Erratum to: Conductivity Sensors Based System Development and Application to Investigate the Interfacial Behaviour between Supersonic Steam Jet and Water

Instruments and Experimental Techniques - An Erratum to this paper has been published: https://doi.org/10.1134/S0020441221050249     

Multi-dimensional Security Range Query for Industrial IoT

The Internet of Things (IoT) has allowed for significant advancements in applications not only in the home, business, and environment, but also in factory automation. Industrial Internet of Things (IIoT) brings all of the benefits of the IoT to industrial contexts, allowing for a wide range of applications ranging from remote sensing and actuation to decentralization and autonomy. The expansion of the IoT has been set by serious security threats and obstacles, and one of the most pressing security concerns is the secure exchange of IoT data and fine-grained access control. A privacy-preserving multi-dimensional secure query technique for fog-enhanced IIoT was proposed in light of the fact that most existing range query schemes for fog-enhanced IoT cannot provide both multi-dimensional query and privacy protection. The query matrix was then decomposed using auxiliary vectors, and the auxiliary vector was then processed using BGN homomorphic encryption to create a query trapdoor. Finally, the query trapdoor may be matched to its sensor data using the homomorphic computation used by an IoT device terminal. With the application of particular auxiliary vectors, the spatial complexity might be efficiently decreased. The homomorphic encryption property might ensure the security of sensor data and safeguard the privacy of the user's inquiry mode. The results of the experiments reveal that the computing and communication expenses are modest.     

Mining the Chatbot Brain to Improve COVID-19 Bot Response Accuracy

People often communicate with auto-answering tools such as conversational agents due to their 24/7 availability and unbiased responses. However, chatbots are normally designed for specific purposes and areas of experience and cannot answer questions outside their scope. Chatbots employ Natural Language Understanding (NLU) to infer their responses. There is a need for a chatbot that can learn from inquiries and expand its area of experience with time. This chatbot must be able to build profiles representing intended topics in a similar way to the human brain for fast retrieval. This study proposes a methodology to enhance a chatbot's brain functionality by clustering available knowledge bases on sets of related themes and building representative profiles. We used a COVID-19 information dataset to evaluate the proposed methodology. The pandemic has been accompanied by an “infodemic” of fake news. The chatbot was evaluated by a medical doctor and a public trial of 308 real users. Evaluations were obtained and statistically analyzed to measure effectiveness, efficiency, and satisfaction as described by the ISO9214 standard. The proposed COVID-19 chatbot system relieves doctors from answering questions. Chatbots provide an example of the use of technology to handle an infodemic.     

Marinobacter lipolyticus from Red Sea for lipase production and modulation of silver nanomaterials for anti‐candidal activities

In this study, the bacterial strain CEES 33 was isolated from the coastal area of the Red Sea, Jeddah, Kingdom of Saudi Arabia. The bacterium isolate was identified and characterized by using biochemical and molecular methods. The isolate CEES 33 has been identified as Gram‐negative rod shaped and cream pigmented spherical colonies. It also demonstrated a positive result for nitrate reduction, oxidase, catalase, citrate utilization, lipase and exopolysaccharide production. Strain CEES 33 was characterized at the molecular level by partial 16S rRNA sequencing and it has been identified as Marinobacter lipolyticus (EMBL|{"type":"entrez-nucleotide","attrs":{"text":"LN835275.1","term_id":"824555294"}}LN835275.1). The lipolytic activity of the isolate was also observed 2.105 nkatml⁻¹. Furthermore, the bacterial aqueous extract was used for green synthesis of silver nanoparticles (AgNPs), which was further confirmed by UV‐visible spectra (430 nm), XRD and SEM analysis. Moreover, the biological functional group that involved in AgNPs synthesis was confirmed by FTIR spectra. The biological activities of AgNPs were also investigated, which showed a significant growth inhibition of Candida albicans with 16 ± 2 mm zone of inhibition at 10 μg dose/wells. Therefore, bacterium Marinobacter lipolyticus might be used in future for lipase production and nanoparticles fabrication for biomedical application, to control fungal diseases caused by C. albicans.Inspec keywords: enzymes, molecular biophysics, biochemistry, silver, nanoparticles, nanofabrication, nanomedicine, antibacterial activity, biomedical materials, ultraviolet spectra, visible spectra, Fourier transform infrared spectra, microorganisms, reduction (chemical), RNA, molecular configurations, X‐ray diffraction, scanning electron microscopy, diseasesOther keywords: lipase production, silver nanomaterial modulation, anticandidal activities, bacterial strain CEES 33, bacterial isolate, biochemical method, molecular method, gram‐negative rod shaped colonies, cream pigmented spherical colonies, nitrate reduction, oxidase, catalase, citrate utilisation, exopolysaccharide production, molecular level, partial 16S rRNA sequencing, Marinobacter lipolyticus strain EMBL|{"type":"entrez-nucleotide","attrs":{"text":"LN835275.1","term_id":"824555294"}}LN835275.1, lipolytic activity, bacterial aqueous extract, green synthesis, UV‐visible spectra, X‐ray diffraction, scanning electron microscopy, biological functional group, AgNPs synthesis, Fourier transform infrared spectroscopy, Candida albicans, media plate, industrial lipase production, biomedical application, fungal diseases, wavelength 430 nm, Ag     

MMSPEED: multipath Multi-SPEED protocol for QoS guarantee of reliability and. Timeliness in wireless sensor networks

In this paper, we present a novel packet delivery mechanism called Multi-Path and Multi-SPEED Routing Protocol (MMSPEED) for probabilistic QoS guarantee in wireless sensor networks. The QoS provisioning is performed in two quality domains, namely, timeliness and reliability. Multiple QoS levels are provided in the timeliness domain by guaranteeing multiple packet delivery speed options. In the reliability domain, various reliability requirements are supported by probabilistic multipath forwarding. These mechanisms for QoS provisioning are realized in a localized way without global network information by employing localized geographic packet forwarding augmented with dynamic compensation, which compensates for local decision inaccuracies as a packet travels towards its destination. This way, MMSPEED can guarantee end-to-end requirements in a localized way, which is desirable for scalability and adaptability to large scale dynamic sensor networks. Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliability and timeliness requirements up to 50 percent (12 flows versus 18 flows).     

Characterization of the 3Dimension optical,geometrical, and mechanical profiles of iPP fiber with necking deformation

We present a method for evaluating the 3D refractive indices and 3D true stress and/or 3D true strain profiles of “isotactic polypropylene iPP” fibers during necking deformation. Observing the changes in geometrical shape during the deformation process is necessary to understand the mechanical performance of iPP fibers. 3D geometric shape profile and actual stress and strain profiles were measured for iPP fibers during the propagation of neck deformation. These measurements were performed with the aid of an in‐situ opto‐ mechanical device to dynamically characterize different properties of fibers at different strain rates. A software image analysis program was used to calculate the 3D opto‐mechanical properties of iPP fibers. The obtained results show that the used dynamic stretching device can be easily used to monitor the deformation process with high accuracy. The effective stress and strain can be determined from the filaments profile. For illustration microinterferograms are given.     

Deep Trajectory Classification Model for Congestion Detection in Human Crowds

In high-density gatherings, crowd disasters frequently occur despite all the safety measures. Timely detection of congestion in human crowds using automated analysis of video footage can prevent crowd disasters. Recent work on the prevention of crowd disasters has been based on manual analysis of video footage. Some methods also measure crowd congestion by estimating crowd density. However, crowd density alone cannot provide reliable information about congestion. This paper proposes a deep learning framework for automated crowd congestion detection that leverages pedestrian trajectories. The proposed framework divided the input video into several temporal segments. We then extracted dense trajectories from each temporal segment and converted these into a spatio-temporal image without losing information. A classification model based on convolutional neural networks was then trained using spatio-temporal images. Next, we generated a score map by encoding each point trajectory with its respective class score. After this, we obtained the congested regions by employing the non-maximum suppression method on the score map. Finally, we demonstrated the proposed framework’s effectiveness by performing a series of experiments on challenging video sequences.     

Modeling and Simulation of Two Axes Gimbal Using Fuzzy Control

The application of the guided missile seeker is to provide stability to the sensor's line of sight toward a target by isolating it from the missile motion and vibration. The main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling approach. The paper is started by deriving the mathematical model for gimbals motion using Newton's second law, followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors and sensors using MATLAB/SimMechanics. Then, a Mamdani-type fuzzy and a Proportional-Integral-Derivative (PID) controllers were designed using MATLAB software. The performance of both controllers was evaluated and tested for different types of input shapes. The simulation results showed that self-tuning fuzzy controller provides better performance, since no overshoot, small steady-state error and small settling time compared to PID controller.