A Dual Wideband Planer Inverted-F Antenna using Reactive Impedance Surface and Defective Ground Surface for WLAN/X-band Applications

This paper presents a reactive impedance surface (RIS) and a defective ground surface (DGS) in a dual wideband planer inverted-F antenna (PIFA).DGS is a technique that allows  tooptimize the antenna's different parameters, like size reduction and bandwidth. The RIS structure, which consists of $3× 3$ periodic metallic unit cells, aids in increasing the antenna’s bandwidth. The RIS PIFA using DGS to design, analyze, and execute antenna a 2.4 and 8.4 GHz. Finally, the complete 3D electromagnetic simulator HFSS used to simulate a prototype. The implemented results -10 dB < S11 impedance bandwidth design has estimated at being 1199 MHz (2.0734-3.26921GHz) 49.95% WLAN bands at 2.4 GHz and 912 MHz (8.0239-8.9321 GHz) 10.03% for X-bands at 8.4GHz

Development of an Personalized Adaptive Learning Systemto improve students learning performances

Computer-assisted education promises open access to top-class instruction and a reduction in the cost of learning. Also, the modern education system has achieved great success in knowledge education, but its role in quality education is unclear.  In the traditional one-on-many instructional approach, learning models and continuing education programs are only based on a uniform approach. Due to the limitation of factors like a teaching process, human power, learner's abilities, and so on, instructors only provide all students with the same materials, and they tend to use an identical teaching approach and the same rate of progress. In this approach, it is difficult to consider the learning needs of individual students. This implies that students dependent on instructors teaching skills so they cannot make effective use of class time to learn. On the other hand, students with insufficient proficiency levels may not be able to understand the content of the course. Researchers are developing adaptive techniques that provide a better educational experience for students in some ways. Researchers offer accurate and perso-nalized content to students in an intelligent way, that may allow for adjustments in course content based on student's most recent performances. This technique allows the student to skip unnecessary learning activities by providing automated and personalized support for the student. These systems provide personalized course units that meet different student's educational needs

Data Migration From On Premise Oracle Database To SQL Manage Instance On Azure Cloud Using Azure Data Factory - A Working Approach

Data Migration has become important aspect nowadays when it comes to data movement from on premise databases to cloud storage or cloud databases. In this paper we present a working case study using cloud based ETL tool known as Azure Data Factory used for Data Migration from on premise Oracle database to cloud based SQL Managed Instance database for an organization. This paper evaluates the implementation of data migration process in general and specific to the tool and technologies involved in data migration process using Azure Data Factory for an organization. When an organization needs to move their application to cloud, the essential of data migration needs to be discussed, proper architecture is required to further break down each task to migrate the data. The proof of concept should be established to see if data is not getting truncated/altered in the process of migration and existing logic on the on premise database works well after moving data to the cloud. In this paper we also discuss about encryption process involved while migrating data as this is an important aspect in data migration to migrate data with existing algorithms used in on premise database and its implementation while data movement takes place using Azure Data Factory. In Oracle there are encryption algorithms being used to store sensitive user data, we have to analyze existing encryption/decryption process and implement an architecture with the help of data migration tool so that data remains intact after movement. Developer has to develop testing strategies to compare on premise data versus the data moved to the cloud storage. Azure Data Factory is powerful cloud-ETL tool to move your hundreds of table data at a time to new cloud database with maximum data transfer throughput. This data migration process requires thorough evaluation of multiple factors e.g. actual table size in migration, throughput, Virtual Machine used for data transfer, network bandwidth etc

Understanding the Order of 500 and 1000 Rupees Notes Ban using Reinforcement Learning

In the field of machine learning called reinforcement learning, complicated sequential decision-making problems have been addressed. The issue that arises when an agent learns behavior by trial-and-error runs to determine the ideal policy, or the sequence of behaviors so that rewards are maximized,is known as reinforcement learning. Because many reinforcement learning methods use dynamic programming approaches, the environment is characterized as a Markov Decision Process (MDP). The research presents reinforcement learning using Bigram, trigram, and 4-gram models for tweets collected for "500 and 1000 notes banned." A multistage graph problem is used to draw the graph and the Bayes method is used to compute the probabilities. For the given word sequence, it determines the shortest route between source and destination. After that, the path is defined by the agent's randomly selected states and actions, which are subsequently followed to receive rewards. Epsilon greedy selection mode randomly chooses an action to explore the environment

Advancements in Prostate Cancer Imaging: Implications for Diagnosis and Treatment

The diagnostic and therapeutic approaches for prostate cancer have been completely transformed by the developments in imaging technology. The development of imaging modalities, such as positron emission tomography (PET) and multiparametric magnetic resonance imaging (mpMRI), is examined in this overview, with an emphasis on the diagnostic value of each and the consequences for treatment choices. These methods help with risk assessment and biopsy guiding by providing improved sensitivity and specificity in the detection and characterization of prostate lesions. Focal treatment and image-guided radiation therapy are two examples of imaging-guided therapies that take advantage of accurate lesion location to maximise therapeutic methods and minimise adverse effects. Furthermore, even at lower prostate-specific antigen (PSA) levels, the incorporation of new molecular imaging tracers—in particular, PSMA ligands—has revolutionised staging accuracy and treatment response evaluation. Notwithstanding these developments, standardisation, affordability, and accessibility issues still exist, impeding wider use. It is important to tackle these obstacles in order to guarantee fair and consistent imaging procedures. Prospective avenues for advancement include the utilisation of cutting-edge technology such as artificial intelligence (AI) to enhance diagnostic precision and customise treatment plans. This thorough analysis highlights the revolutionary effects of cutting-edge imaging modalities on the treatment of prostate cancer and highlights the necessity of teamwork in order to overcome obstacles and improve patient care pathways

An Intensive Spectrum for Intention Mining Analysis

There is huge volume of data in the social networks. This data can be retrieved and integrated to extract useful meaning and come out with the insights which is called as intentions. This can be used in different fields like business, recommender systems, education, Scientific research, games, etc. Also, there are various intention mining techniques which can be applied to several fields as information retrieval, business, etc. There is no specific definition of intention mining and also there is very less existing literature present. Accordingly, there is need to conduct systematic literature review of the very recent research area. Understanding intention mining, purpose of intention mining, categories and techniques of intention mining is the need. The paper endorses a spectrum for intention mining so that further literature review of intention mining can be completed. We validate our work through dimensions, categories and techniques for intention mining

Brain Tumor Classification, Segmentation, and Detection using Deep Learning - A Review

V.Vapnik in 1965 proposed Vector methods. Kimeldorf presented a technique for creating kernel space based on support vectors in 1971. Support Vector Machine (SVM) techniques were initially presented in the 1990s by V. Vapnik in the field of statistical learning.  Since then, pattern recognition, natural language processing, image processing and other areas have seen extensive use of SVM. By converting non-linear sample space into linear space via a kernel approach, the algorithm's complexity is reduced. Image classification is a well-known issue in image processing.  Predicting the input image categories using the features is the main objective of image classification. There are several different classifiers, including Artificial Neural Networks, Support Vector Machines, and Random Forests, Decision Forests, k-NNs (k Nearest Neighbors), and Adaptive Boost. SVM is one of the best techniques for categorizing any image or pattern. A common non-invasive technique used in the medical sector for the analysis, diagnosis, treatment of brain tissues is magnetic resonance imaging.  When a brain tumor is discovered early, the patient's life can be saved by receiving the appropriate care.  It becomes difficult to accurately identify tumors in the MRI slices, which requires fussy work.

Surface ozone variability in the urban and nearby rural locations of tropical India

Surface ozone variability at Pune (an urban location) and nearby rural locations has been studied using KI solution chemical method. The measurement showed well-marked diurnal cycle of ozone concentration with minimum at sunrise and maximum at noon hours. Simultaneous measurements of humidity and temperature along with ozone suggest that the ozone concentration is directly proportional to temperature and inversely proportional to humidity. The averaged diurnal variation of ozone during different months and two seasons, viz. winter and spring show high ozone concentration over the rural locations than the urban location. Higher ozone concentration at the rural locations may be due to slower titration of ozone by nitric oxide in the evening hours

Monsoon circulation induced variability in total column ozone over India

The intra-seasonal variability of daily total column ozone (TCO) over 12 Indian stations has been studied. Total Ozone Mapping Spectrometer daily data from May to September for five years (1998-2002) have been utilized in the study. The power spectrum analysis of daily TCO data showed three dominant modes of period 3-8 days (synoptic), 10-20 days (quasi biweekly, qbw) and 30-60 days (Madden Julian Oscillation, MJO), similar to that found in the Indian Summer Monsoon Rainfall. Mean spatial distribution of the activities of these intra-seasonal modes in TCO variability over the Indian region has been studied. The spatial distribution of the synoptic mode shows the strongest activity over central India. The qbw mode shows strongest activity over northwest India. The MJO mode shows strongest activity over northern most and southern most parts of India

Content Discovery Advertisements: An Explorative Analysis

Content discovery advertisements are type of native ads which have gained traction for driving ad traffic. These advertisements are being hosted on supposedly reputed websites and their popularity has been growing however it has been reported in the media that these ads are deploying click bait ads. In this research, these ads were evaluated for a period of one month to study and examine their credibility. It was found that significant percentage of these ads were malicious in nature