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Cat Swarm Optimization Algorithm Tuned Multilayer Perceptron for Stock Price Prediction
Due to the nonlinear and dynamic nature of stock data, prediction is one of the most challenging tasks in the financial market. Nowadays, soft and bio-inspired computing algorithms are used to forecast the stock price. This article assesses the efficiency of the hybrid stock prediction model using the multilayer perceptron (MLP) and cat swarm optimization (CSO) algorithm. The CSO algorithm is a bio-inspired algorithm inspired by the behavior traits of cats. CSO is employed to find the appropriate value of MLP parameters. Technical indicators calculated from historical data are used as input variables for the proposed model. The model's performance is validated using historical data not used for training. The model's prediction efficiency is evaluated in terms of MSE, MAPE, RMSE and MAE. The model's results are compared with other models optimized by various bio-inspired algorithms presented in the literature to prove its efficiency. The empirical findings confirm that the proposed CSO-MLP prediction model provides the best performance compared to other models taken for analysis. 2022 Polish Academy of Sciences. All rights reserved. -
Performance comparison of artificial neural network techniques for foreign exchange rate forecasting
Artificial Neural Networks is one of the promising techniques for forecasting financial time series markets and business. In this paper, Radial Basis Function is used to forecast the daily foreign exchange rate of USD in terms of Indian rupees in India during the period 2009-2014. Here, seven technical indicators like simple moving average of one week, Two week, Momentum, Price rate of change, Disparity 7, Disparity 14, Price oscillator are proposed as inputs for forecasting the time series. In addition, this study compares the four models namely Pattern Recognition Networks, Feed Forward Back Propagation Networks, Feed Forward Networks with no feedback, and Radial Basis Function Network to forecast the daily currency exchange rate during the period. The performance of all these models are analysed from accuracy measures namely Mean Square Error, Mean Absolute Error, Sum Square Error and Root Mean Square Error. From the simulation results, the average performance of Radial Basis Function network was found considerably better than the other networks. Research India Publications. -
Forecasting of foreign currency exchange rate using neural network
Foreign exchange market is the largest and the most important one in the world. Foreign exchange transaction is the simultaneous selling of one currency and buying of another currency. It is essential for currency trading in the international market. In this paper, we have investigated Artificial Neural Networks based prediction modelling of foreign exchange rates using five different training algorithms. The model was trained using historical data to predict four foreign currency exchange rates against Indian Rupee. The forecasting performance of the proposed system is evaluated by using statistical metric and compared. From the results, it is confirmed that the new approach provided an improve technique to forecast foreign exchange rate. It is also an effective tool and significantly close prediction can be made using simple structure. Among the five models, Levenberg-Marquardt based model outperforms than other models and attains comparable results. It also demonstrates the power of the proposed approach and produces more accurate prediction. In conclusion, the proposed scheme can improve the forecasting performance significantly when measured on three commonly used metrics. -
Crude oil prediction using a hybrid radial basis function network
In the recent years, the crude oil is one of the most important commodities worldwide. This paper discusses the prediction of crude oil using artificial neural networks techniques. The research data used in this study is from 1st Jan 2000- 31st April 2014. Normally, Crude oil is related with other commodities. Hence, in this study, the commodities like historical datas of gold prices, Standard & Poors 500 stock index (S & P 500) index and foreign exchange rate are considered as inputs for the network. A radial basis function is better than the back propagation network in terms of classification and learning speed. When creating a radial basis functions, the factors like number of radial basis neurons, radial layers spread constant are taken into an account. The spread constant is determined using a bio inspired particle swarm optimization algorithm. A hybrid Radial Basis Function is proposed for forecasting the crude oil prices. The accuracy measures like Mean Square Error, Mean Absolute Error, Sum Square Error and Root Mean Square Error are used to access the performance. From the results, it is clear that hybrid radial basis function outperforms the other models. 2005 - 2015 JATIT & LLS. All rights reserved. -
Nanocarbon assisted green hydrogen production: Development and recent trends
The increasing consumption of energy and consequent fast depletion of fossil fuels and associated environmental challenges necessitate transformative innovations in the field of energy conversion. Owing to its exceptional energy density and zero emissions during combustion, Hydrogen is hailed as a promising source of clean and renewable energy that can replace fossil fuels in future energy conversion systems. Since Hydrogen is not readily available in the atmosphere, a variety of pathways have been followed for the evolution of Hydrogen from water and organic materials, which requires the involvement of catalysts to accelerate the reactions. Currently, noble metals and their alloys represent state-of-the-art materials for HER (Hydrogen Evolution Reaction), and the scarcity and high expense of such materials impose significant constraints on their widespread implementation in hydrogen production. In this context, nanocarbons and their composites for HER are worth exploring owing to their abundance, cost-effectiveness, eco-friendliness, exceptionally large surface-to-volume ratio, and excellent electrical and charge transfer properties. Here, three leading hydrogen production methods - biological, electrochemical, and photo-driven- are analyzed based on their characteristics, effectiveness, and limitations w.r.t. different nanocarbon materials. 2023 Hydrogen Energy Publications LLC -
Psychological capital and innovative work behaviour: The role of mastery orientation and creative self-efficacy
Continuous innovation is what helps companies survive the highly discontinuous competition. Securing innovative work behaviour from employees has drawn the attention of businesses and researchers alike. The current work draws on broaden-and-build theory and goal orientation theory to propose how an individual's psychological capital, which is malleable, helps in achieving innovative work behaviour from employees. The study has been conducted in the context of three-star hotels located in and around New Delhi, the capital of India. The data was collected using standard scales from a dyad of 229 employees and their managers. The present study enriches the innovative work behavior literature by combining different perspectives in a coherent framework and demonstrates the partially mediated positive relationship of psychological capital and innovative work behavior via mastery orientation. Also, the study reveals that the partially mediated indirect effect varies among employees based on their level of CSE. 2022 Elsevier Ltd -
Agriculture 4.0 and smart farming: Imperatives of scaling up innovation and farmer capabilities for sustainable business
Smart agriculture adoption during industry 4.0 is creating new scenarios to farmers across the world. Smart farming promotes not only an increase in the agricultural productivity and incomes, but also building resilience to climate change. Small business farmers had to look at all possible means to cope with the technology applications for implementation of agro-transformation agendas for improved production and business performance. Smart farmers have to make use of several technology applications like drones and satellites, IoT (Internet of Things) based sensors, block chain and big data, biotech, farm maintenance technology (optimising water usage, production, and innovation technology) for better agricultural practices. Though such aggrotech opportunities have demonstrated business improvements, how far such smart farming revolution is well received by the agribusiness owners are less researched into. Henceforth, the purpose of this research is to establish the relationship between aggrotech innovation capabilities and farmer's capabilities associated with agriculture firms and its contributions to business performance. Following cross-sectional descriptive study design, and purposive sampling, the study addressed 3 direct and 2 indirect relationships in the model, on 212 farmers. The data was collected from Selangor state of Malaysia. The study applied Smart PLS SEM to analyse the data. The results show that the innovation (technology) capability and farmer's (people) capability have a positive relationship on business performance. The study also shows the partial mediation effect of technology change on innovation capability and business performance as well as employee capability and business performance. The study is novel in its form by applying Resource Based View theory on Smart agriculture, extending possibilities of generalization agriculture sector. 2021 Ecological Society of India. All rights reserved. -
Design of body wearable antenna for medical monitoring devices
In this research work, an inset fed microstrip patch antenna, an analysis of its effect on human body and human body influence on antenna performance are presented. Polystyrene substrate (?r= 2.6) with a 1 mm thickness is used to create the proposed antenna. Use of HFSS Ver. 18.2 is made for simulations. The simulated antenna exhibits S11 of -37.4 dB in the absence of human arm and -28.39 dB in the presence. Similar to this, the SAR findings showed that the Specific Absorption Rate (SAR) value obtained is 1.28 W/kg, which is significantly less than the allowed standard of 2 W/kg, when the suggested antenna is set at an offset of 2 mm off the body's surface. Hence the proposed antenna can be suitable for integrating with medicalmonitoring devices. 2024 Author(s). -
Antenna Array with Non-Uniform Excitation and DNG Hybrid Metasurface for Next Generation Communication Equipment
This paper presents an approach for designing a hybrid metasurface array with nonuniform excitation. The proposed design features a unique feed network with minimal use of Quarter Wave Transformers (QWT's) to reduce the form-factor. The impedance matching between the feed network and the patch is achieved by adjusting the inset position and the gap between the patch and the feed. The metasurface consists of a hybrid metamaterial unit cell with five Split Ring Resonators (SRRs) on the bottom and a hexagonal ring made of six triangles on the top surface improves the bandwidth, gain and directivity of the proposed design. Equivalent circuit of the proposed array is modeled using ADS software. A prototype 1x4 array with metasurface is designed for a resonant frequency of 2.4 GHz and fabricated. A high gain of 9.46 dB with a -10 dB impedance bandwidth of 110 MHz is achieved, which amounts to an improvement of 16.36% gain and 31.58% bandwidth compared to conventional uniform excitation array. In terms of overall size, the proposed array antenna is reduced by 38.05% compared to traditional 1x4 microstrip array. 2021 IAMOT. All Rights Reserved. -
A Slotted Circular Patch Antenna with Defected Ground for Sub 6 GHz 5G Communications
In this paper, a slotted circular patch antenna with Defected Ground Structure (DGS) is presented. The slots created on radiating element and the defect introduced on the ground plane shifted the resonance frequency from 2.49 GHz to 1.17 GHz. This corresponds to 53% reduction in size at 1.17 GHz. The proposed antenna is designed on FR-4 substrate (r=4.4) with thickness of 1.6 mm. Simulations are carried out using HFSS Ver. 18.2. The simulated reflection coefficient of Circular Patch Antenna (CPA) at 2.49 GHz, Slotted Circular Patch antenna (SCPA) at 2.34 GHz and Slotted Circular Patch antenna with Defected Ground Structure (SCPA-DGS) at 1.17 GHz are - 28.7 dB, -31.33 dB and -11.03 dB respectively. For validating the simulated design, SCPA-DGS is fabricated and measured its reflection coefficient and VSWR using Vector Network Analyzer (Anritrsu S820E). The measured and simulated values are very well matched with each other. Therefore the proposed antennas may be used in sub 6 GHz 5G communication applications. 2022 IEEE. -
A miniaturized antenna array for direct air-to-ground communication of aircrafts
In this paper, a miniaturized, high directivity low-cost antenna array is presented. The uniqueness of the proposed array (PA) exists in the feed mechanism designed using Dolph-Chebyshev non-uniform excitations. Authors simulated the designed antenna array using ANSYS EM 18.2 (HFSS) software and characterization is carried out in a fully established anechoic chamber. The simulated array antenna is operating at 2.4 GHz with a gain of 8.12 dB and a reflection coefficient of -28.45 dB having a bandwidth of 110 MHz. On contrast with the traditional array (TA), PA exhibits enhanced resonance characteristics by maintaining the same radiation characteristics. The bandwidth is increased by 37.5%, maintaining the same gain of 8.12 dB. In contrast, there is a remarkable reduction in the size compared to the traditional corporate feed array antenna with non-uniform excitation. The overall size of the PA antenna is 242.5 mm 58.8 mm, which is 33.73% less compared to the TA. Published under licence by IOP Publishing Ltd. -
Performance analysis of optimized corporate-fed microstrip array for ISM band applications
This paper presents a low cost high gain corporate feed rectangular microstrip patch antenna array of two elements having cuttings at the corners, with detailed steps of design process, operates in Industrial Scientific Medical (ISM) band (2.4 GHz). The proposed antenna structures are designed using FR4 dielectric substrate having permittivity ?r= 44 and substrate thickness of 1.6 mm. The gain of these simulated antennas are obtained as 2.4819 dB with return loss of -17.779 dB for a single element patch and 6.3128 dB with return loss of -15.8320 dB for an array of two elements. The simulations have been carried out by using Antenna simulator HFSS version 15.0.0 to obtain the VSWR, return loss and radiation pattern. 2017 IEEE. -
Reflector Backed Conical Dielectric Resonator Antenna with Enhanced Gain
This paper reports a wideband, high gain, slot coupled reflector backed conical dielectric resonator antenna (DRA). The key findings of the work are as follows; i) the antenna operates over 7.73-8.3 GHz, with peak gain of 10.32 dBi, ii) an gain enhancement > 5dBi achieved by placing a reflector below the ground plane, iii) the measured results best matches with their measured counter parts, iv) the antenna deals with many advantages, including performance, volume, and fabrication feasibility. From application point of view the developed model can be successfully used for X-band wireless communication. 2018 IEEE. -
Inculcation of On- Campus Pet Companionship as an Animal- Assisted Therapeutic Intervention for the Psychological Well- Being of College Students
Research on developing coping strategies and therapeutic interventions is crucial for college students due to the seemingly unavoidable stressors they face as young adults. This chapter proposes the inclusion of on- campus pet companionship in higher educational institutions as an intervention to enhance distress tolerance, psychological resilience, and better- coping strategies among college students. It acknowledges existing research on pet companionship's positive effects on well- being while addressing the concerns about potential negative impacts. The study aims to explore the potential effects of pet companionship on college students, discuss methods for introducing on- campus pet companionship, and identify cost- effective and feasible approaches for implementation. 2024 by IGI Global. All rights reserved. -
A Comprehensive Research on Deep Learning Based Routing Optimization Algorithms in Software Defined Networks
Discovering an optimal routing in Software Defined Networks (SDNs) is challenging due to several factors like scalability issues, interoperability, reliability, poor configuration of controllers and security measures. The compromised SDN controller attacks at the control plane layer, packet losses in the topology and end-to-end delay are the most security risk factors in SDNs. To overcome this, in most of the existing researches, Deep Reinforcement Learning (DRL) algorithm with various optimization techniques was implemented for optimal routing in SDN by providing link weights to balance the end-to-end delay and packet losses. DRL used Deterministic Policy Gradient (DPG) method which acts as an actor-critic reinforcement learning agent that searches for an optimal policy to minimize the expected cumulative long-term reward. However, discovering an optimal routing with efficient security measures is still a major challenge in SDNs. This research proposes a detailed review of routing optimization algorithms in SDN using Deep Learning (DL) methods which supports the researchers in accomplishing a better solution for future research. 2023 IEEE. -
Effective View of Swimming Pool Using Autodesk 3ds Max: 3D Modelling and Rendering
As well as setting up the sources, working with editable poly, information in the interior of the swimming pool, using turbo-smooth and symmetry modifier, this procedure of making a 3D swimming pool model is clarified. The lighting the scene and setting up the rendering, the method in which substances are added to the replica is defined. The methods and techniques of rendering are defined, too. The final rendering is the result of multiple images being drawn. The aim of our research work is to create a swimming pool design with enhancing models with materials affect. The shapes used for that are cylinder, sphere, box, plane and splines. The modifiers are editable poly, editable spline and UVW map. Finally, we used a material editor and target lights for enhancing the model. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
An optimized technique to foster omnichannel retail experience leveraging key technology dimensions in the context of an emerging digital market
Customers approach towards shopping has transformed, as a result of their reduced tolerance, increased technology usage and being well informed than ever before. As customers expect a seamless shopping experience regardless of where they are engaged within a retailers network, the line between physical and digital retailing is blurring. Retailers across the world are contemplating on transforming into Omnichannel hubs to deliver an elevated experience anytime anywhere. And, experts have often indicated that an Omnichannel strategy delivers a unified shopping experience than a mere channel experience. However, the true Omnichannel experience is still not evident in India with minimal action in this space, indicating a subverted outlook towards building necessary Omnichannel Capabilities. This paper examines the most essential and significant technology dimensions that are imperative towards fostering a seamless Omnichannel Retail Experience. The findings of this study serve as a basis for retailers in India to evaluate their strategies towards adopting these technology dimensions and respective capabilities, using an optimized approach. The study employed a quantitative research involving survey of executives from major retailers in India. The quantitative data was analyzed applying Structural Equation Modeling, to ascertain the technology dimensions that emerged and their significance in deriving Omnichannel Retail Experience. BEIESP. -
A Comprehensive Review on Image Restoration Methods due to Salt and Pepper Noise
Digital images are well-use in various fields like satellite communication, mobile communication, medical and security. Visualized information helps the people to understand the things easily by seen. Improper capturing, age of camera lens, imperfect storage and transmission leads to introduce noise in the image. Gaussian noise, salt and pepper/impulse noise and speckle noise may affect the original image due to aforementioned reasons. Out of these, impulse noise/salt and pepper noise is one of the major types, degrades the image with black and white spots it results loss of required information. Hence, restoration of ground- truth image from such type of noisy image is a challenging task to provide quality and clarity visuals to users. Several linear and non-linear methods have been proposed by researchers since more than four decades. Nonlinear methods based on; median filtering approach; adaptive median filter approach; median filter with switching condition; and median filter with rank order type; are proposed from early 1980s onwards. All of these operated directly on pixels in spatial domain. Hence, they are very easy to implement and most of them are not that much robust at middle and higher noise density circumstances. Further, various researchers have been implemented linear methods such as wavelet transform methods like SWT and DWT. Majority of these are works well upto 50% noise density conditions and very few works well on higher and multiple noise density conditions also. To overcome these problems CNNs based methods have been developed tremendously by various researchers from last decade and these methods require huge database to train the network model. Most of these, achieved good accuracy rates at higher and multiple noise conditions. Hence, here a detailed review report is presented on impulse noise removal methods with their Peak Signal to Noise Ratio (PSNR). 2023 IEEE. -
A new trained ECG signal Classification method using Modified Spline Activated Neural Network
An ECG (Electrocardiogram) records the electrical activity of the heart and assess heart arrhythmia. Cardiac arrhythmia is an irregular heartbeat caused by unbalanced rhythm. In the past, several works were developed to produce automatic ECG-based heartbeat classification methods. In this work, a modified spline activated neural network, a new approach for cardiac arrhythmia classification by presenting the ECG signal preprocessing, the heartbeat segmentation techniques, the feature description methods and the learning algorithms used. The MIT-BIH arrhythmia database was used and experimented for testing and training. 2018 IEEE. -
Friction and wear behaviour of HVOF sprayed Cr2O3-TiO2 coatings on aluminium alloy
This study investigates the tribological behaviour of Cr2O3-TiO2 composite coatings deposited on aluminium 6061 alloy. Cr2O3-TiO2 composite coatings were deposited by high velocity oxyfuel (HVOF) technique. Developed coatings were subjected to microstructure studies, microhardness test (ASTM E92), friction and wear test (ASTM G99). Pin-on-disc machine was used to evaluate friction and wear characteristics of Cr2O3-TiO2 coatings. Effect of sliding velocity (0.314 m/s-1.26 m/s) and load (20 N-100 N) on friction and wear characteristics of Cr2O3-TiO2 coatings were studied and compared with uncoated aluminium alloy. Results showed 54% improvement in hardness of Cr2O3-TiO2 coatings in comparison with aluminium alloy. Coefficient of friction and wear rate decreases by 12% and 48% respectively when evaluated with uncoated aluminium alloy. Coefficient of friction (COF) and wear rate increases with increase in load and sliding velocity for both coatings and substrate. However, Cr2O3-TiO2 coatings showed lower wear rate and COF at all the loads and sliding velocities studied when compared with uncoated aluminium alloy. Worn out surfaces of uncoated and Cr2O3-TiO2 coated surfaces were subjected to SEM analysis to understand the wear mechanisms in composite coatings. 2021 Inderscience Enterprises Ltd.. All rights reserved.