Semantic and Fuzzy Modelling for Human Behaviour Recognition in Smart Spaces. A case study on Ambient Assisted Living.
24.4.2015 Åbo Akademi University, Finland
Plant leaf identification system using convolutional neural networkjournalBEEI
This paper proposes a leaf identification system using convolutional neural network (CNN). This proposed system can identify five types of local Malaysia leaf which were acacia, papaya, cherry, mango and rambutan. By using CNN from deep learning, the network is trained from the database that acquired from leaf images captured by mobile phone for image classification. ResNet-50 was the architecture has been used for neural networks image classification and training the network for leaf identification. The recognition of photographs leaves requested several numbers of steps, starting with image pre-processing, feature extraction, plant identification, matching and testing, and finally extracting the results achieved in MATLAB. Testing sets of the system consists of 3 types of images which were white background, and noise added and random background images. Finally, interfaces for the leaf identification system have developed as the end software product using MATLAB app designer. As a result, the accuracy achieved for each training sets on five leaf classes are recorded above 98%, thus recognition process was successfully implemented.
Applying Soft Computing Techniques in Information RetrievalIJAEMSJORNAL
There is plethora of information available over the internet on daily basis and to retrieve meaningful effective information using usual IR methods is becoming a cumbersome task. Hence this paper summarizes the different soft computing techniques available that can be applied to information retrieval systems to improve its efficiency in acquiring knowledge related to a user’s query.
Bioinformatics and Artificial Intelligence (AI) the interrelation between the...Swapsg
The relation between the Bioinformatics and the Artificial Intelligence (AI) specified in it as both the fields are new.
credits-https://poweredtemplate.com/03075/0/index.html
Semantics for Bioinformatics: What, Why and How of Search, Integration and An...Amit Sheth
Amit Sheth's Keynote at Semantic Web Technologies for Science and Engineering Workshop (held in conjunction with ISWC2003), Sanibel Island, FL, October 20, 2003.
Plant leaf identification system using convolutional neural networkjournalBEEI
This paper proposes a leaf identification system using convolutional neural network (CNN). This proposed system can identify five types of local Malaysia leaf which were acacia, papaya, cherry, mango and rambutan. By using CNN from deep learning, the network is trained from the database that acquired from leaf images captured by mobile phone for image classification. ResNet-50 was the architecture has been used for neural networks image classification and training the network for leaf identification. The recognition of photographs leaves requested several numbers of steps, starting with image pre-processing, feature extraction, plant identification, matching and testing, and finally extracting the results achieved in MATLAB. Testing sets of the system consists of 3 types of images which were white background, and noise added and random background images. Finally, interfaces for the leaf identification system have developed as the end software product using MATLAB app designer. As a result, the accuracy achieved for each training sets on five leaf classes are recorded above 98%, thus recognition process was successfully implemented.
Applying Soft Computing Techniques in Information RetrievalIJAEMSJORNAL
There is plethora of information available over the internet on daily basis and to retrieve meaningful effective information using usual IR methods is becoming a cumbersome task. Hence this paper summarizes the different soft computing techniques available that can be applied to information retrieval systems to improve its efficiency in acquiring knowledge related to a user’s query.
Bioinformatics and Artificial Intelligence (AI) the interrelation between the...Swapsg
The relation between the Bioinformatics and the Artificial Intelligence (AI) specified in it as both the fields are new.
credits-https://poweredtemplate.com/03075/0/index.html
Semantics for Bioinformatics: What, Why and How of Search, Integration and An...Amit Sheth
Amit Sheth's Keynote at Semantic Web Technologies for Science and Engineering Workshop (held in conjunction with ISWC2003), Sanibel Island, FL, October 20, 2003.
Comparative Analysis of Computational Intelligence Paradigms in WSN: Reviewiosrjce
Computational Intelligence is the study of the design of intelligent agents. An agent is something that
react according to an environment—it does something. Agents includes worms, dogs, thermostats, airplanes,
humans, and society. The purpose of computational intelligence is to understand the principles that make
intelligent behavior possible, in real or artificial systems. Techniques of Computational Intelligence are
designed to model the aspects of biological intelligence. These paradigms include that exhibit an ability to
learn or adapt to new situations,to generalize, abstract, learn and associate. This paper gives review of
comparison between computational intelligence paradigms in Wireless Sensor Network and Finally,a short
conclusion is provided.
Read Between The Lines: an Annotation Tool for Multimodal DataDaniele Di Mitri
This is the presentation of Read Between The Lines, the paper which we published at the Learning Analytics & Knowledge Conference 2019 in Tempe, Arizona (#LAK19).
Link to the paper available in Open Access ACM library https://dl.acm.org/citation.cfm?id=3303776
Abstract:
This paper introduces the Visual Inspection Tool (VIT) which supports researchers in the annotation of multimodal data as well as the processing and exploitation for learning purposes. While most of the existing Multimodal Learning Analytics (MMLA) solutions are tailor-made for specific learning tasks and sensors, the VIT addresses the data annotation for different types of learning tasks that can be captured with a customisable set of sensors in a flexible way. The VIT supports MMLA researchers in 1) triangulating multimodal data with video recordings; 2) segmenting the multimodal data into time-intervals and adding annotations to the time-intervals; 3) downloading the annotated dataset and using it for multimodal data analysis. The VIT is a crucial component that was so far missing in the available tools for MMLA research. By filling this gap we also identified an integrated workflow that characterises current MMLA research. We call this workflow the Multimodal Learning Analytics Pipeline, a toolkit for orchestration, the use and application of various MMLA tools.
Top 5 most viewed articles from academia in 2019 - gerogepatton
The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications
USING ONTOLOGIES TO OVERCOMING DRAWBACKS OF DATABASES AND VICE VERSA: A SURVEYcseij
For a same domain, several databases (DBs) exist. The emergence of classical web to the semantic web has
contributed to the appearance of the notion of ontology that have shared and consensual vocabulary. For a
given, it is more interesting to take advantage of existing databases, to build an ontology. Most of the data
are already stored in these databases. So many DBs can be integrated to enable reuse of existing data for
the semantic web. Even for existing ontologies, the relevance of the information they contain requires
regular updating. These databases can be useful sources to enrich these ontologies. In the other hand, for
these ontologies more than the ratio ‘size of the instances on the size of working memory’ is large more
than the management of these instances, in memory, is difficult. Finding a way to store these instances in a
structured manner to satisfy the needs of performance and reliability required for many applications
becomes an obligation. As a consequence, defining query languages to support these structures becomes a
challenge for SW community. We will show through this paper how ontologies can benefit from DBs to
increase system performance and facilitate their design cycle. The DBs in their turn suffers from several
drawbacks namely complexity of the design cycle and lack of semantics. Since ontologies are rich in
semantic, DBs can profit from this advantage to overcoming their drawbacks.
New research articles 2019 may issue international journal of computer networ...IJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
Advanced Fuzzy Logic Based Image Watermarking Technique for Medical ImagesIJARIIT
The segmentation algorithms vary for the types of medical images such as MRI, CT, US, etc.The current study work
can further be extended to develop a GUI tool based approach for separating the ROI. Additionally, a new technique of
separating ROI form the original image that will be applicable for all type of medical images can be evolved. Separated ROI
can be stored with xmin, xmax, ymin and ymax value so that at the end of embedding process before transmitting watermarked
image, the segmented ROI can be attached with watermarked image. Any medical image watermarking approach will be
suitable, if we segment the ROI from medical image with the four values, then embedding of watermark can be done on whole
medical image, in this paper work on different scan like ctscan ,brain scan etc. our results significant high than other.
Development of durian leaf disease detection on Android device IJECEIAES
Durian is exceedingly abundant in the Philippines, providing incomes for smallholder farmers. But amidst these things, durian is still vulnerable to different plant diseases that can cause significant economic loss in the agricultural industry. The conventional way of dealing plant disease detection is through naked-eye observation done by experts. To control such diseases using the old method is extensively laborious, time-consuming and costly especially in dealing with large fields. Hence, the proponent’s objective of this study is to create a standalone mobile app for durian leaf disease detection using the transfer learning approach. In this approach, the chosen network MobileNets, is pre-trained with a large scale of general datasets namely ImageNet to effective function as a generic template for visual processing. The pre-trained network transfers all the learned parameters and set as a feature extractor for the target task to be executed. Four health conditions are addressed in this study, 10 per classification with a total of 40 samples tested to evaluate the accuracy of the system. The result showed 90% in overall accuracy for detecting algalspot, cercospora, leaf discoloration and healthy leaf.
New Research Articles 2019 October Issue Signal & Image Processing An Interna...sipij
Signal & Image Processing: An International Journal (SIPIJ)
ISSN: 0976 – 710X [Online]; 2229 - 3922 [Print]
http://www.airccse.org/journal/sipij/index.html
Current Issue; October 2019, Volume 10, Number 5
Free- Reference Image Quality Assessment Framework Using Metrics Fusion and Dimensionality Reduction
Besma Sadou1, Atidel Lahoulou2, Toufik Bouden1, Anderson R. Avila3, Tiago H. Falk3 and Zahid Akhtar4, 1Non Destructive Testing Laboratory, University of Jijel, Algeria, 2LAOTI laboratory, University of Jijel, Algeria, 3University of Québec, Canada and 4University of Memphis, USA
Test-cost-sensitive Convolutional Neural Networks with Expert Branches
Mahdi Naghibi1, Reza Anvari1, Ali Forghani1 and Behrouz Minaei2, 1Malek-Ashtar University of Technology, Iran and 2Iran University of Science and Technology, Iran
Robust Image Watermarking Method using Wavelet Transform
Omar Adwan, The University of Jordan, Jordan
Improvements of the Analysis of Human Activity Using Acceleration Record of Electrocardiographs
Itaru Kaneko1, Yutaka Yoshida2 and Emi Yuda3, 1&2Nagoya City University, Japan and 3Tohoku University, Japan
http://www.airccse.org/journal/sipij/vol10.html
With the surge in modern research focus towards Pervasive Computing, lot of techniques and challenges
needs to be addressed so as to effectively create smart spaces and achieve miniaturization. In the process of
scaling down to compact devices, the real things to ponder upon are the Information Retrieval challenges.
In this work, we discuss the aspects of multimedia which makes information access challenging. An
Example Pattern Recognition scenario is presented and the mathematical techniques that can be used to
model uncertainty are also presented for developing a system that can sense, compute and communicate in
a way that can make human life easy with smart objects assisting from around his surroundings.
This is the presentation of the paper entitled “A metamodel proposal for developing learning ecosystems” in the Emerging interactive systems for education session at the HCI International 2017 Conference, held in Vancouver, Canada, 9 - 14 July 2017.
The definition and development of learning ecosystems is a complex process with a wide range of requirements. Although two different institutions or companies share the same problems and goals regarding their learning and training processes, the learning ecosystems to support them are different. The components of the ecosystem, including the human factor as a key element, and the relationships between them, change over time. In other words, learning ecosystems evolve as natural ecosystems; there are many factors, both internal and external, that influence an entity. The authors have defined and developed different learning ecosystems. Moreover, they have transferred the same learning ecosystem, specifically a learning eco-system for knowledge management in a PhD Program, to different domains. These experiences have provided the required information to define the ecosystems metamodel following the Model Driven Architecture proposed by the Object Management Group. The aim of this metamodel is define a Domain Specification Language to develop learning ecosystems.
Comparative Analysis of Computational Intelligence Paradigms in WSN: Reviewiosrjce
Computational Intelligence is the study of the design of intelligent agents. An agent is something that
react according to an environment—it does something. Agents includes worms, dogs, thermostats, airplanes,
humans, and society. The purpose of computational intelligence is to understand the principles that make
intelligent behavior possible, in real or artificial systems. Techniques of Computational Intelligence are
designed to model the aspects of biological intelligence. These paradigms include that exhibit an ability to
learn or adapt to new situations,to generalize, abstract, learn and associate. This paper gives review of
comparison between computational intelligence paradigms in Wireless Sensor Network and Finally,a short
conclusion is provided.
Read Between The Lines: an Annotation Tool for Multimodal DataDaniele Di Mitri
This is the presentation of Read Between The Lines, the paper which we published at the Learning Analytics & Knowledge Conference 2019 in Tempe, Arizona (#LAK19).
Link to the paper available in Open Access ACM library https://dl.acm.org/citation.cfm?id=3303776
Abstract:
This paper introduces the Visual Inspection Tool (VIT) which supports researchers in the annotation of multimodal data as well as the processing and exploitation for learning purposes. While most of the existing Multimodal Learning Analytics (MMLA) solutions are tailor-made for specific learning tasks and sensors, the VIT addresses the data annotation for different types of learning tasks that can be captured with a customisable set of sensors in a flexible way. The VIT supports MMLA researchers in 1) triangulating multimodal data with video recordings; 2) segmenting the multimodal data into time-intervals and adding annotations to the time-intervals; 3) downloading the annotated dataset and using it for multimodal data analysis. The VIT is a crucial component that was so far missing in the available tools for MMLA research. By filling this gap we also identified an integrated workflow that characterises current MMLA research. We call this workflow the Multimodal Learning Analytics Pipeline, a toolkit for orchestration, the use and application of various MMLA tools.
Top 5 most viewed articles from academia in 2019 - gerogepatton
The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications
USING ONTOLOGIES TO OVERCOMING DRAWBACKS OF DATABASES AND VICE VERSA: A SURVEYcseij
For a same domain, several databases (DBs) exist. The emergence of classical web to the semantic web has
contributed to the appearance of the notion of ontology that have shared and consensual vocabulary. For a
given, it is more interesting to take advantage of existing databases, to build an ontology. Most of the data
are already stored in these databases. So many DBs can be integrated to enable reuse of existing data for
the semantic web. Even for existing ontologies, the relevance of the information they contain requires
regular updating. These databases can be useful sources to enrich these ontologies. In the other hand, for
these ontologies more than the ratio ‘size of the instances on the size of working memory’ is large more
than the management of these instances, in memory, is difficult. Finding a way to store these instances in a
structured manner to satisfy the needs of performance and reliability required for many applications
becomes an obligation. As a consequence, defining query languages to support these structures becomes a
challenge for SW community. We will show through this paper how ontologies can benefit from DBs to
increase system performance and facilitate their design cycle. The DBs in their turn suffers from several
drawbacks namely complexity of the design cycle and lack of semantics. Since ontologies are rich in
semantic, DBs can profit from this advantage to overcoming their drawbacks.
New research articles 2019 may issue international journal of computer networ...IJCNCJournal
The International Journal of Computer Networks & Communications (IJCNC) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Computer Networks & Communications. The journal focuses on all technical and practical aspects of Computer Networks & data Communications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced networking concepts and establishing new collaborations in these areas.
Advanced Fuzzy Logic Based Image Watermarking Technique for Medical ImagesIJARIIT
The segmentation algorithms vary for the types of medical images such as MRI, CT, US, etc.The current study work
can further be extended to develop a GUI tool based approach for separating the ROI. Additionally, a new technique of
separating ROI form the original image that will be applicable for all type of medical images can be evolved. Separated ROI
can be stored with xmin, xmax, ymin and ymax value so that at the end of embedding process before transmitting watermarked
image, the segmented ROI can be attached with watermarked image. Any medical image watermarking approach will be
suitable, if we segment the ROI from medical image with the four values, then embedding of watermark can be done on whole
medical image, in this paper work on different scan like ctscan ,brain scan etc. our results significant high than other.
Development of durian leaf disease detection on Android device IJECEIAES
Durian is exceedingly abundant in the Philippines, providing incomes for smallholder farmers. But amidst these things, durian is still vulnerable to different plant diseases that can cause significant economic loss in the agricultural industry. The conventional way of dealing plant disease detection is through naked-eye observation done by experts. To control such diseases using the old method is extensively laborious, time-consuming and costly especially in dealing with large fields. Hence, the proponent’s objective of this study is to create a standalone mobile app for durian leaf disease detection using the transfer learning approach. In this approach, the chosen network MobileNets, is pre-trained with a large scale of general datasets namely ImageNet to effective function as a generic template for visual processing. The pre-trained network transfers all the learned parameters and set as a feature extractor for the target task to be executed. Four health conditions are addressed in this study, 10 per classification with a total of 40 samples tested to evaluate the accuracy of the system. The result showed 90% in overall accuracy for detecting algalspot, cercospora, leaf discoloration and healthy leaf.
New Research Articles 2019 October Issue Signal & Image Processing An Interna...sipij
Signal & Image Processing: An International Journal (SIPIJ)
ISSN: 0976 – 710X [Online]; 2229 - 3922 [Print]
http://www.airccse.org/journal/sipij/index.html
Current Issue; October 2019, Volume 10, Number 5
Free- Reference Image Quality Assessment Framework Using Metrics Fusion and Dimensionality Reduction
Besma Sadou1, Atidel Lahoulou2, Toufik Bouden1, Anderson R. Avila3, Tiago H. Falk3 and Zahid Akhtar4, 1Non Destructive Testing Laboratory, University of Jijel, Algeria, 2LAOTI laboratory, University of Jijel, Algeria, 3University of Québec, Canada and 4University of Memphis, USA
Test-cost-sensitive Convolutional Neural Networks with Expert Branches
Mahdi Naghibi1, Reza Anvari1, Ali Forghani1 and Behrouz Minaei2, 1Malek-Ashtar University of Technology, Iran and 2Iran University of Science and Technology, Iran
Robust Image Watermarking Method using Wavelet Transform
Omar Adwan, The University of Jordan, Jordan
Improvements of the Analysis of Human Activity Using Acceleration Record of Electrocardiographs
Itaru Kaneko1, Yutaka Yoshida2 and Emi Yuda3, 1&2Nagoya City University, Japan and 3Tohoku University, Japan
http://www.airccse.org/journal/sipij/vol10.html
With the surge in modern research focus towards Pervasive Computing, lot of techniques and challenges
needs to be addressed so as to effectively create smart spaces and achieve miniaturization. In the process of
scaling down to compact devices, the real things to ponder upon are the Information Retrieval challenges.
In this work, we discuss the aspects of multimedia which makes information access challenging. An
Example Pattern Recognition scenario is presented and the mathematical techniques that can be used to
model uncertainty are also presented for developing a system that can sense, compute and communicate in
a way that can make human life easy with smart objects assisting from around his surroundings.
This is the presentation of the paper entitled “A metamodel proposal for developing learning ecosystems” in the Emerging interactive systems for education session at the HCI International 2017 Conference, held in Vancouver, Canada, 9 - 14 July 2017.
The definition and development of learning ecosystems is a complex process with a wide range of requirements. Although two different institutions or companies share the same problems and goals regarding their learning and training processes, the learning ecosystems to support them are different. The components of the ecosystem, including the human factor as a key element, and the relationships between them, change over time. In other words, learning ecosystems evolve as natural ecosystems; there are many factors, both internal and external, that influence an entity. The authors have defined and developed different learning ecosystems. Moreover, they have transferred the same learning ecosystem, specifically a learning eco-system for knowledge management in a PhD Program, to different domains. These experiences have provided the required information to define the ecosystems metamodel following the Model Driven Architecture proposed by the Object Management Group. The aim of this metamodel is define a Domain Specification Language to develop learning ecosystems.
Informative Centers' Intelligent Agent Based Model - a preliminary studytulipbiru64
Paper presented by Mazwani Ayu Mazlan, Jannatul Iza Ahmad Kamal, Intan Nurbaizura Zainuddin and Jafalizan Md. Jali at the 4th PERPUN International Conference 2015: Information Revolution, 11-12th August 2015 at Avillion Legacy Hotel, Melaka.
Breve charla dentro del Debate Ciencia ciudadana en acción junto con Ana Omedes, Toni Gabaldón y Daniel García. El debate formaba part de la 5ª edición del Campus Gutenberg, una escuela de verano dedicada a la comunicación y a la cultura científica impulsada por el Máster de Comunicación Científica, Médica y Ambiental (UPF-IDEC) y la Obra Social “la Caixa”, en colaboración con el Centro de Estudios de Ciencia, Comunicación y Sociedad (CCS-UPF) y la Associació Catalana de Comunicació Científica (ACCC). 14 de septiembre de 2015
Collective experimentation on human behaviour using citizen science practices Josep Perelló
Granada Seminar (15-‐19 June 2015). Physics Meets the Social Sciences.
We present the citizen science projects we have been running during the past 3 years. We have adopted the idea of running
collective experiments in public spaces of Barcelona to create
crowd-sourced data atainning to concrete questions.
We have been focussed on non‐permanent
or pop-up experiments on
1. human mobility through voluntary tracking. In a park (Science Festival) and in an exhibition room (museum).
2. human decision making through games, as a complementary approach through three different games (Board Game Festival in Barcelona).
Such data sources have allowed us to develop some stochastic models on human behaviour under concrete situations or circumstances. We critically analyse them and extract experience‐based conclusions from both a methodological and conceptual perspective.
Presentation at the Workshop on Expectations for AAL and enhanced living environments in 2025/2030, by Francisco Florez-Revuelta, Susanna Spinsante, and Nuno Garcia, all members of the Cost Action IC1303 - AAPELE - Algorithms, Architectures and Platforms for Enhanced Living Environments
Franz et al tdwg 2016 new developments for libraries of lifetaxonbytes
Franz et al. @ #TDWG16 - "New developments for the Libraries of Life project and app". Talk # 1138, Friday, December 09, 2016, 02:45 pm. Session Lightning Talks. See https://mbgserv18.mobot.org/ocs/index.php/tdwg/tdwg2016/schedConf/program
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.
An overview on unsupervised deep learning models and strategies to speed up Reinforcement Learning and make it more sample efficient in goal-based robotics tasks.
Representation learning algorithms are designed to learn abstract features that characterize data. State representation learning (SRL) focuses on a particular kind of representation learning where learned features are in low dimension, evolve through time, and are influenced by actions of an agent. As the representation learned captures the variation in the environment generated by agents, this kind of representation is particularly suitable for robotics and control scenarios. In particular, the low dimension helps to overcome the curse of dimensionality, provides easier interpretation and utilization by humans and can help improve performance and speed in policy learning algorithms such as reinforcement learning.
This survey aims at covering the state-of-the-art on state representation learning in the most recent years. It reviews different SRL methods that involve interaction with the environment, their implementations and their applications in robotics control tasks (simulated or real). In particular, it highlights how generic learning objectives are differently exploited in the reviewed algorithms. Finally, it discusses evaluation methods to assess the representation learned and summarizes current and future lines of research.
Deep Learning and Reinforcement Learning summer schools summary
26th June-6th July 2017, Montreal, Quebec
Things I learned. What was your favourite lesson?
Smart Dosing: A mobile application for tracking the medication tray-filling a...Natalia Díaz Rodríguez
Nauman Khan, Natalia Díaz Rodríguez,Ivan Porres and Johan Lilius (Åbo Akademi Univ., Finland)
Riitta Danielsson-Ojala, Hanna Pirinen, Lotta Kauhanen and Sanna Salanterä (University of Turku, Finland)
Sebu Björklund, Joachim Majors and Kimmo Rautanen
(MediaCity Content Testing Lab., Finland)
Tapio Salakoski, IlonaTuominen (University of Turku, Finland)
Presented at 6th International Workshop on Intelligent Environments Supporting Healthcare and Well-being WISHWell'14 within Ambient Intelligence (AmI'14), Eindhoven, The Netherlands. 11/11/14
Understanding Movement and Interaction: An Ontology for Kinect-Based 3D Depth Sensors
Natalia Díaz Rodríguez, Robin Wikström, Johan Lilius, Manuel Pegalajar Cuéllar, Miguel Delgado Calvo-Flores
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
6th International Conference on Machine Learning & Applications (CMLA 2024) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Student information management system project report ii.pdf
PhD Defense Natalia Díaz Rodríguez
1. Semantic and Fuzzy Modelling for Human Behaviour Recognition in Smart
Spaces. A case study on Ambient Assisted Living
1Doctoral Defense 24th April 2015,Turku, Finland
Natalia A. Díaz Rodríguez
Supervisors: Prof. Johan Lilius and Prof. Miguel Delgado Calvo-Flores. Advisor: Prof. Manuel Pegalajar Cuéllar
Turku Centre for Computer Science (TUCS), Dept. of Information Technologies, Åbo Akademi University (Finland)
Dept. of Computer Science and Artificial Intelligence, University of Granada (Spain)
2. 2
SPAIN: 15m of elders in 2049 (1/3 of the population) (INE)
FINLAND population 65+ years: 18.14% [1]
• [1] http://www.finnbay.com/media/news/government-prepares-to-set-out-new-requirements-for-senior-caretakers/
5. Ambient Assisted Living (AAL): usage of
technology to provide assistance to people who
needs it in their daily activities, in the less
obstrusive way
Aim: Independent living, safety, support
older/disadvantaged people
Includes: methods, systems, products and
services
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Background
6. Activity Recognition in Smart Spaces
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[Image: http://www.businesskorea.co.kr/sites/default/files/field/image/smart%20home.jpg + The noun project]
8. Handling uncertainty, vagueness
and imprecision
Broken/ missing sensors
Incomplete data, vagueness
etc.
Different ways of perfor-
ming activities
– Different object usage
Behaviour change
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10. Methods
WHY Semantic Technologies & Ontologies?
Semantic Web: well-defined meaning
Ontology:
– In Philosophy: study of entities and their
relations
– In Artificial Intelligence: “Explicit specification of
a conceptualization” [Gruber, 93]
– Web Ontology Language (OWL)
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14. Methods: Fuzzy Logic
WHY fuzzy (description) logics and fuzzy
ontologies?
Real life is not black & white
– Classical (Crisp) Logic: True/False
– Fuzzy Logic: [0, 1]
• e.g. blond, tall
For automatic reasoning about uncertain,
vague or imprecise knowledge
For natural language expressions
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15. 15
Case study on Ambient Assisted Living:
A fuzzy ontology for activity modelling and recognition
[Image: http://www.harmonizedsystems.co.uk/]
Example: Take Medication
16. 16
Case study on Ambient Assisted
Living: A fuzzy ontology for activity modelling and
recognition
Classes, Individuals, Data Properties and Object Properties
SUBJECT PREDICATE OBJECT
User performs activity Taking medicine =
(0.3 User performs sub-activity reach Cup or Medicine Box)
(0.3 User performs sub-activity move Cup or Medicine Box)
(0.1 User performs sub-activity place Cup or Medicine Box)
(0.1 User performs sub-activity open Medicine Box)
(0.1 User performs sub-activity eat Medicine Box)
(0.1 User performs sub-activity drink Cup)
23. A visual language to
configure the Smart Space behaviour
TARGET USER: non-technical
background
AIM:
– Rapid & easy programming of applications/
services
– Improve interoperability and usability
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25. Main contributions
1. A set of ontologies to model human behaviour and tackle
uncertainty and vagueness inherent to real life
2. An architecture that integrates Semantic Web and
Fuzzy Logic for interpretable activity recognition
3. A hybrid knowledge-based and data-driven algorithm for
real-time, effective and robust activity recognition (84.1%
precision)
4. Design and development of a toolbox for non-expert
users and rapid and easy programming of Smart Spaces
[4 Journals -3 on 3rd Q1-, 9 conference papers, Google Anita Borg,
Nokia and HLF scholar. Entrepreneurship award]
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28. Thank you for your attention
Natalia A. Díaz Rodríguez
https://research.it.abo.fi/personnel/ndiaz
ndiaz@abo.fi
Embedded Systems Lab. Dept. of Information Technologies
Åbo Akademi University, Turku, Finland
TUCS (Turku Centre for Computer Science)
Dept. of Computer Science
and Artificial Intelligence
University of Granada, Spain
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29. Appendix
DTW: O(mn) (m,n length of the time
series)
PAA compression size = 2
Take out food is a subsequence of
microwaving (Subsumption heuristic/filter)
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31. 31
Modelling activities with
fuzzy ontologies
Classes, Individuals, Data Properties and Object Properties
SUBJECT PREDICATE OBJECT
Filomena is a Person
Filomena has heart rate 60
Filomena performs sub-activity Reach glass
Filomena performs sub-activity Move medicine
Filomena performs sub-activity Pour water in glass
Filomena performs sub-activity Eat medicine
Filomena performs sub-activity Drink from glass
32. A crucial but challenging task in Ambient
Intelligence and AAL. Requires:
Context-awareness and heterogeneous data
sources
Training data: examples
Common-sense knowledge
Adaptation of behaviours
Alzheimer, Parkinson
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Human Activity Recognition