Demand response for home energy management system

The optimization of energy consumption, with consequent cost reduction, is one of the main challenges for the present and future smart grid. Demand response (DR) program is expected to be vital in home energy management system (HEMS) which aims to schedule the operation of appliances to save energy costs by considering customer convenience as well as characteristics of electric appliances. The DR program is a challenging optimization problem especially when the formulations are non-convex or NP-hard problems. In order to solve this challenging optimization problem efficiently, an effective heuristic approach is proposed to achieve a near optimal solution with low computational costs. Different from previously proposed methods in literatures which are not suitable to be run in embedded devices such as a smart meter. The proposed algorithm can be implemented in an embedded device which has severe limitations on memory size and computational power, and can get an optimal value in real-time. Numerical studies were carried out with the data simulating practical scenarios are provided to demonstrate the effectiveness of the proposed method.     

Nickel foam-supported Fe,Ni-Polyporphyrin microparticles: Efficient bifunctional catalysts for overall water splitting in alkaline media

Developing highly active, stable and sustainable electrocatalysts for overall water splitting is of great importance to generate renewable H₂ for fuel cells. Herein, we report the synthesis of electrocatalytically active, nickel foam-supported, spherical core-shell Fe-poly(tetraphenylporphyrin)/Ni-poly(tetraphenylporphyrin) microparticles (FeTPP@NiTPP/NF). We also show that FeTPP@NiTPP/NF exhibits efficient bifunctional electrocatalytic properties toward both the oxygen evolution reaction (OER) and the hydrogen evolution reaction (HER). Electrochemical tests in KOH solution (1 M) reveal that FeTPP@NiTPP/NF electrocatalyzes the OER with 100 mA cm⁻² at an overpotential of 302 mV and the HER with 10 mA cm⁻² at an overpotential of 170 mV. Notably also, its catalytic performance for OER is better than that of RuO₂, the benchmark OER catalyst. Although its catalytic activity for HER is slightly lower than that of Pt/C (the benchmark HER electrocatalyst), it shows greater stability than the latter during the reaction. The material also exhibits electrocatalytic activity for overall water splitting reaction at a current density of 10 mA cm⁻² with a cell voltage of 1.58 V, along with a good recovery property. Additionally, the work demonstrates a new synthetic strategy to an efficient, noble metal-free-coordinated covalent organic framework (COF)-based, bifunctional electrocatalyst for water splitting.     

An airlight estimation method for image dehazing based on gray projection

Multimedia Tools and Applications - As the key parameter of dehazing algorithms, airlight value directly affect the calculation accuracy of sky region, and any deviation will lead to the chromatic...     

Simulation of humidity control and greenhouse temperature tracking in a growth chamber using a passive air conditioning unit

In this paper, we define a dynamic discrete model of a passive air conditioning unit, without the more typical compression or absorption-refrigeration cycle. The unit is composed of heat exchangers, a positioning system and humid corrugated pads. The aim of the study was to follow the temperature in a greenhouse and to replicate it with a desired and stable relative humidity in a ventilated growth chamber. A control law, based on a quadratic criterion and dynamic programming, taking output error and energy consumption minimisation into account, was used to control the behaviour of the unit in spite of air intake disturbances. The results of the simulation indicate that the air conditioning unit can produce a variable climate in the growth chamber, with a wide range of relative humidity setpoints.     

A study on flowshop scheduling problem combining Taguchi experimental design and genetic algorithm

As genetic algorithm parameters vary depending on different problem types when applying genetic algorithm to reach global optimum, appropriate design value selection has significant impact on the efficiency of genetic algorithm. However, most users adjust parameters manually based on the reference values of previous literature. Such trial-and-error method is time-consuming, ineffective, and often it could not locate the optimal combination. Therefore, in flowshop scheduling problems, this research anticipates to complete optimal parameter combination design in genetic algorithm using Taguchi experimental design. According to the research results, different ways of producing initial solution have significant influence on this research topic. Consequently, confirmation experiment is conducted using the optimal parameter combination obtained from the research results. It is found that the predicted value of signal-to-noise ratio (S/N ratio) and its actual value exists deviation of 0.238%, indicating repetitiveness and robustness of the obtained parameter combination. Hence, this research method can effectively reduce time spent on parameter design using genetic algorithm and increase efficiency of algorithm.     

Comparison of three internationally certified firefighter protective ensembles: Physiological responses,mobility, and comfort

BackgroundFire protective ensembles (FPEs) are essential to safely perform firefighting job tasks; however, they are often burdensome to the workers. The aim of this study was to compare three internationally certified fire protective ensembles from the European Union (EU), South Korea (SK), and United States (US) on physiological responses, mobility, and comfort.MethodsTen male professional firefighters performed a battery of exercises in the laboratory following the ASTM F3031-17 standard to evaluate mobility, occupation-specific performance, and physiological responses (body weight, heart rate (HR), core temperature (T_c), breathing rate (BR), and rating of perceived exertion (RPE)) to 20 min of treadmill walking (3.2 mph, 5% incline). All participants carried out the evaluation wearing each FPE in a random order. Mixed effects models examined time (pre-vs. post-) by ensemble (EU, SK, US) interactions for all physiological variables and compared comfort, performance, and subjective variables across ensembles.ResultsNo interaction effects were observed for body weight, HR, T_c, BR, or RPE (p = 0.890, p = 0.994, p = 0.897, p = 0.435, and p = 0.221; respectively). SK had greater trunk flexion than EU (78.4° vs. 74.6°, p = 0.026) and US had lower standing reach than EU (105.5 cm vs. 115.4 cm, p = 0.004). Agility circuit time was lower in US (9.3 s) compared to EU (9.8 s) or SK (9.9 s) (p = 0.051 and p = 0.019, respectively).ConclusionsThe findings suggest that physiological burden remained largely unchanged across the international FPEs. However, mobility, performance, and comfort may be significantly influenced across types. International stakeholders and end users should consider design implications when choosing fire protective ensembles.     

The ability of eye-tracking metrics to classify and predict the perceived driving workload

Traffic safety is directly related to the mental and physical condition of the driver. Performing regular secondary tasks while driving is an additional activity that dissipates attention and adds to the drivers' workload. Identifying driver fatigue and workload based on gaze behavior is one way to ensure a safe driving experience. The purpose of this paper is to classify and predict driving perceived workload using a set of eye-tracking metrics (gaze fixation, duration, pointing, and pupil diameter). The ability of eye-tracking metrics to predict driving workload has been investigated. As a result, frustration, performance, and temporal load showed a correlation with gaze metrics. Gaze point, duration, fixation, and pupil diameter significantly influence driving workload.Relevance to industry: Results will supply the specialists in eye-tracking/sensor technologies and traffic safety with new knowledge to improve the design of the driving performance and safety monitoring systems and efficiency of the driving process.     

Segmentation by Continuous Latent Semantic Analysis for Multi-structure Model Fitting

International Journal of Computer Vision - In this paper, we propose a novel continuous latent semantic analysis fitting method, to efficiently and effectively estimate the parameters of model...     

An SVD-based image watermarking in wavelet domain using SVR and PSO

The paper presents a novel blind watermarking scheme for image copyright protection, which is developed in the discrete wavelet transform (DWT) and is based on the singular value decomposition (SVD) and the support vector regression (SVR). Its embedding algorithm hides a watermark bit in the low–low (LL) subband of a target non-overlap block of the host image by modifying a coefficient of U component on SVD version of the block. A blind watermark-extraction is designed using a trained SVR to estimate original coefficients. Subsequently, the watermark bit can be computed using the watermarked coefficient and its corresponding estimate coefficient. Additionally, the particle swarm optimization (PSO) is further utilized to optimize the proposed scheme. Experimental results show the proposed scheme possesses significant improvements in both transparency and robustness, and is superior to existing methods under consideration here.