Using electroencephalogram to continuously discriminate feelings of personal thermal comfort between uncomfortably hot and comfortable environments

Thermal comfort is an important factor for the design of buildings. Although it has been well recognized that many physiological parameters are linked to the state of thermal comfort or discomfort of humans, how to use physiological signal to judge the state of thermal comfort has not been well studied. In this paper, the feasibility of continuously determining feelings of personal thermal comfort was discussed by using electroencephalogram (EEG) signals in private space. In the study, 22 subjects were exposed to thermally comfortable and uncomfortably hot environments, and their EEG signals were recorded. Spectral power features of the EEG signals were extracted, and an ensemble learning method using linear discriminant analysis or support vector machine as a sub-classifier was used to build the discriminant model. The results show that an average discriminate accuracy of 87.9% can be obtained within a detection window of 60 seconds. This study indicates that it is feasible to distinguish whether a person feels comfortable or too hot in their private space by multi-channel EEG signals without interruption and suggests possibility for further applications in neuroergonomics.     

智能化救援监控系统在煤矿安全生产中的应用

针对煤矿发生事故后传统救援监控系统无法实时对井下人员进行动态定位，导致矿井救援盲目性大、救援效率差、救援难度大等技术难题，为了进一步提高煤矿救援效率，通过技术研究，设计了一套以通信基站为核心的智能化救援监控系统，分析了该系统结构组成、工作原理，通过在担水沟煤矿井下实际应用效果来看，智能化救援监控系统对人员定位精准度达95%，实现人员动态位置三维成像，救援效率提高至80%以上，有效缩短了煤矿事故救援时间，取得了显著应用成效。     

Design of Feedback Shift Register of Against Power Analysis Attack

Stream ciphers based on linear feedback shift register (LFSR) are suitable for constrained environments, such as satellite communications, radio frequency identification devices tag, sensor networks and Internet of Things, due to its simple hardware structures, high speed encryption and lower power consumption. LFSR, as a cryptographic primitive, has been used to generate a maximum period sequence. Because the switching of the status bits is regular, the power consumption of the LFSR is correlated in a linear way. As a result, the power consumption characteristics of stream cipher based on LFSR are vulnerable to leaking initialization vectors under the power attacks. In this paper, a new design of LFSR against power attacks is proposed. The power consumption characteristics of LFSR can be masked by using an additional LFSR and confused by adding a new filter Boolean function and a flip-flop. The design method has been implemented easily by circuits in this new design in comparison with the others.     

Predicting the thermodynamics of aluminum dross denitrification of flue gas

Existing alumina extraction and material production methods result in the formation of harmful ammonia gas or ammonia water originating from aluminum nitride (AlN) in dross. Therefore, in this study, aluminum dross was used as a denitration reagent to eliminate nitrogen oxides in flue gas and AlN in dross. Based on the proposed scheme, thermodynamic calculations were performed to investigate the denitrification effect and reduction of aluminum dross in flue gas. The results show that equilibrium concentrations of NO, NO₂, and HF in the flue gas were influenced mainly by temperature; their concentrations increased with an increase in the temperature, reaching 4.4 × 10⁻²⁰, 1.7 × 10⁻³⁸, and 7.0 × 10⁻⁸ g/m³, respectively, at 923 K. The Gibbs free energy corresponding to the reaction of CO₂ with Al/AlN in aluminum dross was −377/–120 kJ/mol. HF, originating from the reaction of NaF and water vapor, maintained an extremely low concentration of 6.99 × 10⁻⁸ g/m³ at 923 K. These results indicate that aluminum dross processing may clean the flue gas and increase the calorific value while eliminating the hazards of AlN. The results obtained herein will provide theoretical guidance toward new avenues of aluminum dross utilization.     

Superior foetal electrocardiogram signal elicitation using a novel artificial intelligent Bayesian methodology

Innumerable casualties due to intrauterine hypoxia are a major worry during prenatal phase besides advanced patient monitoring with latest science and technology. Hence, the analysis of foetal electrocardiogram (fECG) signals is very vital in order to evaluate the foetal heart status for timely recognition of cardiac abnormalities. Regrettably, the latest technology in the cutting edge field of biomedical signal processing does not seem to yield the desired quality of fECG signals required by physicians, which is the major cause for the pathetic condition. The focus of this work is to extort non-invasive fECG signal with highest possible quality with a motive to support physicians in utilizing the methodology for the latest intrapartum monitoring technique called STAN (ST analysis) for forecasting intrapartum foetal hypoxia. However, the critical quandary is that the non-invasive fECG signals recorded from the maternal abdomen are affected by several interferences like power line interference, baseline drift interference, electrode motion interference, muscle movement interference and the maternal electrocardiogram (mECG) being the dominant interference. A novel hybrid methodology called BANFIS (Bayesian adaptive neuro fuzzy inference system) is proposed. The BANFIS includes a Bayesian filter and an adaptive neuro fuzzy filter for mECG elimination and non-linear artefacts removal to yield high quality fECG signal. Kalman filtering frame work has been utilized to estimate the nonlinear transformed mECG component in the abdominal electrocardiogram (aECG). The adaptive neuro fuzzy filter is employed to discover the nonlinearity of the nonlinear transformed version of mECG and to align the estimated mECG signal with the maternal component in the aECG signal for annulment. The outcomes of the investigation by the proposed BANFIS system proved valuable for STAN system for efficient prediction of foetal hypoxia.     

Automated network management and configuration using Probabilistic Trans-Algorithmic Search

Online configuration of large-scale systems such as networks requires parameter optimization within a limited amount of time, especially when configuration is needed as a response to recover from a failure in the system. To quickly configure such systems in an online manner, we propose a Probabilistic Trans-Algorithmic Search (PTAS) framework which leverages multiple optimization search algorithms in an iterative manner. PTAS applies a search algorithm to determine how to best distribute available experiment budget among multiple optimization search algorithms. It allocates an experiment budget to each available search algorithm and observes its performance on the system-at-hand. PTAS then probabilistically reallocates the experiment budget for the next round proportional to each algorithm’s performance relative to the rest of the algorithms. This “roulette wheel” approach probabilistically favors the more successful algorithm in the next round. Following each round, the PTAS framework “transfers” the best result(s) among the individual algorithms, making our framework a trans-algorithmic one. PTAS thus aims to systematize how to “search for the best search” and hybridize a set of search algorithms to attain a better search. We use three individual search algorithms, i.e., Recursive Random Search (RRS) (Ye and Kalyanaraman, 2004), Simulated Annealing (SA) (Laarhoven and Aarts, 1987), and Genetic Algorithm (GA) (Goldberg, 1989), and compare PTAS against the performance of RRS, GA, and SA. We show the performance of PTAS on well-known benchmark objective functions including scenarios where the objective function changes in the middle of the optimization process. To illustrate applicability of our framework to automated network management, we apply PTAS on the problem of optimizing link weights of an intra-domain routing protocol on three different topologies obtained from the Rocketfuel dataset. We also apply PTAS on the problem of optimizing aggregate throughput of a wireless ad hoc network by tuning datarates of traffic sources. Our experiments show that PTAS successfully picks the best performing algorithm, RRS or GA, and allocates the time wisely. Further, our results show that PTAS’ performance is not transient and steadily improves as more time is available for search.     

Neutral axis depth and moment redistribution in FRP and steel reinforced concrete continuous beams

The neutral axis depth is considered the best parameter for quantifying the moment redistribution in continuous concrete beams, as exemplified in various design codes worldwide. It is therefore important to well understand the variation of neutral axis depth against moment redistribution. This paper describes a theoretical investigation into the neutral axis depth and moment redistribution in concrete beams reinforced with fibre reinforced polymer (FRP) and steel bars. A finite element model has been developed. The model predictions are in favourable agreement with experimental results. Three types of reinforcement are considered, namely, glass fibre, carbon fibre and steel. Various levels of reinforcement ratio are used for a parametric evaluation. The results indicate that FRP reinforced concrete continuous beams exhibit significantly different response characteristics regarding the moment redistribution and variation of neutral axis depth from those of steel reinforced ones. In addition, it is found that the code recommendations are generally unsafe for calculating the permissible moment redistribution in FRP reinforced concrete beams, but the neglect of redistribution in such beams may be overconservative.     

Flexural behaviour of RC slabs strengthened with prestressed CFRP strips using different anchorage systems

The Externally Bonded Reinforcement (EBR) technique using Carbon Fiber-Reinforced Polymers (CFRP) has been commonly used to strengthen concrete structures in flexure. The use of prestressed CFRP material offers several advantages well-reported in the literature. Regardless of such as benefits, several studies on different topics are missing. The present work intends to contribute to the knowledge of two commercially available systems that differ on the type of anchorage: (i) the Mechanical Anchorage (MA), and (ii) the Gradient Anchorage (GA). For that purpose, an experimental program was carried out with twelve slabs monotonically tested under displacement control up to failure by using a four-point bending test configuration. The effect of type of anchorage system (MA and GA), prestrain level (0 and 0.4%), width (50 mm and 80 mm) and thickness (1.2 mm and 1.4 mm) of the CFRP laminate, and the surface preparation (grinded and sandblasted) on the flexural response were the main studied parameters. Better performance was observed for the slabs: (i) with prestressed laminates, (ii) for the MA system, and (iii) with sandblasted surface preparation.     

Collapse load of composite laminates: Lower bound evaluation by stress field analytical approximation

The paper proposes a limit analysis approach to define the ultimate load capacity of orthotropic composite laminates under biaxial loading and plane stress conditions. A lower bound to the collapse load multiplier is computed by solving a maximization nonlinear problem, according to the static theorem of limit analysis. To set up the optimization problem a stress field distribution is hypothesized at lamina level, moreover inter-lamina stresses are also considered. The effectiveness and validity of the proposed approach is shown by comparing the obtained numerical predictions both with available experimental data and with other numerical results carried out by means of a different numerical lower bound approach.     

Levelized cost of energy definition – An economic paradox

Using mean value theorem for integrals we show that the well-known LCOE definition is incorrect.