Sensor Actor NETworks (SANET) represent a major component of ubiquitous service environments promising interesting solutions to a wide range of problems. Despite the obvious increase in the research activities proposing architectures and protocols for SANETs, we are still no where near the production of industrial-grade SANET software that can be relied upon for mission critical applications. The cost of programming, deploying and maintaining SANET environments is still highly prohibitive due to the lack of industrial tools capable of realizing adaptive SANET software in a cost effective way

We consider a class of wireless powered devices employing hybrid automatic repeat request to ensure reliable end-to-end communications over a two-state time-varying channel. A receiver, with no power source, relies on the energy transferred by a simultaneous wireless information and power transfer enabled transmitter to receive and decode information. Under the two-state channel model, information is received at two different rates while it is only possible to harvest energy in one of the states. The receiver aims to decode its messages with minimum expected number of re-transmissions. Dynamic

In this paper, we propose a novel physical layer decoding technique for Device-to-Device Network Coded Cooperation (NCC) receivers in the Two Way Relay Channel (TWRC) scenario. The proposed technique is efficiently applicable either when Channel State Information (CSI) are available at the receiver or not. It first employs XOR arithmetic analog mapping to extract a distorted version of the intended signal from the network-coded signal received from the relay. The obtained signal is then combined with the direct signal received from the source, resulting in a higher SNR version of the intended

Convolutional codes are one of the Forward Error Correction (FEC) codes that are used in every robust digital communication system. Viterbi algorithm is employed in wireless communications to decode the convolutional codes. Such decoders are complex and dissipate large amount of power. Software Defined Radio (SDR) is realized using highly configurable hardware platforms. Field Programmable Gate Array technology (FPGA) is a highly configurable option for implementing many sophisticated signal processing tasks in SDR. In this paper, a generic, configurable and low power Viterbi decoder for

This work develops new achievable rate regions for the two way wiretap channel. In our setup, Alice and Bob wish to exchange messages securely in the presence of a passive eavesdropper Eve. In the full-duplex scenario, our achievability argument relies on allowing the two users to jointly optimize their channel prefixing distributions, such that the new channel conditions are favorable compared to that of Eve. Random binning and private key sharing over the channel are then used to exploit the secrecy advantage available in the equivalent cascade channel and to distribute the available secrecy

Monitoring light dose is essential in much clinical procedures like bio-stimulation, neuro-medicine and photodynamic therapy and in many biophotonics applications such as optogenetics and biosensing. However, monitoring the optical power dissipation as light travels in different layers of tissue is essential in determining the required optical dose. Each part in the human body is protected by different thickness of skin layer; therefore, studying the variations of the optical power when light propagates in different thicknesses of the human skin is essential for safe and accurate medical

Surface plasmon resonance (SPR) sensors are increasingly in demand due to their high sensitivity, better accuracy, and improved detection limit. Such performance parameters make these sensors suitable for biological and medical field’s applications. During the last decade, prism coupling-based SPR sensors had been a preferred choice among the designer and developers across the globe. This article summarizes a review of prism coupling-based SPR photonic sensors. Important performance characteristics of such sensors have also been studied with respect to their detection accuracy, sensitivity

A new approach to assess lean manufacturing based on system's variability is proposed. The assessment utilizes a new tool called variability source mapping (VSMII) which focuses on capturing and reducing variability across the production system. The new tool offers a new metric called variability index to measure the overall variability level of the system. Based on the mapping and the new metric, VSMII suggests a variability reduction plan guided by a recommendation list of both lean techniques as well as production control policies. An industrial application is used to demonstrate the new

It is feasible and safe to use unmanned aerial vehicle (UAV) as the data collection platform of the Internet of things (IoT). In order to save the energy loss of the platform and make the UAV perform the collection work effectively, it is necessary to optimize the deployment of UAV. The objective problem is to minimize the sum of the lost energy of UAV and the loss of data transmission of Internet of things devices. The key to solving the problem is to calculate the location of the docking points and the number of docking points when the UAV is working to collect data. This paper proposes a

This paper introduces a heuristic solver based on neural networks and deep learning for the knapsack problem. The solver is inspired by mechanisms and strategies used by both algorithmic solvers and humans. The neural model of the solver is based on introducing several biases in the architecture. We introduce a stored memory of vectors that holds up items representations and their relationship to the capacity of the knapsack and a module that allows the solver to access all the previous outputs it generated. The solver is trained and tested on synthetic datasets that represent a variety of