In this paper, we present a new hybrid binary version of bat and enhanced particle swarm optimization algorithm in order to solve feature selection problems. The proposed is called Hybrid Binary Bat Enhanced Particle Swarm Optimization Algorithm (HBBEPSO). the HBBEPSO algorithm, combine with its capacity for echolocation helping explore space ability converge best global solution search space. investigate general performance compared original optimizers other that have been used past. A set...

We propose a wideband spectrum sensing technique to detect and localize wireless radio frequency (RF) signals of interest in time when uninteresting cause RF interference (RFI). Specifically, we adopt downscale the existing Faster-RCNN (FRCNN) framework achieve better signal detection localization than state-of-the-art. For experimental evaluation, present data generation for Wi-Fi as Bluetooth microwave oven RFI. Experiments reveal that (i) downscaled FRCNN model can up mean average...

Instance Space Analysis is a methodology to evaluate algorithm performance across diverse problem fields. Through visualisation and exploratory data analysis techniques, offers objective, data-driven insights into the diversity of test instances, behaviour, strengths weaknesses. As such, it supports automated selection synthetic instance generation, increasing testing reliability in optimisation, machine learning, scheduling This paper introduces instancespace, Python package that implements...

In this paper, we present a new hybrid binary version of dragonfly and enhanced particle swarm optimization algorithm in order to solve feature selection problems. The proposed is called Hybrid Binary Dragonfly Enhanced Particle Swarm Optimization Algorithm(HBDESPO). the HBDESPO algorithm, combine with its ability encourage diverse solutions formation static swarms exploiting data converge best global solution search space. investigate general performance compared original optimizers other...

Hybrid precoding, a combination of digital and analog is an alternative to traditional precoding methods in massive MIMO systems with large number antenna elements has shown promising results recently. In this paper, we implement parallel framework make hybrid competitive fast-fading environments. A low-complexity algorithm which exploits the block diagonal phase-only nature precoder partially connected structure proposed arrive at solution for multi-carrier single-user system using...

Despite the availability of chromatin conformation capture experiments, discerning relationship between 1D genome and 3D remains a challenge, which limits our understanding their affect on gene expression disease. We propose Hi-C-LSTM, method that produces low-dimensional latent representations summarize intra-chromosomal Hi-C contacts via recurrent long short-term memory neural network model. find these contain all information needed to recreate observed matrix with high accuracy,...

Wireless Sensor Networks (WSN) nowadays are typically utilized for carrying out remote monitoring tasks, while Mobile Network (MWSN) on the other hand, grants flexibility that sensor nodes could relocate in terms of environmental changes, sampling efficiency and energy conservation, etc. The network coverage problem region interest (ROI) hence becomes one critical issues draws intensive attention to researchers. This paper presents a novel approach maximizing lifetime WSN, guaranteeing...

Parking could become a nightmare on busy day, in city like Delhi (India), which has about 7.35 million cars, as per MORTH Barclays Research (2012). An average of seventeen minutes and considerable amount fuel is wasted an effort to find parking spot every time. Additional stress induced due hassles starting from finding empty relocating the car later. We propose system leveraging latest technologies that will help motorists overcome their problems at same time, make managing space easier...

In this paper, we propose a blind timefrequency localization method for wireless signals present in wideband radio frequency (RF) spectrum. The signal detection problem is transformed into an object by converting the RF time-series captures spectrogram images. A deep learning system based on Faster RCNN [2] then configured to suit task. Guidelines are provided make design choices terms of both data pre-processing and FRCNN modeling, example, Short Time Fourier Transform (STFT) parameters,...

In this paper, a new hybrid binary version of Genetic algorithm (GA) and enhanced particle swarm optimization (PSO) is presented in order to solve feature selection (FS) problem. The proposed called Hybrid Binary Enhanced PSO Algorithm (HBGEPSO). the HBGEP SO algorithm, GA combined with its capacity for exploration data through crossover mutation ability converge best global solution search space. investigate general performance HBGEPSO compared original optimizers other that have been used...

Abstract The availability of thousands assays epigenetic activity necessitates compressed representations these data sets that summarize the landscape genome. Until recently, most such were celltype specific, applying to a single tissue or cell state. Recently, neural networks have made it possible across tissues produce pan-celltype representation. In this work, we propose Epi-LSTM, deep long short-term memory (LSTM) recurrent network autoencoder capture long-term dependencies in epigenomic...

The availability of thousands assays epigenetic activity necessitates compressed representations these data sets that summarize the landscape genome. Until recently, most such were cell type-specific, applying to a single tissue or state. Recently, neural networks have made it possible across tissues produce pan-cell type representation. In this work, we propose Epi-LSTM, deep long short-term memory (LSTM) recurrent network autoencoder capture long-term dependencies in epigenomic data....

Abstract Despite the availability of chromatin conformation capture experiments, discerning relationship between 1D genome and 3D remains a challenge, which limits our understanding their affect on gene expression disease. We propose Hi-C-LSTM, method that produces low-dimensional latent representations summarize intra-chromosomal Hi-C contacts via recurrent long short-term memory (LSTM) neural network model. find these contain all information needed to recreate original matrix with high...

Abstract Despite the availability of chromatin conformation capture experiments, understanding relationship between regulatory elements and remains a challenge. We propose Hi-C-LSTM, method that produces low-dimensional latent representations summarize intra-chromosomal Hi-C contacts via recurrent long short-term memory (LSTM) neural network model. find these contain all information needed to recreate original matrix with high accuracy, outperforming existing methods. These enable...