Synthesis,lattice energy and microwave dielectric properties of BaCu2-xCoxSi2O7 ceramics

BaCu_2-xCo_xSi₂O₇ solid solutions with orthorhombic structure (Pnma) were prepared by solid-state reaction method. The phase synthesis process, structural evolution and microwave dielectric properties of BaCu_2-xCo_xSi₂O₇ ceramics were investigated. Single BaCu₂Si₂O₇ phase was obtained when calcined at 950 °C for 3 h and was decomposed into BaCuSi₂O₆ phase when calcined at 1075 °C for 3 h. The sintering process was effectively promoted when Cu²⁺ was replaced by Co²⁺ and the maximum solubility of BaCu_2-xCo_xSi₂O₇ was located between 0.15 and 0.20. P-V-L complex chemical bond theory and Raman spectra were used to explain the structure-property correlations of BaCu_2-xCo_xSi₂O₇ ceramics. The corrected dielectric constant (ε_r-corr) of BaCu_2-xCo_xSi₂O₇ ceramics decreased monotonously with the susceptibility (Σχ^μ) and ionic polarizability of primitive unit cell. The quality factor (Q × f) increased with bond strength and lattice energy (U_cal), especially the lattice energy of the Si-O bond. The temperature coefficient of resonant frequency (τ_f) was determined by the susceptibility and lattice energy of the Cu/Co-O bond. The following optimum microwave dielectric properties were obtained at x = 0.15 when sintered at 1000 °C for 3 h: ε_r = 8.45, Q×f =58958 GHz and τ_f = -34.4 ppm/°C.     

Doping-free hybrid white organic light-emitting diodes with fluorescent blue,phosphorescent green and red emission layers

Industrialized white organic light-emitting diodes (OLEDs) currently require host-guest doping, a complicated process necessitating precise control of the guest concentration to get high efficiency and stability. Two doping-free, hybrid white OLEDs with fluorescent blue, and phosphorescent green and red emissive layers (EMLs) are reported in this work. An ultra-thin red phosphorescent EML was situated in a blue-emitting electron transport layer (ETL), while the ultra-thin green phosphorescent EML was placed either in the ETL (Device 1), or the hole transport layer (HTL) (Device 2). Device 2 exhibits higher efficiency and more stable spectrum due to the enhanced utilization of excitons by ultra-thin green EML at the exciton generation zone within the HTL. Values of current efficiency (CE), power efficiency (PE), and CRI obtained for the optimized hybrid white OLEDs fabricated through a doping-free process were of 23.2 cd/A, 20.5 lm/W and 82 at 1000 cd/m², respectively.     

Retinal Vessel Extraction Framework Using Modified Adaboost Extreme Learning Machine

An explicit extraction of the retinal vessel is a standout amongst the most significant errands in the field of medical imaging to analyze both the ophthalmological infections, for example, Glaucoma, Diabetic Retinopathy (DR), Retinopathy of Prematurity (ROP), Age-Related Macular Degeneration (AMD) as well as non retinal sickness such as stroke, hypertension and cardiovascular diseases. The state of the retinal vasculature is a significant indicative element in the field of ophthalmology. Retinal vessel extraction in fundus imaging is a difficult task because of varying size vessels, moderately low distinction, and presence of pathologies such as hemorrhages, microaneurysms etc. Manual vessel extraction is a challenging task due to the complicated nature of the retinal vessel structure, which also needs strong skill set and training. In this paper, a supervised technique for blood vessel extraction in retinal images using Modified Adaboost Extreme Learning Machine (MAD-ELM) is proposed. Firstly, the fundus image preprocessing is done for contrast enhancement and in-homogeneity correction. Then, a set of core features is extracted, and the best features are selected using “minimal Redundancy-maximum Relevance (mRmR).” Later, using MAD-ELM method vessels and non vessels are classified. DRIVE and DR-HAGIS datasets are used for the evaluation of the proposed method. The algorithm’s performance is assessed based on accuracy, sensitivity and specificity. The proposed technique attains accuracy of 0.9619 on the DRIVE database and 0.9519 on DR-HAGIS database, which contains pathological images. Our results show that, in addition to healthy retinal images, the proposed method performs well in extracting blood vessels from pathological images and is therefore comparable with state of the art methods.     

Optimized dual-function varistor-capacitor ceramics of core-shell structured xBi2/3Cu3Ti4O12/(1-x)CaCu3Ti4O12 composites

xBi_2/3Cu₃Ti₄O₁₂/(1-x)CaCu₃Ti₄O₁₂ composites were prepared by traditional solid-state reaction method. Extremely high nonlinear coefficient of 25 and breakdown field of 18.92 kV·cm⁻¹ were obtained in small current range of 0.1−1 mA·cm^-2. In addition, reduced dielectric loss of 0.055 was achieved with high dielectric constant of 1369. Optimized nonlinear and dielectric properties were integrated to make the composites a promising dual-function varistor-capacitor candidate. Microstructure analysis discovered two areas with various Bi/Ca ratio, designated as Bi-H and Bi-L respectively. It was found that the maximum ratio of Bi-H/Bi-L heterogeneous interface corresponded to optimized nonlinear and dielectric performance, which was associated with elevated potential barrier height and huge grain boundary resistance. Combined with relaxation analysis, a core-shell structure was proposed to elaborate microstructure evolution in xBi_2/3Cu₃Ti₄O₁₂/(1-x)CaCu₃Ti₄O₁₂ composite. According to the core-shell model, variation of heterogeneous interface was illustrated on how to influence nonlinear properties, which was well fitted to experimental results.     

Mining citizen emotions to estimate the urgency of urban issues

Crowdsourcing technology offers exciting possibilities for local governments. Specifically, citizens are increasingly taking part in reporting and discussing issues related to their neighborhood and problems they encounter on a daily basis, such as overflowing trash-bins, broken footpaths and lifts, illegal graffiti, and potholes. Pervasive citizen participation enables local governments to respond more efficiently to these urban issues. This interaction between citizens and municipalities is largely promoted by civic engagement platforms, such as See-Click-Fix, FixMyStreet, CitySourced, and OpenIDEO, which allow citizens to report urban issues by entering free text describing what needs to be done, fixed or changed. In order to develop appropriate action plans and priorities, government officials need to figure out how urgent are the reported issues. In this paper we propose to estimate the urgency of urban issues by mining different emotions that are implicit in the text describing the issue. More specifically, a reported issue is first categorized according to the emotions expressed in it, and then the corresponding emotion scores are combined in order to produce a final urgency level for the reported issue. Our experiments use the SeeClickFix hackathon data and diverse emotion classification algorithms. They indicate that (i) emotions can be categorized efficiently with supervised learning algorithms, and (ii) the use of citizen emotions leads to accurate urgency estimates. Further, using additional features such as the type of issue or its author leads to no further accuracy gains.     

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.     

Contact temperatures and their influence on wear during pin-on-disk tribotesting

It is important to take contact temperatures into account when developing friction and wear tests for potential tribomaterials and when analyzing the results of those tests. This paper presents some of the most useful analytical and numerical methods that can be used to predict surface temperature rises in dry or boundary lubricated pin-on-disk tribotests. The objective is the development of relatively simple, accurate, and easy-to-use expressions that can be used to predict contact temperatures in pin-on-disk sliding contacts. Results of the methods are compared for several different cases, and experimental verification of the predictions are also presented. The resulting expressions are applied to investigate wear of a ceramic (zirconia), metal (stainless steel) and polymer (polyethylene) in pin-on-disk tests.     

Key exchange process of PIM-SM-based for Multiple Group Communication in P2P

Peer-to-Peer Networking and Applications - Recently, as the P2P service environment repeats evolution, its usage in mobile is rapidly increasing. Applications are being developed in various mobile...     

Mechanical properties of graphene films enhanced by homo-telechelic functionalized polymer fillers via π–π stacking interactions

Most researches on graphene/polymer composites are focusing on improving the mechanical and electrical properties of polymers at low graphene content instead of paying attention to constructing graphene’s macroscopic structures. In current study the homo-telechelic functionalized polyethylene glycols (FPEGs) were tailored with π-orbital-rich groups (namely phenyl, pyrene and di-pyrene) via esterification reactions, which enhanced the interaction between polyethylene glycol (PEG) molecules and chemical reduced graphene oxide (RGO) sheets. The π–π stacking interactions between graphene sheets and π-orbital-rich groups endowed the composite films with enhanced tensile strength and tunable electrical conductivity. The formation of graphene network structure mediated by the FPEGs fillers via π–π stacking non-covalent interactions should account for the experimental results. The experimental investigations were also complemented with theoretical calculation using a density functional theory. Atomic force microscope (AFM), scanning electron microscope (SEM), X-ray diffraction (XRD), nuclear magnetic resonance (NMR), thermal gravimetric analysis (TGA), UV–vis and fluorescence spectroscopy were used to monitor the step-wise preparation of graphene composite films.