluations. There are mitigation recommendations available for developers, which recognize its limitations involving a possibly small and homogeneous selection of tested Android applications, the testing environment that could cause some inaccuracies, and the impact of time constraints. Additionally, the study noted insufficient threat modeling and root cause analysis, affecting its generalizability and real-world relevance. However, comprehending and controlling IDOR dangers can enhance Android API security, protect user data, and bolster application resilience. © 2023 IEEE.

关键词： Sensitive data

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Design Project Management System Based on SOA Approach

Design Project Management System Based on SOA Approach

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International Conference on Computation in science and Engineering, ICCSE 2017

作者： Girsang, Abba Suganda Jafar, Fahmi Fajar, Ahmad Nurul Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information System Computer Science Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

Application architecture and information technology systems in the company should be able to support the company's policy that leads to their alignment with the business objectives. The alignment of the implementation of information technology systems to the needs and goals of the organization will be able to be answered by taking into account the integration in the development, so that the gap of these two things can be minimized. As a company engaged in IT consulting, project management system is one form of application systems that support core business objective of the company: to produce high-quality software. Nevertheless, the project management system should be able to work together with other supporting information systems, so that the flow of information within the company can run effectively. To achieve these objectives, required the analysis and design of an integrated system, which can be achieved through a service-oriented architecture based system. which includes the stages of requirements and analysis, design and development, and the last is the IT operations. The final result expected is the design of the service-oriented architecture based project management system which built through top-down approach that focuses on improving the effectiveness of business process. © Published under licence by IOP Publishing Ltd.

关键词： Service oriented architecture (SOA)

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Mining Association rule with Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) data mining technique 2

Mining Association rule with Attribute Oriented Induction Hi...

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2nd International Conference on Inventive Communication and Computational Technologies, ICICCT 2018

作者： Warnars, Harco Leslie Hendric Spits Gaol, Ford Lumban Heryadi, Yaya Trisetyarso, Agung Sanchez, Horacio Emilio Perez Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta11480 Indonesia Guadalupe30107 Spain

ISBN: (纸本)9781538619742

Attribute Oriented Induction High level Emerging Pattern (AOI-HEP) as proposed new data mining technique has been success to mine frequent and similar patterns. Moreover, the AOI-HEP data mining technique has been improved with confidence mining pattern into two terms, where firstly give confidence mining pattern for each AOI-HEP pattern either frequent or similar pattern. Secondly, give confidence for each dataset as confidence AOI-HEP pattern between frequent and similar patterns. Confidence for each AOI-HEP pattern will show how interested each of AOI-HEP pattern between frequent and similar pattern, whilst confidence per dataset will show how interested each dataset between frequent and similar pattern. In this paper the mining of AOI-HEP has been extended to mine AOI-HEP association rules using the current AOI-HEP frequent pattern, since association rule deal with frequent pattern. Based from previous experiments upon 4 UCI machine learning datasets such as adult, breast cancer, census and IPUMS, there are 9 finding AOI-HEP frequent patterns where 8 from adult and breast cancer datasets respectively. Finally, there are 2 and 1 AOI-HEP association rules from adult and breast cancer datasets respectively. © 2018 IEEE.

关键词： Association rules

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Telematics Work Field Review Text Classification Using the Naïve Bayes Method

Telematics Work Field Review Text Classification Using the N...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Maesya, Aries Heryadi, Yaya Arifin, Yulyani Lukas Suparta, Wayan Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia Faculty of Engineering Indonesia

ISBN: (纸本)9781665468763

Indonesia will benefit from a demographic boom in 2030 with a higher labor supply than in earlier decades. Then in industrial revolution 4.0 robotics and artificial intelligence will take the place of low-skilled or menial employment that don't require specialized expertise (AI). To aim research is Telematics Work Field Review Text Classification Using the Naïve Bayes Method. The method using Multinomial Naïve Bayes model which is trained to learn from patterns in training data set without being programmed explicitly. Then, based on the Term Frequency - Inverse Document Frequency, consider the weighting of the word used (TF-IDF). The text classification stage is then carried out using the multinominal nave bayes classification method with evaluation using the confusion matrix, following the acquisition of the TF-IDF value. In the study it took data with web crawling techniques on social media sites twitter. The data collected was 936 data consisting of 7,8% negative sentiments, 26,4% positive sentiments, and 65,8% neutrals. The results of accuracy testing using the Confusion Matrix. And from the results of such tests resulted in an accuracy of 66%, precision 73%, and recall 85%. © 2022 IEEE.

关键词： Telematics

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Explainable Supervised Method for Genetics Ancestry Estimation 1

Explainable Supervised Method for Genetics Ancestry Estimati...

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1st International Conference on computer science and Artificial Intelligence, ICCSAI 2021

作者： Budiarto, Arif Pardamean, Bens Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9781728133331

Ancestry estimation is one crucial stage in genomic research. It generates scores that represent the admixed genetics profile as the result of human evolution. In the previous research, we implemented multiple unsupervised methods to estimate these scores from large genomics data obtained from the 1000 Genome Project. These methods were limited to only cluster the samples to the five global populations in the dataset. The main challenge arose when implementing these methods to cluster the samples into more specific subpopulations. In this paper, we proposed a supervised approach to answer this challenge. Two state-of-the-art supervised machine learning methods, XGBoost and Deep Neural Network (DNN), were applied to the same dataset. These methods were aimed to classify samples, both into five main populations and also into 26 sub-populations. In the first classification task, both methods achieved similar results to our previous unsupervised approach. Interestingly, for the second classification task, which posses a relatively higher difficulty, DNN yielded better performance in the train, validation, and test dataset, despite its overfitting problem. Furthermore, the feature importance scores from each model were calculated using Shapley Additive Explanations (SHAP) method. Finally, 11 overlapped SNPs from all models were evaluated based on the reported Minor Allele Frequency (MAF) from the 1000 Genome Project. Overall, only using these 11 SNPs, we could differentiate each population in regards to its average MAF. © 2021 IEEE.

关键词： Genome

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