LODチャレンジ実行委員会 関西支部長 古崎晃司
LODチャレンジ実行委員会/Linked Open Data Initiative理事 松村冬子
Linked Open Dataの基本的な技術の解説,利用事例の紹介に加え,簡単なサンプルプログラムの紹介など,ハッカソンに活用できるLOD技術や情報ソースについて解説します.
第3回Linked Open Dataハッカソン関西(1日目)アイデアソン
開催日:2014年2月11日(火)
Several recent papers have explored self-supervised learning methods for vision transformers (ViT). Key approaches include:
1. Masked prediction tasks that predict masked patches of the input image.
2. Contrastive learning using techniques like MoCo to learn representations by contrasting augmented views of the same image.
3. Self-distillation methods like DINO that distill a teacher ViT into a student ViT using different views of the same image.
4. Hybrid approaches that combine masked prediction with self-distillation, such as iBOT.
This document summarizes a research paper on scaling laws for neural language models. Some key findings of the paper include:
- Language model performance depends strongly on model scale and weakly on model shape. With enough compute and data, performance scales as a power law of parameters, compute, and data.
- Overfitting is universal, with penalties depending on the ratio of parameters to data.
- Large models have higher sample efficiency and can reach the same performance levels with less optimization steps and data points.
- The paper motivated subsequent work by OpenAI on applying scaling laws to other domains like computer vision and developing increasingly large language models like GPT-3.
LODチャレンジ実行委員会 関西支部長 古崎晃司
LODチャレンジ実行委員会/Linked Open Data Initiative理事 松村冬子
Linked Open Dataの基本的な技術の解説,利用事例の紹介に加え,簡単なサンプルプログラムの紹介など,ハッカソンに活用できるLOD技術や情報ソースについて解説します.
第3回Linked Open Dataハッカソン関西(1日目)アイデアソン
開催日:2014年2月11日(火)
Several recent papers have explored self-supervised learning methods for vision transformers (ViT). Key approaches include:
1. Masked prediction tasks that predict masked patches of the input image.
2. Contrastive learning using techniques like MoCo to learn representations by contrasting augmented views of the same image.
3. Self-distillation methods like DINO that distill a teacher ViT into a student ViT using different views of the same image.
4. Hybrid approaches that combine masked prediction with self-distillation, such as iBOT.
This document summarizes a research paper on scaling laws for neural language models. Some key findings of the paper include:
- Language model performance depends strongly on model scale and weakly on model shape. With enough compute and data, performance scales as a power law of parameters, compute, and data.
- Overfitting is universal, with penalties depending on the ratio of parameters to data.
- Large models have higher sample efficiency and can reach the same performance levels with less optimization steps and data points.
- The paper motivated subsequent work by OpenAI on applying scaling laws to other domains like computer vision and developing increasingly large language models like GPT-3.
IoT(internet of things) devices may be very dangerous for society. IoT cyber security Counter measurement will be proposed. Before study, check some slides, youtube movies and/or quiita contents. Main part will be announced at the room. HAZOP study for security analysis will be introduced today. Electric power source, harmonic generation, smoking, firing, wireless, noise, and human resources are discussed.
On 16 November 2011, Japan Embedded Systems Technology Association (JASA) announced that Platform Research Group of Engineering division has started work on the specification of OpenEL (Embedded Libraries) for Robot.
OpenEL for Robot is an open platform to standardize the specifications of the software implementation of robotics and control systems.
This is the Japanese version of the presentation materials that were presented at Embedded Technology 2011 in Japan. The English version is under construction.
This document discusses the concept of "dividual" or "fragmented person" and proposes a "dividual-type society". It explains that in anthropology, a dividual refers to a person composed of multiple, overlapping relationships and identities, rather than a single, fixed individual. It also discusses how philosophers like Deleuze have analyzed modern society as fragmenting people into dividuals through constant monitoring and data collection. The document argues that a dividual-type society is one where relationships and connections between people are prioritized over ideas of single, independent individuals. It proposes that understanding people as dividuals composed of multiple aspects could make society more inclusive and flexible.
1. The document appears to be a collection of various information on different topics including taxonomy, concepts, papers, events, statistics, and more.
2. It includes definitions of concepts, taxonomic classifications of species over time, bibliographic information on papers, event details, usage statistics of ontology types, and other miscellaneous information.
3. The document touches on a wide range of subjects in a disorganized manner, compiling unrelated facts and references from different domains.
Presented at Journal Paper Track, The Web Conference, Lyon, France, April 15, 2018
https://doi.org/10.1145/3184558.3186234
Abstract: Linked Open Data (LOD) technology enables web of data and exchangeable knowledge graphs through the Internet. However, the change in knowledge is happened everywhere and every time, and it becomes a challenging issue of linking data precisely because the misinterpretation and misunderstanding of some terms and concepts may be dissimilar under different context of time and different community knowledge. To solve this issue, we introduce an approach to the preservation of knowledge graph, and we select the biodiversity domain to be our case studies because knowledge of this domain is commonly changed and all changes are clearly documented. Our work produces an ontology, transformation rules, and an application to demonstrate that it is feasible to present and preserve knowledge graphs and provides open and accurate access to linked data. It covers changes in names and their relationships from different time and communities as can be seen in the cases of taxonomic knowledge.
We propose Crop Vocabulary(CVO) as a basis of the core vocabulary of crop names that becomes the guidelines for data interoperability between agricultural ICT systems on the food chain. Since a single species is treated in different ways, there are many different types of crop names. So, we organize the crop name discriminated by properties such as scientific name, planting method, edible part and registered cultivar information. Also, Crop Vocabulary is also linked to existing vocabularies issued by Japanese government agency and international organization such as AGROVOC. It is expected to use in the data format in the agricultural ICT system.
Presented in 45th Asia Pacific Advanced Network (APAN45) Meeting, Singapore (2018)
Presented as the invited talk at International Workshop on kNowledge eXplication for Industry (kNeXI2017). In this talk, I explain the experience and lesson learnt how to build ontologies. I am currently building the agriculture activity ontology (AAO). It describes classification and properties of various activities in the agriculture domain. It is formalized with Description Logics.
The Japan Link Center (JaLC) was founded in 2012 and is operated by four national organizations to register DOIs for academic content produced in Japan or Japanese. It provides DOI registration services through various methods to accommodate different types of content holders. Over 1.5 million DOIs have been registered since 2013 across various content categories like journal articles, books, theses, and research data. JaLC aims to connect different content producers and users through DOI assignment and resolution. It also engages in outreach activities to promote adoption of DOIs nationwide in a way that fits the local scholarly communication environment and business models in Japan.
Presented at the Interest Group on Agricultural Data (IGAD) ,3 April, 2017, Barcelona, Spain
Abstract: n this talk, we present the current status of our agriculture ontologies that are developed to accelerate the data use in agriculture.
The agriculture activity ontology formalizes the activities in agriculture. We have developed it for three years. Now we are developing its applications. One application is to exchange formats between different farmer management systems. Another ontology is the crop ontology that standardizes the names of crops. The structure is simple but has links to many other standards in distribution industry, food industry and so on.
The document describes the design process of the Agricultural Activity Ontology (AAO) in Japan. It involved surveying existing vocabularies, analyzing agricultural activity data, proposing an initial hierarchical structure, introducing description logics to define properties and relationships, and getting feedback from domain experts. The goal was to standardize vocabulary for agricultural IT systems to improve data sharing and integration. The AAO continues to be expanded with new terms and linkages based on additional data sources through a collaborative and iterative design process.
- Scientific names for species can change over time as taxonomy knowledge evolves
- An event-centric ontology model represents names and changes through time using different URIs for taxon concepts at different times
- Transition and snapshot models can then simplify the descriptions by linking concepts over time or just showing current names
- This approach allows integrated representation of taxonomy knowledge and its revisions in a computable way
What the end of support of Windows 10 will mean?Atomu Hidaka
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What is the end of Windows 10 support? We have investigated and considered the past end of Windows support to find out what will happen when support ends. Although the end of support for Windows 10 is only half a year away, there are not many people who understand from a technical point of view what will happen when support ends, so we have summarized the facts that have happened in the past.
18. Semantic Webの目的“The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.” (セマンティックWebとは現在のWebの拡張であり,そこでは情報はちゃんと定義された意味を与えられていてコンピュータと人のよりよい協調が可能となる).The Semantic Web, Scientific American, May 2001, Tim Berners-Lee, James Hendler and OraLassilaThe Semantic Web is a vision: the idea of having data on the web defined and linked in a way that it can be used by machines not just for display purposes, but for automation, integration and reuse of data across various applications.(セマンティックWebとはビジョンである.データはきちんと定義されリンクされており,単に表示用ではなく自動化,統合,アプリケーションを超えたデータの再利用などに使える)http://www.w3.org/2001/sw/
19. Next Generation WebWebの進化HTML: 表示のためのWebXML:シンタックスをもったWeb?? :セマンティックスをもったWebなぜセマンティックスをWebのメカニズムの中に組み込なねばならないか人間のためのWebから人間と機械のためのWeb ヘcf. 機械ためだけのWeb
24. Semantic Webに関する会議World Wide Web ConferencesにおけるTrack2002-2007: Semantic Web2008,2009: Semantic / Data Webその他セマンティックWebコンファレンス(日本) 2001-2009RuleML (The International RuleML Symposium on Rule Interchange and Applications) 2005-
39. Linking Open Data (LOD)公開されたLinked Dataを集めるプロジェクト主要なLinked Data(データ変換)Dbpedia (Wikipedia) : 百科事典, 2.7億文Geonames:地名と緯度経度, 9300万文MusicBrainz:音楽WordNet:辞書DBLP bibliography:論文の書誌,2800万文US Census Data: 米国国勢調査(2000年), 10億文(クロール)FOAF (Friend Of A Friend):個人と個人関係のプロファイル(ラッパー)Flickr Wrapper