Commitment-based device-pairing protocol with synchronized drawings and comparison metrics

This article presents a new method for pairing devices securely. The commitment-based authentication uses a fuzzy secret that the devices only know approximately. Its novel feature is time-based opening of commitments in a single round. We also introduce a new source for the fuzzy secret: synchronized drawing with two fingers of the same hand on two touch screens or surfaces. The drawings are encoded as strings and compared with an edit-distance metric. A prototype implementation of this surprisingly simple and natural pairing mechanism shows that it accurately differentiates between true positives and man-in-the-middle attackers.     

Optimal siting and sizing of demand response in a transmission constrained system with high wind penetration

This paper describes algorithms that use demand-side management to address large-scale integration of wind power. In particular, demand response (DR) is used to manage wind power intermittency by shifting the time that electrical power system loads occur in response to real-time prices and wind availability. An economic dispatch with transmission, DR capacity and operational constraints is used to model the operation of a transmission constrained system with a high penetration of wind power. This optimization model is used to determine the optimal sizing and distribution of DR given a fixed budget for customer incentives and the installation of enabling technology. We demonstrate the effectiveness of the operational model based on a simple PJM 5-bus system and an IEEE 118-bus system. Simulation results show that transmission constraints have a greater effect on sizing of DR capacity than the location of wind power, which means that buses electrically close to congested lines tend to have higher incentives to deploy DR resources than other buses. The second part of the work examines optimal siting of technology that enables DR based on the frequency of DR based load changes, which are generally a function of the network location.     

A practical assessment of risk-averse approaches in production lot-sizing problems

ABSTRACT

This paper presents an empirical assessment of four state-of-the-art risk-averse approaches to deal with the capacitated lot-sizing problem under stochastic demand. We analyse two mean-risk models based on the semideviation and on the conditional value-at-risk risk measures, and alternate first and second-order stochastic dominance approaches. The extensive computational experiments based on different instances characteristics and on a case-study suggest that CVaR exhibits a good trade-off between risk and performance, followed by the semideviation and first-order stochastic dominance approach. For all approaches, enforcing risk-aversion helps to reduce the cost-standard deviation substantially, which is usually accomplished via increasing production rates. Overall, we can say that very risk-averse decision-makers would be willing to pay an increased price to have a much less risky solution given by CVaR. In less risk-averse settings, though, semideviation and first-order stochastic dominance can be appealing alternatives to provide significantly more stable production planning costs with a marginal increase of the expected costs.     

An investigation into the cause of loss of containment from the supply of mini-bulk lubricants

An Intermediate Bulk Container (IBC) was punctured during its handling, releasing oil onto soil at an environmentally-sensitive region of Australia. The telehandler did not pierce the plastic of the IBC directly (as was expected) but rather one of the tynes had caught on the underside of the metal base plate, despite numerous controls being in place at time of spill, revealing a previously unreported mechanism for a fluid spill from handling of petroleum hydrocarbons. The diverse investigation team used a root cause analysis (RCA) technique to identify the underlying cause: the inspection process was inadequate with contributing factors of not using a spotter and design of IBC did not anticipate conditions. Engineering controls were put in place as part of the change management process to help prevent spills from occurring from piercing from telehandler tynes on the current project site.     

Framework to manage multiple goals in community-based energy sharing network in smart grid

Smart grid has opened up a new role of “prosumer” in an energy value network, transforming many conventional energy consumers into prosumers, who not only generate green energy but also share the surplus with utilities and other consumers. The concept of a goal-oriented prosumer community group (PCG) has emerged recently as an effective way to fulfill sustainable energy exchange. Such community-based energy sharing networks comprise multiple irreconcilable objectives such as demand constraints, cost constraints, and income maximization. In many cases, one goal may be achievable only at the expense of other goals. This necessitates the development of an effective framework to manage the multiple goals and reduce the gap with their achievement levels. Therefore, in this research paper, an effective framework is developed to negotiate among the multiple goals and thus to define optimal mutual goals for each PCG in a more sustainable manner using multiple-criteria goal programming techniques. Simulation results are presented to illustrate how the methods work in practical situations, where each of the objective measure is given a target value and the unwanted deviations from this set are minimized in an achievement function.     

Co-precipitation of nano Mg–Y/ZrO2 ternary oxide eutectic system: Effects of calcination temperature

In the family of inorganic nanomaterials, zirconia is a highly promising functional ceramic with a high refractive index, hardness, and dielectric constant, as well as excellent chemical inertness and thermal stability. These properties are enhanced in nano-zirconia ceramics, because nanopowders have a small particle size, good morphology, and uniform and dispersive distribution. In this study, a co-precipitation process was proposed to synthesise highly dispersed MgO–Y₂O₃ co-stabilized ZrO₂ nanopowders. The effects of different calcination temperatures on the crystallisation degree and particle dispersion of zirconia nanopowders were characterised by X-ray diffraction (XRD), thermogravimetry-differential scanning calorimetry (TG-DSC), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), nitrogen adsorption using the Brunauer–Emmett–Teller (BET) theory, transmission electron microscopy (TEM), and field emission scanning electron microscopy (FESEM). The optimum synthesis conditions were obtained as follows: 6 h of high-energy planetary grinding and calcination at 800 °C in an electric furnace. Under these optimum conditions, the average particle size of the prepared powder was 28.7 nm. This process enriches the literature on the controllable preparation of Mg–Y/ZrO₂ nanopowders obtained by the co-precipitation method.     

Profiling drunk driving recidivists in Denmark

Drunk drivers are a menace to themselves and to other road users, as drunk driving significantly increases the risk of involvement in road accidents and the probability of severe or fatal injuries. Although injuries and fatalities related to road accidents have decreased in recent decades, the prevalence of drunk driving among drivers killed in road accidents has remained stable, at around 25% or more during the past 10 years. Understanding drunk driving, and in particular, recidivism, is essential for designing effective countermeasures, and accordingly, the present study aims at identifying the differences between non-drunk drivers, drunk driving non-recidivists and drunk driving recidivists with respect to their demographic and socio-economic characteristics, road accident involvement and other traffic and non-traffic-related law violations. This study is based on register-data from Statistics Denmark and includes information from 2008 to 2012 for the entire population, aged 18 or older, of Denmark. The results from univariate and multivariate statistical analyses reveal a five year prevalence of 17% for drunk driving recidivism, and a significant relation between recidivism and the drunk drivers’ gender, age, income, education, receipt of an early retirement pension, household type, and residential area. Moreover, recidivists are found to have a higher involvement in alcohol-related road accidents, as well as other traffic and, in particular, non-traffic-related offences. These findings indicate that drunk driving recidivism is more likely to occur among persons who are in situations of socio-economic disadvantage and marginalisation. Thus, to increase their effectiveness, preventive measures aiming to reduce drunk driving should also address issues related to the general life situations of the drunk driving recidivists that contribute to an increased risk of drunk driving recidivism.     

Multi-resource scheduling for FPGA systems

In modern cloud data centers, reconfigurable devices (FPGAs) are used as an alternative to Graphics Processing Units to accelerate data-intensive computations (e.g., machine learning, image and signal processing). Currently, FPGAs are configured to execute fixed workloads, repeatedly over long periods of time. This conflicts with the needs, proper to cloud computing, to flexibly allocate different workloads and to offer the use of physical devices to multiple users. This raises the need for novel, efficient FPGA scheduling algorithms that can decide execution orders close to the optimum in a short time. In this context, we propose a novel scheduling heuristic where groups of tasks that execute together are interposed by hardware reconfigurations. Our contribution is based on gathering tasks around a high-latency task that hides the latency of tasks, within the same group, that run in parallel and have shorter latencies. We evaluated our solution on a benchmark of 37500 random workloads, synthesized from realistic designs (i.e., topology, resource occupancy). For this testbench, on average, our heuristic produces optimum makespan solutions in 47.4% of the cases. It produces acceptable solutions for moderately constrained systems (i.e., the deadline falls within 10% of the optimum makespan) in 90.1% of the cases.     

A size-dependent thermodynamic model for coke crystallites: The carbon–hydrogen system up to 2500 K

The development is presented of a model of the thermodynamic functions of enthalpy, entropy and Gibbs energy for the elements carbon and hydrogen in coke crystallites. It is applicable to varying degrees of graphitization, described by the crystallite length L_a and the crystallite height L_c. The model parameters are derived from known properties such as bond enthalpies and entropies of formation. Good agreement has been obtained between the predicted thermal dehydrogenation of petroleum cokes and experimental data. The removal of hydrogen from idealized coke crystallites is predicted to occur mostly between 1100 and 1300 K. Agreement has also been found in the comparison of the predicted thermodynamic stability of coke relative to graphite, in a previous experimental study. This stability has been determined as at ≈900 J g⁻¹ at temperatures between 950 and 1250 K and for L_a = 10 nm. The current predictive capacity of the present model is valid for temperatures up to 2500 K.     

Performance evaluation of noise reduction method during on-line monitoring of MV switchgear for PD measurements by non-intrusive sensors

Partial Discharge (PD) measurement is a globally accepted method for insulation diagnosis of electrical assets. The consequences of insulation breakdown are well known. The trend is to move from conventional offline testing to online monitoring for insulation life prediction, which results in the inclusion of high frequency noise in the captured signals. Therefore de-noising is of paramount importance in online monitoring to obtain useful information from the signal.In this research, a 20 kV switchgear panel has been subjected to PD faults in the laboratory and measurements have been carried out by using different non-intrusive sensors including a novel sensor, the D-dot sensor and recorded by a high frequency oscilloscope. The measured results show the effective applicability of sensors for switchgear. The Discrete Wavelet Transform (DWT) has been used to de-noise PD signals in this paper. Time domain and frequency domain comparison of original and de-noised PD signals reveals the significance of this technique for online monitoring of Medium Voltage (MV) switchgear. Finally, an adaptive online de-noising concept, based on automatic de-noising is also proposed in this paper.