Search results for "Software"
showing 10 items of 7396 documents
SmartSpectra: Applying multispectral imaging to industrial environments
2005
SmartSpectra is a smart multispectral system for industrial, environmental, and commercial applications where the use of spectral information beyond the visible range is needed. The SmartSpectra system provides six spectral bands in the range 400-1000nm. The bands are configurable in terms of central wavelength and bandwidth by using electronic tunable filters. SmartSpectra consists of a multispectral sensor and the software that controls the system and simplifies the acquisition process. A first prototype called Autonomous Tunable Filter System is already available. This paper describes the SmartSpectra system, demonstrates its performance in the estimation of chlorophyll in plant leaves, …
Probing neural mechanisms of music perception, cognition, and performance using multivariate decoding.
2012
Recent neuroscience research has shown increasing use of multivariate decoding methods and machine learning. These methods, by uncovering the source and nature of informative variance in large data sets, invert the classical direction of inference that attempts to explain brain activity from mental state variables or stimulus features. However, these techniques are not yet commonly used among music researchers. In this position article, we introduce some key features of machine learning methods and review their use in the field of cognitive and behavioral neuroscience of music. We argue for the great potential of these methods in decoding multiple data types, specifically audio waveforms, e…
Face Processing on Low-Power Devices
2009
The research on embedded vision-based techniques is considered nowadays as one of the most interesting matters of computer vision. In this work we address the scenario in which a real-time face processing system is needed to monitor people walking through some locations. Some face detection (e.g., Viola-Jones face detector) and face recognition (e.g., eigenfaces) approaches have reached a certain level of maturity, so we focused on the development of such techniques on embedded systems taking into account both hardware and software constraints. Our goal is to detect the presence of some known individuals inside some sensitive areas producing a compact description of the observed people. Cap…
FoSBaS: A bi-directional secrecy and collusion resilience key management scheme for BANs
2012
Body Area Network (BAN) consists of various types of small physiological sensors, transmission modules and low computational components and can thus form an E-health solution for continuous all-day and any-place health monitoring. To protect confidentiality of collected data, a shared group key is usually deployed in a BAN, and consequently a secure communication group is generated. In this paper, we propose a bi-directional security and collusion resilience key management scheme for BAN, referred to as FoSBaS. Detailed analysis shows that the scheme can provide both forward security and backward security and resist against collusion attacks. Furthermore, the FoSBaS is implemented on a Sun …
Precise and efficient parametric path analysis
2012
Hard real-time systems require tasks to finish in time. To guarantee the timeliness of such a system, static timing analyses derive upper bounds on the worst-case execution time (WCET) of tasks. There are two types of timing analyses: numeric and parametric. A numeric analysis derives a numeric timing bound and, to this end, assumes all information such as loop bounds to be given a priori. If these bounds are unknown during analysis time, a parametric analysis can compute a timing formula parametric in these variables. A performance bottleneck of timing analyses, numeric and especially parametric, is the so-called path analysis, which determines the path in the analyzed task with the longes…
Conceptual Ontological Object Knowledge Base and Language
2008
This paper deals with AI in aspect of knowledge acquisition and ontology base structure. The core of the system was designed in an object model to optimize it for further processing. Direct concept linking was used to assure fast semantic network processing. Predefined attributes used in the core minimize the number of basic connections within the ontology and help in inference. The system is assumed to generate questions and to specify the knowledge. The AI system defined in this way opens a possibility for better understanding of such basic human mind mechanisms as learning or analyzing.
Robustly correlated key‐medical image for DNA‐chaos based encryption
2021
Abstract Medical images include confidential and sensitive information about patients. Hence, ensuring the security of these images is a crucial requirement. This paper proposes an efficient and secure medical image encryption‐decryption scheme based on deoxyribonucleic acid (DNA), one‐dimensional chaotic maps (tent and logistic maps), and hash functions (SHA‐256 and MD5). The first part of the proposed scheme is the key generation based on the hash functions of the image and its metadata. The key then is highly related and intensely sensitive to the original image. The second part is the rotation and permutation of the first two MSB bit‐plans of the medical image to reduce its black backgr…
D Sensor-Based Obstacle Detection Comparing Octrees and Point clouds Using CUDA
2012
This paper presents adaptable methods for achieving fast collision detection using the GPU and Nvidia CUDA together with Octrees. Earlier related work have focused on serial methods, while this paper presents a parallel solution which shows that there is a great increase in time if the number of operations is large. Two dierent models of the environment and the industrial robot are presented, the rst is Octrees at dierent resolutions, the second is a point cloud representation. The relative merits of the two dierent world model representations are shown. In particular, the experimental results show the potential of adapting the resolution of the robot and environment models to the task at h…
Automatic object detection in point clouds based on knowledge guided algorithms
2013
The modeling of real-world scenarios through capturing 3D digital data has been proven applicable in a variety of industrial applications, ranging from security, to robotics and to fields in the medical sciences. These different scenarios, along with variable conditions, present a challenge in discovering flexible appropriate solutions. In this paper, we present a novel approach based on a human cognition model to guide processing. Our method turns traditional data-driven processing into a new strategy based on a semantic knowledge system. Robust and adaptive methods for object extraction and identification are modeled in a knowledge domain, which has been created by purely numerical strate…
Probabilistic Transition-Based Approach for Detecting Application-Layer DDoS Attacks in Encrypted Software-Defined Networks
2017
With the emergence of cloud computing, many attacks, including Distributed Denial-of-Service (DDoS) attacks, have changed their direction towards cloud environment. In particular, DDoS attacks have changed in scale, methods, and targets and become more complex by using advantages provided by cloud computing. Modern cloud computing environments can benefit from moving towards Software-Defined Networking (SDN) technology, which allows network engineers and administrators to respond quickly to the changing business requirements. In this paper, we propose an approach for detecting application-layer DDoS attacks in cloud environment with SDN. The algorithm is applied to statistics extracted from…