Multicriteria Stochastic Shortest Path Problem for Electric Vehicles

This paper formulates the reliable routing of electric vehicles in stochastic networks as a multicriteria shortest path problem with travel time and charging cost components. The reliability term is defined as the probability of finishing the trip without running out of charge. The arc travel times are represented as stochastic variables, and arc energy consumption is modeled as a linear function of arc length and arc travel time. The traveler aims to minimize the generalized cost, formulated as a linear function of travel time and charging cost, subject to a minimum reliability threshold, representing the level of risk a traveler is willing to take in favor of routes with lower cost. We propose a solution algorithm based on generalized dynamic programming and show that the optimal solution may include cycles that visit at least one charging station. The properties of the proposed multicriteria shortest path problem are mathematically proved. The simulation results on randomly-generated networks show that cyclic paths are very rare, and that the generalized cost of travel is a monotone increasing function of minimum reliability threshold.     

Robust manufacturing line design with controlled moderate robustness in bottleneck buffer time to manage stochastic inter-task times

Task time variations in a manufacturing line can result in a longer time to complete tasks than a given cycle time, leading to line stoppage and loss of production time. In practice, a portion of the cycle time is often allocated as a predefined fixed-size buffer time, determined based on experience, to account for such uncertain variations for a paced line without storage-buffers between stations. However, the size of the required buffer time in each station depends on the variation levels of task times and the desired conservatism level for preventing cycle time violation. In addition, there are uncertainties in other non-value adding activity times in stations, known as inter-task times. Although many studies on stochastic manufacturing line design focused on minimizing the cost incurred when the cycle time is exceeded due to task time variations, they mostly disregarded the inter-task times. Furthermore, it is worth studying the simultaneous effect of the manufacturing time uncertainty level and that of the conservatism level on the cycle time. This paper proposes a new method for moderately robust manufacturing line design that incorporates the conservatism level and uncertainties in the task and inter-task times. A new interpretation of the non-productive times in stations is presented by introducing the concept of the α-fractal buffer time to manage the effect of manufacturing time uncertainties. To overcome the problem of excessive robustness, a moderate robust approach with conservatism-level flexibility is used, focusing on the cycle time in the bottleneck station. The effect of the uncertainties and conservatism levels on the cycle time is analyzed through numerical examples. This study can be used for improving a manufacturing system in which uncertainties in tasks and inter-task times significantly degrade its productivity.     

Neural network-based approaches, solving haplotype reconstruction in MEC and MEC/GI models

Single nucleotide polymorphism (SNP) in human genomes is considered to be highly associated with complex genetic diseases. As a consequence, obtaining all SNPs from human populations is one of the primary goals of recent studies on human genomics. The two sequences of SNPs in diploid human organisms are called haplotypes. In this paper, the problem of haplotype reconstruction from SNP fragments with and without genotype information is studied. Minimum error correction (MEC) is an important model for this problem but only effective when the error rate of the fragments is low. MEC/GI, as an extension to MEC model, employs the related genotype information besides the SNP fragments and, therefore, results in a more accurate inference. We introduce algorithmic neural network-based approaches and experimentally prove that our methods are fast and accurate. Particularly, our approach is faster, more accurate, and also compatible for solving MEC model, in comparison with a feed-forward (and back propagation like) neural network.     

Behavior of polymer concrete beam/pile confined with CFRP sleeves

This research investigates the flexural behavior of a polymer concrete beam/pile encased with carbon fiber sleeve. The mechanical properties of carbon fiber sleeves in tension and cement and polymer concrete in compression were determined. Polymer concrete beams were tested in flexure to determine the bending moment capacity. Then, the test results were compared to the theoretical model results. Finally, a parametric study was conducted to determine the influence of beam/pile parameters on the capacity of the element. Based on the investigation, carbon fiber sleeve filled with polymer concrete exhibits outstanding structural performance including ductility and bending capacity.     

Synthesis of biotin‐targeted chitosan/poly (methyl vinyl ether‐alt ‐maleic acid) copolymeric micelles for delivery of doxorubicin

Biotinylated chitosan/poly(methyl vinyl ether‐alt ‐maleic acid) (PMVEMA) copolymer was synthesised by an amide reaction in two steps. Structural characterisation was performed using ¹ HNMR and Fourier transform infra‐red (FTIR) spectra. Critical micelle concentration (CMC) of the copolymer was determined by pyrene as a fluorescent probe. Doxorubicin (DOX) was loaded in the micelles by the direct dissolution method. The effects of different variables including type of copolymer, copolymer concentration, stirring rate and stirring time were studied on the physicochemical properties of the micelles including: particle size, zeta potential, release efficiency and loading efficiency of nanoparticles using an irregular factorial design. The in vitro cytotoxicity of DOX‐loaded biotin‐targeted micelles was studied in HepG2 cells which over express biotin receptors by 3, 5‐[dimethylthiazol‐2‐yl]‐2, 5‐diphenyl tetrazolium bromide assay. The successful synthesis of the biotinylated copolymer of chitosan/PMVEMA was confirmed by FTIR and ¹ HNMR. The optimised micelles showed the CMC of 33 μg/ml, particle size of 247 ± 2 nm, zeta potential of +9.46 mV, polydispersity index of 0.22, drug‐loading efficiency of 71% and release efficiency of 84.5 ± 1.6%. The synthesised copolymer was not cytotoxic. The cytotoxicity of DOX‐loaded in targeted micelles on HepG2 cell line was about 2.2‐fold compared with free drug.Inspec keywords: biomedical materials, cellular biophysics, dissolving, drug delivery systems, drugs, electrokinetic effects, fluorescence, Fourier transform infrared spectra, particle size, polymer blends, spectrochemical analysis, toxicologyOther keywords: ¹ HNMR spectra, biotin‐targeted chitosan‐poly (methyl vinyl ether‐alt‐maleic acid) copolymeric micelles, doxorubicin delivery, amide reaction, structural characterisation, Fourier transform infrared spectra, pyrene, fluorescent probe, direct dissolution method, physicochemical properties, particle size, zeta potential, nanoparticles, irregular factorial design, in vitro cytotoxicity, DOX‐loaded biotin‐targeted micelles, 3, 5‐[dimethylthiazol‐2‐yl]‐2, 5‐diphenyl tetrazolium bromide assay, polydispersity index, drug‐loading efficiency, HepG2 cell line, voltage 9.46 mV     

A 1-V 5-bit 0.5 GS/s time-based flash ADC in 0.18 µm CMOS technology

A novel low-voltage rail-to-rail parallel time-based analog-to-digital converter (ADC) is proposed. The proposed ADC works like a conventional flash ADC except that the process is performed in the time-domain. Since the operation of analog integrated circuits at low supply voltages is limited, converting the voltage signals to the time domain improves the efficiency of the circuit. In this paper, a constant-delay ladder is utilized to make the reference delay-times to compare with the input signal. A 1-V 5-bit 500 MS/s ADC has been designed and simulated in 0.18 µm CMOS technology consumed 3.66 mW. The simulation results show 0.3lsb and 0.2lsb for INL and DNL respectively. Signal-to-noise and distortion ratio (SNDR) of the proposed ADC is 26.7 dB at Nyquist frequency. The rail-to-rail operation and linearity of the voltage-to-time converter (VTC) improved the efficiency of the ADC comparing to the similar time-based ADCs. The figure-of-merit (FoM) of the ADC is about 0.31 (pJ/conv.step).

     

5G for the Support of Public Safety Services

Wireless Personal Communications - The Internet of Things (IoT) is the most recent Internet evolution that integrates many smart devices, such as constrained devices, smart tablets, smart vehicles,...     

Theoretical Analysis of the Underwater Incremental Adaptive Network Performance Based on the VLC Technology

In this paper, the underwater implementation of the incremental adaptive networks is proposed based on the visible light communication technology. The underwater distance between transmitter and receiver nodes and the salinity and temperature levels of the considered water determines the stochastical properties of the underwater link that is modeled with the Log-normal distribution. The incremental network performance can be expressed with the excess mean square error and mean square deviation values and we used them in this paper for our theoretical analysis. Our findings showed that the distances between the nodes must not be more than 10 m or the incremental network will diverge from its estimation goal. The network performance is analyzed through multiple link distances and the results are presented with several simulations. The simulation results are devised in order to elaborate the effects of the underwater turbulent links on the performances of estimating adaptive network. Also, the impacts of different salinity and temperature levels are analyzed theoretically and the results are compared with the simulation results.