National Institute of Technology Karnataka

Various ongoing researches are there on topics like which model will give more compatible results with that of observed discharges. It was argued that even complex modeling does not provide better results. Climate change and soil heterogeneity has got an important role in finding out surface runoff. In this paper, we are going to discuss briefly about variable infiltration capacity model (VIC), TOPMODEL, HBV, MIKESHE and soil and water assessment tool (SWAT) model. VIC performs well in moist areas and can be efficiently used in the water management for agricultural purposes. Requirement of large data and physical parameters makes the use of MIKE SHE model limited to smaller catchments. Only a little direct calibration is required for SWAT model to obtain good hydrologic predictions. HBV model gives satisfactory results and TOPMODEL can be used in catchments with shallow soil and moderate topography.

Soil erosion is a serious problem arising from agricultural intensification, land degradation and other anthropogenic activities. Assessment of soil erosion is useful in planning and conservation works in a watershed or basin. Modelling can provide a quantitative and consistent approach to estimate soil erosion and sediment yield under a wide range of conditions. In the present study, the soil loss model, Revised Universal Soil Loss Equation (RUSLE) integrated with GIS has been used to estimate soil loss in the Nethravathi Basin located in the southwestern part of India. The Nethravathi Basin is a tropical coastal humid area having a drainage area of 3128 km2 up to the gauging station. The parameters of RUSLE model were estimated using remote sensing data and the erosion probability zones were determined using GIS. The estimated rainfall erosivity, soil erodibility, topographic and crop management factors range from 2948.16 to 4711.4 MJ/mm·ha−1hr−1/year, 0.10 to 0.44 t ha−1·MJ−1·mm−1, 0 to 92,774 and 0 to 0.63 respectively. The results indicate that the estimated total annual potential soil loss of about 473,339 t/yr is comparable with the measured sediment of 441,870 t/yr during the water year 2002–2003. The predicted soil erosion rate due to increase in agricultural area is about 14,673.5 t/yr. The probability zone map has been derived by the weighted overlay index method indicate that the major portion of the study area comes under low probability zone and only a small portion comes under high and very high probability zone. The results can certainly aid in implementation of soil management and conservation practices to reduce the soil erosion in the Nethravathi Basin.

The industrial revolution has been the main cause ever since tremendous technological advancement was observed. The ubiquitous deployment of recent information and communication technologies (ICT), namely Artificial Intelligence (AI), Internet of Things (IoT), and Blockchain technology, is hastening the world’s industrial and technological transformation. This technical aggrandizement enhances the working culture and has a favorable impact on the workplace, as per the progressivist perspective. The breakneck pace of technological advancement, as well as AI, has enabled humans to replace manual labor in various industries. As being a domain of science and technology, AI develops machines and programs for computers that are intelligent and can accomplish tasks that would normally require human intelligence abilities. This paper mainly explores the frontiers of artificial intelligence and its applications in various fields. The AI Frontiers promulgate methodical concepts that are peer-reviewed cutting-edge research on the disruptive technological revolution of Artificial Intelligence. Additionally, some key viewpoints in the field of AI have been listed along with the main frontiers, including Machine Learning (ML), Deep Learning (DL), Fuzzy Logic (FL), Natural Language Processor (NLP), and Genetic Algorithm (GA). Furthermore, this paper discussed some common AI applications and a briefing about the current scenario in the worldwide market for artificial intelligence.

Functionally graded composite materials (FGCMs) are inhomogeneous materials, consisting of two (or more) different materials, engineered to have a continuously varying spatial composition profile . This paper describes the overview of FGCM basic concepts, classification, properties and preparation methods. It focuses on an overview of research and Application of FGCM in broad present situation. Based upon analysis of the present application situations and prospect of this kind of materials some existing problems are discussed As a part of present research work, a simple case study is discussed based on CNT reinforced Al Functionally graded composite by Powder metallurgy technique. An insight in to the current status of the research of FGCM is presented and an anticipation of its future development is also presented.

Image fusion is the process of combining high spatial resolution panchromatic (PAN) image and rich multispectral (MS) image into a single image. The fused single image obtained is known to be spatially and spectrally enhanced compared to the raw input images. In recent years, many image fusion techniques such as principal component analysis, intensity hue saturation, brovey transforms and multi-scale transforms, etc., have been proposed to fuse the PAN and MS images effectively. However, it is important to assess the quality of the fused image before using it for various applications of remote sensing. In order to evaluate the quality of the fused image, many researchers have proposed different quality metrics in terms of both qualitative and quantitative analyses. Qualitative analysis determines the performance of the fused image by visual comparison between the fused image and raw input images. On the other hand, quantitative analysis determines the performance of the fused image by two variants such as with reference image and without reference image. When the reference image is available, the performance of fused image is evaluated using the metrics such as root mean square error, mean bias, mutual information, etc. When the reference image is not available the performance of fused image is evaluated using the metrics such as standard deviation, entropy, etc. The paper reviews the various quality metrics available in the literature, for assessing the quality of fused image.

Smart materials, which exhibit piezoelectricity, find an eclectic range of applications in the industry. The direct piezoelectric effect has been widely used in sensor design, and the inverse piezoelectric effect has been applied in actuator design. Ever since 1954, PZT and BaTiO 3 were widely used for sensor and actuator applications despite their toxicity, brittleness, inflexibility, etc. With the discovery of PVDF in 1969, followed by development of copolymers, a flexible, easy to process, nontoxic, high density alternate with high piezoelectric voltage coefficient was available. In the past 20 years, heterostructural materials like polymer ceramic composites, have received lot of attention, since these materials combine the excellent pyroelectric and piezoelectric properties of ceramics with the flexibility, processing facility, and strength of the polymers resulting in relatively high dielectric permittivity and breakdown strength, which are not attainable in a single phase piezoelectric material. The current review article is an attempt to provide a compendium of all the work carried out with reference to PVDF‐PZT composites. The review article evaluates the effect of grain size, content and other factors under the purview of dielectric and piezoelectric properties while evaluating the sensitivity of the material for sensor application. POLYM. ENG. SCI., 55:1589–1616, 2015. © 2015 Society of Plastics Engineers

The tomato crop is an important staple in the Indian market with high commercial value and is produced in large quantities. Diseases are detrimental to the plant's health which in turn affects its growth. To ensure minimal losses to the cultivated crop, it is crucial to supervise its growth. There are numerous types of tomato diseases that target the crop's leaf at an alarming rate. This paper adopts a slight variation of the convolutional neural network model called LeNet to detect and identify diseases in tomato leaves. The main aim of the proposed work is to find a solution to the problem of tomato leaf disease detection using the simplest approach while making use of minimal computing resources to achieve results comparable to state of the art techniques. Neural network models employ automatic feature extraction to aid in the classification of the input image into respective disease classes. This proposed system has achieved an average accuracy of 94-95 % indicating the feasibility of the neural network approach even under unfavourable conditions.

Abstract It is a subject of exploration whether the phase pure anatase or rutile TiO 2 or the band alignment due to the heterojunctions in the two polymorphs of TiO 2 plays the determining role in efficacy of a photocatalytic reaction. In this work, the phase pure anatase and rutile TiO 2 have been explored for photocatalytic nitroarenes reduction to understand the role of surface structures and band alignment towards the reduction mechanism. The conduction band of synthesized anatase TiO 2 has been found to be more populated with electrons of higher energy than that of synthesized rutile. This has given the anatase an edge towards photocatalytic reduction of nitroarenes over rutile TiO 2 . The other factors like adsorption of the reactants and the proton generation did not play any decisive role in catalytic efficacy.

This paper provides a comprehensive analysis of decarbonising cement and concrete production, addressing strategies, technologies, policy considerations, case studies, economic implications, challenges and future recommendations. The cement and concrete industry are major contributors to carbon emissions and environmental degradation, making decarbonisation crucial for sustainable development. The paper explores various strategies, including alternative clinker technologies, carbon capture and storage, improved energy efficiency, low-carbon cements and circular economy approaches. Additionally, it examines technologies such as supplementary cementitious materials, carbonation, low-carbon concrete mixes, recycling and novel manufacturing processes. The importance of policy interventions, collaboration and standards and certifications is emphasised. Case studies and best practices highlight successful decarbonisation initiatives, while economic implications and market opportunities are considered. The paper also identifies challenges, including technological limitations, financing constraints, resistance to change and the need for awareness and education. Finally, future recommendations focus on pathways for deep decarbonisation, policy measures, research priorities and fostering collaboration. This review serves as a valuable resource for researchers, policymakers and industry professionals striving to achieve sustainable and low-carbon cement and concrete production.

The objective of the research was to improve the wear resistance of titanium alloys by ball burnishing process. Burnishing process parameters such as burnishing speed, burnishing feed, burnishing force and number of pass were considered to minimize the specific wear rate and coefficient of friction. Taguchi optimization results revealed that burnishing force and number of pass were the significant parameters for minimizing the specific wear rate, whereas the burnishing feed and speed play important roles in minimizing the coefficient of friction. After burnishing surface microhardness increased from 340 to 405 Hv, surface roughness decreased from 0.45 to 0.12 μm and compressive residual stress were generated immediately below the burnished surface. The optimization results showed that specific wear rate decreased by 52%, whereas coefficient of friction was reduced by 64% as compared to the turned surface. The results confirm that, an improvement in the wear resistance of Ti–6Al–4V alloy has been achieved by the process of ball burnishing.

Stress is a common part of everyday life that most people have to deal with on various occasions. However, having long-term stress, or a high degree of stress, will hinder our safety and disrupt our normal lives. Detecting mental stress earlier can prevent many health problems associated with stress. When a person gets stressed, there are notable shifts in various bio-signals like thermal, electrical, impedance, acoustic, optical, etc., by using such bio-signals stress levels can be identified. This paper proposes different machine learning and deep learning techniques for stress detection on individuals using multimodal dataset recorded from wearable physiological and motion sensors, which can prevent a person from various stress-related health problems. Data of sensor modalities like three-axis acceleration (ACC), electrocardiogram (ECG), blood volume pulse (BVP), body temperature (TEMP), respiration (RESP), electromyogram (EMG) and electrodermal activity (EDA) are for three physiological conditions - amusement, neutral and stress states, are taken from WESAD dataset. The accuracies for three-class (amusement vs. baseline vs. stress) and binary (stress vs. non-stress) classifications were evaluated and compared by using machine learning techniques like K-Nearest Neighbour, Linear Discriminant Analysis, Random Forest, Decision Tree, AdaBoost and Kernel Support Vector Machine. Besides, simple feed forward deep learning artificial neural network is introduced for these three-class and binary classifications. During the study, by using machine learning techniques, accuracies of up to 81.65% and 93.20% are achieved for three-class and binary classification problems respectively, and by using deep learning, the achieved accuracy is up to 84.32% and 95.21% respectively.

Tremendous growth has been witnessed in the field of additive manufacturing (AM) technology over the last few decades. It offers a plethora of applications and is already being utilized in almost every sphere of life. Owing to inherent differences between each AM technique, newer fields of research consistently emerge and demand attention. Also, the innovative applications of AM open up newer challenges and thus avenues for focused attention. One such avenue is AM materials. Raw material plays an important role in determining the properties of fabricated part. The type and form of raw material largely depend on the type of AM fabricators. There is a restriction on material compatibility with most of the established AM techniques. This review aims to provide an overview of various aspects of AM materials highlighting the progress made especially over the past two decades.

Polydopamine modified halloysite nanotubes (HNTs) were synthesised and employed as a well dispersed hydrophilic additive to enhance the filtration properties of polyetherimide (PEI) membranes.

Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Atharva Naik, Arjun Ashok, Arut Selvan Dhanasekaran, Anjana Arunkumar, David Stap, Eshaan Pathak, Giannis Karamanolakis, Haizhi Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Kuntal Kumar Pal, Maitreya Patel, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Savan Doshi, Shailaja Keyur Sampat, Siddhartha Mishra, Sujan Reddy A, Sumanta Patro, Tanay Dixit, Xudong Shen. Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. 2022.

Abstract The anthropogenic inputs of hexavalent chromium [Cr(VI)] have increased enormously during the past few decades and has become a challenge for life on earth and hence removal of this carcinogen has become the need of the hour. Cr(VI) removal through common physicochemical techniques is highly expensive and inappropriate at low concentration. Microbial reduction of Cr(VI) to trivalent form is considered a favorable technique for Cr(VI) removal from wastewater, as it reduces the highly toxic form of Cr to less toxic form and therefore the article conveys essential fundamental information on removal of Cr(VI) by bacteria. For efficient bioremoval of Cr(VI),the main machinery of the process, the microbes, and their conditions, which decide the fate of this heavy metal, should be appropriate. Hence, the authors cover vast information about the isolation of chromium-resistant bacteria from various environment and their Cr(VI) resistance capability. An extensive report is given on information pertaining to the factors such as cell density, pH, temperature, salt concentration, oxidation-reduction potential, electron donor, oxyanions, metabolic inhibitors, and other heavy metals that influence or affect the efficient Cr(VI) removal. Cr(VI) removal by immobilized bacterial cells and their advantages has also been summarized. In transferring this technology from laboratory to a large-scale application, better understanding of all these aspects is necessary. Hence, this developing biotechnological method that encompasses fields from genetic engineering to reactor engineering demands focused research in these directions, which may lead to implementation of this technology on a larger scale and drive it toward being the most opted-for technology. KEY WORDS: bioremediationchromium reducing bacteriahexavalent chromiumimmobilizationmicrobial treatmentwastewater

Hydrologic modeling plays a very important role in assessing the seasonal water availability, which is necessary to take decisions in water resources management. Both climate and land use and land cover change have great influence on the hydrological response of a watershed. The main aim of this study is to provide a detailed review of studies which have been carried out to analyze the hydrological impacts of land use change, and also to evaluate different scenario modeling approaches. In addition, a brief description of basic hydrologic models which are used to simulate the stream flow is provided. This review paper tried to explain the importance of model comparison and performance evaluation in modeling studies. The following conclusions may be drawn from this review: (1) it is necessary to model the possible impacts of land use change and climate change in order to proceed with effective water resources management, (2) it is important to analyze the variation in hydrological response in catchments with different land use characteristics and climatic conditions and also under climate scenarios, and (3) integration of different models with hydrologic models can be considered as an efficient method to forecast future trends in hydrological response.

There are many 3D printing technologies available, and each technology has its strength and weakness. The 3D printing of sand moulds, by binder jetting technology for rapid casting, plays a vital role in providing a better value for the more than 5000 years old casting industry by producing quality and economic sand moulds. The parts of the mould assembly can be manufactured by precisely controlling the process parameters and the gas producible materials within the printed mould. A functional mould can be manufactured with the required gas permeability, strength, and heat absorption characteristics, and hence the process ensures a high success rate of quality castings with an optimised design for weight reduction. It overcomes many of the limitations in traditional mould design with a very limited number of parts in the mould assembly. A variety of powders, of different particle size or shape, and bonding materials can be used to change the thermal and physical properties of the mould and hence provide possibilities for casting a broad range of alloys. Limited studies have been carried out to understand the relationship between the characteristics of the printed mould, the materials used, and the processing parameters for making the mould. These deficiencies need to be addressed to support the numerical simulation of a designed part, to optimise the success rate and for economic as well as environmental reasons. Commonly used binders in this process, e.g. furan resins, are carcinogenic or hazardous, and hence there is a vital need for developing new or improved bonding materials.

AIM: The aim of this study was to determine whether the addition of an autologous platelet rich fibrin (PRF) membrane to a coronally advanced flap (CAF) would improve the clinical outcome in terms of root coverage, in the treatment of isolated gingival recession. MATERIALS AND METHODS: Systemically healthy 20 subjects each with single Miller's class I or II buccal recession defect were randomly assigned to control (CAF) or test (CAF + PRF) group. Clinical outcome was determined by measuring the following clinical parameters such as recession depth (RD), recession width (RW), probing depth (PD), clinical attachment level (CAL), width of keratinized tissue (WKT), gingival thickness (GTH), plaque index (PI), and gingival index (GI) at baseline, 3(rd), and 6(th) month postsurgery. RESULTS: The root coverage was 65.00 ± 44.47% in the control group and 74.16 ± 28.98% in the test group at 6(th) month, with no statistically significant difference between them. Similarly, CAL, PD, and WKT between the groups were not statistically significant. Conversely, there was statistically significant increase in GTH in the test group. CONCLUSION: CAF is a predictable treatment for isolated Miller's class I and II recession defects. The addition of PRF to CAF provided no added advantage in terms of root coverage except for an increase in GTH.

The objective of the present work is to improve the output waveform of three level inverters used in high-power applications, where the switching frequency is very low. This is achieved by maintaining the synchronization, half-wave symmetry, quarter-wave symmetry, and three-phase symmetry in the pulsewidth modulation (PWM) waveforms. The principles of achieving synchronization and symmetries in terms of space vectors for three level inverters are presented. A novel synchronized space vector pulsewidth modulation (SVPWM) algorithms is proposed and verified experimentally. The experimental waveforms of the inverter output voltage and motor no load current for different operating conditions of the drive are presented. The performance measure in terms of the weighted total harmonic distortion (THD) of the line voltage is computed for the linear modulation region of the drive for the proposed algorithm and compared with that of synchronized SVPWM and synchronized sine-triangle pulsewidth modulation (SPWM) technique. The comparative results show that consideration of synchronization and symmetry results in improved THD. Another significant feature of the proposed algorithm is that the symmetry and synchronization leads to self-balancing of the direct current (dc) bus capacitor voltages over every one third cycle of the fundamental

Abstract Native starch is subjected to various forms of modification to improve its structural, mechanical, and thermal properties for wider applications in the food industry. Physical, chemical, and dual modifications have a substantial effect on the gelatinization properties of starch. Consequently, this review explores and compares the different methods of starch modification applicable in the food industry and their effect on the gelatinization properties such as onset temperature ( T o ), peak gelatinization temperature ( T p ), end set temperature ( T c ), and gelatinization enthalpy (Δ H ), studied using differential scanning calorimetry (DSC). Chemical modifications including acetylation and acid hydrolysis decrease the gelatinization temperature of starch whereas cross-linking and oxidation result in increased gelatinization temperatures. Common physical modifications such as heat moisture treatment and annealing also increase the gelatinization temperature. The gelatinization properties of modified starch can be applied for the improvement of food products such as ready-to-eat, easily heated or frozen food, or food products with longer shelf life.