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In this paper, we develop a data-driven performance-based evaluation framework for a novel electric vertical takeoff and landing aircraft (eVTOL) in the context of Urban Air Mobility (UAM) applications. First, a two-stage comprehensive simulation framework is developed to generate a benchmark database for the performance evaluation of both UAS Traffic Management (UTM) algorithms and high-fidelity eVTOL dynamical models. In the developed simulation framework, we implement UTM algorithms and incorporate real-world constraints, e.g., vertiport infrastructures and different wind conditions. From the developed simulation framework, we generate 1,213,010 flight profiles. These flight profiles are used in a model based eVTOL performance evaluation tool as inputs to compute the physical performance of 3 types of eVTOLs. Due to the high computational cost of model-based eVTOL performance evaluation approaches, a clustering-based sampling procedure is employed to reduce the redundancy in the generated flight profiles and utilize the re-sampled flight profiles to form an eVTOL performance analysis dataset. We then train and compare several machine learning models on the eVTOL performance analysis dataset to predict: performance variables-flight conditions, aerodynamic coefficients, aircraft electronics, electric motor and propeller efficiencies. Finally, we deploy the proposed data-driven models in the framework and reduce the eVTOL performance inference time to real-time. The implementation of the proposed framework can be found on GitHub: https://github.com/mrinmoysarkar/eVTOL_performance_evaluation.git

Orthogonal frequency division multiplexing (OFDM) is considered as one of the most significant transmission methodologies of the recent past. Moreover, it permits easy demodulation and modulation. To find the new OFDM-based waveform to be used in fifth generation which is one of the foremost open issues for wireless networks of the next generation. In addition, the OFDM is affected by the maximum Peak-to-Average Power Ratio (PAPR). In order to minimize these problems, this paper proposed a Twin Symbol Hybrid Optimization used as a basis of the Partial Transmit Sequence (TSHO-PTS) method of Cyclic Prefix-OFDM (CP-OFDM). This CP-OFDM achieves the requirements of 5G telecommunication standards. Moreover, the exhaustive searching for optimal phase factors might increase the computational cost of PTS. To beat this problem, a hybrid version of slap swarm optimization (SSO) and Bald Eagle Search (BES) algorithm is introduced to investigate the phase factor optimally by the PTS method. Digital chaotic sequences are used to ensure the physical layer security during the data transmission scheme for the Discrete Fourier Transform Spread OFDM (DFT-S-OFDM) subcarrier allocation. The simulation takes place in the MATLAB platform, and the performances are evaluated by several performance metrics like Complementary cumulative distribution function (CCDF), Bit Error Rate (BER), and computational complexity. The performance of the proposed model is compared with various existing approaches and previous works. From the implemented results, the proposed strategy achieved less (5 dB) PAPR, minimum (10–8) BER, less processing time (0.18 s) than the existing schemes, and hence the complexity also very low (7%) than others.

Fifth generation systems are required to fulfill the objectives like compatibility, flexibility, high speed data rate and low cost. Universal Mobile Telecommunication System (UMTS) use WCDMA as the air interface for 4th generation mobile system. The performance of wireless communication system is often limited by the radio channel models. In urban areas, channel is modeled as Rayleigh fading channel. This channel causes multipath channels and other problems resulting degraded performance. Hence, channel estimation before receiver helps to receive the transmitted signal using rake receiver. Rake receiver is a conventional receiver for DS-CDMA system. In this, channel is estimated adaptively using LMS algorithm and performance of this algorithm is studied for various multipath channels and step sizes. Moreover, the channel introduces Inter Symbol Interference (ISI) and channel equalizers are used to compensate for the ISI. In this work, BER vs. SNR performance of Zero Forcing Equalizer (ZFE), Minimum Mean Square Error (MMSE) and MMSE- Decision Feedback Equalizer (MMSE-DFE) in WCDMA downlink system are compared with conventional rake receiver for various spread factors in Rayleigh multipath fading channel with Additive White Gaussian Noise.

Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical, but also very challenging and risky. Despite first responders putting their lives at risk in saving others, human-physical limits cause delays in response time, resulting in fatality and property damage. In this paper, we proposed and implemented a framework intended for creating collaboration between heterogeneous unmanned vehicles and first responders to make search and rescue operations safer and faster. The framework consists of unmanned aerial vehicles &#x0028 UAVs &#x0029 , unmanned ground vehicles &#x0028 UGVs &#x0029 , a cloud-based remote control station &#x0028 RCS &#x0029 . A light-weight message queuing telemetry transport &#x0028 MQTT &#x0029 based communication is adopted for facilitating collaboration between autonomous systems. To effectively work under unfavorable disaster conditions, antenna tracker is developed as a tool to extend network coverage to distant areas, and mobile charging points for the UAVs are also implemented. The proposed framework&#x02BC s performance is evaluated in terms of end-to-end delay and analyzed using architectural analysis and design language &#x0028 AADL &#x0029 . Experimental measurements and simulation results show that the adopted communication protocol performs more efficiently than other conventional communication protocols, and the implemented UAV control mechanisms are functioning properly. Several scenarios are implemented to validate the overall effectiveness of the proposed framework and demonstrate possible use cases.

In this paper, we propose a data-driven testing and evaluation framework for multi-UAVs to evaluate their performance in executing missions in the physical world. Seven micro-behaviors, termed here as modes of operation, are leveraged to describe the autonomous functionalities of the UAVs. These functionalities are then used to design five scenarios for model training, validation and testing of the proposed framework. Each scenario includes a distinct sequence of behaviors for the UAVs in order for the different autonomous functionalities to be evaluated. We develop and implement a simulation environment using the Robot Operating System (ROS), Gazebo, and the Pixhawk autopilot to generate synthetic data for the training of a classification model. This trained model is then utilized to evaluate the behaviors of the UAVs while performing real-world missions. Finally, the proposed framework is tested using synthetic data generated from a simulation environment and validated using real-world data.

In this paper, a novel technique is presented to test the flight of an unmanned aerial vehicle autonomously in a real-world scenario using a data-driven technique without intervening with its onboard software. With the growing applications of such vehicles, testing of autonomous flight is a very important task for rapid deployment. There are different tools for modeling and simulating unmanned vehicles in virtual worlds such as Gazebo, MATLAB, Simulink, and Webots to name a few. None of these simulation tools are able to model all possible physical parameters of a real-world environment. Hence, the flight controller or mission planning software has to be tested in the physical world in the presence of an expert before deployment for a specific task. A Perception Inference Engine evaluation tool is presented that can infer internal states of the autonomous system from external observations only. The Gazebo simulation platform is used to collect data to develop the perception model. For real-time data collection, a VICON motion capture system is used to observe the autonomous flight of a small unmanned aerial vehicle. A state-of-the-art decision tree algorithm is used to implement the data-driven approach. The technique was tested using simulation data and verified with real-time data from Intel Aero Ready to Fly and Parrot AR. 2.0 drones. Moreover, we analyzed the robustness of the proposed system by introducing noise in sensor measurement and ambiguity in the testing scenario. We compared the performance of the decision tree classifier with Naive bayes and support vector machine classifiers. It is shown that the developed system can be used for the performance evaluation of a UAV operating in the physical world by significantly reducing uncertainty in mission failure due to environmental parameters.

Decreasing the peak‐to‐average power ratio (PAPR) is a great challenge for data communication using OFDM. Here is introduced a new hybrid optimized partial transmit sequence (PTS) for minimizing the PAPR, where data encryption is done with 4D DFT-based hyper-chaotic sequence. An innovative hybrid seagul optimization and salp swarm (HSOSS) optimization are proposed here to produce a phase weight factor for the PTS. Several sizes of the subcarrier are investigating the new approaches performance. The proposed model is implemented in MATLAB platform and performances are calculated with factors like bit error rate (BER) with respect to signal-to-noise ratio(SNR), PAPR complementary cumulative distribution function (CCDF) in regard to SNR, and the finally, based on the computation time, final results are compared.

Twenty different batches of gels containing metaxalone and diclofenac potassium were prepared for topical application. These drugs act synergistically in the management of pain and inflammation. Gels were prepared by varying the type of gelling agent (ten batches each of hydroxyl propyl methyl cellulose and carbopol 934). The prepared gels were characterized and evaluated. Batch F7 emerged as the best batch on the basis of favourable pH, high drug content, homogeneity and drug release. HPLC (High-performance liquid chromatography) method validation of gel formulation was also carried out and the developed and validated method was found to be robust and accurate.

System security is a basic aspect of data sharing. Aspires have been made to exhaust particular defects over the web. For this, different creative usage and security methods have been made. The measure of information exchange isn't a factor. The major factor is, how much it's secure, the channel gives while transmitting information. Cryptography is one such structure, which grants secure information transmission without losing its protection and uprightness. In light of the key circulation, cryptography is also assembled into two critical forms Symmetric Key Cryptography as well as Asymmetric Key Cryptography. RSA is one of the best conspicuous public-key cryptography based algorithms is unequivocally utilized for encryption/decryption. It's far based on the logical arrangement of factorization of strongly enormous whole numbers which is a compute-intensive way. In this paper, we have provided a novel, secure and profitable information communication system dependent on the RSA algorithm. Mystery updating signal dealing with systems have been proposed in the exploration for the two data transmission and the channel estimation stages. The proposed one facilitates the advantages of both RSA calculation and One Time Password (OTP) produced by the sender and got just by the endorsed customer. Despite that not at all like conventional RSA algorithm, in this work we embrace perfect key assurance by particle swarm optimization (PSO) during both encryption and decryption. The use of PSO for perfect key decision makes the general technique proficient by extending the security level and making the computation procedure very easy.

During sudden anti-terrorist drives conducted by the law enforcement agencies, a localized cyber security system happens to be a special tactic to avert the unprecedented massacre and gruesome fatalities against the residents of that area by disconnecting the affected territory from the rest of the world; so that the militants and their outside accomplices cannot communicate with each other and also the terrorists cannot go through the ongoing apprehensive operation via wireless communications. This paper presents a novel framework of an unmanned aerial vehicular networking signal jammer which is oriented to block incoming and outgoing signals of all frequencies transmitted from a specifically marginalized territory scanned and explored by the aerial vehicle. During such a cyber-vigilance operation, the aerial vehicle is equipped with a transmitter and an auto-tuning band-pass filter module with automatic regulation of center frequencies according to the surrounding networking signals, which are considered to be the suppressing noise parameters. In order to restrict the signal blocking operation within the militant hub, the aerial vehicle with the network terminator is controlled to navigate within a particular boundary of a residential area and its navigation is continuously mapped and stored for effective evacuation process directed to save the innocent stranded people. A very low frequency (VLF) metal detector has been designed to trace the explosives and buried landmines inside the exploration arena. An algorithm for 3-D mapping of the metal traces detected by the aerial navigator has been presented in this paper. Signal blocking, metal tracing and stable confined movements have been tested where the testbed is provided with signals of different frequencies along with variation in dimensions of the testing region to evaluate the reliability of the proposed framework.

Ability of red grape juice (RGJ), a known antioxidant, on testis of adult Wister rat to protect from oxidative stress induced damages by heat stress has been investigated in this study. Heat stress was induced maintaining body and testicular temperature at 43°C for 30min/day for 15 days using a hyperthermia induction chamber. Four groups of rats (n=6 per group) comprising of Group-I (control) -kept at 32°C, Group-II -exposed to heat stress alone, Group-III received RGJ (0.8ml/rat/day) alone and Group-IV -exposed to heat stress and received RGJ at same dose. Analysis of blood and testicular tissue exhibited significant reduction in serum testosterone, testicular superoxide dismutase, testicular catalase and testicular glutathione (all p < 0.001); whereas, significant rise in the level of serum corticosteroid, testicular lipid peroxidase and the apoptotic enzyme caspase-3 of testis (all p < 0.001) were observed along with substantial increase in testicular Hsp72 and Hsf-1, and decrease in 17β-HSD3 were noted in heat stressed rats compared to controls. In Group-IV rats, RGJ administration could restore these parameters to normal levels. The signs of retention were clear in Group-IV rats and found to be significantly different as compared to that of the Group-II rats. In testicular histology of rats exposed to heat stress alone revealed remarkable germ cell degeneration and tubular deformations which were prevented by RGJ treatment (Group-IV). The reduced number of sperm level in Group-II also restored in RGJ treatment (Group-IV). The above results indicate that consumption of RGJ may substantially protect testis from heat stress induce dysfunctions.

We report a case of dengue fever in a 9-years old Indian child. She was given “anti-hyper thermic” drug paracetamol and anti-biotic amoxicillin for 5 days. The patient was detected with dengue infection (NS1 positive) with a 5 days history of high fever and headache. After scrutinizing the haematology data, the medications (paracetamol & amoxicillin) were stopped and only diet which was continued is fruit juices (pomegranate and sweet lime juices along with green coconut water) as nutritional supplement. After 48 hours of continuous administration of nutritional supplements, blood parameters showed immense change. From this case study it can be stated that, infection with dengue and subsequent decline in the platelet and leukocyte count can well be restored with pomegranate, sweet lime and green coconut water. Keywords: Dengue, Pomegranate, Sweet Lime, Green Coconut Water

In recent years Unmanned Aerial Vehicles (UAVs) have progressively been utilized for wildfire management, and are especially in prevalent in forest fire monitoring missions. To ensure the fast detection and accurate area estimation of forest fires, a two-step search and survey algorithm for multi-UAV system is proposed to address these fire scenarios. Initially, a grid-based partition method is applied to divide the area-of-interest into several search areas. Then, an archetype search pattern is used to provide timely UAV exploration within those sub-areas. Once the fire zones are detected, a novel survey strategy is employed for UAVs to discover the boundary points of the fire zones, so that the area of the fire zones can be estimated using the sampled boundary points. In addition, the effect of wind is accounted for improving fire zone boundary estimates. The proposed search-and-survey procedure is validated on multiple simulated scenarios using the U.S. Air Force’s mission-realistic Aerospace Multi-Agent Simulation Environment (AMASE) software. Simulation results showcase that the proposed search pattern can effectively discover the seeded fire zones within 40 min of the mission. This is relatively faster than the other two well-known search patterns. Moreover, the proposed survey technique provides a coverage estimate with at least 85% accuracy for the area of interest within 90 min of the mission.

Background The pentacyclic lupane-type (6-6-6-6-5 type) triterpenoid, Betulinic acid (BA) is a potent inhibitor of topoisomerases and is of immense interest as anticancer drugs. However, the compound being highly lipophilic, has limited in vivo uptake capacity. BA derivatives with halogen substituent at C-2 have improved membrane permeability and cytotoxicity against cancer cells. Aim The halogenated triterpenoid, 2α-bromo-dihydrobetulonic acid (B1) was synthesized from betulinic acid (BA) isolated from Bischofia javanica . Aim of the study was to determine whether B1 could act as a more efficient inhibitor of Topo IIα activity and HeLa cell proliferation, in comparison to BA. Result B1 displayed efficient inhibition of DNA relaxation activity of topoisomerase IIα and the inhibitory effect was markedly improved upon pre-incubation of the compound with enzyme. Topoisomerase IIα inhibition by B1 was relieved in presence of increasing concentrations of DNA suggesting the compound as a reversible catalytic inhibitor. Subsequent UV and fluorescence spectroscopy studies indicated that B1 interacts and intercalates with DNA at concentrations signicantly greater than that required for topoisomerase IIα inhibition. The compound showed cytotoxic activity against HeLa cells with significantly lower IC 50 value (7.5 μM) as compared to that of BA (30 μM) and had very low damaging/cytotoxic effect on normal cells. Treatment of B1 impaired HeLa cell proliferation by inducing Go-G1 arrest through lowered expression of cyclin D1 and PCNA polypeptides, and enhanced expression of p21. B1 treatment also increased the accumulation of early and late apoptotic cells in a concentration dependent manner as indicated by annexin V-FITC/PI binding assay.

Maintaining a healthy glycaemic condition is associated with so many more other protective/precautionary attributes. Recent advancement in the field of drug discovery have led us find more and more options to choose from. DPP-4 inhibitor sitagliptin makes sustained expression of incretins GLP-1 and GIP that in turn establishes glycaemic control. But recent reports claimed pro-inflammatory as well as pro-carcinogenic action of the drug after prolonged use in T2DM patients. Interestingly, in those cases also, the effector molecule responsible is said to be the incretin GLP-1. The same molecule has been hypothesized for being responsible to cause thyroid C-cell carcinomas. In vitro investigations using human cell lines did not show any clues in support of carcinoma formation. Instead, the DPP-4 inhibitory action of sitagliptin serves in other complications associated with T2DM. In any tissue injury due to hypoxic stress in T2DM, sitagliptin serves in the tissue repair mechanisms via its DPP-4 inhibiting property. Consequently, DPP-4, for not being able to be active in presence of sitagliptin, fails to truncate the CXCL-12/SDF-1 and therefore helps in the homing of HPCs/EPCs to repair the injured tissue. In conclusion, it can be said that more research is definitely required to be confirmed about the pre-cancerous activity of the drug, and to make the drug more usable in favour of the other beneficial effects of it.

Electrical network frequency (ENF) is a signature of a power distribution grid. It represents the deviation from the nominal frequency (50 or 60 Hz) of a power system network. The variations in ENF sequences within a grid are subject to load fluctuations within that particular grid. These ENF variations are inherently located in a multimedia signal, which is recorded close to the grid or directly from the mains power line. Thus, the specific location of a recording can be identified by analyzing the ENF sequences of the multimedia signal in absence of the concurrent power signal. In this article, a novel approach to location-stamp authentication based on ENF sequences of digital recordings is presented. ENF patterns are extracted from a number of power and audio signals recorded in different grid locations across the world. The extracted ENF signals are decomposed into low outliers and high outliers frequency segments and potential feature vectors are determined for these ENF segments by statistical and signal processing analysis. Then, a multi-class support vector machine (SVM) classification model is developed to verify the location-stamp information of the recordings. The performance evaluations corroborate the efficacy of the proposed framework.

This paper presents an autocorrelation-based double talk detection (DTD) system with a modified normalized least mean squares (NLMS) adaptive filter algorithm for acoustic echo cancellation (AEC). Autocorrelation value of the residual error derived from the difference between the microphone signal and the echo estimation determines the existence of double talk in the speech signal. The algorithms for DTD and adaptive filter for AEC have been tested in terms of probability of missing detection, fraction of times of missing near-end signal and probability of false detection to verify the convergence of the echo canceler in the presence of a near-end signal. The proposed system has been simulated on MATLAB and an application code has been compiled for Xtensa DSP processor. The test results corroborate the reliability of the developed algorithms.

This paper presents a predictive model to compute regional power demand on an hourly interval using regression decision tree machine learning algorithm. The training dataset has been derived from a zone wise hourly load supplied record of power grid company of Bangladesh limited (PGCB) for three regions-Dhaka, Chittagong and Rajshahi for six consecutive days in March, 2018. A regression decision tree based predictive model has been developed for substantial load forecasting application. Computing power data time instants ahead from a historical dataset conforms to an efficient tool for maintaining a balance between demand and supply along with for making preparedness in case of a contingency. The regression algorithm yields to without and with pruning applications to evaluate performance. The predictive model has been simulated on MATLAB and the performance assessments corroborate the reliability of the framework.