Search results for: Chandan Deep Singh

Authors: Y. Suchitra Devi, L. Hemchandra Singh

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Background: Because of its geographical location, Manipur lies in the conventional goiter endemic belt. During the post salt iodization period, endemic goiter was prevalent in the valley districts of Manipur without iodine deficiency. Objectives: The present study aim at the prevalence of goiter among school children (6-12 years) and women of reproductive age group (above 20 years) of Andro Assembly Constituency, Imphal- East, Manipur, India. Method: A total of 3992 individuals were clinically examined for thyroid enlargement. Hormones like TSH, FT₄, FT₃, and Anti-TPO, Anti-Tg were tested, UIC, USCN, testing of iodine in water and salt. Result: Total goiter prevalence was found to be 13.98%, median urinary iodine level was 166.0 µg/l, mean urinary thiocyanate concentration was 0.726 ± 0.408, mean water iodine concentration was 3.843 ± 2.291, and all the salt samples were above 15ppm. 6 out of 41 children and 93 out of 176 women were auto antibody positive. 41 children and 176 women were tested for TSH, FT₄, and FT₃, which shows disturbance in hormone level. Conclusion: The present study showed that the region is mildly goiter endemic without biochemical iodine deficiency.

Keywords: goiter, TSH, FT₄, FT₃, anti-TPO, anti-Tg, UIC, USCN, school children and women of reproductive age

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Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

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Nowadays, steel structures are used for not only common buildings but also high-rise construction and wide span covering. The advanced methods of construction as well as the advanced structural connections have a great effect on architecture. However a better use of steel structural systems will be achieved with the deep understanding of steel structures specifications and their substantial advantages. On the other hand, the steel structures face to the different environmental factors such as air flow which cause erosion and corrosion. With the time passing, the amount of these steel mass damages and also the imposed stress will be increased. In other words, the position of erosion in steel structures related to existing stresses indicates that effective environmental conditions will gradually decrease the structural resistance of steel components and result in decreasing the durability of steel components. In this paper, the durability of different steel structural components is evaluated and on the basis of these stress, architectural strategies for designing the system and the components of steel structures is recognized in order to achieve an optimum life cycle.

Keywords: durability, bending stress, erosion in steel structure, life cycle

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Authors: Zzibu Mark Brian

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As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

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Authors: Sadhana Shukla, Pushplata Singh, Nidhi Didwania

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Arbuscular mycorrhizal (AM) fungi are a highly advantageous and versatile group of fungi that significantly contribute to the formation of soil organic matter by creating a demand for plant carbon (C) and distributing it through below-ground hyphal biomass, regardless of their substantial contribution in enhancing net primary productivity and accumulating additional photosynthetic fixed C in the soil. The genetic role of AM fungi in carbon cycling is largely unexplored. In our study, we propose that AM fungi significantly interact with the soil, particularly: the provision of photosynthates by plants. We have studied the expression of AM fungi genes involved in CO₂ sequestration during host-plant interaction was investigated by qPCR studies. We selected Rhizophagus proliferus (AM fungi) and Oryza sativa (Rice) (inoculated with or without 200ppg AMF inoculums per plant) and investigated the effect of AM fungi on soil organic carbon (SOC) and rice growth under field conditions. Results thus provided faster SOC turnover, 35% increased nutrient uptake in plants and pronounced hyphal biomass of AM fungi which enhanced soil carbon storage by 15% in comparison to uninoculated plants. This study will offer a foundation for delving into various carbon-soil studies while also advancing our comprehension of the relationship between AM fungi and the sustainability of agricultural ecosystems.

Keywords: arbuscular mycorrhizal (AM) fungi, carbon sequestration, gene expression, soil health, plant development.

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Authors: Raghvendra Singh Yadav, Ivo Kuřitka, Jarmila Vilcakova, Jaromir Havlica, Lukas Kalina, Pavel Urbánek, Michal Machovsky, Milan Masař, Martin Holek

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In this work, CoFe₂₋ₓGdₓO₄ (x=0.00, 0.05, 0.10, 0.15, 0.20) spinel ferrite nanoparticles are synthesized by sonochemical method. The structural properties and cation distribution are investigated using X-ray Diffraction (XRD), Raman Spectroscopy, Fourier Transform Infrared Spectroscopy and X-ray photoelectron spectroscopy. The morphology and elemental analysis are screened using field emission scanning electron microscopy (FE-SEM) and energy dispersive X-ray spectroscopy, respectively. The particle size measured by FE-SEM and XRD analysis confirm the formation of nanoparticles in the range of 7-10 nm. The electrical properties show that the Gd³⁺ doped cobalt ferrite (CoFe₂₋ₓGdₓO₄; x= 0.20) exhibit enhanced dielectric constant (277 at 100 Hz) and ac conductivity (20.17 x 10⁻⁹ S/cm at 100 Hz). The complex impedance measurement study reveals that as Gd³⁺ doping concentration increases, the impedance Z’ and Z’ ’ decreases. The influence of Gd³⁺ doping in cobalt ferrite nanoparticles on the magnetic property is examined by using vibrating sample magnetometer. Magnetic property measurement reveal that the coercivity decreases with Gd³⁺ substitution from 234.32 Oe (x=0.00) to 12.60 Oe (x=0.05) and further increases from 12.60 Oe (x=0.05) to 68.62 Oe (x=0.20). The saturation magnetization decreases with Gd³⁺ substitution from 40.19 emu/g (x=0.00) to 21.58 emu/g (x=0.20). This decrease follows the three-sublattice model suggested by Yafet-Kittel (Y-K). The Y-K angle increases with the increase of Gd³⁺ doping in cobalt ferrite nanoparticles.

Keywords: sonochemical method, nanoparticles, magnetic property, dielectric property, electrical property

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Authors: Vikram Singh, Parmod Kumar Sethi

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The objective of the study was to study the effectiveness of common yoga protocol on reaction time (choice visual reaction time, measured in milliseconds/seconds) of male football players in the age group of 16 to 21 years. The 40 boys were measured initially on parameters of years of experience, level of participation. They were randomly assigned into two groups i.e. control and experimental. CVRT for both the groups was measured on day-1 and post intervention (common yoga protocol here) was measured after 45 days of training to the experimental group after they had finished with their regular fitness and soccer skill training. One way ANOVA (Univariate analysis) and Independent t-test using SPSS 23 statistical package were applied to get and analyze the results. The experimental yoga protocol group showed a significant reduction in CVRT, whereas the insignificant difference in reaction times was observed for control group after 45 days. The effect size was more than 52% for CVRT indicating that the effect of treatment was large. Power of the study was also found to be high (> .80). There was a significant difference after 45 days of yoga protocol in choice visual reaction time of experimental group (p = .000), t (21.93) = 6.410, p = .000 (two-tailed). The null hypothesis (that there would be no difference in reaction times of control and experimental groups) was rejected. Where p< .05. Therefore alternate hypothesis was accepted.

Keywords: reaction time, yoga protocol, t-test, soccer players

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Authors: Srinivasan Chandrasekaran, Manda Hari Venkata Ramachandra Rao

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Increase in the oil and gas exploration in ultra deep-water demands an adaptive structural form of the platform. Triceratops has superior motion characteristics compared to that of the Tension Leg Platform and Single Point Anchor Reservoir platforms, which is well established in the literature. Buoyant legs that support the deck are position-restrained to the sea bed using tethers with high axial pretension. Environmental forces that act on the platform induce dynamic tension variations in the tethers, causing the failure of tethers. The present study investigates the dynamic response behavior of the restraining system of the platform under the failure of a single tether of each buoyant leg in high sea states. Using the rain-flow counting algorithm and the Goodman diagram, fatigue damage caused to the tethers is estimated, and the fatigue life is predicted. Results shows that under failure conditions, the fatigue life of the remaining tethers is quite alarmingly low.

Keywords: fatigue life, pm spectrum, rain flow counting, triceratops, failure analysis

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Authors: Minaj Ranjita Singh, Meghna Mukherjee, Abhijeet Jadhav

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This is an exploratory qualitative study with an objective to understand the bathing practices followed by rural women and its consequences. Access to safe bathing spaces in rural India is a neglected issue due to which women are affected in various ways. Today, government policies are largely focused towards the building of toilets, but no importance has been given to the construction of bathrooms. Both qualitative and quantitative data were collected using in-depth interviews and focused group discussions with rural women in six villages of Odisha, India. The study was approved by an Institutional Research and Ethics Committee, and informed consent was taken from participants. For most of the participants, the access to water, bathing space and toilet was compromised posing various challenges in their daily lives. Women's daily schedule, hygiene practices, dignity, and health are greatly affected due to this lack. Since bathing in the open has been an ancient practice, the community's perception is benign towards the hardship of women. Lack of exposure to concealed bathing, necessary funds, and competing priorities are some of the household level factors which never let them think about having bathrooms and the lack of water supply, proper drainage system, subsidy or financial support are the governance and policy related factors which prevent their access to secured bathing spaces.

Keywords: bathrooms, dignity, exploratory, rural, qualitative, women's health, women

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Authors: Shaban Aly, Ali Al-Qahtani, Houari B. Khenous

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Synchronization is an important phenomenon commonly observed in nature. A system of periodically forced complex Duffings oscillators was introduced and shown to display chaotic behavior and possess strange attractors. Such complex oscillators appear in many problems of physics and engineering, as, for example, nonlinear optics, deep-water wave theory, plasma physics and bimolecular dynamics. In this paper, we study the remarkable phenomenon of chaotic synchronization on these oscillator systems, using impulsive synchronization techniques. We derive analytical expressions for impulsive control functions and show that the dynamics of error evolution is globally stable, by constructing appropriate Lyapunov functions. This means that, for a relatively large set initial conditions, the differences between the drive and response systems vanish exponentially and synchronization is achieved. Numerical results are obtained to test the validity of the analytical expressions and illustrate the efficiency of these techniques for inducing chaos synchronization in our nonlinear oscillators.

Keywords: complex nonlinear oscillators, impulsive synchronization, chaotic systems, global exponential synchronization

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Authors: Kaustav Mukherjee

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In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

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Authors: Jonas De Kerf, Rein De Cooman, Sara De Gieter

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For many decades, scholars have aimed to understand how work can become more meaningful by maximizing both potential and enhancing feelings of satisfaction. One of the largest contributions towards such positive psychology was made with the introduction of the concept of ‘flow,’ which refers to a condition in which people feel intense engagement and effortless action. Since then, valuable research on work-related flow has indicated that this state of mind is related to positive outcomes for both organizations (e.g., social, supportive climates) and workers (e.g., job satisfaction). Yet, scholars still do not fully comprehend how such deep involvement at work is obtained, given the notion that flow is considered a short-term, complex, and dynamic experience. Most research neglects that people who experience flow ought to be optimally challenged so that intense concentration is required. Because attention is at the core of this enjoyable state of mind, this study aims to comprehend how elements that affect workers’ cognitive functioning impact flow at work. Research on cognitive performance suggests that working on mentally demanding tasks (e.g., information processing tasks) requires workers to concentrate deeply, as a result leading to flow experiences. Based on social facilitation theory, working on such tasks in an isolated environment eases concentration. Prior research has indicated that working at home (instead of working at the office) or in a closed office (rather than in an open-plan office) impacts employees’ overall functioning in terms of concentration and productivity. Consequently, we advance such knowledge and propose an interaction by combining cognitive task characteristics and work environments among part-time teleworkers. Hence, we not only aim to shed light on the relation between cognitive tasks and flow but also provide empirical evidence that workers performing such tasks achieve the highest states of flow while working either at home or in closed offices. In July 2022, an experience-sampling study will be conducted that uses a semi-random signal schedule to understand how task and environment predictors together impact part-time teleworkers’ flow. More precisely, about 150 knowledge workers will fill in multiple surveys a day for two consecutive workweeks to report their flow experiences, cognitive tasks, and work environments. Preliminary results from a pilot study indicate that on a between level, tasks high in information processing go along with high self-reported fluent productivity (i.e., making progress). As expected, evidence was found for higher fluency in productivity for workers performing information processing tasks both at home and in a closed office, compared to those performing the same tasks at the office or in open-plan offices. This study expands the current knowledge on work-related flow by looking at a task and environmental predictors that enable workers to obtain such a peak state. While doing so, our findings suggest that practitioners should strive for ideal alignments between tasks and work locations to work with both deep involvement and gratification.

Keywords: cognitive work, office lay-out, work location, work-related flow

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Authors: Seyed Abolhasan Naeini, Javad Shamsi Soosahab

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The use of geosynthetic reinforcement within the footing soils is a very effective and useful method to avoid the construction of costly deep foundations. This study investigated the use of geosynthetics for soil improvement based on numerical modeling using FELA software. Pressure settlement behavior and bearing capacity ratio of foundation on geogrid reinforced sand is investigated and the effect of different parameters like as number of geogrid layers and vertical distance between elements in three different relative density soil is studied. The effects of geometrical parameters of reinforcement layers were studied for determining the optimal values to reach to maximum bearing capacity. The results indicated that the optimum range of the distance ratio between the reinforcement layers was achieved at 0.5 to 0.6 and after number of geogrid layers of 4, no significant effect on increasing the bearing capacity of footing on reinforced sandy with geogrid

Keywords: geogrid, reinforced sand, FELA software, distance ratio, number of geogrid layers

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Authors: Harinder Singh

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The paper sheds light on the perceptions of the uninsured workers employed in the urban informal sector of India, towards the health insurance. In addition to this, it also explores the association of the identified perceptions with household decisions to enroll for health insurance schemes in India. Firstly the data taken from the primary survey of the uninsured workers employed in the urban informal sector was analyzed using exploratory factor analysis to evaluate the perceptions. Thereafter, logistic regression was employed to determine the association of the identified perceptions regarding the enrollment. Our study identifies twelve perceptions related to the health insurance enrollment of the uninsured workers employed in the urban informal sector of India. The study demonstrates that perceptions have the strongest association with the voluntary enrollment. These specifically relate to the lack of awareness about the need to buy health insurance; comprehensive coverage; income constraint; future contingencies and social obligations; lack of information; availability of subsidized government health care; linkage with government hospitals and preference for government schemes. Conclusions: Along with the food security, health security has become a crying need of the workers employed in the informal sector and the time has come to scale up the health insurance schemes for them in the country. Policy makers or marketers of health insurance policies should recognize the household perceptions as a potential barrier and try to develop a health insurance package as per the actual needs of the informal sector (low income) in India.

Keywords: association, enrollment, health insurance, informal sector, perceptions, uninsured

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Authors: Dhanpat Singh Dhania

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Kurma-avatara and the Kachchhapraj is the name of the same person. Tortoise is called Kurma in Kerma valley (Nubia) and also called Kachchhap in India. Wherever a culture migrates, its faiths and beliefs remain intact. The tortoise culture of Kurma valley migrated to Dholavira, and its cultural symbolism remained the same as Kurma, the tortoise. Culture is known by burial traditions, pottery formations, language use, faiths, and beliefs. Following the cultural identification methodology, the Kurma culture buried their dead in circular burials found during excavation at Toshka, Nubia, and built their houses the type of tortoise shell. The Nubian tortoise of a specific species had a triangular on the shell found to be extinct was the cultural symbolism of the culture found on the excavated pottery. Kurma cultural head known as the Seth was known as Kurma-avatara. The Seth of Egypt came to know when the combined efforts of the Seth and the Osiris defeated the Egyptian 1st dynastic rule in about 2775 BCE. Osiris became the king of the 2nd dynastic Egypt. It annoyed Seth. He killed the Osiris and went to Rann of Kachchh and declared him as the Chachchhapraj, the king of Kachchh (now Gujarat, India). The Kurma (Kachchhap) culture migration at Dholavira (Gujarat) attested by the Dholavira signboard found during excavation and deciphered as the ‘Chakradhar’, the eighth incarnation of Kurma-avatara.

Keywords: Kurma, Egyptian, Kachchhap, Dholavira, Harappan

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Authors: Tanish Mittal, Preyansh Agrawal, Esha Pahwa, Aarya Makwana

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Multi-Scale and U-shaped Networks are widely used in various image restoration problems, including deblurring. Keeping in mind the wide range of applications, we present a comparison of these architectures and their effects on image deblurring. We also introduce a new block called as NFResblock. It consists of a Fast Fourier Transformation layer and a series of modified Non-Linear Activation Free Blocks. Based on these architectures and additions, we introduce NFResnet and NFResnet+, which are modified multi-scale and U-Net architectures, respectively. We also use three differ-ent loss functions to train these architectures: Charbonnier Loss, Edge Loss, and Frequency Reconstruction Loss. Extensive experiments on the Deep Video Deblurring dataset, along with ablation studies for each component, have been presented in this paper. The proposed architectures achieve a considerable increase in Peak Signal to Noise (PSNR) ratio and Structural Similarity Index (SSIM) value.

Keywords: multi-scale, Unet, deblurring, FFT, resblock, NAF-block, nfresnet, charbonnier, edge, frequency reconstruction

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Authors: Sonveer Singh, Sanjay Agrawal, D. V. Avasthi, Jayant Shekhar

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The aim of this paper is to improve the efficiency of photovoltaic thermal (PVT) system with the help of Genetic Algorithms with multi-objective function. There are some parameters that affect the efficiency of PVT system like depth and length of the channel, velocity of flowing fluid through the channel, thickness of the tedlar and glass, temperature of inlet fluid i.e. all above parameters are considered for optimization. An attempt has been made to the model and optimizes the parameters of glazed hybrid single channel PVT module when two objective functions have been considered separately. The two objective function for optimization of PVT module is overall electrical and thermal efficiency. All equations for PVT module have been derived. Using genetic algorithms (GAs), above two objective functions of the system has been optimized separately and analysis has been carried out for two cases. Two cases are: Case-I; Improvement in electrical and thermal efficiency when overall electrical efficiency is optimized, Case-II; Improvement in electrical and thermal efficiency when overall thermal efficiency is optimized. All the parameters that are used in genetic algorithms are the parameters that could be changed, and the non-changeable parameters, like solar radiation, ambient temperature cannot be used in the algorithm. It has been observed that electrical efficiency (14.08%) and thermal efficiency (19.48%) are obtained when overall thermal efficiency was an objective function for optimization. It is observed that GA is a very efficient technique to estimate the design parameters of hybrid single channel PVT module.

Keywords: genetic algorithm, energy, exergy, PVT module, optimization

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Authors: Rupinder Kaur, Parmjit S. Panesar, Ram S. Singh

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Whey is the lactose rich by-product of the dairy industry, having good amount of nutrient reservoir. Most abundant nutrients are lactose, soluble proteins, lipids and mineral salts. Disposing of whey by most of milk plants which do not have proper pre-treatment system is the major issue. As a result of which, there can be significant loss of potential food and energy source. Thus, whey has been explored as the substrate for the synthesis of different value added products such as enzymes. β-galactosidase is one of the important enzymes and has become the major focus of research due to its ability to catalyze both hydrolytic as well as transgalactosylation reaction simultaneously. The enzyme is widely used in dairy industry as it catalyzes the transformation of lactose to glucose and galactose, making it suitable for the lactose intolerant people. The enzyme is intracellular in both bacteria and yeast, whereas for molds, it has an extracellular location. The present work was carried to utilize the whey for the production of β-galactosidase enzyme using both yeast and fungal cultures. The yeast isolate Kluyveromyces marxianus WIG2 and various fungal strains have been used in the present study. Different disruption techniques have also been investigated for the extraction of the enzyme produced intracellularly from yeast cells. Among the different methods tested for the disruption of yeast cells, SDS-chloroform showed the maximum β-galactosidase activity. In case of the tested fungal cultures, Aureobasidium pullulans NCIM 1050, was observed to be the maximum extracellular enzyme producer.

Keywords: β-galactosidase, fungus, yeast, whey

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Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

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Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

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Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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Authors: Sanjeet Kumar Singh, Shanatanu Bhattacharaya

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Design of high- efficiency low, frequency (<1000Hz) soundproof window or wall absorber which is transparent to airflow is presented. Due to the massive rise in human population and modernization, environmental noise has significantly risen globally. Prolonged noise exposure can cause severe physiological and psychological symptoms like nausea, headaches, fatigue, and insomnia. There has been continuous growth in building construction and infrastructure like offices, bus stops, and airports due to urban population. Generally, a ventilated window is used for getting fresh air into the room, but at the same time, unwanted noise comes along. Researchers used traditional approaches like noise barrier mats in front of the window or designed the entire window using sound-absorbing materials. However, this solution is not aesthetically pleasing, and at the same time, it's heavy and not adequate for low-frequency noise shielding. To address this challenge, we design a transparent hexagonal panel based on Sierpiński fractal triangle, which is aesthetically pleasing, demonstrates normal incident sound absorption coefficient more than 0.96 around 700 Hz and transmission loss around 23 dB while maintaining e air circulation through triangular cutout. Next, we present a concept of fabrication of large acoustic panel for large-scale applications, which lead to suppressing the urban noise pollution.

Keywords: acoustic metamaterials, noise, functional materials, ventilated

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Authors: Ayush Shrivastava, Arpit Chaudhary, Devang Kulshreshtha, Vibhav Prakash Singh, Rajeev Srivastava

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Early diagnosis of breast cancer can improve the survival rate by detecting cancer at an early stage. Breast region segmentation is an essential step in the analysis of digital mammograms. Accurate image segmentation leads to better detection of cancer. It aims at separating out Region of Interest (ROI) from rest of the image. The procedure begins with removal of labels, annotations and tags from the mammographic image using morphological opening method. Pectoral Muscle Sliding Window Algorithm (PMSWA) is used for removal of pectoral muscle from mammograms which is necessary as the intensity values of pectoral muscles are similar to that of ROI which makes it difficult to separate out. After removing the pectoral muscle, Dispersed Region Growing Algorithm (DRGA) is used for segmentation of mammogram which disperses seeds in different regions instead of a single bright region. To demonstrate the validity of our segmentation method, 322 mammographic images from Mammographic Image Analysis Society (MIAS) database are used. The dataset contains medio-lateral oblique (MLO) view of mammograms. Experimental results on MIAS dataset show the effectiveness of our proposed method.

Keywords: CAD, dispersed region growing algorithm (DRGA), image segmentation, mammography, pectoral muscle sliding window algorithm (PMSWA)

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Authors: Heval Serhat Uluk, Sam M. Dakka, Kuldeep Singh, Richard Jefferson-Loveday

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This paper will focus on the suitability of a trapped vortex combustor as a candidate for gas turbine combustor objectives to minimize pressure drop across the combustor and investigate aerodynamic performance. Non-reacting simulation of axisymmetric cavity trapped vortex combustors were simulated to investigate the pressure drop for various cavity aspect ratios of 0.3, 0.6, and 1 and for air mass flow rates of 14 m/s, 28 m/s, and 42 m/s. A numerical study of an axisymmetric trapped vortex combustor was carried out by using two-dimensional and three-dimensional computational domains. A comparison study was conducted between Reynolds Averaged Navier Stokes (RANS) k-ε Realizable with enhanced wall treatment and RANS k-ω Shear Stress Transport (SST) models to find the most suitable turbulence model. It was found that the k-ω SST model gives relatively close results to experimental outcomes. The numerical results were validated and showed good agreement with the experimental data. Pressure drop rises with increasing air mass flow rate, and the lowest pressure drop was observed at 0.6 cavity aspect ratio for all air mass flow rates tested, which agrees with the experimental outcome. A mixing enhancement study showed that 30-degree angle air injectors provide improved fuel-air mixing.

Keywords: aerodynamic, computational fluid dynamics, propulsion, trapped vortex combustor

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Authors: Taha Kadir Yesin, Hanyu Liu, Zhangfan Ding, Amit Singh, Qi Tian, Yuheng Zhang, Biswajyoti Borah, Junyu Chen, Anjali P. Kusumbe

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The skeletal structure and bone marrow endothelium collectively form a critical functional unit essential for bone development, health, and aging. At the core of osteogenesis and bone formation lies the dynamic process of angiogenesis. In this study, we reveal a potent endogenous anabolic NCAM1-14.3.3. ζδ-derived- Peptide interaction, which stimulates bone angiogenesis and osteogenesis during homeostasis, aging, and age-related bone diseases. Employing high-resolution imaging and inducible cell-specific mouse genetics, our results elucidate the pivotal role of the NCAM1-14.3.3.ζδ-derived-Peptide interaction in driving the expansion of Clec14a+ angiogenic endothelial cells. Notably, Clec14a+ endothelial cells express key osteogenic factors. The NCAM1-14.3.3.ζδ-derived-Peptide interaction in osteoblasts drives osteoblast differentiation, ultimately contributing to the genesis of bone. Moreover, the NCAM1-14.3.3.ζδ-derived-Peptide interaction leads to a reduction in bone resorption. In age-associated vascular and bone loss diseases, stimulating the NCAM1-14.3.3.ζδ-derived-Peptide interaction not only promotes angiogenesis but also reverses bone loss. Consequently, harnessing the endogenous anabolic potential of the NCAM1-14.3.3.ζδ-derived-Peptide interaction emerges as a promising therapeutic modality for managing age-related bone diseases.

Keywords: endothelial cell, NCAM1, Clec14a, 14.3.3.ζδ

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Authors: Xiuying Wang, Changliang Li, Bo Xu

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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

Abstract:

Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

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Authors: Atwari Rawani, Suresh Prasad Sharma, K. D. P. Singh

Abstract:

In this paper, an analytical investigation based on energy and exergy analysis of the parabolic trough collector (PTC) with alternate clockwise and counter-clockwise twisted tape inserts in the absorber tube has been presented. For fully developed flow under quasi-steady state conditions, energy equations have been developed in order to analyze the rise in fluid temperature, thermal efficiency, entropy generation and exergy efficiency. Also the effect of system and operating parameters on performance have been studied. A computer program, based on mathematical models is developed in C++ language to estimate the temperature rise of fluid for evaluation of performances under specified conditions. For numerical simulations four different twist ratio, x = 2,3,4,5 and mass flow rate 0.06 kg/s to 0.16 kg/s which cover the Reynolds number range of 3000 - 9000 is considered. This study shows that twisted tape inserts when used shows great promise for enhancing the performance of PTC. Results show that for x=1, Nusselt number/heat transfer coefficient is found to be 3.528 and 3.008 times over plain absorber of PTC at mass flow rate of 0.06 kg/s and 0.16 kg/s respectively; while corresponding enhancement in thermal efficiency is 12.57% and 5.065% respectively. Also the exergy efficiency has been found to be 10.61% and 10.97% and enhancement factor is 1.135 and 1.048 for same set of conditions.

Keywords: exergy efficiency, twisted tape ratio, turbulent flow, useful heat gain

Procedia PDF Downloads 173

Authors: Yogendra Sisodia

Abstract:

Researchers are becoming more interested in extracting useful information from legal documents thanks to the development of large-scale language models in natural language processing (NLP), and deep learning has accelerated the creation of powerful text mining models. Legal fields like contracts benefit greatly from semantic text search since it makes it quick and easy to find related clauses. After collecting sentence embeddings, it is relatively simple to locate sentences with a comparable meaning throughout the entire legal corpus. The author of this research investigated two pre-trained language models for this task: MiniLM and Roberta, and further fine-tuned them on Legal Contracts. The author used Multiple Negative Ranking Loss for the creation of sentence transformers. The fine-tuned language models and sentence transformers showed promising results.

Keywords: legal contracts, multiple negative ranking loss, natural language inference, sentence transformers, semantic textual similarity

Procedia PDF Downloads 108

Authors: Veepaul Kaur Mann Balwinder Singh

Abstract:

The COVID-19 had an intense impact on several countries across the world. National governments have imposed widespread restrictions to prevent the growth of this pandemic. The new health competitive scenario induced by the COVID-19 crisis raised many issues on how business activities should be reorganized due to the difficulties of physical interactions with distributors, suppliers and customers. The pandemic has particularly affected the whole selling process because of the relevant issues that emerged in managing physical sale channels and interactions with one another, both in the Business-to-Consumer and in the Business-to-Business markets. Recent research about the appropriate actions and strategies that could help firms overcome the crisis has highlighted the key role of digital expertise that may ensure connections and, thus, help business activities run smoothly. This could be true, especially with the occurrence of strong limitations on physical interactions during the COVID-19 pandemic. The catastrophe changes life publically and economically. People are living alone for following the social distancing norms. In that set-up, Digital Marketing is playing an important role in civilization. Anyone can buy any item, pay bills, transfer money and compare items through Digital Marketing without physical interactions. After COVID-19, people will be more aware of health safety and trust. So, through Digital Marketing, organizations can approach customers and provide good service environments. In such a situation, the online network becomes the most important encouraging for online customers to get in contact with the firm and carry out online selling and purchasing activities around the world.

Keywords: COVID-19, business, digital marketing, online customer

Procedia PDF Downloads 54

Authors: Aneri Mehta, Krunal Mehta

Abstract:

Administration is largely based on two sciences: ‘management science’ and ‘political science’. The approach of new public management is more inclined towards the management science. Era of ‘New Public Management’ has affected the developing countries very immensely. Public management reforms are needed to enhance the development of the countries. This reform mainly includes capacity building, control of corruption, political decentralization, debureaucratization and public empowerment. This gives the opportunity to create self-sustaining change in the governance. This paper includes the link of approach of new public management and their effect on building effective democratization in the country. This approach mainly focuses on rationality and effectiveness of governance system. These need to have deep efforts on technological, organizational, social and cultural fields. Bringing citizen participation in governance is main objective of NPM. The shift from traditional public management to new public management have low success rate of reforms. This research includes case study of RTI which is a big step of government towards citizen centric approach of governance. The aspect of ‘publicness’ in the democratic policy implementation is important for good governance in India.

Keywords: public management, development, public empowerment, governance

Procedia PDF Downloads 506

Authors: Arun Kumar Singh, Rupesh M. Das, Shailendra Saini

Abstract:

The effect of solar cycle and seasons on the total electron content has been investigated over high latitude region during 24th solar cycle (2010-2014). The total electron content data has been observed with the help of Global Ionospheric Scintillation and TEC monitoring (GISTM) system installed at Indian permanent scientific 'Maitri station' [70˚46’00”S 11˚43’56” E]. The dependence of TEC over a solar cycle has been examined by the performing linear regression analysis between the vertical total electron content (VTEC) and daily total sunspot numbers (SSN). It has been found that the season and level of geomagnetic activity has a considerable effect on the VTEC. It is observed that the VTEC and SSN follow better agreement during summer seasons as compared to winter and equinox seasons and extraordinary agreement during minimum phase (during the year 2010) of the solar cycle. There is a significant correlation between VTEC and SSN during quiet days of the years as compared to overall days of the years (2010-2014). Further, saturation effect has been observed during maximum phase (during the year 2014) of the 24th solar cycle. It is also found that Ap index and SSN has a linear correlation (R=0.37) and the most of the geomagnetic activity occurs during the declining phase of the solar cycle.

Keywords: high latitude ionosphere, sunspot number, correlation, vertical total electron content

Procedia PDF Downloads 193