NON-INVASIVE IMAGE DENOISING AND CONTRAST ENHANCEMENT TECHNIQUES FOR RETINAL FUNDUS IMAGES

The analysis of retinal vasculature in digital fundus images is important for diagnosing eye related diseases. However, digital colour fundus images suffer from low and varied contrast, and are also affected by noise, requiring the use of fundus angiogram modality. The Fundus Fluorescein Angiogram (FFA) modality gives 5 to 6 time’s higher contrast. However, FFA is an invasive method that requires contrast agents to be injected and this can lead other physiological problems. A reported digital image enhancement technique named RETICA that combines Retinex and ICA (Independent Component Analysis) techniques, reduces varied contrast, and enhances the low contrast blood vessels of model fundus images

Majority Rule: better patching via Self-Consistency

Large Language models (LLMs) can be induced to solve non-trivial problems with "few-shot" prompts including illustrative problem-solution examples. Now if the few-shots also include "chain of thought" (CoT) explanations, which are of the form problem-explanation-solution, LLMs will generate a "explained" solution, and perform even better. Recently an exciting, substantially better technique, self-consistency [1] (S-C) has emerged, based on the intuition that there are many plausible explanations for the right solution; when the LLM is sampled repeatedly to generate a pool of explanation-solution pairs, for a given problem, the most frequently occurring solutions in the pool (ignoring the explanations) tend to be even more likely to be correct! Unfortunately, the use of this highly-performant S-C (or even CoT) approach in software engineering settings is hampered by the lack of explanations; most software datasets lack explanations. In this paper, we describe an application of the S-C approach to program repair, using the commit log on the fix as the explanation, only in the illustrative few-shots. We achieve state-of-the art results, beating previous approaches to prompting-based program repair, on the MODIT dataset; we also find evidence suggesting that the correct commit messages are helping the LLM learn to produce better patches

The Effect of Backrest Roller on Warp Tension in Modern Loom

The Backrest roller is one of the key parts of the weaving machine. In this study, the effect of the various position of backrest and dropper has been assessed. The tension is measured by using the integrated tension measuring device of the loom. The tension can be found on the display board. The effect of backrest position can be described in two different ways viz. keeping constant dropper position (distance between dropper line and backrest roller) and keeping constant dropper depth (distance between held frame and dropper line). If dropper position (distance between backrest roller to dropper line) is kept constant then the backward movement of backrest roller will entail low tension. The reason behind this is, the dropper weight will be moved toward the backrest roller and will lose its influence on warp tension. But if dropper depth is kept constant (i,e dropper line is kept intact) then the backward movement of backrest will require more tension as the influence of dropper will more on warp length. On the other hand, when backrest height is lowered then, the downward movement of backrest roller will need low tension and upward movement of backrest roller will need more tension. As the warp length and lap angle increases with the backrest height. In this paper, the whole phenomenon is explained with illustration

Improving Few-Shot Prompts with Relevant Static Analysis Products

Large Language Models (LLM) are a new class of computation engines, "programmed" via prompt engineering. We are still learning how to best "program" these LLMs to help developers. We start with the intuition that developers tend to consciously and unconsciously have a collection of semantics facts in mind when working on coding tasks. Mostly these are shallow, simple facts arising from a quick read. For a function, examples of facts might include parameter and local variable names, return expressions, simple pre- and post-conditions, and basic control and data flow, etc. One might assume that the powerful multi-layer architecture of transformer-style LLMs makes them inherently capable of doing this simple level of "code analysis" and extracting such information, implicitly, while processing code: but are they, really? If they aren't, could explicitly adding this information help? Our goal here is to investigate this question, using the code summarization task and evaluate whether automatically augmenting an LLM's prompt with semantic facts explicitly, actually helps. Prior work shows that LLM performance on code summarization benefits from few-shot samples drawn either from the same-project or from examples found via information retrieval methods (such as BM25). While summarization performance has steadily increased since the early days, there is still room for improvement: LLM performance on code summarization still lags its performance on natural-language tasks like translation and text summarization. We find that adding semantic facts actually does help! This approach improves performance in several different settings suggested by prior work, including for two different Large Language Models. In most cases, improvement nears or exceeds 2 BLEU; for the PHP language in the challenging CodeSearchNet dataset, this augmentation actually yields performance surpassing 30 BLEU

The Fundamental Deviation and the Riddle of Manipulation: A Critical Analysis in the Context of Bangladesh Stock Market Crash in 2010-11

The capital market in Bangladesh does not always act based on the fundamentals. Fundamental means the set of ethics, principles, guidance, various market instruments and well structural set up that helps the stock market for operating well. Structural weakness is a thing which may ruin the market base or fundamentals. But the capital market as part of the economy should function based on the fundamental norms, principles and proper rules and regulations. Otherwise, there may be some detrimental effects on the market. Stock market anomalies bring harm not only to destroy market fundamentals but also to spread manipulation inside the stock market. Moreover, the recent stock market crash in 2010-11 was the biggest shock for the 3.3 million innocent and small investors in the capital market of Bangladesh. A section of greedy investors resorted to manipulation at different levels to cash in on the lack of small investors’ proper knowledge about market fundamentals. The excessive fraudulent activities of the unscrupulous manipulators just hastened the fall of the market. So, much of the focus of this study has been put on the causes and consequences of the fundamental deviation and the riddle of manipulation based on the relevant facts and figures

Loom Settings and Fabric Structure: Two Major Influencing Factors of Warp Tension Variation

The Warp tension has a great influence on fabric quality and production. Warp tension is related with various loom settings like backrest position, backrest height, dropper position, dropper height and fabric structure. If backrest roller is moved at backward position keeping the dropper line intact then the required warp tension will be reduced. But if the intact dropper line comes at the middle due to the changing of backrest roller position then the required tension will be high. Tension is also influenced by backrest height like higher backrest height will need high tension and lower backrest height will need low tension. Again, dropper position and dropper height affect the tension at a large scale. When the dropper position (distance from backrest to dropper line) increases then the required tension will also increase. In case of dropper height, when dropper line is lifted then the required tension will be decreased provided that the dropper line is situated about the middle position of warp yarn. However when the dropper line is situated closer to the heald frame then the effect of dropper height will be substituted by the effect of dropper position. On the other hand fabric structure or weave has substantial influence on warp tension. Plain weave require more tension than any other weave

Future of Microgrids with Distributed Generation and Electric Vehicles

This chapter examines the current energy scenario for microgrids over the world and discusses the challenges and opportunities due to the increasing penetration of distributed power generation systems and electric vehicles (EVs) into the microgrids. Wind power and solar power can be generated by wind turbines and photovoltaics, respectively, while these are intermittent in nature. EVs and hybrid EVs use a battery energy storage system and charging facilities while the latter also include an Internal Combustion Engine (ICE) to provide an extra energy source. The features of these systems in the context of microgrids are studied in detail, in terms of their components, efficiency, reliability, charging and discharging arrangements, active and reactive power control. The chapter provides a reference to the development of microgrid systems especially for developing countries