2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)最新文献_第2页

Deep Learning-based model for the detection of Parkinson’s disease using voice data 基于深度学习的语音数据帕金森病检测模型

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844185

Waseem Ahmad Mir, Iqra Nissar, Izharuddin, D. Rizvi, S. Masood, Asif Hussain

{"title":"Deep Learning-based model for the detection of Parkinson’s disease using voice data","authors":"Waseem Ahmad Mir, Iqra Nissar, Izharuddin, D. Rizvi, S. Masood, Asif Hussain","doi":"10.1109/ICAITPR51569.2022.9844185","DOIUrl":"https://doi.org/10.1109/ICAITPR51569.2022.9844185","url":null,"abstract":"The advancements in deep learning and their applications in the field of health diagnosis have been very encouraging, therefore providing a better way for healthcare and also in the early detection of many diseases. Large databases of clinical data are accessible. The secondary use of these medical databases for prediction purposes involving deep learning has fueled the excitement of health experts. In this study, a custom deep neural network is employed for the Parkinson's disease (PD) prediction using voice data. Research studies have shown that voice is an early marker for PD detection. We have also employed the resampling technique to handle the class imbalance issue in the dataset along with a feature selection method known as the minimum redundancy maximum relevance to highlight the relevant features in the dataset. Numerous simulations were performed over the proposed deep neural network model to obtain better-generalized results. The performance of our proposed model was equated with state-of-the-art methods, applied in recent research, over the same dataset. The results obtained indicated that the proposed model has significantly outperformed all the existing models. Our proposed model achieved the best validation accuracy of 99.12%.The values of several performance metrics suggest that the proposed model is highly efficient to accomplish the task of PD detection.","PeriodicalId":262409,"journal":{"name":"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116161112","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}

引用次数: 1

Rainfall Prediction Using Machine Learning 使用机器学习进行降雨预测

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844203

Akash Gupta, Hitesh Kumar Mall, S. Janarthanan

引用次数: 15

LSTM Based Named Entity Chunking and Entity Extraction 基于LSTM的命名实体分块和实体提取

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844180

Bhogadi Godha Pallavi, E. R. Kumar, Ramesh Karnati, Ravula Arun Kumar

{"title":"LSTM Based Named Entity Chunking and Entity Extraction","authors":"Bhogadi Godha Pallavi, E. R. Kumar, Ramesh Karnati, Ravula Arun Kumar","doi":"10.1109/ICAITPR51569.2022.9844180","DOIUrl":"https://doi.org/10.1109/ICAITPR51569.2022.9844180","url":null,"abstract":"Some Natural Language Processing (NLP) jobs require the automatic extraction of key information from a text document, which is why automatic extraction is required. With the rise of social media, digital journalism, and blogging, automatic extraction is becoming increasingly important. The amount of information available is enormous, and information extraction will aid in the management of such vast amounts of data. A important subtask of automatic information extraction is named entity recognition (NER), also known as entity identification, entity chunking, and entity extraction. NER is also known as entity chunking and entity extraction. In an unstructured text document, it locates and categorises the identified entities with unique significance by categorising them into pre-defined categories like person, organisation, location, and so on. In a large number of occasions, this contain the most important information about the document. There are numerous applications for this information. It can be used to improve the ordering and filtering of key terms in documents, or it can simply be used as an input to NLP activities such as text summarization, question answering, and machine translation, among other things..","PeriodicalId":262409,"journal":{"name":"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129170964","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}

引用次数: 1

Virtual Machine allocation in multiple Data Centers using Throttled Load Balancing to improve the performance in Cloud 使用节流负载平衡在多个数据中心中分配虚拟机，以提高云中的性能

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844202

B. Ramana Reddy, M. Indiramma

{"title":"Virtual Machine allocation in multiple Data Centers using Throttled Load Balancing to improve the performance in Cloud","authors":"B. Ramana Reddy, M. Indiramma","doi":"10.1109/ICAITPR51569.2022.9844202","DOIUrl":"https://doi.org/10.1109/ICAITPR51569.2022.9844202","url":null,"abstract":"Today, Cloud Computing is a distributed system environment. These days the services are available pay as you go model. Cloud users are paying as per their services in the cloud environment. The services available to the Cloud users are Infrastructure as a service, platform as a service, software as a service and security as a service. Nowadays, most users are migrating to cloud platforms. In Covid - 19 pandemic situation, most large and small scale organizations operating their business using cloud platforms. On the other end due to industrial automation, the companies switched their operations to a cloud environments. Due to the rapid business migration, the demand for cloud computing increased. With the increase of demand in the cloud, the service providers are satisfied. On the other end, a challenging issue is resource allocation. The best resource allocation strategy will provide quick services to the cloud users and minimum cost to the cloud providers. In this paper, we will discuss, resource allocation procedure, the throttled load balancing algorithm and the results are compared with other resource optimization techniques.","PeriodicalId":262409,"journal":{"name":"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)","volume":"390 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123362121","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}

引用次数: 1

A Diagnostic survey on Sybil attack on cloud and assert possibilities in risk mitigation 对云上的Sybil攻击进行诊断性调查，并断言降低风险的可能性

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844217

Ravula Arun Kumar, Srikar Goud Konda, Ramesh Karnati, Ravi Kumar.E, NarenderRavula

{"title":"A Diagnostic survey on Sybil attack on cloud and assert possibilities in risk mitigation","authors":"Ravula Arun Kumar, Srikar Goud Konda, Ramesh Karnati, Ravi Kumar.E, NarenderRavula","doi":"10.1109/ICAITPR51569.2022.9844217","DOIUrl":"https://doi.org/10.1109/ICAITPR51569.2022.9844217","url":null,"abstract":"Any decentralized, biased distributed network is susceptible to the Sybil malicious attack, in which a malicious node masquerades as numerous different nodes, collectively referred to as Sybil nodes, causing the network to become unresponsive. Cloud computing environments are characterized by their loosely linked nature, which means that no node has comprehensive information of the entire system. In order to prevent Sybil attacks in cloud computing systems, it is necessary to detect them as soon as they occur. The network’s ability to function properly A Sybil attacker has the ability to construct. It is necessary to have multiple identities on a single physical device in order to execute a concerted attack on the network or switch between networks identities in order to make the detection process more difficult, and thereby lack of accountability is being promoted throughout the network. The purpose of this study is to Various varieties of Sybil assaults have been documented, including those that occur in Peer-to-peer reputation systems, self-organizing networks, and other similar technologies. The topic of social network systems is discussed. In addition, there are other approaches in which it has been urged over time that they be reduced or eliminated Their potential risks are also thoroughly investigated.","PeriodicalId":262409,"journal":{"name":"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116850340","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}

引用次数: 0

A Comparative Investigation on the use of Machine Learning Techniques for Currency Authentication 使用机器学习技术进行货币认证的比较研究

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844207

Arpit Sharma, B. Prathap, Javid Hussain

{"title":"A Comparative Investigation on the use of Machine Learning Techniques for Currency Authentication","authors":"Arpit Sharma, B. Prathap, Javid Hussain","doi":"10.1109/ICAITPR51569.2022.9844207","DOIUrl":"https://doi.org/10.1109/ICAITPR51569.2022.9844207","url":null,"abstract":"In the present banking sector, identifying the real and the fake note is a very challenging task because if we do it manually, it takes a long time to check which is real and which is fake. This research study article aims to authenticate the money between real and fake by using different machine algorithms facilitating learning, such as K-means Clustering, Random Forest Classification, Support Vector Machines, and logistics Regression. Specifically, we consider the banknote dataset. The data of money is extracted from various banknote images by using the wavelet transform tool, which is primarily used to remove elements from the images. However, we are mainly concerned with the different machine learning algorithms, so we take the two variables, where the first variable indicates image variance and the second indicates image skewness. We use these two variables to train our machine learning algorithms. So, majorly, by applying the different machine learning algorithms, which are supervised and unsupervised, we find the accuracy for the respective machine learning algorithms and then visualize and classify the real and fake notes separately. Finally, the prediction is based on integrity, which means the efficiency value is based on how much the mechanism system can uncover the fake notes. Then, after calculating the accuracy of currency authentication, there is a high possibility that the accuracy of the particular algorithm is the best algorithm, so the application of currency authentication will be very useful for the bank to easily find duplicate notes.","PeriodicalId":262409,"journal":{"name":"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116966205","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}

引用次数: 0

Detection of service time of automobiles and detection of faulty parts using IoT via CSVPCV 通过CSVPCV利用物联网进行汽车使用时间检测和故障部件检测

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844190

V. Kanakala, K. Mohan, V. Reddy

{"title":"Detection of service time of automobiles and detection of faulty parts using IoT via CSVPCV","authors":"V. Kanakala, K. Mohan, V. Reddy","doi":"10.1109/ICAITPR51569.2022.9844190","DOIUrl":"https://doi.org/10.1109/ICAITPR51569.2022.9844190","url":null,"abstract":"Nowadays, the auto-mobile maintenance became expensive. If the service scheduled won’t be followed by the users that would cause to bear more expenditure because of some parts may not function. Because of negligence of the users, the expenditure would cause bearing of penalty due to lack of knowledge of servicing deadline. Hence, IoT and appropriate sensors such as reading levels or information of the part are placed at important places in the auto-mobile for easy observation and such sensors are initially fed with pre-defined cut-offs. This feeding of details would be helpful in alerting the user as like alarm many times such as LED colour, buzzer and locks the driving through a display if the user won’t accept the severity. In addition to this, it is also needed to determine the faulty parts which are not performing their behaviour and are idle in functioning. The sensors for monitoring of significant parts would possess two checks such as alerting when crossing of predefined cut-offs as well as alerting when predefined behaviour of few parts is found idle or abnormal than regular behaviour. This scenario is named as customized sensors for verifying the predefined cut-off values which is called in short form as CSVPCV. The sensors incorporated in the automobile are built up with predefined logic that demonstrate its behaviour. The central sensor is placed which would receive the details of other sensors.","PeriodicalId":262409,"journal":{"name":"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115023710","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}

引用次数: 0

Study on Information Management System that connects students and instructor through chatting 以聊天方式连接学生与教师的信息管理系统的研究

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844222

Akash Sharma, Abhishek Gupta, S. Janarthanan

引用次数: 0

Feature Based Opinion Mining for Mobile Reviews 基于特征的移动评论意见挖掘

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844200

Rahul Gupta, Satyam Pathak, Mansi Sharma, G. Poornalatha

引用次数: 1

Inter country poetry classification using Topic modeling 使用主题模型的跨国诗歌分类

2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR) Pub Date : 2022-03-10 DOI: 10.1109/ICAITPR51569.2022.9844213

K. P. Kumar, T. Padmaja

{"title":"Inter country poetry classification using Topic modeling","authors":"K. P. Kumar, T. Padmaja","doi":"10.1109/ICAITPR51569.2022.9844213","DOIUrl":"https://doi.org/10.1109/ICAITPR51569.2022.9844213","url":null,"abstract":"Poetry is an art of arranging the carefully picked words in a specific order to express the authors experience and emotions. Poetry in India has its strong roots with world famous and excellent poets, amongst few renowned poets are “Universal Poet” Rabindranath Tagore, “Nightingale of India” Sarojini Naidu and “Swami” Vivekananda. Poetry style varies from country to country depending on the author. Author’s poetry topics, words and style depends on the circumstances they raised in, situations they faced, and their mind set. Many authors who belongs to India but settled in western countries and written their poems, in this context automatically identifying a poem’s author is a challenging task for the literary scholars who analyze the poetry. In this work authors proposed a method based on Latent Dirichlet Allocation(LDA) topic modeling to classify the poetry written by Indian or western(American)poet based on the distribution of topics per document. The experiment is performed on 3 data sets 128, 1600 and author wise poems respectively. This experiment is performed based on semantic features. Best result 91% precision and 88% accuracy is achieved on author wise poems data set using random forest algorithm","PeriodicalId":262409,"journal":{"name":"2022 First International Conference on Artificial Intelligence Trends and Pattern Recognition (ICAITPR)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125348204","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}

引用次数: 0