Rise of Data Virtualization
Hybrid Data Stores Become More Common
Semantics Becomes Standard
Hadoop Without Map-Reduce and Map-Reduce Without Hadoop
Databases Become Working Memory
Towards a Universal Data Query Language
Data Analytics Moves Beyond SQL
The JavaScript Stack Solidifies
from here.
I am not sure about sematics and I am not sure about Universal Data Query Language. Vice versa, I am sure they are not :)
This paper summarizes definitions and uses cases for the sharing location information via geo messages. Geo messages let users of location based systems share location information as signatures to the standard messages (e.g., email, SMS). Rather than let some service perform the constant monitoring for the user’s location (Google Latitude) or share location info within any social circle (Facebook’s check-in, etc.) Geo Messages approach lets users share location data on the peer to peer basis. Users can share own location info via any of existing messaging systems. The basic tenet of this process is the separation of the identification and location information.
With this approach shared location information (geo-coded link, map, etc.) does not contain the users’ identity. It uses identity information from the messaging system. It means that the whole process of location info exchange does not reveal user’s privacy. For a multilateral exchange of geo-positional information, this approach proposes a scheme with replaceable user authentication where only the creator of temporary name knows the identity mapping between temporary names and true identities.
The common goal of current metadata formats for REST APIs is to specify:
Entry point(s)
Resource paths
Methods to access these resources (GET, POST, PUT, etc.…)
Parameters that need to be supplied with these methods (Query, Template, HTTP Header, etc.)
Formats of inbound / outbound messages/representations (JSON Schema, XML Schema, Relax NG, etc.)
Status codes and error/fault messages
Documentary information (descriptions, etc.) for all these
WSDL is a good example from SOAP world. What do we have with REST?
The journal is published by the OIT Lab (Open Information Technologies Lab, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University).
Indexing: Google Scholar, DOAJ, Ulrich's Periodicals Directory, ResearchBib, Elibrary.ru (RINC)
In this paper, we would like to discuss software standards in the connection with the development of emerging telecom applications. Emerging (military) telecom applications present one of the biggest challenges for the developers (design and development) and telecom providers (deployment and maintenance). It is especially true in the context of transition from TDM to IP networks. This transition may bring own challenges associated with the priorities in data transmission, security, etc. We describe two biggest telecom related examples (GIG and FI-WARE), discuss the challenges and propose directions for software standards development and deployment.
P.S. See here the previous post about microservices.
Understanding Machine Learning: From Theory to Algorithms
Bayesian Reasoning and Machine Learning
Machine Learning: a Probabilistic Perspective
Computer Vision: Models, Learning, and Inference
Data Mining and Analysis: Fundamental Concepts and Algorithms
The Elements of Statistical Learning
An Introduction to Statistical Learning
Reinforcement Learning: An Introduction
Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems
Algorithms for Reinforcement Learning
The journal is published by the OIT Lab (Open Information Technologies Lab, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University).
Indexing: Google Scholar, DOAJ, Ulrich's Periodicals Directory, ResearchBib, Elibrary.ru (RINC)
The journal is published by the OIT Lab (Open Information Technologies Lab, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University).
Indexing: Google Scholar, DOAJ, Ulrich's Periodicals Directory, ResearchBib, Elibrary.ru (RINC)
The journal is published by the OIT Lab (Open Information Technologies Lab, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University).
Indexing: Google Scholar, DOAJ, Ulrich's Periodicals Directory, ResearchBib, Elibrary.ru (RINC)
Please, support our presentation
It is published by the OIT Lab (Open Information Technologies Lab, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University).
Indexing: Google Scholar, DOAJ, Ulrich's Periodicals Directory, ResearchBib, Elibrary.ru (RINC)
This paper provides an overview for existing and upcoming system software platforms for M2M applications. In this article we discuss system software models from the developer’s point of view, rather than network related aspects. The primary goal is to find the common and reusable aspects across existing models as well as discuss their possible coexistence. Can we extract the common elements for the different M2M software models? Are there some reusable patterns? What should developers and system architects pay attention to? These are the main issues addressed in this article.
P.S. See also the previous paper: Namiot, Dmitry, and Manfred Sneps-Sneppe. "On M2M Software." International Journal of Open Information Technologies 2.6 (2014): 29-36
The paper discusses phone as a sensor model. For many applied tasks smart phones are an ideal platform for collecting and processing context-related data. The most popular example is, probably, computational social science. Phones can collect data for conducting various social researches about people’s social behavior. This paper presents an attempt to describe and categorize existing open source libraries for mobile sensing, describe architecture and design patterns as well as discover directions for the future development.
/via GPS Business News
For example, we can take our BDP application, points service to its page in Google Play and automatically get this landing page for our application: Bluetooth Data Points
Digify - mobile application
Secure notes - web service and REST API
This paper discusses the global unified standards for software products and existing approaches (de-facto standards). Using specific examples of interaction with Bluetooth Low Energy tags we compared existing approaches to the development and the proposed global standards (FI-WARE). Can a unified approach to the creation of services to cover all the possible use cases and scenarios for new services? The paper emphasizes the need to address the prevailing trends in the design to create a standard. Also, we highlight the critical importance of such a thing as the time to market for new applications and services developed according to the proposed standards.
DOI: 10.1109/Kaleidoscope.2014.6858494
There are several our papers, devoted to check-in advertising:
lat - a latitude of place
lng - a longitude of place
For example: City chat, Palo Alto.
Techically, it is a mobile web mashup which uses Foursquare and chat engine from Coldbeans.
As a similar "city-related" application see also City forums, geo-chat and
Never eat alone application.
/via Geo Messages
lat - latitude of the place
lng - longitude of the place
for example: Palo Alto, University Avenue, Starbucks
There is the similar mobile mashup City chat - the dialogues there are connected to some place from Foursquare. Geo chat is almost the same, but implemented for any geo place without the connection to some predefined place
Technically, it is a web mashup that uses chat engine from Coldbeans.
As per similar "city-level" applications check out also City forums or City Guide
P.S. as per hyper-local chat see also WiFi chat application
Deep learning from the bottom up
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Linguistic Regularities in Continuous Space Word Representations
Playing Atari with Deep Reinforcement Learning
General guidelines for Deep Neural Networks
Practical recommendations for gradient-based training of deep architectures
http://cforum.linkstore.ru
(it is a mobile site).
You can copy this link right to your mobile browser with QR-code above. Alternatively you can use the following short URL: http://bit.ly/aFCbjF
BDP approach lets mobile users (enterprises) associate own data snippets with Bluetooth nodes. So, other mobile users in proximity (Bluetooth radio distance) will be able to discover and read them. You can think about the web browsing, where web pages provide some hyper-local data. Read more.
/via Geo Messages
P.S. and a good discussion on YC related to this paper.
Comments and remarks are more than welcome.
/via Geo Messages
Bluetooth Data Points (BDP) is a new approach for creating mobile services with wireless tags. It is a yet another use case for the network proximity. Mobile application (Android) lets any user post some announce (advertising, classified, etc.) and associate it with Bluetooth node on the phone. The same application on another phone can scan nearby Bluetooth nodes and collect local announces. Dislike iBeacon and similar applications:
a) this approach is based on the Core Bluetooth rather than on Bluetooth Low Energy. So it will work with any phone;
b) this application works like a browser. So, mobile user decides when to run and what to read rather than constantly get unwanted notifications.
The following picture illustrates BDP (Bluetooth Data Points) approach:
BDP uses Core Bluetooth. So, it could be used with almost any smartphone. Let us see how it works:
1. Mobile user can browse local announces:
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2. Another user publish own announce:
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It is simply a text. User can publish links (URLs), email, phone or links to Twitter: @t411
3. Application switch on Bluetooth for published announces:
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Of course, the publisher can switch Bluetooth off and make own announces unavailable. And later, switch it on again, etc. So, publisher's announces will follow his phone. When published materials are on, other mobile users nearby will the them:
Mobile application for Android, which implements this approach could be downloaded right from Google Play: BDP on Google Play. Here is an appropriate QR-code:
You can download it right from our site too: BDP on servlewtsuite. And here is an appropriate QR-code:
As the possible use cases for this approach we can mention applications for retail, indoor navigation, as well as context-dependent services for Smart Cities.
P.S. We've used the similar approach for Wi-Fi: SpotEx
P.S. Btw, here you can find online courses
Bluetooth Data Points (BDP) is a new approach for creating mobile services with wireless tags. It is a yet another use case for the network proximity. Mobile application (Android) lets any user post some announce (advertising, classified, etc.) and associate it with Bluetooth node on the phone. The same application on another phone can scan nearby Bluetooth nodes and collect local announces. Dislike iBeacon and similar applications:
a) this approach is based on the Core Bluetooth rather than on Bluetooth Low Energy. So it will work with any phone;
b) this application works like a browser. So, mobile user decides when to run and what to read rather than constantly get unwanted notifications.
The following picture illustrates BDP (Bluetooth Data Points) approach:
BDP uses Core Bluetooth. So, it could be used with almost any smartphone. Let us see how it works:
1. Mobile user can browse local announces:
|
|
|
2. Another user publish own announce:
|
|
|
It is simply a text. User can publish links (URLs), email, phone or links to Twitter: @t411
3. Application switch on Bluetooth for published announces:
|
|
|
Of course, the publisher can switch Bluetooth off and make own announces unavailable. And later, switch it on again, etc. So, publisher's announces will follow his phone. When published materials are on, other mobile users nearby will the them:
Mobile application for Android, which implements this approach: BDP (Bluetooth Data Point). You can download it right from our site servletsuite.com. And here is an appropriate QR-code:
As the possible use cases for this approach we can mention applications for retail, indoor navigation, as well as context-dependent services for Smart Cities.
P.S. We've used the similar approach for Wi-Fi: SpotEx
a) this approach is based on the Core Bluetooth rather than on Bluetooth Low Energy. So it will work with any phone;
b) this application works like a browser. So, mobile user decides when to run and what to read rather than constantly getting unwanted notifications
The following picture illustrates BDP (Bluetooth Data Points) approach:
You can download this application right from our server: BDP.apk
The same idea for courses from Coursera. CS four-year curriculum
/via Geo Messages
/via Geo Messages
/via Geo Messages
It is published by the OIT Lab (Open Information Technologies Lab, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University).
Indexing: Google Scholar, DOAJ, Ulrich's Periodicals Directory, ResearchBib, Elibrary.ru (RINC)
/via Geo Messages
/via Geo Messages
/via Geo Messages
This paper describes a new model for delivering hyper-local data for mobile subscribers. Our model uses Wi-Fi proximity as a service. According to this concept, any existing or even a specially created Wi-Fi hot spot could be used as presence sensor that can trigger access for some user-generated information snippets. In this article we present several examples for deployment: context-aware browser, integration for proximity and social streams and human dynamics models based on proximity data. As the possible use-cases, we can mention, for example, news and deals delivery in malls, news feeds for office centers and campuses, social curation, Smart City projects, personal classifieds, etc.
Send CV to info@servletsuite.com
It is published by the OIT Lab (Open Information Technologies Lab, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University).
/via Geo Messages
It is anticipated that the DDD initiative will make about 15 awards at ~$1,500,000 each, at $200K-$300K/year for five years.
read more here.
It is published by the OIT Lab (Open Information Technologies Lab, Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University).
/via Geo Messages
