2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)最新文献

{"title":"A Comparative Study on Shortest Path Visualization using Artificial Intelligence","authors":"Gyanendra Mohan Patel, Ashutosh Kumar Singh, Tan Bhala, Aryaman Jora, Divyansh Chandna","doi":"10.1109/icrito51393.2021.9596550","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596550","url":null,"abstract":"In the modern computation system, that rely on various aspects to obtain the optimal results in easy manner appears more deterministic. There are several algorithms available that can distinguish a probable shortest path between two points, which helps students actively study algorithms with visualization. Therefore, in this study, we developed the GUI based shortest path finding tool consists of Dijkstra and A* algorithm. Further, in this study, the obtained shortest path results were graphically visualised and tabular output are stored in the database. The implementation of the algorithm and visualization was developed using Java AWT API and SWING package of Java. The Dijkstra and A* algorithm comparative analysis showed that the checks value and path length in terms of the A* algorithm is comparatively less than Dijkstra. Thus, it is affirmative that A * approach produces faster results and appeared as more efficient in terms of destination path finding than Dijkstra algorithm. Path finding is a fundamental feature of many significant applications and can be applied in static, interactive, and real-time situations. Such information shed light on the efficient application for computer gaming, robots, logistics, and crowd simulation.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122403947","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":"Investigating Efficacy of Deep Trained Soil Classification System with Augmented Data","authors":"Vikas Khullar, S. Ahuja, Rai Gaurang Tiwar, Ambuj Kumar Agarwa","doi":"10.1109/icrito51393.2021.9596515","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596515","url":null,"abstract":"Farmers need to be aware of the correct soil type for a specific crop to maximize agricultural yield, which affects the rising demand for food. In this paper, an appropriate and efficient soil classification system was aimed to propose by implementing deep learning approaches. Image-based soil data set was collected and pre-processed according to algorithmic requirements. Initially, classification was implemented using machine learning classification algorithms and then it compares with deep learning algorithms. Due to fewer images approximately 30 images in five categories, algorithmic training was resulted in low. To improve accuracy data augmentation was implemented. Further, the augmented dataset was utilized to train the machine learning and deep learning models. Based on the comparison, efficient algorithms were proposed.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122564793","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":"[Copyright notice]","authors":"","doi":"10.1109/icrito51393.2021.9596426","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596426","url":null,"abstract":"","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124024618","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":"An Analysis of Recurrent Neural Network variants to predict yield of Wheat crop in Punjab region","authors":"Nishu Bali, Anshu Singla","doi":"10.1109/icrito51393.2021.9596127","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596127","url":null,"abstract":"Yield prediction of a crop prior to harvest is an important aspect of agriculture. The alarming rate at which the population of the world is increasing is making it necessary to take measures to increase the yield of major food crops. The advancements in the area of data sciences especially in the field of machine learning and deep learning has come up as a major breakthrough in the area of crop yield prediction. The ability of deep learning to perform accurate predictions even in the areas with huge and diverse natured data has made it the most sort after technique for predictions in agriculture. There are many agriculture based regions in India where the efficiency of these advanced techniques is still not fully utilized in the field of crop yield prediction. The objective of the present study is to evaluate the efficiency of variants of Recurrent Neural Network, to predict the yield of Wheat crop for a region of Punjab state in India.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127838308","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 Modern Comparison of ML Algorithms for Cardiovascular Disease Prediction","authors":"Aviral Chanchal, A. S. Singh, K. Anandhan","doi":"10.1109/icrito51393.2021.9596228","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596228","url":null,"abstract":"In today's world, with rise in number of people following a sedentary lifestyle, heart disease has become the top reason of death. It is tough for healthcare personnel to forecast such an ailment in advance because it is a complex undertaking that demands competence and a greater knowledge for prediction. We aimed this study towards looking into the topic of predicting cardiovascular disease in advance with use of different ML models, and comparing the accuracies of different older as well newer techniques, on the Framingham heart study dataset from Kaggle. We have investigated the cardiovascular disease prediction using several techniques, namely, Decision Tree, KNN, Naϊve Bayes, SVM, XGBoost, and Random Forest. The prediction accuracy, ROC curve, and AUC value are all used to evaluate the performance of these machine learning techniques. Based on accuracy scores, KNN, SVM, and RFC perform equally well while scoring an accuracy of 85.33%. However, an analysis of the ROC curve and AUC value provides us with a different picture of how despite slightly lesser accuracy percentages, Naϊve Bayes, the modern method XGBoost, and Random Forest actually perform better than the techniques anticipated earlier based on accuracy alone.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127919767","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":"Use of Pupillometry for Emotion Recognition and Ophthalmology Studies: A Systematic Review","authors":"Rishu","doi":"10.1109/icrito51393.2021.9596098","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596098","url":null,"abstract":"In recent years, the study of emotion has increased due to the interaction of humans with the machine. It is helpful to interpret human actions and to improve the relationship between humans and machines for developing software that can understand the human states and can take action accordingly. The most accurate approach to recognize emotions, pupil diameter (PD) has been discussed in this study. The reason for selecting this approach is that it is directly controlled by the Autonomic Nervous System (ANS) and is easy to detect. The main aim of this paper is to recognize the difference in pupil diameter due to the positive and negative emotional states of a person. Numerous researches have proposed different methods for detecting emotions by using pupillary response and achieved reliable accuracy. The study showed that the pupil diameter is influenced by different video, image, and script content indicating the state of the user. This study provides empirical evidence demonstrating how changes in the state of the user can be unobtrusively identified.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129207161","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":"Demystifying Security and Applications of Internet of Things","authors":"Vandana Choudhary, Sarvesh Tanwar, A. Rana","doi":"10.1109/icrito51393.2021.9596471","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596471","url":null,"abstract":"Internet of Things (IoT) is a scientific advancement that is likely to transfigure our traditional way of life by automating everything connected to the internet. Smart physical devices/objects have become indispensable part of our lives thereby making our being simplified and way more organized. Internet of Things encompass and empower several heterogeneous physical devices/objects for sensing and gathering information from surroundings, consequently exchanging it in a seamless mode to realize smart application goals without human intervention, for instance, home automation, smart cities, smart agriculture, and smart industries etc. The growth in the number of such wired/wireless physical devices/objects and the speed of that growth raises concern over security. To be able to implement a smart world with such billions of physical devices/objects, appropriate mechanisms are required to provide secure end-to-end communications amongst them. In addition to it, a variety of attacks may occur in various layers of Internet of Things. Without a well-founded and congruous Internet of Things environment, budding Internet of Things applications cannot be exploited to their full potential. Hence, reliability, security and recovery from attacks are amongst the most unsparing sides of the Internet of Things. In this paper, we have presented a comprehensive review of Internet of Things security issues followed by security measures in Internet of Things. The focus in this paper is also on research challenges and application domains of Internet of Things.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129305463","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":"Affordable Housing and its Sustainability-A review of Critical Success Factors (CSFs)","authors":"Shagun Agarwal, S. Mandal, D. Bajaj, Archit Agarwal, T. Singh","doi":"10.1109/icrito51393.2021.9596156","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596156","url":null,"abstract":"Rapid urbanization has led to migration of people from rural to urban areas in large numbers. This shift is especially significant in developing countries like India. Our cities themselves are in a state of change, adapting to the advancement in technology and other global influences. These urban centers do not have the adequate infrastructure to accommodate the huge influx of people migrating to cities in search of better job opportunities and living conditions. This group of people is only looking for employment and decent accommodation with basic amenities. The real challenge for them is to manage daily expenses along with the transportation costs and also, pay for accommodation; be it owned or rental. In order to manage housing costs, government has floated several schemes over a period of time that provides incentives and most importantly, land at subsidized rates to developers. Often, in an attempt to make housing economically affordable to people, the government and developers compromise on the design, construction quality, location, technology, access to basic amenities and other features, which hold significant value to the consumer. As a result, all the efforts made by the government and the private developers do not bear the expected or desired results. The literature review highlights the gap in understanding the correct and complete criteria essential for successful housing implementation and occupation. Besides the cost of housing unit and managing other living expenses, there are other factors - easy access to school, medical facility, water, sewerage; accessibility to public transport; sense of community; imageability of housing, social inclusion, value appreciation and use of technology; amongst others that play a key role in decision making for the consumer in making housing choices. These factors can be categorized under Economic, Socio-cultural and Environmental sustainability, associated with housing.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128713510","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":"Application of Deep Learning Algorithms for Discerning the Presence of Pneumonia","authors":"Aditya Kaushik, Mihir Gada, Suchita Patil, Jyothi M. Rao","doi":"10.1109/icrito51393.2021.9596547","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596547","url":null,"abstract":"Pneumonia is a fatal disease that involves inflammation of the air sacs in the lungs, resulting in breathing difficulties. As a result, early discovery of the condition is critical, as it can be deadly in its later stages, leading to respiratory issues. Chest X-rays have long been used to reliably diagnose Pneumonia. Human-assisted diagnosis, on the other hand, has constraints such as the availability of an expert and involves significant expenditures for the necessary equipment. As a result, there has been a spike in demand for alternative methods for identifying pneumonia from chest x-rays using Deep Learning. To aid this, the usage of Convolutional Neural Networks (CNN) and other classification algorithms has increased and is now being used in important decision-making processes in the medical profession. This paper compares several convolutional neural network architectural models such as VGG-16, InceptionV3, DenseNet169, and CNN for identifying the presence of pneumonia using chest x-ray images, and finally, the models have been evaluated using performance metrics for better analysis.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117146175","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":"Image Enhancer","authors":"Atul, Pardeep, Manjit Kaur","doi":"10.1109/icrito51393.2021.9596268","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596268","url":null,"abstract":"Image processing is done using machine learning algorithms and tools like OpenCV (short for Open Computer Vision). This research paper shows an improved and convenient approach towards processing of images. Images that are highly distorted by any means or noise are too common in todays' era. This problem can rise by too many reasons be it transmitting from one source to another, by physical device damages, signals poor decoding from the source and even the noise from the sensor of the device they are taken. Prior to the invention of computers and applications such as Photoshop, these jobs were clearly performed only by experts with extensive knowledge in these areas. They mainly used to process physical copies of the images like enhancing the images by brushing techniques. For eliminating undesired noises and thus providing higher image quality, a new decision-based filtering strategy combining K-means and PCA is proposed. Now a days, there are various filters available in many free editing tools that surely do enhance the quality of the image the way you want them to be.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114322791","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}