An Effective Wireless Sensor Network Routing Protocol Based on Particle Swarm Optimization Algorithm

Improving wireless communication and artificial intelligence technologies by using Internet of Things (Itoh) paradigm has been contributed in developing a wide range of different applications. However, the exponential growth of smart phones and Internet of Things (IoT) devices in wireless sensor networks (WSNs) is becoming an emerging challenge that adds some limitations on Quality of Service (QoS) requirements. End-to-end latency, energy consumption, and packet loss during transmission are the main QoS requirements that could be affected by increasing the number of IoT applications connected through WSNs. To address these limitations, an effective routing protocol needs to be designed for boosting the performance of WSNs and QoS metrics. In this paper, an optimization approach using Particle Swarm Optimization (PSO) algorithm is proposed to develop a multipath protocol, called a Particle Swarm Optimization Routing Protocol (MPSORP). The MPSORP is used for WSN-based IoT applications with a large volume of traffic loads and unfairness in network flow. For evaluating the developed protocol, an experiment is conducted using NS-2 simulator with different configurations and parameters. Furthermore, the performance of MPSORP is compared with AODV and DSDV routing protocols. The experimental results of this comparison demonstrated that the proposed approach achieves several advantages such as saving energy, low end-to-end delay, high packet delivery ratio, high throughput, and low normalization load.publishedVersio

Intelligent Malaysian Sign Language Translation System Using Convolutional-Based Attention Module with Residual Network

(e deaf-mutes population always feels helpless when they are not understood by others and vice versa. (is is a big humanitarian problem and needs localised solution. To solve this problem, this study implements a convolutional neural network (CNN), convolutional-based attention module (CBAM) to recognise Malaysian Sign Language (MSL) from images. Two different experiments were conducted for MSL signs, using CBAM-2DResNet (2-Dimensional Residual Network) implementing “Within Blocks” and “Before Classifier” methods. Various metrics such as the accuracy, loss, precision, recall, F1-score, confusion matrix, and training time are recorded to evaluate the models’ efficiency. (e experimental results showed that CBAM-ResNet models achieved a good performance in MSL signs recognition tasks, with accuracy rates of over 90% through a little of variations. (e CBAM-ResNet “Before Classifier” models are more efficient than “Within Blocks” CBAM-ResNet models. (us, the best trained model of CBAM-2DResNet is chosen to develop a real-time sign recognition system for translating from sign language to text and from text to sign language in an easy way of communication between deaf-mutes and other people. All experiment results indicated that the “Before Classifier” of CBAMResNet models is more efficient in recognising MSL and it is worth for future research

Accuracy of seizure semiology obtained from first-time seizure witnesses

Abstract Background Little is known of how accurately a first-time seizure witness can provide reliable details of a semiology. Our goal was to determine how accurately first-time seizure witnesses could identify key elements of an epileptic event that would aid the clinician in diagnosing a seizure. Methods A total of 172 participants over 17 years of age, with a mean (sd) of 33.12 (13.2) years and 49.4% female, composed of two groups of community dwelling volunteers, were shown two different seizure videos; one with a focal seizure that generalized (GSV), and the other with a partial seizure that did not generalize (PSV). Participants were first asked about what they thought was the event that had occurred. They then went through a history-taking scenario by an assessor using a battery of pre-determined questions about involvement of major regions: the head, eyes, mouth, upper limbs, lower limbs, or change in consciousness. Further details were then sought about direction of movement in the eyes, upper and lower limbs, the side of limb movements and the type of movements in the upper and lower limbs. Analysis was with descriptive statistics and logistic regression. Results One hundred twenty-two (71.4%) identified the events as seizure or epilepsy. The accuracy of identifying major areas of involvement ranged from 60 to 89.5%. Horizontal head movements were significantly more recognized in the PSV, while involvement of the eyes, lateralization of arm movement, type of left arm movement, leg involvement, and lateralization of leg movement were significantly more recognized in the GSV. Those shown the GSV were more likely to recognize the event as "seizure" or "epilepsy" than those shown the PSV; 78 (84.8%) vs 44 (55.7%), (OR 0.22, p < 0.0001). Younger age was also associated with correct recognition (OR 0.96, P 0.049). False positive responses ranged from 2.5 to 32.5%. Conclusion First-time witnesses can identify important elements more than by chance alone, and are more likely to associate generalized semiologies with seizures or epilepsy than partial semiologies. However, clinicians still need to navigate the witness’s account carefully for additional information since routine questioning could result in a misleading false positive answer

A universal transfer route for graphene

Often synthetic graphene requires transfer onto an arbitrary substrate prior to use because the substrate it was originally synthesized on is inappropriate for either electrical measurement or characterization. While a variety of routes have been developed they are substrate dependant and often involve the use of harsh treatments. Here we present a facile and cheap route that can be applied to graphene over any substrate. This universal transfer route is based on a wet chemical reaction producing gaseous species which can intercalate between the substrate and the graphene and thus gently delaminate the two

An Effective Wireless Sensor Network Routing Protocol Based on Particle Swarm Optimization Algorithm

Improving wireless communication and artificial intelligence technologies by using Internet of Things (Itoh) paradigm has been contributed in developing a wide range of different applications. However, the exponential growth of smart phones and Internet of Things (IoT) devices in wireless sensor networks (WSNs) is becoming an emerging challenge that adds some limitations on Quality of Service (QoS) requirements. End-to-end latency, energy consumption, and packet loss during transmission are the main QoS requirements that could be affected by increasing the number of IoT applications connected through WSNs. To address these limitations, an effective routing protocol needs to be designed for boosting the performance of WSNs and QoS metrics. In this paper, an optimization approach using Particle Swarm Optimization (PSO) algorithm is proposed to develop a multipath protocol, called a Particle Swarm Optimization Routing Protocol (MPSORP). The MPSORP is used for WSN-based IoT applications with a large volume of traffic loads and unfairness in network flow. For evaluating the developed protocol, an experiment is conducted using NS-2 simulator with different configurations and parameters. Furthermore, the performance of MPSORP is compared with AODV and DSDV routing protocols. The experimental results of this comparison demonstrated that the proposed approach achieves several advantages such as saving energy, low end-to-end delay, high packet delivery ratio, high throughput, and low normalization load

In Vitro and Ex Vivo Evaluation of Fluocinolone Acetonide&ndash;Acitretin-Coloaded Nanostructured Lipid Carriers for Topical Treatment of Psoriasis

Psoriasis is chronic autoimmune disease that affects 2&ndash;5% of the global population. Fluocinolone acetonide (FLU) and acitretin (ACT) are widely used antipsoriatic drugs that belong to BCS classes II and IV, respectively. FLU exhibits side effects, such as skin irritation and a burning sensation. ACT also shows adverse effects, such as gingivitis, teratogenic effects and xerophthalmia. In the present study, topical nanostructured lipid carriers (NLCs) were fabricated to reduce the side effects and enhance the therapeutic efficacy. FLU&ndash;ACT-coloaded NLCs were prepared by the modified microemulsion method and optimized by the Box&ndash;Behnken model of Design Expert&reg; version 12. The optimization was based on the particle size (PS), zeta potential (ZP) and percentage of encapsulation efficiency (%EE). The physicochemical analyses were performed by TEM, FTIR, XRD and DSC to assess the morphology, chemical interactions between excipients, crystallinity and thermal behavior of the optimized FLU&ndash;ACT-coloaded NLCs. The FLU&ndash;ACT-coloaded NLCs were successfully loaded into gel and characterized appropriately. The dialysis bag method and Franz diffusion cells were used for the in vitro release and ex vivo permeation studies, respectively. The optimized FLU&ndash;ACT-coloaded NLCs had the desired particle size of 288.2 &plusmn; 2.3 nm, ZP of &minus;34.2 &plusmn; 1.0 mV and %EE values of 81.6 &plusmn; 1.1% for ACT and 75 &plusmn; 1.3% for FLU. The TEM results confirmed the spherical morphology, while the FTIR results showed the absence of chemical interactions of any type among the ingredients of the FLU&ndash;ACT-coloaded NLCs. The XRD and DSC analyses confirmed the amorphous nature and thermal behavior. The in vitro study showed the sustained release of the FLU and ACT from the optimized FLU&ndash;ACT-coloaded NLCs and FLU&ndash;ACT-coloaded NLC gel compared with the FLU&ndash;ACT suspension and conventional gel. The ex vivo study confirmed the minimal permeation of both drugs from the FLU&ndash;ACT-coloaded NLC gel

Chemical Vapor Deposition Growth of Large Single-Crystal Mono‑, Bi‑, Tri-Layer Hexagonal Boron Nitride and Their Interlayer Stacking

Two-dimensional hexagonal boron nitride (h-BN) is a wide bandgap material which has promising mechanical and optical properties. Here we report the realization of an initial nucleation density of h-BN <1 per mm² using low-pressure chemical vapor deposition (CVD) on polycrystalline copper. This enabled wafer-scale CVD growth of single-crystal monolayer h-BN with a lateral size up to ∼300 μm, bilayer h-BN with a lateral size up to ∼60 μm, and trilayer h-BN with a lateral size up to ∼35 μm. Based on the large single-crystal monolayer h-BN domain, the sizes of the as-grown bi- and trilayer h-BN grains are 2 orders of magnitude larger than typical h-BN multilayer domains. In addition, we achieved coalesced h-BN films with an average grain size ∼100 μm. Various flake morphologies and their interlayer stacking configurations of bi- and trilayer h-BN domains were studied. Raman signatures of mono- and multilayer h-BN were investigated side by side in the same film. It was found that the Raman peak intensity can be used as a marker for the number of layers

Bandgap engineering of two-dimensional semiconductor materials

© 2020 Springer Nature Limited Semiconductors are the basis of many vital technologies such as electronics, computing, communications, optoelectronics, and sensing. Modern semiconductor technology can trace its origins to the invention of the point contact transistor in 1947. This demonstration paved the way for the development of discrete and integrated semiconductor devices and circuits that has helped to build a modern society where semiconductors are ubiquitous components of everyday life. A key property that determines the semiconductor electrical and optical properties is the bandgap. Beyond graphene, recently discovered two-dimensional (2D) materials possess semiconducting bandgaps ranging from the terahertz and mid-infrared in bilayer graphene and black phosphorus, visible in transition metal dichalcogenides, to the ultraviolet in hexagonal boron nitride. In particular, these 2D materials were demonstrated to exhibit highly tunable bandgaps, achieved via the control of layers number, heterostructuring, strain engineering, chemical doping, alloying, intercalation, substrate engineering, as well as an external electric field. We provide a review of the basic physical principles of these various techniques on the engineering of quasi-particle and optical bandgaps, their bandgap tunability, potentials and limitations in practical realization in future 2D device technologies.11Nsciescopu

Bandgap engineering of two-dimensional semiconductor materials

© 2020 Springer Nature Limited Semiconductors are the basis of many vital technologies such as electronics, computing, communications, optoelectronics, and sensing. Modern semiconductor technology can trace its origins to the invention of the point contact transistor in 1947. This demonstration paved the way for the development of discrete and integrated semiconductor devices and circuits that has helped to build a modern society where semiconductors are ubiquitous components of everyday life. A key property that determines the semiconductor electrical and optical properties is the bandgap. Beyond graphene, recently discovered two-dimensional (2D) materials possess semiconducting bandgaps ranging from the terahertz and mid-infrared in bilayer graphene and black phosphorus, visible in transition metal dichalcogenides, to the ultraviolet in hexagonal boron nitride. In particular, these 2D materials were demonstrated to exhibit highly tunable bandgaps, achieved via the control of layers number, heterostructuring, strain engineering, chemical doping, alloying, intercalation, substrate engineering, as well as an external electric field. We provide a review of the basic physical principles of these various techniques on the engineering of quasi-particle and optical bandgaps, their bandgap tunability, potentials and limitations in practical realization in future 2D device technologies.11Nsciescopu