A linear programming-based method for job shop scheduling

We present a decomposition heuristic for a large class of job shop scheduling problems. This heuristic utilizes information from the linear programming formulation of the associated optimal timing problem to solve subproblems, can be used for any objective function whose associated optimal timing problem can be expressed as a linear program (LP), and is particularly effective for objectives that include a component that is a function of individual operation completion times. Using the proposed heuristic framework, we address job shop scheduling problems with a variety of objectives where intermediate holding costs need to be explicitly considered. In computational testing, we demonstrate the performance of our proposed solution approach

A review on hierarchical routing protocols for wireless sensor networks

The routing protocol for Wireless Sensor Networks (WSNs) is defined as the manner of data dissemination from the network field (source) to the base station (destination). Based on the network topology, there are two types of routing protocols in WSNs, they are namely flat routing protocols and hierarchical routing protocols. Hierarchical routing protocols (HRPs) are more energy efficient and scalable compared to flat routing protocols. This paper discusses how topology management and network application influence the performance of cluster-based and chain-based hierarchical networks. It reviews the basic features of sensor connectivity issues such as power control in topology set-up, sleep/idle pairing and data transmission control that are used in five common HRPs, and it also examines their impact on the protocol performance. A good picture of their respective performances give an indication how network applications, i.e whether reactive or proactive, and topology management i.e. whether centralized or distributed would determine the network performance. Finally, from the ensuring discussion, it is shown that the chain-based HRPs guarantee a longer network lifetime compared to cluster-based HRPs by three to five times

Pattern formation dynamics in a Memristor Cellular Nonlinear Network structure with a numerically stable VO2 memristor model

In this work, we explore pattern formation dynamics across a diffusively coupled Memristor Cellular Nonlinear Network (MCNN), which is composed of identical cells with locally active memristors. We bias the cells on the edge-of-chaos, introduce a systematic design procedure to induce complexity in the array, and extract the element values analytically in a parametric form. In order to enhance the stability and speed of the numerical simulations, we apply a simple variable transformation to a core memristor model while we include the additional effect of parasitic resistors to investigate the locally active dynamics of a VO2 device. We first take a close look at the effect of the linear coupling resistor on pattern formation, and later study how nonlinearly-resistive coupling, based upon tangent hyperbolic law, affect the emergence of complex patterns. Simulation results reveal that a variety of static patterns with different characteristics can emerge across the proposed MCNN

Breastfeeding Success among Infants with Phenylketonuria

Breast milk is the nutrition of choice for human infants (American Academy of Pediatrics, 2005; American Association of Family Physicians, 2008; Association of Women’s Health Obstetric and Neonatal Nurses, 2005; Canadian Paediatric Society, 2005; U.S. Preventive Services Task Force, 2008; World Health Organization, 2009). The literature on the benefits of breast milk and breastfeeding for infants and mothers has established multiple positive outcomes for infants (Hoddinott, Tappin, & Wright, 2008; Horta, Bahl, Martines, & Victora, 2007; Ip et al., 2007). Breast milk has advantages for infants that distinguish it from standard commercial infant formulas. These advantages include growth factors, hormones, immunological factors, and long-chain polyunsaturated fatty acids. For infants with phenylketonuria (PKU), breast milk has additional advantages over any standard commercial infant formula, such as a lower concentration of protein and a lower content of the amino acid, phenylalanine. Despite these benefits, some clinics encourage mothers of infants with PKU to breastfeed whereas others present breastfeeding as an unacceptable option. Although the possible risks and benefits of breastfeeding infants with PKU have been discussed, there is limited research and practice describing breastfeeding infants with PKU. As a result, breastfeeding infants with PKU is based more upon limited clinical experiences rather than upon evidence based practice that aims to apply the best scientific evidence gained from research to clinical decision making

The State Change Per Cycle Map a novel system-theoretic analysis tool for periodically-driven ReRAM cells

Memristive devices are the subject of extensive studies nowadays. While the Dynamic Route Map is a powerful tool for analyzing the response of first-order memristors under DC stimuli, the development of an equivalent tool for investigating the response of these devices to AC stimuli is still an open question. Recently, Pershin and Slipko introduced a graphic method, which we name Time Average State Dynamic Route (TA-SDR), applicable to study first-order memristors subject to periodic rectangular pulse train-based stimuli. In this paper we introduce an alternative investigation tool, referred to as State Change Per Cycle Map (SCPCM), which is applicable in these very same scenarios. The novel analysis technique, inspired by the work of the French mathematician Henri Poincaré, reduces the investigation of a first-order non-autonomous continuous-time system to a simpler study of a first-order discrete-time map. A State Change Per Cycle Map defines precisely how the stimulus modulates each of the admissible device memory states over one input cycle. It is derivable either by means of numerical simulations, where a model for the ReRAM cell is available, or experimentally, in the case where the device memory state is accessible. While the predictive capability of a TA-SDR is limited to those case studies, where the AC periodic voltage signal applied across the device induces negligible changes in the respective memory state over each cycle, the conclusions drawn by analyzing a SCPCM have general validity, irrespective of the properties of the stimulus. The advantages of the novel analysis method for periodically driven ReRAM cells over the classical TA-SDR tool are highlighted through a number of case studies, some of which reveal the interesting capability of the ReRAM cell to display multiple oscillatory operating modes upon periodic stimulation via trains with a suitable number of SET and RESET pulses per period

On Local Activity and Edge of Chaos in a NaMLab Memristor

Local activity is the capability of a system to amplify infinitesimal fluctuations in energy. Complex phenomena, including the generation of action potentials in neuronal axon membranes, may never emerge in an open system unless some of its constitutive elements operate in a locally active regime. As a result, the recent discovery of solid-state volatile memory devices, which, biased through appropriate DC sources, may enter a local activity domain, and, most importantly, the associated stable yet excitable subdomain, referred to as edge of chaos, which is where the seed of complexity is actually planted, is of great appeal to the neuromorphic engineering community. This paper applies fundamentals from the theory of local activity to an accurate model of a niobium oxide volatile resistance switching memory to derive the conditions necessary to bias the device in the local activity regime. This allows to partition the entire design parameter space into three domains, where the threshold switch is locally passive (LP), locally active but unstable, and both locally active and stable, respectively. The final part of the article is devoted to point out the extent by which the response of the volatile memristor to quasistatic excitations may differ from its dynamics under DC stress. Reporting experimental measurements, which validate the theoretical predictions, this work clearly demonstrates how invaluable is non-linear system theory for the acquirement of a comprehensive picture of the dynamics of highly non-linear devices, which is an essential prerequisite for a conscious and systematic approach to the design of robust neuromorphic electronics. Given that, as recently proved, the potassium and sodium ion channels in biological axon membranes are locally active memristors, the physical realization of novel artificial neural networks, capable to reproduce the functionalities of the human brainmore closely than state-of-the-art purely CMOS hardware architectures, should not leave aside the adoption of resistance switching memories, which, under the appropriate provision of energy, are capable to amplify the small signal, such as the niobium dioxide micro-scale device fromNaMLab, chosen as object of theoretical and experimental study in this work

Theoretico-experimental analysis of bistability in the oscillatory response of a TaOx ReRAM to pulse train stimuli

Fading memory is the capability of a physical system to approach a unique asymptotic behaviour, irrespective of the initial conditions, when stimulated by an input from a certain class. Standard stimuli from the AC periodic class typically induce fading memory effects in non-volatile memristors, as uncovered for the first time back in 2016. Very recently, a deep investigation of resistance switching phenomena in a TaOx resistive random access memory cell revealed the capability of the nano-device to exhibit one of two possible oscillatory behaviours, depending upon the initial condition, when subject to a particular periodic excitation. This interesting finding was, however, left unexplained. Bistability is the simplest form of local fading memory. In a system, endowed with local fading memory under a given stimulus, the initial condition does not affect the long-term behaviour of the state as long as it is drawn from the basin of attraction of either of the distinct coexisting state-space attractors (two limit cycles for the periodically forced memristor acting as a bistable oscillator). Here, the history of the system, encoded in the initial condition, is, thus, erasable only locally through ad hoc stimulation. Motivated by the discovery of local history erase effects in our resistive random access memory cell, this study applies a powerful system-theoretic tool, enabling the analysis of the response of first-order systems to square pulse train-based periodic stimuli, known as the time-average state dynamic route, to an accurate physics-based mathematicalmodel, earlier fitted to the nano-device, to determine a strategy for specifying the parameters of an excitation signal, consisting of the sequence of two square pulses of opposite polarity per period so as to induce various forms of monostability or multistability in the non-volatile memristor. In particular, as an absolute novelty in the literature, experimental measurements validate the theoretical prediction on the capability of the device to operate as one of two distinct oscillators, depending upon the initial condition, under a specific pulse train excitation signal. The coexistence of multiple oscillatory operating modes in the periodically forced resistive random access memory cell, an example par excellence of their unique nonlinear dynamics, may inspire the development and circuit implementation of novel sensing and mem-computing paradigms

A Deep Study of Resistance Switching Phenomena in TaOx ReRAM Cells: System-Theoretic Dynamic Route Map Analysis and Experimental Verification

The multidisciplinary field of memristors calls for the necessity for theoreticallyinclined researchers and experimenters to join forces, merging complementary expertise and technical know-how, to develop and implement rigorous and systematic techniques to design variability-aware memristor-based circuits and systems. The availability of a predictive physics-based model for a memristor is a necessary requirement before commencing these investigations. An interesting dynamic phenomenon, occurring ubiquitously in non-volatile memristors, is fading memory. The latter may be defined as the appearance of a unique steady-state behavior, irrespective of the choice of the initial condition from an admissible range of values, for each stimulus from a certain family, for example, the DC or the purely-AC periodic input class. This paper first provides experimental evidence for the emergence of fading memory effects in the response of a TaOx redox-based random access memory cell to inputs from both of these classes. Leveraging the predictive capability of a physics-based device model, called JART VCM v1, a thorough system-theoretic analysis, revolving around the Dynamic Route Map graphic tool, is presented. This analysis allows to gain a better understanding of the mechanisms, underlying the emergence of history erase effects, and to identify the main factors, that modulate this nonlinear phenomenon, toward future potential applications