Analysis of crowds' movement using Twitter

Over the last decade, the infrastructure supporting the smart city has lived together with and was surpassed by the rise of social media. The tremendous growth of both mobile devices and social media users has unearthed a new kind of services in the so‐called location‐based social networks (LBSNs). In this new scenario, the term crowdsensing refers to sharing data collected by sensing humans with the aim of measuring phenomena of common interest. Crowd‐sourced location data provide the ability to study, for the first time, the movement of individuals in urban environments. In this paper, we address the problem of monitoring crowds, whereabouts and movement, which can assist decision making in education, emergency training, urban planning, traffic engineering, etc. Precisely, two‐phase density‐based analysis for collectives and crowds (2PD‐CC) is a novel methodology over public data in LBSN, which combines density‐based clustering, outlier detection a topic modeling over a region under study to detect, predict, and explain abnormal group behavior. In order to validate the methodology and its potential application to full‐scale problems, an experiment over Twitter data was performed in Madrid city.     

Energy harvesting from far field RF signals

In this article, an alternative source of energy harvesting is proposed. It is based on the concept of charge pump electronics circuit and radio frequency (RF) signal amplifier. The RF signals are acquired by the Dickson charge pump circuit, amplified, and converted into a desired DC signal. To ensure the maximum power extraction, the proposed energy harvester circuit includes multiple circuit level approach. The diode‐capacitor charge pump generated the step‐up stage in the system. The proposed idea is designed and implemented using a suitable hardware successfully. Initially, the designed circuit is simulated and tested using the MultiSim software and then hardware implemented to obtained the desired 1‐5 V DC signal. The presented circuit can be used in various applications such as electronic devices charging, power supply, energy harvesting, etc.     

The Robust Regression Methods for Estimating of Finite Population Mean Based on SRSWOR in Case of Outliers

The ordinary least square (OLS) method is commonly used in regression analysis. But in the presence of outlier in the data, its results are unreliable. Hence, the robust regression methods have been suggested for a long time as alternatives to the OLS to solve the outliers problem. In the present study, new ratio type estimators of finite population mean are suggested using simple random sampling without replacement (SRSWOR) utilizing the supplementary information in Bowley’s coefficient of skewness with quartiles. For these proposed estimators, we have used the OLS, Huber-M, Mallows GM-estimate, Schweppe GM-estimate, and SIS GM-estimate methods for estimating the population parameters. Theoretically, the mean square error (MSE) equations of various estimators are obtained and compared with the OLS competitor. Simulations for skewed distributions as the Gamma distribution support the results, and an application of real data set containing outliers is considered for illustration.     

Exploration of Advanced Electrode Materials for Approaching High‐Performance Nickel‐Based Superbatteries

The surging interest in high performance, low‐cost, and safe energy storage devices has spurred tremendous research efforts in the development of advanced electrode active materials. Herein, the in situ growth of zinc–iron layered double hydroxide (Zn–Fe LDH) on graphene aerogel (GA) substrates through a facile, one‐pot hydrothermal method is reported. The strong interaction and efficient electronic coupling between LDH and graphene substantially improve interfacial charge transport properties of the resulting nanocomposite and provide more available redox active sites for faradaic reactions. An LDH–GA||Ni(OH)₂ device is also fabricated that results in greatly enhanced specific capacity (187 mAh g^?1 at 0.1 A g^?1), outstanding specific energy (147 Wh kg^?1), excellent specific power (16.7 kW kg^?1), along with 88% capacity retention after >10 000 cycles. This approach is further extended to Ni–MH and Ni–Cd batteries to demonstrate the feasibility of compositing with graphene for boosting the energy storage performance of other well‐known Ni‐based batteries. In contrast to conventional Ni‐based batteries, the nearly flat voltage plateau followed by a sloping potential profile of the integrated supercapacitor–battery enables it to be discharged down to 0 V without being damaged. These findings provide new prospects for the design of high‐performance and affordable superbatteries based on earth‐abundant elements.     

Effect of pre-deposition annealing on physical properties of CZTSSe thin films deposed by RF-sputtering based on nanoparticles synthesized by solvothermal technique

This work aims to highlight the beneficial effect of annealing of Cu₂ZnSn(S,Se)₄ (CZTSSe) nanoparticles (NPs) on the properties of the obtained films by RF-magnetron sputtering at room temperature (RT) and at 200 °C. The CZTSSe targets used for the deposition are obtained using nanoparticles synthesized by solvothermal technique. It is denoted that the elemental composition of thin films becomes independent of the growth temperature in the case of annealed CZTSSe NPs. The optical investigation gives that the gap energy is ranging between 1.26 and 1.40 eV with an Urbach’s energy between 100 and 200 meV. By using the Wemple and Didominico model to analyze the refractive index spectra, we have identified common oscillator energy for all CZTSSe thin films and dispersion energy ranging from 2.63 to 5.81 eV. CZTSSe thin films obtained by means of annealed NPs exhibit higher dielectric constant and refractive index. The dispersion of different parameters with experimental conditions is analyzed via a common relationship that illustrates the linear dependence of n₀, E_d, ε_s, and ε_L on the square of the valence difference (ΔZ). The conductivity spectra are deduced, and a theoretical model was identified to fit the permittivity spectra. The obtained results are promising for solar cell applications.

     

Automatic pick-and-place using a magnetically navigated microrobot and a motorized micromanipulator

This paper demonstrates the automatic pick-and-place of a small object in 2D using a magnetically navigated microrobot (MNM) and a motorized micromanipulator (MM). A master/slave control mechanism is used in the manipulation process. The MM is the master manipulator. The MNM is the slave manipulator. To avoid damaging the object by large holding force and to maintain successful holding, a position-based impedance control algorithm is implemented to the slave side. The feedback force to the impedance controller is obtained from an off-board force determination mechanism which overcomes the disadvantages of installing an on-board force sensor on the MNM. The performance of the proposed manipulation system was examined experimentally by transporting a hard-shell object to its desired destinations with predefined holding force. To the authors knowledge, this is the first work reported using a magnetically navigated microrobot to complete manipulation tasks with a screw type manipulator. The proposed system has potential utility in microinjection if the MNM was scaled down to proper size.