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Transformational leadership and organizational citizenship behavior: new mediating roles for trustworthiness and trust in team leaders
This study investigates the pivotal role of trust in bridging the effects of transformational leadership on organizational citizenship behavior (OCB). The study was conducted using a multilevel longitudinal approach with 276 employees in 71 teams from private medium-sized organizations in Kuala Lumpur, Malaysia. Transformational leadership was found to be positively related to: (1) three facets of trustworthiness (ability, benevolence, and integrity); (2) trust in the leader; and (3) OCB. All three facets of trustworthiness mediated the relationship between transformational leadership and trust in leaders. In addition, trust in the leader mediated only the relationship between the benevolence facet of trustworthiness and OCB. As OCB is inherently benevolent, these findings not only are consistent with the principle of compatibility, but they also contribute to theorizing about how trust plays an important role in the influence of transformational leadership on employees. The Author(s) 2023. -
Continuous emotion estimation for human machine interaction
Humans are able to interact and bond very efficiently with other species because every living organism has some form of emotion in them. Due to the advances in science and technology human life has become more dependent on machines for better living. The recent advances in technology enabled machines to become smarter but not efficient in terms of interaction with humans. Hence to address this issue and to bridge the gap between human machine interactions we propose a system to estimate human emotions from facial expressions. We believe that facial expressions are a form of nonverbal communication and primary means of conveying information. The system uses linear regression model to calculate emotional state of a facial expression which is mapped onto continuous 2-D coordinates with arousal and valence as axis from a captured digital image. Thus the proposed method estimates emotion continuously and predictively like humans rather than classifying the emotions because emotions are continuous and they have many dimensions. By estimating emotions continuously machines can better interact with humans. Experimental results showed that our system provides superior predictive performance. 2015 American Scientific Publishers. All rights reserved. -
Effect of fiber types, shape, aspect ratio and volume fraction on properties of geopolymer concrete A review
Researchers have emphasized on sustainable construction with utilization of industrial wastes or byproducts in production of concrete. Geopolymer concrete is one of the popular construction materials which has shown promising results and potential to substitute conventional energy intensive materials such as Portland cement concrete. Further, the use of fibers has shown potential to overcome various deficiencies of geopolymer concrete. However, there are limited studies which explore the benefits of fiber reinforced geopolymer concrete and its applications. The development of fiber reinforced geopolymer concrete is relatively new construction material and has to be experimentally validated in order to increase its usage in the construction industry. As a result, this review paper is an attempt to discuss the effect of shape, type, aspect ratio and volume fraction of fibers on strength and durability properties of geopolymer concrete. From this detailed review it can be concluded that fiber reinforced geopolymer concrete enhances ductile behavior, tensile strength, toughness & energy absorption capacities. 2022 -
Durability Studies and Stress Strain Characteristics of hooked end steel fiber reinforced ambient cured geopolymer concrete
For conventional concrete, the use of fibers has proven to improve the strength properties of the material. However, in the case of ambient cured geopolymer concrete, there are limited studies that explore the application of fibers, in particular, the use of hooked end steel fibers. Further, it is important to study the durability properties of geopolymer concrete with fibers, since it will influence the service life of the structures in practice. Therefore, in the present study, fiber-reinforced geopolymer concrete was synthesized using fly ash, GGBS, hooked end steel fibers, and alkaline solution made with Na2SiO3 and NaOH. The percentage of steel fibers varied in the range of 0.5% to 2% with an increment of 0.5% by volume fraction of the binder. The precursor materials were characterized using techniques such as X-ray fluorescence (XRF), X-ray diffraction (XRD), and scanning electron microscope (SEM). Durability studies like water absorption, drying shrinkage, sulphate attack were studied. In addition, the elastic constants were determined through stress strain behaviour of geopolymer concrete in uniaxial compression. The results of the experimental study showed that the addition of hooked end steel fibers influences the strength of geopolymer concrete up to an optimal percentage, which was found to be 1%. Furthermore, in terms of durability properties, the addition of fibers exhibited better results in terms of resistance to water absorption and chemical attack, and this was validated by the microstructural studies, where the specimens with hooked end steel fibers revealed much denser hardened geopolymer matrix when compared to the mixes without fibers. Published under licence by IOP Publishing Ltd. -
Effect of hooked end steel fibers on strength and durability properties of ambient cured geopolymer concrete
Growing carbon emissions in the construction industry have warranted the use of alternative materials such as geopolymer concrete. At the same time exposure of concrete material to harsh environmental conditions has compelled to design of durable geopolymer concrete. The use of hooked-end steel fibers in conventional fiber-reinforced concrete has proven to improve its crack resistance, and thus, positively influence the durability properties of concrete structures. Nevertheless, limited studies explore the effect of hooked-end steel fibers on the strength and durability properties of ambient cured geopolymer concrete with a low NaOH content (i.e., 8 M concentration). In this study, ambient cured geopolymer concrete was prepared by fly ash, ground granulated blast furnace slag (GGBS), NaOH, Na2SiO3, manufactured sand, and natural coarse aggregates. Additionally, hooked-end steel fibers with an aspect ratio of 67 were added to the mix by volume fraction in dosages of 0 %, 0.5 %, 1 %, 1.5 %, and 2 %. The experimental results showed that the addition of fibers reduced the workability with a minimum slump of 70 mm and a maximum Vee Bee time of 8 s for mixes with 2 % steel fibers. The addition of fibers improved the compressive strength, split tensile strength, and flexural strength of geopolymer concrete, with a maximum strength of 41.44 MPa, 4.28 MPa, and 5.23 MPa at an optimum fiber dose of 1 %, respectively. Above the optimum dose, the strength of the steel fiber-reinforced geopolymer concrete (SFRGPC) was reduced. The depth of water penetration reduced in SFRGPC when compared to GPC. Moreover, the resistance to chloride ion penetration was not significantly affected by addition of steel fibers till optimum dose of 1 %. The scanning electron microscopic results revealed the positive effect of steel fibers in restricting the progression of cracks. This has resulted in smaller crack width in the SFRGPC when compared to GPC. Overall, steel fibers in optimum dose have improved the performance of geopolymer concrete and this will contribute towards low carbon material. 2023 The Authors -
BTS: Belonging and Becoming
[No abstract available] -
From Namaskara to Annyeong Questioning Where I Belong
[No abstract available] -
Importance of political cartoons to newspapers /
Political cartoons are an important part in any newspaper. Political cartoons adorn a small part of a newspaper, often in a corner. The position of this piece although small the impact is huge. A cartoon conveys a lot of information in very few words. The emotions behind the political cartoons are genuine and although harsh, are taken with a sense of humour. While incomparison editorials are, firstly for the elite masses who understand the highly intellectual content of the piece, also editorials have a tendency to be politically correct and hold back, unlike cartoons. Cartoons are generally blatant about their stand on the issue. There have been controversial cartoons like JyllandsPostenthe Mohammad cartoon and the effective yet less controversial R.K.Laxman. -
AstroSat's view of 4U 1735-44: spectral, temporal, and type I X-ray burst studies
This study utilizes the simultaneous broad-band observations of 4U 1735-44 from AstroSat, offering enhanced spectral and temporal resolution, to investigate its spectral properties, temporal behaviour, and burst characteristics. Spectral, type I X-ray burst, and temporal analyses on 4U 1735-44 were performed using AstroSat/Soft X-ray Telescope and Large Area X-ray Proportional Counter (LAXPC) observations. The hardness-intensity diagram from LAXPC-20 showed a positive correlation between hardness and intensity, with a pattern resembling the banana branch typical of atoll sources. Spectral analysis carried out in the 0.7-20.0 keV energy range, using the model combination - (), suggested a cool accretion disc truncated at a large distance from the neutron star in the system. Time-resolved spectral studies of two type I X-ray bursts detected from the source revealed evidence of photospheric radius expansion, allowing for an estimation of the source distance. Temporal analysis showed the presence of low-frequency quasi-periodic oscillation at 69 Hz (3.3 significance with more than 99 per cent confidence) and prominent noise features below 30 Hz. 2024 The Author(s). -
Blackberry gel-assisted combustion modified MgO: Sm3+ nanoparticles for photocatalytic, battery, sensor and antibacterial applications
Green synthetic methods are currently preferred in industry over other physicochemical methods. Herein, we present a facile, environmentally friendly, non-toxic approach for the fabrication of MgO using jamun fruit extract. The phytochemicals present in the fruit extract, such as kaemferol, glucoside, anthocyanins, ellagic acid, myricetin, and isoquercetin, facilitate the bio-reduction of Mg(NO3)2. Pure and Sm3+ (17 mol %) doped MgO nanomaterials were synthesized using this bio-mediated synthetic method. The structural and morphological properties of the synthesized nanomaterials were studied using Powder X-ray diffraction (PXRD), Field Emission Scanning Electron Microscopy (FE-SEM), Energy Dispersive Spectroscopy (EDS), and Diffused Reflectance Spectroscopy (DRS) techniques. The effect of Sm3+ ions on the host matrix for the photo-catalytic oxidation of Fast Orange-Red (FOR) dye was investigated under UV light irradiation. MgO: Sm3+(3 mol %) exhibited superior (94 %) degradation of the dye compared to pristine and other doped catalysts, attributed to the maximum migration of charge carriers at the catalyst's surface. Additionally, the 3 mol % Sm3+ doped MgO electrode demonstrated a smaller charge transfer resistance, indicating superior capacitive properties compared to pristine and other doped electrodes. The synthesized materials also exhibited effective bacterial activity against pathogens. This research demonstrates the potential of the synthesized nanomaterials for environmental pollution purification, as well as their utility as electrode materials for supercapacitors, batteries, sensors, and antibacterial applications. 2024 The Author(s) -
Green-Synthesized Sm3+-Doped ZnO Nanoparticles for Multifunctional Applications
The present study focuses on the green-mediated synthesis of pristine and Sm3+-doped ZnO nanoparticles using Syzygium cumini fruit extract. The prepared material was characterized by various characterization techniques. Photocatalytic degradation of a fast orange red (FOR) dye under UV light resulted in 88% degradation, with a minimal decrease (87.90%) observed even after five successive runs, indicating the stability and effectiveness of the catalyst. The enhancement in degradation efficiency is attributed to the incorporation of Sm3+ ions into the ZnO lattice. Utilizing the optimized Sm3+ (5 mol%)-doped ZnO nanoparticles, cyclic voltammetry (CV) and electrochemical impedance spectra (EIS) were performed on the prepared electrode, demonstrating the excellent CV properties; this enhancement is attributed to the modification of ZnO's redox chemistry and the alteration of charge transfer kinetics at the electrode-electrolyte interface due to the addition of Sm3+ into the ZnO structure. The antibacterial activity was performed against two pathogenic strains, i.e., Escherichia coli and Streptococcus aureus. The obtained results suggest that the prepared material holds great promise for catalytic, energy storage, antibacterial, and other multifunctional applications. 2024 Lavanya R. et al. -
Oral cancer analysis using machine learning techniques
Oral cancer staging is most required task of examining treatment and required medication for the patients. In oral cancer staging is of two types, namely, clinical and pathological. TNM (Tumor, Node, and Metastasis) staging is clinical system of predicting oral cancer stages, on the other hand Histology, p63 and podoplanin expressions are pathological staging system which is obtained after biopsy test. These staging systems are used in machine leaning techniques to analyze the different stages of oral cancer. The main aim of the paper is to classify different stages of oral cancer using machine learning techniques. The experimental work is based on clinical and pathological staging system. The data set used for this research work is based on Oral Leukoplakia. The data transformation is applied to standardize the data and the features were extracted using correlation coefficient. The extracted features were classified using Decision tree and random forest which are compared against other popular classification methods like SVM, KNN, MLP and Logistic Regression. From the experimental work, it is found that the various stage classification of oral cancer can be classified efficiently with help of Random Forest and Decision Tree. So the classification of various oral cancers can be performed with help of random forest and Decision Tree. International Research Publication House. -
A new shape of the supply chain during the COVID-19 pandemic
Purpose: The COVID-19 pandemic has created a new normal for international business (IB) activities, leaving them pondering their next steps. The decreasing effectiveness of current vaccines to protect individuals against new variants have created uncertainty on how to respond to the new waves of the COVID-19 infection. This study aims to empirically assesses how IBs perceive the unfolding challenges in the supply chain due to the pandemic and the solutions. Design/methodology/approach: The survey data is obtained from 166 logistics professionals in Hong Kong and India. Findings: The results reveal that returns on investment, logistics, delays and imports are the most affected areas. The most often recommended solutions for supply chain management (SCM) include using local manufacturing capabilities, analytics and automation, offering better customer service, providing more effective transportation means, ensuring diligence around optimization and focusing on sustainability. Originality/value: The findings of this study help to improve supply chain operations. This study also provides recommendations for changes to SCM in response to the new normal. 2022, Emerald Publishing Limited. -
Comparative Performance of LSTM and ARIMA for the Short-Term Prediction of Bitcoin Prices
This research assesses the prediction of Bitcoin prices using the autoregressive integrated moving average (ARIMA) and long-short-term memory (LSTM) models. We forecast the price of Bitcoin for the following day using the static forecast method, with and without re-estimating the forecast model at each step. We take two different training and test samples into consideration for the cross-validation of forecast findings. In the first training sample, ARIMA outperforms LSTM, but in the second training sample, LSTM exceeds ARIMA. Additionally, in the two test-sample forecast periods, LSTM with model re-estimation at each step surpasses ARIMA. Comparing LSTM to ARIMA, the forecasts were much closer to the actual historical prices. As opposed to ARIMA, which could only track the trend of Bitcoin prices, the LSTM model was able to predict both the direction and the value during the specified time period. This research exhibits LSTM's persistent capacity for fluctuating Bitcoin price prediction despite the sophistication of ARIMA. 2023, University of Wollongong. All rights reserved. -
Web mining patterns discovery and analysis using custombuilt Apriori Algorithm
International Journal of Engineering Inventions Vol.2, Issue 5,pp.16-21 ISSN No. 2278-7461 -
Deep Learning Approaches for Environmental Monitoring in Smart Cities
It introduces a novel integrated environmental monitoring system capable of doing on-the-go measurements. In metropolitan settings, air pollution is one of the most serious environmental threats to human health. The widespread use of automobiles, emissions from manufacturing processes, and the use of fossil fuels for propulsion and power generation have all contributed to this issue. Air quality predictions in smart cities may now be made using deep learning methods, thanks to the widespread adoption of these tools and their continued rapid growth. Particulate Matter (PM) with a width of less than 2.5 m (PM2.5) is one of the most perilous kinds of air pollution. To anticipate the hourly gauge of PM2.5 focus in Delhi, India, we utilized verifiable information of poisons, meteorological information, and PM2.5 fixation in the adjoining stations to make a spatial-worldly element for our CNN-LSTM-based deep learning arrangement. According to our experiments, our 'hybrid CNN-LSTM multivariate' method outperforms all of the above conventional models and allows for more precise predictions. 2024 IEEE. -
A Scoping Review of Formal Care to Children with Special Needs during the Covid-19 Pandemic
The Covid-19 pandemic caused an unprecedented closure of direct service for children with special needs (CSNs), which shifted service to remote mode. This scoping review analyzed the strategies adopted by different formal care services for CSNs, their strengths and weaknesses, and the challenges faced by the formal care providers (FCPs). This study identified relevant articles through academic databases and Google searches using appropriate search strings and keywords. It included ten journal articles (n=10) and eight pieces (n=8) of grey literature through a meticulous selection process and extracted data. This review drew results by collating the descriptive numerical data analysis and qualitative thematic analysis and interpreting them. Reporting incor-porated all the possible items recommended by the PRISMA-ScR guidelines. This review demonstrated that pediatric rehabilitation adopted the telehealth approach and that special education changed to remote learning. When childcare programs in the USA functioned according to specific guidelines, residential care in South Asian countries faced a financial crunch. FCPs faced personal and professional challenges that required systematic training to deal with pandemic situations. This scoping review made suggestions for relevant policy formulations for equitable and effective service delivery to CSNs during pandemic situations, and it exposed new avenues for research. 2022 Authors. -
Impact of lockdown during COVID-19 pandemic on the learning status of undergraduate and postgraduate students of Bangalore
Background: The COVID 19 pandemic has created various impacts on every human's life. COVID 19 lockdown has provoked enormous changes in the education sector which in turn influences the student's life in many aspects. The scope of this study is to understand the impact in both undergraduate and postgraduate students. Aim: This study aims at incisively analyzing the impact of lockdown imposed due to the COVID-19 pandemic on graduate students of Bangalore. Method: It is an online survey that encompasses a structural questionnaire with open-ended questions created using Google Forms, which were sent across the students through social media platforms. Results: A total of 115 students from both undergraduate and postgraduate programs have participated in this survey. Simple percentage distribution was estimated to evaluate the pedagogy, opinion on educational decisions, modes of learning, socio-economic conditions, and problems pertaining to academia because of this pandemic. As per this analysis, 80.9% of students faced difficulty due to lockdown. 67% of students thought that their family's income will be affected by this pandemic. 68.7% of students felt stressed, depressed and 52.3% of students could not find a suitable environment in their home to study during this lockdown. When we see this pandemic in an optimistic light, it has created various opportunities such as Digital learning and adoption of new health habits. 2021. RIGEO. All Rights Reserved. -
Digital filter architectures for multi-standard wireless transceivers
This paper addresses on two different architectures of digital decimation filter design of a multi-standard RF transceivers. Instead of using single stage decimation filter network, the filters are implemented in multiple stages using FPGA to optimize the area and power. The proposed decimation filter architectures reflect the considerable reduction in area & power consumption without degradation of performance. The filter coefficients are derived from MATLAB , the filter architectures are implemented and tested using Xilinx SPARTAN FPGA . The Xilinx ISE 9.2i tool is used for logic synthesis and the Xpower analysis tool is used for estimating the power consumption. First, the types of decimation filter architectures are tested and implemented using conventional binary number system. Then the different encoding scheme i.e. Canonic Signed Digit (CSD) representation is used for filter coefficients and then the architecture performance is tested .The results of CSD based architecture shows a considerable reduction in the area & power against the conventional number system based filter design implementation. -
Hybrid architecture of digital filter for multi-standard transceivers
This paper addresses on three different architectures of digital decimation filter design of a multi-standard RF transceivers. Instead of using single stage decimation filter network, the filters are implemented in multiple stages using FPGA to optimize the area and power. The proposed decimation filter architectures reflect the considerable reduction in area & power consumption without degradation of performance. First, the types of decimation filter architectures are tested and implemented using conventional binary number system. Then the two different encoding schemes i. e. Canonic Signed Digit (CSD) and Minimum Signed Digit (MSD) are used for filter coefficients and then the architecture performances are tested using FPGA. The results of CSD and MSD based architectures show a considerable reduction in the area & power against the conventional number system based filter design implementation. The implementation results reflect that considerable reduction in area of 25. 64% and power reduction of 16. 45% are achieved using hybrid architecture. Research India Publications.