Search results for "Artificial"
showing 10 items of 7394 documents
Experimental Characterization of Mobile Fading Channels Aiming the Design of Non-Wearable Fall Detection Radio Systems at 5.9 GHz
2016
One of the major concerns for the independent living of elderlies is a fall incident. To decrease human interaction errors and user privacy concerns of existing fall detection systems, a new generation of fall detection systems is emerging. The new trend is to design non-wearable devices that can monitor the physical activities of the home user using radio waves reflected off the body. This paper reports an in-home radio measurement campaign at 5.9 GHz, which has been conducted to study the impacts of different physical activities of the user, including fall incidents, on the channel transfer function (CTF) and the power delay profile (PDP) of indoor mobile radio channels. The home is equip…
A Sentiment Enhanced Deep Collaborative Filtering Recommender System
2021
Recommender systems use advanced analytic and learning techniques to select relevant information from massive data and inform users’ smart decision-making on their daily needs. Numerous works exploiting user’s sentiments on products to enhance recommendations have been introduced. However, there has been relatively less work exploring higher-order user-item features interactions for sentiment enhanced recommender system. In this paper, a novel Sentiment Enhanced Deep Collaborative Filtering Recommender System (SE-DCF) is developed. The architecture is based on a Neural Attention network component aggregated with the output predictions of a Convolution Neural Network (CNN) recommender. Speci…
Reconstruction Improvement in Integral Fourier Holography by Micro-Scanning Method
2015
Although integral holography has many promising advantages in the field of 3D imaging, the resolution of reconstructed holographic image is still limited by the insufficient information captured. To improve the reconstruction quality, an integral Fourier holographic imaging method based on micro-scanning of the micro-lens array is proposed in this paper. The micro-scanning of the micro-lens array can increase the sampling rate in spatial frequency domain and the information of the generated Fourier hologram, which will eventually eliminate the overlapping effect in the reconstructed 3D image. Experiments for different micro-scanning modes are carried out to verify the feasibility of the pro…
Polarization-based Robot Orientation and Navigation
2015
From insects in your garden to creatures in the sea, inspiration can be drawn from nature to design a whole new class of smart robotic devices. These smart machines may move like living creatures. They can be launched toward a specific target for a pre-defined task. Bio-inspiration is developing to meet the needs of many challenges particularly in machine vision. Some species in the animal kingdom like cephalopods, crustaceans and insects are distinguished with their visual capabilities which are strongly improved by means of polarization. This work surveys the most recent research in the area of bio-inspired polarization based robot orientation and navigation. Firstly, the authors will bri…
Locality-sensitive hashing enables signal classification in high-throughput mass spectrometry raw data at scale
2021
Mass spectrometry is an important experimental technique in the field of proteomics. However, analysis of certain mass spectrometry data faces a combination of two challenges: First, even a single experiment produces a large amount of multi-dimensional raw data and, second, signals of interest are not single peaks but patterns of peaks that span along the different dimensions. The rapidly growing amount of mass spectrometry data increases the demand for scalable solutions. Existing approaches for signal detection are usually not well suited for processing large amounts of data in parallel or rely on strong assumptions concerning the signals properties. In this study, it is shown that locali…
Cognitive Reasoning and Inferences through Psychologically based Personalised Modelling of Emotions Using Associative Classifiers
2014
The development of Microsoft Kinect opened up the research field of computational emotions to a wide range of applications, such as learning environments, which are excellent candidates to trial computational emotions based algorithms but were never feasible for given consumer technologies. Whilst Kinect is accessible and affordable technology it comes with its' own additional challenges such as the limited number of extracted Action Units (AUs). This paper presents a new approach that attempts at finding patterns of interaction between AUs and each other on one hand and patterns that link the related AUs to a given emotion. In doing so, this paper presents the ground work necessary to reac…
Sub-symbolic Mapping of Cyc Microtheories in Data-Driven “Conceptual” Spaces
2007
The presented work aims to combine statistical and cognitive-oriented approaches with symbolic ones so that a conceptual similarity relationship layer can be added to a Cyc KB microtheory. Given a specific microtheory, a LSA-inspired conceptual space is inferred from a corpus of texts created using both ad hoc extracted pages from the Wikipedia repository and the built-in comments about the concepts of the specific Cyc microtheory. Each concept is projected in the conceptual space and the desired layer of subsymbolic relationships between concepts is created. This procedure can help a user in finding the concepts that are "sub-symbolically conceptually related" to a new concept that he want…
Evaluating Classifiers for Mobile-Masquerader Detection
2006
As a result of the impersonation of a user of a mobile terminal, sensitive information kept locally or accessible over the network can be abused. The means of masquerader detection are therefore needed to detect the cases of impersonation. In this paper, the problem of mobile-masquerader detection is considered as a problem of classifying the user behaviour as originating from the legitimate user or someone else. Different behavioural characteristics are analysed by designated one-class classifiers whose classifications are combined. The paper focuses on selecting the classifiers for mobile-masquerader detection. The selection process is conducted in two phases. First, the classification ac…
Personalized distance learning based on multiagent ontological system
2004
The paper presents architecture of a personalized distance learning system based on multiagent technology and ontological modelling of students' profiles. Delocalization of a student data in the system is achieved by software agents, which assumed to be distributed at different platforms. These platforms operate as separate Web services and use the ACL (agent communication language) for the data transfer. In this paper the algorithm is proposed, according to which the multiagent ontological system for personalized distance learning (MOSPDL) solves the tasks of distant learning process automation, which assume utilization of the ontological models of students' and learning resources' profile…
On the Generalizability of Programs Synthesized by Grammar-Guided Genetic Programming
2021
Grammar-guided Genetic Programming is a common approach for program synthesis where the user’s intent is given by a set of input/output examples. For use in real-world software development, the generated programs must work on previously unseen test cases too. Therefore, we study in this work the generalizability of programs synthesized by grammar-guided GP with lexicase selection. As benchmark, we analyze proportionate and tournament selection too. We find that especially for program synthesis problems with a low output cardinality (e.g., a Boolean output) lexicase selection overfits the training cases and does not generalize well to unseen test cases. An analysis using common software metr…