Search results for: Navin Kumar

Authors: Vikrant Sinha, Himanshu Singh, Nitish Kumar Singh, Sujal Nag

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This research creates an urgent and complex challenge for marine ecosystems. Microplastics were primarily found on land, but now they are pervasive in marine environments as well, affecting a wide range of marine species, from zooplankton to larger mammals that live in those environments. These pollutants interfere with major biological processes like feeding and reproduction, causing disruption throughout the food web as microplastics are getting accumulated at different tropic levels. Meanwhile, climatic changes made these effects more accelerated, and the concentration of microplastics due to these occurrences is increasing day by day. Rising temperatures, melting ice, increased runoff due to rainfall, and shifting wind patterns are transforming marine life in a way that intensifies the burden on marine life. This dual stress is particularly present in fragile ecosystems of marine life, such as coral reefs and mangroves. Addressing this twisted crisis requires not only efforts to restrain plastic pollution but also adapts strategies for climate mitigation. This research emphasizes the critical need to combine approaches to save marine biodiversity and withstand the rapid changes in the environment.

Keywords: microplastic pollution, climate change impacts, marine ecosystems, biodiversity threats, zooplankton ingestion, trophic accumulation, coral reef degradation, ecosystem resilience, plastic pollution mitigation, climate adaptation strategies, SST, sea surface temperature

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Authors: Nagri Sateesh, Kundavarapu Vengalrao, Kopparthi Phaneendra Kumar

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Vacuum assisted resin transfer molding (VARTM) is one of the manufacturing technique that is viable for production of fiber reinforced polymer composite components suitable for aerospace, marine and commercial applications. However, the repeatable quality of the product can be achieved by critically fixing the process parameters such as Vacuum Pressure (VP) and permeability of the preform. The present investigation is aimed at studying the effect of permeability for production of Glass Fiber Reinforced Plastic (GFRP) components with consistent quality. The VARTM mould is made with an acrylic transparent top cover to observe and record the resin flow pattern. Six layers of randomly placed glass fiber under five different vacuum pressures VP1 = 0.013, VP2 = 0.026, VP3 = 0.039, VP4 = 0.053 and VP5 = 0.066 MPa were studied. The laminates produced by this process under the above mentioned conditions were characterized with ASTM D procedures so as to study the effect of these process parameters on the quality of the laminate. Moreover, as mentioned there is a considerable effect of permeability on the impact strength and the void content in the laminates under different vacuum pressures. SEM analysis of the impact tested fractured GFRP composites showed the bonding of fiber and matrix.

Keywords: permeability, vacuum assisted resin transfer molding (VARTM), ASTM D standards, SEM

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Authors: B. Pavan Kumar Reddy, P. Michael Preetam Raj, Souri Banerjee, Souvik Kundu

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In this work, the fabrication and characterization of copper-doped zinc oxide (Cu:ZnO) based memristor devices with aluminum (Al) and indium tin oxide (ITO) metal electrodes are reported. The thin films of Cu:ZnO was synthesized using low-cost and low-temperature chemical process. The Cu:ZnO was then deposited onto ITO bottom electrodes using spin-coater technique, whereas the top electrode Al was deposited utilizing physical vapor evaporation technique. Ellipsometer was employed in order to measure the Cu:ZnO thickness and it was found to be 50 nm. Several surface and materials characterization techniques were used to study the thin-film properties of Cu:ZnO. To ascertain the efficacy of Cu:ZnO for memristor applications, electrical characterizations such as current-voltage (I-V), data retention and endurance were obtained, all being the critical parameters for next-generation memory. The I-V characteristic exhibits switching behavior with asymmetrical hysteresis loops. This work imputes the resistance switching to the positional drift of oxygen vacancies associated with respect to the Al/Cu:ZnO junction. Further, a non-linear curve fitting regression techniques were utilized to determine the equivalent circuit for the fabricated Cu:ZnO memristors. Efforts were also devoted in order to establish its potentiality for different electronic applications.

Keywords: copper doped, metal-oxides, oxygen vacancies, resistive switching

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Authors: Sresha Yadav, Ishwar Kumar

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Second language learning is an important area of research in the language and linguistic domains. Literature suggests that several factors impact second language learning, including age, motivation, objectives, teacher, instructional material, classroom interaction, intelligence and previous background, previous linguistic experience, other student characteristics. Previous researchers have also highlighted that classroom atmospherics has a significant impact on learning as well as on the performance of students. However, the impact of classroom atmospherics on second language learning is still not known in the existing literature. Therefore, the purpose of the present study is to explore whether classroom atmospherics has an impact on second language learning or not? And if it does, it would be worthwhile to explore the nature of such relationship. The present study aims to explore the impact of classroom atmospherics on second language learning by dwelling into the existing literature to explore factors which impact second language learning, classroom atmospherics which impact language learning and the metrics through which such learning impacts could be measured. Based on the findings of literature review, the researchers have adopted a clustering approach for categorization and positioning of various measures of second language learning. Based on the clustering approach, the researchers have approach for measuring the impact of classroom atmospherics on second language learning by drawing a student sample consisting of 80 respondents. The results of the study uncover various basic premises of second language learning, especially with regard to classroom atmospherics. The present study is important not only from the point of view of language learning but implications could be drawn with regard to the design of classroom atmospherics, environmental psychology, anthropometrics, etc as well.

Keywords: classroom atmospherics, cluster analysis, linguistics, second language learning

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Authors: Raman Kumar, Jasgurpreet Singh Chohan, Chander Shekhar Verma

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Today, the manufacturing industries respond rapidly to new demands and compete in this continuously changing environment, thus seeking out new methods allowing them to remain competitive and flexible simultaneously. The aim of the manufacturing organizations is to reduce manufacturing costs and wastes through system simplification, organizational potential, and proper infrastructural planning by using modern techniques like lean manufacturing. In India, large number of medium and large scale manufacturing industries has successfully implemented lean manufacturing techniques. Keeping in view the above-mentioned facts, different tools will be involved in the successful implementation of the lean approach. The present work is focused on the auto part manufacturing industry to improve the performance of the recliner assembly line. There is a number of lean manufacturing tools available, but the experience and complete knowledge of manufacturing processes are required to select an appropriate tool for a specific process. Fishbone diagrams (scrap, inventory, and waiting) have been drawn to identify the root cause of different. Effect of cycle time reduction on scrap and inventory is analyzed thoroughly in the case company. Results have shown that there is a decrease in inventory cost by 7 percent after the successful implementation of the lean tool.

Keywords: lean tool, fish-bone diagram, cycle time reduction, case study

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Authors: R. Kanmaniraja, R. Freshipali, J. Abdullah, K. Niranjan, K. Balasubramani, V. R. Sanal Kumar

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The present environmental issues have made aircraft jet noise reduction a crucial problem in aero-acoustics research. Acoustic studies reveal that addition of chevrons to the nozzle reduces the sound pressure level reasonably with acceptable reduction in performance. In this paper comprehensive numerical studies on acoustic characteristics of different types of chevron nozzles have been carried out with non-reacting flows for the shape optimization of chevrons in supersonic nozzles for aerospace applications. The numerical studies have been carried out using a validated steady 3D density based, k-ε turbulence model. In this paper chevron with sharp edge, flat edge, round edge and U-type edge are selected for the jet acoustic characterization of supersonic nozzles. We observed that compared to the base model a case with round-shaped chevron nozzle could reduce 4.13% acoustic level with 0.6% thrust loss. We concluded that the prudent selection of the chevron shape will enable an appreciable reduction of the aircraft jet noise without compromising its overall performance. It is evident from the present numerical simulations that k-ε model can predict reasonably well the acoustic level of chevron supersonic nozzles for its shape optimization.

Keywords: supersonic nozzle, Chevron, acoustic level, shape optimization of Chevron nozzles, jet noise suppression

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Authors: Shalini Tripathi, Pardeep Kumar

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The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

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Authors: Angad S. Kushwaha, Rajeev Kumar, Monika Srivastava, S. K. Srivastava

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A lot of research work is going on in the field of graphene based SPR biosensor. In the conventional SPR based biosensor, graphene is used as a biomolecular recognition element. Graphene adsorbs biomolecules due to carbon based ring structure through sp2 hybridization. The proposed SPR based biosensor configuration will open a new avenue for efficient biosensing by taking the advantage of Graphene and its fascinating nanofabrication properties. In the present study, we have studied an SPR biosensor based on graphene mediated by Zinc Oxide (ZnO) and Gold. In the proposed structure, prism (BK7) base is coated with Zinc Oxide followed by Gold and Graphene. Using the waveguide approach by transfer matrix method, the proposed structure has been investigated theoretically. We have analyzed the reflectance versus incidence angle curve using He-Ne laser of wavelength 632.8 nm. Angle, at which the reflectance is minimized, termed as SPR angle. The shift in SPR angle is responsible for biosensing. From the analysis of reflectivity curve, we have found that there is a shift in SPR angle as the biomolecules get attached on the graphene surface. This graphene layer also enhances the sensitivity of the SPR sensor as compare to the conventional sensor. The sensitivity also increases by increasing the no of graphene layer. So in our proposed biosensor we have found minimum possible reflectivity with optimum level of sensitivity.

Keywords: biosensor, sensitivity, surface plasmon resonance, transfer matrix method

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Authors: Santosh Kumar Ketham

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Climate change creating most dramatic and destructive consequences, the result is global warming and sea-level rise, flooding coastal cities around the world forming vulnerable situations affecting in multiple ways: environment, economy, social and political. The aim and goal of the research is to develop cities on water. Taking the problem as an opportunity to bring science, engineering, policies and design together to make a resilient and sustainable floating community on water considering existing/new technologies of floating. The quest is to make sustainable habitat on water to live, work, learn and play.  To make sustainable energy generation and storage alongside maintaining balance of land and marine to conserve Ecosystem. The research would serve as a model for sustainable neighbourhoods designed in a modular way and thus can easily extend or re-arranged, to adapt for future socioeconomic realities.  This research paper studies primarily on climate change problems, effects, risks and opportunities. It does so, through analysing existing case studies, books and writings published on coastal cities and understanding its various aspects for making sustainable habitat.

Keywords: floating cities, flexible modular typologies, rising sea levels, sustainable architecture and urbanism

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Authors: Su Xiaohan, Jin Chicheng, Liu Yijing, Burra Venkata Durga Kumar

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Energy-aware scheduling in real-time systems aims to minimize energy consumption, but issues related to resource reservation and timing constraints remain challenges. This study focuses on analyzing two scheduling algorithms, Fair-Share Scheduling (FFS) and Priority-Driven Preemptive Scheduling (PDPS), for solving these issues and energy-aware scheduling in real-time systems. Based on research on both algorithms and the processes of solving two problems, it can be found that Fair-Share Scheduling ensures fair allocation of resources but needs to improve with an imbalanced system load, and Priority-Driven Preemptive Scheduling prioritizes tasks based on criticality to meet timing constraints through preemption but relies heavily on task prioritization and may not be energy efficient. Therefore, improvements to both algorithms with energy-aware features will be proposed. Future work should focus on developing hybrid scheduling techniques that minimize energy consumption through intelligent task prioritization, resource allocation, and meeting time constraints.

Keywords: energy-aware scheduling, fair-share scheduling, priority-driven preemptive scheduling, real-time systems, optimization, resource reservation, timing constraints

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Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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Traditional execution process follows the path of execution drawn by the process analyst without observing the behaviour of resource and other real-time constraints. Identifying process model, predicting the behaviour of resource and recommending the optimal path of execution for a real time process is challenging. The proposed AlfyMiner: αyM iner gives a new dimension in process execution with the novel techniques Process Model Analyser: PMAMiner and Resource behaviour Analyser: RBAMiner for recommending the probable path of execution. PMAMiner discovers next probable activity for currently executing activity in an online process using variant matching technique to identify the set of next probable activity, among which the next probable activity is discovered using decision tree model. RBAMiner identifies the resource suitable for performing the discovered next probable activity and observe the behaviour based on; load and performance using polynomial regression model, and waiting time using queueing theory. Based on the observed behaviour αyM iner recommend the probable path of execution with; next probable activity and the best suitable resource for performing it. Experiments were conducted on process logs of CoSeLoG Project1 and 72% of accuracy is obtained in identifying and recommending next probable activity and the efficiency of resource performance was optimised by 59% by decreasing their load.

Keywords: cross-organization process mining, process behaviour, path of execution, polynomial regression model

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Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu

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Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.

Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli

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Authors: Gourav Jain, Sameer Dixit, Surjeet Kumar Arya, Praveen C. Verma

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Plant cell wall plays a major role in defence mechanism against biotic and abiotic stress as it constitutes the physical barrier between the microenvironment and internal component of the cell. It is a complex structure composed of mostly carbohydrates among which cellulose and hemicelluloses are most abundant that is embedded in a matrix of pectins and proteins. Multiple enzymes have been reported which plays a vital role in cell wall modification, Pectin Methylesterase (PME) is one of them which catalyses the demethylesterification of homogalacturonans component of pectin which releases acidic pectin and methanol. As emitted methanol is toxic to the insect pest, we use PME gene for the better methanol production. In the current study we showed overexpression of PME gene isolated from Withania somnifera under the insect inducible promoter causes enhancement of methanol production at the time of insect feeds to plants, and that provides better insect resistance property. We found that the 85-90% mortality causes by transgenic tobacco in both chewing (Spodoptera litura larvae and Helicoverpa armigera) and sap-sucking (Aphid, mealybug, and whitefly) pest. The methanol content and emission level were also enhanced by 10-15 folds at different inducible time point interval (15min, 30min, 45min, 60min) which would be analysed by Purpald/Alcohol Oxidase method.

Keywords: methanol, Pectin methylesterase, inducible promoters, Purpald/Alcohol oxidase

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Authors: Rajesh Kumar Ulaganathan, Yi-Ying Lu, Chia-Jung Kuo, Srinivasa Reddy Tamalampudi, Raman Sankar, Fang Cheng Chou, Yit-Tsong Chen

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In this paper, we report the optoelectronic properties of multi-layered GeS nanosheets (~28 nm thick)-based field-effect transistors (called GeS-FETs). The multi-layered GeS-FETs exhibit remarkably high photoresponsivity of Rλ ~ 206 AW-1 under illumination of 1.5 µW/cm2 at  = 633 nm, Vg = 0 V, and Vds = 10 V. The obtained Rλ ~ 206 AW-1 is excellent as compared with a GeS nanoribbon-based and the other family members of group IV-VI-based photodetectors in the two-dimensional (2D) realm, such as GeSe and SnS2. The gate-dependent photoresponsivity of GeS-FETs was further measured to be able to reach Rλ ~ 655 AW-1 operated at Vg = -80 V. Moreover, the multi-layered GeS photodetector holds high external quantum efficiency (EQE ~ 4.0 × 104 %) and specific detectivity (D* ~ 2.35 × 1013 Jones). The measured D* is comparable to those of the advanced commercial Si- and InGaAs-based photodiodes. The GeS photodetector also shows an excellent long-term photoswitching stability with a response time of ~7 ms over a long period of operation (>1 h). These extraordinary properties of high photocurrent generation, broad spectral range, fast response, and long-term stability make the GeS-FET photodetector a highly qualified candidate for future optoelectronic applications.

Keywords: germanium sulfide, photodetector, photoresponsivity, external quantum efficiency, specific detectivity

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Authors: Soo Hong Da, Ng Zheng Yao, Burra Venkata Durga Kumar

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The Healthcare sector is a business that consists of providing medical services, manufacturing medical equipment and drugs as well as providing medical insurance to the public. Most of the time, the data stored in the healthcare database is to be related to patient’s information which is required to be accurate when it is accessed by authorized stakeholders. In distributed systems, one important issue is concurrency in the system as it ensures the shared resources to be synchronized and remains consistent through multiple read and write operations by multiple clients. The problems of concurrency in the healthcare sector are who gets the access and how the shared data is synchronized and remains consistent when there are two or more stakeholders attempting to the shared data simultaneously. In this paper, a framework that is beneficial to distributed healthcare sector concurrent environment is proposed. In the proposed framework, four different level nodes of the database, which are national center, regional center, referral center, and local center are explained. Moreover, the frame synchronization is not symmetrical. There are two synchronization techniques, which are complete and partial synchronization operation are explained. Furthermore, when there are multiple clients accessed at the same time, synchronization types are also discussed with cases at different levels and priorities to ensure data is synchronized throughout the processes.

Keywords: resources, healthcare, concurrency, synchronization, stakeholders, database

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Authors: Anjali Verma, Mahesh Pal, Veena Pande, Dalip Kumar Upreti

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The present study is carried out to explore the anti-hyperglycemic activity of Leucas cephalotes plant parts. A fruit, leaves, stems, and roots part of the Leucas cephalotes has been extracted in ethanol and have been evaluated for anti-hyperglycemic activity. The present study indicated that, ethanolic extract of fruit and leaves have shown significant α- amylase inhibitory activity with IC50 value of 92.86 ± 0.89 μg/mL and 98.09 ± 0.69 μg/mL respectively. Two known compounds β-sitosterol and lupeol were isolated from ethanolic extract of L. cephalotes leaves and were subjected to anti-hyperglycemic activity. Lupeol shows the best activity with IC50 55.73 ± 0.47 μg/mL and the results were verified by docking study of these compounds with mammalian α-amylase was carried out on its active site. It was concluded from the study that β-sitosterol and lupeol form one H-bond interactions with the active site residues either Asp212 or Thr21. The estimated free energy binding of β-sitosterol was found to be -9.47 kcal mol-1 with an estimated inhibition constant (Ki) of 558.94 nmol whereas the estimated free energy binding of lupeol was -11.73 kcal mol-1 with an estimated inhibition constant (Ki) of 476.71pmmol. The present study clearly showed that lupeol is more potent in comparison to β-sitosterol. The study indicates that L. cephalotes have significant potential to inhibit α-amylase enzyme.

Keywords: alpha-amylase, beta-sitosterol, hyperglycemia, lupeol

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Authors: Malkhan Thakur, P. Deepak Kumar, P. K. S. Dikshit

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In recent years, the hydraulic behavior of side weirs has been the subject of many investigations. Most of the studies have been in connection with specific problems and have involved models. This is perhaps understandable, since a generalized treatment is made difficult by the large number of possible variables to be used to define the problem. A variety of empirical head discharge relationships have been suggested for side weirs. These empirical approaches failed to adequately consider the actual situation, and produced equations applicable only in circumstances virtually identical to those of the experiment. The present investigation is targeted to study to a greater depth the effect of different trapezium angles of a trapezoidal side weir and study of water surface profile in spatially varied flow with decreasing discharge maintaining the main channel flow subcritical. On the basis of experiment, the relationship between upstream Froude number and coefficient of discharge has been established. All the characteristics of spatially varied flow with decreasing discharge have been studied and subsequently formulated. The scope of the present investigation has been basically limited to a one-dimensional model of flow for the purpose of analysis. A formulation has been derived using the theoretical concept of constant specific energy. Coefficient of discharge has been calculated and experimental results were presented.

Keywords: weirs, subcritical flow, rectangular channel, trapezoidal side weir

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Y. A. Kumar

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Environmental awareness issues in Kazakhstan are one of the most undermined topics both among the public community and in terms of state rhetoric. In the context of official state documents, so far only two official environmental codes and national programs called Zhasyl Kazakhstan were introduced in the country in 2021. While on the one hand the Environmental Code was introduced with the purpose to modernize, frame and enlist main legislative aspects on various sectors of environmental law in Kazakhstan, on the other hand, the Zhasyl Kazakhstan Program has been implemented as a state program to address with numerous environmental projects various environmental issues ranging from air pollution to waste management as well as aspects related to ecological education and low environmental awareness matters. In this regard, the main goal of this paper is to analyze critically the main content of both of these documents with a particular focus on sections related to environmental awareness-raising aspects. For that, this paper applied a subjective-based content analysis in order to identify interesting insights on regulatory legal aspects, future research streams, and uncovering of improved legislative frameworks in the context of an environmental awareness issue. Apart from that, five open-ended questions were sent out to the Ministry of Ecology, Geology and Natural Resources to obtain primary data on the state’s view in regards to current previous, recent and future aspects of environmental awareness issues in the country.

Keywords: Kazakhstan, environmental awareness, environmental code, Zhasyl Kazakhstan, content analysis

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Authors: R. Kanthavel, R. Yogesh Kumar, T. Narendrakumar, B. Santhosh, S. Surya Prakash

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This paper primarily focuses on developing an affordable personal assistant and the implementation of it in the field of Artificial Intelligence (AI) to create a virtual assistant/friend. The problem in existing home automation techniques is that it requires the usage of exact command words present in the database to execute the corresponding task. Our proposed work is ATOM a.k.a ‘Artificial intelligence Talking Omnipresent Machine’. Our inspiration came from an unlikely source- the movie ‘Iron Man’ in which a character called J.A.R.V.I.S has omnipresence, and device controlling capability. This device can control household devices in real time and send the live information to the user. This device does not require the user to utter the exact commands specified in the database as it can capture the keywords from the uttered commands, correlates the obtained keywords and perform the specified task. This ability to compare and correlate the keywords gives the user the liberty to give commands which are not necessarily the exact words provided in the database. The proposed work has a higher flexibility (due to its keyword extracting ability from the user input) comparing to the existing work Intelligent Home automation System (IHAS), is more accurate, and is much more affordable as it makes use of WI-FI module and raspberry pi 2 instead of ZigBee and a computer respectively.

Keywords: home automation, speech recognition, voice control, personal assistant, artificial intelligence

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: John Abraham, Ramesh Saravana Kumar, Francis, Xavier, Deepak Mathew

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Broiler slaughter waste has become a major source of pollution throughout the world. Utilization of broiler slaughter waste by dry rendering process produced Rendered Chicken Oil (RCO) a cheap raw material for biodiesel production and Carcass Meal a feed ingredient for pets and fishes. Conversion of RCO into biodiesel may open new vistas for generating wealth from waste besides controlling the major havoc of environmental pollution. A two-step process to convert RCO to good quality Biodiesel was invented. Acid catalysed esterification of FFA followed by base catalysed transesterification of triglycerides was carried out after meticulously standardising the methanol molar ratio, catalyst concentration, reaction temperature and reaction time to obtain the maximum biodiesel yield of 97.62% and lowest glycerol yield of 6.96%. RCO biodiesel blended was tested in a Mahindra Scorpio CRDI engine. The results revealed that the blending of commercial diesel with 20% RCO biodiesel lead to less engine wear, a quieter engine and better fuel economy. The better lubricating qualities of RCO B20 prevented over heating of engine, which prolongs the engine life. The blending of biodiesel at 20% to commercial diesel can reduce the import of costly crude oil and simultaneously, substantially reduce the engine emissions as proved by significantly lower smoke levels, thus mitigating climatic changes.

Keywords: broiler waste, rendered chicken oil, biodiesel, engine testing

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Authors: Bhim Kumar Dahal

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Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: cement, improvement, physical properties, strength

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Authors: Rameshaiah Gowdara Narayanappa, Manikonda Prithvi, Manoj Kumar, Suraj Bhavani, Vikram Singh

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Long ago heating of food was only related to fire or electricity. Heating and storage of consumer foods were satisfied by the use of vacuum thermo flaks, electric heating cans and DC powered heating cans. But many of which did not sustain the heat for a long period of time and were impractical for remote areas. The use of chemical energy for heating foods directed us to think about the applications of exothermic reactions as a source of heat. Initial studies of calcium oxide showed desirability but not feasible because the reaction was uncontrollable and irreversible. In this research work we viewed at crystallization of super saturated sodium acetate trihydrate solution. Supersaturated sodium acetate trihydrate has a freezing point of 540 C (1300 F), but it observed to be stable as a liquid at much lower temperatures. Mechanical work is performed to create an active chemical energy zone within the working fluid, when crystallization process is initiated. Due to this the temperature rises to its freezing point which in turn heats the contents in the storage container. Present work endeavor to design a self-heating storage container is suitable for consumer dedications.

Keywords: crystallization, exothermic reactions, self-heating container, super saturation, vacuum thermo flask

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Authors: Narayan Gurung, Fawu Wang, Ranjan Kumar Dahal

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Nepal is highly prone to earthquakes and has witnessed at least one major earthquake in 80 to 90 years interval. The Gorkha earthquake, that measured 7.8 RS in magnitude and struck Nepal on 25th April 2015, after 81 years since Mw 8.3 Nepal Bihar earthquake in 1934, was the largest earthquake after Mw 8.3 Nepal Bihar earthquake. In this paper, an attempt has been made to highlight the lessons learnt from the MwW 7.8 Gorkha (Nepal) earthquake. Several types of damage patterns in buildings were observed for reinforced concrete buildings, as well as for unreinforced masonry and adobe houses in the earthquake of 25 April 2015. Many field visits in the affected areas were conducted, and thus, associated failure and damage patterns were identified and analyzed. Damage patterns in non-engineered buildings, middle and high-rise buildings, commercial complexes, administrative buildings, schools and other critical facilities are also included from the affected districts. For most buildings, the construction and structural deficiencies have been identified as the major causes of failure; however, topography, local soil amplification, foundation settlement, liquefaction associated damages and buildings built in hazard-prone areas were also significantly observed for the failure or damages to buildings and hence are reported. Finally, the lessons learnt from Mw 7.8 Gorkha (Nepal) earthquake are presented in order to mitigate impacts of future earthquakes in Nepal.

Keywords: Gorkha earthquake, reinforced concrete structure, Nepal, lesson learnt

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Authors: Abouzar Kaboudian, Ravi Chaithanya Mysa, Boo Cheong Khoo, Rajeev Kumar Jaiman

Abstract:

Vortex induced vibrations can significantly affect the effectiveness of structures in aerospace as well as offshore marine industries. The oscillatory nature of the forces resulting from the vortex shedding around bluff bodies can result in undesirable effects such as increased loading, stresses, deflections, vibrations and noise in the structures, and also reduced fatigue life of the structures. To date, most studies concentrate on either the free oscillations or the prescribed motion of the bluff bodies. However, the structures in operation are usually subject to the external oscillatory forces (e.g. due to the platform motions in offshore industries). Periodic forces can be considered as a combinations of sinusoids. In this work, we present the effects of sinusoidal external cross-flow forces on the vortex-induced vibrations of an oscillating cylinder. The effects of the amplitude, as well as the frequency of these sinusoidal external force on the fluid-forces on the oscillating cylinder are carefully studied and presented. Moreover, we present the transition of the response to be dominated by the vortex-induced-vibrations to the range where it is mostly dictated by the external oscillatory forces. Furthermore, we will discuss how the external forces can affect the flow structures around a cylinder. All results are compared against free oscillations of the cylinder.

Keywords: circular cylinder, external force, vortex-shedding, VIV

Procedia PDF Downloads 369

Authors: Arjun K., Arumugam Sankaran, Sanjay Kumar, Mousumi Das

Abstract:

The paper analyses the existence of endogenous growth scenario emanating from the demographic dividend in India during the liberalization period starting from 1980. Demographic dividend creates a fertile ground for the cultivation of human and knowledge capitals contributing to technological progress which can be measured using total factor productivity. The relationship among total factor productivity, human and knowledge capitals are examined in an open endogenous framework for the period 1980-2016. The control variables such as foreign direct investment, trade openness, energy consumption are also employed. The data are sourced from Reserve Bank of India, World Bank, International Energy Agency and The National Science and Technology Management Information System. To understand the dynamic association among variables, ARDL bounds approach to cointegration followed by Toda-Yamamoto causality test are used. The results reveal a short run and long run relationship among the variables supported by the existence of causality. This calls for an integrated policy to build and augment human capital and research and development activities to sustain and pace up growth and development in the nation.

Keywords: demographic dividend, young population, open endogenous growth models, human and knowledge capital

Procedia PDF Downloads 151

Authors: Mrinmoy Majumder, Apu Kumar Saha

Abstract:

The ever-increasing human population and its demand for energy is placing stress upon conventional energy sources; and as demand for power continues to outstrip supply, the need to optimize energy distribution and utilization is emerging as an important focus for various stakeholders. The distribution of available energy must be achieved in such a way that the needs of the consumer are satisfied. However, if the availability of resources is not sufficient to satisfy consumer demand, it is necessary to find a method to select consumers based on factors such as their socio-economic or environmental impacts. Weighting consumer types in this way can help separate them based on their relative importance, and cognitive optimization of the allocation process can then be carried out so that, even on days of particularly scarce supply, the socio-economic impacts of not satisfying the needs of consumers can be minimized. In this context, the present study utilized fuzzy logic to assign weightage to different types of consumers based at an educational campus in India, and then established optimal allocation by applying the non-linear mapping capability of neuro-genetic algorithms. The outputs of the algorithms were compared with similar outputs from particle swarm optimization and differential evolution algorithms. The results of the study demonstrate an option for the optimal utilization of available energy based on the socio-economic importance of consumers.

Keywords: power allocation, optimization problem, neural networks, environmental and ecological engineering

Procedia PDF Downloads 479

Authors: Vinod Kumar, Surjit Angra

Abstract:

The objective of this theoretical study is to develop simple design formulas for the prediction of minimum film thickness and maximum mean film temperature rise in lightly loaded high-speed rolling/sliding lubricated elliptical contacts incorporating starvation effect. Herein, the reported numerical analysis focuses on thermoelastohydrodynamically lubricated rolling/sliding elliptical contacts, considering the Newtonian rheology of lubricant for wide range of operating parameters, namely load characterized by Hertzian pressure (PH = 0.01 GPa to 0.10 GPa), rolling speed (>10 m/s), slip parameter (S varies up to 1.0), and ellipticity ratio (k = 1 to 5). Starvation is simulated by systematically reducing the inlet supply. This analysis reveals that influences of load, rolling speed, and level of starvation are significant on the minimum film thickness. However, the maximum mean film temperature rise is strongly influenced by slip in addition to load, rolling speed, and level of starvation. In the presence of starvation, reduction in minimum film thickness and increase in maximum mean film temperature are observed. Based on the results of this study, empirical relations are developed for the prediction of dimensionless minimum film thickness and dimensionless maximum mean film temperature rise at the contacts in terms of various operating parameters.

Keywords: starvation, lubrication, elliptical contact, traction, minimum film thickness

Procedia PDF Downloads 392

Authors: Rajinder Pal Kaur, Amit Sharma, Anuj Kumar Sharma, Govind Prasad Sahu

Abstract:

The existence of chaos in the marine ecosystems may cause planktonic blooms, disease outbreaks, extinction of some plankton species, or some complex dynamics in oceans, which can adversely affect the sustainable marine ecosystem. The control of the chaotic plankton-fish dynamics is one of the main motives of marine ecologists. In this paper, we have studied the impact of phytoplankton refuge, zooplankton refuge, and fear effect on the chaotic plankton-fish dynamics incorporating phytoplankton, zooplankton, and fish biomass. The fear of fish predation transfers the unpredictable(chaotic) behavior of the plankton system to a stable orbit. The defense mechanism developed by prey species due to fear of the predator population can also terminate chaos from the given dynamics. Moreover, the impact of external disturbances like seasonality, noise, periodic fluctuations, and time delay on the given chaotic plankton system has also been discussed. We have applied feedback mechanisms to control the complexity of the system through the parameter noise. The non-feedback schemes are implemented to observe the role of seasonal force, periodic fluctuations, and time delay in suppressing the given chaotic system. Analytical results are substantiated by numerical simulation.

Keywords: plankton, chaos, noise, seasonality, fluctuations, fear effect, prey refuge

Procedia PDF Downloads 84