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Auscultation of the respiratory sounds is an inexpensive and effective method for diagnosing cardio-pulmonary disorders using lung sounds from chest and back. Nowadays, high system performances in the management of robust processes that require great attention were increased using the computer-aided analysis methods and the developments of the diagnosis system. Analysis of the respiratory sounds with...
A restricted Boltzmann machine (RBM) processor (RBM-P) supporting on-chip learning and inference is proposed for machine learning applications in this paper. Featuring neural network (NN) model reduction for external memory bandwidth saving, low power neuron binarizer (LPNB) with dynamic clock gating and area-efficient NN-like activation function calculators, user-defined connection map (UDCM) for...
This paper presents an ultra-high-performance neural network engine fabricated in a 65nm CMOS technology. The 0.9mm2 core relies on an energy-efficient resonant clock mesh running at 5.5GHz to achieve 0.76 8-bit TOPS, improving throughput by over 4x, area efficiency by over 8×, and energy-delay-area product by over 1.8× compared to previous state-of-the-art neural network designs. Achieving a charge...
In this paper, we investigate the problem of finding argumentation graphs consistent with some observed statement labellings. We consider a general abstract framework, where the structure of arguments is left unspecified, and we focus on particular grounded argument labellings where arguments can be omitted. The specification of such grounded labellings, the Principle of Multiple Explanations and...
Procedural content generation (PCG) systems are designed to automatically generate content for video games. PCG for physics-based puzzles requires one to simulate the game to ensure feasibility and stability of the objects composing the puzzle. The major drawback of this simulation-based approach is the overall running time of the PCG process, as the simulations can be computationally expensive. This...
Nowadays, people might need super resolution to obtain high quality images. Super resolution algorithm enhances high frequency information (texture or edges) to improve the image quality. We can do more things with super resolution, such as road surveillance system. The image quality would be degraded by illumination, angle, distance, and other conditions, and it will result in failing to recognize...
After analyzing the advance of technology, it is clear that use of the Internet, computers, smart phones and tablets has become ubiquitous and therefore, the creation and proliferation of cyber threats and attacks has grown exponentially. Consequently, Anti-Virus companies and researchers have developed new approaches for dealing with discovering and classifying malware. Among these, machine learning...
Automatic prediction of photo aesthetic quality is useful for many practical purposes. Current computational approaches typically solved this problem by assigning a categorical label (good or bad) to a photo. However, due to the subjectivity and complexity of humans aesthetic judgments, only a categorical label is insufficient to represent humans perceived aesthetic quality of a photo. This paper...
The success of the deep learning and specifically learning layer by layer led to many impressive results in several contexts that include neural network. This gave us the idea to apply this principle of learning on wavelet network because it is an active research topic at the moment. This paper present our approach for image classification by the combination of two techniques of learning: the wavelet...
The semiconductor counterfeiting has become a serious problem. Several Physical Unclonable Functions (PUFs), which utilizes the variation when manufacturing, are proposed as a countermeasure for imitation electronics. An arbiter PUF is one of the most popular PUFs. The operation of an arbiter PUF can be expressed by using a delay model. An arbiter PUF is reported to be attacked by forcing them to...
Today, web-based education technologies such as e-learning, distance learning, online course, virtual classrooms and interactive learning are commonly used outside the traditional education systems. Massive Open Online Courses, which were adopted with the evolution of these systems in 2008, have become the most popular education systems of today and access to a very large audiences with many modules...
The results of the requirements engineering process are predominantly documented in natural language requirements specifications. Besides the actual requirements, these documents contain additional content such as explanations, summaries, and figures. For the later use of requirements specifications, it is important to be able to differentiate between legally relevant requirements and other auxiliary...
Automatic recognition of emotion through facial expressions remains an active area of study. This study concerns the detection of shyness in smiles. As far as our knowledge is concerned, detecting the emotion of shyness through smile thus far has not been studied. Experiment was conducted where test subjects underwent an experiment with a stimuli designed to elicit shyness in their smiles. The expected...
Recent years have seen increased interest in the use of off-grid solutions for electrification of rural areas. Off-grid electrification (such as solar home systems and micro-grids) are particularly applicable to the rural African context, where little infrastructure exists and in many regions grid extension is prohibitively expensive. To be economically viable, these systems must maximize the power...
Diabetic Retinopathy (DR) is the leading cause of blindness in the working-age population. Microaneurysms (MAs), due to leakage from retina blood vessels, are the early signs of DR. However, automated MA detection is complicated because of the small size of MA lesions and the low contrast between the lesion and its retinal background. Recently deep learning (DL) strategies have been used for automatic...
The aim of this work is to develop a wearable device for the safety and protection of women and girls. This objective is achieved by the analysis of physiological signals in conjunction with body position. The physiological signals that are analyzed are galvanic skin resistance and body temperature. Body position is determined by acquiring raw accelerometer data from a triple axis accelerometer. Acquisition...
There exists unequivocal evidence denoting the dire consequences which organisations and governmental institutions face from insider threats. While the in-depth knowledge of the modus operandi that insiders possess provides ground for more sophisticated attacks, organisations are ill-equipped to detect and prevent these from happening. The research community has provided various models and detection...
This paper presents a new approach to predictive data analytics, called Radius of Neighbors (RN), and its mobile application, a multilingual RN-Chatter, devoted to improve communication among people, speaking different languages. RN is a modeless method of unsupervised machine learning, what makes it a fairly simple but effective way of analyzing big amounts of data while keeping acceptable speed...
The MoveUs project funded by the European Commission aims to foster sustainable eco-friendly mobility habits in cities. In this context predicting the traffic flow is useful for managers to optimize the configuration of the road network towards reducing the congestions and ultimately, the pollution. With the explosion of the so-called Big Data concept and its application to traffic data, a wide range...
Advancements in social media technology have resulted in the booming of massive public data. The availability of these huge data sets offers numerous research opportunities for deriving meaningful cause-effect relationships for many applications. One important application domain is the cause of side effects of drugs. In this paper, we applied supervised learning to extract useful cause-and-effect...
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