100+ Alternative Search Engines You Should Know by Kay Tan
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Understanding the Value of Arts & Culture | the AHRC Cultural Value
Understanding the value of arts & culture The AHRC Cultural Value Project Geoffrey Crossick & Patrycja Kaszynska 2 Understanding the value of arts & culture The AHRC Cultural Value Project Geoffrey Crossick & Patrycja Kaszynska THE AHRC CULTURAL VALUE PROJECT CONTENTS Foreword 3 4. The engaged citizen: civic agency 58 & civic engagement Executive summary 6 Preconditions for political engagement 59 Civic space and civic engagement: three case studies 61 Part 1 Introduction Creative challenge: cultural industries, digging 63 and climate change 1. Rethinking the terms of the cultural 12 Culture, conflict and post-conflict: 66 value debate a double-edged sword? The Cultural Value Project 12 Culture and art: a brief intellectual history 14 5. Communities, Regeneration and Space 71 Cultural policy and the many lives of cultural value 16 Place, identity and public art 71 Beyond dichotomies: the view from 19 Urban regeneration 74 Cultural Value Project awards Creative places, creative quarters 77 Prioritising experience and methodological diversity 21 Community arts 81 Coda: arts, culture and rural communities 83 2. Cross-cutting themes 25 Modes of cultural engagement 25 6. Economy: impact, innovation and ecology 86 Arts and culture in an unequal society 29 The economic benefits of what? 87 Digital transformations 34 Ways of counting 89 Wellbeing and capabilities 37 Agglomeration and attractiveness 91 The innovation economy 92 Part 2 Components of Cultural Value Ecologies of culture 95 3. The reflective individual 42 7. Health, ageing and wellbeing 100 Cultural engagement and the self 43 Therapeutic, clinical and environmental 101 Case study: arts, culture and the criminal 47 interventions justice system Community-based arts and health 104 Cultural engagement and the other 49 Longer-term health benefits and subjective 106 Case study: professional and informal carers 51 wellbeing Culture and international influence 54 Ageing and dementia 108 Two cultures? 110 8. -
Free Views Tiktok
Free Views Tiktok Free Views Tiktok CLICK HERE TO ACCESS TIKTOK GENERATOR tiktok auto liker hack In July 2021, "The Wall Street Journal" reported the company's annual revenue to be approximately $800 million with a loss of $70 million. By May 2021, it was reported that the video-sharing app generated $5.2 billion in revenue with more than 500 million users worldwide.", free vending machine code tiktok free pro tiktok likes and followers free tiktok fans without downloading any apps The primary difference between Tencent’s WeChat and ByteDance’s Toutiao is that the former has yet to capitalize on the addictive nature of short-form videos, whereas the latter has. TikTok — the latter’s new acquisition — is a comparatively more simple app than its parent company, but it does fit in well with Tencent’s previous acquisition of Meitu, which is perhaps better known for its beauty apps.", In an article published by The New York Times, it was claimed that "An app with more than 500 million users can’t seem to catch a break. From pornography to privacy concerns, there have been quite few controversies surrounding TikTok." It continued by saying that "A recent class-action lawsuit alleged that the app poses health and privacy risks to users because of its allegedly discriminatory algorithm, which restricts some content and promotes other content." This article was published on The New York Times.", The app has received criticism from users for not creating revenue and posting ads on videos which some see as annoying. The app has also been criticized for allowing children younger than age 13 to create videos. -
An Innovative Video Searching Approach Using Video Indexing
IJCSN - International Journal of Computer Science and Network, Volume 8, Issue 2, April 2019 ISSN (Online) : 2277-5420 www.IJCSN.org Impact Factor: 1.5 An Innovative Video Searching Approach using Video Indexing 1 Jaimon Jacob; 2 Sudeep Ilayidom; 3 V.P.Devassia [1] Department of Computer Science and Engineering, Govt. Model Engineering College, Thrikkakara, Ernakulam,Kerala,, India,682021 [2] Division of Computer Engineering, School of Engineering, Cochin University of Science and Technology, Thrikkakara, Ernakulam, Kerala,, India,682022 [3] Former Principal, Govt. Model Engineering College, Thrikkakara, Ernakulam,Kerala,, India,682021 Abstract - Searching for a Video in World Wide Web has augmented expeditiously as there’s been an explosion of growth in video on social media channels and networks in recent years. At present video search engines use the title, description, and thumbnail of the video for identifying the right one. In this paper, a novel video searching methodology is proposed using the Video indexing method. Video indexing is a technique of preparing an index, based on the content of video for the easy access of frames of interest. Videos are stored along with an index which is created out of video indexing technique. The video searching methodology check the content of index attached with each video to ensure that video is matching with the searching keyword and its relevance ensured, based on the word count of searching keyword in video index. The video searching methodology check the content of index attached with each video to ensure that video is matching with the searching keyword and its relevance ensured, based on the word count of searching keyword in video index. -
SEO-A Review Sonu B
International Journal of Research and Scientific Innovation (IJRSI) | Volume V, Issue II, February 2018 | ISSN 2321–2705 SEO-A Review Sonu B. Surati, Ghanshyam I. Prajapati Department of Information Technology, Shri S’ad Vidya Mandal Institute of Technology, Bharuch, Gujarat, India Abstract— Search Engine Optimization (SEO) is the process of affecting online visibility of a website or web page. This is important to improve rank of search result for website and get more page views, which are requested by user and these users can be converted into customers. A Search Engine Optimization may target on different search engines like image, video, academic, news, industry etc. and using these engine ranks they provide better and optimized result for user. These ranks help them to view popular page among the number of page available in the (non-paid) search result. Also, SEO is to help website managers to improve traffic of website, to making site friendly, to building link, and marketing unique value of site. SEO classified in two categories as either white hat SEO or black hat SEO. White hats tend to produce results that last a long time, whereas black hats anticipate that their sites may eventually be banned either temporarily or permanently. SEO is used to improve their frames and create more economic effectiveness and social effectiveness and also they can focus on national and international searcher(s). Keywords— Search Engine Optimization, White Hat, Black Hat, Link- Building, Marketing, Website, Social Sharing, Ranking. I. INTRODUCTION Fig.1 History of SEO search engine is software that is designed to search for So using cluster k- means algorithm solve delay problems, A information on World Wide Web. -
A Method for a Small Web Site to Add Some Video Sharing Features
LiU-ITN-TEK-A--08/013--SE A method for a small web site to add some video sharing features Juan Lucas Madurga Martín-Serrano 2008-01-31 Department of Science and Technology Institutionen för teknik och naturvetenskap Linköping University Linköpings Universitet SE-601 74 Norrköping, Sweden 601 74 Norrköping LiU-ITN-TEK-A--08/013--SE A method for a small web site to add some video sharing features Examensarbete utfört i datavetenskap vid Tekniska Högskolan vid Linköpings unversitet Juan Lucas Madurga Martín-Serrano Examinator Bengt Lennartsson Norrköping 2008-01-31 Upphovsrätt Detta dokument hålls tillgängligt på Internet – eller dess framtida ersättare – under en längre tid från publiceringsdatum under förutsättning att inga extra- ordinära omständigheter uppstår. Tillgång till dokumentet innebär tillstånd för var och en att läsa, ladda ner, skriva ut enstaka kopior för enskilt bruk och att använda det oförändrat för ickekommersiell forskning och för undervisning. Överföring av upphovsrätten vid en senare tidpunkt kan inte upphäva detta tillstånd. All annan användning av dokumentet kräver upphovsmannens medgivande. För att garantera äktheten, säkerheten och tillgängligheten finns det lösningar av teknisk och administrativ art. Upphovsmannens ideella rätt innefattar rätt att bli nämnd som upphovsman i den omfattning som god sed kräver vid användning av dokumentet på ovan beskrivna sätt samt skydd mot att dokumentet ändras eller presenteras i sådan form eller i sådant sammanhang som är kränkande för upphovsmannens litterära eller konstnärliga anseende eller egenart. För ytterligare information om Linköping University Electronic Press se förlagets hemsida http://www.ep.liu.se/ Copyright The publishers will keep this document online on the Internet - or its possible replacement - for a considerable time from the date of publication barring exceptional circumstances. -
FEBRUARY 2021 Company Overview: Parallel / Ceres Acquisition Corp
FEBRUARY 2021 Company Overview: Parallel / Ceres Acquisition Corp. SPAC Transaction DISCLOSURES CAUTIONARY STATEMENT This presentation is provided for informational purposes only and has been prepared to assist interested parties in making their own evaluation with respect to an investment in securities in connection with a potential business combination between SH Parent, Inc., a Delaware corporation (“Parallel” or the “Corporation”) and Ceres Acquisition Corp. (“Ceres”) and related transactions (collectively, the “Transaction”) and for no other purpose. This presentation does not contain, nor does it purport to contain, a summary of all the material information concerning Parallel or the terms and conditions of any potential investment in connection with the Transaction. If and when you determine to proceed with discussions and investigations regarding a possible investment in connection with the Transaction, prospective investors are urged to carry out independent investigations in order to determine their interest in investing in connection with the Transaction. The information contained in this presentation has been prepared by Parallel and Ceres and contains confidential information pertaining to the business and operations of the Corporation following the Transaction (the “Resulting Company”). The information contained in this presentation: (a) is provided as at the date hereof, is subject to change without notice, and is based on publicly available information, internally developed data as well as third party information from other -
Google's Next Generation Music Recognition 1
Google’s Next Generation Music Recognition By: Yash Dadia www.attuneww.com All Rights Reserved Table of Content Google’s “Now Playing” Introduction How to set Now Playing on your Device Now Playing versus Sound Search The Core Matching Process of Now Playing Increasing Up Now Playing for the Sound Search Server Updated Overview of Now Playing About Attune Google's Next Generation Music Recognition 1 Google’s “Now Playing” Introduction ● In 2017 Google launched Now Playing on the Pixel 2, using deep neural networks to bring low-power, always-on music recognition to mobile devices. In developing Now Playing, Google’s goal was to create a small, efficient music recognizer which requires a very small fingerprint for each track in the database, allowing music recognition to be run fully on-device without an internet connection. ● As it turns out, Now Playing was not only useful for an on-device music recognizer, but also greatly exceeded the accuracy and efficiency of Google’s then-current server-side system, Sound Search, which was built before the large use of deep neural networks. Naturally, Google wondered if they could bring the same technology that powers Now Playing to the server-side Sound Search, with the goal of making Google’s music recognition capabilities the best in the world. ● Recently, Google introduced a new version of Sound Search that is powered by some of the same technology used by Now Playing. You can use it through the Google Search app or the Google Assistant on any Android Device. Just start a voice query, and if there’s music playing near you, a “What’s this song?” suggestion will pop up just you have to press.You can also ask, “Hey Google, what’s this song?” in the latest version of Sound Search, you’ll get faster, more accurate results than ever before! Google's Next Generation Music Recognition 2 How to set Now Playing on your Device ● If you have used Google to identify a song with your device, you’ve probably seen how to find all those past discoveries. -
IASA Journal 35 CS3-2.Indd
Article The VIDI-Video semantic video search engine Marco Bertini, Università di Firenze, Italy, Marco Rendina, Fondazione Rinascimento Digitale, Italy128 Introduction Video is becoming vital to society and economy. It plays a key role in information distribution and access, and it is also becoming the natural form of communication on the Internet and via mobile devices. The massive increase in digital audiovisual information will pose high demands on advanced storage and retrieval engines, and it is certain that consumers and professionals will need advanced storage and search technologies for the management of large-scale video assets. Current search engines, however, mostly rely on keyword-based access that uses manually annotated metadata, and do not allow for content-based search of images or videos. At present, even state-of-the-art video search engines are able to annotate automatically only a limited set of semantic concepts, and retrieval is usually allowed using only a keyword-based approach based on a lexicon. The VIDI-Video project, funded in the 6th Framework Program by the EU, has taken on the challenge of creating substantially enhanced semantic access to video. The project has aimed to integrate and develop state-of-the-art components from many technologies — such as machine learning, audio event detection, video processing, visual feature processing, knowledge modeling and management, interaction and visualization — into a fully implemented audiovisual search engine, combining large numbers of audiovisual concepts and -
Design Document V3
My (Musical) Life Design Document Team Number: sddec20-13 Adviser & Client: Dr. Henry Duwe Team Members: Christian Hernandez - Project Manager Chaz Clark - iOS Developer Daksh Goel - Backend Developer Vignesh Krishnan - Frontend Developer Vatsal Bhatt - Backend Developer Team Email: [email protected] Team Website: http://sddec20-13.sd.ece.iastate.edu/ sddec20-13 1 Executive Summary Development Standards & Practices Used ● Development Standards ○ Commented Code ○ Quality ○ Efficiency ○ Apple Developer Standards ○ Waterfall Design ● Practices ○ Test code regularly ○ Agile Development ● Engineering Standards ○ Quality ○ Performance ○ Safety Summary of Requirements ● Functional requirements ○ User Data (from their mobile device) ■ Location ■ Weather ■ Schedule ○ A music Streaming service account ○ Music Recommendations ○ Mapping Sensor Inputs to Songs/Playlists ○ Volume Control ● Non-functional requirements ○ Security (SSL, TLS, WPA2) ■ Account logins ■ Location information ■ Calendar data ■ Music preferences ○ AWS Security ■ Database ■ Lambda data ○ Response time/performance ■ Crash Rate: 1-2% ■ API Latency: 1 sec ■ End-to-end app latency: <3 sec ● Economical requirements ○ Spotify Premium Subscription sddec20-13 2 ● Environmental requirements ○ Network reception in user’s mobile device ○ iOS device (iPhone) ● Apple Design Guideline Requirements ○ Consistency ○ Feedback ○ Direct manipulation ○ User control Applicable Courses from Iowa State University Curriculum ● S E 185 - Problem Solving in Software Engineering ● CPR E 185 - Introduction -
Google Buys Songza Streaming Music Service 1 July 2014
Google buys Songza streaming music service 1 July 2014 It has applications tailored for mobile devices powered by Apple or Google-backed Android software. Songza features that have resonated with users will be woven into Google Play Music and YouTube where possible, the California-based technology titan said in a post at its Google+ social network. "They've built a great service which uses contextual expert-curated playlists to give you the right music at the right time," Google said. New York-based Songza has been likened to The Google logo seen at Google headquarters in Pandora, which has a leading ad-supported Mountain View, California on September 2, 2011 streaming music model. Google, Amazon and Apple have music services that compete in a market where Pandora and Google on Tuesday said that it has bought Spotify have found success. Songza, a free online streaming music service that recommends tunes based on what people might Apple in May bought Beats Music and Beats be in the mood to hear. Electronics in a deal worth $3 billion to bolster its position in the hotly contested online music sector. Financial terms of the deal were not disclosed, but unconfirmed online reports valued the deal at The move is expected to help the US tech giant—a around $15 million. pioneer in digital music with its wildly popular iTunes platform—ramp up its efforts to counter the "We're thrilled to announce that we're becoming successful models of streaming services like part of Google," Songza said on its website. Pandora, Spotify and others. -
A Scalable Video Search Engine Based on Audio Content
A Scalable Video Search Engine Based on Audio Content Indexing and Topic Segmentation Julien Lawto, Jean-Luc Gauvain, Lori Lamel, Gregory Grefenstette, Guillaume Gravier, Julien Despres, Camille Guinaudeau, Pascale Sébillot To cite this version: Julien Lawto, Jean-Luc Gauvain, Lori Lamel, Gregory Grefenstette, Guillaume Gravier, et al.. A Scalable Video Search Engine Based on Audio Content Indexing and Topic Segmentation. 2011 Networked and Electronic Media (NEM) Summit : Implementing Future Media Internet, Sep 2011, Torino, Italy. 160 p. hal-00645228 HAL Id: hal-00645228 https://hal.archives-ouvertes.fr/hal-00645228 Submitted on 27 Nov 2011 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. A SCALABLE VIDEO SEARCH ENGINE BASED ON AUDIO CONTENT INDEXING AND TOPIC SEGMENTATION Julien LawTo1, Jean-Luc Gauvain2, Lori Lamel2, Gregory Grefenstette1, Guillaume Gravier3, Julien Despres4, Camille Guinaudeau3, Pascale Sebillot3 1Dassault Systèmes/Exalead, Paris, France; 2LIMSI, Orsay, France ; 3IRISA, Rennes, France ; 4Vocapia Research, Orsay, France E-mail: 13ds.com, 2limsi.fr, 3irisa.fr, 4vocapia.com Abstract: One important class of online videos is that Most current video search engines rely, in a large part, on of news broadcasts. Most news organisations provide indexing the textual metadata associated with the video near-immediate access to topical news broadcasts over (title, tags, surrounding page-text). -
Text-Based Description of Music for Indexing, Retrieval, and Browsing
JOHANNES KEPLER UNIVERSITAT¨ LINZ JKU Technisch-Naturwissenschaftliche Fakult¨at Text-Based Description of Music for Indexing, Retrieval, and Browsing DISSERTATION zur Erlangung des akademischen Grades Doktor im Doktoratsstudium der Technischen Wissenschaften Eingereicht von: Dipl.-Ing. Peter Knees Angefertigt am: Institut f¨ur Computational Perception Beurteilung: Univ.Prof. Dipl.-Ing. Dr. Gerhard Widmer (Betreuung) Ao.Univ.Prof. Dipl.-Ing. Dr. Andreas Rauber Linz, November 2010 ii Eidesstattliche Erkl¨arung Ich erkl¨are an Eides statt, dass ich die vorliegende Dissertation selbstst¨andig und ohne fremde Hilfe verfasst, andere als die angegebenen Quellen und Hilfsmittel nicht benutzt bzw. die w¨ortlich oder sinngem¨aß entnommenen Stellen als solche kenntlich gemacht habe. iii iv Kurzfassung Ziel der vorliegenden Dissertation ist die Entwicklung automatischer Methoden zur Extraktion von Deskriptoren aus dem Web, die mit Musikst¨ucken assoziiert wer- den k¨onnen. Die so gewonnenen Musikdeskriptoren erlauben die Indizierung um- fassender Musiksammlungen mithilfe vielf¨altiger Bezeichnungen und erm¨oglichen es, Musikst¨ucke auffindbar zu machen und Sammlungen zu explorieren. Die vorgestell- ten Techniken bedienen sich g¨angiger Web-Suchmaschinen um Texte zu finden, die in Beziehung zu den St¨ucken stehen. Aus diesen Texten werden Deskriptoren gewon- nen, die zum Einsatz kommen k¨onnen zur Beschriftung, um die Orientierung innerhalb von Musikinterfaces zu ver- • einfachen (speziell in einem ebenfalls vorgestellten dreidimensionalen Musik- interface), als Indizierungsschlagworte, die in Folge als Features in Retrieval-Systemen f¨ur • Musik dienen, die Abfragen bestehend aus beliebigem, beschreibendem Text verarbeiten k¨onnen, oder als Features in adaptiven Retrieval-Systemen, die versuchen, zielgerichtete • Vorschl¨age basierend auf dem Suchverhalten des Benutzers zu machen.