2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)最新文献

{"title":"OptSpec: Optimization of Specifications Data for Engine Anatomy","authors":"P. Hegade, Kshitij Tiwari, Amit Godikar","doi":"10.1109/DELCON57910.2023.10127318","DOIUrl":"https://doi.org/10.1109/DELCON57910.2023.10127318","url":null,"abstract":"Search engines are progressing with design and technology to meet the business models' continually changing and evolving needs. From crawling the links for indexing them to presenting the results based on the user query, search engine components have been researched in depth and breadth. This research investigation is focused on managing and processing the name-value pair data. 21K e-commerce data items were processed into JSON format in key-value pairs to explore the combinatorial explosion and its impact of the smaller subsets, items segregated by the domains. An item might not have all of its specifications contributing to the results in the query management. We propose a method to generate subsets of categories that can potentially contribute to the processing and results. One of the ways to manage huge data is using threads and parallel processing. We use the approach and compare the results with single threaded model. The processed and raw data storage methods have also been compared for different item sets. The model also presents the approaches of selecting the right set of specifications depending on the user query. Several methods are compared based on the limiting set threshold. The results appear to be an effective way of managing associative data. The known methods and parameters are positively better than the neural and deep learning networks that keep the methodology hidden and in the black box from the users. When the thresholds and sets are known, the algorithms can make better decisions.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125863856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brain Tumor Detection And Segmentation Analysis With Machine Learning And Sub-Variant Techniques: A Perspective Study","authors":"Ravika Goel, N. K. Trivedi, S. Gaur","doi":"10.1109/DELCON57910.2023.10127518","DOIUrl":"https://doi.org/10.1109/DELCON57910.2023.10127518","url":null,"abstract":"Researchers in the fields of image separation, interpretation, and computer vision are always at work on automating tasks such as tumor segmentation, anomaly detection, classification, and the prediction of other structural disorders with the assistance of a computer. Brain tumors (BT) and other structural brain abnormalities are diagnosed, and their prognoses are determined with the help of several medical imaging modalities. This study aims to encapsulate the accomplishments and advancements in medical image segmentation and classification with reverence to unsupervised, supervised, and hybrid Machine learning and its derivative techniques for detecting abnormalities in the brain. The distinct objective of the research work is to implement descriptive analysis and identify the efficient ML technique. The study is comprehended with DWAE and SVM as efficient hybrid ML techniques foreseeing to enfold prominent features of accurately and precisely classifying brain tumor disorders.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125307178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Review on Opportunistic Routing Protocols for Underwater Sensor Networks with Open Issues","authors":"Ramanjeet Singh, Amit Jain","doi":"10.1109/DELCON57910.2023.10127422","DOIUrl":"https://doi.org/10.1109/DELCON57910.2023.10127422","url":null,"abstract":"Due to their usefulness in many fields, Underwater Wireless Sensor Networks (UWSN) have gained more focus in the present. It relies on data collected and sent through a network of sensor nodes distributed around the ocean at varying depths. There has been a lot of interest from researchers in Opportunistic Routing (OR) because of its potential to improve the efficiency of wireless networks. For sensor networks to effectively communicate, a dynamic routing strategy is required. UWSNs have their own set of challenges, like dynamic topology, energy consumption, and delay. For these reasons, efficient routing protocols are being developed specifically for use in UWSNs. It is difficult to build OR procedures for UWSNs because of the unique properties of underwater communication. In this paper, the parameters such as complexity, packet delivery ratio, etc. that are involved in the analysis of OR protocols are expressed through a comparative analysis. Also being highlighted are several issues that are still open with the OR methods.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121935091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Static Method to Locate Risky Features in Android Applications","authors":"Vaibhav Khullar, Tanya Gera, Tanya Mehta","doi":"10.1109/DELCON57910.2023.10127577","DOIUrl":"https://doi.org/10.1109/DELCON57910.2023.10127577","url":null,"abstract":"Over the past many years, there’s been an exponential development in the number of Android phone users across the world. Allowing for the exchange of real-time data and information that may revolutionize people’s lives. However, this provided an edge to hackers as well. They distribute thousands of malware apps to steal people’s data and make money. They employ reverse engineering to launch their harmful programs at the victim. Android application developers make every effort to avoid copying. But hackers always come up with various different attacks, techniques, and tools to avoid the identification of malware by anti-malware software. Android’s operating system is vulnerable to a variety of security exploits and weaknesses due to security flaws. In this article, we have devised a simple yet prominent strategy to extract the top risky features used by suspicious applications. Our research shows that the bulk of current research makes use of different designs, data sources, and approaches, including static, dynamic, and hybrid. Static analysis will be used in this article to identify the security vulnerabilities and risks in mobile applications. We have used a dataset of around 3000 applications and carried out a methodical investigation of it. Existing studies focus heavily on the safety of smartphone operating systems. We feel, however, that there is a need for detailed coverage of Android security issues, including the proliferation of malware, the investigation of anti-analysis tactics, and the analysis of current detection procedures. In this study, we cover topics such as Android’s security enforcement systems, threats to those mechanisms, associated difficulties, the evolution of malware from 2019 to 2022, and the cover tactics malware developers use to avoid detection. This study sheds light on the benefits and drawbacks of existing research methods and offers academics and practitioners a starting point for developing innovative approaches to Android malware detection, analysis, and protection.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"319 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116604347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of Metaphors in Problem Based Learning","authors":"P. Hegade, Aryan, A. Shettar","doi":"10.1109/DELCON57910.2023.10127310","DOIUrl":"https://doi.org/10.1109/DELCON57910.2023.10127310","url":null,"abstract":"The paradigm of education has undergone a significant transition from traditional teacher-directed instruction to student-centered problem-based learning. In various contexts, problem-based learning, computational thinking, and metaphor-based learning approaches have been used to deliver an efficacious learning of the concept. This paper puts forward a model and its usage to build metaphor based case studies directing towards cognitive thinking, self-directed learning and lifelong learning. The model directly influences on the problem solving thought process. The paper further presents a case study on application of this model and its effectiveness validated through the embedded design method. The method appears to be effective in from model analysis and feedback collected. This directly connects to the pattern recognition paradigm of the computational thinking process.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129922376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding the Influence of Student’s Emotions in Academic Success","authors":"Sahana Koppad, Jyoti Gadad, Preeti B Patil, V. M.","doi":"10.1109/DELCON57910.2023.10127402","DOIUrl":"https://doi.org/10.1109/DELCON57910.2023.10127402","url":null,"abstract":"Humanity has evolved, changing how one perceives and experiences emotions. Darwin states that emotions serve a purpose because they wouldn’t have developed if they were purely incidental. Typically, emotions are triggered by an interior or exterior experience that has either a positive or negative meaning for the person in question. Emotional intelligence (EI) is the ability to deal with a situation consciously. Emotional intelligence is not likely a significant predictor of work success. Emotions and moods are distinct; the former is more robust and less long-lasting. It has been observed that students have a lot to deal with emotionally (academic/non-academic). This observation necessitates researchers to understand how emotional intelligence affects students’ academic performance. The current study focuses on how engineering students’ academic performance is significantly influenced by emotional intelligence. The study used a quantitative research approach. The study is to investigate the impact of EI on the academic performance of 5th-semester undergraduate engineering students at KLE Technological University in India. For collecting the data, a purposive sampling strategy was used. The information was gathered through a questionnaire asking students about their emotional intelligence. A sample size of 159 was obtained and analysed.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129273540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intelligent Technique for Smart Locust Swarm Detection and Prevention Shield for Agricultural Fields","authors":"K. Mehta, V. Sood, Aayushi Aayushi, Pratham Chhabra","doi":"10.1109/DELCON57910.2023.10127416","DOIUrl":"https://doi.org/10.1109/DELCON57910.2023.10127416","url":null,"abstract":"In today's world, the agriculture industry has a lot of room for growth by incorporating the newest technical progressions and decision support systems to have enough surplus food output to feed the growing population. To perform and monitor numerous agricultural tasks in the fields, smart devices, remote sensors, the Internet of Things (IoT), and UAVs/Drones can be utilized to meet market demand for food and sustain the planet's survival. Since ancient times, locust and pests have destroyed fields and caused considerable problems with food security. Both historical and modern literature has reported serious outbreaks. Innovative technologies, such as the Internet of Things (IoT), offer a lot of promise to improve agricultural operations. Farmers will be able to make more informed decisions in less time, allowing them to manage their crops more effectively while lowering costs and boosting yields. The offered paper covers several topics linked to IoT-based technologies, as well as the many types of devices and sensors that can be used to detect locust and prevent crop destruction. The Smart Locust Swarm Detection and Prevention Shield is a machine-assisted repellent system in which Speech Recognition Sensors are utilized to detect the voice of a locust swarm using a Noise Compensated Model capable of detecting the ideal vocal qualities even in loud environments. This paper explains the components required to detect the presence of a locust swarm, including Voice Recording sensors, Motor Module Controller, GSM Module, Microphone, Solar Panel Directional Speakers, and Voice Recognized Input Signal transmitted by the Motor Module Controller. This paper looks at how the IoT is being utilized in agriculture to achieve smart and precise farming. Conventional survey methods fell far short of delivering the accurate forecasting and ongoing locust tracking that was needed. Traditional survey methodologies fall far short of meeting the need for precise forecasting and real-time monitoring of locust occurrence. In this context, this paper presents a collection of IoT options for locust status monitoring. This paper has examined how smart and accurate farming was made possible by the internet of things in agriculture. Traditional survey techniques fell far short of providing the precise forecasting and real-time monitoring of locust occurrence that was required.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128095263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Method for Enhancing Retinal Images using Vesselness","authors":"Rajwinder Kaur, R. Brar, G. Jagdev","doi":"10.1109/DELCON57910.2023.10127477","DOIUrl":"https://doi.org/10.1109/DELCON57910.2023.10127477","url":null,"abstract":"The motive of image enhancement is to focus on highlighting the hidden details of the image and removing the noise from the image. The research paper conducts the enhancement of the retinal images via CLAHE and four Morphological Operations (MOs). The Digital Retinal Images for Vessel Extraction (DRIVE) dataset of retinal images is used to conduct the research work. The extraction of the vessel profile spontaneously from the retinal images is a significant step in analyzing the retinal images. The proposed method conducted vesselness of retinal images at three different scales of 0.5, 1.0, and 1.5 for both colored and grayscale images. The proposed method makes use of Gaussian kernels to calculate Eigenvectors and eigenvalues, Histogram Equalization and Median filter to enhance the images, Gaussian filter to remove noise, and power law to sharpen the output image. The proposed method is more robust as compared to CLAHE and MOs. The enhancement achieved by the proposed methodology outperformed the enhancement achieved by CLAHE and morphological operations. The average PSNR of the proposed method is 57.39dB as compared to 36.11dB and 50.68dB for CLAHE and MOs respectively. The average value of MSE and RMSE for the proposed method is 0.3454 and 0.5872 as compared to 3.9919 and 1.997 for CLAHE and 0.7454 and 0.8633 for MOs respectively. The suggested approach can serve as an effective preprocessing tool for segmenting and classifying the DR-related feature methods. The authenticity of the work done is justified by calculating the values of PSNR (Peak Signal Noise Ratio), MSE (Mean Square Error), and RMSE (Root Mean Square Error) in each case which are used as performance evaluation metrics.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122271199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chitkara University Organized IEEE Delhi Section Conference – DELCON 2023","authors":"Sagar Juneja, Rishu Chhabra, Rajnish Sharma","doi":"10.1109/delcon57910.2023.10127463","DOIUrl":"https://doi.org/10.1109/delcon57910.2023.10127463","url":null,"abstract":"","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115951368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of Electron and Hole Transport Layers in MASnI3 Perovskite Solar Cell","authors":"Abhilash Prasad Sharma, S. Chanana","doi":"10.1109/DELCON57910.2023.10127260","DOIUrl":"https://doi.org/10.1109/DELCON57910.2023.10127260","url":null,"abstract":"Considering the characteristics and applications of Perovskite solar cell, it has garnered much attention in the field of research in thin-film photovoltaics owing to its comparable low-cost fabrication methods and hence showing its dominance in photovoltaic applications in daily life. The mixed halide perovskite has shown a promising power conversion efficiency of more than 25%, but the toxicity of lead is the main concern. Hence, it is important to dig out some nontoxic, environment friendly perovskite materials, which can be used as solar cell absorber materials, such as methyl ammonium tin iodide (MASnI3). Numerical analysis is used since it plays a critical role in the designing of realistic problems with ease and hence experimenting with different hypothesis can be easily carried out. In this paper, we have used 1-dimensional solar cell capacitor simulator (SCAPS-1D) software to demonstrate the simulation of MASnI3- based solar cell with various HTL (hole transport layer) and ETL (electron transport layer) combinations. Results show that the TiO2 and P3HT combination produced the highest Jsc (current density) of 32.52 mA/cm2 with the best power conversion efficiency of 25.75%. This study can offer a better accurate picture of understanding in choosing ETL and HTL materials for the better performance of the perovskite solar cell.","PeriodicalId":193577,"journal":{"name":"2023 2nd Edition of IEEE Delhi Section Flagship Conference (DELCON)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134264252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}