Binary convolutional neural networks (BCNN) have been proposed in the literature for resource-constrained IoTs nodes and mobile computing devices. Such computing platforms have strict constraints on the power budget, system performance, processing and memory capabilities. Nonetheless, the platforms are still required to efficiently perform classification and matching tasks needed in various applications. The memristor device has shown promising results when utilized for in-memory computing architectures, due to its ability to perform storage and computation using the same physical element

This paper introduces some generalized fundamentals for fractional-order RL β C α circuits as well as a gradient-based optimization technique in the frequency domain. One of the main advantages of the fractional-order design is that it increases the flexibility and degrees of freedom by means of the fractional parameters, which provide new fundamentals and can be used for better interpretation or best fit matching with experimental results. An analysis of the real and imaginary components, the magnitude and phase responses, and the sensitivity must be performed to obtain an optimal design

Infusion Stand is one of the medical supportive tools in the field of biomedical that assist in holding and carrying medications to patients via intravenous injections. Mobilization of Infusion Stand from a place to another place is necessary not only for the patients itself but also for the nurses. Therefore, this leads to not only uneasiness but also inconvenience for both parties. Therefore, to improve the existing situation and current Infusion Stand in the market, a proposal to design and implement a prototypic Robotic Infusion Stand is submitted. In this paper, 2-Degree of Freedom

Convolutional Neural Networks (CNNs) for Artificial Intelligence (AI) algorithms have been widely used in many applications especially for image recognition. However, the growth in CNN-based image recognition applications raised challenge in executing millions of Multiply and Accumulate (MAC) operations in the state-of-The-Art CNNs. Therefore, GPUs, FPGAs, and ASICs are the feasible solutions for balancing processing speed and power consumption. In this paper, we propose an efficient hardware architecture for CNN that provides high speed, low power, and small area targeting ASIC implementation

We have investigated different nonidealities in Cu2ZnSnSe4-CdS-ZnO solar cells with 9.7% conversion efficiency, in order to determine what is limiting the efficiency of these devices. Several nonidealities could be observed. A barrier of about 300 meV is present for electron flow at the absorber-buffer heterojunction leading to a strong crossover behavior between dark and illuminated current-voltage curves. In addition, a barrier of about 130 meV is present at the Mo-absorber contact, which could be reduced to 15 meV by inclusion of a TiN interlayer. Admittance spectroscopy results on the

Recently, emerging vehicular applications are increasing the demand of vehicles which form significant burdens on network backhaul and represents a cause to the quality of experience (QoE) decay of the vehicular users. Proactive caching is a promising technique to mitigate the load on core networks by caching some of the expected data items. This work proposes a hierarchical proactive caching scheme which jointly considers caching in vehicles and roadside units (RSUs). Minimization of the vehicle communication latency is the main objective of our study. The optimization problem is formulated

In this paper, we introduce a novel geographic routing with cooperation scheme for 5G Device-to-Device ad hoc networks. The prime focus of our scheme (coined Cooperative Routing for Reliable Paths (CRRP)) is to enhance the routing performance in cooperative communication networks in terms of the path length and reliability. In particular, it introduces novel algorithms for cooperative relay and forwarder selections, which strike the best balance between path length and achieved symbol error rate, compared to prior work in the literature. Moreover, it exhibits the flexibility of deciding

We consider a secondary user with energy harvesting capability. We design access schemes for the secondary user which incorporate random spectrum sensing and random access, and which make use of the primary automatic repeat request (ARQ) feedback. The sensing and access probabilities are obtained such that the secondary throughput is maximized under the constraints that both the primary and secondary queues are stable and that the primary queueing delay is kept lower than a specified value needed to guarantee a certain quality of service (QoS) for the primary user. We consider spectrum sensing

We consider a cognitive radio scenario with an energy harvesting secondary user (SU) attempting to access a primary channel randomly. We assume multipacket reception (MPR) capability and investigate a system in which the SU may or may not exploit the primary feedback messages. The access probabilities are obtained to maximize the secondary throughput under the constraints of primary queue stability and such that the primary queueing delay is kept below a specified value in order to guarantee a certain quality of service (QoS) for the primary user (PU). We investigate the impact of the energy

We show that the four parameters of a single-dispersion Cole-Cole bio-impedance model can be extracted from an one time-domain measurement with a fixed frequency. In particular, a periodic triangle waveform current excitation signal is injected into the biological sample under study while measuring the voltage developed across this sample in a galvanostatic measurement setup. The voltage response due to this triangle-wave excitation is firstly analytically derived in closed form. After that the Flower Pollination optimization Algorithm (FPA) is applied to extract the unknown model parameters