Showing papers by "Government College published in 2022"

Optimising the Eu2O3 concentration and tuning the photoluminescence attributes of Eu2O3 doped borate glasses by Co–doping with silver nanoparticles

Abstract: Efficacy of silver nanoparticles on photoluminescence properties on optimized Eu2O3 doped borate glasses has been studied and discussed in detail. The presence of homogeneously distributed and spherically shaped Ag nanoparticles was confirmed by electron microscopic images. With increase of AgNO3 concentration the photoluminescence intensity of Eu3+ transitions improved up to 0.6 mol% and subsequently quenched at 0.8 mol% of AgNO3. The enhancement in photoluminescence properties observed as the AgNO3 concentration raised to higher level was ascribed to local field effect and transmit of energy from Ag nanoparticles to the tri–positive europium ions. While the reduction in photoluminescence properties at higher doping level of AgNO3 was attributed to reverse transmit of energy from tri–valent europium ions to Ag nanoparticles. Other mechanisms liable for the attenuation in photoluminescence properties are also highlighted. The energy transfer from Eu3+ ions to Ag0 nanoparticles was responsible for the reduction in radiative lifetime magnitudes. The studies suggest the glass sample containing 0.6 mol% of AgNO3 (i.e. SNBEuAg0.6) beneficial for optoelectronic and photonic applications.

Investigation of digital video broadcasting application employing the modulation formats like QAM and PSK using OWC, FSO, and LOS-FSO channels

Abstract: The optical communication system is preferred over microwave and radio frequency communication systems because of license free operation. Simulative analysis of 10gbps bandwidth using different optical communication channels have been performed in this paper. The different modulation formats of QAM and PSK have been compared for its performances under all the three optical channels OWC, FSO, and LOS-FSO which are an unguided form of optical communication. The optical channels under these modulation formats are extensively used in Digital Video Broadcasting Communication. The parameters such as Q-factor, BER and Eye height can be obtained by varying the wavelengths in the range of 850 nm 1064 nm, 1330 nm and 1550 nm. From the design and performance analysis, the system with the maximum Q-factor and minimum BER can be found for the wavelength of 1064 nm.

Optical constants, optical dispersion and group index parameters of Mn2O3 thin films

Abstract: In this work, we report on the diverse optical parameters of Mn2O3 thin films prepared by nebulized spray pyrolysis technique by the effect of spray solution concentration. X-ray diffraction study confirmed the Mn2O3 films belong to cubic structure. The Raman vibrational band observed at 636 cm−1 is related with the symmetric stretching of Mn–O bond of trivalent manganese ions (Mn3+). The surface morphological study showed that the nano-sized particles are homogenously distributed on the film surface. The films exhibit the highest transmittance in the near infrared region. The spray solution concentration induced reduction of Urbach energy (from 677 to 655 meV) indicates the decrease in degree of crystal defects in the film. The extinction coefficient of the film was obtained in the order of 10−2. It was observed that the optical dispersion threshold point (TODT) of Mn2O3 thin film is coincides with the refractive index threshold wavelength (λrtw) of the material. This was further corroborated from the intersection of phase velocity and group velocity curves at the point of λrtw or TODT. This indicates that no optical dispersion was taken place at that point and therefore the phase velocity is equal to the group velocity. The possible correlations among the data were made with the light of underlying concepts.

Upconversion, MRI imaging and optical trapping studies of silver nanoparticle decorated multifunctional NaGdF4:Yb,Er nanocomposite.

Abstract: The multifunctional upconversion nanoparticles (UCNPs) are fascinating tool for biological applications. In the present work, photon upconverting NaGdF4:Yb,Er and Ag nanoparticles decorated NaGdF4:Yb,Er (NaGdF4:Yb,Er@Ag) nanoparticles were prepared using a simple polyol process. Rietveld refinement was performed for detailed crystal structural and phase fraction analysis. The morphology of the NaGdF4:Yb,Er@Ag was examined using high-resolution transmission electron microscope, which reveals silver nanoparticles of 8 nm in size were decorated over spherical shaped NaGdF4:Yb,Er nanoparticles with a mean particle size of 90 nm. The chemical compositions were confirmed by EDAX and inductively coupled plasma-optical emission spectrometry analyses. The upconversion luminescence (UCL) of NaGdF4:Yb,Er at 980 nm excitation showed an intense red emission. After incorporating the silver nanoparticles, the UCL intensity decreased due to weak scattering and surface plasmon resonance effect. The VSM magnetic measurement indicates both the UCNPs possess paramagnetic behaviour. The NaGdF4:Yb,Er@Ag showed computed tomography imaging. Magnetic resonance imaging study exhibited better T1 weighted relaxivity in the NaGdF4:Yb,Er than the commercial Gd-DOTA. For the first time, the optical trapping was successfully demonstrated for the upconversion NaGdF4:Yb,Er nanoparticle at near-infrared 980 nm light using an optical tweezer setup. The optically trapped UCNP possessing paramagnetic property exhibited a good optical trapping stiffness. The UCL of trapped single UCNP is recorded to explore the effect of the silver nanoparticles. The multifunctional properties for the NaGdF4:Yb,Er@Ag nanoparticle are demonstrated.

Internet of Things Based Best Fruit Segregation and Taxonomy System for Smart Agriculture

Abstract: The Internet of Things (IoT) playing an important role in every sector. The use of number of IoT devices becomes double every year. Smart agriculture is evolving as a need. Automation is playing an important role in agriculture sector. The quality, growth, and productivity of yield is increased due to automation. Manual segregation of fruits decreases the quality. A lot of time is wasted in grading of fruits. As sorting being one of the most important industrial challenge, a reliable segregation and taxonomy system is needed. In the proposed system, by using the multiple processed algorithmic photos, the system will recognize suitable things on the basis of its color, look, size and the amount of damage. System will provide good kind of photo that can provide facility for packing to the farmers if they want to. By the assistance of preparing and analyzing pictures, the system will find the items dependent on its shading, surface, size, and deformities. The procedure will provide a higher caliber of the image with a reason to help comparatively for bundling the items in ventures. The utilization of raspberry pi together with the sensor and flapper instrument, the method of programmed bundling will enhance the nature of outcomes in a higher manner. Right from plucking to packing all things are connected with the IoT which helps to perform tasks more smoothly, timely and improves the connectivity between different units of smart agriculture. The proposed system is more reliable, efficient and gives better performance as compared to existing one.

Effect of number of quantum wells on modulation and distortion characteristics of transistor laser

Abstract: Numerical analysis on the effect of number of quantum wells (QW) on the modulation and distortion characteristics of 1300 nm Transistor Laser (TL) is reported. The terminal currents are found by using triangular charge model in the base region. The parameters such as threshold current and optical power are analyzed from the DC characteristics for different number of quantum wells. Modulation depth, frequency response are determined by providing an ac input signal with dc bias offset. It is found that the modulation depth decreases for increasing the number of quantum wells and input bias current under CE and CB configuration respectively. From this analysis, the Transistor Laser bandwidth, resonance frequency are estimated for different number of quantum wells and a maximum bandwidth of 27.5 GHz and 44.3 GHz for 25Ith are observed under CE and CB configurations respectively. Further, the distortion characteristics such as second harmonic and intermodulation products are analyzed at 2.4 GHz band for Radio over Fiber applications. The magnitude of 2HD and IMD3 components are found to decrease for increase in number of quantum wells and bias current under both CE and CB configurations. A minimum value of magnitude of 2HD components is obtained as −27.58 dBc at 25IBth and −17.82 dBc at 1.8IEth under CE and CB configuration respectively for six quantum wells in the transistor laser. Similarly, minimum value of IMD3 magnitude is obtained as − 40.47 dBc at 25IBth and − 36.91 dBc at 1.8IEth under CE and CB configuration respectively. A maximum Spurious Free Dynamic Range of 58.85 dB-Hz2/3 is predicted at 10IEth for four number of quantum wells under CE configuration.

Fog-Computing: A Novel Approach for Cloud-Based Devices Using Perceptual Cloning Manifestation-PerColNif Taxonomy by Energy Optimization

Abstract: Computing Paradigms on the Cloud-platform has become an integral service of computing devices that uses internet and big data as the core platform, Computation of big-data under the cloud structure has an emerging need to support the time-sensitive applications over the existing intelligence services. Increase in volume of load leads to increased latency time and reduces the overall efficiency of the services due to access delay. Hence a systematic architecture is proposed for time-line based emergency services to bridge the two platforms namely cloud-server and the edge devices by supporting computational task through fog-cloning over the multiple Cloud Servers and their by ensuring optimal utilization of energy with improved residual sources retained. A novel taxonomy is proposed as a part of minimizing energy consumed through perceptual cloning which aids in identifying time-sensitive data using the location-awareness in the areas not limiting to Military applications, Health Monitoring equipments, Accident Detection Process, etc., thus the latency time of network bandwidth is efficiently reduced with increased resource availability and ensuring improved the quality of service.

Execution Improvement of Intrusion Detection System Through Dimensionality Reduction for UNSW-NB15 Information

Abstract: Computer security is a significant issue in the present networking conditions. These days, with the improvement of Web advances administrations on the planet, the gatecrashers have been expanded promptly. Consequently, the need for an intrusion detection system (IDS) framework in the security of the organization field keeps interlopers from approaching the data. IDS is a gadget or programming application that screens the organization or framework for malevolent action or strategy infringement and sends caution to framework and managers at a legitimate time. IDS screens both inbound and outbound traffics and is used to recognize potential interruptions. In this article, IDSs are assembled utilizing machine learning (ML) methods. IDSs dependent on ML techniques are viable and exact in identifying network assaults. In any case, the presentation of these frameworks diminishes for high-dimensional information spaces. It is necessary to perform a fitting component extraction strategy that can prune a portion of the highlights that does not have an incredible effect in the characterization cycle. Feature choice is expected to choose the ideal subset of highlights that delivers to the whole dataset to expand the precision and the characterization execution of IDS. In this work, the UNSW-NB15 interruption discovery dataset is examined to prepare and test the models. Additionally, a covering-based element is applied to decrease the strategy by utilizing the SVM-RFE calculation for IDS to choose the best subset of highlights. At that point, the two ML approaches are executed to utilize the diminished component space such as decision tree and support vector machine (SVM). The outcomes exhibited that the support vector machine RFE-based component determination strategy takes into consideration techniques; for example, the decision tree is build to test the exactness from 98.89 to 99.99% for the twofold order plot. The investigation results affirmed the adequacy of the proposed feature determination strategy in improving organization IDS.

Regulation of plant defense against biotic stressors by brassinosteroids

Abstract: Brassinosteroids (BRs) are steroidal phytohormones that play a multitasking role during the growth and development period as well as stress responses. Plant mutants in BR production or defective signaling result in various physiological as well as phenotypical abnormalities. Presently, various studies have highlighted stress tolerance induction by brassinosteroids in various plant species indicating BRs as a broad spectrum key regulator participating in various molecular processes. The present chapter highlights the studies on BRs regarding their potent role in inducing stress tolerance during viral, fungal, bacterial or nematode attacks in plants. BR's multifaceted role during stress and its potential cross-talk with other phytohormones in adapting and ameliorating the stress have been critically analyzed. The divergence in dosage of BR analogs and their mode of application for management of stress are also discussed which serves as a future area of interest in challenging agriculture, thereby highlighting relevant knowledge gaps.

Optimal and Higher Order Sliding Mode Control for Systems with Disturbance Rejection

Abstract: This paper presents the higher order sliding mode control for a typical unstable process to maintain the system’s stability with disturbance rejection. The control of uncertainty and distance rejection is a difficult task in control engineering applications. The literature found that non-linear uncertain systems have been studied by different researchers in the control engineering field. In this paper second-order integral sliding mode control (SMC) surface is chosen to derive the value of switching surface control. The proposed controller design depends on the calculation of poles of the systems irrespective of stable or unstable poles and gives practical value for the control input signal, and it is implemented for the system’s nominal model. In the optimal controller, the computed values of gains from systems poles are used to derive the one of SMC law. In the presented work, the system’s unstable or stable poles give the proper value for the control input signal. The proposed technique’s significant advantages include disturbance rejection, insensitivity to variation in plant variables, and implementation issues. The simulation results show an advantage over the designed SMC approach to stabilize the system and its output responses.

Implementation of TLBO Optimised PI λ D μ Controller for LFC of Nonlinear Reheat Thermal Power System

Abstract: This article explains the load frequency control (LFC) of dual area interlinked reheat type thermal plant including nonlinearities such as generation rate constraint (GRC) and governor dead band (GDB) by employing fractional order proportional integral derivative (PIλDμ) controller. A PID controller is also separately implemented for performance comparison. The parameters corresponding to both the controllers are fine-tuned by application of a teaching learning based optimisation (TLBO) algorithm using integral time absolute error (ITAE) as the fitness function. A comparative performance analysis is accomplished between the two types of controllers by injecting an instantaneous load of 10% in area-1. It is seen that the TLBO optimised PIλDμ controller yields better transient response when compared with the other controller. Lastly, the robustness of the TLBO optimised PIλDμ controller is verified by applying a randomly varying step load in area-1.

Co-ordination Control of Hybrid AC/DC Micro Grid Using High Frequency Transformer

Abstract: A Micro grid is a group of interconnected loads and distributed energy resources within a clearly defined electrical boundaries that act as a single controllable entity with respect to the grid. In AC and DC Micro grids multiple reverse conversions are required in an individual AC/DC loads. This may add additional losses to the system operation and make current home and office appliances more complicated. As a result, system co-ordination becomes too difficult in conventional micro grid. To overcome this drawbacks, hybrid micro grid which is an integral part of the smart grid is the most suitable solution to provide for the increasing penetration of DC-compatible energy sources, storage and loads which is recently prevalent in all Electric Power Industries. One of the most important feature of hybrid micro grid is advanced structure which can facilitate the connection of various AC, DC generation systems with optimal asset utilization and operation efficiency. It consists of both AC and DC networks connected together by multi bi-directional converters. AC sources and loads are connected to the AC networks. Similarly DC sources and loads are connected to the DC networks. Energy storage system can be connected to the DC or AC links. In this paper DC/DC converter with High frequency transformer is used to replace a normal conventional bulky transformer for bus voltage matching and galvanic isolation. Among different DHFT topologies, CLLC-TYPE has been suggested for its bidirectional power flow, seamless transition and low switching losses. DHFT open-loop control has been performed to simplify the systematic co-ordination and provide a smooth power transfer between AC/DC links. It has been designed in order to maximize the conversion efficiency and minimize the output voltage variations in different load conditions. Thus the hybrid micro grid has been simulated and analyzed using Simulink in MATLAB.

Numerical Study of Twisted Tape with Circular Cutout and Triangular Cutout in a Circular Tube

Abstract: Every industry has one common instrument that is heat exchanger. From a bike to a solar desalination plant that is spread in acres, heat exchangers are regular signtings. But sometimes they lack in their performance, to overcome which many accessories are used. Diverse method to improve the thermophysical performances is twisted wires and twisted tapes. A literary analysis has been conducted in this study on the application of twisted tape with air, nanofluid and water as working fluids, along with numerical analysis of simple twisted tape. In the current numerical analysis, Simple Twisted Tape (STT), Triangular Cutout Twisted Tape (TCTT) and Circular Cutout Twisted Tape (CCTT) have been compared and the relationship Reynolds number, Heat transfer, Outlet Temperature and pressure has been studied.

Estimation of Sundarban Reserve Forest Using Self-organizing Maps and Remote Sensing Data

Abstract: The present study quantifies the classification and change detection of the Sundarban forest from 1975 to 2018 using self-organizing neural network with the help of remote sensing data and GIS. The satellite data has been classified using self-organizing maps (SOM) and classes are healthy vegetation, unhealthy vegetation, wet land, and water bodies. Here, SOM method is used for classification of satellite images because the performance of this method is better as compared with the other existing classification techniques. Study revealed that overall forest areas were gradually decreased by around 2.47% (55.57 km2) from 1975 to 2018. On the other hand, other geographical features also proportionally changes. The performance of image classification is assessed by using overall accuracy and Kappa statistic. In this study, overall accuracy (88.91%, 89.32%, 90.32%, 89.93%, and 92.17%) and Kappa statistic (0.85, 0.86, 0.87, 0.86, and 0.89) were found for the images in the year of 1975, 1990, 2000, 2010, and 2018 respectively. The change detection outcomes show the decrease in forest areas was converted into the open land, and water bodies. Therefore, this study may helpful for the decision and policy makers to protect the natural forest ecosystem of the Sundarban delta.