PLATOP: a novel planarized trench isolation and field oxideformation using poly-silicon

A novel isolation scheme named planarized trench isolation and field oxide formation using poly-silicon (PLATOP) Is described. PLATOP is applicable to high-performance submicron VLSI since it results in encroachment-free shallow trenches, and planarized field oxide. The process offers poly silicon-filled deep trenches. The process also relies on noncritical lithography and novel etch processes to planarize the deposited poly-silicon from the top of the active areas, and oxidation to consume the poly-silicon in the field regions. Electrical results are presented proving the viability of the isolation scheme     

The State of the Art of Piezo1 Channels in Skeletal Muscle Regeneration

Piezo1 channels are highly mechanically-activated cation channels that can sense and transduce the mechanical stimuli into physiological signals in different tissues including skeletal muscle. In this focused review, we summarize the emerging evidence of Piezo1 channel-mediated effects in the physiology of skeletal muscle, with a particular focus on the role of Piezo1 in controlling myogenic precursor activity and skeletal muscle regeneration and vascularization. The disclosed effects reported by pharmacological activation of Piezo1 channels with the selective agonist Yoda1 indicate a potential impact of Piezo1 channel activity in skeletal muscle regeneration, which is disrupted in various muscular pathological states. All findings reported so far agree with the idea that Piezo1 channels represent a novel, powerful molecular target to develop new therapeutic strategies for preventing or ameliorating skeletal muscle disorders characterized by an impairment of tissue regenerative potential.     

PriorVAE: encoding spatial priors with variational autoencoders for small-area estimation

Gaussian processes (GPs), implemented through multivariate Gaussian distributions for a finite collection of data, are the most popular approach in small-area spatial statistical modelling. In this context, they are used to encode correlation structures over space and can generalize well in interpolation tasks. Despite their flexibility, off-the-shelf GPs present serious computational challenges which limit their scalability and practical usefulness in applied settings. Here, we propose a novel, deep generative modelling approach to tackle this challenge, termed PriorVAE: for a particular spatial setting, we approximate a class of GP priors through prior sampling and subsequent fitting of a variational autoencoder (VAE). Given a trained VAE, the resultant decoder allows spatial inference to become incredibly efficient due to the low dimensional, independently distributed latent Gaussian space representation of the VAE. Once trained, inference using the VAE decoder replaces the GP within a Bayesian sampling framework. This approach provides tractable and easy-to-implement means of approximately encoding spatial priors and facilitates efficient statistical inference. We demonstrate the utility of our VAE two-stage approach on Bayesian, small-area estimation tasks.     

Towards a classification of energy aware MAC protocols for wireless sensor networks

Power management is an important issue in wireless sensor networks (WSNs) because wireless sensor nodes are usually battery powered, and an efficient use of the available battery power becomes an important concern specially for those applications where the system is expected to operate for long durations. This necessity for energy efficient operation of a WSN has prompted the development of new protocols in all layers of the communication stack. Provided that, the radio transceiver is the most power consuming component of a typical sensor node, large gains can be achieved at the link layer where the medium access control (MAC) protocol controls the usage of the radio transceiver unit. MAC protocols for sensor networks differ greatly from typical wireless networks access protocols in many issues. MAC protocols for sensor networks must have built‐in power conservation, mobility management, and failure recovery strategies. Furthermore, sensor MAC protocols should make performance trade‐off between latency and throughput for a reduction in energy consumption to maximize the lifetime of the network. This is in general achieved through duty cycling the radio transceiver. Many MAC protocols with different objectives were proposed for wireless sensor networks in the literature. Most of these protocols take into account the energy efficiency as a main objective. There is much more innovative work should be done at the MAC layer to address the hard unsolved problems. In this paper, we first outline and discuss the specific requirements and design trade‐offs of a typical wireless sensor MAC protocol by describing the properties of WSN that affect the design of MAC layer protocols. Then, a typical collection of wireless sensor MAC protocols presented in the literature are surveyed, classified, and described emphasizing their advantages and disadvantages whenever possible. Finally, we present research directions and identify open issues for future medium access research. Copyright © 2009 John Wiley & Sons, Ltd.     

A Distributed and Elastic Application Processing Model for Mobile Cloud Computing

The latest developments in mobile computing technology have increased the computing capabilities of smart mobile devices (SMDs). However, SMDs are still constrained by low bandwidth, processing potential, storage capacity, and battery lifetime. To overcome these problems, the rich resources and powerful computational cloud is tapped for enabling intensive applications on SMDs. In Mobile Cloud Computing (MCC), application processing services of computational clouds are leveraged for alleviating resource limitations in SMDs. The particular deficiency of distributed architecture and runtime partitioning of the elastic mobile application are the challenging aspects of current offloading models. To address these issues of traditional models for computational offloading in MCC, this paper proposes a novel distributed and elastic applications processing (DEAP) model for intensive applications in MCC. We present an analytical model to evaluate the proposed DEAP model, and test a prototype application in the real MCC environment to demonstrate the usefulness of DEAP model. Computational offloading using the DEAP model minimizes resources utilization on SMD in the distributed processing of intensive mobile applications. Evaluation indicates a reduction of 74.6% in the overhead of runtime application partitioning and a 66.6% reduction in the CPU utilization for the execution of the application on SMD.

     

Synthesizing Energy-Efficient Embedded Systems with LOPOCOS

In this paper, we introduce the LOPOCOS (Low Power Co-synthesis) system, a prototype CAD tool for system level co-design. LOPOCOS targets the design of energy-efficient embedded systems implemented as heterogeneous distributed architectures. In particular, it is designed to solve the specific problems involved in architectures that include dynamic voltage scalable (DVS) processors. The aim of this paper is to demonstrate how LOPOCOS can support the system designer in identifying energy-efficient hardware/software implementations for the desired embedded systems. Hence, highlighting the necessary optimization steps during design space exploration for DVS enable architectures. The optimization steps carried out in LOPOCOS involve component allocation and task/communication mapping as well as scheduling and dynamic voltage scaling. LOPOCOS has the following key features, which contribute to this energy efficiency. During the voltage scaling valuable power profile information of task execution is taken into account, hence, the accuracy of the energy estimation is improved. A combined optimization for scheduling and communication mapping based on genetic algorithm, optimizes simultaneously execution order and communication mapping towards the utilization of the DVS processors and timing behaviour. Furthermore, a separation of task and communication mapping allows a more effective implementation of both task and communication mapping optimizationsteps. Extensive experiments are conducted to demonstrate the efficiency of LOPOCOS. We report up to 38% higher energy reductions compared to previous co-synthesis techniques for DVS systems. The investigations include a real-life example of an optical flow detection algorithm.     

Exploring network-level performances of wireless nanonetworks utilizing gains of different types of nano-antennas with different materials

Wireless nanonetworks are not a simple extension of traditional communication networks at the nano-scale. Owing to being a completely new communication paradigm, existing research in this field is still at an embryonic stage. Furthermore, most of the existing studies focus on performance enhancement of nanonetworks via designing new channel models and routing protocols. However, the impacts of different types of nano-antennas on the network-level performances of the wireless nanonetworks remain still unexplored in the literature. Therefore, in this paper, we explore the impacts of different well-known types of antennas such as patch, dipole, and loop nano-antennas on the network-level performances of wireless nanonetworks. We also investigate the performances of nanonetworks for different types of traditional materials (e.g., copper) and for nanomaterials (e.g., carbon nanotubes and graphene). We perform rigorous simulation using our customized ns-2 simulation to evaluate the network-level performances of nanonetworks exploiting different types of nano-antennas using different materials. Our evaluation reveals a number of novel findings pertinent to finding an efficient nano-antenna from its several alternatives for enhancing network-level performances of nanonetworks. Our evaluation demonstrates that a dipole nano-antenna using copper material exhibits around 51% better throughput and about 33% better end-to-end delay compared to other alternatives for large-size nanonetworks. Furthermore, our results are expected to exhibit high impacts on the future design of wireless nanonetworks through facilitating the process of finding the suitable type of nano-antenna and suitable material for the nano-antennas.

     

An Enhanced Cooperative Communication Scheme for Physical Uplink Shared Channel in NB-IoT

Wireless Personal Communications - Smart Home is one of the most established applications of the Internet of Things. Almost every equipment we use in our daily life—appliances, electric...