Papers by Dr. Alok Singh Chauhan
Maternal Health Risk Classification - A Comparison between Algorithm Decision Tree and k-Nearest Neighbor (kNN)
An Overview of Implementation Strategies on Cyber Security
2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET)
Face Detection System Using Machine Learning Algorithm
2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET)
Research Square (Research Square), Nov 2, 2022
The spinal curve that represents an abnormally rounded back is known as kyphosis, and it can be c... more The spinal curve that represents an abnormally rounded back is known as kyphosis, and it can be caused by stress, infectious disease, developmental abnormalities, genetic disease, and occasionally iatrogenic disease. Due to the fact that it provides technical explanations and a signi cant standard, the emergence of machine learning and deep learning has demonstrated that they can better characterize data. Machine Learning and Deep Learning are promising approaches that help in the prediction, diagnosing of sickness. Compared to conventional computing algorithms, deep learning algorithms are far more effective in disease detection and diagnosing. In this study, Random Forest (RF), K-Nearest Neighbors (KNN), Support Vector Machine (SVM) and Deep Neural Network (DNN) models are applied to detect the presence of kyphosis in youngsters supported medicine information and compared to point out the rise in the potency of predictions associated with kyphosis. Each classi cation algorithm that makes use of the hyperparameter tuning and control feature enhances the algorithms' overall prediction performance, which enhances the algorithms' overall performance. The potency of the planned models were enforced and checked over medical dataset utilized from Kaggle. Overall, the DNN model performed best among the wide range of different models and achieved maximum accuracy and other performance metrics scores derived from the strati ed K-Fold cross-validation. It is advised that after a patient has completed a clinical procedure, the DNN model be trained to identify and forecast kyphosis disease.
Materials
The crystals of Mn4+-activated fluorides, such as those of the hexafluorometallate family, are wi... more The crystals of Mn4+-activated fluorides, such as those of the hexafluorometallate family, are widely known for their luminescence properties. The most commonly reported red phosphors are A2XF6: Mn4+ and BXF6: Mn4+ fluorides, where A represents alkali metal ions such as Li, Na, K, Rb, Cs; X=Ti, Si, Ge, Zr, Sn, B = Ba and Zn; and X = Si, Ge, Zr, Sn, and Ti. Their performance is heavily influenced by the local structure around dopant ions. Many well-known research organizations have focused their attention on this area in recent years. However, there has been no report on the effect of local structural symmetrization on the luminescence properties of red phosphors. The purpose of this research was to investigate the effect of local structural symmetrization on the polytypes of K2XF6 crystals, namely Oh-K2MnF6, C3v-K2MnF6, Oh-K2SiF6, C3v-K2SiF6, D3d-K2GeF6, and C3v-K2GeF6. These crystal formations yielded seven-atom model clusters. Discrete Variational Xα (DV-Xα) and Discrete Variation...
International Journal of Advanced Research in Science, Communication and Technology, Apr 21, 2023
The newsly web is a platform where we are filtering, aggregating news and providing the informati... more The newsly web is a platform where we are filtering, aggregating news and providing the information or news for user friendly experience at one place. Newsly aggregator is a very simple and userfriendly application. In a news aggregator, user can select the websites user want to follow. Visiting many separate websites frequently to find out if the content on the site has been updated can take a long time. Newsly Aggregation technology helps to consolidate many websites into one page that can show only the new or updated information from many sites. Newsly Aggregators reduce the time and effort. News and providing the content for user friendly experience at one place In Newsly we have used HTML, CSS, JavaScript and bootstrap for the front End. We use crispy forms python, Django for the back-end support. This paper will explore the advancements in AI and NLP that are expected to shape the future, as well as the potential implications of human interaction.
African Journal of Biological Sciences, Jun 17, 2024
India, often referred to as an agricultural country, has 52% of its population engaged in agricul... more India, often referred to as an agricultural country, has 52% of its population engaged in agriculture. The agricultural sector's prosperity is heavily dependent on regional climatic conditions. Adverse weather events significantly impact farmers' economic stability, exacerbating existing pressures and contributing to high rates of farmer suicides. This paper proposes a novel solution: the integration of regression-fuzzy models for predicting the economic conditions of farmers. By utilizing historical weather data spanning the past decade, this model aims to forecast economic fluctuations and mortality rates among farmers. The primary objective is to reduce the mortality rate by providing accurate predictions based on weather impacts on crop production, specifically focusing on Kharif and Rabi seasons. Through the application of fuzzy clustering and rule generation, the model classifies farmers' economic conditions and assesses the influence of weather on their production. This approach offers actionable insights to enhance economic resilience and mitigate distress in the agricultural sector.
Deleted Journal, Jun 25, 2023
The domain of machine learning has experienced an unparalleled increase in attention and implemen... more The domain of machine learning has experienced an unparalleled increase in attention and implementation, becoming an essential component of diverse businesses. This review paper provides a thorough analysis of the comprehensive handbook named "Machine Learning Basics: A Comprehensive Guide." Written by [Dr. Jane Doe], this guide has become a vital reference for those at all levels of expertise seeking to comprehend and traverse the intricate realm of machine learning.
Journal of integrated science and technology, Feb 8, 2024
Deep learning techniques have recently demonstrated promising outcomes in the segmentation of bra... more Deep learning techniques have recently demonstrated promising outcomes in the segmentation of brain tumors from MRI images. Due to its capability to handle high-resolution images and segment the entire tumor region, the U-Net model is one of them and is frequently utilized. For the analysis and planning of brain tumors treatments, accurate segmentation of brain tumors using multi-contrast MRI images is essential. Deep learning models including U-Net, PSPNet, DeepLabV3+, and ResNet50 have demonstrated encouraging outcomes in the segmentation of brain tumors. Using the BraTS 2018 dataset, we compare these models in this research. We evaluate the models using a variety of measures, including the Hausdorff Distance (HD), the Absolute Volume Difference (AVD), and the Dice Similarity Coefficient (DSC), and we look into how data augmentation and transfer learning approaches affect the models' performance. The findings demonstrate that the 3D U-Net model performed the best, with a DSC of 0.90, HD of 10.69mm, and AVD of 11.15%. The PSPNet model achieved comparable performance, with a DSC of 0.89, HD of 11.37mm, and AVD of 12.24%. The DeepLabV3+ and ResNet50 models achieved lower performance, with DSCs of 0.85 and 0.83, respectively. Based on the discoveries and analysis, the 3D U-Net model with data augmentation and transfer learning is suggested for brain tumors segmentation utilizing multi-contrast MRI images.
Mobile ad hoc networks (MANETs) are wireless networks that can be configured at will. It has no i... more Mobile ad hoc networks (MANETs) are wireless networks that can be configured at will. It has no infrastructure and centralized control, so it is only suitable for provisional communications. In a dynamically topological and resource-constrained network, ensuring QoS and security is challenging. MANETs are dynamic networks, so navigating them can be challenging and more susceptible to attacks. MANET requires significant memory, speed, and transmission bandwidth for conventional security measures like cryptographic techniques. Consequently, these methods are unsuitable for identifying malicious behaviour or self-centered nodes. Nodes that are malicious, selfish, or malfunctioning can be identified based on the trust method, which calculates how much trust exists between them. A trust-based QOS-aware routing protocol is proposed in this paper to calculate trust in MANET (I-TQAR). The tree important performance metrics are considered for result validation such as delay, throughput and packet delivery ratio (PDR). I-TQAR offers significantly improved performance in all areas compared to the existing TQR and TQOR protocols.
International Journal of Computer Applications, 2015
Stock determines the share of the ownership of a company. It represents the assets and earnings a... more Stock determines the share of the ownership of a company. It represents the assets and earnings and overall contribution of the company in any country's economy. The stock of a company is partitioned into shares.
KnE Social Sciences, Dec 21, 2022
The Indonesian Ministry of Education, Culture, Research, and Technology (Kemendikbudristek) recen... more The Indonesian Ministry of Education, Culture, Research, and Technology (Kemendikbudristek) recently released several educational platforms like Merdeka Belajar, Rapor Pendidikan, Belajar.id, ARKAS, TanyaBOS, SiPLah and Kampus Merdeka to make a leap in educational progress. However, the user percentage is still low, which may be due to various reasons such as limited internet access and reluctance to learn new technology. Discussion on which priority technology platforms are and how they are used to support Kurikulum Merdeka's implementation has been limited. Therefore, this paper will analyze the primary educational platforms useful for the implementation of Kurikulum Merdeka. We carried out a systematic review of the relevant databases on the digitalization of education in implementing Kurikulum Merdeka. Although the current educational platforms are still being developed, they provide unique features which facilitate students, teachers, administrators, and principals in the learningmanagement process at all levels of education. This work has the potential to become an essential reference that provides guidelines for using the educational platform to improve the number of users.
2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET)
In this paper, we proposed a facial recognition system using machine learning, specifically suppo... more In this paper, we proposed a facial recognition system using machine learning, specifically support vector machines (SVM). The first step required is face detection which we accomplish using a widely used method called the Viola-Jones algorithm. The Viola-Jones algorithm is highly desirable due to its high detection rate and fast processing time. Once the face is detected, feature extraction on the face is performed using histogram of oriented gradients (HOG) which essentially stores the edges of the face as well as the directionality of those edges. HOG is an effective form of feature extraction due its high performance in normalizing local contrast. Lastly, training and classification of the facial databases is done using the a multi-class SVM where each unique face in the facial database is a class. We attempt to use this facial recognition system on two sets of databases, the AT&T face database and the YALE B face database and will analyze the results.
Higher education is a crucial zone for any successful nation. All exploration and developments fo... more Higher education is a crucial zone for any successful nation. All exploration and developments for the most part originates from advanced education. Top most profitable experts like designers, supervisors, researchers are originates from the channel of higher education. The supervision of the scholarly execution of designing/understudies is fundamental amid a beginning time of their educational module. In reality, their evaluations in particular center/real courses and additionally their combined General Point Average (GPA) are conclusive when relating to their capacity/condition to seek after higher examinations. Information mining joins machine learning, measurements and perception methods to find and concentrate learning. This paper proposes to apply data mining strategies to anticipate understudies' scholastic execution in higher instructive establishments. In this paper we additionally utilized information mining and factual strategies to enhance students' execution and...
Applied Sciences
Although Kyphosis, an excessive forward rounding of the upper back, can occur at any age, adolesc... more Although Kyphosis, an excessive forward rounding of the upper back, can occur at any age, adolescence is the most common time for Kyphosis. Surgery is frequently performed on Kyphosis patients; however, the condition may persist after the operation. The tricky part is figuring out, based on the patient’s traits, if the Kyphosis condition will continue after the treatment. There have been numerous models employed in the past to predict the Kyphosis disease, including Logistic Regression (LR), Naive Bayes (NB), Random Forest (RF), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Deep Neural Network (DNN), and others. Unfortunately, the precision was overestimated. Based on the dataset received from Kaggle, we investigated how to predict Kyphosis disorders more accurately by using these models with Hyperparameter tuning. While the calculations were being performed, certain variables were modified. The accuracy was increased by optimizing the fit parameters based on Hyperparamet...
Polyhedron International Journal in Mathematics Education
Each student has their own characteristics and way of doing 3D geometric thinking. The way of thi... more Each student has their own characteristics and way of doing 3D geometric thinking. The way of thinking that students do influences the resulting understanding of the concept of 3D geometry. Therefore, this study aims to investigate students' geometric thinking based on the level of achievement of students in completing the 3D geometric thinking ability test (3D GTA). This study uses an exploratory case study design. The participants who voluntarily participated were 33 junior high school students (14 boys, 19 girls) in one of the schools in Indramayu Regency, Indonesia. Data obtained from the process of observation, tests, interviews, and documentation were analyzed qualitatively using Atlas. ti 8 software. The findings revealed that students with low 3D GTA achievements experienced difficulties in representing and calculating the surface area and volume of 3D shapes. In addition, students with moderate 3D GTA achievements experienced difficulties in representing 3D shapes but w...
Mesopotamian Journal of Cyber Security
SQL injection is a type of security vulnerability that occurs in database-driven web applications... more SQL injection is a type of security vulnerability that occurs in database-driven web applications where an attacker injects malicious code into the application to gain unauthorized access to sensitive information. This paper aims to provide a comprehensive and systematic review of the existing methods for preventing and detecting SQL injection attacks. The review covers a range of techniques, including input validation, parameterized queries, and intrusion detection systems, as well as the advantages and disadvantages of each method. The most common prevention techniques include input validation, parameterized queries, and stored procedures, while the most common detection techniques include intrusion detection systems (IDS), honeypots, and signature-based detection. The choice of method will depend on the specific requirements of the organization and the level of security required. Still, a combination of prevention and detection methods is likely to be the most effective way to se...
The spinal curve that represents an abnormally rounded back is known as kyphosis, and it can be c... more The spinal curve that represents an abnormally rounded back is known as kyphosis, and it can be caused by stress, infectious disease, developmental abnormalities, genetic disease, and occasionally iatrogenic disease. Due to the fact that it provides technical explanations and a significant standard, the emergence of machine learning and deep learning has demonstrated that they can better characterize data. Machine Learning and Deep Learning are promising approaches that help in the prediction, diagnosing of sickness. Compared to conventional computing algorithms, deep learning algorithms are far more effective in disease detection and diagnosing. In this study, Random Forest (RF), K-Nearest Neighbors (KNN), Support Vector Machine (SVM) and Deep Neural Network (DNN) models are applied to detect the presence of kyphosis in youngsters supported medicine information and compared to point out the rise in the potency of predictions associated with kyphosis. Each classification algorithm t...
Healthcare decision making using k-means clustering technique
Pranjana:The Journal of Management Awareness
Modeling and Predicting Student Academic Performance in Higher Education Using Data Mining Techniques
International Journal of Software Innovation, 2022
The primary goal of upper education foundations is to offer quality instruction to its understudi... more The primary goal of upper education foundations is to offer quality instruction to its understudies. One approach to accomplish most elevated level of import during advanced education framework is by finding learning for forecast with reference to enrollment of understudies in a specific course, estrangement of typical study hall showing model, discovery of out of line means that used in on-line assessment, identification of surprising qualities within the outcome sheets of the understudies, expectation concerning understudies' exhibition, etc. the educational is tucked away among the instructive infoal index and it's removable through information mining ways. This paper is intended to let the limits of data mining methodologies in setting of cutting edge training by giving a data mining model to higher education framework inside institute. During this exploration, the classification and prediction tasks are employed to assess understudy’s presentation and as there are vario...
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Papers by Dr. Alok Singh Chauhan