This paper is a step towards ‘green telecom tower’ by eliminating the diesel generator from telecom power supply. The fuel cell based power supply has been proposed for telecom towers in remote and rural areas. The challenge of meeting the prerequisite of telecom power supply which are reliability and regulated DC distribution bus voltage in the environment of fuel cell is addressed by proposing the

A novel deep learning framework is proposed for lesion segmentation and classification. The proposed technique incorporates two primary phases. For lesion segmentation, Mask recurrent convolutional neural network (MASK R-CNN) based architecture is implemented. In this architecture, Resnet50 along with feature pyramid network (FPN) is utilized as a backbone. Later, fully connected layer-based features

The recognition of breast abnormality, which mainly consists of mass and micro-calcification, plays a critical role in the detection of breast cancer. To facilitate the procedure of making decisions on suspicious regions in mammograms, we proposed a light-weighted deep convolutional neural network (CNN) recognition system termed DisepNet, a light-weighted fully convolutional network that shows promising

In this work, we propose a deep learning framework for the classification of COVID-19 pneumonia infection from normal chest CT scans. In this regard, a 15-layered convolutional neural network architecture is developed which extracts deep features from the selected image samples – collected from the Radiopeadia. Deep features are collected from two different layers, global average pool and fully connected

Instance selection is an important problem in medical data mining. It focuses on selecting representative data samples from a given training set, whereas unrepresentative (or noisy) data samples are filtered out. This reduces the size of the training set, which then requires less storage space. In addition, when the instance selection algorithm was carefully chosen, a reduction in the training set

It is very important to obtain smooth power and limit over-currents in grid-connected doubly fed induction generator (DFIG)-based wind turbines. Therefore, the rotor resistance unit can be used for power and over-currents control in DFIG. However, it may be insufficient to reduce oscillations in large power systems. This study aims to develop a new rotor resistance unit for low voltage ride through

Evaluating the reliability of component-based software systems from their architecture is of great importance. This paper proposes metrics to assess the reliability of software systems considering the self-healing effect of components on software reliability. A self-healing component when being broken, heals itself with a probability and returns to normal conditions. Because designing a self-healing

Many traders participate in activities known as "day-trading", trading Bitcoin against the dollar bill as the United States Dollar (USD) on very short timeframes to squeeze out profits from small market fluctuations. This paper aims to help traders decide how to best act by creating a model that can predict price movement's direction for the next 5-min time frame. Several machine-learning models have

The consumption data from smart meters and complex questionnaires reveals the electricity consumers’ willingness to adapt their lifestyle to reduce or change their behaviour in electricity usage to flatten the peak in electricity consumption and release the stress in the power grid. Thus, the electricity consumption can support the enforcement of tariff and demand response strategies. Although the

Given the importance of reducing energy consumption and the challenge of heat generation in classic CMOS circuits, adiabatic circuits are believed as an appropriate alternative. Most of the adiabatic circuit families come with a dual-rail structure, which provides them with an inherent hardware redundancy. Although this redundancy could be used for improving their reliability, no studies have been

The time-current curve type and the considered fault locations influence the optimal coordination of directional overcurrent protections. It is shown that curve type can determine the feasibility of having solutions and the feasibility of obtaining reasonably low trip times. It is also shown that constraints for faults near to the main relay location must be complemented with those of other fault locations

This article presents a novel fractional order proportional–integral–derivative (FOPID) controller with fractional filter for an automatic voltage regulator (AVR) system. The proposed controller has seven independent parameters to be set. These parameters are optimally tuned by using sine–cosine algorithm (SCA) capable of balancing exploration and exploitation phases to find the optimal solution. The

The conventional bypass diodes used in solar photo-voltaic panel have side-effects of forward voltage drop, reduction in efficiency and a few operational problems under partial shading condition. In this work, this bypass diode is replaced by an electromagnetic relay through an efficient alternative approach that consumes less power and offers higher efficiency under partial shading condition of solar

The malware detection methods are classified into two categories, namely, dynamic analysis (active analysis) and static analysis (passive analysis). These methods undergo unusual obstruction, and challenges that are process complexity, limitation over detection accuracy. The static method serves to discover malicious applications using various parameters like permission analysis, signature verification

Low power multiplier unit design is one of Digital Signal Processing (DSP) processors’ requirements to meet the growing demands. Though the higher radix Booth multiplier shows the marginal decrease in the power, the generation of hard multiples in the generation unit becomes the bottleneck in implementing the multiplier unit. This paper proposes an energy-efficient radix-16 Booth multiplier design

This paper presents an extensive simulation-based and experimental validation of One-Cycle Control (OCC) over a nine-level power inverter using Cyclone III FPGA from Intel. OCC is a technique that exploits the nonlinear nature of multilevel power converters to overcome issues such as fast dynamic response, robustness and perturbations on either the source or the load side. Simulations performed in

This paper presents a non-linear model to simulate and predict the spreading of the newly discovered disease caused by a new series of a Novel Coronavirus (COVID-19). The mathematical modeling in this study is based on the Susceptible Infected Recovery (SIR) model, where key controlling parameters are considered, namely: human contact factor b, transmit factor (a), health medication factor (m) and

Network function virtualization promises a significant advantage for addressing diverse quality of service requirements via chains of Virtual Network Functions (VNFs). Service Function Chain (SFC) mapping, composed of placing VNF in the physical network and routing traffic through them, is the key problem to meet the requirements. In the recent mission-critical applications, delay guarantee and fault