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2022 Interdisciplinary Research in Technology and Management (IRTM)最新文献

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Approach for Preprocessing in Offline Optical Character Recognition (OCR) 离线光学字符识别(OCR)中的预处理方法
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791698
Raghunath Dey, R. Balabantaray, Surajit Mohanty, Debabrata Singh, Marimuthu Karuppiah, Debabrata Samanta
{"title":"Approach for Preprocessing in Offline Optical Character Recognition (OCR)","authors":"Raghunath Dey, R. Balabantaray, Surajit Mohanty, Debabrata Singh, Marimuthu Karuppiah, Debabrata Samanta","doi":"10.1109/irtm54583.2022.9791698","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791698","url":null,"abstract":"Offline optical character recognition (Offline OCR) is one of the important applications of pattern recognition. To achieve a better recognition result, the input character images must have good quality. That is why the preprocessing step be-comes essential for any image identification task. Lots of research has been performed in numerous jobs towards this preprocessing in the literature. Here, an attempt has been made to summarize different procedures and aspects of preprocessing adopted in implementing these preprocessing techniques. This is done in the hope that this may help the research community towards the gaining of knowledge of different preprocessing techniques used in offline OCR. Offline OCR has several applications, such as old manuscript digitization, signature authentication, bank cheque automatic clearance and postal letter sorting, etc. Finally, an overall summary in a concise way has been presented based on different preprocessing techniques used in offline OCR.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132092567","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: 2
Forecasting India's Bank Nifty Index - A Time Series Approach 预测印度银行漂亮指数-时间序列方法
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791767
Rajveer S. Rawlin, Priyanjali Das
{"title":"Forecasting India's Bank Nifty Index - A Time Series Approach","authors":"Rajveer S. Rawlin, Priyanjali Das","doi":"10.1109/irtm54583.2022.9791767","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791767","url":null,"abstract":"Forecasting stock market indices and individual stocks has been an emerging area in the investing landscape. Fundamental and technical analysis are widely used by investors in analysing and predicting future stock returns. Researchers have used various methods to forecast stock prices such as Hidden Markov models, genetic algorithms, and neural networks. Time series analysis is also popular in forecasting asset prices. Indian banks are among the best-performing stocks on the Indian stock exchanges over the last decade. The bank nifty index contains India's largest banks and has outperformed most other sector indices over the past decade. ARIMA is a univariate time series approach that can be used to forecast stock and stock index prices. This study aimed to evaluate the effectiveness of the ARIMA model in forecasting the bank nifty index. Forecasted values differed from actual prices, suggesting markets may be efficient. Additionally other variables not considered in the study may also prove to be influential in forecasting the bank nifty index.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133614362","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
Prediction of Parkinson's Disorder: A Machine Learning Approach 帕金森病的预测:一种机器学习方法
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791490
D. Patnaik, M. Henriques, Ashin Laurel
{"title":"Prediction of Parkinson's Disorder: A Machine Learning Approach","authors":"D. Patnaik, M. Henriques, Ashin Laurel","doi":"10.1109/irtm54583.2022.9791490","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791490","url":null,"abstract":"Parkinson's Disease (PD) is a neurodegenerative disorder that affects the dopamine neurons. The study aimed at predicting the risk of developing Parkinson's Disease in individuals with REM sleep Behavior Disorder (RBD) and Early untreated Parkinson's Disease. Data was obtained from Charles University in Prague which consisted of 30 individuals with early untreated Parkinson's Disease, 50 individuals with REM sleep behavior disorder (RBD) and 50 healthy controls. Logit model was used to analyze the data. Further a Machine learning model was used to predict the risk of developing Parkinson's Disease. It is concluded that Logit models and Machine learning successfully predict the risk of Parkinson's Disease development.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115648472","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
Forecasting GDP per capita of OECD countries using machine learning and deep learning models 使用机器学习和深度学习模型预测经合组织国家的人均GDP
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791714
Vedant Bhardwaj, Param Bhavsar, D. Patnaik
{"title":"Forecasting GDP per capita of OECD countries using machine learning and deep learning models","authors":"Vedant Bhardwaj, Param Bhavsar, D. Patnaik","doi":"10.1109/irtm54583.2022.9791714","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791714","url":null,"abstract":"The paper discusses the performance of different machine learning models and a deep learning model in forecasting annual Gross Domestic Product (GDP) per capita (PPP) data of 33 OECD countries using past year variables. It focuses on creating a universal forecasting model. For the analysis, the paper uses cross-country panel data consisting of 262 time-series variables with annual periodicity, including various growth, development, health, energy, finance, and social indicators and their lag terms for five years. The paper shows that the Artificial Deep Neural Network performed the best among the considered machine learning and deep learning models, followed by Gradient Boosted Regressor, whereas Ridge Regressor performed the worst. This paper gives insight into the application of machine learning and deep learning in forecasting GDP per capita. It shows how the further improvement of these computational methods and data availability would improve the forecast accuracy and precision.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117011927","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
Refurbished Medical Imaging Equipment through Technology 通过技术翻新的医学成像设备
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791731
Vanishree Pabalkar, R. Chanda, S. J
{"title":"Refurbished Medical Imaging Equipment through Technology","authors":"Vanishree Pabalkar, R. Chanda, S. J","doi":"10.1109/irtm54583.2022.9791731","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791731","url":null,"abstract":"Purpose - the purpose of this paper is to study the market assessment for Refurbished Imaging Equipment through understanding the Technological advancements in the Sector. Design/methodology/approach - Data has been collected from Primary sources and Secondary sources. The researcher applies Factor analysis, Principal Component an analysis and Component Score Coefficient Matrix for the analysis. Findings - Though there is ample potential for refurbished medical imaging equipment market, itis due to lack of confidence in refurbished equipment, healthcare providers prefer not to go for refurbished. Procurement policies of most public and large private hospitals are against use of refurbished medical equipment due to lack of standards and regulations for manufacturing, imports, and sale of new and pre-owned/used/refurbished medical equipment in India. Originality/value - The Statistical analysis from the study will help the Hospitals, Medical Practitioners, in understanding the merits of using a refurbished Imaging equipment that comes with Low cost of Ownership, Higher end equipment in lower budget, keeping cost of diagnosis low.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123668649","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
Linkages between news and dividend decisions using neural networks 利用神经网络分析新闻与股利决策之间的联系
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791672
D. Patnaik, D. Mehta, Sameer M Shaikh
{"title":"Linkages between news and dividend decisions using neural networks","authors":"D. Patnaik, D. Mehta, Sameer M Shaikh","doi":"10.1109/irtm54583.2022.9791672","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791672","url":null,"abstract":"Dividends are considered to be one of the most important management decisions from the point of views of investors, however in the area of corporate finance it still remains a controversial issue [1]. Despite the existent literature on dividends and stock market relationships, little focus is found on media events and its impact on Indian stock market outcomes. This article uses neural network theory to examine the quantitative relation between news, dividend payouts and its determinants. Further the research focuses on understanding whether different sectors and industries relate to stock market outcomes post event impact. Using a sample of 1362 companies listed on the National Stock Exchange of India Ltd between the periods of 2001–2015, we find that variables of net sales, profit after tax, cash balances, total reserves, previous year dividends, net block of assets and forex revenue earnings and expenses are significant in determining the payout decision across the nine sectors examined. The results from random forest regression score above the other neural models used in the study. Lastly, inflation, gold prices, US federal interest rates, ECB interest rates and dollar exchange rates carry significant influence on the determinants of dividend payout decision and eventually the payout.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121536768","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
Keywords Generator From Paragraph Text Using Text Mining in Bahasa Indonesia 基于文本挖掘的印尼语段落文本生成器
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791753
Berlian Rahmy Lidiawaty, Muhammad Estu Zulfaqor, Okcelen Diyantara, Dian Retiana Shinta Dewi
{"title":"Keywords Generator From Paragraph Text Using Text Mining in Bahasa Indonesia","authors":"Berlian Rahmy Lidiawaty, Muhammad Estu Zulfaqor, Okcelen Diyantara, Dian Retiana Shinta Dewi","doi":"10.1109/irtm54583.2022.9791753","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791753","url":null,"abstract":"When reading a document text such as news or article, people tend to read related information topic. However, when they try to use search engine for looking into it, they don't have any idea what the keywords are. Copying the whole text to the search engine's bar is not the best solution, since it will increase the searching process time but make the search engine nonoptimal. It also makes people get unrelated topic. Therefore, this research has a purpose to make an application that generates keyword from inputted text of paragraph. Despite of input the whole paragraph or text in the search bar, user can input the text in the developed application and get the best keyword based on the text. The main method that has been used in this research is a text mining. First, we perform a pre-processing which are turn the inputted text to be in lower case. The second, we remove the stop words and some characters from text. The third, we perform a tokenizing method to separate each word and store it in an array. The main step is calculating the score of each word that has been stored in array. The result of this research is three words that generated by the system from inputted paragraph text. The keywords that generated by system are the same with the method's calculation. However, this application system needs to improve more to get a better performance.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128718307","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
Multi-Band Frequency Selective Surfaces Using Square Loops with Splits 使用带分裂的方形环的多频带频率选择曲面
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791530
Atul Shaw, Sayanta Dutta, Injamamul Haque, Rahul Sil, Upasana Mondal, A. Chatterjee
{"title":"Multi-Band Frequency Selective Surfaces Using Square Loops with Splits","authors":"Atul Shaw, Sayanta Dutta, Injamamul Haque, Rahul Sil, Upasana Mondal, A. Chatterjee","doi":"10.1109/irtm54583.2022.9791530","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791530","url":null,"abstract":"Reflective Frequency Selective Surfaces (FSS) with square loop shaped patches loaded with splits are proposed for multiband applications. A FSS with dual band response is proposed followed by another design with triple band response. The FSS unit cell designs differ in number of loops with splits. The triple band FSS exhibits stop bands near 2.4 GHz, 4.8 GHz, 8.8 GHz with adequate -10 dB bandwidths of 0.31 GHz, 0.55 GHz and 1.14 GHz respectively. Such response makes the FSS suitable for ISM band, C band X band applications. Various orientations of the split loaded loops are also studied and the studies are presented in the paper.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131246510","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
An Experimental Investigation of Surface Roughness and Print Duration on FDM Printed Polylactic Acid (PLA) Parts FDM打印聚乳酸(PLA)零件表面粗糙度和打印时间的实验研究
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791603
Rupam Rakshit, A. Ghosal, P. K, Sanghamitra Podder, D. Misra, S. C. Panja
{"title":"An Experimental Investigation of Surface Roughness and Print Duration on FDM Printed Polylactic Acid (PLA) Parts","authors":"Rupam Rakshit, A. Ghosal, P. K, Sanghamitra Podder, D. Misra, S. C. Panja","doi":"10.1109/irtm54583.2022.9791603","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791603","url":null,"abstract":"Fused deposition modeling (FDM) is a polymer based material extrusion process which comes under additive manufacturing. PLA (polylactic acid) is a biodegradable polymer which has diverse use in medical applications. Nine number of PLA specimens have been designed and developed using Stratasys F170 FDM printer. Infill angle and orientation angle with three levels are considered as input process parameters. Surtronic $3+$ surface profilometer has been selected to conduct surface roughness measurement. The lowest value of roughness average (Ra) is registered as 5.29 µm at 0° infill angle and 9° orientation angle. Print duration has a pivotal role in making a product at a low cost and just-in-time production. Printing duration of each sample is recorded. Print duration is directly affected by orientation angle. At orientation angle, 5 minute print time has been achieved, which is found to be the lowest among all others. It is observed here also that the staircase effect may be responsible for bad surface finish of 3D printed parts.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"247 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123026916","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
An Empirical Analysis of Anxiety and Depression During COVID-19 新冠肺炎患者焦虑抑郁的实证分析
2022 Interdisciplinary Research in Technology and Management (IRTM) Pub Date : 2022-02-24 DOI: 10.1109/irtm54583.2022.9791544
D. Patnaik, Aaryaman Gupta, M. L. Henriques
{"title":"An Empirical Analysis of Anxiety and Depression During COVID-19","authors":"D. Patnaik, Aaryaman Gupta, M. L. Henriques","doi":"10.1109/irtm54583.2022.9791544","DOIUrl":"https://doi.org/10.1109/irtm54583.2022.9791544","url":null,"abstract":"The Covid-19 pandemic has caused a lot of stress and anxiety. This study aims to observe the impact of the demographic variables of age, gender, educational level and area of residence on the anxiety and depression levels due to the pandemic. Data was obtained using a questionnaire to record demographic variables such as Age, Gender, educational level and area of residence. Data was also obtained using a questionnaire that measured questions related to depression and anxiety. Results indicated that age recorded a significant impact of chances for depression. This means that individuals between the age group of <30years had a 3 times greater chance of developing depression due to the pandemic compared to the 30–59 years and >60-year-old age groups. On the other hand, males recorded an increased level of anxiety which was 2.5 times higher than females.","PeriodicalId":426354,"journal":{"name":"2022 Interdisciplinary Research in Technology and Management (IRTM)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115166047","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
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