Agreement is a crucial component of many distributed systems. It is the feature that is at the center of critical algorithms that provide consensus, election, and failure detection, among others. Intuitively, agreement between processes is possible only in the presence of uninterrupted or well ordered operations. One such powerful primitive is atomic, or ‘total order,’ broadcast. The way in whi...

This project aims to build an accurate, smallfootprint, low-latency Speech Command Recognition system that is capable of detecting predefined keywords. Using the Speech Commands Dataset provided by Google’s TensorFlow and AIY teams, we have implemented different architectures using different machine learning algorithms. Our models include: Vanilla Single-Layer softmax model, Deep Neural Network...

Detecting intrusion in network traffic has remained a problematic task for years. Progress the field of machine learning is paving way enhancing detection systems. Due to this progress become an integral part security. Intrusion achieved high accuracy with help supervised methods. A key factor performance classifiers how data augmented training classification model. Data real-world networks or ...

neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...

This paper reports experiments conducted to classify single channel Surface Electromyogram recorded from the forearm with the flexion and extension of the different fingers. Controlled experiments were conducted where single channel SEMF was recorded from the flexor digitorum superficialis muscle for various finger positions from the volunteers. A modified wavelet network called Thresholding Wa...

With the evolvement of fMRI’s, a great amount of attention has been given to classifying cognitive states of human beings. Several machine learning approaches have been used to train single-subject classifiers to do so. We present a different method using a neural network and a RBF SVM to train one classifier across all subjects. For the single-subject classifier case, we experiment with PCA as...

Optimizing multiple co-located networks, each with a variable number of network functionalities that influence each other, is a complex problem that has not yet received a lot of attention in the research community. However, since independent co-located networks increasingly influence each other, optimization solutions can no longer afford to look only at the performance of a single network. To...

Parallel processing is an area of growing interest to the computer science and engineering communities. This paper is an introduction to some of the concepts involved in the design and use of large-scale parallel systems. Parallel machines that are classified as SIMD (synchronous) and MIMD (asynchronous) systems, composed of a large number of microprocessors, are explored. Parallel algorithms a...

Checkpointing in a homogeneous environment, where both checkpointing and recovery are performed on the same type of machine and operating system, has been studied extensively. As heterogeneous distributed systems become pervasive, it is desirable to extend the capability of checkpointing to non-homogeneous environments. This paper describes a prototype, PREACHES, that achieves portable checkpoi...