Reducing web latency with coding-based fast multi-path loss recovery

Wireless Networks - TCP latency is critical to the performance of Web services. However, packet loss greatly impairs the TCP performance due to its poor loss recovery mechanisms. Recent work FUSO...     

Novel Collision Detection and Avoidance System for Midvehicle Using Offset-Based Curvilinear Motion

In recent days, the manufacture of automotive vehicles is dramatically enhanced worldwide. Most vehicle crashes are due to the drive distraction on the real highway roads and traffic-density. In this proposed method, a novel collision detection and avoidance algorithm are coined for Midvehicle Collision Detection and Avoidance System (MCDAS), addressing two scenarios, namely, (a) A rear-end collision avoidance with host vehicle under no front-end vehicle condition and (b) offset-based curvilinear motion under critical conditions, while, suitable parallel parking manoeuvring also addressed using offset-based curvilinear motion. The Monte Carlo analysis of the proposed MCDAS is demonstrated using the Constant Velocity (CV) manoeuvring strategy and simulated with real-time data using the NGSIM database.

     

An Adaptive Neuro-Fuzzy Inference System and Black Widow Optimization Approach for Optimal Resource Utilization and Task Scheduling in a Cloud Environment

Wireless Personal Communications - With the enhancing demand of the cloud computing products, task scheduling issue has become the hot study topic in this area. The task scheduling issue of the...     

The P-graph approach for systematic synthesis of wastewater treatment networks

Wastewater treatment consists of three or four sequential stages: preliminary, primary, secondary, and tertiary. Each stage can comprise multiple alternative technologies that can perform the same tasks with different efficiencies, operating times, and costs. Thus, we propose a systematic approach for designing wastewater treatment networks by utilizing principles of mathematical modeling and generating an exhaustive enumeration of all the possible technologies and their connections during the early stages of designing a treatment facility. Some of these structures are nonintuitive and include recycling, reprocessing, bypasses, and multiple technologies in parallel or series to remove the same contaminant. The nonintuitive structures with multiple technologies may provide a measure of resilience compared to typical heuristic designs. Thus, the combination of P-graph methodology and the sequence of treatment technologies predicted via the optimization algorithm from the maximal structure is based on holistic considerations and does not lead to suboptimal solutions.     

Optimized Path and Reduced Rule Caching Cost for Software Defined Network (SDN) Based Internet of Things (IOT)

Wireless Personal Communications - 2In Software Defined Network based Internet of Things (SDN-IoT), the path selected for forwarding the packets as per rules, should be Quality of Service (QoS)...     

Micro-expression recognition from local facial regions

MiE is a facial involuntary reaction that reflects the real emotion and thoughts of a human being. It is very difficult for a normal human to detect a Micro-Expression (MiE), since it is a very fast and local face reaction with low intensity. As a consequence, it is a challenging task for researchers to build an automatic system for MiE recognition. Previous works for MiE recognition have attempted to use the whole face, yet a facial MiE appears in a small region of the face, which makes the extraction of relevant features a hard task. In this paper, we propose a novel deep learning approach that leverages the locality aspect of MiEs by learning spatio-temporal features from local facial regions using a composite architecture of Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). The proposed solution succeeds to extract relevant local features for MiEs recognition. Experimental results on benchmark datasets demonstrate the highest recognition accuracy of our solution with respect to state-of-the-art methods.     

Influencer-defaulter mutation-based optimization algorithms for predicting electricity prices

Efficient electricity price forecasting plays a significant role in our society. In this paper, a novel influencer-defaulter mutation (IDM) mutation operator has been proposed. The IDM operator has been combined with six well-known optimization algorithms to create mutated optimization algorithms whose performance has been tested on twenty-four standard benchmark functions. Further, the artificial neural network is integrated with mutated optimization algorithms to solve the electricity price prediction problem. The policymakers can identify appropriate variables based on the predicted prices to help future market planning. The statistical results prove the efficacy of the IDM operator on the recent optimization algorithms.     

Temperature dependent negative permittivity in solid solutions Sr2Mn1-xSnxO4 (x = 0, 0.3, 0.5)

A few compositions of the system Sr₂Mn_1-xSn_xO₄ (x = 0.0, 0.3, 0.5) were synthesized in the air by the solid-state ceramic route. A change in the sign (positive to negative) of the permittivity above a particular temperature (T_C) is observed at all the measured frequencies. The negative permittivity was analyzed by the Drude-Lorentz model. It was found that negative permittivity is caused by the plasma oscillations of thermally excited free charge carriers. Analysis of XPS spectra confirmed the presence of mixed-valence states of both Mn (Mn⁴⁺ and Mn³⁺) and Sn (Sn⁴⁺ and Sn²⁺) ions. The UV–vis.-IR spectroscopy results indicated generation of a large number of defect states in the forbidden bandgap region of Sr₂MnO₄ on the substitution of Sn at Mn site. Synthesized samples are promising metamaterials for radio frequency (10 Hz -2 MHz) region applications due to the high-temperature plasmonic behavior.     

A novel solution of deep learning for endoscopic ultrasound image segmentation: enhanced computer aided diagnosis of gastrointestinal stromal tumor

Multimedia Tools and Applications - Gastrointestinal stromal tumor is one of the critical tumors that doctors do not suggest to get frequent endoscopy, so there is a need for a diagnosis system...