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This paper introduces a hybrid method to synthesize area-efficient fault-secure NoC switches to detect all errors resulting from any single-point combinational or transition fault in switches and interconnect links. Firstly, the structural faults that are always detectable by data encoding at flit-level are identified. Next, the fault-secure structure is constructed with minimized area such that errors...
A key requirement for modern Networks-on-Chip (NoC) is the ability to detect and diagnose faults and failures. A novel approach is proposed which addresses the challenge of fault detection using an online mechanism. The approach minimises online intrusion by employing dynamic rates of testing to maximize NoC throughput while still ensuring sufficient testing. This is achieved using a novel Monitor...
In this paper, we propose a new feature learning approach called complete discriminative feature learning (CDFL) for heterogeneous face recognition. Unlike most existing heterogeneous face recognition methods where hand-crafted feature descriptors are used for face representation, the proposed CD-FL aims to learn an optimal weighted discriminative image filter to improve learning discriminative filters,...
In this paper we propose a modification of double error correcting (DEC) BCH codes that allows for a fast correction of arbitrary 1-bit and 2-bit errors, as well as 3-bit errors comprising adjacent 2-bit errors in certain bit positions. The proposed code has the same number of check bits as a double error correcting, triple error detecting (DEC-TED) BCH code with code distance 6. The proposed code...
In this paper, we present a data-driven fault detection and isolation method for linear time-invariant system. This approach is inspired by a newly popular subspace identification method called predictor-based subspace identification. Residual estimators can be generated without any prior knowledge about mechanism of the system through the proposed method. These estimators are actually evaluations...
Automatic human action recognition is a core functionality of systems for video surveillance and human-object interaction. However, the diverse nature of human actions and the noisy nature of most video content make it difficult to achieve effective human action recognition. To overcome the aforementioned problems, Sparse Representation (SR) has recently attracted substantial research attention. However,...
In this study, a theoretical model for the combination of all individual questions from a questionnaire is investigated. For this implementation, a well-fitted Elman neural network is used in order to formulate the weighting relations between questions of the questionnaire which is produced for the project “Innovative Services to Strengthen Cooperation and Internationalization between SMEs” (I.S.C...
For the purpose of smooth human-robot interaction, a robot is supposed to be capable of semantically parsing the human instructions in a large scale. However, the existing supervised approaches to learning a large-scale semantic parser needs a good deal of training examples with annotations. The exhaustive cost of annotating enough sentences prevents them from learning such parser for interpreting...
Moment descriptors have been applied in object recognition as the features since the moment method was introduced by Hu [1]. The moment based features capture the global properties of an object rather than the local ones. In this research, a set of Zernike moment based feature vectors is proposed for a Chinese characters recognition system. We have composed three different feature vectors in the four-dimensional...
System on chip (SOC) makes it possible to design a complex system in a short period of time by using intellectual property (IP) blocks. The complexity of the design makes testing of the SOC a very difficult task. To alleviate this test access issue, IEEE 1500 has been introduced. It has become a widely used option because of its completeness and easy to use approach, but this standard is only supported...
We present an architecture of a spike based multiclass classifier using neurons with non-linear dendrites and sparse synaptic connectivity where each synapse takes a binary value. The learning in this model happens not through weight updates but through structural changes, i.e. a change of connectivity between inputs and dendrites. Hence, it is well suited for implementation in neuromorphic systems...
This paper addresses the design of input signals for the purpose of discriminating among a finite set of models of a dynamic system within a given finite time interval. A motivating application is fault detection and isolation. We propose several specific optimization problems with objectives or constraints based on signal power, signal amplitude, and probability of successful model discrimination...
In this paper, we study the following variant of the junta learning problem. We are given oracle access to a Boolean function f on n variables that only depends on k variables, and, when restricted to them, equals some predefined function h. The task is to identify the variables the function depends on. This is a generalisation of the Bernstein-Vazirani problem (when h is the XOR function) and the...
Factor analysis is mainly by extracting the compact representations of speakers' utterances, which are referred to as i-vectors. A low new space called total variability space, which is speaker and channel dependent is trained in the modeling. During the experiments, channel compensation approaches are used to remove the interference included by i-vectors. They are respectively are Nuisance Attribute...
Accidental falling is one of the health hazards for seniors. A well falling detection mechanism can help the caregivers to save the elders in time. Falling detection technique becomes a critical factor to improve the quality of home care. Generally, the acceleration of a human's waist is smooth. Only the unstable state will generate acute acceleration. Therefore, in this paper, we installed the G-sensor...
The tailsitter aircraft merges the endurance and speed of fixed-wing aircraft with the flexibility and VTOL abilities of rotorcraft. Because of the requirement to be functional at a full range of attitudes, quaternions are typically employed to calculate attitude error. Attitude control is then accomplished by using the vector component of the error quaternion to drive flight control surfaces. This...
One of the challenges in IT Service Management is an assessment of an innovation benefit introduced into service delivery on performance of IT System Administrator (SA). The question is especially complex when variability of the service requests load is taken into account. We used the sequential probability ratio test to assess effects of innovation for a case when a load of the service teams is constant...
Known as “the art of strokes”, Chinese calligraphy expresses its aesthetic through the strokes. A calligraphy learner practise the strokes and compose a calligraphic character by the strokes thereafter. Following the same process, the calligraphy robot, Callibot [2] needs to extract the strokes from a character. Therefore, we propose an approach to extract strokes using the geometric properties on...
Dyspepsia is a condition of indigestion and became one of the diseases with a large number of patients in Indonesia. Early detection of Dyspepsia is done to assist in the prevention of the disease. Iridology is a method of early detection in human organs disorders by analyzing the iris patterns. However, the application of Iridology technique often finds difficulties because it requires a high level...
This paper deals with coherent multi-polarization SAR change detection assuming the availability of reference and test images collected from N multiple polarimetric channels. At the design stage, the change detection problem is formulated as a binary hypothesis testing problem and the principle of invariance is used to come up with decision rules sharing the Constant False Alarm Rate (CFAR) property...
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