Autonomous Traffic Signal Control using Decision Tree

The objective of this paper is to introduce an effective and efficient way of traffic signal light control to optimize the traffic signal duration across each lanes and thereby, to minimize or completely eliminate traffic congestion. This paper introduces a new approach to resolve the traffic congestion problem at junctions by making use of decision trees. The vehicle count in the real time traffic video is determined by Image Processing technique. This information is fed to the decision tree based on which the decision is made regarding the status of traffic signal lights of each lane at the junction at any given instant of time

Performance Analysis of Mesh-based NoC’s on Routing Algorithms

The advent of System-on-Chip (SoCs), has brought about a need to increase the scale of multi-core chip networks. Bus Based communications have proved to be limited in terms of performance and ease of scalability, the solution to both bus – based and Point-to-Point (P2P) communication systems is to use a communication infrastructure called Network-on-Chip (NoC). Performance of NoC depends on various factors such as network topology, routing strategy and switching technique and traffic patterns. In this paper, we have taken the initiative to compile together a comparative analysis of different Network on Chip infrastructures based on the classification of routing algorithm, switching technique, and traffic patterns. The goal is to show how varied combinations of the three factors perform differently based on the size of the mesh network, using NOXIM, an open source SystemC Simulator of mesh-based NoC. The analysis has shown tenable evidence highlighting the novelty of XY routing algorithm

Multimodality in Online Education: A Comparative Study

The commencement of the decade brought along with it a grave pandemic and in response the movement of education forums predominantly into the online world. With a surge in the usage of online video conferencing platforms and tools to better gauge student understanding, there needs to be a mechanism to assess whether instructors can grasp the extent to which students understand the subject and their response to the educational stimuli. The current systems consider only a single cue with a lack of focus in the educational domain. Thus, there is a necessity for the measurement of an all-encompassing holistic overview of the students' reaction to the subject matter. This paper highlights the need for a multimodal approach to affect recognition and its deployment in the online classroom while considering four cues, posture and gesture, facial, eye tracking and verbal recognition. It compares the various machine learning models available for each cue and provides the most suitable approach given the available dataset and parameters of classroom footage. A multimodal approach derived from weighted majority voting is proposed by combining the most fitting models from this analysis of individual cues based on accuracy, ease of procuring data corpus, sensitivity and any major drawbacks

Continuously infusing hyperpolarized 129Xe into flowing aqueous solutions using hydrophobic gas exchange membranes.

Hyperpolarized (HP) (129)Xe yields high signal intensities in nuclear magnetic resonance (NMR) and, through its large chemical shift range of approximately 300 ppm, provides detailed information about the local chemical environment. To exploit these properties in aqueous solutions and living tissues requires the development of methods for efficiently dissolving HP (129)Xe over an extended time period. To this end, we have used commercially available gas exchange modules to continuously infuse concentrated HP (129)Xe into flowing liquids, including rat whole blood, for periods as long as one hour and have demonstrated the feasibility of dissolved-phase MR imaging with submillimeter resolution within minutes. These modules, which exchange gases using hydrophobic microporous polymer membranes, are compatible with a variety of liquids and are suitable for infusing HP (129)Xe into the bloodstream in vivo. Additionally, we have developed a detailed mathematical model of the infused HP (129)Xe signal dynamics that should be useful in designing improved infusion systems that yield even higher dissolved HP (129)Xe signal intensities