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An Efficient Quantum Transfer Learning for Cancer Prediction Using Tumour Markers: New Era of Computer in Medical
Ovarian cancer prediction models or algorithms estimate a person's risk of getting the disease based on different variables, such as their medical history, genetics, and biomarkers. Early identification and intervention will enhance patient successive diagnosis outcomes. Tumour markers are chemicals frequently detected in higher concentrations than usual in cancer patient's blood, urine, or tissues. They could be certain chemicals or proteins linked to the presence of tumours or cancer kinds. Tumour markers are employed for diagnosis, prognosis, and treatment response monitoring. Applying information or models from one quantum job to enhance the performance of another requires quantum transfer learning. Transferring knowledge from one domain to another seeks to increase learning effectiveness in novel quantum contexts. The main goal of efficient Quantum Transfer Learning (QTL) is to minimize the resources (computer power, data, or time) necessary to transfer between tasks successfully. In this research work, QTL is used to predict Ovarian Cancer (OC) with the assistance of biomarkers. The Quantum Transfer Learning- Ovarian Cancer (QTL-OC) achieves 93.78% accuracy and outperforms the existing techniques. 2023 IEEE. -
An efficient reconfigurable band tuning filter design for channelizer in transponder satellite system
For improved performance in a variety of applications, the transponder in satellite systems must be very flexible. The channelizer-dependent transponder system significantly boosts the operation of a satellite system. When channelizing wideband input signals, a digital filter bank is typically used to extract several small sub-bands. In this research, a reconfigurable band tuning (RBT) design for the channelizer in the satellite transponder system is designed and implemented. Cosine modulation, exponential modulation and IFIR filter are the techniques behind the RBT design. The RBT design facilitates the generation of many channels enabling channelization with non-uniform narrow transition width. A number of examples are presented to illustrate how well the RBT design performs. Findings indicate that there are fewer filter coefficients in the RBT design than there are in the current approaches Effective implementation of a properly designed RBT design lowers power consumption and simplifies the hardware. 2024 The Franklin Institute -
An Efficient Routing Strategy for Energy Management in Wireless Sensor Network Using Hybrid Routing Protocols
In these days, Wireless Sensor Networks (WSN) shows a huge impact on all appliances but one of the huge challenges in WSN is management of energy because the nodes in the network run with battery power. As the replacement of energy drained nodes is difficult, and frequent failure of links may occur and it incurs huge data loss. To avoid this issue the we proposed a Hybrid Krill Herd and Spider Monkey with Grid-Based Data Dissemination (HKHSM-GBDD) protocol with the Shortest Energy Resourceful Routing (SERR) mechanism to develop an efficient and better wireless communication channel. The presented HKHSM framework is utilized to classify malicious and energy drained nodes in earlier stage and to detect the link failure. Furthermore, the SERR mechanism is processed to recover the link and route maintenance. This novel proposed protocol has improved packet delivery ratio and energy consumption. It also enhances energy state of sensor nodes by mounting its lifetime and rerouting. Finally, the competence of the proposed mechanism is compared with existing works and it shows significant improvement over existing algorithms for the considered parameters. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
An efficient scheme for water leakage detection using support vector machines (SVM)-Zig
Water is one of the most essential and valuable resources for all living beings, yet in the present day, there is a scarcity of it. Half of the water loss in large cities and industries is due to leaks and illegal lines. 10%-20% of water loss can be reduced by detecting leaks but without the presence of advanced monitoring systems, this problem is typically worsened. Monitoring the consumption and leak detection for such large areas is a challenging task. To overcome this issue a small prototype is prepared called Zig. Zig is designed for both household and industrial purposes. Its main aim is to monitor the flow and consumption of water at different levels of a building like a first-floor and so on which may represent some industrial and household situation. This work focuses on pressure/flow monitoring method to reduce the operational cost and also to detect leakage. One of the machine learning algorithms, Support Vector Machines (SVM) has been applied to detect the leakage and it is compared with Random Forest algorithm to show that proposed scheme is detecting water leakage better. BEIESP. -
An Efficient Security-Enabled Routing Protocol for Data Transmission in VANET Using Blockchain Ripple Protocol Consensus Algorithm
The security quality in Vehicular Ad-hoc NETworks (VANET) has improved as a result of recent developments in Intelligent Transportation Systems (ITS). However, within the current VANET system, providing a cheap computational cost with a high serving capability is a significant necessity. When a vehicle user goes between one Roadside Unit (RSU) to another RSU region in the current scenario, the current RSU periodically needs re-authentication of the vehicle user. This increases the computational complexity of the system. The gathering and broadcast of existing traffic event information by automobiles are critical in Vehicular Ad-hoc Networks (VANET). Traditional VANETs, on the other hand, have several security concerns. This work develops a blockchain-based authentication protocol to address the aforementioned difficulty. To address critical message propagation issues in the VANET, we invent a novel type of blockchain. We develop a local blockchain for exchanging real-world event messages among cars within a countrys borders, which is a novel sort of blockchain ideal for the VANET. We describe a public blockchain RPCA that records the trustworthiness of nodes and messages in such a distributed ledger suitable for secure message distribution. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
An Efficient Sorting Algorithm for Capacitor Voltage Balance of Modular Multilevel Converter With Space Vector Pulsewidth Modulation
Thisarticle presents an efficient analogue sorting algorithm for balancing the submodule (SM) capacitor voltages of modular multilevel converter (MMC). The proposed analogue sorting algorithm offers the advantage of fast convergence rate without any need of recursive loops for the implementation on embedded devices. It can be easily implemented with combinational logic operations on field programmable gate array (FPGA) and provides less hardware and computational overhead. The functionality and performance of the proposed analogue sorting algorithm is evaluated with the simulation model of three phase five-level MMC in MATLAB/Simulink environment. The real time implementation of the proposed sorting algorithm with the SM capacitor voltage balancing strategy is implemented on Altera/Cylone - I (EP1C12Q240C8N) FPGA. A five-level continuous space vector pulsewidth modulation (CSVPWM) is realized on a PIC microcontroller (PIC18F452). A down-scaled model of single-phase five-level MMC is designed and constructed to investigate the reliable and stable operation of MMC with the proposed analogue sorting algorithm and SVPWM method. Simulation and experimental results are presented for validation. 1986-2012 IEEE. -
An efficient technique for generalized conformablePochhammerChree models of longitudinal wave propagation of elastic rod
In this article, we introduce analytical-approximate solutions of time-fractional generalized Pochhammer-Chree equations for wave propagation of elastic rod by means of the q-homotopy analysis of the transform method (q-HATM). In the Caputo sense, basic concepts for fractional derivatives are defined. Several examples are given and the results are illustrated via some surface plots to present the physical representation. The results show that the current methodology is productive, powerful, efficient, easy to use, and ready to incorporate a wide variety of partial fractional differential equations. 2022, Indian Association for the Cultivation of Science. -
An Efficient Technique for One-Dimensional Fractional Diffusion Equation Model for Cancer Tumor
This study intends to examine the analytical solutions to the resulting one-dimensional differential equation of a cancer tumor model in the frame of time-fractional order with the Caputo-fractional operator employing a highly efficient methodology called the q-homotopy analysis transform method. So, the preferred approach effectively found the analytic series solution of the proposed model. The procured outcomes of the present framework demonstrated that this method is authentic for obtaining solutions to a time-fractional-order cancer model. The results achieved graphically specify that the concerned paradigm is dependent on arbitrary order and parameters and also disclose the competence of the proposed algorithm. 2024 The Authors. -
An efficient technique to analyze the fractional model of vector-borne diseases
In the present work, we find and analyze the approximated analytical solution for the vector-borne diseases model of fractional order with the help of q -homotopy analysis transform method ( q -HATM). Many novel definitions of fractional derivatives have been suggested and utilized in recent years to build mathematical models for a wide range of complex problems with nonlocal effects, memory, or history. The primary goal of this work is to create and assess a Caputo-Fabrizio fractional derivative model for Vector-borne diseases. In this investigation, we looked at a system of six equations that explain how vector-borne diseases evolve in a population and how they affect community public health. With the influence of the fixed-point theorem, we establish the existence and uniqueness of the models system of solutions. Conditions for the presence of the equilibrium point and its local asymptotic stability are derived. We discover novel approximate solutions that swiftly converge. Furthermore, the future technique includes auxiliary parameters that are both trustworthy and practical for managing the convergence of the solution found. The current study reveals that the investigated model is notably dependent on the time chronology and also the time instant, which can be effectively studied with the help of the arbitrary order calculus idea. 2022 IOP Publishing Ltd. -
An Efficient Underwater Image Restoration Model for Digital Image Processing
Digital image processing (DIP) is showing a massive growth intodays trending world particularly, in the field of biological research. Underwater image analysis plays a vital role, where the images are easily prone to attenuation and haziness. Capturing underwater images has always been a challenging job due to dispersion and scattering of light inside water on a high scale. Several image enhancement and restoration methodologies are currently available to address these issues, where hazing and color diffusion are viewed as a common phenomenon in it. Such procedures normally includes two basic methodologies in it, namely dehazing and contrast or color enhancement, which improves the overall output of the degraded image. However, the quality and processing time of the images can still be enhanced with additional techniques incorporated to it. This work is intended toward proposing one such channel called improvised bright channel prior for dehazing the underwater images. The technique further improves on the existing methodologies by estimating the atmospheric light and refining the transmittance of the image along with image restoration. The experimental results show that the improvised bright channel prior methodology is found to perform better in dehazing underwater images with a balanced intensity in terms of dark and white patches obtained from it. When comparing and contrasting the processing time of the proposed methodology with the existing techniques, it is found that improvised bright channel prior performs better. Also, the quality of the dehazed underwater image obtained from the proposed channel is found to be effective when compared with the existing channels. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
An Efficient Wireless Sensor Network based Intrusion Detection System
Wireless Sensor Networks (WSNs) are widely used in diverse applications due to their cost-effectiveness and versatility. However, they face substantial difficulties because of their innate resource constraints and susceptibility to security attacks. A possible method to improve the security of WSNs is clustering-based intrusion detection and responding mechanisms. An in-depth analysis of the clustering-based intrusion detection and response method for WSNs is presented in this study. The suggested method efficiently uses data mining and machine learning techniques to identify unusual behaviour and probable intrusions. The system effectively analyses data inside clusters by grouping Sensor Nodes (SN) into clusters, allowing it to differentiate between legitimate patterns and insecure activity. The network may respond promptly to identified breaches and react to the responsive mechanism, which reduces their impact and protects network integrity. The proposed Mathematically Modified Gene Populated Spectral Clustering Based Intrusion Detection System and Responsive Mechanism (MMMMGPSC-IDS-RM) is compared with existing state-of-art techniques, and MMMMGPSC-IDS-RM outperforms with the highest detection rate of 96%. 2023 IEEE. -
An efficient ZnO and Ag/ZnO honeycomb nanosheets for catalytic green one-pot synthesis of coumarins through Knoevenagel condensation and antibacterial activity
This study pioneers the synthesis of porous Ag/ZnO nanosheets, focusing on their role as a catalyst in Knoevenagel condensation. Notably, these nanosheets display exceptional catalytic efficacy and captivating antibacterial properties. The research delves into the Ag/ZnO catalyst's recyclability and proposes a potential reaction mechanism, marking the first comprehensive exploration of Knoevenagel condensation on porous Ag/ZnO nanosheets. Key findings underscore the successful synthesis of coumarin derivatives using various o-hydroxy benzaldehyde and 1,3-dicarbonyl compounds, with nano-Ag/ZnO serving as a catalyst via a monomode microwave-assisted approach. X-ray diffraction (XRD), Field Emission Scanning Electron Microscopy (FE-SEM), Transmission Electron Microscopy (TEM) and UV-Vis spectroscopy were used in conjunction with other physicochemical methods to characterize the synthesized catalytic samples. The method boasts advantages such as high product yields, brief reaction durations, and the ability to reuse the catalyst for multiple cycles. The Ag/ZnO nanosheets, functioning as an acid catalyst, activate carbonyl groups and facilitate their interaction with methylene-containing active molecules. In addition, antibacterial activity assessments demonstrate the superior effectiveness of Ag/ZnO nanocomposites compared to ZnO nanosheets against Staphylococcus aureus germs. This multifaceted study not only advances catalytic synthesis but also unveils promising biological applications of porous Ag/ZnO nanosheets. 2024 Walter de Gruyter GmbH, Berlin/Boston 2024. -
An electrochemical sensor for nanomolar detection of caffeine based on nicotinic acid hydrazide anchored on graphene oxide (NAHGO)
A simple modified sensor was developed with nicotinic acid hydrazide anchored on graphene oxide (NAHGO), by ultrasonic-assisted chemical route, using hydroxy benzotriazole as a mediator. Structural and morphologies of NAHGO samples were investigated in detail by Fourier-Transform Infrared spectroscopy (FT-IR), Powder X-ray diffraction (P-XRD), Raman spectroscopy, Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and Thermogravimetric analysis (TGA). The detailed morphological examination and electrochemical studies revealed the delaminated sheet with the tube-like structure of NAHGO provided the route for more electroactive surface which influenced the electrooxidation of caffeine with increased current. The electrochemical behaviour of NAHGO on a glassy carbon electrode (GCE) for caffeine detection was demonstrated by employing voltammetric techniques. The influence of scan rate, pH, and concentration on caffeine's peak current was also studied. The NAHGO sensor was employed for the determination of caffeine in imol plus and energy drinks. The detection limit determined was 8.7 109M, and the best value was reported so far. The results show that NAHGO modified electrodes are one of the best preferences to establish new, efficient, and reliable analytical tools for the detection of caffeine. 2021, The Author(s). -
An empirical analysis of android permission system based on user activities
In today's world there has been an exponential growth among smart-phone users which has led to the unbridled growth of smart-phone apps available in Google play store, app store etc., In case of android application, there are many free applications for which the user need not shell out a penny to use the services. Here the magic word is "free" which entices millions of pliant people into installing those apps and giving unnecessary access to their data and device control. Current studies have shown that over 70% of the apps in market, request to gather data digressive to the most functions of apps that might cause seeping of personal data or inefficient use of mobile resources. Of late, couple of malignant applications gather unobtrusive information of the user through third-party applications by increasing their permissions to high-level on the Android Operating System. Android permission system provides, the user access to the third party apps and in return based on the permissions granted by the user, an app can access the related resource from the user's mobile. A user is bound to grant or deny permits during the installation of the application. For the most part, users don't focus on the asked permissions, or sometimes users do not understand the meaning of the permission and install the app on their device. They allow a way for attackers to perform the malicious task by demanding for more than expected set of permissions. These extra permissions permit the attacker to exploit the device and also retrieve sensitive information from it. In this research paper we describe how permission system security can create an awareness among the users that would assist them in deciding on permission grants. This improved and responsible user activities in Android OS can help the users in utilizing their device securely. 2018 Ankur Rameshbhai Khunt and P. Prabu. -
An Empirical Analysis of Factors and Variables Influencing Internet Banking among Bangalore Customers
International Journal of Research in Computer Application & Management, Vol. 2, Issue 10, pp. 143-148, ISSN No. 2231-1009 -
An empirical analysis of ICT tools with gamification for the Indian school education system
Information and communication technologies (ICTs) are used as a part of different fields, for example, training, business, and healthcare. The main objective of this paper is to introduce ICT as a better method to teach and test student's performance so it can become a part of the school curriculum and enhance learner's experience. To accomplish this objective, multiple kinds of literature were studied to get insights into the factors associated with ICT and gamification. Based on the findings, a survey was conducted on teachers to know the favourability of ICT in modern schools. Based on the response, two application prototypes are developed for students to get their performance and results that support the study. Most importantly, similar concepts were taught to students using both, traditional and ICT based approaches. A test was conducted via both methods. It was discovered that the performance of the students increased by 13% when the modern approach was followed to conduct the test. Copyright 2021 Inderscience Enterprises Ltd. -
An empirical analysis of price discovery in spot and futures market of gold in India /
Pacific Business Review International, Vol.7, Issue 10, pp.80-88 -
An empirical analysis of similarity measures for unstructured data
With fast growth in size of digital text documents over internet and digital repositories, the pools of digital document is piling up day by day. Due to this digital revolution and growth, an efficient and effective technique is required to handle such an enormous amount of data. It is extremely important to understand the documents properly to mine them. To find coherence among documents text similarity measurement pays a humongous role. The goal of similarity computation is to identify cohesion among text documents and to make the text ready for the required applications such as document organization, plagiarism detection, query matching etc. This task is one of the most fundamental task in the area of information retrieval, information extraction, document organization, plagiarism detection and text mining problems. But effectiveness of document clustering is highly dependent on this task. In this paper four similarity measures are implemented and their descriptive statistics is compared. The results are found to be satisfactory. Graphs are drawn for visualization of results. 2019 COMPUSOFT, An international journal of advanced computer technology. -
An empirical analysis of similarity measures for unstructured data /
An International Journal of Advanced Computer Technology, Vol.8, Issue 8, pp.3302-3306, ISSN No: 2320-0790. -
An empirical analysis of sustainability of public debt among BRICS nations
The main objective of this paper is to verify the sustainability of public debt among Brazil, Russia, India, China and South Africa (BRICS) in a political economy framework. Annual panel data have been used for BRICS countries from World Development Indicators of World Bank for the period 19802017 for the analysis. Bohn's sustainability framework is used to examine the sustainability of public debt in BRICS nations and verify the influence of political economic variables such as election year, coalition dummy, ideology of the government and unemployment on public debt sustainability. The results suggest that public debt sustainability is weak for BRICS as a whole. China and India have a better public debt sustainability coefficients compared to the same for Brazil, Russia and South Africa. Structural change dummy included in the model suggests that debt sustainability is severely affected after the 2008 crisis period. Political factors have influence on debt sustainability in BRICS. Electoral cycle year and coalition dummy variables adversely affect public debt sustainability in BRICS. While centrist political ideology is found to be significant and negative, left and right ideologies are not significant for debt sustainability. Since debt sustainability is found to be weak in BRICS, countries in the region need to adopt necessary measures to improve their primary balance through appropriate fiscal and debt management. Besides, it is important for the governments to prioritize fiscal prudence irrespective of their ideologies and political compulsions. 2020 John Wiley & Sons, Ltd