GE8151-PROBLEM SOLVING AND PYTHON PROGRAMMING-UNIT I
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Rigor, ethics, wellbeing and resilience in the ICT doctoral journey
Rigor, ethics, wellbeing and resilience in the ICT doctoral journeyYannis The doctoral thesis trajectory has been often characterized as a “long and windy road” or a journey to “Ithaka”, suggesting the promises and challenges of this journey of initiation to research. The doctoral candidates need to complete such journey (i) preserving and even enhancing their wellbeing, (ii) overcoming the many challenges through resilience, while keeping (iii) high standards of ethics and (iv) scientific rigor. This talk will provide a personal account of lessons learnt and recommendations from a senior researcher over his 30+ years of doctoral supervision and care for doctoral students. Specific attention will be paid on the special features of the (i) interdisciplinary doctoral research that involves Information and Communications Technologies (ICT) and other scientific traditions, and (ii) the challenges faced in the complex technological and research landscape dominated by Artificial Intelligence.
22PCOAM16 _ML_Unit 3 Notes & Question bank
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📦 What Is LED Binning?
• The process of sorting LEDs by color temperature, brightness, voltage, and CRI
• Ensures visual and performance consistency across large installations
🎨 Why It Matters:
• Inconsistent binning leads to uneven color and brightness
• Impacts brand perception, customer satisfaction, and warranty claims
📊 Key Concepts Explained:
• SDCM (Standard Deviation of Color Matching)
• Recommended bin tolerances by application (e.g., 1–3 SDCM for retail/museums)
• How to read bin codes from LED datasheets
• The difference between ANSI/NEMA standards and proprietary bin maps
🧠 Advanced Practices:
• AI-assisted bin prediction
• Color blending and dynamic calibration
• Customized binning for high-end or global projects
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Top Cite Articles- International Journal on Soft Computing, Artificial Intell...
Top Cite Articles- International Journal on Soft Computing, Artificial Intell...ijscai International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI) is an open access peer-reviewed journal that provides an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Soft Computing. The Journal looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the Journal is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
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A Comprehensive Investigation into the Accuracy of Soft Computing Tools for D...
A Comprehensive Investigation into the Accuracy of Soft Computing Tools for D...Journal of Soft Computing in Civil Engineering This study will provide the audience with an understanding of the capabilities of soft tools such as Artificial Neural Networks (ANN), Support Vector Regression (SVR), Model Trees (MT), and Multi-Gene Genetic Programming (MGGP) as a statistical downscaling tool. Many projects are underway around the world to downscale the data from Global Climate Models (GCM). The majority of the statistical tools have a lengthy downscaling pipeline to follow. To improve its accuracy, the GCM data is re-gridded according to the grid points of the observed data, standardized, and, sometimes, bias-removal is required. The current work suggests that future precipitation can be predicted by using precipitation data from the nearest four grid points as input to soft tools and observed precipitation as output. This research aims to estimate precipitation trends in the near future (2021-2050), using 5 GCMs, for Pune, in the state of Maharashtra, India. The findings indicate that each one of the soft tools can model the precipitation with excellent accuracy as compared to the traditional method of Distribution Based Scaling (DBS). The results show that ANN models appear to give the best results, followed by MT, then MGGP, and finally SVR. This work is one of a kind in that it provides insights into the changing monsoon season in Pune. The anticipated average precipitation levels depict a rise of 300–500% in January, along with increases of 200-300% in February and March, and a 100-150% increase for April and December. In contrast, rainfall appears to be decreasing by 20-30% between June and September.
A DECISION SUPPORT SYSTEM FOR ESTIMATING COST OF SOFTWARE PROJECTS USING A HY...
A DECISION SUPPORT SYSTEM FOR ESTIMATING COST OF SOFTWARE PROJECTS USING A HY...ijfcstjournal One of the major challenges for software, nowadays, is software cost estimation. It refers to estimating the
cost of all activities including software development, design, supervision, maintenance and so on. Accurate
cost-estimation of software projects optimizes the internal and external processes, staff works, efforts and
the overheads to be coordinated with one another. In the management software projects, estimation must
be taken into account so that reduces costs, timing and possible risks to avoid project failure. In this paper,
a decision- support system using a combination of multi-layer artificial neural network and decision tree is
proposed to estimate the cost of software projects. In the model included into the proposed system,
normalizing factors, which is vital in evaluating efforts and costs estimation, is carried out using C4.5
decision tree. Moreover, testing and training factors are done by multi-layer artificial neural network and
the most optimal values are allocated to them. The experimental results and evaluations on Dataset
NASA60 show that the proposed system has less amount of the total average relative error compared with
COCOMO model.
A Comprehensive Investigation into the Accuracy of Soft Computing Tools for D...
A Comprehensive Investigation into the Accuracy of Soft Computing Tools for D...Journal of Soft Computing in Civil Engineering
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