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#methods

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Public
ポイズン雷花

ＡＩ絵生成　Генерація зображень ШІ
ＡＩ絵生成ソフトで何処が失敗してるかと云えば、人間の体の構造や比率を充分学習させてないと云う点が大きい。
Основна помилка програмного забезпечення для створення зображень ШІ полягає в тому,

note.com/poison_raika/n/n501ac

<>

note（ノート）ＡＩ絵生成　Генерація зображень ШІ｜ポイズン雷花ＡＩ絵生成ソフトで何処が失敗してるかと云えば、人間の体の構造や比率を充分学習させてないと云う点が大きい。 各部位の配置や形状、詳しい構造等を３ｄモデルを絵に重ねて学習させる等の新しい仕法を開発する必要が有るのは明確です。 ただ画像を見せて学習させると云う従来の仕法では限界が有るのは明らか。特に手足の部分に乱れが非常に高い頻度で発生するのは皆さんもよく感じてるでしょう？ 勿論、人間だけでは無い。動物や物においても充分学習出来てない部分が多々有ります。 後は見えない部分も又３ｄで可視化して、全体を３次元で解析出来るシステムの構築が必要でしょう。対象が３ｄか２ｄに関わらず、そう云うアプローチ
#AI#3d#image
Public *
Douglas E. Welch

14 Ways to Quickly Improve Your Photography fro, Digital Photography School [Shared]

Feeling like your photography skills have plateaued? It happens to the best of us. One minute, you’re cruising along, picking up new techniques and elevating your sense of composition and light like a boss – and the next, you’ve hit a creative wall.

But don’t worry! While there’s no single magic bullet for improving your photography, I do have plenty of techniques and exercises that are designed to help you level up your skills, and that’s what I share in this article.

Note that different techniques will work better for different shooters, so if you don’t like a method, just skip it and move on. With any luck, you’ll find an approach that works for you, and you’ll be able to develop that creative eye once again.

welchwrite.com/blog/2025/03/26

The image features a person holding a Canon camera, positioned outdoors with a blurred background of greenery. The individual is wearing a bright orange sweater with the word "WING" partially visible. The camera strap is visible around the person's neck. The image has a blue and orange graphic overlay with the text "HOW TO IMPROVE YOUR PHOTOGRAPHY (FAST!)" in white, bold letters. The logo "ds" is present in the bottom left corner of the overlay. The overall composition suggests a focus on photography tips or a tutorial. Provided by @altbot, generated privately and locally using Ovis2-8B
#photography#photos#education
Public
Bioinfhotep

link.springer.com/article/10.1
#networksAnalysis #rstats #methods #bioinformatics

SpringerLinkCross-validation for training and testing co-occurrence network inference algorithms - BMC BioinformaticsBackground Microorganisms are found in almost every environment, including soil, water, air and inside other organisms, such as animals and plants. While some microorganisms cause diseases, most of them help in biological processes such as decomposition, fermentation and nutrient cycling. Much research has been conducted on the study of microbial communities in various environments and how their interactions and relationships can provide insight into various diseases. Co-occurrence network inference algorithms help us understand the complex associations of micro-organisms, especially bacteria. Existing network inference algorithms employ techniques such as correlation, regularized linear regression, and conditional dependence, which have different hyper-parameters that determine the sparsity of the network. These complex microbial communities form intricate ecological networks that are fundamental to ecosystem functioning and host health. Understanding these networks is crucial for developing targeted interventions in both environmental and clinical settings. The emergence of high-throughput sequencing technologies has generated unprecedented amounts of microbiome data, necessitating robust computational methods for network inference and validation. Results Previous methods for evaluating the quality of the inferred network include using external data, and network consistency across sub-samples, both of which have several drawbacks that limit their applicability in real microbiome composition data sets. We propose a novel cross-validation method to evaluate co-occurrence network inference algorithms, and new methods for applying existing algorithms to predict on test data. Our method demonstrates superior performance in handling compositional data and addressing the challenges of high dimensionality and sparsity inherent in real microbiome datasets. The proposed framework also provides robust estimates of network stability. Conclusions Our empirical study shows that the proposed cross-validation method is useful for hyper-parameter selection (training) and comparing the quality of inferred networks between different algorithms (testing). This advancement represents a significant step forward in microbiome network analysis, providing researchers with a reliable tool for understanding complex microbial interactions. The method’s applicability extends beyond microbiome studies to other fields where network inference from high-dimensional compositional data is crucial, such as gene regulatory networks and ecological food webs. Our framework establishes a new standard for validation in network inference, potentially accelerating discoveries in microbial ecology and human health.
Public
ポイズン雷花

ＡＩ絵生成　Генерація зображень ШІ
ＡＩ絵生成ソフトで何処が失敗してるかと云えば、人間の体の構造や比率を充分学習させてないと云う点が大きい。
Основна помилка програмного забезпечення для створення зображень ШІ полягає в тому,

note.com/poison_raika/n/n501ac

<>

note（ノート）ＡＩ絵生成　Генерація зображень ШІ｜ポイズン雷花ＡＩ絵生成ソフトで何処が失敗してるかと云えば、人間の体の構造や比率を充分学習させてないと云う点が大きい。 各部位の配置や形状、詳しい構造等を３ｄモデルを絵に重ねて学習させる等の新しい仕法を開発する必要が有るのは明確です。 ただ画像を見せて学習させると云う従来の仕法では限界が有るのは明らか。特に手足の部分に乱れが非常に高い頻度で発生するのは皆さんもよく感じてるでしょう？ 勿論、人間だけでは無い。動物や物においても充分学習出来てない部分が多々有ります。 後は見えない部分も又３ｄで可視化して、全体を３次元で解析出来るシステムの構築が必要でしょう。対象が３ｄか２ｄに関わらず、そう云うアプローチ
#AI#3d#image
Public
ポイズン雷花

ＡＩ絵生成　Генерація зображень ШІ
ＡＩ絵生成ソフトで何処が失敗してるかと云えば、人間の体の構造や比率を充分学習させてないと云う点が大きい。
Основна помилка програмного забезпечення для створення зображень ШІ полягає в тому,

note.com/poison_raika/n/n501ac

<>

note（ノート）ＡＩ絵生成　Генерація зображень ШІ｜ポイズン雷花ＡＩ絵生成ソフトで何処が失敗してるかと云えば、人間の体の構造や比率を充分学習させてないと云う点が大きい。 各部位の配置や形状、詳しい構造等を３ｄモデルを絵に重ねて学習させる等の新しい仕法を開発する必要が有るのは明確です。 ただ画像を見せて学習させると云う従来の仕法では限界が有るのは明らか。特に手足の部分に乱れが非常に高い頻度で発生するのは皆さんもよく感じてるでしょう？ 勿論、人間だけでは無い。動物や物においても充分学習出来てない部分が多々有ります。 後は見えない部分も又３ｄで可視化して、全体を３次元で解析出来るシステムの構築が必要でしょう。対象が３ｄか２ｄに関わらず、そう云うアプローチ
#AI#3d#image
Public
svoop ✊

Here's a #Ruby #design #question that regularly pops up in various contexts such as this: The Mailjet gem is a REST API adapter, 99% generated code. It exposes things as #class #methods like `Mailjet::Contact.create`. For a simpler, more consistent interface, I'm wrapping these in my own #PORO service class, all class methods as well, but I don't like this orgy of `class << self`. How to better design this? Here's a gist with the method bodies removed for readability: gist.github.com/svoop/25accb41

GitHub Gist: instantly share code, notes, and snippets.
Gistwebhook_service.rbGitHub Gist: instantly share code, notes, and snippets.
Public
Frédéric Rimet

and this paper also in MBMG erally nice : good work Tiina 😀
mbmg.pensoft.net/article/13083
Technology Readiness Level of biodiversity monitoring with molecular methods – where are we on the road to routine implementation?
by Laamanen et al.
#edna #methods #TRL #metabarcoding #standardisation

Metabarcoding and MetagenomicsTechnology Readiness Level of biodiversity monitoring with molecular methods – where are we on the road to routine implementation?Human activities are causing rapid biodiversity loss across ecosystems, affecting human well-being and crucial ecosystem services. Traditional biodiversity monitoring tools cannot keep up with the increasing demands of monitoring due to their limited spatial or temporal coverage, high costs, and lack of taxonomic expertise. Thus, implementation of novel molecular monitoring methods such as environmental DNA (eDNA) and DNA metabarcoding, are necessary. Molecular monitoring methods offer significant benefits for biodiversity monitoring and environmental assessment: high sensitivity and accuracy, non-invasive sampling, broad taxonomic range and cost and time efficiency. However, the diverse methodological approaches lead to poor comparability between studies and surveys, highlighting the need for standardised assessments. We used the Technology Readiness Level (TRL) framework to evaluate the maturity of molecular monitoring methods, providing a structured assessment of their readiness for routine use. In a systematic literature review, 420 articles fulfilling the study criteria were assessed and both individual studies and method categories ranked according to the TRL scale. The findings revealed a growing number of studies, particularly in aquatic environments, with most studies validating molecular technologies on a small scale but lacking large-scale system demonstrations. Aquatic eDNA-based methods targeting fish showed overall higher technology readiness compared to other sample types and taxa and applications of molecular monitoring methods ranked into the highest TRL were predominantly freshwater studies. Key barriers to the broader implementation of molecular methods to monitoring include the need for international standards, better quantitative estimates and comprehensive reference libraries. National and international cooperation is crucial for establishing common standards, ensuring reliable and comparable results and expediting the routine use of molecular methods in biodiversity monitoring. Recent efforts towards international standardisation are encouraging, but further coordinated actions are necessary for the global implementation and acceptance of these methods.
Public
Frédéric Rimet

Nice paper in MBMG about eDNA methods standardisation
mbmg.pensoft.net/article/13207
What is eDNA method standardisation and why do we need it? by Theroux et al.
#Environmental #DNA #lab #accreditation #management #methods #standardisation #edna

Metabarcoding and MetagenomicsWhat is eDNA method standardisation and why do we need it?The rapid advancement of environmental DNA (eDNA) science in the past two decades has inspired a concomitant growth in the development of eDNA sampling and analytical methods. However, these methods are often developed by individual laboratories or institutions, which can isolate protocols within programmes, agencies or regions and prevent the beneficial exchange of data and ideas. Recent efforts to advance national and international coordination have resulted in a groundswell of standardisation efforts, but there is still considerable confusion around the role of formal standards for regulatory or research applications. With this commentary, we hope to provide clarity on the terminology used in standardisation discussions, including the differences between formal standards and best practice guidelines. Additionally, we discuss how eDNA method choice may be informed by environmental management scenarios and review examples of formal eDNA method standards being used to inform management action. The eDNA community now has an opportunity to develop a roadmap for method development to help close standardisation gaps, advance eDNA method adoption and accelerate our ability to monitor biological life at the scales our current environmental challenges demand.
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Aral Balkan

Oh my goodness, how did I miss that in ES7 you can use a closure as a method. Goodbye `bind()`, you will not be missed :)

e.g.,

```js
class A {
b = () => console.log(this)
}

const a = new A()
a.b() // A { b: [Function: b] }

const c = a.b
c() // A { b: [Function:b] }
```

Nice! :)

**Edit**: Be careful with this. See this note by @marsup: mastodon.social/@marsup/113799

MastodonMarsup (@marsup@mastodon.social)@aral@mastodon.ar.al Respectfully, this looks like an anti-pattern. `b` won't be part of the prototype, potentially preventing some meta programming, and you're going to get a new `b` for each instance of that class, consuming that much more memory for each instance you hold.
#JavaScript#EcmaScript7#ES7
Continued thread
Public
Aurélien

A bunch of related HCI refs on deployment failures :

- Baumer & Silberman (2011). When the implication is not to design (technology).
- Gaver, Bowers, Kerridge, Boucher & Jarvis (2009). Anatomy of a failure: how we knew when our design went wrong, and what we learned from it.
- Into the wild: challenges and opportunities for field trial methods.
- Cracks in the Success Narrative: Rethinking Failure in Design Research through a Retrospective Trioethnography

#design#hci#methods
Public *
Thomas

I recommend reading #JacquesEllul "Le fascisme, fils du libéralisme" ("Fascism, son of Liberalism, 1937).

Ellul was an eye-witness of fascism in Italy, Germany and Spain. He argued that fascism is a method, not an ideology, a technology of the social. By using industrial organization methods it turns a society into a totalitarian enterprise.

An OCRed version of the articler is available on JSTOR (a free account is sufficient)..

Screenshot of Ellul's article in French. Here is the English translation (Google Translate didn't get it right): "(When people) faced thinking disembodied of its role, there was only one cry: death to Byzantinisms - we must act. To act, methods were found: one no longer searched for a reason to act, but for a justification for action. Doctrine was replaced by method - the electoral program. One would make a method of taking power, the same as a method of absorbing surplus wheat, but no general thought dominates and centers the act. And then we see appearing, in the domain of intelligence, the primacy of technique: because method is nothing other than a technique of intelligence. Here again, technique triumphs over what's human. Now this passage from system to method characterizes exactly, from the intellectual point of view, the passage from liberalism to fascism."
#Fascism#systemsthinking#methods
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