People use smartphones in daily activities for accessing and storing information in various situations. In this paper, we present a work in progress for detecting and automating some of these activities. To explore the possible patterns we developed an experimental application to detect daily tasks used by smartphones and analyzed it to provide suggestions for “routines”. We conducted a two-week user study with 10 users to evaluate the approach. During the study the application logged the usage patterns, sent information to the server where it was analysed and clustered. The participants could also automate their smartphone tasks using the analysed data. The findings suggest that people would be willing to automatize tasks given that the approach gives flexibility and expressiveness without too much information overload. Future work includes refining the algorithms based on the gathered real-life data and modifying the interaction design to approach the challenges found with the initial study.
Understanding the Privacy Implications of Using Context-based Awareness Cues ...Ville Antila
Information from the physical world is increasingly being digitalized and shared in social networks. We share our locations, tag photos and add different kinds of informal awareness cues about the physical world to our online communities. In this paper, we investigate the privacy implications of shared context cues in social networking services. We present an experimental mobile application, which allows users to add different descriptions of context information to their Facebook and Twitter status updates. The application was used by 12 persons during a two-week user trial using their own devices and Facebook accounts. The results indicate that user-defined abstractions of context items were often preferred over more accurate indicators due to privacy concerns or discomfort in sharing. We also found out that using shared context from friends in vicinity needs careful design to overcome the extended privacy implications.
ContextCapture: Using Context-based Awareness Cues to Create Narrative Events...Ville Antila
In this paper we introduce an experimental application to demonstrate the usage of context-based awareness cues in status updates, especially in SNS’s (Social Networking Services). The presented application allows users to add different descriptions of context information to their Twitter messages and Facebook status updates in a narrative format. We have also developed an adapted version of the system including conference-specific context-types such as the timetable of the presentations and indoor-location detection using Bluetooth beacons. One goal for the demonstrator is to explore the practical use of context abstractions in a conference setup and synthesize interesting insight based on the usage patterns during the event.
ContextCapture: Exploring the Usage of Context-based Awareness Cues in Inform...Ville Antila
In this paper, we investigate the usage of context-based awareness cues in informal information sharing, especially in social networking services. We present an experimental mobile application, which allows users to add different descriptions of context information to their Facebook status updates. The meaningfulness and the usage of different context descriptions were evaluated in a two-week user trial. The results show that the most frequently used awareness cues in the test setting were location, surroundings, friends and activity. The results also indicate that user-defined semantic abstractions of context items (e.g. “home”, “work”) were often more informative and useful than more accurate indicators (e.g. the address or the name of the place). We also found out that using shared context from friends in vicinity (e.g. identifying the people around) needs careful design to overcome the extended privacy implications.
This poster introduces an experimental application to demonstrate the usage of context-based awareness cues in status updates, especially in SNS’s (Social Networking Services). The presented application allows users to add different descriptions of context information to their Twitter messages and Facebook status updates in a narrative format.
MindTrek2011 - ContextCapture: Context-based Awareness Cues in Status UpdatesVille Antila
Presentation of an experimental mobile application, which allows users to add different descriptions of context information to their Facebook status updates. The meaningfulness and the usage of different context descriptions were evaluated in a two-week user trial. The results show that the most frequently used awareness cues in the test setting were location, surroundings, friends and activity. The results also indicate that user-defined semantic abstractions of context items (e.g. “home”, “work”) were often more informative and useful than more accurate indicators (e.g. the address or the name of the place). We also found out that using shared context from friends in vicinity (e.g. identifying the people around) needs careful design to overcome the extended privacy implications.
Understanding the Privacy Implications of Using Context-based Awareness Cues ...Ville Antila
Information from the physical world is increasingly being digitalized and shared in social networks. We share our locations, tag photos and add different kinds of informal awareness cues about the physical world to our online communities. In this paper, we investigate the privacy implications of shared context cues in social networking services. We present an experimental mobile application, which allows users to add different descriptions of context information to their Facebook and Twitter status updates. The application was used by 12 persons during a two-week user trial using their own devices and Facebook accounts. The results indicate that user-defined abstractions of context items were often preferred over more accurate indicators due to privacy concerns or discomfort in sharing. We also found out that using shared context from friends in vicinity needs careful design to overcome the extended privacy implications.
ContextCapture: Using Context-based Awareness Cues to Create Narrative Events...Ville Antila
In this paper we introduce an experimental application to demonstrate the usage of context-based awareness cues in status updates, especially in SNS’s (Social Networking Services). The presented application allows users to add different descriptions of context information to their Twitter messages and Facebook status updates in a narrative format. We have also developed an adapted version of the system including conference-specific context-types such as the timetable of the presentations and indoor-location detection using Bluetooth beacons. One goal for the demonstrator is to explore the practical use of context abstractions in a conference setup and synthesize interesting insight based on the usage patterns during the event.
ContextCapture: Exploring the Usage of Context-based Awareness Cues in Inform...Ville Antila
In this paper, we investigate the usage of context-based awareness cues in informal information sharing, especially in social networking services. We present an experimental mobile application, which allows users to add different descriptions of context information to their Facebook status updates. The meaningfulness and the usage of different context descriptions were evaluated in a two-week user trial. The results show that the most frequently used awareness cues in the test setting were location, surroundings, friends and activity. The results also indicate that user-defined semantic abstractions of context items (e.g. “home”, “work”) were often more informative and useful than more accurate indicators (e.g. the address or the name of the place). We also found out that using shared context from friends in vicinity (e.g. identifying the people around) needs careful design to overcome the extended privacy implications.
This poster introduces an experimental application to demonstrate the usage of context-based awareness cues in status updates, especially in SNS’s (Social Networking Services). The presented application allows users to add different descriptions of context information to their Twitter messages and Facebook status updates in a narrative format.
MindTrek2011 - ContextCapture: Context-based Awareness Cues in Status UpdatesVille Antila
Presentation of an experimental mobile application, which allows users to add different descriptions of context information to their Facebook status updates. The meaningfulness and the usage of different context descriptions were evaluated in a two-week user trial. The results show that the most frequently used awareness cues in the test setting were location, surroundings, friends and activity. The results also indicate that user-defined semantic abstractions of context items (e.g. “home”, “work”) were often more informative and useful than more accurate indicators (e.g. the address or the name of the place). We also found out that using shared context from friends in vicinity (e.g. identifying the people around) needs careful design to overcome the extended privacy implications.
Following the user’s interests in mobile context aware recommender systemsBouneffouf Djallel
The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information depending on her/his situation and interests. Two key questions have to be considered 1) how to recommend the user information that follows his/her interests evolution? 2) how to model the user’s situation and its related interests? To the best of our knowledge, no existing work proposing a MCRS tries to answer both questions as we do. This paper describes an ongoing work on the implementation of a MCRS based on the hybrid-ε-greedy algorithm we propose, which combines the standard ε-greedy algorithm and both content-based filtering and case-based reasoning techniques.
In this presentation, I describe the Context-Aware concept, Context-Aware Computing, and Context-Aware application with some application example of use it
Resource Identification Using Mobile QueriesIDES Editor
Location based mobile services (LBS) are budding
significantly along with development of GPS-enabled mobile
phones, smart phones and PDAs. Mobile users may submit the
query to the server for knowing about nearest resources such
as fuel stations, hospitals, ATM centers etc to get the services.
In this scenario, identifying locations of resources is highly
significant. This paper focuses on query management in
mobile environments to locate the most appropriate location of
the required services.
Conceptual Design of Fuzzy Rule Based Context Aware Meeting Room SystemEditor IJMTER
Due to the exponential growth of wireless network based miniaturized device and
sensors, the dream of context aware ubiquitous computing world is becoming realistic. In this
ubiquitous world of context aware applications the users can get the information and share the
information elsewhere instantaneously. Context aware meeting room is one of the interesting context
aware systems where in the meeting of a given set of users will be organized as per the situation of
users. In this paper we present the conceptual design and development of service recommendation
system for prototypical context aware meeting room using Fuzzy Rules .The proposed
recommendation system for context aware meeting room recommends the services by considering
the users contextual parameters like role, priority and environmental conditions. The fuzzy rule is
constructed using history database and knowledge base of the meeting.
Vertical Fragmentation of Location Information to Enable Location Privacy in ...ijasa
The aim of the development of Pervasive computing was to simplify our lives by integrating
communication technologies into real life. Location aware computing which is evolved from pervasive
computing performs services which are dependent on the location of the user or his communication
device. The advancements in this area have led to major revolutions in various application areas,
especially mass advertisements. It has long been evident that privacy of personal information, in this
case location of the user, is rather a touchy subject with most people. This paper explores the Location
Privacy issue in location aware computing. Vertical fragmentation of the stored location information of
users has been proposed as an effective solution for this issue.
DOTI North - Data and Design; Prof Matthew ChalmersSnook
Matthew is a professor in the School of Computing Science at the University of Glasgow. His work focuses on data visualisation and analytics, data ethics and ethical systems design, and mobile and ubiquitous computing.
Matthew worked in industrial research labs, including Xerox PARC in Palo Alto, California, before returning to Scotland in 2000. Since then he’s been an academic at University of Glasgow, leading projects exploring topics such as mobile computing for health and fitness, user experience design that bridges digital and analogue media, using commercial app stores for user trials, and large scale data analytics and visualisation. Today he’ll be talking about an approach to the design of complex systems that could perhaps be better known outside of the world of research: ’seamful design’, that started at PARC in the 1980s, and which he and his research group have advanced over the past years.
Bridging Sensor Data Streams and Human KnowledgeMattia Zeni
Generating useful and meaningful knowledge out of personal big data is a difficult task that presents multiple challenges due to the intrinsic characteristics of these type of data, namely their volume, velocity, variety and noisiness. This work proposes an interdisciplinary approach for solving this problem that is based on the idea that the user and the world surrounding him can be modeled, defining most of the elements of her context as entities (locations, people, objects) in addition with their attributes and the relations among them. This allows to create a structure out of the unstructured, noisy and highly variable sensor data that can then be used by the machine to provide personalized, context-aware services to the final user with the final goal of improving her quality of life.
Proactive Intelligent Home System Using Contextual Information and Neural Net...IJERA Editor
Nowadays, cities around the world intend to use information technology to improve the lives of their citizens.
Future smart cities will incorporate digital data and technology to interact differently with their human
inhabitants.
Among the key component of a smart city, we find the smart home component. It is an autonomic environment
that can provide various smart services by considering the user’s context information. Several methods are used
in context-aware system to provide such services. In this paper, we propose an approach to offer the most
relevant services to the user according to any significant change of his context environment. The proposed
approach is based on the use of context history information together with user profiling and machine learning
techniques. Experimentations show that the proposed solution can efficiently provide the most useful services to
the user in an intelligent home environment.
This paper aims to provide an overview of the
contents and design of the all newspapers. Majority of the
newspapers use Blog, RSS and Facebook to connect with
their readers. An online newspaper service providing project.
In this software system users may register as users to read
newspapers online. Once they register they may pay via
dummy credit cards and get access to reading newspapers
online for a month
Following the user’s interests in mobile context aware recommender systemsBouneffouf Djallel
The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information depending on her/his situation and interests. Two key questions have to be considered 1) how to recommend the user information that follows his/her interests evolution? 2) how to model the user’s situation and its related interests? To the best of our knowledge, no existing work proposing a MCRS tries to answer both questions as we do. This paper describes an ongoing work on the implementation of a MCRS based on the hybrid-ε-greedy algorithm we propose, which combines the standard ε-greedy algorithm and both content-based filtering and case-based reasoning techniques.
In this presentation, I describe the Context-Aware concept, Context-Aware Computing, and Context-Aware application with some application example of use it
Resource Identification Using Mobile QueriesIDES Editor
Location based mobile services (LBS) are budding
significantly along with development of GPS-enabled mobile
phones, smart phones and PDAs. Mobile users may submit the
query to the server for knowing about nearest resources such
as fuel stations, hospitals, ATM centers etc to get the services.
In this scenario, identifying locations of resources is highly
significant. This paper focuses on query management in
mobile environments to locate the most appropriate location of
the required services.
Conceptual Design of Fuzzy Rule Based Context Aware Meeting Room SystemEditor IJMTER
Due to the exponential growth of wireless network based miniaturized device and
sensors, the dream of context aware ubiquitous computing world is becoming realistic. In this
ubiquitous world of context aware applications the users can get the information and share the
information elsewhere instantaneously. Context aware meeting room is one of the interesting context
aware systems where in the meeting of a given set of users will be organized as per the situation of
users. In this paper we present the conceptual design and development of service recommendation
system for prototypical context aware meeting room using Fuzzy Rules .The proposed
recommendation system for context aware meeting room recommends the services by considering
the users contextual parameters like role, priority and environmental conditions. The fuzzy rule is
constructed using history database and knowledge base of the meeting.
Vertical Fragmentation of Location Information to Enable Location Privacy in ...ijasa
The aim of the development of Pervasive computing was to simplify our lives by integrating
communication technologies into real life. Location aware computing which is evolved from pervasive
computing performs services which are dependent on the location of the user or his communication
device. The advancements in this area have led to major revolutions in various application areas,
especially mass advertisements. It has long been evident that privacy of personal information, in this
case location of the user, is rather a touchy subject with most people. This paper explores the Location
Privacy issue in location aware computing. Vertical fragmentation of the stored location information of
users has been proposed as an effective solution for this issue.
DOTI North - Data and Design; Prof Matthew ChalmersSnook
Matthew is a professor in the School of Computing Science at the University of Glasgow. His work focuses on data visualisation and analytics, data ethics and ethical systems design, and mobile and ubiquitous computing.
Matthew worked in industrial research labs, including Xerox PARC in Palo Alto, California, before returning to Scotland in 2000. Since then he’s been an academic at University of Glasgow, leading projects exploring topics such as mobile computing for health and fitness, user experience design that bridges digital and analogue media, using commercial app stores for user trials, and large scale data analytics and visualisation. Today he’ll be talking about an approach to the design of complex systems that could perhaps be better known outside of the world of research: ’seamful design’, that started at PARC in the 1980s, and which he and his research group have advanced over the past years.
Bridging Sensor Data Streams and Human KnowledgeMattia Zeni
Generating useful and meaningful knowledge out of personal big data is a difficult task that presents multiple challenges due to the intrinsic characteristics of these type of data, namely their volume, velocity, variety and noisiness. This work proposes an interdisciplinary approach for solving this problem that is based on the idea that the user and the world surrounding him can be modeled, defining most of the elements of her context as entities (locations, people, objects) in addition with their attributes and the relations among them. This allows to create a structure out of the unstructured, noisy and highly variable sensor data that can then be used by the machine to provide personalized, context-aware services to the final user with the final goal of improving her quality of life.
Proactive Intelligent Home System Using Contextual Information and Neural Net...IJERA Editor
Nowadays, cities around the world intend to use information technology to improve the lives of their citizens.
Future smart cities will incorporate digital data and technology to interact differently with their human
inhabitants.
Among the key component of a smart city, we find the smart home component. It is an autonomic environment
that can provide various smart services by considering the user’s context information. Several methods are used
in context-aware system to provide such services. In this paper, we propose an approach to offer the most
relevant services to the user according to any significant change of his context environment. The proposed
approach is based on the use of context history information together with user profiling and machine learning
techniques. Experimentations show that the proposed solution can efficiently provide the most useful services to
the user in an intelligent home environment.
This paper aims to provide an overview of the
contents and design of the all newspapers. Majority of the
newspapers use Blog, RSS and Facebook to connect with
their readers. An online newspaper service providing project.
In this software system users may register as users to read
newspapers online. Once they register they may pay via
dummy credit cards and get access to reading newspapers
online for a month
Real-time Activity Recognition using Smartphone Accelerometerijtsrd
To identify the real time activities, an online algorithm need be considered. In this paper, we will first segment entire one activity as one time interval using Bayesian online detection method instead of fixed and small length time interval. Then, we introduce two layer random forest classification for real time activity recognition on the smartphone by embedded accelerometers. We evaluate the performance of our method based on six activities walking, upstairs, downstairs, sitting, standing, and laying on 30 volunteers. For the data considered, we get 92.4 overall accuracy based on six activities and 100 overall accuracy only based on dynamic activity and static activity. Shuang Na | Kandethody M. Ramachandran | Ming Ji | Yicheng Tu "Real-time Activity Recognition using Smartphone Accelerometer" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-1 , December 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29550.pdf Paper URL: https://www.ijtsrd.com/mathemetics/other/29550/real-time-activity-recognition-using-smartphone-accelerometer/shuang-na
Large scale geospatial analysis on mobile application usageEricsson
Several studies indicate that mobile usage habits can be affected by the user’s location, such as rural areas and points of interest (schools, airports).
Behavior-Based Security for Mobile Devices Using Machine Learning Techniquesgerogepatton
The goal of this research project is to design and implement a mobile application and machine learning techniques to solve problems related to the security of mobile devices. We introduce in this paper a
behavior-based approach that can be applied in a mobile environment to capture and learn the behavior of
mobile users. The proposed system was tested using Android OS and the initial experimental results show
that the proposed technique is promising, and it can be used effectively to solve the problem of anomaly
detection in mobile devices.
Master thesis exploring the emerging field of Mobile App Analytics. We explore the potentials of the mobile app as a data source and the current stage within mobile app analytics
Data Management In Cellular Networks Using Activity MiningIDES Editor
In the recent technology advances, an increasing
number of users are accessing various information systems
via wireless communication. The majority users in a mobile
environment are moving and accessing wireless services for
the activities they are currently unavailable inside. We
propose the idea of complex activity for characterizing the
continuously changing complex behavior patterns of mobile
users. For the purpose of data management, a complex activity
is copy as a sequence of location movement, service requests,
the coincidence of location and service, or the interleaving of
all above. An activity may be composed of sub activities.
Different activities may exhibit dependencies that affect user
behaviors. We argue that the complex activity concept provides
a more specific, rich, and detail description of user behavioral
patterns which are very useful for data management in mobile
environments. Correct exploration of user activities has the
possible of providing much higher quality and personalized
services to individual user at the right place on the right time.
We, therefore, propose new methods for complex activity
mining, incremental maintenance, online detection and
proactive data management based on user activities. In
particular, we develop pre-fetching and pushing techniques
with cost sensitive control to make easy analytical data
allocation. First round implementation and simulation results
shows that the proposed framework and techniques can
significantly increase local availability, conserve execution
cost, reduce response time, and improve cache utilization.
Real-time human activity recognition from smart phone using linear support ve...TELKOMNIKA JOURNAL
The recognition of human activity (HAR) the use of cell devices embedded in its exten sively disbursed sensors affords guidance, instructions, and take care of citizens of smart cities. Consequently, it became essential to analyze human every day sports. To examine statistical models of human conduct, synthetic intelligence strategies such as machine studying can be used. Many studies have not studied type overall performance in real-time due to statistics series. To remedy this trouble, this paper proposes a structure primarily based on open supply technology and platforms consisting of Apache Kafka, for messages to flow over the internet, method them and provide shape for existing facts in real-time and formulates the trouble of identifying human pastime by using a smartphone tool as a type hassle using statistics collection by telephone sensors. The proposed version is skilled by some machine learning algorithms. The algorithm that has proven superior and quality results helps a linear vector machines.
An effective approach to develop location-based augmented reality information...IJECEIAES
Using location-based augmented reality (AR) for pedestrian navigation can greatly improve user action to reduce the travel time. Pedestrian navigation differs in many ways from the conventional navigation system used in a car or other vehicles. A major issue with using location-based AR for navigation to a specific landmark is their quality of usability, especially if the active screen is overcrowded with the augmented POI markers which were overlap each other at the same time. This paper describes the user journey map approach that led to new insights about how users were using location-based AR for navigation. These insights led to a deep understanding of challenges that user must face when using location-based AR application for pedestrian navigation purpose, and more generally, they helped the development team to appreciate the variety of user experience in software requirement specification phase. To prove our concept, a prototype of intuitive location-based AR was built to be compared with existing standard-location based AR. The user evaluation results reveal that the overall functional requirements which are gathered from user journey have same level of success rate criteria when compared with standard location-based AR. Nevertheless, the field study participants highlighted the extended features in our prototype could significantly enhance the user action on locating the right object in particular place when compared with standard location-based AR application (proved with the required time).
Data Analytics Project proposal: Smart home based ambient assisted living - D...Tarun Swarup
In Ambient Assisted Living environments, monitoring the elderly population can detect a wide range of environmental and user-specific parameters such as daily activities, a regular period of inactivity, usual behavioural patterns and other basic routines. The prime goal of this proposal is to experiment the anomaly detection methods and clustering techniques such as K-means, local outlier factor, K-nearest, DBSCAN and CURE on data and determine the most efficient and accurate method among all.
Network Driven Behaviour Modelling for Designing User Centred IoT ServicesFahim Kawsar
We are observing a monumental effort from the industry and academia to make everything connected. Naturally, to understand the needs of these connected things, we need a better understanding of humans and where, when, and how they interact. Then we can create digital services and capabilities that fundamentally change the way we experience our lives. IoT 1.0 is all about connectivity, and scale. IoT 2.0 will be about learning and contextual automation. Designing intention- and behavior-aware services will be the principal source of differentiation, and competitive advantage for the industry players. In this talk I argue that for wide scale adoption, and market penetration of personalized IoT services, existing network infrastructure should play the key role for sensing and learning, by eliminating the cost of deployment and management of many sensors. I will show then how wireless network can be used as a sensing platform to model human behaviour and to redefine people-content, people-thing, and people-people interaction experience in an IoT enabled world.
Quantified Self movement allows to collect a lot of
personal data which can be used to nurture the model
of the users. Evenly, when aggregated, these personal
data become a picture of the people of a space in a City
Model. This model can be fed also by data coming from
crowdsensing. The resulting City Model can be used to
provide personalized services to citizen, and to increase
people awareness about their behaviour that can help
in promoting collective behavioural change. The paper
SMARCOS Abstract Paper submitted to ICCHP 2012Smarcos Eu
This study is part of the European project "Smarcos" (http://www.smarcos-project.eu/) that includes among its goals the development of services which are specifically designed and accessible for blind users.
In this paper we present the prototype application designed to make the main phone features available in a way which is accessible for a blind user. The prototype has been developed to firstly evaluate the interaction modalities based on gestures, audio and vibro-tactile feedback.
Similar to RoutineMaker: Towards End-User Automation of Daily Routines Using Smartphones (20)
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
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RoutineMaker: Towards End-User Automation of Daily Routines Using Smartphones
1. RoutineMaker: Towards End-User Automation of Daily Routines Using
Smartphones
Ville Antila, Jussi Polet, Arttu Lämsä, Jussi Liikka
Context-Awareness and Service Interaction
VTT Technical Research Centre of Finland
Oulu, Finland
{ville.antila, jussi.polet, arttu.lamsa, jussi.liikka}@vtt.fi
Abstract — People use smartphones in daily activities for the context or situation of the user, maybe even better than
accessing and storing information in various situations. In this more traditional and quantifiable sensors of context can.
paper, we present a work in progress for detecting and In this paper, we study the possibilities of detecting and
automating some of these activities. To explore the possible automating smartphone usage routines. With a routine we
patterns we developed an experimental application to detect mean an association of a location, used application and the
daily tasks used by smartphones and analyzed it to provide time of day. To reveal some of these somewhat hidden
suggestions for “routines”. We conducted a two-week user patterns, we developed an application to detect the day-to-
study with 10 users to evaluate the approach. During the study day smartphone use by logging the application usage and
the application logged the usage patterns, sent information to
locations and clustering them to identifiable patterns. We
the server where it was analysed and clustered. The
participants could also automate their smartphone tasks using
also implemented a functionality to automate these patterns
the analysed data. The findings suggest that people would be using the application. One reason for this functionality was
willing to automatize tasks given that the approach gives to find out whether the users could actually detect some
flexibility and expressiveness without too much information routine-like behaviour from their smartphone usage patterns;
overload. Future work includes refining the algorithms based which would then help us to evaluate our approach
on the gathered real-life data and modifying the interaction qualitatively.
design to approach the challenges found with the initial study.
II. RELATED WORK
Keywords - Context-awareness; Routine detection; Sensing; The idea of extracting usage patterns and routines from
Smartphones; Task automation; smartphone usage data is not unique or novel as such. There
has been a body of research exploring different quantitative
I. INTRODUCTION methods to mine patterns of human activities from large
datasets. Eagle and Pentland demonstrate the ability to use
Smartphones are becoming ubiquitous and ever more
mobile devices to recognise social patterns, identify
important for the daily activities of their users. The multitude
significant locations, and model organisational rhythms [4].
of smartphone applications, dedicated to help in daily tasks,
Farrahi and Gatica-Perez suggest that human interaction
are used almost everywhere at any time. Smartphones and
data, or human proximity, obtained by mobile phone
their applications, serving as pocket PCs and extending our
Bluetooth sensor data, can be integrated with human location
desktop experience, are becoming so ubiquitous part of our
data, obtained by mobile cell tower connections, to mine
ways to store and access information that some of the tasks
meaningful details about human activities from large and
we perform with them have become daily routines. Examples
noisy datasets [6]. They also present a framework to classify
of routine-like behaviour can include checking e-mail in the
people’s daily routines (defined by day type and by group
morning, reading the news or listening to music while
affiliation type) from the data [7]. Similarly Verkasalo
commuting, searching local information, navigating or
illustrates the relationships between common locations, such
checking-in to places to assess and comment our on-the-go
as office or home, to the usage patterns of different
experiences. People also use smartphones to complement
applications [10]. In our work we are concentrating on real-
other daily activities or routines such as watching TV,
time analysis and presentation of routines of an individual
reading newspaper and going to the grocery store [8].
user rather than modelling the group behaviour. We are also
On the other hand, the latest consumer studies indicate
looking into qualitatively evaluating the found patterns by
that the emerging user patterns could be more application-
the user (by the act of saving or modifying the routine).
specific than they are device-specific [5]. The routine of
Chittaranjan et al. investigate the relationship between
“checking Facebook in the evening from bed” could be done
behavioural characteristics derived from rich smartphone
either with a smartphone, laptop or a tablet device. The
data and self-reported personality traits [1]. The data stems
action or behaviour is often associated to a specific service or
from smartphones of a set of 83 individuals collected over a
application it is done with more than the device mediating
continuous period of 8 months. From the analysis, they show
the experience. Therefore we can hypothesize that the usage
that aggregated features obtained from smartphone usage
of a specific application can also indicate something about
data can be indicators of the Big-Five personality traits.
2. Additionally, they present an automatic method to infer the automated routine out of it. The saved routine is then sent to
personality type of a user based on cell phone usage with up the server as well for persistent storage and further analysis.
to 75.9% accuracy. This work gives an interesting insight
into how the collected behavioural data can be related to B. Mobile Application
known personality traits, and as a concept could be applied The RoutineMaker mobile application visualises the
in our research as well in the future. detected routines (see Figure 1) by showing the location
In addition to detecting the routines using smartphones, clusters on a map view as well as on a list view. The
there has been research on how to present it to the user for a MapView shows the location cluster markers, by which
potential user action. Dearman et al. present an approach to tapping the user can see a preview list of the most used
present information to the user based on the location and applications in that cluster. The user can also switch from the
knowledge of the task. Examples include location-based task MapView to the ListView, which shows an in-depth list of
notifications and support for opportunistically suggesting the location clusters. In the ListView, the user can select
places for certain activities on-the-go [2, 3]. While these desired applications to be launched at specific times and save
studies have similar goals than our approach, the intended the sequence as a routine. The RoutineMaker mobile
usage situations are somewhat different; nevertheless we application checks frequently, if there are any routines to run
think that the application presented in this paper could and if so, it checks whether the current location and time is
benefit from introducing some form of serendipitous or associated with any routines. Should there be a match; the
opportunistic presentation of data to the user regarding the specified routine is run automatically.
routines.
We also acknowledge in our work that the breadth of
analysis done with the data can also be potentially misused.
Shilton discusses the privacy of collecting multi-dimensional
sensor data from mobile phones [9]. As by using
smartphones it is possible to gather an extensive set of
information about people’s locations, habits and routines,
even personality traits, it might be that smartphones at the
extreme could be the most widespread embedded
surveillance tools in the history. The trade-off for the user is
between the perceived benefit and privacy concerns, and we
see that this trade-off should be balanced by the user via her
actions using the system (explicitly sharing what is needed
and wanted to be shared).
III. ROUTINEMAKER APPLICATION
In this section we present the developed application for
detecting and automating daily routines with smartphones.
The application logs daily smartphone usage data (locations, Figure 1. Cluster overview shown in the MapView and
time and used applications) and tries to detect patterns, such cluster details shown in the ListView
as a sequence of applications used or tasks done on a certain C. Server
time at a certain location. Once the possible routines are
The server-side application is responsible for creating the
detected, the application displays them to the user. The user
application-location clusters from the logged data received
can accept and create a “routine” from the suggested
from the client devices. The algorithm is split into two main
patterns or modify the suggested pattern and then save it.
phases: geographical and application clustering. The steps
The user can also name the routines in similar way than one
are illustrated in Figure 2.
would do with ordinary applications (e.g. “going to sleep”-
First step of the process is the geographical clustering
routine, “going to movies”-routine, “going to work”-
which filters out the most significant locations from the data
routine).
(visited or stayed most often). After the geographical
A. Software Design and Implementation clustering is done, an application table is generated, where
The prototype consists of a mobile application, which each column represents a five-minute time slot in a day and a
collects usage data and presents the processed usage data to row is generated for each application. Then the cluster
the user and a server-side application, which performs the samples are gone through and the value of the table element
data processing. The mobile application gathers usage data representing the time-application combination of the sample
(location and applications used) from the device. This data is is increased by one. After this, the whole table is normalised
sent to the server and analysed to find location clusters and by dividing it by the maximum element of the table. A usage
used applications in those clusters. The mobile client table, containing Boolean values, is generated from the
presents this analysed data to the user. If the user notices application table. The usage table is the same size as the
helpful or useful routines from the data she can create an application table and the elements contain value true, if the
application table value in this element is greater than a
3. threshold value, otherwise the elements contain value false. Table 3 Research questions
This is followed by applying a smoothing filter to the usage ID Question
table. This removes false slots that are located in between RQ-1 Is it possible to extract routines or tasks from the historical
two true elements in the usage table. usage data?
RQ-2 Were the extracted and suggested routines helpful?
RQ-3 [Following from the RQ-2] Could they be useful?
Geographic clustering Application clustering RQ-4 [Following from the RQ-2] Did they reveal any other possibly
interesting or important information?
Add samples to clusters Generate table of active
applications ordered by time
A. Participants
Filter out clusters with not Normalize table and get We recruited ten participants from three countries using
enough samples application usage times to e-mail lists. There were nine male participants and one
usage table
female. The participants had to be active smartphone users.
Combine clusters close to The participants also had to have suitable mobile phones
each other Apply smoothing filter to supported by the application (Android v2.2 or higher). The
usage table
participants were in the age range of 27 to 33 years with
Filter out samples far away average age of 29.7 and were very active smartphone users,
from cluster centers Get application launch times as 62% of them used smartphone applications a couple of
from usage table
times a day and 25% used them a couple of times in an hour.
Figure 2. Algorithm structure (repeated for each user) B. Findings
In this section, we provide a brief analysis of the gathered
The application launch times are then read from the data. The sources for the gathered data are the initial
usage table. Always when an element containing the value questionnaire, the logged data from the user study, the post
true is found proceeded by false; an application launch time questionnaire and open ended questions the users were asked
is detected. Table 1 and Table 2 contain an example of the in the end of the study.
application and usage tables. The generated application table
1) Perceived usefulness of routine detection and the
is shown in the Table 1. The usage table shown in the Table
2 is obtained by using a threshold value of 0.7. In this RoutineMaker application
example, two launch times are detected; 13:05 for “Music First, we asked how useful the participants rated
player” and 13:20 for “E-mail”. detecting their smartphone usage routines. The results show
that this was considered as useful (avg. 3.7, sd. 0.8, on a
Table 1 Application table scale from 1 to 5). We also asked how useful they perceived
Application Time
the RoutineMaker application as such. The results showed
13:00 13:05 13:10 13:15 13:20 13:25 13:30 that the approach was not perceived as very useful (avg. 2.1,
Music player 0 0.8 0.74 0.8 0.4 0 0 sd. 0.9). The reason for this was visible in the comments:
Web browser 0 0 0 0 0 0 0 First of all, the application could only automatically launch
E-mail 0 0 0 0 0.9 1 0 applications when they were at a certain location at a certain
Notebook 0 0 0 0.3 0.1 0.2 0 time. What the users wanted was even more automatic
behaviour, such as performing a certain task on its own
Table 2 Usage table without any user intervention. With the current design, such
Application Time
13:00 13:05 13:10 13:15 13:20 13:25 13:30
elaborate tasks were impossible to make with the application.
Music player false true true true false false false This lowered the perceived usefulness. Nevertheless, these
Web browser false false false false false false false comments give good insight into developing the application
E-mail false false false false true true false further.
Notebook false false false false false false false 2) Understanding the important factors of smartphone
routine detection
IV. USER STUDY To get a better insight into the design space of
The RoutineMaker application was evaluated with ten smartphone routine detection, we asked the participants to
users, who used the application for two weeks. During the rate 4 different factors or parameters of the routine detection
two weeks, the application logged the routines of the user, on a scale from 1 to 5. These parameters were: quality of
sent this information to the server, where it was analysed and detected patterns, amount of detected patterns, resolution of
clustered. The participants could automate their smartphone detected patterns and the accuracy of detection. Based on the
tasks using the analysed data. In the study, we included a results, the most important factor was accuracy (avg. 4.3, sd.
start and end questionnaires and a set of open-ended 0.76), while the amount of detected patterns was rated as
questions to probe the participants about their needs and least important (avg. 2.9, sd. 0.9). Resolution and quality
experiences related to the application concept and the actual were rated as somewhat important factors (avg. 3.6, sd. 0.79
usage of the prototype application. The research questions and avg. 3.3, sd. 1.1). The standard deviation was large in
for the user study are listed below in Table 3 Research quality ratings; taking a closer look at the results it seems
questions). that some participants did think that quality was important
4. whereas some did not rate it as important. It is possible that still offering suggestions based on the detected behaviour,
quality as a measurement was not very well understood in we can enable an easy and fast interface for users to
this context, or that it was already incorporated in the other customise and automate their routine-like behaviour without
ratings. limiting only to the specific smartphone tasks.
We also asked how well the RoutineMaker application The lessons learned from the application development
performed regarding the selected factors (quality, amount, and the user study include that the amount of detected
resolution and accuracy). In general, the application clusters (potential routines) can be quite high, therefore
performance was in line with the importance of the factors. leaving the selection and creation of routines more to the
The accuracy of routine detections was rated good (avg. 3.5, user. Nevertheless the suggestions should include only
sd. 0.84), as well as the resolution of the detected routines relevant applications, which are detected usually during the
(avg. 3.25, sd. 1.17). These were rated as most important same times during the day, in a routine-like manner.
factors, so we can conclude that some of the parameters The future work consists in developing the application
selected for the routine detection algorithms were and algorithms further using the data gathered from the
corresponding to what the participants thought as important study. In some cases the algorithm for detecting the routines
or useful. was “too adaptive” and some clusters were removed if the
The amount of detected routines was rated the worst of user had an unordinary day during the week. We are seeking
these factors (avg. 2.25, sd. 1.05). This can be due to a to tweak the threshold for the adaption and include better
relatively large number of false positive detections of fitness values for the detected, possible routines, and
applications due to the features of the underlying OS weighting them in the algorithm enabling the process to learn
(Android), which opportunistically leaves applications which kind of application sequences are perceived as useful
running in the background to increase user experience (such routines. We are also looking into doing more user studies
as the response times of applications). This issue can be with larger group of participants learning more about the
fixed by filtering out processes which the user is not actively user behaviours and surveying the routines people currently
using. Nevertheless, we can also hypothesise that leaving have while using smartphones.
some of these applications to be selectable can create certain
serendipity in creating the routines and allows users to create REFERENCES
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