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721 research outputs found
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An Efcient Approach for Semantic Segmentation of Salt Domes in Seismic Images Using Improved UNET Architecture
Full text linkMany areas of Earth’s surface with large accumulations of gas and oil even have huge deposits of salt under the surface. Exploring such deposits helps many countries to increase the storage capacity of their Petroleum reserves and explore new ones. But fnding such deposits is a herculean task. Expert seismic imaging requires human interpretation of salt bodies. But this leads to very biased and highly variable translations. So the idea behind this paper is to build an approach that accurately and automatically identifes if the seismic image contains any region of salt deposit or not. If a surface is found to have salt deposits, then it may contain the accumulations of oil or gas and even the salt domes or caverns can be used as a storage site for already available petroleum or oil. Since semantic segmentation classifes every pixel in the given image to its class label, this can be used to segment the salt deposits from the provided seismic images. In this paper, we introduce a variation of UNet, a popular segmentation model, for seismic
image segmentation. We have added a batch normalization
layer following every convolution layer as a deeper network
helps extract better features which turned out to be tru
An Integrated Framework with Deep Learning for Segmentation and Classification of Cancer Disease
Full text linkThis paper addresses radiologists' specific diagnosis of cancer disease effectively using integrated framework of deep learning model. Although several existing diagnosis systems have
been adopted by a physician, in few cases, it is not so practical to see the infected area from images in the normal eye. Thus, a fully integrated diagnosis framework for disease detection is proposed to find out the infected area from image using deep learning approaches in this paper. In this proposed
framework, various components are designed through deep learning approaches such as detection, segmentation, classification etc. based on mass region. The classification technique is used to classify the disease as either benign or malignant. The vital part of this framework is developed by
using a full resolution convolutional network (FrCN) that supports different stages of image processing, especially breast cancer disease. Different experimental evaluation is taken to perform on the accuracy, cross-validation tests, and the comparative testing. Since we have taken 4-fold evaluation, the FrCN performs with an average 98.7% Dice index, 97.8% TS/CSI coefficient, 99.1% overall accuracy, and 98.15% MCC. Our experiments demonstrated that the proposed diagnosis
system performs on the deep learning approaches at each segmentation stage and classification with good result
Congestion Avoidance Using Enhanced Blue Algorithm
Full text linkThis paper addresses congestion avoidance using enhanced blue algorithm (EBA) for data transferring in a network. The congestion of data always afects the data transmission on
the internet for various applications. For developing data transmission performance, the congestion of data is a challenging task. Although, diferent approaches have been used
to avoid data congestion, yet we have considered a data transmission framework for better performance compare to existing approaches. Thus, we considered the advanced Blue
Algorithm which is used to determine the node’s capacity with middle path and it prevents
congestion by monitoring of data during data transmission. The role of gateway is considered to supervise status of congestion for both data sending and receiving based on positive
or negative acknowledgment as well as data size. The gateway is also used for a congestion notifcation system to alleviate congestion and enhance throughput. During experimental analysis, we have taken comparative performance between existing and our proposed model. For example, in Enhanced Ad hoc On-demand Distance Vector (EAODV), during the packet size of 10, the average end-to-end delay is 32.63 ms whereas in proposed advanced Blue algorithm, the average delay is only 19.11 ms. Thus, the proposed model using Blue algorithm is performed better than existing metho
Automated Attendance Tracking System using Face Recognition Technology
Full text linkThis abstract describes a face recognitionbased attendance system that utilizes advanced computer vision and machine learning techniques to accurately identify individuals and record their attendance. The system uses a camera to capture images of individuals, which are then processed by a deep learning model to extract facial features and match them against a database of known individuals. The system can handle large groups of people and can operate in various lighting and environmental conditions. The system provides real-time monitoring of attendance and generates reports, making it suitable for use in a wide range of applications, including schools, universities, and workplaces. Overall, this system offers a reliable and effcient alternative to traditional attendance tracking methods
Enhanced biosorption of Cr(VI) from contaminated water using biodegradable natural polymeric biosorbent
No full textBiosorption is a new technology for the exclusion of heavy metals from industrial runoffs. The current research was focused on an exploration of the sequestration of Cr(VI) from synthetic medium using turmeric leaves powder (TLP). Characterization of TLP before and after biosorption was studied using FTIR, SEM, EDS. Central Composite Design (CCD) based on Response Surface Methodology (RSM) was utilized to optimize key process variables like pH, initial concentration and dose. The maximum % biosorption (97.84 %) was achieved at optimized conditions of 2.14 pH, 20.32 mg/L initial concentration and 0.038 g dosage. Langmuir model and Pseudo second order rate models best suited the adsorption process, implying that Cr(VI) ions were adsorbed onto the TLP in monolayer due to their chemical affinity. The thermodynamic characteristics prove the process' feasibility, spontaneity, and exothermic nature of adsorption. Desorption tests were carried out to investigate the regain performance of the TLP in a variety of applications. The result infers that TLP is a promising, eco-friendly, effectual and economic biosorbent for removing Cr(VI) from aqueous media
Optimization of dead metal zone to reduce cutting forces in micro milling of Inconel 718 using RSM
Full text linkThis study focuses on the mechanism of DMZ (dead metal zone) creation, as well as the impact of cutting edge geometries (sharp, chamfered, double chamfered, and blunt edges), cutting speed, and coefficient of friction on DMZ formation while milling Inconel 718 material (FEM). A non-contact type sensor called a laser doppler vibrometer (LDV) is used to monitor the vibration of rotating surfaces. In current research work, the LDV is used to measure the mill cutter vibration in micro-milling of Inconel 718 in terms of acoustic optic emission signals. A FFT (fast fourier transformer) is used for signals processing in to frequency domain. Design of experiments as per Taguchi, experiments were performed on the alloy at three levels of spindle speeds, depth of cuts, feed rates. Experimental results on the amplitude o vibration of tool along X and Y directions, surface roughness were measured and analysed using response surface methodology. Analysis obtained from the variance was used to recognize the significant parameters which effect the vibration of tool and roughness of surface. RSM was implemented and optimized process parameters for the minimum vibration amplitude and surface roughnes
Block chain-based security and privacy framework for point of care health care IoT devices
Full text linkAs a consequence of linking technological advances, the IoE (Internet of Everything) and smarter living concepts have been formed. For enhancing people’s standard of living, getting anything intelligent becomes a key goal. Smarter medicine seems to be a fantastic illustration of that system because it offers timely, cost-effective, as well as ecological social activities. Furthermore, one of the biggest problems with intelligent medical apps is information safety but also confidentiality. Because of its irreversibility and transparent attributes, Block chain (BC) is being viewed as a possible alternative for such private administration of medical information. Moreover, there involves a trade-off between openness,as well as the security of customer information, that represents a significant obstacle to the adoption using BC for medical purposes. While many scientists have thought about client database security, as well as offered limited remedies, the most recent systems do not take database proprietors’ desires for accessing restrictions into account. Within that study, we initially classify different available privacy-enhancing techniques (PETs) and then evaluate their applicability to IoT applications that require confidentiality. Additionally, we classify any security concerns, dangers, or leaks associated with specific IoT usage scenarios. For ensuring safety but also anonymity throughout IoT applications, we also present a straightforward, new architecture for protecting confidentiality that is built on several applicable privacy-enhancing techniques. Utilizing a grouping technique, we tackle fundamental scaling, latency, and overall latency real-world BC developing concerns. Our in-depth empirical investigation demonstrates BC Research’s effectiveness (concerning calculation and execution duration), as well as resistance to various safety assaults
Design, synthesis and anticancer activity of sulfonamide derivatives of 1,2,3-triazole-indoles
No full textABSTRACT
A new series of sulfonamide derivatives of 1,2,3-triazole-indole (12a–j) were designed and pre�pared. All compounds were characterized by 1 HNMR, 13CNMR and mass spectral data. Further, all compounds (12a–j) were assessed for their in vitro anticancer effects against four different types of human cancer cell lines including Cervix cancer (SiHa), Lung cancer (A549), Breast cancer (MCF-7) and Colon cancer (Colo-205) using MTT method. Among the tested compounds, 12a, 12b, 12e, 12h, 12i and 12j displayed more potent anticancer activities as etoposide. Principally, one compound 12j possessed superior activity
Combustion, performance and emission characteristics of CI engine fueled with diesel and hydrogen based reactor
No full textThere is a significant role of using hydrogen in engines than pure disesel, bio diesels. A combination of hydrogen at different flow rates and diesel can be used. Hydrogen tanks with storage capacity is used in vehicle which is very dangerous, so here we include a hydrogen reactor in which chemicals are mixed
to produce hydrogen and can be sent to the engine along with diesel. In this work, an on-demand hydrogen generation setup was used to generate hydrogen for the purpose of burning it in the engine along with diesel under dual fuel mode. A solid-state hydrogen generation mechanism was employed in a purpose-built reactor using Sodium Borohydride (NaBH4) and Aluminium Sulphate (Al2(SO4)3) mixed in water. The experimentation was done on 4 S VCR diesel engine with single cylinder which was modified into duel fuel mode. The studies were carried with pure diesel and hydrogen at 15lit per min at 16, 17 and 18 compression ratioby holding speed to be 1500 rpm with varied loads from 0 to 12 kg with an interval of 3 kg. The cylinder pressure got increased, performance parameters like brake thermal efficiency got enhanced due to the usage of hydrogen than pure diesel. The emission parameter such as
nitrogen oxide increased when hydrogen was injecte
Microwave-assisted extraction of dragon fruit seed oil: Fatty acid profile and functional properties
Full text linkDragon fruit is gaining its popularity in all over the world. The seed of the dragon fruit is highly nutritious in terms of essential fatty acid. The utilization of seed oils is getting increasingly common these days. In this work, a comparative analysis was undertaken for control and microwave-assisted extraction (MAE) samples, using the RSM-CCD (Response Surface Methodology – Central composite Design) design, to determine the influences power and time on dragon fruit seed oil's Yield, PV, DPPH, and polyphenol content. The optimization was done, where the extraction yield (34.30 %), PV (3.23 me quiiv O2/kg), DPPH (69.65 %), and polyphenol (96.71 mg GAE/g) was observed. While comparing with the control sample the antioxidant activity of the seed oil in terms of (%DPPH, FRAP and ORAC) was better in microwave treated sample. The saturated fatty acid is 25 % with a monounsaturated fatty acid 20 % and Polyunsaturated fatty acid of 55 %. High amount of tocopherol content was determined having 93 % of γ -tocopherol. Dragon fruit seed oil has the possibility to be a good source for the functional components in the near future due to the presence of antioxidant compounds and essential fats