The Role of Deep Learning in Parking Space Identification andPredictionSystems

In today’s smart city transportation, traffic congestion is a vexing issue, and vehicles seeking parking spaces have been identified as one of the causes leading to approximately 40% of traffic congestion. Identifying parking spaces alone is insufficient because an identified available parking space may have been taken by another vehicle when it arrives, resulting in the driver’s frustration and aggravating traffic jams while searching for another parking space. This explains the need to predict the availability of parking spaces. Recently, deep learning (DL) has been shown to facilitate drivers to find parking spaces efficiently, leading to a promising performance enhancement in parking identification and prediction systems. However, no work reviews DL approaches applied to solve parking identification and prediction problems. Inspired by this gap, the purpose of this work is to investigate, highlight, and report on recent advances in DL approaches applied to predict and identify the availability of parking spaces. A taxonomy of DL-based parking identification and prediction systems is established as a methodology by classifying and categorizing existing literature, and by doing so, the salient and supportive features of different DL techniques for providing parking solutions are presented. Moreover, several open research challenges are outlined. This work identifies that there are various DL architectures, datasets, and performance measures used to address parking identification and prediction problems. Moreover, there are some open-source implementations available that can be used directly either to extend existing works or explore a new domain. This is the first short survey article that focuses on the use of DL-based techniques in parking identification and prediction systems for smart cities. This study concludes that although the deployment of DL in parking identification and prediction systems provides various benefits, the convergence of these two types of systems and DL brings about new issues that must be resolved in the near future.     

Physical Properties and Thermal Decomposition of Aqueous Solutions of 2-Amino-2-hydroxymethyl-1, 3-propanediol (AHPD)

Physical properties such as density, viscosity, refractive index, surface tension, and thermal stability of 2-amino-2-hydroxymethyl-1,3-propanediol (AHPD) were experimentally measured. All the experimental measurements were made over a wide range of temperatures from (298.15 to 333.15) K and AHPD concentrations of (1, 7, 13, 19, and 25) mass%. An overall decrease in all the measured physical properties was observed with increasing temperature. The experimental results are presented as a function of temperature and AHPD mass fraction. All the measured physical properties were correlated as a function of temperature. Thermal decomposition of pure and aqueous solutions of AHPD was investigated using a thermo-gravimetric analyzer (TGA) at a heating rate of 10 K · min⁻¹.     

Evaluating the Impact of Software Security Tactics: A Design Perspective

Design architecture is the edifice that strengthens the functionalities as well as the security of web applications. In order to facilitate architectural security from the web application’s design phase itself, practitioners are now adopting the novel mechanism of security tactics. With the intent to conduct a research from the perspective of security tactics, the present study employs a hybrid multi-criteria decision-making approach named fuzzy analytic hierarchy process-technique for order preference by similarity ideal solution (AHP-TOPSIS) method for selecting and assessing multi-criteria decisions. The adopted methodology is a blend of fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity ideal solution (fuzzy TOPSIS). To establish the efficacy of this methodology, the results are obtained after the evaluation have been tested on fifteen different web application projects (Online Quiz competition, Entrance Test, and others) of the Babasaheb Bhimrao Ambedkar University, Lucknow, India. The tabulated outcomes demonstrate that the methodology of the Multi-Level Fuzzy Hybrid system is highly effective in providing accurate estimation for strengthening the security of web applications. The proposed study will help experts and developers in developing and managing security from any web application design phase for better accuracy and higher security.     

A Cost-Efficient Environment Monitoring Robotic Vehicle for Smart Industries

Environmental monitoring is essential for accessing and avoiding the undesirable situations in industries along with ensuring the safety of workers. Moreover, inspecting and monitoring of environmental parameters by humans lead to various health concerns, which in turn brings to the requirement of monitoring the environment by robotics. In this paper, we have designed and implemented a cost-efficient robotic vehicle for the computation of various environmental parameters such as temperature, radiation, smoke, and pressure with the help of sensors. Furthermore, the robotic vehicle is designed in such a way that it can be dually controlled by using the remote control along with the distant computer. In addition, contrary to the existing researches, the GSM modules are used to achieve the two-way long distance communication between the robotic vehicle and the distant computer. On the distant computer, the above-mentioned environmental parameters can be monitored along with controlling the robotic vehicle with the help of Graphical User Interface (GUI). In order to fulfill the given tasks, we have proposed two algorithms implemented at the robotic vehicle and the distant computer respectively in this paper. The final results validate the proposed algorithms where the above-mentioned environmental parameters can be monitored along with the smooth-running operation of the robotic vehicle.     

A Robust Wearable Point-of-Care CNT-Based Strain Sensor for Wirelessly Monitoring Throat-Related Illnesses

Point-of-care testing (POC) has the ability to detect chronic and infectious diseases early or at the time of occurrence and provide a state-of-the-art personalized healthcare system. Recently, wearable and flexible sensors have been employed to analyze sweat, glucose, blood, and human skin conditions. However, a flexible sensing system that allows for the real-time monitoring of throat-related illnesses, such as salivary parotid gland swelling caused by flu and mumps, is necessary. Here, for the first time, a wearable, highly flexible, and stretchable piezoresistive sensing patch based on carbon nanotubes (CNTs) is reported, which can record muscle expansion or relaxation in real-time, and thus act as a next-generation POC sensor. The patch offers an excellent gauge factor for in-plane stretching and spatial expansion with low hysteresis. The actual extent of muscle expansion is calculated and the gauge factor for applications entailing volumetric deformations is redefined. Additionally, a bluetooth-low-energy system that tracks muscle activity in real-time and transmits the output signals wirelessly to a smartphone app is utilized. Numerical calculations verify that the low stress and strain lead to excellent mechanical reliability and repeatability. Finally, a dummy muscle is inflated using a pneumatic-based actuator to demonstrate the application of the affixed wearable next-generation POC sensor.     

Fabrication of a <Emphasis Type="Italic">p</Emphasis>–<Emphasis Type="Italic">n</Emphasis> Heterojunction Using Topological Insulator Bi<Subscript>2</Subscript>Te<Subscript>3</Subscript>–Si and Its Annealing Response

A junction device has been fabricated by growing p-type Bi₂Te₃ topological insulator (TI) film on an n-type silicon (Si) substrate using a thermal evaporation technique. Annealing using different temperatures and durations was employed to improve the quality of the film, as confirmed by microstructural study using x-ray diffraction (XRD) analysis and atomic force microscopy (AFM). The p–n diode characteristics of the junction devices were studied, and the effect of annealing investigated. An improved diode characteristic with good rectification ratio (RR) was observed for devices annealed for longer duration. Reduction in the leakage or reverse saturation current (\( I_{\rm{R}} \)) was observed with increase in the annealing temperature. The forward-bias current (\( I_{\rm{F}} \)) dropped in devices annealed above 400°C. The best results were observed for the sample device annealed at 450°C for 3 h, showing figure of merit (FOM) of 0.621 with RR ≈ 504 and \( I_{\rm{R}} \) = 0.25 μA. In terms of ideality factor, the sample device annealed at 550°C for 2 h was found to be the best with \( n \) = 6.5, RR ≈ 52.4, \( I_{\rm{R}} \) = 0.61 μA, and FOM = 0.358. The majority-carrier density \( \left( {N_{\rm{A}} } \right) \) in the p-Bi₂Te₃ film of the heterojunction was found to be on the order of 10⁹/cm³ to 10¹¹/cm³, quite close to its intrinsic carrier concentration. These results are significant for fundamental understanding of device applications of TI materials as well as future applications in solar cells.     

发酵条件对红茶菌发酵品质及风味的影响

探究发酵条件对红茶菌发酵品质及发酵液风味的影响。以发酵产酸率、感官评分为指标,考察红茶品种、茶叶浸提方式、糖添加量、茶叶添加量及红茶菌膜接种量的影响;同时,对发酵过程中风味物质的变化进行分析。结果表明:将水煮沸后,加0.5%醇香红茶浸提15 min,加入7%糖,冷却后加8%红茶菌膜于30℃条件下发酵10 d,得到的产品感官品质好,发酵液呈清澈淡黄色,酸甜适中,微酸,口味纯;茶汤经发酵后风味物质显著改变,共检测到19种风味成分,其中醇类7种、酯类6种、酸类4种、酚类1种、烷烃类1种,即风味物质多为醇类、酯类和酸类。醇类的含量为25.09%,其中乙醇含量为21.51%;酸类的含量为46.40%,其中正辛酸含量为19.41%;酯类的含量为15.91%,其中乙酸乙酯含量为9.47%。     

Implementation and validation of a triaxiality dependent cohesive model: experiments and simulations

A recently formulated triaxiality dependent cohesive model for plane strain is implemented and its versatility is tested in simulation of ductile fracture of mild steel at different states of stress. The triaxiality dependent model was implemented as linear displacement formulation based elements whose constitutive behaviour was dependent on the stress-state of the neighbouring continuum element. By comparing the experimental data and predictions of corresponding plane strain simulations, the model parameters are estimated. The model is shown to be effective in reproducing characteristic features of the macroscopic response of both pre-cracked as well as geometries without a preexisting nominal defect. Since the model parameters are held constant for simulations at different stress-states, they are effectively material constants.